Symbol-Level Precoding Made Practical for Multi-Level Modulations via Block-Level Rescaling

TL;DR

This paper introduces a practical interference exploitation symbol-level precoding method for multi-level modulations that reduces signaling overhead and improves error-rate performance through block-level rescaling.

Contribution

It presents a novel block-level rescaling approach for SLP that reduces signaling overhead and offers a closed-form solution, making SLP more practical for multi-level modulations.

Findings

Reduces signaling overhead significantly.

Improves error-rate performance.

Enables practical implementation of SLP.

Abstract

In this paper, we propose an interference exploitation symbol-level precoding (SLP) method for multi-level modulations via an in-block power allocation scheme to greatly reduce the signaling overhead. Existing SLP approaches require the symbol-level broadcast of the rescaling factor to the users for correct demodulation, which hinders the practical implementation of SLP. The proposed approach allows a block-level broadcast of the rescaling factor as done in traditional block-level precoding, greatly reducing the signaling overhead for SLP without sacrificing the performance. Our derivations further show that the proposed in-block power allocation enjoys an exact closed-form solution and thus does not increase the complexity at the base station (BS). In addition to the significant alleviation of the signaling overhead validated by the effective throughput result, numerical results demonstrate that the proposed power allocation approach also improves the error-rate performance of the existing SLP. Accordingly, the proposed approach enables the practical use of SLP in multi-level modulations.