One-Bit Symbol-Level Precoding for MU-MISO Downlink with Intelligent Reflecting Surface

TL;DR

This paper introduces a joint design of one-bit symbol-level precoding and IRS phase shifts for MU-MISO downlink, improving symbol error probability under low-resolution DAC constraints.

Contribution

It proposes a novel joint optimization framework for one-bit SLP and IRS phase shifts, addressing a complex MINLP problem with alternating optimization techniques.

Findings

Achieves lower symbol error probability compared to conventional methods.

Demonstrates the effectiveness of the joint design through numerical simulations.

Provides a practical solution for low-resolution DAC systems with IRS assistance.

Abstract

This paper considers symbol-level precoding (SLP) for multiuser multi-input single-output (MISO) downlink transmission with the aid of intelligent reflecting surface (IRS). Specifically, by assuming one-bit transmitted signals at the base station (BS), which arises from the use of low-resolution DACs in the regime of massive transmit antennas, a joint design of one-bit SLP at the BS and the phase shifts at the IRS is proposed with a goal of minimizing the worst-case symbol error probability (SEP) of the users under the PSK modulation. This joint design problem is essentially a mixed integer nonlinear program (MINLP). To tackle it, we alternately optimize the one-bit signal and the phase shifts. For the former, a dual of the relaxed one-bit SLP problem is solved by the mirror descent (MD) method with the maximum block improvement (MBI) heuristics. For the latter, the accelerated projected gradient (APG) method is employed to optimize the phases. Numerical results demonstrate that the proposed joint design can attain better SEP performance than the conventional linear precoding and one-bit SLP.