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Detection for Uplink Massive MIMO System: A Survey

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Advanced Hybrid Information Processing (ADHIP 2019)

Abstract

In this paper, we make a compressive survey for the research on detection in uplink Massive multiple input and multiple output (MIMO) system. As one key technology in Massive MIMO system, which is also one primary subject for the fifth generation wireless communications, this research is significant to be developed. As a result of large scaled antennas, the channel gain matrix in Massive MIMO system is asymptotic diagonal orthogonal, and it is an non-deterministic polynomial hard problem to obtain the optimum bits error rate (BER) performance during finite polynomial complexity time. The traditional detection algorithms for MIMO system are not efficient any more due to poor BER performance or high computational complexity. The exiting detection algorithms for Massive MIMO system are able to solve this issue. However, there are still crucial problems for them, including employing the deep learning technology for detection in Massive MIMO system, and not work for the millimeter wave Massive MIMO system in the strong spatial correlation environment even exiting keyhole effect, which is not rich scattering, as well as application in Hetnets wireless communications, and etc. Therefore, the research on detection for uplink Massive MIMO system is still in its early stage, there are lots of significant and urgent issues to overcome in the future.

This work was sponsored by National Natural Science Foundation of China: No. 61871155.

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Correspondence to Weixiao Meng .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, L., Meng, W. (2019). Detection for Uplink Massive MIMO System: A Survey. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-36402-1_31

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  • DOI: https://doi.org/10.1007/978-3-030-36402-1_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36401-4

  • Online ISBN: 978-3-030-36402-1

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