Reconfigurable Intelligent Surface-Aided NOMA with Limited Feedback

TL;DR

This paper analyzes the impact of limited feedback on RIS-aided NOMA systems, deriving bounds on rate loss due to quantization errors and showing performance approaches full CSI with more feedback bits.

Contribution

It provides a theoretical analysis of rate loss in RIS-aided NOMA systems with limited feedback, including bounds based on feedback bits and RIS size.

Findings

Rate loss bounds depend on feedback bits and RIS size.

Sum rate approaches full CSI performance as feedback increases.

Quantization methods impact the system's rate performance.

Abstract

The design of feedback channels in frequency division duplex (FDD) systems is a major challenge because of the limited available feedback bits. We consider non-orthogonal multiple access (NOMA) systems that incorporate reconfigurable intelligent surfaces (RISs). In limited feedback RIS-aided NOMA systems, the RIS-aided channel and the direct channel gains should be quantized and fed back to the transmitter. This paper investigates the rate loss of the overall RIS-aided NOMA systems suffering from quantization errors. We first consider random vector quantization for the overall RIS-aided channel and identical uniform quantizers for the direct channel gains. We then obtain an upper bound for the rate loss, due to the quantization error, as a function of the number of feedback bits and the size of RIS. Our numerical results indicate the sum rate performance of the limited feedback system approaches that of the system with full CSI as the number of feedback bits increases.