# Radio Resource Dimensioning for Low Delay Access in Licensed OFDMA IoT Networks +
## 6 Conclusions  
In this paper, we focus on licensed OFDMA-based IoT networks which corresponds to NB-IoT, LTE-M and to some extent 5G network using the numerology 0. We assume a wireless sensor network in which sensor nodes and collectors are distributed according a spatial PPP. A statistical method \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \(\lambda_{b}\) & **SISO** & \(\mathbf{1\times 8}\) **SIMO** & \(\mathbf{1\times 8}\) **SIMO** & \(\mathbf{1\times 8}\) **MU-MIMO** & \(\mathbf{1\times 8}\) **MU-MIMO** \\  & & **Selection** & **MRC** & \(\boldsymbol{n_{u}=2}\) & \(\boldsymbol{n_{u}=4}\) \\ \hline
0.1 & 23.40\% & 5.62\% & \(\boldsymbol{1.01\%}\) & 1.40\% & 2.90\% \\ \hline
0.3 & 7.13\% & 0.31\% & \(\boldsymbol{0.03\%}\) & 0.07\% & 0.27\% \\ \hline
0.5 & 3.97\% & 0.09\% & \(\boldsymbol{0.02\%}\) & 0.05\% & 0.20\% \\ \hline
0.7 & 2.84\% & 0.07\% & \(\boldsymbol{0.01\%}\) & 0.05\% & 0.20\% \\ \hline
0.9 & 2.30\% & 0.06\% & \(\boldsymbol{0.01\%}\) & 0.04\% & 0.21\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistical individual OFF probability with regard to antenna configuration, transmission mode and collector intensity \(\lambda_{b}\). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Power** & **SISO** & \(\mathbf{1\times 8}\) **SIMO** & \(\mathbf{1\times 8}\) **SIMO** & \(\mathbf{1\times 8}\) **MU-MIMO** & \(\mathbf{1\times 8}\) **MU-MIMO** \\
**(mW)** & & **Selection** & **MRC** & \(\boldsymbol{n_{u}=2}\) & \(\boldsymbol{n_{u}=4}\) \\ \hline Off & 3.97\% & 0.09\% & \(\boldsymbol{0.02\%}\) & 0.05\% & 0.20\% \\ \hline \(P_{\text{RR}}\) & 90.76\% & 99.39\% & \(\boldsymbol{99.92\%}\) & 99.80\% & 99.17\% \\ \hline
2\(P_{\text{RR}}\) & 2.81\% & 0.35\% & 0.04\% & 0.10\% & 0.40\% \\ \hline
3\(P_{\text{RR}}\) & 1.11\% & 0.09\% & 0.01\% & 0.03\% & 0.12\% \\ \hline
4\(P_{\text{RR}}\) & 0.10\% & 0 based on PPP is proposed to model and analyze the average behavior of the cellular IoT networks. This method is used for statistical resource planning to support the dominant uplink communications in the IoT networks and fulfill the network requirements in terms of limited transmission power per RR, low access delay, preset network outage probability and target data rate. Different antenna configurations and transmission modes are taken into account, e.g., SISO, SIMO, and MU-MIMO. Based on the preset tolerated average access delay and target data rate, the specific total number of RRs required for the typical cell is further calculated. Numerical results are finally given to assess our statistical analysis. We compare the theoretical results with the empirical simulation results in detail. The comparison shows that the results obtained from our statistical model are very close to the empirical results. Moreover, the results highlight and quantify the radio resources gain obtained by the receiver diversity techniques and the multiuser gains. Conceptualization: Y.Y., L.M., P.M., G.V. and M.T. ; methodology, Y.Y., L.M., P.M., G.V. and M.T. ; software, Y.Y. and L.M. ; validation, Y.Y. and L.M. ; formal analysis, L.M., Y.Y. and P.M.; writing--original draft preparation, Y.Y., L.M. ; writing--review and editing, L.M. ; visualization, Y.Y. ; supervision, L.M., M.T. ; project administration, G.V. ; funding acquisition, L.M. and G.V. All authors have read and agreed to the published version of the manuscript. This research was funded by French Agence Nationale de la Recherche (ANR), under grant ANR-16-CE25-0002-05 (project EPHYL). The authors declare no conflict of interest. The following abbreviations are used in this manuscript: