Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO

Abstract

Non-orthogonal multiple access technique (NOMA) is based on the principle of sharing the same physical resource, over several power levels, where user’s signals are transmitted by using the superposition-coding scheme at the transmitter and these users signals are decoded by the receiver by means of successive interference cancellation technique (SIC). In this work, performance of NOMA Downlink network under Rayleigh fading distribution is studied, in the power domain where a power beacon (PB) is used to help a base station (BS) to serve distant users, by Wireless Power Transfer (WPT). The harvested energy permits by the BS, supports information signal transmission to NOMA users. This concept can be an effective way to power Internet of Things (IoT) devices, reduce battery dependency, and promote energy sustainability and may be used in SWIPT systems and vehicular networks. To improve the key performance indicators of the system expressed by the outage performance of NOMA users and system throughput, a Multi-Objective Grey Wolf Optimizer algorithm (MOGWO) is used to find optimal values of several influencing parameters. These parameters are partition time expressing the harvesting energy time, the power conversion factor and power allocation coefficients.