On Secondary Throughput Maximization and Eavesdropping Protection in RIS-Aided Underlay Green Cognitive Radio Networks

Abstract

In this work, a reconfigurable intelligent surface (RIS)-aided energy harvesting (EH) scheme on cognitive radio network (CRN), operating in an underlay mode, is considered in presence of an eavesdropper. Both primary user (PU) and secondary user (SU) networks, each one consisting of one transmitter-receiver pair, share the same spectrum simultaneously with a single antenna. The aim of the study is to maximize the secondary throughput while meeting PU data rate, SU energy causality and secrecy capacity constraints. The present work adopts an SU-centric RIS design, where the RIS phases are configured to coherently enhance the received signal at the SU receiver. Based on this design, the optimal phase and amplitude of each RIS element are determined, and the resulting configuration is employed in the joint optimization of SU transmit power (<inline-formula> <tex-math notation="LaTeX">$P_{S}$ </tex-math></inline-formula>) and the EH time allocation factor (<inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>). The optimal values of <inline-formula> <tex-math notation="LaTeX">$P_{S}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> are calculated through Lagrange method. The impact of RIS placement on SU throughput near/far to SU transmitter/receiver, PU receiver and eavesdropper are analyzed. SU throughput analysis with the change in the number of reflecting elements (‘M’) and amplitude attenuation of RIS are also analyzed in this work. Simulation results show efficacy of RIS on SU throughput as ~41.88% and ~96.85% gain over the existing works at <inline-formula> <tex-math notation="LaTeX">$M=64$ </tex-math></inline-formula> for ideal unit modulus reflection.