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Research on Signal Detection Algorithms and Circuit Structures in Large-scale MIMO Systems
- 1 Shandong University, Jinan City, Shandong Province, 250100, China
* Author to whom correspondence should be addressed.
Abstract
Large-scale Multiple-Input Multiple-Output (MIMO) systems are crucial for improving both the spectral efficiency and reliability of communication links. Additionally, they contribute to reducing the power consumption of base stations (BS), which is a significant concern in modern wireless networks. In this context, data detection plays an essential role, particularly in the uplink of large-scale MIMO systems. However, one of the major challenges lies in the substantial increase in computational complexity required for base stations to process the data efficiently in such systems. The conventional optimal detection techniques, such as ML detection, SD detection, MMSE detection, and ZF detection, are widely employed in MIMO systems. While these methods offer optimal performance in terms of detection accuracy, they suffer from extremely high computational demands, which can be impractical for real-time implementation in large-scale networks. Under the premise of approaching the performance of the optimal calculation methods, this paper analyzes three new algorithms with lower computational complexity, including iterative algorithms, matrix approximation algorithms, and K-Best algorithms. This paper conducts a detailed study on the advantages and disadvantages of the calculation methods and circuit structures of these algorithms.
Keywords
High-capacity MIMO detection, Iterative methods, Matrix approximation algorithms, K-Best algorithm
[1]. Wu, M., Yin, B., Vosoughi, A., et al. (2013). Approximate matrix inversion for high-throughput data detection in the large-scale MIMO uplink. 2013 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE. https://doi.org/10.1109/ISCAS.2013.6572301
[2]. Yin, B., Wu, M., Wang, G., et al. (2014). A 3.8Gb/s large-scale MIMO detector for 3GPP LTE-Advanced. IEEE International Conference on Acoustics. IEEE. https://doi.org/10.1109/ICASSP.2014.6854328
[3]. Wang, F., Zhang, C., Yang, J., et al. (2015). Efficient matrix inversion architecture for linear detection in high-capacity MIMO systems. IEEE. https://doi.org/10.1109/ICDSP.2015.7251869
[4]. Wu, Z., Zhang, C., Xue, Y., et al. (2016). Efficient architecture for soft-output high-capacity MIMO detection with Gauss-Seidel method. 2016 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE. https://doi.org/10.1109/ISCAS.2016.7538940
[5]. Yin, B., Wu, M., Cavallaro, J. R., et al. (2015). VLSI design of large-scale soft-output MIMO detection using conjugate gradients. IEEE. https://doi.org/10.1109/ISCAS.2015.7168929
[6]. Zhang, P., Liu, L., Peng, G., et al. (2016). Large-scale MIMO detection design and FPGA implementations using SOR method. IEEE. https://doi.org/10.1109/ICCSN.2016.7586650
[7]. Ji, Y., Wu, Z., Shen, Y., et al. (2018). A low-complexity high-capacity MIMO detection algorithm based on matrix partition. IEEE. https://doi.org/10.1109/SiPS.2018.8598436
[8]. Zhang, Y., Jing, S., Zhang, Z., et al. (2019). Efficient belief propagation detection based on channel hardening for high-capacity MIMO. IEEE. https://doi.org/10.1109/ICASSP.2019.8682557
[9]. He, J. J., & Fan, C. P. (2015). Design and VLSI implementation of novel pre-screening and simplified sorting based K-best detection for MIMO systems. IEEE. https://doi.org/10.1109/VLSI-DAT.2015.7114511.
Cite this article
Wang,D. (2025). Research on Signal Detection Algorithms and Circuit Structures in Large-scale MIMO Systems. Applied and Computational Engineering,141,70-80.
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 Mechatronics and Smart Systems
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