Spatial Sigma-Delta Massive MIMO: Improved Channel Estimation and Achievable Rates

Shilpa Rao, Hessam Pirzadeh, Gonzalo Seco-Granados, A. Lee Swindlehurst

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Resumen

Spatial S sampling has recently been proposed to improve the performance of massive MIMO systems with low-resolution quantization for cases where the users are confined to a certain angular sector, or the array is spatially oversampled. We derive a linear minimum mean squared error (LMMSE) channel estimator for the S array based on an element-wise Bussgang decomposition that reformulates the nonlinear quantizer operation using an equivalent linear model plus quantization noise. Both the case of one- and two-bit quantization is considered. We then evaluate the achievable rate of the S system assuming that a linear receiver based on the LMMSE channel estimate is used to decode the data. Our numerical results demonstrate that S architecture is able to achieve superior channel estimates and sum spectral efficiency compared to conventional low-resolution quantized massive MIMO systems.

Idioma originalInglés
Título de la publicación alojadaConference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
EditoresMichael B. Matthews
Páginas379-383
Número de páginas5
ISBN (versión digital)9780738131269
DOI
EstadoPublicada - 1 nov 2020

Serie de la publicación

NombreConference Record - Asilomar Conference on Signals, Systems and Computers
Volumen2020-November
ISSN (versión impresa)1058-6393

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