Multi-ARIS Backscatter Enabled Downlink NOMA Communication for Cognitive Radio Systems
Shuai Han, Zeyang Sun, Sai Xu, Dan Xie, Cheng Li
Abstract
This paper investigates an active reconfigurable intelligent surface (ARIS) backscatter communication (BackCom) enabled downlink NOMA scheme in a cognitive radio (CR) system. Specifically, a dedicated primary beacon (PB) is deployed to serve the primary user while providing carrier signal for ARIS-BackCom units, which act as secondary transmitters (STs) to communicate with secondary users (SUs). Notably, the deployment of multiple ARIS-BackCom devices not only reduces the radio frequency (RF) component costs in the secondary network, but also provides multiple reflective link array gains, and overcomes the double-fading phenomenon effect. Based on the established system framework, we formulate the joint optimization problem of the beamforming vectors at the PB and the STs to maximize the weighted sum rate of the SUs while ensuring quality of service for the PU. The highly-coupled non-convex problem is decomposed into three sub-problems, which can be effectively addressed jointly using fractional programming, Lagrangian dual transform, difference-of-convex, and successive convex optimization methods. Finally, the comprehensive simulation results demonstrate that, in comparison with the traditional passive RIS-BackCom network, the proposed scheme significantly boosts the network’s weighted sum rate (WSR) by a minimum of 60%.