Reduced complexity signal detection and channel estimation for iterative MIMO-OFDM systems

Licai Fang

Reduced complexity signal detection and channel estimation for iterative MIMO-OFDM systems

Licai Fang

Research output: Thesis › Doctoral Thesis

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Abstract

Multi-Input Multi-Output (MIMO) is a key technology in broadband wireless communications. Conventional MIMO detection and channel estimation algorithms require a matrix inversion with cubic complexity, which is a major challenge for practical implementation. In this thesis, we have proposed several approximation methods to reduce the complexity to a quadratic level. The proposed methods are particularly useful for massive MIMO systems. In addition, an interpolation based method is proposed to reduce the number of matrix inversion required for data detection of massive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	The University of Western Australia
Supervisors/Advisors	Huang, David, Supervisor Guo, Qinghua, Supervisor
Award date	11 Jan 2017
Publication status	Unpublished - 2016

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THESIS - DOCTOR OF PHILOSOPHY - FANG Licai - 2016
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title = "Reduced complexity signal detection and channel estimation for iterative MIMO-OFDM systems",

abstract = "Multi-Input Multi-Output (MIMO) is a key technology in broadband wireless communications. Conventional MIMO detection and channel estimation algorithms require a matrix inversion with cubic complexity, which is a major challenge for practical implementation. In this thesis, we have proposed several approximation methods to reduce the complexity to a quadratic level. The proposed methods are particularly useful for massive MIMO systems. In addition, an interpolation based method is proposed to reduce the number of matrix inversion required for data detection of massive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems.",

keywords = "Detection, Channel estimation, Matrix inversion, Massive MIMO, Interpolation, Neumann series expansion, MIMO-OFDM, MMSE",

author = "Licai Fang",

year = "2016",

language = "English",

school = "The University of Western Australia",

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TY - BOOK

T1 - Reduced complexity signal detection and channel estimation for iterative MIMO-OFDM systems

AU - Fang, Licai

PY - 2016

Y1 - 2016

N2 - Multi-Input Multi-Output (MIMO) is a key technology in broadband wireless communications. Conventional MIMO detection and channel estimation algorithms require a matrix inversion with cubic complexity, which is a major challenge for practical implementation. In this thesis, we have proposed several approximation methods to reduce the complexity to a quadratic level. The proposed methods are particularly useful for massive MIMO systems. In addition, an interpolation based method is proposed to reduce the number of matrix inversion required for data detection of massive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems.

AB - Multi-Input Multi-Output (MIMO) is a key technology in broadband wireless communications. Conventional MIMO detection and channel estimation algorithms require a matrix inversion with cubic complexity, which is a major challenge for practical implementation. In this thesis, we have proposed several approximation methods to reduce the complexity to a quadratic level. The proposed methods are particularly useful for massive MIMO systems. In addition, an interpolation based method is proposed to reduce the number of matrix inversion required for data detection of massive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) systems.

KW - Detection

KW - Channel estimation

KW - Matrix inversion

KW - Massive MIMO

KW - Interpolation

KW - Neumann series expansion

KW - MIMO-OFDM

KW - MMSE

M3 - Doctoral Thesis

ER -

Reduced complexity signal detection and channel estimation for iterative MIMO-OFDM systems

Abstract

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