Semi-blind channel identification and equalization in OFDM: An expectation-maximization approach

Tareq Y. Al-Naffouri; Ahmad Bahai; Arogyaswami Paulraj

Semi-blind channel identification and equalization in OFDM: An expectation-maximization approach

Tareq Y. Al-Naffouri^*, Ahmad Bahai, Arogyaswami Paulraj

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

This work proposes an expectation-maximization approach to channel identification and equalization in OFDM. The algorithm exploits the natural constraints imposed by the channel (sparsity, maximum delay spread, and a priori statistical information) and those imposed by the transmitter (pilots, cyclic prefix, and the finite alphabet constraint). These constraints are used to reduce the number of pilots needed for channel and data recovery and also to perform this task within one packet.

Original language	English (US)
Pages (from-to)	13-17
Number of pages	5
Journal	IEEE Vehicular Technology Conference
Volume	56
Issue number	1
State	Published - 2002
Externally published	Yes

ASJC Scopus subject areas

Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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title = "Semi-blind channel identification and equalization in OFDM: An expectation-maximization approach",

abstract = "This work proposes an expectation-maximization approach to channel identification and equalization in OFDM. The algorithm exploits the natural constraints imposed by the channel (sparsity, maximum delay spread, and a priori statistical information) and those imposed by the transmitter (pilots, cyclic prefix, and the finite alphabet constraint). These constraints are used to reduce the number of pilots needed for channel and data recovery and also to perform this task within one packet.",

author = "Al-Naffouri, {Tareq Y.} and Ahmad Bahai and Arogyaswami Paulraj",

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AU - Bahai, Ahmad

AU - Paulraj, Arogyaswami

PY - 2002

Y1 - 2002

N2 - This work proposes an expectation-maximization approach to channel identification and equalization in OFDM. The algorithm exploits the natural constraints imposed by the channel (sparsity, maximum delay spread, and a priori statistical information) and those imposed by the transmitter (pilots, cyclic prefix, and the finite alphabet constraint). These constraints are used to reduce the number of pilots needed for channel and data recovery and also to perform this task within one packet.

AB - This work proposes an expectation-maximization approach to channel identification and equalization in OFDM. The algorithm exploits the natural constraints imposed by the channel (sparsity, maximum delay spread, and a priori statistical information) and those imposed by the transmitter (pilots, cyclic prefix, and the finite alphabet constraint). These constraints are used to reduce the number of pilots needed for channel and data recovery and also to perform this task within one packet.

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M3 - Article

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JO - IEEE Vehicular Technology Conference

JF - IEEE Vehicular Technology Conference

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IS - 1

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Semi-blind channel identification and equalization in OFDM: An expectation-maximization approach

Abstract

ASJC Scopus subject areas

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