Improved Gauss–Seidel detector for large‐scale MIMO systems
Abstract Large‐scale multiple‐input multiple‐output (LS‐MIMO) is one of the promising technologies beyond the 5G cellular system in which large antenna arrays at the base station (BS) improve the system capacity and energy‐efficiency. However, the large number of antennas at the BS makes it challeng...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-03-01
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| Series: | IET Communications |
| Online Access: | https://doi.org/10.1049/cmu2.12331 |
| _version_ | 1818288348718956544 |
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| author | Imran A. Khoso Xiaofei Zhang Abdul Hayee Shaikh Fahad Sahito Zaheer Ahmed Dayo |
| author_facet | Imran A. Khoso Xiaofei Zhang Abdul Hayee Shaikh Fahad Sahito Zaheer Ahmed Dayo |
| author_sort | Imran A. Khoso |
| collection | DOAJ |
| description | Abstract Large‐scale multiple‐input multiple‐output (LS‐MIMO) is one of the promising technologies beyond the 5G cellular system in which large antenna arrays at the base station (BS) improve the system capacity and energy‐efficiency. However, the large number of antennas at the BS makes it challenging to design low‐complexity high‐performance data detectors. Thus, a number of iterative detection methods, such as Gauss–Seidel and conjugate gradient, are introduced to achieve complexity‐performance tradeoff. However, their performance deteriorates for the systems with small BS‐to‐user antenna ratio or for the channels that exhibit correlation. This paper proposes a new efficient iterative detection algorithm based on the improved Gauss–Seidel iteration to address this problem. The proposed method performs one conjugate gradient iteration that enables better performance with less number of iterations. A new hybrid iteration is introduced and a low‐complexity initial estimation is utilised to enhance detection accuracy while reducing the complexity further. In addition, a novel preconditioning technique is proposed to maintain the benefits of the proposed detector in correlated MIMO channels. It is mathematically demonstrate that the proposed detector achieves low approximated error. Theoretical analysis and numerical results show that the proposed algorithm provides a faster convergence rate compared to conventional methods. |
| first_indexed | 2024-12-13T01:54:57Z |
| format | Article |
| id | doaj.art-1c09c2865d674cedb019c456ce503c24 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-12-13T01:54:57Z |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-1c09c2865d674cedb019c456ce503c242022-12-22T00:03:24ZengWileyIET Communications1751-86281751-86362022-03-0116429130210.1049/cmu2.12331Improved Gauss–Seidel detector for large‐scale MIMO systemsImran A. Khoso0Xiaofei Zhang1Abdul Hayee Shaikh2Fahad Sahito3Zaheer Ahmed Dayo4College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing People's Republic of ChinaCollege of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing People's Republic of ChinaCollege of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing People's Republic of ChinaCollege of Electronic and Communication Engineering Beijing University of Posts and Telecommunications Beijing People's Republic of ChinaCollege of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing People's Republic of ChinaAbstract Large‐scale multiple‐input multiple‐output (LS‐MIMO) is one of the promising technologies beyond the 5G cellular system in which large antenna arrays at the base station (BS) improve the system capacity and energy‐efficiency. However, the large number of antennas at the BS makes it challenging to design low‐complexity high‐performance data detectors. Thus, a number of iterative detection methods, such as Gauss–Seidel and conjugate gradient, are introduced to achieve complexity‐performance tradeoff. However, their performance deteriorates for the systems with small BS‐to‐user antenna ratio or for the channels that exhibit correlation. This paper proposes a new efficient iterative detection algorithm based on the improved Gauss–Seidel iteration to address this problem. The proposed method performs one conjugate gradient iteration that enables better performance with less number of iterations. A new hybrid iteration is introduced and a low‐complexity initial estimation is utilised to enhance detection accuracy while reducing the complexity further. In addition, a novel preconditioning technique is proposed to maintain the benefits of the proposed detector in correlated MIMO channels. It is mathematically demonstrate that the proposed detector achieves low approximated error. Theoretical analysis and numerical results show that the proposed algorithm provides a faster convergence rate compared to conventional methods.https://doi.org/10.1049/cmu2.12331 |
| spellingShingle | Imran A. Khoso Xiaofei Zhang Abdul Hayee Shaikh Fahad Sahito Zaheer Ahmed Dayo Improved Gauss–Seidel detector for large‐scale MIMO systems IET Communications |
| title | Improved Gauss–Seidel detector for large‐scale MIMO systems |
| title_full | Improved Gauss–Seidel detector for large‐scale MIMO systems |
| title_fullStr | Improved Gauss–Seidel detector for large‐scale MIMO systems |
| title_full_unstemmed | Improved Gauss–Seidel detector for large‐scale MIMO systems |
| title_short | Improved Gauss–Seidel detector for large‐scale MIMO systems |
| title_sort | improved gauss seidel detector for large scale mimo systems |
| url | https://doi.org/10.1049/cmu2.12331 |
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