Channel-Coded Precoding for Multi-User MISO Systems

TL;DR

This paper introduces a novel channel-coded precoding (CCP) framework for multi-user MISO systems that integrates channel coding into precoding design, improving system performance by leveraging error correction capabilities.

Contribution

The paper proposes the first data-dependent precoding framework that incorporates channel coding into MISO systems, enhancing performance and robustness with a gradient-based design approach.

Findings

CCP outperforms existing precoding methods in simulations.

Incorporating channel coding increases degrees of freedom in transmit signal design.

Robust CCP handles imperfect channel state information effectively.

Abstract

Precoding is a critical and long-standing technique in multi-user communication systems. However, the majority of existing precoding methods do not consider channel coding in their designs. In this paper, we consider the precoding problem in multi-user multiple-input single-output (MISO) systems, incorporating channel coding into the design. By leveraging the error-correcting capability of channel codes we increase the degrees of freedom in the transmit signal design, thereby enhancing the overall system performance. We first propose a novel data-dependent precoding framework for coded MISO systems, referred to as channel-coded precoding (CCP), which maximizes the probability that information bits can be correctly recovered by the channel decoder. This proposed CCP framework allows the transmit signals to produce data symbol errors at the users' receivers, as long as the overall information BER performance can be improved. We develop the CCP framework for both one-bit and multi-bit error-correcting capacity and devise a projected gradient-based approach to solve the design problem. We also develop a robust CCP framework for the case where knowledge of perfect channel state information (CSI) is unavailable at the transmitter, taking into account the effect of both noise and channel estimation errors. Finally, we conduct numerous simulations to verify the effectiveness of the proposed CCP and its superiority compared to existing precoding methods, and we identify situations where the proposed CCP yields the most significant gains.