A forward-backward kalman for the estimation of time-variant channels in OFDM

Tareq Y. Al-Naffouri; Arogyswami Paulraj

doi:10.1109/SPAWC.2005.1506224

A forward-backward kalman for the estimation of time-variant channels in OFDM

Tareq Y. Al-Naffouri^*, Arogyswami Paulraj

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

5 Scopus citations

Abstract

OFDM combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem- a structure induced by the data and channel constraints. These constraints include pilots, the cyclic prefix, and the finite alphabet constraints on the data, and sparsity, finite delay spread, and the statistical properties of the channel (frequency and time correlation). The algorithm boils down to a forward-backward (FB) Kalman filter. We also suggest a suboptimal modification that is able to track the channel and recover the data with no latency.

Original language	English (US)
Pages	670-674
Number of pages	5
DOIs	https://doi.org/10.1109/SPAWC.2005.1506224
State	Published - 2005
Externally published	Yes
Event	2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2005 - New York, NY, United States Duration: Jun 5 2005 → Jun 8 2005

Other

Other	2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2005
Country/Territory	United States
City	New York, NY
Period	06/5/05 → 06/8/05

ASJC Scopus subject areas

Signal Processing
General Engineering

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10.1109/SPAWC.2005.1506224

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title = "A forward-backward kalman for the estimation of time-variant channels in OFDM",

abstract = "OFDM combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem- a structure induced by the data and channel constraints. These constraints include pilots, the cyclic prefix, and the finite alphabet constraints on the data, and sparsity, finite delay spread, and the statistical properties of the channel (frequency and time correlation). The algorithm boils down to a forward-backward (FB) Kalman filter. We also suggest a suboptimal modification that is able to track the channel and recover the data with no latency.",

author = "Al-Naffouri, {Tareq Y.} and Arogyswami Paulraj",

year = "2005",

doi = "10.1109/SPAWC.2005.1506224",

language = "English (US)",

pages = "670--674",

note = "2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2005 ; Conference date: 05-06-2005 Through 08-06-2005",

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AU - Al-Naffouri, Tareq Y.

AU - Paulraj, Arogyswami

PY - 2005

Y1 - 2005

N2 - OFDM combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem- a structure induced by the data and channel constraints. These constraints include pilots, the cyclic prefix, and the finite alphabet constraints on the data, and sparsity, finite delay spread, and the statistical properties of the channel (frequency and time correlation). The algorithm boils down to a forward-backward (FB) Kalman filter. We also suggest a suboptimal modification that is able to track the channel and recover the data with no latency.

AB - OFDM combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem- a structure induced by the data and channel constraints. These constraints include pilots, the cyclic prefix, and the finite alphabet constraints on the data, and sparsity, finite delay spread, and the statistical properties of the channel (frequency and time correlation). The algorithm boils down to a forward-backward (FB) Kalman filter. We also suggest a suboptimal modification that is able to track the channel and recover the data with no latency.

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DO - 10.1109/SPAWC.2005.1506224

M3 - Paper

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T2 - 2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2005

Y2 - 5 June 2005 through 8 June 2005

ER -

A forward-backward kalman for the estimation of time-variant channels in OFDM

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