Stochastic Firefly Optimization and Multi-Objective Greedy Algorithm-based Resource Allocation Scheme for Underlay D2D Communication

Abstract

Device-to-device (D2D) communication is a vital technology in fifth-generation (5G) networks, enabling direct communication between nearby devices without passing data through a base station (BS). In inband underlay D2D communication, devices share cellular user resources, leading to interference. Managing this interference is crucial for seamless cellular and D2D communication. This paper proposes a resource allocation scheme using the Stochastic Firefly Optimization (SFO) algorithm to enhance system throughput while avoiding infeasible solutions. Additionally, the Multi-Objective Greedy (MOG) algorithm predicts optimal communication modes and resource allocation, improving energy and spectral efficiency. Simulation results validate the algorithm’s effectiveness in managing interference and boosting performance. A comparative analysis against existing algorithms highlights the scheme’s superiority in terms of data rate, energy efficiency, and spectral efficiency, establishing it as a robust solution for advancing D2D communication in 5G networks.