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Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment

We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopte...

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Published in:EURASIP journal on wireless communications and networking 2018-09, Vol.2018 (1), p.1-12
Main Authors: Liu, Juan, Dai, Jianxin, Wang, Jiangzhou, Yin, Xiaohui, Jiang, Zhifang, Wang, Jinyuan
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Dai, Jianxin
Wang, Jiangzhou
Yin, Xiaohui
Jiang, Zhifang
Wang, Jinyuan
description We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopted and imperfect channel state information (CSI) is assumed. In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems.
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In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. 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All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1186/s13638-018-1242-y</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-5735-4000</orcidid><oa>free_for_read</oa></addata></record>
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subjects Achievable rates
Antennas
Communication channels
Communications Engineering
Digital to analog conversion
Digital to analog converters
Engineering
Error analysis
Full-duplex
Imperfect CSI
Information Systems Applications (incl.Internet)
Interference
Low-resolution ADCs/DACs
Massive MIMO
Mean square errors
Measurement
MIMO (control systems)
Networks
Noise
Scaling laws
Signal,Image and Speech Processing
State (computer science)
Ultra-Reliable-and-Available Low-Latency Communications for 5G/B5G-enabled IoT
title Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment
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