## 2 System Model
### Radio Part  
The impact of the radio part manifests itself in two critical parameters: (i) coverage of the BS \(r\) and (ii) resource request characterization, \(b_{k}^{\min}\), \(b_{k}^{\max}\). These two quantities can be obtained by utilizing session rate requirements \(c_{k}^{\min}\), \(c_{k}^{\max}\) and radio part models, including propagation, antenna, and blockage models specified in [19] depending on the considered deployment and operational frequency. Below, we illustrate the basic steps involved in parameterization [20; 21]. The exposure provided below is applicable for both microwave (\(\mu\)Wave) and millimeter wave (mmWave) 5G NR systems, see, for example, [22]. The coverage radius \(r\) of the cell is assumed to be the maximum separation between the UE and the NR BS, such that the UE is not in an outage. The signal-to-interference-plus-noise ratio (SINR) at the 3D distance \(y\) is provided by  
\[S(y)=\frac{P_{B}G_{B}G_{U}M_{SF}L(y)}{N_{0}B+M_{I}}, \tag{1}\]  
where \(P_{B}\) is the NR BS emitted power; \(G_{B}\) and \(G_{U}\) are the BS and UE antenna gains, respectively, obtained from [23]; \(N_{0}\) is the thermal noise power spectral density; \(B\) is the system bandwidth; \(M_{SF}\sim N(0,\sigma_{SF})\) is the shadowing; \(M_{I}\) is the cross-cell interference margin; and \(L(y)\) is the path loss that can be obtained from TR 38.901 [19]. \[L_{dB}(y)=\beta+10\zeta\log_{10}y+20\log_{10}f_{c}, \tag{2}\]  
where \(f_{c}\) is the carrier frequency measured in GHz, \(\beta\), and \(\zeta\) are the parameters provided in [19] that depend on the utilized band and propagation conditions. To derive \(r\), we assume the worst-case scenario for millimeter wave communications, such that UE at the cell edge is in non-line-of-sight (nLoS) conditions and is also blocked. Figure 1: The considered system model and its formalization in terms of a queueing system: (**a**) system model, (**b**) queueing model. Observe that the path loss in (2) can be represented in the linear scale by utilizing the model in the form \(Ay^{\zeta_{nLoS}}\), where \(A=10^{2\log_{10}f_{c}+\beta}\). The 3D distance \(y\) is given by  
\[y=\sqrt{r^{2}+[h_{BS}-h_{UE}]^{2}}. \tag{3}\]  
By solving (1) and (3) with respect to \(r\), we have  
\[r=\sqrt{\left(\frac{P_{B}G_{B}G_{U}M_{SF}}{10^{\frac{\beta}{6}}f_{c}^{2}(N_{0} B+M_{I})S_{th}}\right)^{\frac{2}{\zeta_{nLoS}}}(h_{BS}-h_{UE})^{2}}, \tag{4}\]  
where \(\zeta_{nLoS}=3.19\), \(\beta=52.4\) dB, \(S_{th}=-8.97\) dB is the SINR threshold corresponding to the minimum feasible modulation and coding scheme (MCS) in 5G NR [19; 24]. Select \(r\) such that the UE at the cell edge spends no more than 5% of time in outage conditions. The corresponding value of \(M_{SF}\) is provided by solving  
\[M_{SF}=\sqrt{2}\text{erfc}^{-1}(2p_{out})\sigma_{\text{SF}}, \tag{5}\]  
where \(p_{out}=0.05,\text{erfc}^{-1}(\cdot)\) is the inverse complementary error function, \(\sigma_{\text{SF}}\) is the standard deviation of the shadow fading distribution in the nLoS state tabulated in [19]. Once radius \(r\) is obtained, one may characterize the required resources \(b_{k}^{\min}\), \(b_{k}^{\max}\)\(k=1,2,\ldots,K\), to satisfy session rate requirements, \(c_{k}^{\min}\), \(c_{k}^{\max}\). Recalling that UEs are assumed to be uniformly distributed in the coverage of NR BS with the probability density function (pdf) in the form \(f(y)=2y/r^{2}\), \(0<y<r\)[25], the mean spectral efficiency can be obtained as follows  
\[E[C_{e}]=\int_{0}^{r}\frac{2y}{r^{2}}\log_{2}[1+S(y)]dy, \tag{6}\]  
where \(S(y)\) is the SINR at 3D distance \(y\).