Multi-objective genetic algorithm downlink resource allocation in LTE: Exploiting the cell-edge vs. Cell-center trade-off

Resource allocation in LTE networks is a challenging problem as multiple users, under a variety of channel conditions, compete for scarce network resources. Moreover, targeting the optimization of the network capacity while still guaranteeing a minimum quality of service complicates the problem considerably. Traditional schedulers can achieve a single tradeoff between the conflicting capacity optimization and fairness objectives. This paper presents a novel allocation strategy based on genetic algorithms in which both objectives are simultaneously optimized. This is done by maximizing both the total cell rate and cell-edge rate. The results show that the proposed algorithm offers a range of Pareto optimal solutions that outperform all other reference strategies.