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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Abstract

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 Creators	ORCiD
Shafivulla, Sayyed	UNSPECIFIED
Patel, Aaqib	UNSPECIFIED
Khan, Mohammed Zafar Ali	UNSPECIFIED

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://raiithold.iith.ac.in/id/eprint/8338