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Multi-user data detection in massive MIMO with 1-bit ADCS

Radbord, Amin; Atzeni, Italo; Tölli, Antti (2023-05-05)

 
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https://doi.org/10.1109/ICASSP49357.2023.10096485

Radbord, Amin
Atzeni, Italo
Tölli, Antti
Institute of Electrical and Electronics Engineers
05.05.2023

A. Radbord, I. Atzeni and A. Tölli, "Multi-User Data Detection in Massive MIMO with 1-Bit ADCS," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10096485

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doi:https://doi.org/10.1109/icassp49357.2023.10096485
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Abstract

We provide new analytical results on the uplink data detection in massive multiple-input multiple-output systems with 1-bit analog-to-digital converters. The statistical properties of the soft-estimated symbols (i.e., after linear combining and prior to the data detection process) have been previously characterized only for a single user equipment (UE) and uncorrelated Rayleigh fading. In this paper, we consider a multi-UE setting with correlated Rayleigh fading, where the soft-estimated symbols are obtained by means of maximum ratio combining based on imperfectly estimated channels. We derive a closed-form expression of the expected value of the soft-estimated symbols, which allows to understand the impact of the specific data symbols transmitted by the interfering UEs. Building on this result, we design efficient data detection strategies based on the minimum distance criterion, which are compared in terms of symbol error rate and complexity.

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