[1] Perkins CE, Royer EM. Ad-hoc on-demand distance vector routing. In: Mobile Computing Systems and Applications. 1999 Proceedings of the Second IEEE Workshop on WMCSA'99. for mobile ad hoc networks. In: Proceedings of the 2002 International Symposium on Low Power Electronics and Design, 2002. ISLPED'02. IEEE.

[9] Johnson DB, Maltz DA, Broch J, et al. DSR: The dynamic source routing protocol for multi-hop wireless ad hoc networks. Ad-Hoc Networks. 2001;**5**:

[10] Haas ZJ, Pearlman MR. Protocol, the performance of query control schemes for the zone routing. IEEE/ ACM Transactions of Networking (TON). 2001;**9**(4):427-438

[11] Hussain S, Ahmad N. Cluster based controlling of route exploring packets in

Innovation, Systems and Technologies. Springer International Publishing; 2014.

[12] Haas ZJ, Pearlman MR, Samar P. The Zone Routing Protocol (ZRP) for Ad Hoc Networks, Internet Draft. Mobile Ad-Hoc Network (MANET) Working Group, IETF; 2002

[13] Kataria J, Dhekne PS, Sanyal S. Acrr: Ad hoc on-demand distance vector routing with controlled route requests. 2010. arXiv preprint arXiv:1005.0139

[14] Ahmad N, Hussain SZ. Broadcast expenses controlling techniques in mobile ad-hoc networks: A survey. Journal of King Saud University-Computer and Information Sciences.

[15] Al-Rodhaan MA, Mackenzie L, Ould-Khaoua M. Improvement to Blocking Expanding Ring Search for Manets. Glasgow, UK: Department of Computing Science, University of

ad-hoc networks. In: Advanced Computing, Networking and Informatics, vol. 28 of Smart

2002. pp. 72-75

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Glasgow; 2008

[2] Tonguz OK, Wisitpongphan N, Parikh JS, Bai F, Mudalige P,

Sadekar VK. On the broadcast storm problem in ad hoc wireless networks. In:

Broadband Communications, Networks and Systems, BROADNETS 2006, IEEE.

[3] Barjini H, Othman M, Ibrahim H, Udzir NI. Shortcoming, problems and analytical comparison for flooding-

unstructured p2p networks. Peer-to-Peer Networking and Applications.

[4] Lima R, Baquero C, Miranda H. Broadcast cancellation in search

mechanisms. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing, SAC '13. ACM; 2013.

[5] Aitha N, Srinadas R. A strategy to reduce the control packet load of AODV using weighted rough set model for MANET. International Arab Journal of Information Technology. 2009.

[6] Ahmad N, Hussain SZ. Analytical comparisons of query-broadcast repealing schemes in manets.

Telecommunication Systems. 2018:1-13

[7] Clausen T, Jacquet P, Adjih C, Laouiti A, Minet P, Muhlethaler P, et al. Optimized link state routing protocol (OLSR). RFC 3626 (Experimental);

[8] Maleki M, Dantu K, Pedram M. Power-aware source routing protocol

based search techniques in

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[17] Dubois-Ferriere H, Grossglauser M, Vetterli M. Age matters: Efficient route discovery in mobile ad hoc networks using encounter ages. In: Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking & Computing. ACM; 2003. pp. 257-266

[18] Preetha K, Unnikrishnan A, Jacob KP. A probabilistic approach to reduce the route establishment overhead in AODV algorithm for Manet. arXiv preprint arXiv:1204.1820; 2012

[19] Gargano L, Hammar M. Limiting flooding expenses in on-demand sourceinitiated protocols for mobile wireless networks. In: 18th International Parallel and Distributed Processing Symposium, 2004, Proceedings. IEEE. 2004. p. 220

[20] Zhang H, Jiang Z-P. On reducing broadcast expenses in ad-hoc route discovery. In: Distributed computing systems workshops. In: 2005. 25th IEEE International Conference on IEEE. 2005. pp. 946-952

[21] Chang N, Liu M. Revisiting the ttlbased controlled flooding search: Optimality and randomization. In: Proceedings of the 10th Annual International Conference on Mobile Computing and Networking. ACM; 2004. pp. 85-99

[22] Park I, Kim J, Pu I, et al. Blocking expanding ring search algorithm for efficient energy consumption in mobile ad hoc networks. In: WONS 2006: Third Annual Conference on Wireless Ondemand Network Systems and Services. 2006. pp. 191-195

[23] Pu IM, Stamate D, Shen Y. Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks. Journal of Discrete Algorithms. 2014;**24**:59-67

[24] Pu IM, Shen Y. Enhanced blocking expanding ring search in mobile ad hoc networks. In: 2009 3rd International Conference on New Technologies, Mobility and Security (NTMS), IEEE. 2009. pp. 1-5

**37**

**Chapter 3**

**Abstract**

ered in this work.

importance of 5G

**1. Introduction**

and their corresponding spectral bandwidth.

anticipated deployment for this community is 2020.

Wireless Systems

Importance of Fifth Generation

*K. Sakthidasan Sankaran, G. Ramprabu and V.R. Prakash*

Fifth generation wireless communications are denoted by 5G technology. 5G schemes are coming from first generation analog communication, 2G of Global System for Mobile communication (GSM), then 3G of Code Division Multiple Access (CDMA), after that fourth generation of long-term evaluation (LTE), and now fifth generation World Wide Wireless Web (WWWW). This research investigation presents issues, challenges, and the importance of 5G Wifi communication. In the 5G digital cellular network, the coverage area of the service providers is separated into small area called cells. All the audio, video, and image files are digitized and converted by an ADC (Analog to Digital Converter) and transmitted through stream of bits. 5G wireless devices are communicated using radio waves in a geographically reusable common pool of frequency band. Using wireless backhaul connection, the local antennas are connected with the internet/telephone network. Spectrum speed is substantially higher in millimeter wave. Hence, this was consid-

**Keywords:** 5G, wifi communication systems, WWWW, challenges, issues and

First, the goal of 5G network is to offer an extremely high speed data rate to enormous customers. Subsequently, to deploy a huge sensors in order to support abundant simultaneous connections, there must be a significant improvement inside the spectral performance of 5G [1] network when compared to 4G network. The telecommunication region has been introducing every 10 years a brand new generation of mobile networks in view that the creation of 1G. Introduction to any new cellular network requires new frequency assignment and a wide spectral BW (bandwidth). **Table 1** shows the progress of different telecommunication structures

Other parameters like bit rate (higher peak), managing of concurrently connected devices, spectral performance, lesser battery intake, outage opportunity, higher bit rate, lower latencies, no. of supported gadgets, lower deployment cost and an additional dependable communication are predicted to be better in 5G. The

Network will not suitable to support such increasingly more community usages

is the major issue. In an effort to boom want to set up a flatter and greater dispensed community. The abundant file formats which includes all supported image, video, audio and information via NW (network) suggests that new source coding

### **Chapter 3**

### Importance of Fifth Generation Wireless Systems

*K. Sakthidasan Sankaran, G. Ramprabu and V.R. Prakash*

### **Abstract**

Fifth generation wireless communications are denoted by 5G technology. 5G schemes are coming from first generation analog communication, 2G of Global System for Mobile communication (GSM), then 3G of Code Division Multiple Access (CDMA), after that fourth generation of long-term evaluation (LTE), and now fifth generation World Wide Wireless Web (WWWW). This research investigation presents issues, challenges, and the importance of 5G Wifi communication. In the 5G digital cellular network, the coverage area of the service providers is separated into small area called cells. All the audio, video, and image files are digitized and converted by an ADC (Analog to Digital Converter) and transmitted through stream of bits. 5G wireless devices are communicated using radio waves in a geographically reusable common pool of frequency band. Using wireless backhaul connection, the local antennas are connected with the internet/telephone network. Spectrum speed is substantially higher in millimeter wave. Hence, this was considered in this work.

**Keywords:** 5G, wifi communication systems, WWWW, challenges, issues and importance of 5G

### **1. Introduction**

First, the goal of 5G network is to offer an extremely high speed data rate to enormous customers. Subsequently, to deploy a huge sensors in order to support abundant simultaneous connections, there must be a significant improvement inside the spectral performance of 5G [1] network when compared to 4G network. The telecommunication region has been introducing every 10 years a brand new generation of mobile networks in view that the creation of 1G. Introduction to any new cellular network requires new frequency assignment and a wide spectral BW (bandwidth). **Table 1** shows the progress of different telecommunication structures and their corresponding spectral bandwidth.

Other parameters like bit rate (higher peak), managing of concurrently connected devices, spectral performance, lesser battery intake, outage opportunity, higher bit rate, lower latencies, no. of supported gadgets, lower deployment cost and an additional dependable communication are predicted to be better in 5G. The anticipated deployment for this community is 2020.

Network will not suitable to support such increasingly more community usages is the major issue. In an effort to boom want to set up a flatter and greater dispensed community. The abundant file formats which includes all supported image, video, audio and information via NW (network) suggests that new source coding

### *Mobile Computing*

### **Table 1.**

*Network generations and its spectrum value.*

**Figure 1.** *5G structure for future networks.*

along with H.264 is needed for sharing and shifting. Some other aspect that ought to be taken into consideration is using superior radio access networks (RANs) including heterogeneous networks, and complex methodologies for RAT which includes a new WWAN (wireless wide area network). In the future demand of 5G, improvement in technologies that are associated with transportation cell, network speed and interoperability should be increased. Typically, the optimization can be done on the programs, devices and network. 5G wifi method offers a huge excessive bandwidth by the way we use wifi devices. Further about 5G is, without any boundary limit, 5G will interconnect the complete world through an exclusive clever era. In order to offer an actual worldwide wireless web (WWWW), a new innovative idea of a multipath data course scheme is applied. To implement this kind of wifi globally network mixing is required. The final 5G architecture is designed in reality with multi-bandwidth path by collecting the current and network destiny. **Figure 1** depicts the structure, which incorporates the prevailing and destiny system.

Consequently, in such an actual 5G, code-division multiple access (CDMA), multicarrier code-division multiple access (MCCDMA), ultra wide band (UWB),

**39**

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

speedy solutions.

**2.1 Access networks**

**2.2 User equipment**

the fundamental entry to network [3].

orthogonal frequency-division multiplexing (OFDM), and Internet protocol version 6 (IPv6) will maintain the complete system. Because of such an in depth structure, by way of the use of 5G it will be potential to have super records talents and join limitless decision volumes and endless records broadcast. This potential needs that the implemented generation for access points and transfer in 5G has to offer an excessive connection for the community. Some other expectation of 5G is its potential to allocate net get admission to networks across the world at a clean velocity. The use of 5G, the furnished decision for a wifi community could be excessive and there may be big bandwidth shaping in both the direction. Capacity in remote diagnostics is an extremely good characteristic of 5G era. Through faraway management users will experience a network with

**2. Challenges and issues in fifth generation wireless systems**

for a roadmap nearer to an additional bigger counter measures.

cells which can also be viable assaults at the 5G networks.

