TY - GEN
T1 - Quantized MIMO
T2 - 2022 IEEE International Symposium on Information Theory, ISIT 2022
AU - Khalili, Abbas
AU - Erkip, Elza
AU - Rangan, Sundeep
N1 - Funding Information:
The work supported in part by NSF grants 1952180, 1925079, 1564142, 1547332, SRC, and the industrial affiliates of NYU WIRELESS.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Millimeter wave systems suffer from high power consumption and are constrained to use low resolution quantizers - digital to analog and analog to digital converters (DACs and ADCs). However, low resolution quantization leads to reduced data rate and increased out-of-band emission noise. In this paper, a multiple-input multiple-output (MIMO) system with linear transceivers using low resolution DACs and ADCs is considered. An information-theoretic analysis of the system to model the effect of quantization on spectrospatial power distribution and capacity of the system is provided. It is shown that the impact of quantization can be accurately described via a linear model with additive independent Gaussian noise. This model in turn leads to simple and intuitive expressions for spectrospatial power distribution of the transmitter and a lower bound on the achievable rate of the system. The derived model is validated through simulations and numerical evaluations, where it is shown to accurately predict both spectral and spatial power distributions.
AB - Millimeter wave systems suffer from high power consumption and are constrained to use low resolution quantizers - digital to analog and analog to digital converters (DACs and ADCs). However, low resolution quantization leads to reduced data rate and increased out-of-band emission noise. In this paper, a multiple-input multiple-output (MIMO) system with linear transceivers using low resolution DACs and ADCs is considered. An information-theoretic analysis of the system to model the effect of quantization on spectrospatial power distribution and capacity of the system is provided. It is shown that the impact of quantization can be accurately described via a linear model with additive independent Gaussian noise. This model in turn leads to simple and intuitive expressions for spectrospatial power distribution of the transmitter and a lower bound on the achievable rate of the system. The derived model is validated through simulations and numerical evaluations, where it is shown to accurately predict both spectral and spatial power distributions.
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U2 - 10.1109/ISIT50566.2022.9834605
DO - 10.1109/ISIT50566.2022.9834605
M3 - Conference contribution
AN - SCOPUS:85136266387
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2303
EP - 2308
BT - 2022 IEEE International Symposium on Information Theory, ISIT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 June 2022 through 1 July 2022
ER -