Massive MIMO Precoding and Spectral Shaping with Low Resolution Phase-only DACs and Active Constellation Extension

TL;DR

This paper introduces a novel precoding and spectral shaping method for massive MIMO systems using low-resolution phase-only DACs, employing advanced algorithms and theoretical analysis to improve detection and spectral efficiency.

Contribution

It develops a joint nonlinear precoding and pulse shaping technique with active constellation extension, solved via a modified GAMP algorithm, and provides theoretical performance analysis for low-resolution DAC systems.

Findings

Performance comparable between MSE and SER approaches.

Good accuracy of analytical predictions at medium SNR.

Significant improvements over linear methods in detection and spectral efficiency.

Abstract

Nonlinear precoding and pulse shaping are jointly considered in multi-user massive multiple-input multiple-output (MIMO) systems with low-resolution D/A-converters (DACs) in terms of algorithmic approach as well as large system performance. Two design criteria are investigated: the mean {squared} error (MSE) with active constellation extension (ACE) and the symbol error rate (SER). Both formulations are solved based on a modified version of the generalized approximate message passing (GAMP) algorithm. Furthermore, theoretical performance results are derived based on the state evolution analysis of the GAMP algorithm. The MSE based technique is extended to jointly perform over-the-air (OTA) spectral shaping and precoding for frequency-selective channels, in which the spectral performance is characterized at the transmitter and at the receiver. Simulation and analytical results demonstrate that the MSE based approach yields the same performance as the SER based formulation in terms of uncoded SER. The analytical results provide good performance predictions up to medium SNR. Substantial improvements in detection, as well as spectral performance, are obtained from the proposed combined pulse shaping and precoding approach compared to standard linear methods.