Uplink Performance of Cell-Free Massive MIMO With Multi-Antenna Users Over Jointly-Correlated Rayleigh Fading Channels
In this paper, we investigate a cell-free massive MIMO system with both access points (APs) and user equipments (UEs) equipped with multiple antennas over jointly-correlated Rayleigh fading channels. We study four uplink implementations, from fully centralized processing to fully distributed process...
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Veröffentlicht in: | IEEE transactions on wireless communications 2022-09, Vol.21 (9), p.7391-7406 |
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description | In this paper, we investigate a cell-free massive MIMO system with both access points (APs) and user equipments (UEs) equipped with multiple antennas over jointly-correlated Rayleigh fading channels. We study four uplink implementations, from fully centralized processing to fully distributed processing, and derive their achievable spectral efficiency (SE) expressions with minimum mean-squared error successive interference cancellation (MMSE-SIC) detectors and arbitrary combining schemes. Furthermore, the global and local MMSE combining schemes are derived based on full and local channel state information (CSI) obtained under pilot contamination, which can maximize the achievable SE for the fully centralized and distributed implementation, respectively. We study a two-layer decoding implementation with an arbitrary combining scheme in the first layer and optimal large-scale fading decoding (LSFD) in the second layer. Besides, we compute novel closed-form SE expressions for the two-layer decoding implementation with maximum ratio (MR) combining. In the numerical results, we compare the SE performance for different implementation levels, combining schemes, and channel models. It is important to note that increasing the number of antennas per UE may degrade the SE performance. |
doi_str_mv | 10.1109/TWC.2022.3158353 |
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We study four uplink implementations, from fully centralized processing to fully distributed processing, and derive their achievable spectral efficiency (SE) expressions with minimum mean-squared error successive interference cancellation (MMSE-SIC) detectors and arbitrary combining schemes. Furthermore, the global and local MMSE combining schemes are derived based on full and local channel state information (CSI) obtained under pilot contamination, which can maximize the achievable SE for the fully centralized and distributed implementation, respectively. We study a two-layer decoding implementation with an arbitrary combining scheme in the first layer and optimal large-scale fading decoding (LSFD) in the second layer. Besides, we compute novel closed-form SE expressions for the two-layer decoding implementation with maximum ratio (MR) combining. In the numerical results, we compare the SE performance for different implementation levels, combining schemes, and channel models. It is important to note that increasing the number of antennas per UE may degrade the SE performance.</description><identifier>ISSN: 1536-1276</identifier><identifier>EISSN: 1558-2248</identifier><identifier>DOI: 10.1109/TWC.2022.3158353</identifier><identifier>CODEN: ITWCAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Antennas ; Cell-free massive MIMO ; Central Processing Unit ; Channel models ; Channels ; Codes ; Correlation ; Couplings ; Decoding ; Distributed processing ; Fading ; MIMO communication ; MMSE processing ; spectral efficiency ; Uplinking ; Weichselberger model ; Wireless communication</subject><ispartof>IEEE transactions on wireless communications, 2022-09, Vol.21 (9), p.7391-7406</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-6e7f69dde43ba108f08372b6eecc1a2262240250183669aef9125fdd88d3499f3</citedby><cites>FETCH-LOGICAL-c291t-6e7f69dde43ba108f08372b6eecc1a2262240250183669aef9125fdd88d3499f3</cites><orcidid>0000-0003-2434-4329 ; 0000-0002-9307-2120 ; 0000-0001-6850-0595 ; 0000-0001-5745-7640</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9737367$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9737367$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wang, Zhe</creatorcontrib><creatorcontrib>Zhang, Jiayi</creatorcontrib><creatorcontrib>Ai, Bo</creatorcontrib><creatorcontrib>Yuen, Chau</creatorcontrib><creatorcontrib>Debbah, Merouane</creatorcontrib><title>Uplink Performance of Cell-Free Massive MIMO With Multi-Antenna Users Over Jointly-Correlated Rayleigh Fading Channels</title><title>IEEE transactions on wireless communications</title><addtitle>TWC</addtitle><description>In this paper, we investigate a cell-free massive MIMO system with both access points (APs) and user equipments (UEs) equipped with multiple antennas over jointly-correlated Rayleigh fading channels. We study four uplink implementations, from fully centralized processing to fully distributed processing, and derive their achievable spectral efficiency (SE) expressions with minimum mean-squared error successive interference cancellation (MMSE-SIC) detectors and arbitrary combining schemes. Furthermore, the global and local MMSE combining schemes are derived based on full and local channel state information (CSI) obtained under pilot contamination, which can maximize the achievable SE for the fully centralized and distributed implementation, respectively. We study a two-layer decoding implementation with an arbitrary combining scheme in the first layer and optimal large-scale fading decoding (LSFD) in the second layer. Besides, we compute novel closed-form SE expressions for the two-layer decoding implementation with maximum ratio (MR) combining. In the numerical results, we compare the SE performance for different implementation levels, combining schemes, and channel models. 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subjects | Antennas Cell-free massive MIMO Central Processing Unit Channel models Channels Codes Correlation Couplings Decoding Distributed processing Fading MIMO communication MMSE processing spectral efficiency Uplinking Weichselberger model Wireless communication |
title | Uplink Performance of Cell-Free Massive MIMO With Multi-Antenna Users Over Jointly-Correlated Rayleigh Fading Channels |
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