Coordinated Per-Antenna Power Minimization for Multicell Massive MIMO Systems with Low-Resolution Data Converters
Yunseong Cho, Jinseok Choi, Brian L. Evans

TL;DR
This paper introduces a novel coordinated beamforming method for multicell massive MIMO systems with low-resolution converters, minimizing per-antenna power while ensuring signal quality, validated through simulations.
Contribution
It formulates a dual problem for power minimization in low-resolution massive MIMO systems, demonstrating strong duality and proposing an iterative algorithm for practical implementation.
Findings
Effective reduction in maximum antenna transmit power.
Improved peak-to-average-power ratio performance.
Validated algorithm through extensive simulations.
Abstract
A multicell-coordinated beamforming solution for massive multiple-input multiple-output orthogonal frequency-division multiplexing (OFDM) systems is presented when employing low-resolution data converters and per-antenna level constraints. For a more realistic deployment, we aim to find the downlink (DL) beamformer that minimizes the maximum power on transmit antenna array of each basestation under received signal quality constraints while minimizing per-antenna transmit power. We show that strong duality holds between the primal DL formulation and its manageable Lagrangian dual problem which can be interpreted as the virtual uplink (UL) problem with adjustable noise covariance matrices. For a fixed set of noise covariance matrices, we claim that the virtual UL solution is effectively used to compute the DL beamformer and noise covariance matrices can be subsequently updated with an…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Antenna Design and Optimization · Direction-of-Arrival Estimation Techniques
