User Association in Cell-less 5G Networks Exploiting Particle Swarm Optimisation

In heterogeneous networks (HetNets), users can by default associate with the macro base stations (BSs) while the small cell BSs are underloaded. Biasing user association is a simple and realistic approach to balance the load in HetNets, as well as creating a cell-less architecture where a user does not connect to the closest base station. Most of the existing research focuses on the static biasing scheme which is not the optimal strategy to improve the system performance. In this paper, the biasing factors are generated dynamically by the algorithm of particle swarm optimisation (PSO) with the objective of balancing the load and maximising the cell spectral efficiency (CSE). This work studies two different interference cases: the first case is when each tier uses different radio resources (typical when multiple radio access technologies are used) and a user receives interference only from same-tier base stations, whereas the second interference case is when all tiers use the same radio resources and a user receives interference from the same-tier and other tier BSs. The simulation results show that the dynamic biasing using PSO outperforms the static biasing in terms of balancing the load and maximising the CSE