Compensation of Phase Noise in Massive-MIMO Uplink Communications Based on Expectation-Maximization Algorithm

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Main Authors: Tarable, Alberto, Escribano, Francisco J.
Format: Preprint
Published: 2022
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author Tarable, Alberto
Escribano, Francisco J.
author_facet Tarable, Alberto
Escribano, Francisco J.
contents Phase noise (PN) is a major disturbance in MIMO systems, where the contribution of different oscillators at the transmitter and the receiver side may degrade the overall performance and offset the gains offered by MIMO techniques. This is even more crucial in the case of massive MIMO, since the number of PN sources may increase considerably. In this work, we propose an iterative receiver based on the application of the expectation-maximization algorithm. We consider a massive MIMO framework with a general association of oscillators to antennas, and include other channel disturbances like imperfect channel state information and Rician block fading. At each receiver iteration, given the information on the transmitted symbols, steepest descent is used to estimate the PN samples, with an optimized adaptive step size and a threshold-based stopping rule. The results obtained for several test cases show how the bit error rate and mean square error can benefit from the proposed phase-detection algorithm, even to the point of reaching the same performance as in the case where no PN is present, offering better results than a state-of-the-art alternative. Further analysis of the results allow to draw some useful trade-offs respecting final performance and consumption of resources.
format Preprint
id arxiv_https___arxiv_org_abs_2207_08213
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Compensation of Phase Noise in Massive-MIMO Uplink Communications Based on Expectation-Maximization Algorithm
Tarable, Alberto
Escribano, Francisco J.
Information Theory
Signal Processing
Phase noise (PN) is a major disturbance in MIMO systems, where the contribution of different oscillators at the transmitter and the receiver side may degrade the overall performance and offset the gains offered by MIMO techniques. This is even more crucial in the case of massive MIMO, since the number of PN sources may increase considerably. In this work, we propose an iterative receiver based on the application of the expectation-maximization algorithm. We consider a massive MIMO framework with a general association of oscillators to antennas, and include other channel disturbances like imperfect channel state information and Rician block fading. At each receiver iteration, given the information on the transmitted symbols, steepest descent is used to estimate the PN samples, with an optimized adaptive step size and a threshold-based stopping rule. The results obtained for several test cases show how the bit error rate and mean square error can benefit from the proposed phase-detection algorithm, even to the point of reaching the same performance as in the case where no PN is present, offering better results than a state-of-the-art alternative. Further analysis of the results allow to draw some useful trade-offs respecting final performance and consumption of resources.
title Compensation of Phase Noise in Massive-MIMO Uplink Communications Based on Expectation-Maximization Algorithm
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2207.08213