BP-algorithm based on factor diagram about massive MIMO system

Research Article
Open access

BP-algorithm based on factor diagram about massive MIMO system

Jiaqian Ling 1*
  • 1 Southeast University, Nanjing, Jiangsu Province, China    
  • *corresponding author 213202717@seu.edu.cn
Published on 14 June 2023 | https://doi.org/10.54254/2755-2721/6/20230776
ACE Vol.6
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-915371-59-1
ISBN (Online): 978-1-915371-60-7

Abstract

In order to meet the growing demand for high-speed mobile data business, there has been a constant concern for the fifth-generation mobile communication system. 5G large-scale Multiple Input Multiple Output (MIMO) technique has significantly improved the system spectral efficiency and energy efficiency. In order to study the signal detection method under the large-scale MIMO system and improve the existing methods, the article describes the background of signal detection. It introduces the development of the belief propagation (BP) algorithm. There are four main BP algorithms: Original-BP algorithm, RDF-BP algorithm, EBRDF-BP algorithm, and GAI-BP algorithm. One algorithm is proposed based on these fundamental algorithms to improve the whole detection performance. This algorithm reduces complexity while not increasing the error rate too much, which means that it has certain feasibility and practicability.

Keywords:

MIMO, factor graph, belief propagation (BP), signal detection

Ling,J. (2023). BP-algorithm based on factor diagram about massive MIMO system. Applied and Computational Engineering,6,154-161.
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References

[1]. C. -X. Wang et al., “Cellular architecture and key technologies for 5G wireless communication networks,” in IEEE Communications Magazine, vol. 52, no. 2, pp. 122-130, February 2014, doi: 10.1109/MCOM.2014.6736752.

[2]. Boccardi, F., Heath, R., Lozano, A., Marzetta, T. and Popovski, P., 2014. Five disruptive technology directions for 5G. IEEE Communications Magazine, 52(2), pp.74-80.

[3]. Marzetta, T., 2010. Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas. IEEE Transactions on Wireless Communications, 9(11), pp.3590-3600.

[4]. Rusek, F., Persson, D., Buon Kiong Lau, Larsson, E., Marzetta, T. and Tufvesson, F., 2013. Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays. IEEE Signal Processing Magazine, 30(1), pp.40-60.

[5]. J. Hoydis, S. ten Brink and M. Debbah, “Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do This paper Need?,” in IEEE Journal on Selected Areas in Communications, vol. 31, no. 2, pp. 160-171, February 2013, doi: 10. 1109/JSAC. 2013. 130205.

[6]. Foschini, G., 2002. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Technical Journal, 1(2), pp.41-59.

[7]. Jun Hu and Duman, T., 2008. Graph-based detection algorithms for layered space-time architectures. IEEE Journal on Selected Areas in Communications, 26(2), pp.269-280.

[8]. P. Som, T. Datta, A. Chockalingam and B. S. Rajan, Improved large-MIMO detection based on damped belief propagation, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo), 2010, pp. 1-5, doi: 10. 1109/ITWKSPS. 2010. 5503188.

[9]. F. Long, T. Lv, R. Cao and H. Gao, Single edge based belief propagation algorithms for MIMO detection, 34th IEEE Sarnoff Symposium, 2011, pp. 1-5, doi: 10. 1109/SARNOF. 2011. 5876456.

[10]. Yang, J., Song, W., Zhang, S., You, X. and Zhang, C., 2017. Low-Complexity Belief Propagation Detection for Correlated Large-Scale MIMO Systems. Journal of Signal Processing Systems, 90(4), pp.585-599.

[11]. Tan, X., Xu, W., Sun, K., Xu, Y., Be’ery, Y., You, X. and Zhang, C., 2020. Improving Massive MIMO Message Passing Detectors With Deep Neural Network. IEEE Transactions on Vehicular Technology, 69(2), pp.1267-1280.

[12]. B. Hassibi, “An efficient square-root algorithm for BLAST,” 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2000, pp. II737-II740 vol.2, doi: 10.1109/ICASSP.2000.859065.

Cite this article

Ling,J. (2023). BP-algorithm based on factor diagram about massive MIMO system. Applied and Computational Engineering,6,154-161.

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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About volume

Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

ISBN：978-1-915371-59-1(Print) / 978-1-915371-60-7(Online)
Editor：Omer Burak Istanbullu
Conference website: http://www.confspml.org
Conference date: 25 February 2023
Series: Applied and Computational Engineering
Volume number: Vol.6
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. C. -X. Wang et al., “Cellular architecture and key technologies for 5G wireless communication networks,” in IEEE Communications Magazine, vol. 52, no. 2, pp. 122-130, February 2014, doi: 10.1109/MCOM.2014.6736752.

[2]. Boccardi, F., Heath, R., Lozano, A., Marzetta, T. and Popovski, P., 2014. Five disruptive technology directions for 5G. IEEE Communications Magazine, 52(2), pp.74-80.

[3]. Marzetta, T., 2010. Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas. IEEE Transactions on Wireless Communications, 9(11), pp.3590-3600.

[4]. Rusek, F., Persson, D., Buon Kiong Lau, Larsson, E., Marzetta, T. and Tufvesson, F., 2013. Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays. IEEE Signal Processing Magazine, 30(1), pp.40-60.

[5]. J. Hoydis, S. ten Brink and M. Debbah, “Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do This paper Need?,” in IEEE Journal on Selected Areas in Communications, vol. 31, no. 2, pp. 160-171, February 2013, doi: 10. 1109/JSAC. 2013. 130205.

[6]. Foschini, G., 2002. Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas. Bell Labs Technical Journal, 1(2), pp.41-59.

[7]. Jun Hu and Duman, T., 2008. Graph-based detection algorithms for layered space-time architectures. IEEE Journal on Selected Areas in Communications, 26(2), pp.269-280.

[8]. P. Som, T. Datta, A. Chockalingam and B. S. Rajan, Improved large-MIMO detection based on damped belief propagation, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo), 2010, pp. 1-5, doi: 10. 1109/ITWKSPS. 2010. 5503188.

[9]. F. Long, T. Lv, R. Cao and H. Gao, Single edge based belief propagation algorithms for MIMO detection, 34th IEEE Sarnoff Symposium, 2011, pp. 1-5, doi: 10. 1109/SARNOF. 2011. 5876456.

[10]. Yang, J., Song, W., Zhang, S., You, X. and Zhang, C., 2017. Low-Complexity Belief Propagation Detection for Correlated Large-Scale MIMO Systems. Journal of Signal Processing Systems, 90(4), pp.585-599.

[11]. Tan, X., Xu, W., Sun, K., Xu, Y., Be’ery, Y., You, X. and Zhang, C., 2020. Improving Massive MIMO Message Passing Detectors With Deep Neural Network. IEEE Transactions on Vehicular Technology, 69(2), pp.1267-1280.

[12]. B. Hassibi, “An efficient square-root algorithm for BLAST,” 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2000, pp. II737-II740 vol.2, doi: 10.1109/ICASSP.2000.859065.

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