The maximum appealing objective for destiny attacker within the impending communications system of 5G can be the consumer instrumentation, accessing of a network, communication through mobile operator and outside IP networks. To assist the density protection problems and challenge in 5G system parts, we bequest cell structures which will have a sway on the future 5G communications systems have a tendency to gift adviser samples of viable threats and assaults explicit to those parts [2]. To receive these examples, we have a tendency to discover threats and assaults against by means of exploiting explicit capabilities with this latest communication principle. For the instance attacks, we have a tendency to in addition speak potential mitigation methods resultant from the literature that enables you

In fifth generation wireless systems, access points are anticipated to be notably complicated and heterogeneous, together with a couple of distinctive radio get right of entry to technologies and other advanced get admission to schemes, consisting of femtocells in order to guarantee the carrier availability. In non-existence of 4G for a while, the UE have to set up the connection over networks of 2G or 3G. Still, the reality that 5G network structures will help to inherit all the protection troubles of

During the transition from 4G to 5G communication, more desirable safety techniques must be carried out to counter prominent protection threats on 5G get right of entry to networks. To cope with this trouble, potential safety threats to the future 5G get right of entry to networks need to be first of all diagnosed. In this phase, awareness on attack presence on modern 4G access points and HeNB femto-

In the fifth generation wireless systems era, User Equipment (UE), which includes powerful clever phones and pills, may be a completely important a part of our day by day existence. Such system will provide an extensive range of attractive functions to permit give up consumers to access an abundance of high-first-rate customized offerings. In any case, the normal creating acknowledgment of the fate UE, joined with the increased measurements transmission skills of 5G systems, the colossal selection of open working structures and the truth that the future UE will

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

*Mobile Computing*

**Table 1.**

*Network generations and its spectrum value.*

**38**

**Figure 1.**

*5G structure for future networks.*

and destiny system.

along with H.264 is needed for sharing and shifting. Some other aspect that ought to be taken into consideration is using superior radio access networks (RANs) including heterogeneous networks, and complex methodologies for RAT which includes a new WWAN (wireless wide area network). In the future demand of 5G, improvement in technologies that are associated with transportation cell, network speed and interoperability should be increased. Typically, the optimization can be done on the programs, devices and network. 5G wifi method offers a huge excessive bandwidth by the way we use wifi devices. Further about 5G is, without any boundary limit, 5G will interconnect the complete world through an exclusive clever era. In order to offer an actual worldwide wireless web (WWWW), a new innovative idea of a multipath data course scheme is applied. To implement this kind of wifi globally network mixing is required. The final 5G architecture is designed in reality with multi-bandwidth path by collecting the current and network destiny. **Figure 1** depicts the structure, which incorporates the prevailing

**Network generation Year of appearance Spectrum value** 4G 2012 <100 MHz 3G 2001 <20 MHz 2G 1991 <200 KHz 1G 1981 <30 KHz

Consequently, in such an actual 5G, code-division multiple access (CDMA), multicarrier code-division multiple access (MCCDMA), ultra wide band (UWB), orthogonal frequency-division multiplexing (OFDM), and Internet protocol version 6 (IPv6) will maintain the complete system. Because of such an in depth structure, by way of the use of 5G it will be potential to have super records talents and join limitless decision volumes and endless records broadcast. This potential needs that the implemented generation for access points and transfer in 5G has to offer an excessive connection for the community. Some other expectation of 5G is its potential to allocate net get admission to networks across the world at a clean velocity. The use of 5G, the furnished decision for a wifi community could be excessive and there may be big bandwidth shaping in both the direction. Capacity in remote diagnostics is an extremely good characteristic of 5G era. Through faraway management users will experience a network with speedy solutions.

### **2. Challenges and issues in fifth generation wireless systems**

The maximum appealing objective for destiny attacker within the impending communications system of 5G can be the consumer instrumentation, accessing of a network, communication through mobile operator and outside IP networks. To assist the density protection problems and challenge in 5G system parts, we bequest cell structures which will have a sway on the future 5G communications systems have a tendency to gift adviser samples of viable threats and assaults explicit to those parts [2]. To receive these examples, we have a tendency to discover threats and assaults against by means of exploiting explicit capabilities with this latest communication principle. For the instance attacks, we have a tendency to in addition speak potential mitigation methods resultant from the literature that enables you for a roadmap nearer to an additional bigger counter measures.

### **2.1 Access networks**

In fifth generation wireless systems, access points are anticipated to be notably complicated and heterogeneous, together with a couple of distinctive radio get right of entry to technologies and other advanced get admission to schemes, consisting of femtocells in order to guarantee the carrier availability. In non-existence of 4G for a while, the UE have to set up the connection over networks of 2G or 3G. Still, the reality that 5G network structures will help to inherit all the protection troubles of the fundamental entry to network [3].

During the transition from 4G to 5G communication, more desirable safety techniques must be carried out to counter prominent protection threats on 5G get right of entry to networks. To cope with this trouble, potential safety threats to the future 5G get right of entry to networks need to be first of all diagnosed. In this phase, awareness on attack presence on modern 4G access points and HeNB femtocells which can also be viable assaults at the 5G networks.

### **2.2 User equipment**

In the fifth generation wireless systems era, User Equipment (UE), which includes powerful clever phones and pills, may be a completely important a part of our day by day existence. Such system will provide an extensive range of attractive functions to permit give up consumers to access an abundance of high-first-rate customized offerings. In any case, the normal creating acknowledgment of the fate UE, joined with the increased measurements transmission skills of 5G systems, the colossal selection of open working structures and the truth that the future UE will

help a tremendous style of network choices are issues that provides the future UE an ideal objective for cyber-criminals. Aside from the customary SMS/MMS-based absolutely Denial of Service (DoS) assaults, the future UE can likewise be revealed to more noteworthy refined assaults started from portable malware with the goal that you can focus on each the UE and the 5G cell network. The unprotected running structures will permit stop clients to introduce programs on gadgets, no longer easiest from trusted yet additionally from suspicious resources. Therefore, cell malware, which will be ensured in bundles made to give off an impression of being blameless programming, will be downloaded and introduced on stop client's cell devices presenting them to numerous dangers. Portable malware can be intended to empower aggressors to exploit the put away private realities on the gadget or to discharge assaults contrary to different substances, which incorporates diverse UE, the cell get right of section to systems, the cell administrator's middle system and distinctive outer systems connected to the cell focus network. Henceforth, traded off future cell phones will now not exclusively be a peril to their clients, anyway likewise to the whole 5G cell network serving those [4].

### **2.3 External IP networks**

In 5G wifi systems, the goal of DDoS attack is an external IP networks, wherein cellular back end generates traffic and finally transmits it to the goal over the core cellular network. Moreover, outside internet protocol systems, which incorporate organization systems, might be a delicate objective for being undermined by methods for malware through tainted cell contraptions getting to them. In this subsection, we blessing a delegate situation, in view of on [5], of how an association network might be undermined through the kindled 5G cell phone of a worker.

### **2.4 Core network for mobile operators**

Because of their IP-primarily depends open structure, 5G versatile structures may be powerless to IP ambushes which are ordinary compared to the Internet. DoS attacks, that are a central shot at the Internet these days, will be blessing on the predetermination 5G correspondences structures concentrated on substances on the portable administrator's center network [2]. In any case, the 5G versatile administrator's middle network might be moreover influenced by DDoS assaults focused on outside elements, anyway moving their malevolent site guests over it. Potential ambushes include:

Mobile Operator's Core Network is targeted by DDoS attacks:

### **3. Importance of fifth generation**

Few importances of fifth generation wireless systems are demonstrated in **Figure 2**. In the subsequent, all of the importances is intricate and highlights their function and importance for accomplishing fifth generation.

**41**

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

**3.1 Existing RATs evolution**

*Importance of fifth generation networks.*

**Figure 2.**

5th generation will rarely be a particular RAT, as a substitute it's miles possibly that it is going to be a combination of RATs along with the development of current methodology with new innovative plan complimented. In that capacity, the first and the most extreme intensely evaluated answer for adapt to the 1000× capacity crunch is the development of current RATs as far as SE, EE and inactivity, just as helping adaptable RAN sharing among more than one supplier. In particular, LTE needs to comply with help enormous/3-D MIMO to what's more exploit the spatial degree of freedom (DOF) by means of cutting edge multi-consumer bar shaping, to comparably decorate impedance crossing out and obstruction coordination capacities in a hyper thick small-cell sending situation. WiFi also wishes to conform to higher make the most to be had unauthorized spectrum. IEEE 802.11 ac, the modern-day enhancement of the WiFi era, can offer broadband wifi pipes with multi-Gbps facts charges. It uses the bandwidth extensively of hundred and sixty MHz on the much less polluted 5 GHz ISM band, using as much as 256 Quadrature Amplitude Modulation (QAM). It bolster concurrent transmissions up to 4 streams utilizing multi-person MIMO system [2]. The included shaft framing approach has helped the protection by methods for a few sets of significance, contrasted with its antecedent (IEEE 802.11n). At last, significant telecom organizations comprehensive of Qualcomm have as of late been running on creating LTE in the unlicensed range just as coordinating 3G/4G/WiFi handsets into a solitary multi-mode base station (BS) unit. In such manner, its miles expected that the upcoming UE will

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

*Mobile Computing*

help a tremendous style of network choices are issues that provides the future UE an ideal objective for cyber-criminals. Aside from the customary SMS/MMS-based absolutely Denial of Service (DoS) assaults, the future UE can likewise be revealed to more noteworthy refined assaults started from portable malware with the goal that you can focus on each the UE and the 5G cell network. The unprotected running structures will permit stop clients to introduce programs on gadgets, no longer easiest from trusted yet additionally from suspicious resources. Therefore, cell malware, which will be ensured in bundles made to give off an impression of being blameless programming, will be downloaded and introduced on stop client's cell devices presenting them to numerous dangers. Portable malware can be intended to empower aggressors to exploit the put away private realities on the gadget or to discharge assaults contrary to different substances, which incorporates diverse UE, the cell get right of section to systems, the cell administrator's middle system and distinctive outer systems connected to the cell focus network. Henceforth, traded off future cell phones will now not exclusively be a peril to their clients, anyway

In 5G wifi systems, the goal of DDoS attack is an external IP networks, wherein cellular back end generates traffic and finally transmits it to the goal over the core cellular network. Moreover, outside internet protocol systems, which incorporate organization systems, might be a delicate objective for being undermined by methods for malware through tainted cell contraptions getting to them. In this subsection, we blessing a delegate situation, in view of on [5], of how an association network might be undermined through the kindled 5G cell phone of a

Because of their IP-primarily depends open structure, 5G versatile structures may be powerless to IP ambushes which are ordinary compared to the Internet. DoS attacks, that are a central shot at the Internet these days, will be blessing on the predetermination 5G correspondences structures concentrated on substances on the portable administrator's center network [2]. In any case, the 5G versatile administrator's middle network might be moreover influenced by DDoS assaults focused on outside elements, anyway moving their malevolent site guests over it. Potential

• External units over a Mobile Operator's Core Network are targeted by DDoS

Few importances of fifth generation wireless systems are demonstrated in **Figure 2**. In the subsequent, all of the importances is intricate and highlights their

function and importance for accomplishing fifth generation.

Mobile Operator's Core Network is targeted by DDoS attacks:

likewise to the whole 5G cell network serving those [4].

**2.3 External IP networks**

**2.4 Core network for mobile operators**

worker.

ambushes include:

• HSS Saturation

attacks.

• Signaling Amplification

**3. Importance of fifth generation**

**40**

**Figure 2.** *Importance of fifth generation networks.*

### **3.1 Existing RATs evolution**

5th generation will rarely be a particular RAT, as a substitute it's miles possibly that it is going to be a combination of RATs along with the development of current methodology with new innovative plan complimented. In that capacity, the first and the most extreme intensely evaluated answer for adapt to the 1000× capacity crunch is the development of current RATs as far as SE, EE and inactivity, just as helping adaptable RAN sharing among more than one supplier. In particular, LTE needs to comply with help enormous/3-D MIMO to what's more exploit the spatial degree of freedom (DOF) by means of cutting edge multi-consumer bar shaping, to comparably decorate impedance crossing out and obstruction coordination capacities in a hyper thick small-cell sending situation. WiFi also wishes to conform to higher make the most to be had unauthorized spectrum. IEEE 802.11 ac, the modern-day enhancement of the WiFi era, can offer broadband wifi pipes with multi-Gbps facts charges. It uses the bandwidth extensively of hundred and sixty MHz on the much less polluted 5 GHz ISM band, using as much as 256 Quadrature Amplitude Modulation (QAM). It bolster concurrent transmissions up to 4 streams utilizing multi-person MIMO system [2]. The included shaft framing approach has helped the protection by methods for a few sets of significance, contrasted with its antecedent (IEEE 802.11n). At last, significant telecom organizations comprehensive of Qualcomm have as of late been running on creating LTE in the unlicensed range just as coordinating 3G/4G/WiFi handsets into a solitary multi-mode base station (BS) unit. In such manner, its miles expected that the upcoming UE will

be shrewd adequate to lift the pleasant interface for making connection with the RAN fundamentally dependent on the QoS necessities of the currently running implementation.

