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

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