Joint Carrier Frequency Offset and Fast Time-Varying Channel Estimation for MIMO-OFDM Systems

In this paper, a novel pilot-aided algorithm is developed for multiple-input-multiple-output (MIMO) orthogonal frequency-division-multiplexing (OFDM) systems operating in a fast time-varying environment. The algorithm has been designed to work with both the parametric L -path channel model (with kno...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2011-03, Vol.60 (3), p.955-965
Main Authors: Simon, Eric Pierre, Ros, Laurent, Hijazi, Hussein, Jin Fang, Gaillot, Davy Paul, Berbineau, Marion
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Approximation
Capacitors. Resistors. Filters
Carrier frequencies
Channel estimation
Channels
Computer Science
Covariance matrix
Delay
Detection, estimation, filtering, equalization, prediction
Electrical engineering. Electrical power engineering
Engineering Sciences
Equations
Exact sciences and technology
High speed
Information, signal and communications theory
Kalman filtering
Kalman filters
Mathematical model
Multiplexing
Niobium
OFDM
Offsets
Orthogonal Frequency Division Multiplexing
Signal and communications theory
Signal and Image processing
Signal, noise
Studies
Symbols
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
time-varying channels
Transmission and modulation (techniques and equipments)
Various equipment and components
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Summary:In this paper, a novel pilot-aided algorithm is developed for multiple-input-multiple-output (MIMO) orthogonal frequency-division-multiplexing (OFDM) systems operating in a fast time-varying environment. The algorithm has been designed to work with both the parametric L -path channel model (with known path delays) and the equivalent discrete-time channel model to jointly estimate the multipath Rayleigh channel complex amplitude (CA) and the carrier frequency offset (CFO). Each CA time variation within one OFDM symbol is approximated by a basis expansion model representation. An autoregressive model is built for the parameters to be estimated. The algorithm performs estimation using extended Kalman filtering. The channel matrix is thus easily computed, and the data symbol is estimated without intercarrier interference (ICI) when the channel matrix is QR-decomposed. It is shown that our algorithm is far more robust to high speed than the conventional algorithm, and the performance approaches that of the ideal case for which the channel response and CFO are known.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2011.2104970