Resource Allocation Optimization In 5G Communication Network Using Bacterial Foraging Optimization Algorithm

Abstract

In wireless communication networks, resource allocation is a severe challenge because of trade-off between bandwidth efficiency, network performance, and power consumption. This research is employing a Bio-inspired algorithm namely BFO (Bacterial Foraging Optimization), using MATLAB, for improving the resource allocation optimization among multiple users in a 5G wireless network system. The two key network resources which are considered in this optimization problem are and Bandwidth and Power. The fitness function that is considered for this optimization is based on three parameters viz. latency, throughput and reliability. A population of bacteria is simulated by the proposed algorithm which explores the resource space thoroughly following three steps viz. chemotaxis, reproduction, and elimination- dispersal. A possible resource allocation solution is represented by each bacterium which evolves over several iterations for improving the performance. The fitness function has been developed in such a way that its value improves by minimizing latency and maximizing throughput and reliability. In this optimization problem 5 users have been considered with an independent bacteria population for each. Simulation results display efficacy of BFO to provide optimal solutions within minimal iterations. Findings guide that the BFO is providing an adaptive and robust method for wireless resource allocation optimization making it a promising candidate for future intelligent systems pertaining to wireless network management.