Performance Analysis of RIS-Assisted Spectrum Sharing Systems

TL;DR

The paper addresses RIS-assisted underlay spectrum sharing in a Rician fading environment, where a secondary source uses a RIS to communicate with a secondary destination under a peak power constraint $P$ and an interference limit $Q$ at the primary receiver. It develops novel analytical tools by deriving the SNR statistics $\rho$ in terms of incomplete $H$-functions and uses them to obtain exact outage probability, ergodic capacity, and BER, along with high-$P$ asymptotics. The key contributions include exact and asymptotic expressions for performance metrics that account for the RIS-induced sum channel $R = \sum_{n=1}^N \alpha_n \beta_n$ and the Rayleigh/Rician fading components, with validation via extensive Monte Carlo simulations. The results show substantial benefits from increasing the RIS size $N$ and provide practical insights for RIS deployment in spectrum-sharing scenarios, including design guidelines under interference constraints.

Abstract

We propose a reconfigurable intelligent surface (RIS)-assisted underlay spectrum sharing system, in which a RIS-assisted secondary network shares the spectrum licensed for a primary network. The secondary network consists of a secondary source (SS), an RIS, and a secondary destination (SD), operating in a Rician fading environment. We study the performance of the secondary network while considering a peak power constraint at the SS and an interference power constraint at the primary receiver (PR). Initially, we characterize the statistics of the signal-to-noise ratio (SNR) of the RIS-assisted secondary network by deriving novel analytical expressions for the cumulative distribution function (CDF) and probability density function (PDF) in terms of the incomplete H-function. Building upon the SNR statistics, we analyze the outage probability, ergodic capacity, and average bit error rate, subsequently deriving novel exact expressions for these performance measures. Furthermore, we obtain novel asymptotic expressions for the performance measures of interest when the peak power of the SS is high. Finally, we conduct exhaustive Monte-Carlo simulations to confirm the correctness of our theoretical analysis.

Figures (6)

• Figure 1: A RIS-aided secondary network shares the spectrum allocated to a primary network consisting of $M$PTs simultaneously communicating with a PR.
• Figure 2: Outage probability of the secondary network versus the SS peak power $P$ for various values of RIS elements $N$ at $\lambda= -5 \ \text{dB}$, $\gamma_{\mathrm{th}}= 10 \ \text{dB}$, and $Q= 0 \ \text{dB}$.
• Figure 3: Ergodic Capacity of the secondary network versus the SS peak power $P$ for various values of RIS elements $N$ at $\lambda= 0 \ \text{dB}$ and $Q= -10 \ \text{dB}$.
• Figure 4: Ergodic Capacity of the secondary network versus the interference power limit $Q$ for various values of RIS elements $N$ at $\lambda= 0 \ \text{dB}$ and $P= 10 \ \text{dB}$.
• Figure 5: Ergodic Capacity of the secondary network versus the number of RIS elements $N$ for various values of $Q$ at $\lambda= 0 \ \text{dB}$ and $P= 10 \ \text{dB}$.