Generalized Sparse-Aware Minimum Mean Square Error Detector for Large-Scale MU-MIMO Systems with Higher-Order QAM Modulation Schemes | IEEE Conference Publication | IEEE Xplore

Generalized Sparse-Aware Minimum Mean Square Error Detector for Large-Scale MU-MIMO Systems with Higher-Order QAM Modulation Schemes


Abstract:

This paper considers an uplink multiuser multiple-input-multiple-output (MU-MIMO) system. In this system, we have presented a sparse-aware minimum-mean-square-error (SA-M...Show More

Abstract:

This paper considers an uplink multiuser multiple-input-multiple-output (MU-MIMO) system. In this system, we have presented a sparse-aware minimum-mean-square-error (SA-MMSE) detector which improves an underlying linear detector using the sparsity of a residual error vector (difference from the transmit vector and the detected one by the linear detector). Despite its attractive performance, the conventional SA-MMSE detector is only available for 4-QAM systems. In this paper, we generalize the SA-MMSE detector for a higher-order modulation system in a non-trivial method. This is referred to as generalized SA-MMSE (GSA-MMSE) detector. The key idea of the proposed detector is to exploit the hierarchical structure of a residual error vector. To be specific, the residual error vector can be decomposed into orthogonal sub-error vectors and, leveraging the orthogonality, the sub-error vectors can be decoded using the corresponding SA-MMSE detector in a successive fashion. Via simulation results, we demonstrate that the GSA-MMSE detector significantly outperforms the conventional linear detectors with a comparable complexity.
Date of Conference: 20-24 May 2018
Date Added to IEEE Xplore: 30 July 2018
ISBN Information:
Electronic ISSN: 1938-1883
Conference Location: Kansas City, MO, USA

References

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