### **3.2 Hyper dense small-cell deployment**

When an additional EE is brought up in the device, hyper dense deployment of small-cell is every other challenging task to achieve the capacity in multiples of 1000. It is also called HetNet, Which in turn noticeably beautify the spectral efficiency (b/s/Hz/m2) of the region. Recently, many extraordinary ways are there to understand HetNet: (i) covering a cell device with small cells of identical technology with micro-, P.C.-, or femtocells; (ii) small-scale cells of various technology are masked in dissimilarity to simply the cellular one. The method is known as multi-tier HetNet, at latter point it has been denoted as multi-RAT HetNet.

On Qualcomm, a main organization in addressing 1000× potential undertaking via hyper dense small-cellular usage, has established that including small cells has the ability to scale the community nearly in a progressively increasing style, as depicted through diagram 3 [6]. That is, when small cells are increased then the capability also increased every time. Also, signal utilization and inter-mobile interference are increased when the cell length is reduced. To triumph over this downside, complex inter-cellular interference management strategies are wanted on the system stage together with complementary interference cancelation methods at the UEs. Enhancement of small-mobile changed into focus of LTE R-12, where the New Carrier Type (NCT) changed into delivered to manage small-scale cells by its host macro-cell. This lets in extra green manage plane functioning via the macro-layer at the same time by offering a maximum capacity and spectrally green records plane through the small-scale cells [7]. At last, reduction of cellular size enhances the network energy efficiency by keeping the community nearer to the UEs (**Figure 3**).

### **3.3 Self-organizing network**

Self-Organizing Network (SON) usefulness is very important thing of 5G. SON benefits additional energy when the mass of little cells build. Practically 80% of the wifi site guests is created inside. To convey this enormous site guests, we need hyper thick small-cellular arrangements in houses—set up and kept up specifically with the guide of the clients—refractory administrators. Indoor little cells should be selfcustomizable and mounted in an attachment and recreational way [2]. Besides, the

**43**

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

**3.4 Machine type communication**

**3.5 Millimeter-wave rats development**

from 4G to 5G.

ability of SON is required to shrewdly adjust to the neighboring little cells to restrain inter-mobile obstruction. For exemplar, a little versatile can do that through selfgoverning synchronizing with the network and astutely altering its radio inclusion.

Aside from people, interfacing cell machines is some other key issue of 5G. Machine type communication (MTC) is bringing programming up in which both one and both of the stop clients of the verbal trade meeting include machines. MTC forces two chief requesting circumstances on the system. To start with, the amount of gadgets that should be connected is generally enormous. Ericsson anticipates that 50 billion devices should be joined together inside the fate arranged society; the association imagines 'anything which can pick up from being connected may be connected' [8]. In the cell structure mechanism of a network, the diverse test forced with the guide of MTC is very quickening call for the management of actual-time and remote. It needs a truly low dormancy of considerably lower than an ms, so- alluded to as "tactile Internet" [9], managing 20× inactivity development

The ordinary sub-three GHz range is to transform into progressively more clogged and the current RATs are drawing close to Shannon's capacity limitation. All things considered, examines on investigating cm- and mmWave groups for versatile correspondences has just been initiated. Despite the fact that the examinations on this era are still in its early stages, the output looks encouraging. It has three principle obstacles for mmWave portable correspondences. To begin with, the course misfortune is exceptionally better at those groups, contrasted with a standard sub-3GHz groups. Secondly, EM signals have a tendency to proliferate in the Line-Of-Sight (LOS) way, representing the connections of radio inclined and found to be obstructed by utilizing moving contraptions or individuals. Finally and yet importantly, the infiltration misfortune through the homes is considerably huge

In spite of these confinements, there are heap gifts for mmWave interchanges. A significant measure of range is accessible in mmWave band; for instance, at 60 GHz, there might be 9 GHz of unlicensed range accessible. This is huge range, particularly the worldwide designated range for every cell innovation barely surpasses 780 MHz [10]. This measure of range can completely change portable interchanges through expert viding extremely-broadband remote pipes that can flawlessly stick the focused and the remote systems. Different advantages of mm Wave interchanges comprise of the little reception apparatus sizes (λ/2) and their little detachments, empowering many radio wire variables to be pressed in just one square centimeter. This in flip grants us to achieve exceptionally exorbitant bar shaping benefits in immensely little region, in such a way it can be connected at each the BS and the UE. Consolidating savvy staged cluster receiving wires, we will totally exploit the spatial level of opportunity of the wifi channel that may further improve the machine potential. At last, in light of the fact that the versatile station moves round, bar shaping loads can be balanced adaptively all together that the

As of late, a manufacturing company boss is investigating mm Wave groups for cell correspondences, tried an innovation which could accomplish 2 Gbps realities cost with 1 km assortment in a city surroundings [11]. Besides, Professor Theodore Rappaport and his examinations bunch on the Polytechnic Institute of New York

at these groups, shutting the exit way for indoor clients of RATs.

receiving wire shaft is always indicating the BS.

**Figure 3.** *Capacity scales linearly with the number of added small cells.*

*Mobile Computing*

implementation.

**3.2 Hyper dense small-cell deployment**

**3.3 Self-organizing network**

be shrewd adequate to lift the pleasant interface for making connection with the RAN fundamentally dependent on the QoS necessities of the currently running

When an additional EE is brought up in the device, hyper dense deployment of small-cell is every other challenging task to achieve the capacity in multiples of 1000. It is also called HetNet, Which in turn noticeably beautify the spectral efficiency (b/s/Hz/m2) of the region. Recently, many extraordinary ways are there to understand HetNet: (i) covering a cell device with small cells of identical technology with micro-, P.C.-, or femtocells; (ii) small-scale cells of various technology are masked in dissimilarity to simply the cellular one. The method is known as multi-tier HetNet, at latter point it has been denoted as multi-RAT HetNet.

On Qualcomm, a main organization in addressing 1000× potential undertaking via hyper dense small-cellular usage, has established that including small cells has the ability to scale the community nearly in a progressively increasing style, as depicted through diagram 3 [6]. That is, when small cells are increased then the capability also increased every time. Also, signal utilization and inter-mobile interference are increased when the cell length is reduced. To triumph over this downside, complex inter-cellular interference management strategies are wanted on the system stage together with complementary interference cancelation methods at the UEs. Enhancement of small-mobile changed into focus of LTE R-12, where the New Carrier Type (NCT) changed into delivered to manage small-scale cells by its host macro-cell. This lets in extra green manage plane functioning via the macro-layer at the same time by offering a maximum capacity and spectrally green records plane through the small-scale cells [7]. At last, reduction of cellular size enhances the network energy efficiency by keeping the community nearer to the UEs (**Figure 3**).

Self-Organizing Network (SON) usefulness is very important thing of 5G. SON benefits additional energy when the mass of little cells build. Practically 80% of the wifi site guests is created inside. To convey this enormous site guests, we need hyper thick small-cellular arrangements in houses—set up and kept up specifically with the guide of the clients—refractory administrators. Indoor little cells should be selfcustomizable and mounted in an attachment and recreational way [2]. Besides, the

**42**

**Figure 3.**

*Capacity scales linearly with the number of added small cells.*

ability of SON is required to shrewdly adjust to the neighboring little cells to restrain inter-mobile obstruction. For exemplar, a little versatile can do that through selfgoverning synchronizing with the network and astutely altering its radio inclusion.

### **3.4 Machine type communication**

Aside from people, interfacing cell machines is some other key issue of 5G. Machine type communication (MTC) is bringing programming up in which both one and both of the stop clients of the verbal trade meeting include machines. MTC forces two chief requesting circumstances on the system. To start with, the amount of gadgets that should be connected is generally enormous. Ericsson anticipates that 50 billion devices should be joined together inside the fate arranged society; the association imagines 'anything which can pick up from being connected may be connected' [8]. In the cell structure mechanism of a network, the diverse test forced with the guide of MTC is very quickening call for the management of actual-time and remote. It needs a truly low dormancy of considerably lower than an ms, so- alluded to as "tactile Internet" [9], managing 20× inactivity development from 4G to 5G.

### **3.5 Millimeter-wave rats development**

The ordinary sub-three GHz range is to transform into progressively more clogged and the current RATs are drawing close to Shannon's capacity limitation. All things considered, examines on investigating cm- and mmWave groups for versatile correspondences has just been initiated. Despite the fact that the examinations on this era are still in its early stages, the output looks encouraging. It has three principle obstacles for mmWave portable correspondences. To begin with, the course misfortune is exceptionally better at those groups, contrasted with a standard sub-3GHz groups. Secondly, EM signals have a tendency to proliferate in the Line-Of-Sight (LOS) way, representing the connections of radio inclined and found to be obstructed by utilizing moving contraptions or individuals. Finally and yet importantly, the infiltration misfortune through the homes is considerably huge at these groups, shutting the exit way for indoor clients of RATs.

In spite of these confinements, there are heap gifts for mmWave interchanges. A significant measure of range is accessible in mmWave band; for instance, at 60 GHz, there might be 9 GHz of unlicensed range accessible. This is huge range, particularly the worldwide designated range for every cell innovation barely surpasses 780 MHz [10]. This measure of range can completely change portable interchanges through expert viding extremely-broadband remote pipes that can flawlessly stick the focused and the remote systems. Different advantages of mm Wave interchanges comprise of the little reception apparatus sizes (λ/2) and their little detachments, empowering many radio wire variables to be pressed in just one square centimeter. This in flip grants us to achieve exceptionally exorbitant bar shaping benefits in immensely little region, in such a way it can be connected at each the BS and the UE. Consolidating savvy staged cluster receiving wires, we will totally exploit the spatial level of opportunity of the wifi channel that may further improve the machine potential. At last, in light of the fact that the versatile station moves round, bar shaping loads can be balanced adaptively all together that the receiving wire shaft is always indicating the BS.

As of late, a manufacturing company boss is investigating mm Wave groups for cell correspondences, tried an innovation which could accomplish 2 Gbps realities cost with 1 km assortment in a city surroundings [11]. Besides, Professor Theodore Rappaport and his examinations bunch on the Polytechnic Institute of New York

University have approved that cell interchanges at 28 GHz in a thick metropolitan condition alongside Manhattan, NY, is reasonable with a portable size of 200 m the utilization of dual 25 dBi reception apparatuses, one in base station and second in the UE, it promptly sensible the utilization of cluster receiving wires and the shaft shaping strategy [10].

Finally, foliage misfortune for mmWaves is full-size and might confinement the engendering. Besides, mmWave transmissions may likewise encounter tremendous weakenings in the event of a substantial downpour for the reason that rain droplets are equivalent to the radio wavelength size (millimeters) and subsequently can reason dispersing. In this manner, a reinforcement cell contraption working in inheritance sub-3 GHz groups is most likely required as a piece of the mmWave answer [10].

### **3.6 Redesign of backhaul links**

Updating the backhaul hyperlinks is consequent crucial trouble of 5th generation network. To improve the RAN in parallel backhaul interfaces should be reengineered to hold the huge client traffic produced in network cells. Something else, the backhaul connections will before long become bottlenecks, undermining the correct activity of the entire contraption. This issue increases more prominent energy on the grounds that the number of inhabitants in little cells increments [2]. Diverse verbal trade method can be thought by including optical fiber, mmWave and microwave. Explicitly, mmWave factor-to-point connections misusing exhibit radio wires with exceptionally sharp shafts are considered for solid self-backhauling in the absence of meddling with different cells or with the entrance hyperlinks.

### **3.7 Energy efficiency**

EE is a challenging factor while growing 5G. Currently, Information and Communication Technology (ICT) expends as a decent arrangement as 5% of the power delivered far and wide and is responsible for about 2% of overall nursery fuel outflows—generally equivalent to the emanations made with the guide of the aeronautics venture. What issues more prominent is the truth that on the off chance that we do never again take any degree to decrease the carbon emanations, the commitment is anticipated to twofold by 2020 [12]. Consequently, it is important to seek after electricity-efficient format forms from RAN and backhaul connections for the UEs.

