Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System
For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it invol...
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| Format: | Article |
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MDPI AG
2020-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/6/1564 |
| _version_ | 1818038800242180096 |
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| author | Hebiao Wu Bin Shen Shufeng Zhao Peng Gong |
| author_facet | Hebiao Wu Bin Shen Shufeng Zhao Peng Gong |
| author_sort | Hebiao Wu |
| collection | DOAJ |
| description | For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations. |
| first_indexed | 2024-12-10T07:48:30Z |
| format | Article |
| id | doaj.art-8967e4d7916040b5b3dbf6d8d521012f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T07:48:30Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8967e4d7916040b5b3dbf6d8d521012f2022-12-22T01:57:07ZengMDPI AGSensors1424-82202020-03-01206156410.3390/s20061564s20061564Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO SystemHebiao Wu0Bin Shen1Shufeng Zhao2Peng Gong3Chongqing Key Laboratory of Mobile Communications Technology, School of Communication and Information Engineering (SCIE), Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, ChinaChongqing Key Laboratory of Mobile Communications Technology, School of Communication and Information Engineering (SCIE), Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, ChinaChongqing Key Laboratory of Mobile Communications Technology, School of Communication and Information Engineering (SCIE), Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, ChinaNational Key Laboratory of Mechatronical Engineering and Control, School of Mechatronical Engineering, Beijing Institute of Technology (BIT), Beijing 100081, ChinaFor multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.https://www.mdpi.com/1424-8220/20/6/1564massive mimolow-complexitykaczmarz iterationrelaxation parametersoft output |
| spellingShingle | Hebiao Wu Bin Shen Shufeng Zhao Peng Gong Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System Sensors massive mimo low-complexity kaczmarz iteration relaxation parameter soft output |
| title | Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System |
| title_full | Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System |
| title_fullStr | Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System |
| title_full_unstemmed | Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System |
| title_short | Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System |
| title_sort | low complexity soft output signal detection based on improved kaczmarz iteration algorithm for uplink massive mimo system |
| topic | massive mimo low-complexity kaczmarz iteration relaxation parameter soft output |
| url | https://www.mdpi.com/1424-8220/20/6/1564 |
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