Efficient Massive MIMO Detection for M-QAM Symbols.

Entropy (Basel)

School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China.

Published: February 2023

Massive multiple-input multiple-output (MIMO) systems significantly outperform small-scale MIMO systems in terms of data rate, making them an enabling technology for next-generation wireless systems. However, the increased number of antennas increases the computational difficulty of data detection, necessitating more efficient detection techniques. This paper presents a detector based on joint deregularized and box-constrained dichotomous coordinate descent (BOXDCD) with iterations for rectangular m-ary quadrature amplitude modulation (M-QAM) symbols. Deregularization maximized the energy of the solution. With the box-constraint, the deregularization forces the solution to be close to the rectangular boundary set. The numerical results demonstrate that the proposed detector achieves a considerable performance gain compared to existing detection algorithms. The performance advantage increases with the system size and signal-to-noise ratio.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047872PMC
http://dx.doi.org/10.3390/e25030391DOI Listing

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Efficient Massive MIMO Detection for M-QAM Symbols.

Entropy (Basel)

February 2023

School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China.

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