The advantage of power-green system layout is manifold. To begin with, it can assume a basic job in supportable improvement by lessening the carbon impression of a cell endeavor itself. Secondly, ICT in light of the way that the inside allowing development of the fate shrewd towns similarly can play an essential limit in cutting down the carbon impression of different parts. Third, it might expand the offers of portable administrators by bringing down their operational consumption by saving money with their quality bills. Before the last step, bringing down the 'Joule per bit' cost can save versatile contributions ease for the clients, permitting level rate evaluating paying little mind to the 10–100× measurements expense advancement foreseen through 2020. Last anyway no longer least, the battery life of the UEs can be extended, this has been observed by methods for the statistical surveying organization TNS [13] in light of the fact that the main measure of the overall population of the shoppers obtaining a wireless.

### **3.8 New spectrum allocation for 5G**

Spectrum allocation of new gas wifi communications in the subsequent decade is an additional concern about 5G. The 1000× site visitors flow can infrequently be

**45**

**4. Conclusion**

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

**3.9 Bandwidth sharing**

**3.10 Ran virtualization**

following WRC convention, classified by ITU-R in 2015.

multi-tenant community operation and it will become sizeable.

adjusted by means of most effective spectral performance enhancement or by using hyper-compaction. Actually, the main telecom groups which include Qualcomm and NSN consider that beyond technology modernization, extra bandwidth in multiples of 10 is wanted to fulfill the call for [2]. Allocating 100 MHz spectrums at 700 MHz and 400 MHz bandwidth at 3.6 GHz, in addition to the ability of numerous GHz bandwidth allocations in cm or mm wavelength to 5G can be focused the

Original spectrum management is highly time ingesting. Hence the utilization of available bandwidth is critical. Sharing bandwidth in various methods may be accepted to conquer the verified regulatory boundaries. Military radars are allocated with huge radio spectrums, where it is not completely applied over the period of 24 hours for all the days in a week or within the complete coverage area. In contrast, bandwidth purification is highly hard as a few spectrum are impossible to clean or will take very long time to clean it effectively; beyond that, the spectrum may be cleaned in a few locations however no longer in the whole state. Exactly, the Authorized/Licensed Shared Access (ASA/LSA) technique has been suggested via Qualcomm in order to obtain the advantage of spectrum in small-scale regions without interfering with the regime person [14]. This kind of allocation of spectrum can balance the spectrum cleaning slowly. This is well significant citing that as cell site visitor increase quickens, spectrum reforming becomes essential to smooth an already allotted bandwidth and ensuring its availability for 5G. Cognitive Radio ideas are also rechecked to mutually make use of certified and unlicensed spectrums. Finally, an innovative model to share the spectrum may be required as

The final but no longer least important is virtualization of RAN by enabling 5G, permits to share wifi infrastructure over multiple carriers. Network virtualization has to be driven from stressed out core community towards the RAN. For network virtualization, the intelligence wishes to be drawn out from the RAN and guided in a centralized method the usage of a software program mind, it can be accomplished in various community coats. Network virtualization can bring numerous blessings to the wifi area, inclusive of each Capex and Opex financial savings through multiple user network and sharing of the network system, stepped forward EE, increasing the required assets on-demand basis, by reducing the TTM (time to market) of modern offerings leads to expand the community agility, in addition to clean maintenance and rapid troubleshooting via improved transparency of the community [15–18]. Virtualization can serve converge for both wired and the wifi mesh by means of mutually coping with the entire community using primary orchestration set, also to improve the network performance. At last, multiple RANs assisting 3G, 4G or wireless may be accepted wherein exclusive interfaces using radio signals may be grew to become OFF or ON via CSPCU (central software program control unit) to enhance Quality of Experience (QoE) or Energy Efficiency (EE) of stop consumers.

The concept of fifth generation wireless communication technology WWWW is initiated from fourth generation LTE technique. Accordingly, fifth generation

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

adjusted by means of most effective spectral performance enhancement or by using hyper-compaction. Actually, the main telecom groups which include Qualcomm and NSN consider that beyond technology modernization, extra bandwidth in multiples of 10 is wanted to fulfill the call for [2]. Allocating 100 MHz spectrums at 700 MHz and 400 MHz bandwidth at 3.6 GHz, in addition to the ability of numerous GHz bandwidth allocations in cm or mm wavelength to 5G can be focused the following WRC convention, classified by ITU-R in 2015.

### **3.9 Bandwidth sharing**

*Mobile Computing*

shaping strategy [10].

**3.7 Energy efficiency**

of the shoppers obtaining a wireless.

**3.8 New spectrum allocation for 5G**

**3.6 Redesign of backhaul links**

University have approved that cell interchanges at 28 GHz in a thick metropolitan condition alongside Manhattan, NY, is reasonable with a portable size of 200 m the utilization of dual 25 dBi reception apparatuses, one in base station and second in the UE, it promptly sensible the utilization of cluster receiving wires and the shaft

Finally, foliage misfortune for mmWaves is full-size and might confinement the engendering. Besides, mmWave transmissions may likewise encounter tremendous weakenings in the event of a substantial downpour for the reason that rain droplets are equivalent to the radio wavelength size (millimeters) and subsequently can reason dispersing. In this manner, a reinforcement cell contraption working in inheritance sub-3 GHz groups is most likely required as a piece of the mmWave answer [10].

Updating the backhaul hyperlinks is consequent crucial trouble of 5th generation network. To improve the RAN in parallel backhaul interfaces should be reengineered to hold the huge client traffic produced in network cells. Something else, the backhaul connections will before long become bottlenecks, undermining the correct activity of the entire contraption. This issue increases more prominent energy on the grounds that the number of inhabitants in little cells increments [2]. Diverse verbal trade method can be thought by including optical fiber, mmWave and microwave. Explicitly, mmWave factor-to-point connections misusing exhibit radio wires with exceptionally sharp shafts are considered for solid self-backhauling in the absence of meddling with different cells or with the entrance hyperlinks.

EE is a challenging factor while growing 5G. Currently, Information and Communication Technology (ICT) expends as a decent arrangement as 5% of the power delivered far and wide and is responsible for about 2% of overall nursery fuel outflows—generally equivalent to the emanations made with the guide of the aeronautics venture. What issues more prominent is the truth that on the off chance that we do never again take any degree to decrease the carbon emanations, the commitment is anticipated to twofold by 2020 [12]. Consequently, it is important to seek after electricity-efficient format forms from RAN and backhaul connections for the UEs. The advantage of power-green system layout is manifold. To begin with, it can assume a basic job in supportable improvement by lessening the carbon impression of a cell endeavor itself. Secondly, ICT in light of the way that the inside allowing development of the fate shrewd towns similarly can play an essential limit in cutting down the carbon impression of different parts. Third, it might expand the offers of portable administrators by bringing down their operational consumption by saving money with their quality bills. Before the last step, bringing down the 'Joule per bit' cost can save versatile contributions ease for the clients, permitting level rate evaluating paying little mind to the 10–100× measurements expense advancement foreseen through 2020. Last anyway no longer least, the battery life of the UEs can be extended, this has been observed by methods for the statistical surveying organization TNS [13] in light of the fact that the main measure of the overall population

Spectrum allocation of new gas wifi communications in the subsequent decade is an additional concern about 5G. The 1000× site visitors flow can infrequently be

**44**

Original spectrum management is highly time ingesting. Hence the utilization of available bandwidth is critical. Sharing bandwidth in various methods may be accepted to conquer the verified regulatory boundaries. Military radars are allocated with huge radio spectrums, where it is not completely applied over the period of 24 hours for all the days in a week or within the complete coverage area. In contrast, bandwidth purification is highly hard as a few spectrum are impossible to clean or will take very long time to clean it effectively; beyond that, the spectrum may be cleaned in a few locations however no longer in the whole state. Exactly, the Authorized/Licensed Shared Access (ASA/LSA) technique has been suggested via Qualcomm in order to obtain the advantage of spectrum in small-scale regions without interfering with the regime person [14]. This kind of allocation of spectrum can balance the spectrum cleaning slowly. This is well significant citing that as cell site visitor increase quickens, spectrum reforming becomes essential to smooth an already allotted bandwidth and ensuring its availability for 5G. Cognitive Radio ideas are also rechecked to mutually make use of certified and unlicensed spectrums. Finally, an innovative model to share the spectrum may be required as multi-tenant community operation and it will become sizeable.

### **3.10 Ran virtualization**

The final but no longer least important is virtualization of RAN by enabling 5G, permits to share wifi infrastructure over multiple carriers. Network virtualization has to be driven from stressed out core community towards the RAN. For network virtualization, the intelligence wishes to be drawn out from the RAN and guided in a centralized method the usage of a software program mind, it can be accomplished in various community coats. Network virtualization can bring numerous blessings to the wifi area, inclusive of each Capex and Opex financial savings through multiple user network and sharing of the network system, stepped forward EE, increasing the required assets on-demand basis, by reducing the TTM (time to market) of modern offerings leads to expand the community agility, in addition to clean maintenance and rapid troubleshooting via improved transparency of the community [15–18]. Virtualization can serve converge for both wired and the wifi mesh by means of mutually coping with the entire community using primary orchestration set, also to improve the network performance. At last, multiple RANs assisting 3G, 4G or wireless may be accepted wherein exclusive interfaces using radio signals may be grew to become OFF or ON via CSPCU (central software program control unit) to enhance Quality of Experience (QoE) or Energy Efficiency (EE) of stop consumers.

### **4. Conclusion**

The concept of fifth generation wireless communication technology WWWW is initiated from fourth generation LTE technique. Accordingly, fifth generation

should create a significant divergence and include few extra services and traits to the global over fourth generation. Fifth generation must be gifted technology that communicates the globe with no edges. Consequently, in this article the main importance of fifth generation wireless communication systems are proposed and also the issues and challenges of fifth generation communication systems are also described. The major benefit of switching to 5G is convergence of multi-network functions in order to reduce the complexity, cost, power, rapid speed and incredibly low latency. Even though 5G provides better infrastructure for new business models, help to streamline communications, organizing to handle big data using its efficient transfer speed without going away from its core function. That is to serve as a mobile network. Also 5G enable us to explore technologies like virtual reality (VR) and augmented reality (AR). In the future, it will lend his hands on new innovations such as remote robotic surgery and personalized wearable health trackers. Not but the least IoT security will be a source of major investment in forthcoming years.

### **Author details**

K. Sakthidasan Sankaran1 \*, G. Ramprabu<sup>2</sup> and V.R. Prakash1

1 Hindustan Institute of Science and Technology, Chennai, Tamil Nadu, India

2 New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**47**

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

> [11] Pi Z, Khan F. An introduction to millimeter-wave mobile broadband systems. IEEE Communications Magazine. 2011;**49**(6):101-107

[13] TNS. 'Two-Day Battery Life' Tops Wish List for Future All-in-One Phone

[14] Qualcomm, 1000x: More Spectrum–

Especially for Small Cell. 2013a

[15] Chowdhury NMK, Boutaba R. Network virtualization: State of the art and research challenges. IEEE Communications Magazine.

[16] Goudos SK, Diamantoulakis PD, Karagiannidis GK. Multi-objective optimization in 5G wireless

networks with massive MIMO. IEEE

[17] Salem AA, El-Rabaie S, Shokair M. Energy efficient ultra- dense networks based on multi-objective optimisation

[18] Hussain M, Rasheed H. March. Communication infrastructure for stationary and organized distributed smart meters. In: 2019 2nd International

Conference on Communication, Computing and Digital Systems (C-CODE) (pp. 17-22). IEEE; 2019

Communications Letters. 2018;**22**(11):2346-2349

framework. IET Networks.

2018;**7**(6):398-405

Device. 2005

2009;**47**(7):20-26

[12] Saghezchi FB, Radwan A, Rodriguez J, Dagiuklas T. Coalition formation game toward green mobile terminals in heterogeneous wireless networks. IEEE Wireless Communications. 2013;**20**(5):85-91

[1] Arjmandi MK. "5G overview: Key technologies", chapter 2. In: Opportunities in 5G Networks. Boca Raton: CRC Press; 2016. pp. 19-32

[2] Rodriguez J. Fundamentals of 5G Mobile Networks. Wiley: John Wiley and

[3] Piqueras Jover R. Security attacks against the availability of LTE mobility networks: Overview and research directions. In: Wireless Personal Multimedia Communications, IEEE, 16th International Symposium. 2013.

