General Recursive Least Square Algorithm for Distributed Detection in Massive MIMO
In this paper, a general recursive least square (GRLS) detection algorithm is proposed for the uplink of distributed massive multiple-input multiple-output (MIMO) to alleviate the bottlenecks in both computational complexity and data bandwidth for interconnection. Different from the existing recursi...
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          | Published in | IEEE transactions on vehicular technology Vol. 73; no. 8; pp. 12137 - 12142 | 
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| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        New York
          IEEE
    
        01.08.2024
     The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0018-9545 1939-9359  | 
| DOI | 10.1109/TVT.2024.3370611 | 
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| Abstract | In this paper, a general recursive least square (GRLS) detection algorithm is proposed for the uplink of distributed massive multiple-input multiple-output (MIMO) to alleviate the bottlenecks in both computational complexity and data bandwidth for interconnection. Different from the existing recursive least square (RLS) detection algorithm which only supports a single antenna in each distributed unit (DU), the proposed GRLS allows for multiple antennas in each DU, rendering it adaptable to a variety of practical scenarios. Moreover, among the total <inline-formula><tex-math notation="LaTeX">C</tex-math></inline-formula> DUs and with an integer parameter <inline-formula><tex-math notation="LaTeX">C_{0}</tex-math></inline-formula>, the computational complexity of <inline-formula><tex-math notation="LaTeX">C-C_{0}</tex-math></inline-formula> DUs in GRLS can be significantly reduced by leveraging the channel hardening property. Through analysis, we demonstrate that the convergence of the GRLS algorithm is guaranteed if <inline-formula><tex-math notation="LaTeX">C_{0} \geq \lfloor {(\sqrt{{{B}}/{2}}+\sqrt{K})^{2}}/{B} \rfloor</tex-math></inline-formula> holds, where <inline-formula><tex-math notation="LaTeX">K</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">B</tex-math></inline-formula> denote the numbers of antennas at the user side and each DU, respectively. Furthermore, based on the daisy-chain architecture, the proposed GRLS algorithm also enjoys excellent scalability, which can be easily extended with extra DUs for further improvement. Finally, the detection complexity and data bandwidth analysis are also provided to unveil the superiority of GRLS compared to other distributed detection schemes for massive MIMO. | 
    
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| AbstractList | In this paper, a general recursive least square (GRLS) detection algorithm is proposed for the uplink of distributed massive multiple-input multiple-output (MIMO) to alleviate the bottlenecks in both computational complexity and data bandwidth for interconnection. Different from the existing recursive least square (RLS) detection algorithm which only supports a single antenna in each distributed unit (DU), the proposed GRLS allows for multiple antennas in each DU, rendering it adaptable to a variety of practical scenarios. Moreover, among the total [Formula Omitted] DUs and with an integer parameter [Formula Omitted], the computational complexity of [Formula Omitted] DUs in GRLS can be significantly reduced by leveraging the channel hardening property. Through analysis, we demonstrate that the convergence of the GRLS algorithm is guaranteed if [Formula Omitted] holds, where [Formula Omitted] and [Formula Omitted] denote the numbers of antennas at the user side and each DU, respectively. Furthermore, based on the daisy-chain architecture, the proposed GRLS algorithm also enjoys excellent scalability, which can be easily extended with extra DUs for further improvement. Finally, the detection complexity and data bandwidth analysis are also provided to unveil the superiority of GRLS compared to other distributed detection schemes for massive MIMO. In this paper, a general recursive least square (GRLS) detection algorithm is proposed for the uplink of distributed massive multiple-input multiple-output (MIMO) to alleviate the bottlenecks in both computational complexity and data bandwidth for interconnection. Different from the existing recursive least square (RLS) detection algorithm which only supports a single antenna in each distributed unit (DU), the proposed GRLS allows for multiple antennas in each DU, rendering it adaptable to a variety of practical scenarios. Moreover, among the total <inline-formula><tex-math notation="LaTeX">C</tex-math></inline-formula> DUs and with an integer parameter <inline-formula><tex-math notation="LaTeX">C_{0}</tex-math></inline-formula>, the computational complexity of <inline-formula><tex-math notation="LaTeX">C-C_{0}</tex-math></inline-formula> DUs in GRLS can be significantly reduced by leveraging the channel hardening property. Through analysis, we demonstrate that the convergence of the GRLS algorithm is guaranteed if <inline-formula><tex-math notation="LaTeX">C_{0} \geq \lfloor {(\sqrt{{{B}}/{2}}+\sqrt{K})^{2}}/{B} \rfloor</tex-math></inline-formula> holds, where <inline-formula><tex-math notation="LaTeX">K</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">B</tex-math></inline-formula> denote the numbers of antennas at the user side and each DU, respectively. Furthermore, based on the daisy-chain architecture, the proposed GRLS algorithm also enjoys excellent scalability, which can be easily extended with extra DUs for further improvement. Finally, the detection complexity and data bandwidth analysis are also provided to unveil the superiority of GRLS compared to other distributed detection schemes for massive MIMO.  | 
    
| Author | Ma, Cong Ng, Derrick Wing Kwan Wang, Zheng Chen, Qiqiang Dai, Xiaoming  | 
    
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| SubjectTerms | Algorithms Antenna arrays Antennas Bandwidth Bandwidths Complexity Complexity theory Computer architecture Daisy-chain decentralized signal detection Detection algorithms distributed MIMO detection Least squares Massive MIMO MIMO communication RLS  | 
    
| Title | General Recursive Least Square Algorithm for Distributed Detection in Massive MIMO | 
    
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