Maximizing IoT Throughput with Optimized IRS-Assisted Symbiotic Radio

Abstract

Symbiotic Radio (SR) is one of the techniques recognized by 6G for wireless communication networks performance enhancement. In this paper, SR is used to improve the performance of the Internet of Things (IoT) network by enabling IoT tags backscatter the neighbor smart phone primary signal rely on the None Orthogonal Multiple Access (NOMA) technique. Furthermore, Intelligent Reflecting Surfaces (IRS) are also proposed to enhance the channel Quality of Service (QoS); the service performance; between the IoT tags and the smartphones either using LTE or Wi-Fi network by smartly reconfiguring the signal propagation for performance improvement. We formulate an optimization problem to achieve the optimum location and phase shifts of the IRS, aiming to maximize the throughput of the IoT system. Proximal Policy Optimization (PPO) algorithm is introduced as a solution for this problem. The main idea of PPO is to minimize the divergence between the new and old policy while maximizing the expected reward. This is achieved by using a surrogate objective function that approximates the policy update. Simulation results demonstrate that the proposed algorithms can improve the total system data rate by an average of 40% above the system without using IRS and it also, improves the system capacity by 40% on average when compared to a system without the IRS scheme at smart phones p =4 which serve tags T =20.