Programmable Metasurface Based Multicast Systems: Design and Analysis

TL;DR

This paper introduces a novel beam training method and analyzes the multicast rate for programmable metasurface-based multi-antenna systems, providing closed-form solutions and insights into system optimization.

Contribution

It proposes a low-overhead beam training approach and derives analytical expressions for multicast rate and optimal power allocation in PMS-based systems.

Findings

Beam training achieves performance comparable to exhaustive search with lower overhead.

Multicast rate increases with more reflecting elements and RF chains.

Equal power allocation is optimal under certain conditions, but adaptive power improves performance for weaker users.

Abstract

This paper considers a multi-antenna multicast system with programmable metasurface (PMS) based transmitter. Taking into account of the finite-resolution phase shifts of PMSs, a novel beam training approach is proposed, which achieves comparable performance as the exhaustive beam searching method but with much lower time overhead. Then, a closed-form expression for the achievable multicast rate is presented, which is valid for arbitrary system configurations. In addition, for certain asymptotic scenario, simple approximated expressions for the multicase rate are derived. Closed-form solutions are obtained for the optimal power allocation scheme, and it is shown that equal power allocation is optimal when the pilot power or the number of reflecting elements is sufficiently large. However, it is desirable to allocate more power to weaker users when there are a large number of RF chains. The analytical findings indicate that, with large pilot power, the multicast rate is determined by the weakest user. Also, increasing the number of radio frequency (RF) chains or reflecting elements can significantly improve the multicast rate, and as the phase shift number becomes larger, the multicast rate improves first and gradually converges to a limit. Moreover, increasing the number of users would significantly degrade the multicast rate, but this rate loss can be compensated by implementing a large number of reflecting elements.