Power beacon and NOMA-assisted cooperative IoT networks with co-channel interference: Performance analysis and deep learning evaluation

Abstract

This study investigates a two-way relaying non-orthogonal multiple access (TWR-NOMA) enabled Internet-of-Things (IoT) network, in which two NOMA users communicate via an IoT access point (IAP) relay using a decode-and-forward (DF) protocol. A power beacon (PB) is used to power the IAP to address the IAP's limited lifetime due to energy constraints. Since co-channel interference (CCI) is inevitable in IoT systems, this effect is also studied in the proposed system to improve practicality. Based on the proposed system model, the closed-form equations for the exact and asymptotic outage probability (OP) and ergodic data (ED) of the NOMA users' signals are first derived to describe the performance of TWR-NOMA systems. The system's diversity order and throughput are then evaluated according to the derived results. To further improve the system's performance, a low-complexity strategy 2D golden section search (GSS) is performed, subject to power allocation (PA) and time-switching (TS) factors, to optimize the outage performance. Finally, a deep learning design with minimal computing complexity and precision OP prediction is established for a real-time IoT network configuration. The numerical results are discussed and analyzed in terms of the effects of the CCI, the TS ratio, the PA factor, the fading parameter on the OP, system throughput, and ED.