Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems

TL;DR

This paper introduces an efficient method for designing quantized constant envelope precoding in massive MIMO systems, reducing hardware costs and energy consumption while handling the challenges of discrete signal constraints.

Contribution

The paper develops a novel penalty-based relaxation and an alternating optimization algorithm for QCE precoding with PSK modulation in massive MIMO systems.

Findings

Proposed approach outperforms existing algorithms in simulations.

The penalty model effectively relaxes discrete constraints.

AO algorithm achieves efficient closed-form updates.

Abstract

Quantized constant envelope (QCE) precoding, a new transmission scheme that only discrete QCE transmit signals are allowed at each antenna, has gained growing research interests due to its ability of reducing the hardware cost and the energy consumption of massive multiple-input multiple-output (MIMO) systems. However, the discrete nature of QCE transmit signals greatly complicates the precoding design. In this paper, we consider the QCE precoding problem for a massive MIMO system with phase shift keying (PSK) modulation and develop an efficient approach for solving the constructive interference (CI) based problem formulation. Our approach is based on a custom-designed (continuous) penalty model that is equivalent to the original discrete problem. Specifically, the penalty model relaxes the discrete QCE constraint and penalizes it in the objective with a negative $\ell_2$-norm term, which leads to a non-smooth non-convex optimization problem. To tackle it, we resort to our recently proposed alternating optimization (AO) algorithm. We show that the AO algorithm admits closed-form updates at each iteration when applied to our problem and thus can be efficiently implemented. Simulation results demonstrate the superiority of the proposed approach over the existing algorithms.