Efficient optimal joint channel estimation and data detection for massive MIMO systems

Haider Ali Jasim Alshamary; Weiyu Xu

doi:10.1109/isit.2016.7541424

Efficient optimal joint channel estimation and data detection for massive MIMO systems

Haider Ali Jasim Alshamary, Weiyu Xu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.

Original language	English (US)
Title of host publication	2016 IEEE International Symposium on Information Theory (ISIT)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	875-879
Number of pages	5
ISBN (Print)	9781509018062
DOIs	https://doi.org/10.1109/isit.2016.7541424
State	Published - Aug 15 2016
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Xu's work is supported by Simons Foundation, KAUST grant, and NIH 1 RO 1 EB020665-0 I.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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10.1109/isit.2016.7541424

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@inproceedings{b173f6d9f54f4ab59d16dc07704a4c9f,

title = "Efficient optimal joint channel estimation and data detection for massive MIMO systems",

abstract = "In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.",

author = "Alshamary, {Haider Ali Jasim} and Weiyu Xu",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: Xu's work is supported by Simons Foundation, KAUST grant, and NIH 1 RO 1 EB020665-0 I. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2016",

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day = "15",

doi = "10.1109/isit.2016.7541424",

language = "English (US)",

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AU - Alshamary, Haider Ali Jasim

AU - Xu, Weiyu

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: Xu's work is supported by Simons Foundation, KAUST grant, and NIH 1 RO 1 EB020665-0 I. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2016/8/15

Y1 - 2016/8/15

N2 - In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.

AB - In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.

UR - http://hdl.handle.net/10754/623538

UR - http://ieeexplore.ieee.org/document/7541424/

UR - http://www.scopus.com/inward/record.url?scp=84985939925&partnerID=8YFLogxK

U2 - 10.1109/isit.2016.7541424

DO - 10.1109/isit.2016.7541424

M3 - Conference contribution

SN - 9781509018062

SP - 875

EP - 879

BT - 2016 IEEE International Symposium on Information Theory (ISIT)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Efficient optimal joint channel estimation and data detection for massive MIMO systems

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