[4] La Polla M, Martinelli F,

Surveys and Tutorials. 2012;**15**(1):446-471

Sgandurra D. A survey on security for mobile devices. IEEE Communications

[5] Li F, Peng W, Huang CT, Zou X. Smartphone strategic sampling in defending enterprise network security. In: Communications, IEEE International

Conference. 2013. pp. 2155-2159

[7] Hoymann C, Larsson D,

and Vision, White paper. 2013

Magazine. 2014;**52**(2):140-145

Access. 2013;**1**:335-349

[10] Rappaport TS, Sun S, Mayzus R, et al. Millimeter wave mobile communications for 5G cellular: It will work! IEEE

[6] Qualcomm 1000x: More Small Cells– Hyper-Dense Small Cell Deployments.

Koorapaty H, Cheng JF. A lean carrier for LTE. IEEE Communications Magazine. 2013;**51**(2):74-80

[8] Ericsson. 5G Radio Access–Research

[9] Fettweis G, Alamouti S. 5G: Personal mobile internet beyond what cellular did to telephony. IEEE Communications

Sons Ltd; 2015

**References**

pp. 1-9

2004

*Importance of Fifth Generation Wireless Systems DOI: http://dx.doi.org/10.5772/intechopen.89345*

### **References**

*Mobile Computing*

**46**

**Author details**

Tamil Nadu, India

K. Sakthidasan Sankaran1

provided the original work is properly cited.

\*, G. Ramprabu<sup>2</sup>

\*Address all correspondence to<EMAIL_ADDRESS>
1 Hindustan Institute of Science and Technology, Chennai, Tamil Nadu, India

should create a significant divergence and include few extra services and traits to the global over fourth generation. Fifth generation must be gifted technology that communicates the globe with no edges. Consequently, in this article the main importance of fifth generation wireless communication systems are proposed and also the issues and challenges of fifth generation communication systems are also described. The major benefit of switching to 5G is convergence of multi-network functions in order to reduce the complexity, cost, power, rapid speed and incredibly low latency. Even though 5G provides better infrastructure for new business models, help to streamline communications, organizing to handle big data using its efficient transfer speed without going away from its core function. That is to serve as a mobile network. Also 5G enable us to explore technologies like virtual reality (VR) and augmented reality (AR). In the future, it will lend his hands on new innovations such as remote robotic surgery and personalized wearable health trackers. Not but the least IoT security will be a source of major investment in forthcoming years.

2 New Prince Shri Bhavani College of Engineering and Technology, Chennai,

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and V.R. Prakash1

[1] Arjmandi MK. "5G overview: Key technologies", chapter 2. In: Opportunities in 5G Networks. Boca Raton: CRC Press; 2016. pp. 19-32

[2] Rodriguez J. Fundamentals of 5G Mobile Networks. Wiley: John Wiley and Sons Ltd; 2015

[3] Piqueras Jover R. Security attacks against the availability of LTE mobility networks: Overview and research directions. In: Wireless Personal Multimedia Communications, IEEE, 16th International Symposium. 2013. pp. 1-9

[4] La Polla M, Martinelli F, Sgandurra D. A survey on security for mobile devices. IEEE Communications Surveys and Tutorials. 2012;**15**(1):446-471

[5] Li F, Peng W, Huang CT, Zou X. Smartphone strategic sampling in defending enterprise network security. In: Communications, IEEE International Conference. 2013. pp. 2155-2159

[6] Qualcomm 1000x: More Small Cells– Hyper-Dense Small Cell Deployments. 2004

[7] Hoymann C, Larsson D, Koorapaty H, Cheng JF. A lean carrier for LTE. IEEE Communications Magazine. 2013;**51**(2):74-80

[8] Ericsson. 5G Radio Access–Research and Vision, White paper. 2013

[9] Fettweis G, Alamouti S. 5G: Personal mobile internet beyond what cellular did to telephony. IEEE Communications Magazine. 2014;**52**(2):140-145

[10] Rappaport TS, Sun S, Mayzus R, et al. Millimeter wave mobile communications for 5G cellular: It will work! IEEE Access. 2013;**1**:335-349

[11] Pi Z, Khan F. An introduction to millimeter-wave mobile broadband systems. IEEE Communications Magazine. 2011;**49**(6):101-107

[12] Saghezchi FB, Radwan A, Rodriguez J, Dagiuklas T. Coalition formation game toward green mobile terminals in heterogeneous wireless networks. IEEE Wireless Communications. 2013;**20**(5):85-91

[13] TNS. 'Two-Day Battery Life' Tops Wish List for Future All-in-One Phone Device. 2005

[14] Qualcomm, 1000x: More Spectrum– Especially for Small Cell. 2013a

[15] Chowdhury NMK, Boutaba R. Network virtualization: State of the art and research challenges. IEEE Communications Magazine. 2009;**47**(7):20-26

[16] Goudos SK, Diamantoulakis PD, Karagiannidis GK. Multi-objective optimization in 5G wireless networks with massive MIMO. IEEE Communications Letters. 2018;**22**(11):2346-2349

[17] Salem AA, El-Rabaie S, Shokair M. Energy efficient ultra- dense networks based on multi-objective optimisation framework. IET Networks. 2018;**7**(6):398-405

[18] Hussain M, Rasheed H. March. Communication infrastructure for stationary and organized distributed smart meters. In: 2019 2nd International Conference on Communication, Computing and Digital Systems (C-CODE) (pp. 17-22). IEEE; 2019

**49**

Section 2

Mobile Networks

## Section 2 Mobile Networks

**51**

**Chapter 4**

**Abstract**

forecasting

**1. Introduction**

Networks

*Thembelihle Dlamini*

Softwarization in Future Mobile

The data growth generated by pervasive mobile devices and the Internet of Things at the network edge (i.e., closer to mobile users), couple with the demand for ultra-low latency, requires high computation resources which are not available at the end-user device. This demands a new network design paradigm in order to handle user demands. As a remedy, a new MN network design paradigm has emerged, called *Mobile Edge Computing* (MEC), to enable low-latency and locationaware data processing at the network edge. MEC is based on network function virtualization (NFV) technology, where mobile network functions (NFs) that formerly existed in the evolved packet core (EPC) are moved to the access network [i.e., they are deployed on local cloud platforms in proximity to the base stations (BSs)]. In order to reap the full benefits of the virtualized infrastructure, the NFV technology shall be combined with intelligent mechanisms for handling network resources. Despite the potential benefits presented by MEC, energy consumption is a challenge due to the foreseen dense deployment of BSs empowered with computation capabilities. In the effort to build greener 5G mobile network (MN), we advocate the integration of energy harvesting (EH) into future edge systems.

**Keywords:** softwarization, energy harvesting, soft-scaling, energy self-sustainability,

The evolution towards a softwarized evolved packet core (EPC) is the driving force towards overcoming the challenges observed in current mobile networks (MNs) and set the way for handling the high data rate and ultra-low latency

demands required by mobile users. This change avails the possibility of running network functions (NFs) in software, instead of proprietary hardware devices, and also it permits the possibility of dynamically scaling the network resources for a more robust network management in 5G and beyond as network complexity is reduced. Softwarization and virtualization of resources and services are undoubtedly among the main drivers of 5G and beyond 5G networks, as they will provide the mechanism for network management, that is, network flexibility and adaptability is guaranteed [1, 2], and also facilitate network maintenance and update all networks with ease. To address the need for MN evolution, different design approaches have been investigated towards the state-of-the-art EPC architecture where vendors and

Networks and Energy Efficient

### **Chapter 4**

## Softwarization in Future Mobile Networks and Energy Efficient Networks

*Thembelihle Dlamini*

### **Abstract**

The data growth generated by pervasive mobile devices and the Internet of Things at the network edge (i.e., closer to mobile users), couple with the demand for ultra-low latency, requires high computation resources which are not available at the end-user device. This demands a new network design paradigm in order to handle user demands. As a remedy, a new MN network design paradigm has emerged, called *Mobile Edge Computing* (MEC), to enable low-latency and locationaware data processing at the network edge. MEC is based on network function virtualization (NFV) technology, where mobile network functions (NFs) that formerly existed in the evolved packet core (EPC) are moved to the access network [i.e., they are deployed on local cloud platforms in proximity to the base stations (BSs)]. In order to reap the full benefits of the virtualized infrastructure, the NFV technology shall be combined with intelligent mechanisms for handling network resources. Despite the potential benefits presented by MEC, energy consumption is a challenge due to the foreseen dense deployment of BSs empowered with computation capabilities. In the effort to build greener 5G mobile network (MN), we advocate the integration of energy harvesting (EH) into future edge systems.

**Keywords:** softwarization, energy harvesting, soft-scaling, energy self-sustainability, forecasting

### **1. Introduction**

The evolution towards a softwarized evolved packet core (EPC) is the driving force towards overcoming the challenges observed in current mobile networks (MNs) and set the way for handling the high data rate and ultra-low latency demands required by mobile users. This change avails the possibility of running network functions (NFs) in software, instead of proprietary hardware devices, and also it permits the possibility of dynamically scaling the network resources for a more robust network management in 5G and beyond as network complexity is reduced. Softwarization and virtualization of resources and services are undoubtedly among the main drivers of 5G and beyond 5G networks, as they will provide the mechanism for network management, that is, network flexibility and adaptability is guaranteed [1, 2], and also facilitate network maintenance and update all networks with ease.

To address the need for MN evolution, different design approaches have been investigated towards the state-of-the-art EPC architecture where vendors and

researchers proposed the (i) grouping of the EPC functions [3–5], (ii) running the virtualized functions on clouds [6, 7], (iii) partitioning the network resources into network slices [8–11], which refers to an isolated set of (programmable) resources to enable NFs and services, and (iv) redesigning the network to be based on network function virtualization (NFV) technology [12, 13].

The architectural evolution involving the redesigning of the network based on NFV is currently appealing towards 5G and beyond, as it allows the virtualization of the mobile NFs and then placing them within the access network. This is motivated by the expected data explosion in the volume, variety, and velocity, generated by pervasive mobile devices and the Internet of Things [14] at the network edge (i.e., in close proximity to mobile devices, sensors, actuators, and connected things). This is coupled with the demand for stringent latency, requiring high computation resources which are not available at the end-user device. As a remedy, *Mobile Edge Computing* (MEC) has recently emerged to enable ultra-low latency, distributed intelligence and location-aware data processing closer to mobile users [2, 12, 13]. Undoubtedly, offloading to a powerful computation resource-enriched MEC server located closer to mobile users is an ideal solution.

Software-defined networking (SDN) and NFV are the emerging virtualization technologies that will enable flexibility and agility in MNs. SDN supports programmable interfaces to provide flexibility and agility on the network control management [14, 15], and NFV softwarizes the mobile NFs [16]. Both technologies limit the use of specialized hardware devices as they have been the limiting factor towards MNs evolution and the fast deployment of new services within the mobile space. The technologies can co-exist within the same network, where SDN employs a centralized approach on switching and routing elements [3], while NFV migrates the NFs out of dedicated hardware into software that is imported into general purpose hardware. In addition, these technologies are expected to facilitate the ease of efficient network management. The key to virtualization is that it enables *on-demand* or *utility* computing, a just in time resource provisioning model in which computing resources such as central processing unit (CPU), memory, and disk space are made available to applications only as needed and not allocated statistically based on the peak workload demand [17].

In light of the dense deployment pattern that is foreseen in 5G systems [18], the expected dense deployment of MEC servers and base stations (BSs) raises concerns related to energy consumption. Specifically, energy drained in BSs is due to the always-on approach (dimensioned for maximum expected capacity, yet traffic varies during the day), and in MEC servers, it is due to the computing-pluscommunication processes associated with: (i) the running virtual entities [virtual machines (VMs) or containers] [19, 20]; (ii) the communication within the server's virtual local area network (VLAN) [21], and the presence of transmission (optical) drivers (fast tunable optical drivers for data transfer) within the MN infrastructure [22, 23]. Since energy consumption is a challenge within a BS system and the virtualized computing nodes (i.e., MEC servers), quantifying the energy consumption within computing platforms and transmission nodes is of great importance towards the development of robust energy management procedures. In addition, to address the carbon footprint emission and dependence in the powered grid, methods for using renewable (green) energy coupled with sustainable energy storage solutions are now receiving more attention than before. The motivation towards green energy is that the components in solar- and wind-based systems are usually modular, which makes the design, expansion, and installation of these types of systems for the BS sites very practical and feasible. This result in energy harvesting (EH)-powered BSs (EH BSs) and MEC (EH-MEC) systems.

