Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network
Energy scarcity is a major problem for resource constrained Internet of Things (IoT) devices. Nowadays, Energy harvesting (EH) has emerged as a promising solution to prolong the network lifetime using radio signals in wireless relay networks. In this article, we propose an optimization algorithm, based on meta-heuristic, to enhance the energy efficiency of amplify and forward relay IoT networks. Energy constraint relay exploits power-splitting based relay protocol to acquire energy from source and transfer information to destination. We derive expression for energy efficiency of the system using the throughput at destination and outage probability for performance evaluation. This investigation studies energy efficiency of the network against the various system parameters which are relay location, power-splitting factor, power transmitted, data rate, energy conversion efficiency and noise power and it enables us to find out which parameters need to be optimized. Further, an objective function is formulated to achieve the optimal solution for power transmitted by the source and an adaptive particle swarm optimization (OPA-APSO) algorithm is proposed to attain maximized energy efficiency. OPA-APSO differs from most existing approaches as it considers the amount of energy harvested while optimizing the solution. Finally, simulation results demonstrate that OPA-APSO improves energy efficiency and throughput of the network significantly as compared to other existing techniques.