Stable Matching Relay Selection (SMRS) for TWR D2D Network With RF/RE EH Capabilities

The green Internet of Things (IoT) has emerged as a promising paradigm to reduce the energy consumed by nodes in dense networks. To ensure energy efficiency (EE) operation, network devices are equipped with energy harvesting (EH) batteries that can further prolong the network lifetime. This study investigates a two-way relaying (TWR) device-to-device (D2D) model sharing the same resources with the underlying cellular network where all devices can harvest renewable energy (RE) from the surrounding environment. Each relay can assist one D2D link and harvest part of the received signal using the power splitting (PS) protocol. The radio frequency (RF) harvested energy is modeled using a non-linear EH model to match the behavior of the practical energy harvester. The main objective is to maximize the data rate (DR) of D2D links while preserving the quality of service (QoS) constraints. Therefore, a joint optimization solution based on particle swarm optimization (PSO) for power allocation (PA) and one-to-one stable matching (SM) for best relay selection (RS) is performed to untangle the mixed integer non-linear programming (MINLP) problem. Simulation results illustrate the behavior of the proposed model under different parameters as well as it is superiority over the most recent algorithm in terms of D2D link rate and EE.