**53**

**Figure 1.**

*and container-based virtualization (right) [2].*

*Softwarization in Future Mobile Networks and Energy Efficient Networks*

functions being softwarized, technologies used, and so forth.

the underlying supporting software is rather different.

Softwarization and virtualization is the driving force towards network evolution. Towards this end, researchers from industry and academia have presented different proposals towards the EPC architectural evolution. Their contributions result into fragmented inputs (see [2] for more details about EPC architectural proposals), with a unified goal of having an energy efficient EPC architecture for future MNs. The outcome is designs/proposals that are somehow overlapping in terms of the

The virtualization tools consist of the *hypervisor* and *docker engine*, and they are illustrated in **Figure 1**. Virtualization making use of the hypervisor is referred to as *hypervisor-based* virtualization, with the VMs as the computing resources or computer emulators, and for the environment using docker engine is referred to as *container-based* virtualization, with the containers as the computing resources. These different virtualization techniques share a similar architectural structure. However, the way in which each technique builds virtualized applications on top of

A *hypervisor-based virtualization* simply isolates the operating system (OS) and applications from the underlying computer hardware [24]. This abstraction allows the underlying "host machine" hardware to independently operate one or more VMs as "guest machines" (also referred to as guest VMs), allowing them to share the systems physical computing resources, such as processing time, memory space, network bandwidth, etc. The hypervisor is the software that provides the environment in which the VMs operate. A new agnostic OS is generated to manage the underlying resources. Since the hypervisor sit between the actual physical hardware

*Container-based* virtualization involves the use of containers as the computing resources within the virtualized computing platforms. Containers are abstraction units for isolating applications and their dependencies that can run in any environment. They can run on the same machine, on top of the docker engine, sharing the OS kernel with other containers. The docker engine is a software technology written

*An illustration showing the architectures of virtualization technologies: hypervisor-based virtualization (left)*

and the guest OS, it is also referred to as virtual machine monitor (VMM).

*DOI: http://dx.doi.org/10.5772/intechopen.89607*

**1.1 Softwarization of mobile networks**

*1.1.1 Virtualization technologies and tools*

### **1.1 Softwarization of mobile networks**

*Mobile Computing*

researchers proposed the (i) grouping of the EPC functions [3–5], (ii) running the virtualized functions on clouds [6, 7], (iii) partitioning the network resources into network slices [8–11], which refers to an isolated set of (programmable) resources to enable NFs and services, and (iv) redesigning the network to be based on net-

The architectural evolution involving the redesigning of the network based on NFV is currently appealing towards 5G and beyond, as it allows the virtualization of the mobile NFs and then placing them within the access network. This is motivated by the expected data explosion in the volume, variety, and velocity, generated by pervasive mobile devices and the Internet of Things [14] at the network edge (i.e., in close proximity to mobile devices, sensors, actuators, and connected things). This is coupled with the demand for stringent latency, requiring high computation resources which are not available at the end-user device. As a remedy, *Mobile Edge Computing* (MEC) has recently emerged to enable ultra-low latency, distributed intelligence and location-aware data processing closer to mobile users [2, 12, 13]. Undoubtedly, offloading to a powerful computation resource-enriched MEC server

Software-defined networking (SDN) and NFV are the emerging virtualization technologies that will enable flexibility and agility in MNs. SDN supports programmable interfaces to provide flexibility and agility on the network control management [14, 15], and NFV softwarizes the mobile NFs [16]. Both technologies limit the use of specialized hardware devices as they have been the limiting factor towards MNs evolution and the fast deployment of new services within the mobile space. The technologies can co-exist within the same network, where SDN employs a centralized approach on switching and routing elements [3], while NFV migrates the NFs out of dedicated hardware into software that is imported into general purpose hardware. In addition, these technologies are expected to facilitate the ease of efficient network management. The key to virtualization is that it enables *on-demand* or *utility* computing, a just in time resource provisioning model in which computing resources such as central processing unit (CPU), memory, and disk space are made available to applications only as needed and not allocated statistically based on the

In light of the dense deployment pattern that is foreseen in 5G systems [18], the expected dense deployment of MEC servers and base stations (BSs) raises concerns related to energy consumption. Specifically, energy drained in BSs is due to the always-on approach (dimensioned for maximum expected capacity, yet traffic varies during the day), and in MEC servers, it is due to the computing-pluscommunication processes associated with: (i) the running virtual entities [virtual machines (VMs) or containers] [19, 20]; (ii) the communication within the server's virtual local area network (VLAN) [21], and the presence of transmission (optical) drivers (fast tunable optical drivers for data transfer) within the MN infrastructure [22, 23]. Since energy consumption is a challenge within a BS system and the virtualized computing nodes (i.e., MEC servers), quantifying the energy consumption within computing platforms and transmission nodes is of great importance towards the development of robust energy management procedures. In addition, to address the carbon footprint emission and dependence in the powered grid, methods for using renewable (green) energy coupled with sustainable energy storage solutions are now receiving more attention than before. The motivation towards green energy is that the components in solar- and wind-based systems are usually modular, which makes the design, expansion, and installation of these types of systems for the BS sites very practical and feasible. This result in energy harvesting (EH)-powered BSs

work function virtualization (NFV) technology [12, 13].

located closer to mobile users is an ideal solution.

peak workload demand [17].

(EH BSs) and MEC (EH-MEC) systems.

**52**

Softwarization and virtualization is the driving force towards network evolution. Towards this end, researchers from industry and academia have presented different proposals towards the EPC architectural evolution. Their contributions result into fragmented inputs (see [2] for more details about EPC architectural proposals), with a unified goal of having an energy efficient EPC architecture for future MNs. The outcome is designs/proposals that are somehow overlapping in terms of the functions being softwarized, technologies used, and so forth.

### *1.1.1 Virtualization technologies and tools*

The virtualization tools consist of the *hypervisor* and *docker engine*, and they are illustrated in **Figure 1**. Virtualization making use of the hypervisor is referred to as *hypervisor-based* virtualization, with the VMs as the computing resources or computer emulators, and for the environment using docker engine is referred to as *container-based* virtualization, with the containers as the computing resources. These different virtualization techniques share a similar architectural structure. However, the way in which each technique builds virtualized applications on top of the underlying supporting software is rather different.

A *hypervisor-based virtualization* simply isolates the operating system (OS) and applications from the underlying computer hardware [24]. This abstraction allows the underlying "host machine" hardware to independently operate one or more VMs as "guest machines" (also referred to as guest VMs), allowing them to share the systems physical computing resources, such as processing time, memory space, network bandwidth, etc. The hypervisor is the software that provides the environment in which the VMs operate. A new agnostic OS is generated to manage the underlying resources. Since the hypervisor sit between the actual physical hardware and the guest OS, it is also referred to as virtual machine monitor (VMM).

*Container-based* virtualization involves the use of containers as the computing resources within the virtualized computing platforms. Containers are abstraction units for isolating applications and their dependencies that can run in any environment. They can run on the same machine, on top of the docker engine, sharing the OS kernel with other containers. The docker engine is a software technology written

### **Figure 1.**

*An illustration showing the architectures of virtualization technologies: hypervisor-based virtualization (left) and container-based virtualization (right) [2].*

in the Go programming language and it avails the environment for developing and running applications. It runs natively on Linux systems (in recent Linux kernels), where it uses Linux kernel features like namespaces, to provide a private, restricted view on certain system resources within a container (i.e., a form of sandboxing), and control groups (cgroups), a technology that limits an application to a specific set of resources (i.e., provides resource management, e.g., limits and priorities, for groups of processes). We observe that the entire OS level architecture is being shared across them. The only parts that are created from scratch are the *Bins* and *Libs*. Despite the process isolation and lightweight character, containers are less secure and more vulnerable compared to hypervisor-based virtualization, and thus, they can be used as alternatives of hypervisor-based virtualization.

Determining the most suitable technology for a specific scenario requires a thorough analysis of the scenario design and performance requirements, along with an ultra-careful analysis of the benefits and drawbacks associated with the use of one tool over the other. What can be observed is that virtualization tools can play a role towards energy efficiency (EE) improvement within MNs. Considering the hypervisor-based virtualization, the hypervisor can report resource usage to the orchestrator in order to trigger system automated sleep mode states and also to implement policies that are provided by management and orchestration entity, which includes power management and power stepping [24]. On the other hand, container-based virtualization can be considered as an alternative of hypervisorbased virtualization, as containers demand less memory space, portable and lightweight, and have a shorter start-up time which translates to low latency and power consumption [19].

### *1.1.2 NFV-based EPC architectural evolution*

The works of [6, 7] proposed the use of a cloud-based approach with NFV platform, for the EPC evolution, in order to enable dynamic deployment of edge networks, the scaling of NFs, network monitoring, and load management. Both architectures avail the possibility of intelligently pooling capacity of resources when required.

In [6], the key elements of the architecture are (1) data-driven network intelligence for optimizing network resources usage and planning and (2) relaying and nesting techniques: to support multiple devices, group mobility, and nomadic hotspots. The EPC is virtualized into three parts, namely: (i) control plane entity (CPE), which is responsible for authentication, mobility management, radio resource control, and non-access stratum (NAS) and access stratum (AS) integration, (ii) the user plane entity (UPE), acting as a gateway, mobility anchor, and overthe-air (OTA) security provisioner. Lastly, (iii) the network intelligence (NI) plane is for the extraction of actionable insights from big data, orchestration or required services and functionalities (e.g., traffic optimization, caching, etc.). The realization of the network cloud can be achieved by enabling virtual function instances to be hosted in data centers when needed. The use of virtualization techniques will enable quick deployment and scalability of CPE and UPE functions. For example, in case of a natural disaster, with this technology, the local data center maybe unable to cope with the traffic upsurge; therefore, additional capacity can be sourced quickly from other data centers. A different strategy is employed in [7]. In that paper, the EPC architectural proposal simply abstracts the EPC network functions, decomposing and allowing them to run as software instances (virtual machines), on standard servers. This allows service providers to customize services and policies to design networks in new ways, to reduce costs, and simplify operations.

**55**

**Figure 2.**

*Softwarization in Future Mobile Networks and Energy Efficient Networks*

The aforementioned architecture proposals differ from one another. SDN is integrated with NFV in [6] to provide network control and to host the network intelligence, and in [7] only the NFV platform is available for enabling network services provision. Moreover, the architecture proposed in [7] is commercially available. Their contributions towards energy efficiency is as follows: (i) both make use of NFV and cloud computing platforms, and this avails the possibility of dynamically scaling resources based on demand as presented in [6] and (ii) through the information centric approach (collection of user-centric, network-centric, and context-centric data), intelligent algorithms, mainly network optimization tools, can be applied to the aggregated data in order to provide useful outlook for network

There is growing awareness to the fact that the communication sector uses significant amount of energy [25]. This is especially true for wireless and in particular for the BSs of cellular networks, where energy costs make up a large part of the operating expenses of mobile operators. In addition, in future MNs, the BSs will be empowered with computation capabilities to enable local workload offloading (computation) and the provision of ultra-low latency services, as well as EH systems. This gives rise to the need for efficient energy management procedures employing machine learning and control-theoretic techniques, within the MEC paradigm.

As EH technologies advance, powering the network apparatuses (edge systems) with green energy (e.g., solar and/or wind) is a promising solution to reduce ongrid power due to their location, reliability, carbon footprint, and cost. The network infrastructure is illustrated in **Figure 2**, where a computing site is shown. The virtualized computing platform (MEC server) consists of the VMs (this can also be

*The virtualized network infrastructure powered by hybrid energy sources: On-grid power and green energy.*

*The electro-mechanical switch (SW) selects the appropriate source of energy [26].*

*DOI: http://dx.doi.org/10.5772/intechopen.89607*

planning and resource management.

**2.1 Network infrastructure**

**2. Energy efficient in future mobile networks**

*Softwarization in Future Mobile Networks and Energy Efficient Networks DOI: http://dx.doi.org/10.5772/intechopen.89607*

The aforementioned architecture proposals differ from one another. SDN is integrated with NFV in [6] to provide network control and to host the network intelligence, and in [7] only the NFV platform is available for enabling network services provision. Moreover, the architecture proposed in [7] is commercially available. Their contributions towards energy efficiency is as follows: (i) both make use of NFV and cloud computing platforms, and this avails the possibility of dynamically scaling resources based on demand as presented in [6] and (ii) through the information centric approach (collection of user-centric, network-centric, and context-centric data), intelligent algorithms, mainly network optimization tools, can be applied to the aggregated data in order to provide useful outlook for network planning and resource management.

### **2. Energy efficient in future mobile networks**

There is growing awareness to the fact that the communication sector uses significant amount of energy [25]. This is especially true for wireless and in particular for the BSs of cellular networks, where energy costs make up a large part of the operating expenses of mobile operators. In addition, in future MNs, the BSs will be empowered with computation capabilities to enable local workload offloading (computation) and the provision of ultra-low latency services, as well as EH systems. This gives rise to the need for efficient energy management procedures employing machine learning and control-theoretic techniques, within the MEC paradigm.

### **2.1 Network infrastructure**

*Mobile Computing*

power consumption [19].

required.

*1.1.2 NFV-based EPC architectural evolution*

in the Go programming language and it avails the environment for developing and running applications. It runs natively on Linux systems (in recent Linux kernels), where it uses Linux kernel features like namespaces, to provide a private, restricted view on certain system resources within a container (i.e., a form of sandboxing), and control groups (cgroups), a technology that limits an application to a specific set of resources (i.e., provides resource management, e.g., limits and priorities, for groups of processes). We observe that the entire OS level architecture is being shared across them. The only parts that are created from scratch are the *Bins* and *Libs*. Despite the process isolation and lightweight character, containers are less secure and more vulnerable compared to hypervisor-based virtualization, and thus,

Determining the most suitable technology for a specific scenario requires a thorough analysis of the scenario design and performance requirements, along with an ultra-careful analysis of the benefits and drawbacks associated with the use of one tool over the other. What can be observed is that virtualization tools can play a role towards energy efficiency (EE) improvement within MNs. Considering the hypervisor-based virtualization, the hypervisor can report resource usage to the orchestrator in order to trigger system automated sleep mode states and also to implement policies that are provided by management and orchestration entity, which includes power management and power stepping [24]. On the other hand, container-based virtualization can be considered as an alternative of hypervisorbased virtualization, as containers demand less memory space, portable and lightweight, and have a shorter start-up time which translates to low latency and

The works of [6, 7] proposed the use of a cloud-based approach with NFV platform, for the EPC evolution, in order to enable dynamic deployment of edge networks, the scaling of NFs, network monitoring, and load management. Both architectures avail the possibility of intelligently pooling capacity of resources when

In [6], the key elements of the architecture are (1) data-driven network intelligence for optimizing network resources usage and planning and (2) relaying and nesting techniques: to support multiple devices, group mobility, and nomadic hotspots. The EPC is virtualized into three parts, namely: (i) control plane entity (CPE), which is responsible for authentication, mobility management, radio resource control, and non-access stratum (NAS) and access stratum (AS) integration, (ii) the user plane entity (UPE), acting as a gateway, mobility anchor, and overthe-air (OTA) security provisioner. Lastly, (iii) the network intelligence (NI) plane is for the extraction of actionable insights from big data, orchestration or required services and functionalities (e.g., traffic optimization, caching, etc.). The realization of the network cloud can be achieved by enabling virtual function instances to be hosted in data centers when needed. The use of virtualization techniques will enable quick deployment and scalability of CPE and UPE functions. For example, in case of a natural disaster, with this technology, the local data center maybe unable to cope with the traffic upsurge; therefore, additional capacity can be sourced quickly from other data centers. A different strategy is employed in [7]. In that paper, the EPC architectural proposal simply abstracts the EPC network functions, decomposing and allowing them to run as software instances (virtual machines), on standard servers. This allows service providers to customize services and policies to design

networks in new ways, to reduce costs, and simplify operations.

they can be used as alternatives of hypervisor-based virtualization.

**54**

As EH technologies advance, powering the network apparatuses (edge systems) with green energy (e.g., solar and/or wind) is a promising solution to reduce ongrid power due to their location, reliability, carbon footprint, and cost. The network infrastructure is illustrated in **Figure 2**, where a computing site is shown. The virtualized computing platform (MEC server) consists of the VMs (this can also be

### **Figure 2.**

*The virtualized network infrastructure powered by hybrid energy sources: On-grid power and green energy. The electro-mechanical switch (SW) selects the appropriate source of energy [26].*

containers), as the computing resources, empowered with EH capabilities through a solar panel and an energy buffer (EB) that enables energy storage. The power grid is also available for energy back up. The MEC node is assumed to be equipped with higher computational and storage resources compared to the end-user device. The energy manager (EM) is an entity responsible for selecting the appropriate energy source and for monitoring the energy level of the EB. The virtualized access control router (ACR) acts as an access gateway, responsible for routing, and it is locally hosted as an application. The input and output buffer are responsible for buffering admitted computation workload and storing aggregate computation results.

### *2.1.1 Energy consumption*

As suggested by ETSI [12, 27], the virtualized network functions (VNFs) can be deployed at the base station (BS), that is, the BS site is empowered with computation capabilities where the MEC server is co-located with the BS or placed at an aggregation point (a point in close proximity to a group of BS) for edge network management.

We consider a MEC deployment scenario where the BS is co-located with a MEC server, as an example, and the total energy consumption ([J]) for the communication site is formulated as follows, inspired by [28, 29] and the virtualization knowledge from [21]:

$$
\Theta\_{\text{Tot}}(t) = \Theta\_{\text{BS}}(t) + \Theta\_{\text{MEC}}(t),
$$

where θ*BS*(*t*) is the BS transmission energy (the load independent and the load dependent component), θ*MEC*(*t*) is the energy drained due to computation and due to intra-communications processes in the MEC server at time slot t. It is worth noting that the computational (MEC) energy cost includes: (i) the energy drained due to the running computing resources (VMs or containers), w.r.t CPU utilization, (ii) the energy drained due to VM/containers switching their processing rates, and (iii) the energy induced by the transmission control protocol (TCP)/Internet protocol (IP) offload on the network interface card (NIC, partial computation at the network adapter such as TCP/IP checksum offload). Regarding the communication energy cost, we have energy drained due to the communication links (to-and-from each VM/container) and the energy drained due to the number of transmission (optical) drivers used for the data transfer to target BS(s).

### **2.2 Energy saving strategies in MEC**

Considering the ultra-dense deployment of BSs and the dynamic characteristics of MNs, energy saving is of importance in green networks in order to exploit the benefits of sustainable computing and networking within edge systems. The sources of energy consumption in MEC are the BSs and the computing platforms. Towards this end, two large trends appear in the literature to address the energy efficiency challenge: (i) search for more energy efficient transmission devices and technologies; (ii) new technology proposals aimed at improving energy consumption in BSs, such as sleep mode, as it is known that switching on/off the BS transmission power during low traffic demand can yield significant energy savings [30–32]. Trend (ii) is more appealing due to the fact that future BS functions will be virtualized [1], thus enabling the ease of deactivating some of the BS functions. Within MEC servers, a joint *soft-scaling* (the reduction of computing resources per time instance) of the computing resources and the provision of minimum number of transmission drivers for data transfer to BS(s) in real-time is appealing.

**57**

heuristic algorithm.

*2.2.2 Energy savings in virtualized platforms using soft-scaling*

*Softwarization in Future Mobile Networks and Energy Efficient Networks*

The dramatic growth in mobile data has spurred the dense deployment of small cell BSs to enhance spectrum efficiency and increase network capacity. Although small cell BSs consume less power compared with macro BSs, the overall power consumption of a large number of small cell BSs is phenomenal. To address the energy saving procedures, sleep mode is adopted. The sleep mode application can be observed from a single mobile operator or multiple operators perspective, with the main goal of maximizing energy savings without any significant network impact. Towards energy savings in dense environment clustering algorithms have been proposed as a way of switching off BSs to reduce the energy consumption within MNs [33, 34]. However, the dynamic BS switching on/off strategies may have an *impact* on the network due to the traffic load that is offloaded to the neighboring BSs. To avoid this, the BS to be switched off must be carefully identified within a BS cluster. In [35], the *network impact* is used to identify the BS to be switched off within a cluster, one at a time, with no significant network performance degradation. Moreover, the network impact has been used in [36] to identify a BS to be switched off within a BS cluster where each BS is empowered with computation capabilities. With the advent of EH, it is desirable to incorporate the green energy utilization as a *performance metric* in traffic load balancing strategies [37, 38].

In the effort of greening future MNs, BSs are expected to be powered by green energy sources. On the other hand, NFV technology is expected to improve energy consumption by enabling the BS sleep modes, that is, scaling down the NFs during low traffic periods [24] or at low EB levels. Along the lines of MN softwarization, a distributed user association scheme that makes use of the soft-radio access network (RAN) concept for traffic load balancing via the RAN controller (RANC) is presented in [37]. Here, the user association algorithm is proposed and it runs in the RANC. The role of the algorithm is to enhance the network performance by reducing the average traffic delivery latency in BSs as well as to reduce the on-grid power consumption by optimizing the green energy usage. In cases where there is no centralized entity for edge network management, the need for distributed algorithm arises, which is the case with BSs co-located with MEC servers.

Furthermore, towards the effort of reducing the energy consumption through BS sleep modes, it is observed in the literature that most of the existing works considered clusters of BSs from a single mobile operator perspective, where some functions of the BS can be switched off and then the remaining active BSs handle the upcoming traffic. A new mechanism is presented in [39], which exploits the coexistence of multiple BSs from different mobile operators in the same area. An intra-cell roaming-based infrastructure-sharing strategy is proposed, followed by a distributed game-theoretic switching-off scheme that takes into account the conflicts and interaction among the different operators. Then, the work [40] of investigate the energy and cost efficiency of multiple HetNets [i.e., each HetNet is composed of eNodeBs (eNBs) and small cell BSs from one operator] that share their infrastructure and also are able to switch off part of it. Here, a form of roaming-based sharing is also adopted, whereby the operator can roam its traffic to a rival operator during a predefined period of time and area. An energy efficient optimization problem is formulated and solved using a cooperative greedy

To address 5G use cases in a more energy efficient way, visibility into power usage is required for developing power management policies in virtualized

*DOI: http://dx.doi.org/10.5772/intechopen.89607*

*2.2.1 Sleep-modes strategies in MNs*

### *2.2.1 Sleep-modes strategies in MNs*

*Mobile Computing*

*2.1.1 Energy consumption*

management.

knowledge from [21]:

containers), as the computing resources, empowered with EH capabilities through a solar panel and an energy buffer (EB) that enables energy storage. The power grid is also available for energy back up. The MEC node is assumed to be equipped with higher computational and storage resources compared to the end-user device. The energy manager (EM) is an entity responsible for selecting the appropriate energy source and for monitoring the energy level of the EB. The virtualized access control router (ACR) acts as an access gateway, responsible for routing, and it is locally hosted as an application. The input and output buffer are responsible for buffering admitted computation workload and storing aggregate computation results.

