A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO

L. Fang; Lu Xu; Qinghua Guo; David Huang; S. Nordholm

doi:10.1109/ICASSP.2015.7178509

A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO

L. Fang, Lu Xu, Qinghua Guo, David Huang, S. Nordholm

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

11 Citations (Scopus)

Abstract

© 2015 IEEE. In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model based MMSE detection algorithm to implement MMSE-PIC with low complexity. This algorithm, which can detect a length-Nr received data block by a single Hermitian matrix (sized Nt × Nt) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas Nt from each end terminal is much less than the number of receive antennas Nr in the Base Station. Then we derive a new method to calculate the matrix inversion by a linear combination of two matrices, which reduces the complexity from O(Nt 3) to O(Nt 2). At last, in order to improve the system performance for the first pass when there is no a priori information available, a self-iteration method is proposed and thus a system performance gain of 1dB to 2dB is achieved at the cost of modest complexity increase.

Original language	English
Title of host publication	IEEE International Conference on Acoustics, Speech and Signal Processing
Place of Publication	USA
Publisher	Wiley-IEEE Press
Pages	2939-2943
Volume	2015-August
ISBN (Print)	9781467369978
DOIs	https://doi.org/10.1109/ICASSP.2015.7178509
Publication status	Published - 2015
Event	2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015 - Brisbane, Australia Duration: 19 Apr 2015 → 24 Apr 2015

Conference

Conference	2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015
Abbreviated title	ICASSP 2015
Country/Territory	Australia
City	Brisbane
Period	19/04/15 → 24/04/15

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10.1109/ICASSP.2015.7178509

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@inproceedings{a2e979d72bae4b669a19f8221edcd2fc,

title = "A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO",

abstract = "{\textcopyright} 2015 IEEE. In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model based MMSE detection algorithm to implement MMSE-PIC with low complexity. This algorithm, which can detect a length-Nr received data block by a single Hermitian matrix (sized Nt × Nt) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas Nt from each end terminal is much less than the number of receive antennas Nr in the Base Station. Then we derive a new method to calculate the matrix inversion by a linear combination of two matrices, which reduces the complexity from O(Nt 3) to O(Nt 2). At last, in order to improve the system performance for the first pass when there is no a priori information available, a self-iteration method is proposed and thus a system performance gain of 1dB to 2dB is achieved at the cost of modest complexity increase.",

author = "L. Fang and Lu Xu and Qinghua Guo and David Huang and S. Nordholm",

year = "2015",

doi = "10.1109/ICASSP.2015.7178509",

language = "English",

isbn = "9781467369978",

volume = "2015-August",

pages = "2939--2943",

booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing",

publisher = "Wiley-IEEE Press",

note = "2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, ICASSP 2015 ; Conference date: 19-04-2015 Through 24-04-2015",

}

Fang, L, Xu, L, Guo, Q , Huang, D & Nordholm, S 2015, A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO. in IEEE International Conference on Acoustics, Speech and Signal Processing. vol. 2015-August, Wiley-IEEE Press, USA, pp. 2939-2943, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, Brisbane, Australia, 19/04/15. https://doi.org/10.1109/ICASSP.2015.7178509

TY - GEN

T1 - A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO

AU - Fang, L.

AU - Xu, Lu

AU - Guo, Qinghua

AU - Huang, David

AU - Nordholm, S.

PY - 2015

Y1 - 2015

N2 - © 2015 IEEE. In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model based MMSE detection algorithm to implement MMSE-PIC with low complexity. This algorithm, which can detect a length-Nr received data block by a single Hermitian matrix (sized Nt × Nt) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas Nt from each end terminal is much less than the number of receive antennas Nr in the Base Station. Then we derive a new method to calculate the matrix inversion by a linear combination of two matrices, which reduces the complexity from O(Nt 3) to O(Nt 2). At last, in order to improve the system performance for the first pass when there is no a priori information available, a self-iteration method is proposed and thus a system performance gain of 1dB to 2dB is achieved at the cost of modest complexity increase.

AB - © 2015 IEEE. In MIMO applications, the minimum mean square error parallel interference cancellation (MMSE-PIC) based Soft-Input Soft-Output (SISO) detector has been widely adopted because of its low complexity and good bit error rate (BER) performance. In this paper, we firstly propose to use a Gaussian model based MMSE detection algorithm to implement MMSE-PIC with low complexity. This algorithm, which can detect a length-Nr received data block by a single Hermitian matrix (sized Nt × Nt) inversion, is especially preferable in Massive MIMO up-link applications where the number of transmit antennas Nt from each end terminal is much less than the number of receive antennas Nr in the Base Station. Then we derive a new method to calculate the matrix inversion by a linear combination of two matrices, which reduces the complexity from O(Nt 3) to O(Nt 2). At last, in order to improve the system performance for the first pass when there is no a priori information available, a self-iteration method is proposed and thus a system performance gain of 1dB to 2dB is achieved at the cost of modest complexity increase.

U2 - 10.1109/ICASSP.2015.7178509

DO - 10.1109/ICASSP.2015.7178509

M3 - Conference paper

SN - 9781467369978

VL - 2015-August

SP - 2939

EP - 2943

BT - IEEE International Conference on Acoustics, Speech and Signal Processing

PB - Wiley-IEEE Press

CY - USA

T2 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015

Y2 - 19 April 2015 through 24 April 2015

ER -

A low complexity iterative soft-decision feedback MMSE-PIC detection algorithm for massive MIMO

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