Optimal Quantized Multi-Cell MMSE Precoding With Low Resolution Data Converters

doi:10.1109/LCOMM.2024.3509916

Optimal Quantized Multi-Cell MMSE Precoding With Low Resolution Data Converters

2025-01-01

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Qurrat-Ul-Ain Nadeem *

DOI：10.1109/LCOMM.2024.3509916

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This work considers a multi-cell multi-user multiple-input multiple-output (MIMO) system that employs low resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) at each base station (BS) to limit the power consumption. Existing precoder designs for quantization-free systems are sub-optimal for such quantized systems, while the existing precoder designs for quantized systems consider single-cell settings and perfect channel state information (CSI). To address these gaps, we study the downlink linear precoder optimization problem in a cellular system under the distortions introduced by low resolution DACs based on a minimum mean square error (MMSE) approach, while accounting for imperfect CSI obtained in the uplink under distortions introduced by low resolution ADCs. The problem is analytically solved resulting in an optimal quantized multi-cell MMSE precoder that reduces both intra-cell and inter-cell interference under quantization errors, and yields better bit error rate performance than applying the existing conventional multi-cell and quantized single-cell linear precoders to a quantized multi-cell massive MIMO system.

Keyword:

Quantization (signal)

Radio frequency

Training

Signal resolution

Distortion

Channel estimation

Noise

Massive MIMO

Intercell interference

Precoding

Multi-cell massive multiple-input multiple-output

quantization

data converters linear precoding

Optimal Quantized Multi-Cell MMSE Precoding With Low Resolution Data Converters

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