As suggested by ETSI [12, 27], the virtualized network functions (VNFs) can be deployed at the base station (BS), that is, the BS site is empowered with computation capabilities where the MEC server is co-located with the BS or placed at an aggregation point (a point in close proximity to a group of BS) for edge network

We consider a MEC deployment scenario where the BS is co-located with a MEC server, as an example, and the total energy consumption ([J]) for the communication site is formulated as follows, inspired by [28, 29] and the virtualization

θ*Tot*(*t*) = θ*BS*(*t*) + θ*MEC*(*t*),

where θ*BS*(*t*) is the BS transmission energy (the load independent and the load dependent component), θ*MEC*(*t*) is the energy drained due to computation and due to intra-communications processes in the MEC server at time slot t. It is worth noting that the computational (MEC) energy cost includes: (i) the energy drained due to the running computing resources (VMs or containers), w.r.t CPU utilization, (ii) the energy drained due to VM/containers switching their processing rates, and (iii) the energy induced by the transmission control protocol (TCP)/Internet protocol (IP) offload on the network interface card (NIC, partial computation at the network adapter such as TCP/IP checksum offload). Regarding the communication energy cost, we have energy drained due to the communication links (to-and-from each VM/container) and the energy drained due to the number of transmission

Considering the ultra-dense deployment of BSs and the dynamic characteristics of MNs, energy saving is of importance in green networks in order to exploit the benefits of sustainable computing and networking within edge systems. The sources of energy consumption in MEC are the BSs and the computing platforms. Towards this end, two large trends appear in the literature to address the energy efficiency challenge: (i) search for more energy efficient transmission devices and technologies; (ii) new technology proposals aimed at improving energy consumption in BSs, such as sleep mode, as it is known that switching on/off the BS transmission power during low traffic demand can yield significant energy savings [30–32]. Trend (ii) is more appealing due to the fact that future BS functions will be virtualized [1], thus enabling the ease of deactivating some of the BS functions. Within MEC servers, a joint *soft-scaling* (the reduction of computing resources per time instance) of the computing resources and the provision of minimum number

of transmission drivers for data transfer to BS(s) in real-time is appealing.

(optical) drivers used for the data transfer to target BS(s).

**2.2 Energy saving strategies in MEC**

**56**

The dramatic growth in mobile data has spurred the dense deployment of small cell BSs to enhance spectrum efficiency and increase network capacity. Although small cell BSs consume less power compared with macro BSs, the overall power consumption of a large number of small cell BSs is phenomenal. To address the energy saving procedures, sleep mode is adopted. The sleep mode application can be observed from a single mobile operator or multiple operators perspective, with the main goal of maximizing energy savings without any significant network impact.

Towards energy savings in dense environment clustering algorithms have been proposed as a way of switching off BSs to reduce the energy consumption within MNs [33, 34]. However, the dynamic BS switching on/off strategies may have an *impact* on the network due to the traffic load that is offloaded to the neighboring BSs. To avoid this, the BS to be switched off must be carefully identified within a BS cluster. In [35], the *network impact* is used to identify the BS to be switched off within a cluster, one at a time, with no significant network performance degradation. Moreover, the network impact has been used in [36] to identify a BS to be switched off within a BS cluster where each BS is empowered with computation capabilities. With the advent of EH, it is desirable to incorporate the green energy utilization as a *performance metric* in traffic load balancing strategies [37, 38].

In the effort of greening future MNs, BSs are expected to be powered by green energy sources. On the other hand, NFV technology is expected to improve energy consumption by enabling the BS sleep modes, that is, scaling down the NFs during low traffic periods [24] or at low EB levels. Along the lines of MN softwarization, a distributed user association scheme that makes use of the soft-radio access network (RAN) concept for traffic load balancing via the RAN controller (RANC) is presented in [37]. Here, the user association algorithm is proposed and it runs in the RANC. The role of the algorithm is to enhance the network performance by reducing the average traffic delivery latency in BSs as well as to reduce the on-grid power consumption by optimizing the green energy usage. In cases where there is no centralized entity for edge network management, the need for distributed algorithm arises, which is the case with BSs co-located with MEC servers.

Furthermore, towards the effort of reducing the energy consumption through BS sleep modes, it is observed in the literature that most of the existing works considered clusters of BSs from a single mobile operator perspective, where some functions of the BS can be switched off and then the remaining active BSs handle the upcoming traffic. A new mechanism is presented in [39], which exploits the coexistence of multiple BSs from different mobile operators in the same area. An intra-cell roaming-based infrastructure-sharing strategy is proposed, followed by a distributed game-theoretic switching-off scheme that takes into account the conflicts and interaction among the different operators. Then, the work [40] of investigate the energy and cost efficiency of multiple HetNets [i.e., each HetNet is composed of eNodeBs (eNBs) and small cell BSs from one operator] that share their infrastructure and also are able to switch off part of it. Here, a form of roaming-based sharing is also adopted, whereby the operator can roam its traffic to a rival operator during a predefined period of time and area. An energy efficient optimization problem is formulated and solved using a cooperative greedy heuristic algorithm.

### *2.2.2 Energy savings in virtualized platforms using soft-scaling*

To address 5G use cases in a more energy efficient way, visibility into power usage is required for developing power management policies in virtualized

computing platforms (i.e., MEC servers or data centers). In virtualized computing platforms, the energy consumption is related to the computing and communication processes. To minimize energy consumption within such environments, energy saving studies have involved the scaling up/down of servers/VMs [29, 41–43], VM migration (process of duplicating and transmitting the VM memory image over the network, in virtualized data centers, without or least service interruption [44]), and soft resource scaling (shortening the access time to physical resources [45]). With the advent of NFV, it is expected that the NFV framework [24, 46] can exploit the benefits of virtualization technologies to significantly reduce the energy consumption of large scale network infrastructures. In addition, the EE control framework [47] shall provide the control sequence and procedures for controlling and managing energy efficiency, within self-managed automated edge systems. Virtualization provides a promising approach for consolidating multiple online services onto few computing resources within an enterprise data center. By dynamically provisioning VMs, consolidating the workload, and switching servers on/off as needed, service providers can maintain the desired QoS while achieving higher server utilization and EE. In [17], a dynamic resource provisioning framework for a virtualized computing environment is presented and it is experimentally validated on a small server cluster that provides online services. Along the lines of MEC [28, 36], the long-term short memory (LSTM) neural network is used for forecasting the traffic load and harvested energy, and then the limited lookahead control (LLC) technique uses the forecasted traffic load and harvested energy to obtain the best control input that will drive the edge systems into the desired behavior.

### **3. Mobile datasets for network solutions**

To enable power transmission adaptation and load balancing across BSs, traffic load information (operator mobile traffic datasets) obtained from the EPC can be utilized to extract relevant demand patterns to design dynamic BS management mechanisms [48, 49]. Optimization based on mobile traffic datasets, obtained from multiple network elements described in [49], will make it possible to minimize the amount of time it takes to steer traffic on a real time basis, thus provisioning the network resources for computing and communication. From a networking perspective, the understanding and characterization of the traffic consumption within the network can pave the way towards more efficient and user/traffic-oriented networking solutions.

A greedy algorithm is used to estimate the energy savings through dynamic BS operation based on real cellular traffic traces and actual BS location, within an urban environment [48]. In addition, during crowded events (e.g., concerts and soccer games), MNs face voice and data traffic volumes that are often orders of magnitude higher than what they face during normal days. In [50], datasets usage show the potential of dynamically switching on/off BSs around a stadium (soccer field), as some of the BSs experience low traffic load during a large event. Moreover, it is shown that the use of real-world voice and data traces can provide insights about when to tune the radio resource allocation and to make use of opportunistic connection sharing (the aggregating of traffic from multiple devices into a single cellular connection) towards network improvement, without incurring any costs related to infrastructure changes [51]. To improve energy savings and guarantee QoS, within the MEC paradigm, in [28, 36] the traffic load and energy datasets (solar and wind) are used to provide a short-term forecast, that is then used by the foresighted optimization algorithm towards dynamic resource allocation.

**59**

**Author details**

Thembelihle Dlamini

University of Padova, Padova, Italy

provided the original work is properly cited.

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Softwarization in Future Mobile Networks and Energy Efficient Networks*

Future mobile networks are envisioned to be softwarized and the network functions virtualized. In light of this evolution, MEC has emerged to enable ultralow latency services, distributed intelligence, and location-aware data processing at the network edge. The foreseen dense deployment of base stations empowered with computation capabilities motivates the need for energizing the edge systems (BSs and MEC servers) with green energy (solar and/or wind energy) in order to minimize the carbon footprint and the dependence on the power grid. Moreover, the use of green energy promotes energy self-sustainability within the network. In order to improve the energy efficiency, mobile traffic datasets can be used to come up with traffic-oriented network management solutions. For dynamic resource management, over a look-ahead prediction horizon, machine learning methods and control-theoretic techniques (foresighted optimization) are foreseen as tools for edge network management, i.e., for green energy-aware network apparatuses.

*DOI: http://dx.doi.org/10.5772/intechopen.89607*

**4. Conclusion**

*Softwarization in Future Mobile Networks and Energy Efficient Networks DOI: http://dx.doi.org/10.5772/intechopen.89607*

### **4. Conclusion**

*Mobile Computing*

computing platforms (i.e., MEC servers or data centers). In virtualized computing platforms, the energy consumption is related to the computing and communication processes. To minimize energy consumption within such environments, energy saving studies have involved the scaling up/down of servers/VMs [29, 41–43], VM migration (process of duplicating and transmitting the VM memory image over the network, in virtualized data centers, without or least service interruption [44]), and soft resource scaling (shortening the access time to physical resources [45]). With the advent of NFV, it is expected that the NFV framework [24, 46] can exploit the benefits of virtualization technologies to significantly reduce the energy consumption of large scale network infrastructures. In addition, the EE control framework [47] shall provide the control sequence and procedures for controlling and managing energy efficiency, within self-managed automated edge systems. Virtualization provides a promising approach for consolidating multiple online services onto few computing resources within an enterprise data center. By dynamically provisioning VMs, consolidating the workload, and switching servers on/off as needed, service providers can maintain the desired QoS while achieving higher server utilization and EE. In [17], a dynamic resource provisioning framework for a virtualized computing environment is presented and it is experimentally validated on a small server cluster that provides online services. Along the lines of MEC [28, 36], the long-term short memory (LSTM) neural network is used for forecasting the traffic load and harvested energy, and then the limited lookahead control (LLC) technique uses the forecasted traffic load and harvested energy to obtain the best

control input that will drive the edge systems into the desired behavior.

To enable power transmission adaptation and load balancing across BSs, traffic load information (operator mobile traffic datasets) obtained from the EPC can be utilized to extract relevant demand patterns to design dynamic BS management mechanisms [48, 49]. Optimization based on mobile traffic datasets, obtained from multiple network elements described in [49], will make it possible to minimize the amount of time it takes to steer traffic on a real time basis, thus provisioning the network resources for computing and communication. From a networking perspective, the understanding and characterization of the traffic consumption within the network can pave the way towards more efficient and user/traffic-oriented

A greedy algorithm is used to estimate the energy savings through dynamic BS operation based on real cellular traffic traces and actual BS location, within an urban environment [48]. In addition, during crowded events (e.g., concerts and soccer games), MNs face voice and data traffic volumes that are often orders of magnitude higher than what they face during normal days. In [50], datasets usage show the potential of dynamically switching on/off BSs around a stadium (soccer field), as some of the BSs experience low traffic load during a large event. Moreover, it is shown that the use of real-world voice and data traces can provide insights about when to tune the radio resource allocation and to make use of opportunistic connection sharing (the aggregating of traffic from multiple devices into a single cellular connection) towards network improvement, without incurring any costs related to infrastructure changes [51]. To improve energy savings and guarantee QoS, within the MEC paradigm, in [28, 36] the traffic load and energy datasets (solar and wind) are used to provide a short-term forecast, that is then used by the foresighted optimization algorithm towards dynamic

**3. Mobile datasets for network solutions**

networking solutions.

resource allocation.

**58**

Future mobile networks are envisioned to be softwarized and the network functions virtualized. In light of this evolution, MEC has emerged to enable ultralow latency services, distributed intelligence, and location-aware data processing at the network edge. The foreseen dense deployment of base stations empowered with computation capabilities motivates the need for energizing the edge systems (BSs and MEC servers) with green energy (solar and/or wind energy) in order to minimize the carbon footprint and the dependence on the power grid. Moreover, the use of green energy promotes energy self-sustainability within the network. In order to improve the energy efficiency, mobile traffic datasets can be used to come up with traffic-oriented network management solutions. For dynamic resource management, over a look-ahead prediction horizon, machine learning methods and control-theoretic techniques (foresighted optimization) are foreseen as tools for edge network management, i.e., for green energy-aware network apparatuses.

### **Author details**

Thembelihle Dlamini University of Padova, Padova, Italy

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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