Stochastic Analysis of UDNs With Resource Capacity and User Scheduling

Abstract

In this paper, we investigate the impact of antenna elevation, resource capacity and user scheduling on the performance of ultra-dense networks (UDNs). Using tools from stochastic geometry (SG), we extend a recently introduced definition of coverage probability by inducing a generic thinning that can capture BSs with available resource capacity to transmit users data. Analytical results are then derived for the coverage probability and the average achievable rate, where we obtain closed-form expressions allowing to assess UDNs performance in a more tractable and meaningful fashion compared to the conventional definition of coverage probability. Moreover, we show that the average rate under the new definition requires only the computation of a two-fold numerical integral rather than a four-fold integral in the previous works, which is expected to significantly reduce computational complexity. Comparing the obtained results, we find that the impact of parameters, such as resource capacity, BS transmit power as well as the implementation complexity of scheduling schemes are irrelevant as network density increases, which suggests new insights into the role of these parameters in UDNs.