RIS-Assisted Wireless Communications: Long-Term versus Short-Term Phase Shift Designs

TL;DR

This paper compares long-term and short-term RIS phase shift designs in wireless networks, deriving analytical expressions for coverage and rate, and proposes an optimized RIS placement strategy to enhance system performance.

Contribution

It introduces a comprehensive analysis of RIS phase shift designs based on channel statistics and proposes a novel placement optimization method using partial channel information.

Findings

Short-term RIS design outperforms long-term in coverage probability.

Optimized RIS placement significantly improves system performance.

Analytical expressions validate simulation results.

Abstract

Reconfigurable intelligent surface (RIS) has recently gained significant interest as an emerging technology for future wireless networks thanks to its potential for improving the coverage probability in challenging propagation environments. This paper studies an RIS-assisted propagation environment, where a source transmits data to a destination in the presence of a weak direct link. We analyze and compare RIS designs based on long-term and short-term channel statistics in terms of coverage probability and ergodic rate. For the considered optimization designs, we derive closed-form expressions for the coverage probability and ergodic rate, which explicitly unveil the impact of both the propagation environment and the RIS on the system performance. Besides the optimization of the RIS phase profile, we formulate an RIS placement optimization problem with the aim of maximizing the coverage probability by relying only on partial channel state information. An efficient algorithm is proposed based on the gradient ascent method. Simulation results are illustrated in order to corroborate the analytical framework and findings. The proposed RIS phase profile is shown to outperform several heuristic benchmarks in terms of outage probability and ergodic rate. In addition, the proposed RIS placement strategy provides an extra degree of freedom that remarkably improves system performance.