Radio resource allocation using genetic algorithm in heterogeneous networks

Abstract

SummaryRadio resource management to enable user association and resource block (RB) allocation is crucial for enhancing the performance of heterogeneous networks (HetNets), which are required for fifth generation (5G) mobile networks. This paper proposed a resource allocation technique based on a genetic algorithm (GA) for use in HetNets. We aimed to optimize user association and RB allocation simultaneously to fulfill multiple objectives, such as throughput and fairness measure. In addition to the four primary phases used in GA process, namely initialization, crossover, mutation, and selection, a further operator was provided for managing illegal offspring generated during a GA process. We performed a simulation to compare the proposed GA‐based approach with best channel quality indicator (CQI) algorithm and integer linear programming (ILP) approach in terms of total throughput and fairness measure. The simulation results revealed that the total throughput obtained using the proposed approach is 32.7% and 37.6% better than that obtained using the ILP and best CQI approaches, respectively. Moreover, the fairness measure obtained using the proposed GA‐based approach was 31.8% and 33.2% higher than that obtained using ILP and best CQI approaches, respectively.