Applied and Computational Engineering
- The Open Access Proceedings Series for Conferences
Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
Series Vol. 6 , 14 June 2023
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Access | Article
Improved SSOR-based signal detector by using based on gauss-seidel method for large-scale MIMO systems
* Author to whom correspondence should be addressed.
Abstract
As the core technology in large-scale MIMO system, the reliability of signal detection has an important impact on the whole system. Traditional linear detectors, such as the zero-forcing (ZF), often involve very complex matrix inverse calculations when the number of antennas in large-scale MIMO systems is too large. In this paper, we first introduce the traditional signal detector based on SSOR method, the iterative operation is used to replace the complex matrix inverse calculation, thus reducing the computational complexity. Then, the Gauss-Seidel method is proposed to calculate the initial iteration value, and the simulation results show that the bit error rate (BER) performance of the improved SSOR method is greatly improved.
Keywords
signal detector, low complexity, large-scale MIMO systems, Gauss-Seidel(GS), symmetric successive over-relaxation(SSOR)
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
- ISBN (Print)
- 978-1-915371-59-1
- ISBN (Online)
- 978-1-915371-60-7
- Published Date
- 14 June 2023
- Series
- Applied and Computational Engineering
- ISSN (Print)
- 2755-2721
- ISSN (Online)
- 2755-273X
- DOI
- 10.54254/2755-2721/6/20230304
- Copyright
- 14 June 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited