Low Complexity Signal Detection for Massive-MIMO Systems

Shafivulla, Sayyed and Patel, Aaqib and Khan, Mohammed Zafar Ali (2020) Low Complexity Signal Detection for Massive-MIMO Systems. IEEE Wireless Communications Letters, 9 (9). pp. 1467-1470. ISSN 2162-2337

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Maximum likelihood detection is infeasible in uplink multiuser massive multiple-input and multiple-output (m-MIMO) systems due to the large dimension of the MIMO systems. Accordingly, suboptimal or near-optimal alternatives like linear minimum mean square error (LMMSE) detector and Zero Forcing (ZF) are used. However, the LMMSE and the ZF detectors need matrix inversion, which is computationally costly. We propose two detection schemes for massive MIMO, which compute an approximate inverse based on the Cayley-Hamilton theorem, and have quadratic complexity in the number of users. Simulation results exhibit the similarity of the BER performance of the proposed schemes to that of the ideal ZF or LMMSE.

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IITH Creators:
IITH CreatorsORCiD
Shafivulla, SayyedUNSPECIFIED
Khan, Mohammed Zafar AliUNSPECIFIED
Item Type: Article
Uncontrolled Keywords: Approximate inverse; Cayley-hamilton theorem; Detection scheme; Linear minimum mean square error(LMMSE); Matrix inversions; Maximum likelihood detection; Multiple input and multiple outputs; Quadratic complexity
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 15 Jul 2021 07:45
Last Modified: 15 Jul 2021 07:45
URI: http://raiith.iith.ac.in/id/eprint/8338
Publisher URL: http://doi.org/10.1109/LWC.2020.2994058
OA policy: https://v2.sherpa.ac.uk/id/publication/23590
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