Reconfigurable Intelligent Surfaces Assisted Communication Under Different CSI Assumptions

TL;DR

This paper analyzes the performance of RIS-assisted multi-user MISO systems under imperfect CSI, comparing two channel estimation protocols and optimizing RIS phase-shifts for improved sum-rate.

Contribution

It introduces and compares two CSI acquisition protocols, deriving asymptotic SINR and sum-rate expressions, and demonstrates the advantages of a low-overhead direct estimation protocol.

Findings

Low-overhead DE protocol outperforms full CE in sum-rate.

S-CSI based RIS design achieves higher sum-rate than full I-CSI design.

Asymptotic SINR and sum-rate expressions enable effective RIS optimization.

Abstract

This work studies the net sum-rate performance of a distributed reconfigurable intelligent surfaces (RISs)-assisted multi-user multiple-input-single-output (MISO) downlink communication system under imperfect instantaneous-channel state information (I-CSI) to implement precoding at the base station (BS) and statistical-CSI (S-CSI) to design the RISs phase-shifts. Two channel estimation (CE) protocols are considered for I-CSI acquisition: (i) a full CE protocol that estimates all direct and RISs-assisted channels over multiple training sub-phases, and (ii) a low-overhead direct estimation (DE) protocol that estimates the end-to-end channel in a single sub-phase. We derive the asymptotic equivalents of signal-to-interference-plus-noise ratio (SINR) and ergodic net sum-rate under both protocols for given RISs phase-shifts, which are then optimized based on S-CSI. Simulation results reveal that the low-complexity DE protocol yields better net sum-rate than the full CE protocol when used to obtain CSI for precoding. A benchmark full I-CSI based RISs design is also outlined and shown to yield higher SINR but lower net sum-rate than the S-CSI based RISs design.