Block-Level Interference Exploitation Precoding for MU-MISO: An ADMM Approach

TL;DR

This paper introduces a novel ADMM-based algorithm for block-level interference exploitation precoding in MU-MISO systems, enabling efficient large-scale optimization with proven feasibility and flexible performance tradeoffs.

Contribution

It extends CI-BLP analysis to fewer symbol slots than users, providing a closed-form solution and a low-complexity ADMM algorithm for large-scale systems.

Findings

The pseudo-inverse can be used for optimal CI-BLP precoding.

The ADMM algorithm efficiently solves large-scale QP problems.

Numerical results confirm the algorithm's effectiveness and flexibility.

Abstract

We study constructive interference based block-level precoding (CI-BLP) in the downlink of multi-user multiple-input single-output (MU-MISO) systems. Specifically, our aim is to extend the analysis on CI-BLP to the case where the considered number of symbol slots is smaller than that of the users. To this end, we mathematically prove the feasibility of using the pseudo-inverse to obtain the optimal CI-BLP precoding matrix in a closed form. Similar to the case when the number of users is small, we show that a quadratic programming (QP) optimization on simplex can be constructed. We also design a low-complexity algorithm based on the alternating direction method of multipliers (ADMM) framework, which can efficiently solve large-scale QP problems. We further analyze the convergence and complexity of the proposed algorithm. Numerical results validate our analysis and the optimality of the proposed algorithm, and further show that the proposed algorithm offers a flexible performance-complexity tradeoff by limiting the maximum number of iterations, which motivates the use of CI-BLP in practical wireless systems.