comprises of $K$ subsets, $\Phi_k$ for $k\in \mathcal K \buildrel \Delta \over = \{1,\cdots, K\}$, where each subset refers to a specific type of IoT service. Traffic from different subsets differ in the way they use the time-frequency resources, i.e. in frequency of packet generation $1/T_k$, signal bandwidth $w_k$, packet transmission time $\tau_k$, number of replicas[^1] transmitted per packet $n_k$, and transmit power $P_k$. Subscript $k$ refers to the type of IoT devices. For PCP of type-$k$ IoT traffic, the $(\lambda_k, \upsilon_k, \text{f}({\bf x}))$ tuple characterizes the distribution process in which, $\lambda_k$ is the density of the parent points and $\upsilon_k$ is the average number of daughter points per parent point[^2], as defined in [@pcp]. Also, $\text{f}({\bf x})$ is an isotropic function representing scattering density of the daughter points around a parent point, e.g. a normal distribution: $$\label{nor}\text{f}({\bf x})={\exp(-||{\bf x}-{\bf x}_0||^2/(2\sigma^2))}/{\sqrt{2\pi\sigma^2}},$$ where $\sigma$ is the variance of distribution and ${\bf x}_0$ is the location of parent point. A frequency spectrum of $W$ is shared for communications, on which the power spectral density of noise is denoted by $\mathcal N$. We aim at collecting data from a subset of $\mathcal K$, denoted by $\phi$, where $|\phi|\le |\mathcal K|$. Devices in $\phi$ 