the sets of mIoT slices and URLLC slices, respectively. We focus on the modelling of uplink IoT data transmission in mIoT slices and the modelling of downlink URLLC data transmission in URLLC slices. The IoT devices are spatially distributed in ${\mathbb R}^2$ according to an independent homogeneous Poisson point process (PPP) $\Phi_s = \{u_{i,s}; s \in \mathcal{S}^I, i = 1, 2, \ldots\}$ with intensity $\lambda_s^I$, where $u_{i,s}$ denotes the location of the $i$-th IoT device in the $s$-th mIoT slice. There are also $N^u$ URLLC devices that are randomly and evenly distributed in ${\mathbb R}^2$. The RRHs are spatially distributed in ${\mathbb R}^2$ according to an independent PPP $\Phi_R = \{v_j; j = 1, 2, \ldots\}$ with intensity $\lambda_R$, where $v_j$ represents the location of the $j$-th RRH. The number and locations of IoT devices and RRHs will be fixed once deployed. Besides, each RRH is equipped with $K$ antennas, and each device is equipped with a single antenna. In IoT network slices, each IoT device is assumed to connect to its geographically closest RRH [@jiang2018analyzing]; thus, the cell area of each RRH constitutes a Voronoi tessellation. In URLLC network slices, RRHs cooperate to transmit signals to a URLLC device 