An adaptive semi-blind algorithm for channel identification in OFDM

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

doi:10.1109/acssc.2001.987630

An adaptive semi-blind algorithm for channel identification in OFDM

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

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

OFDM is a convenient vehicle for high rate transmission. However, this requires an accurate estimation of the channel at the receiver side. This paper proposes an iterative/adaptive algorithm for semi-blind channel estimation. An initial channel estimate is obtained by relying on the artificial constraint of pilots. The algorithm subsequently switches to the blind mode powered by the natural constraints imposed by the sparsity of the channel and the redundant and finite alphabet nature of the data. It iterates between using the channel estimate to detect the data, and using the data estimate to further improve the channel estimate. The diagonal nature of the OFDM channel makes it possible to optimally detect the data with low complexity. The complexity of the algorithm is further reduced by performing channel estimation adaptively. The simulation results demonstrate the favorable behavior of the algorithm and the tradeoff that it provides between the number of pilots used and convergence speed.

Original language	English (US)
Pages (from-to)	921-925
Number of pages	5
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	2
DOIs	https://doi.org/10.1109/acssc.2001.987630
State	Published - 2001
Externally published	Yes
Event	35th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 4 2001 → Nov 7 2001

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

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10.1109/acssc.2001.987630

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title = "An adaptive semi-blind algorithm for channel identification in OFDM",

abstract = "OFDM is a convenient vehicle for high rate transmission. However, this requires an accurate estimation of the channel at the receiver side. This paper proposes an iterative/adaptive algorithm for semi-blind channel estimation. An initial channel estimate is obtained by relying on the artificial constraint of pilots. The algorithm subsequently switches to the blind mode powered by the natural constraints imposed by the sparsity of the channel and the redundant and finite alphabet nature of the data. It iterates between using the channel estimate to detect the data, and using the data estimate to further improve the channel estimate. The diagonal nature of the OFDM channel makes it possible to optimally detect the data with low complexity. The complexity of the algorithm is further reduced by performing channel estimation adaptively. The simulation results demonstrate the favorable behavior of the algorithm and the tradeoff that it provides between the number of pilots used and convergence speed.",

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

year = "2001",

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note = "35th Asilomar Conference on Signals, Systems and Computers ; Conference date: 04-11-2001 Through 07-11-2001",

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AU - Al-Naffouri, Tareq Y.

AU - Toumpakaris, Dimitrios

AU - Bahai, Ahmad

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PY - 2001

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N2 - OFDM is a convenient vehicle for high rate transmission. However, this requires an accurate estimation of the channel at the receiver side. This paper proposes an iterative/adaptive algorithm for semi-blind channel estimation. An initial channel estimate is obtained by relying on the artificial constraint of pilots. The algorithm subsequently switches to the blind mode powered by the natural constraints imposed by the sparsity of the channel and the redundant and finite alphabet nature of the data. It iterates between using the channel estimate to detect the data, and using the data estimate to further improve the channel estimate. The diagonal nature of the OFDM channel makes it possible to optimally detect the data with low complexity. The complexity of the algorithm is further reduced by performing channel estimation adaptively. The simulation results demonstrate the favorable behavior of the algorithm and the tradeoff that it provides between the number of pilots used and convergence speed.

AB - OFDM is a convenient vehicle for high rate transmission. However, this requires an accurate estimation of the channel at the receiver side. This paper proposes an iterative/adaptive algorithm for semi-blind channel estimation. An initial channel estimate is obtained by relying on the artificial constraint of pilots. The algorithm subsequently switches to the blind mode powered by the natural constraints imposed by the sparsity of the channel and the redundant and finite alphabet nature of the data. It iterates between using the channel estimate to detect the data, and using the data estimate to further improve the channel estimate. The diagonal nature of the OFDM channel makes it possible to optimally detect the data with low complexity. The complexity of the algorithm is further reduced by performing channel estimation adaptively. The simulation results demonstrate the favorable behavior of the algorithm and the tradeoff that it provides between the number of pilots used and convergence speed.

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An adaptive semi-blind algorithm for channel identification in OFDM

Abstract

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