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HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels.

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Published

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HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels. / Ding, Z.; Ratnarajah, T.; Cowan, C.
In: IEEE Transactions on Signal Processing, Vol. 56, No. 1, 01.2008, p. 248-255.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Ding, Z, Ratnarajah, T & Cowan, C 2008, 'HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels.', IEEE Transactions on Signal Processing, vol. 56, no. 1, pp. 248-255. https://doi.org/10.1109/TSP.2007.908349

APA

Ding, Z., Ratnarajah, T., & Cowan, C. (2008). HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels. IEEE Transactions on Signal Processing, 56(1), 248-255. https://doi.org/10.1109/TSP.2007.908349

Vancouver

Ding Z, Ratnarajah T, Cowan C. HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels. IEEE Transactions on Signal Processing. 2008 Jan;56(1):248-255. doi: 10.1109/TSP.2007.908349

Author

Ding, Z. ; Ratnarajah, T. ; Cowan, C. / HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels. In: IEEE Transactions on Signal Processing. 2008 ; Vol. 56, No. 1. pp. 248-255.

Bibtex

@article{cfe221a40cb4490086999605c10df54a,
title = "HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels.",
abstract = "In this paper, we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training-based method with the same training information used and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.",
keywords = "DCS-publications-id, art-904, DCS-publications-credits, coding-fa, DCS-publications-personnel-id, 147",
author = "Z. Ding and T. Ratnarajah and C. Cowan",
year = "2008",
month = jan,
doi = "10.1109/TSP.2007.908349",
language = "English",
volume = "56",
pages = "248--255",
journal = "IEEE Transactions on Signal Processing",
issn = "1053-587X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels.

AU - Ding, Z.

AU - Ratnarajah, T.

AU - Cowan, C.

PY - 2008/1

Y1 - 2008/1

N2 - In this paper, we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training-based method with the same training information used and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.

AB - In this paper, we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training-based method with the same training information used and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.

KW - DCS-publications-id

KW - art-904

KW - DCS-publications-credits

KW - coding-fa

KW - DCS-publications-personnel-id

KW - 147

U2 - 10.1109/TSP.2007.908349

DO - 10.1109/TSP.2007.908349

M3 - Journal article

VL - 56

SP - 248

EP - 255

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

SN - 1053-587X

IS - 1

ER -