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

Liu, Juan, Dai, Jianxin, Wang, Jiangzhou, Yin, Xiaohui, Jiang, Zhifang, Wang, Jinyuan (2018) Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment. EURASIP Journal on Wireless Communications and Networking, 2018 . Article Number 222. ISSN 1687-1472. E-ISSN 1687-1499. (doi:10.1186/s13638-018-1242-y) (KAR id:69326)

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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.

Item Type: Article
DOI/Identification number: 10.1186/s13638-018-1242-y
Uncontrolled keywords: Full-duplex, Massive MIMO, Low-resolution ADCs/DACs, Imperfect CSI, Achievable rates
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Jiangzhou Wang
Date Deposited: 01 Oct 2018 12:01 UTC
Last Modified: 16 Feb 2021 13:58 UTC
Resource URI: (The current URI for this page, for reference purposes)
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