Minimum Symbol-Error Probability Symbol-Level Precoding with Intelligent Reflecting Surface

TL;DR

This paper proposes a joint symbol-level precoding and IRS reflection design to minimize symbol-error probability in IRS-assisted multiuser MISO systems, demonstrating significant performance improvements especially with many IRS elements.

Contribution

It introduces a novel joint design framework for SLP and IRS reflection to minimize SEP, addressing a non-convex optimization problem with an alternating minimization approach.

Findings

Enhanced bit-error rate performance with IRS aid

Significant improvements with increasing IRS elements

Effective joint optimization for symbol-level precoding and IRS reflection

Abstract

Recently, the use of intelligent reflecting surface (IRS) has gained considerable attention in wireless communications. By intelligently adjusting the passive reflection angle, IRS is able to assist the base station (BS) to extend the coverage and improve spectral efficiency. This paper considers a joint symbol-level precoding (SLP) and IRS reflecting design to minimize the symbol-error probability (SEP) of the intended users in an IRS-aided multiuser MISO downlink. We formulate the SEP minimization problems to pursue uniformly good performance for all users for both QAM and PSK constellations. The resulting problem is non-convex and we resort to alternating minimization to obtain a stationary solution. Simulation results demonstrate that under the aid of IRS our proposed design indeed enhances the bit-error rate performance. In particular, the performance improvement is significant when the number of IRS elements is large.