Resource allocation and client association in mmWave 5G networks using stochastic geometry

A 5G millimeter wave (mmWave) network, which operates at frequency bands above 24 GHz, is able to deliver speeds of Gbps through the use of beam-forming and the dense deployment of small cell access points (APs). In order to achieve load balancing among APs and fair allocations of channel resources among clients, a distributed algorithm based on dual decomposition has been proposed in the literature to deal with the problem of the associations of clients with APs and the allocations of channel resources. In order to obtain the overall throughput performance of a mmWave 5G network, clients are generally assumed to be evenly distributed over a service area, and a point Poisson process (PPP) is performed to generate the locations of clients and APs in each simulation run. In this paper, a different approach is adopted, in which stochastic geometry is employed to estimate the theoretical average throughput performance, without having to resort to a large number of simulations.