Energy Harvesting Optimization of Uplink-NOMA System for IoT Networks Based on Channel Capacity Analysis Using the Water Cycle Algorithm

Abstract

This article presents energy harvesting (EH) in 5G networks for uplink-NOMA systems for Rician and Rayleigh fading channels via optimizing the radio frequency (RF) energy charging period and the data transmission rate for each user. The model aims to maximize the EH system's efficiency depending on the number of users, time-slot, resource blocks, path loss, and base station power (BS). In this work, a simple, efficient, and multi-objective the Water Cycle Algorithm (WCA) is presented for calculating transmission rate and EH duration. Furthermore, simulation, performance analysis, and complexity results of WCA are shown by comparing its performance to those of the standard well-known Exhaustive Search Algorithm (ESA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). According to the optimization results within 6,800,000 possibilities, the WCA provides 11 percent more power allocation for the energy harvesting and more smooth time-sharing per user than the literature.