An Energy Efficient Hybrid Metaheuristic Approach for Optimal D2D Communication with an Optimal Relay Selection

Device-to-Device (D2D) multicast communication is a cutting-edge technology in 5 G networks that enables efficient content sharing among users through direct communication between nearby devices. The energy consumption of D2D relay networks is a key barrier to D2D communication. It is critical to optimize energy efficiency to fully realize the promise of D2D communication. Relay-assisted D2D communications within cellular networks are made more energy-efficient by using a joint power allocation and relay selection scheme. The optimization problem is framed as a “mixed integer nonlinear fractional programming (MINLP)” problem, to maximize the total energy efficiency for D2D pairs. D2D communication can be achieved by selecting the most suitable relay and cluster head. A novel algorithm named self-improved hybrid Aquila Optimization (AO) and Mayfly Optimization (MO) algorithm is proposed to utilize the parameters of the D2D environment to form clustering, aiming to achieve optimal resource allocation, energy efficiency, and optimal relay selection. A Support Vector Machine (SVM)-based scheme is proposed to select an optimal relay for the D2D communication system. The scheme is designed to maximize energy efficiency by selecting the best relay. The proposed model is implemented in MATLAB, and spectral efficiency, energy efficiency, and throughput are some of the metrics are used to assess performance.