Distributed bayesian compressive sensing based blind carrier-frequency offset estimation for interleaved OFDMA uplink

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Conference Proceeding
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2013, pp. 801 - 806
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Carrier-frequency offset (CFO) estimation for orthogonal frequency-division multiplexing access (OFDMA) systems operating in multiuser uplink transmission is very challenging due to the presence of a multiple-parameter estimation problem. In this paper, we propose a novel blind CFO estimation method for interleaved OFDMA uplink based on distributed Bayesian compressive sensing (DBCS) theory. Considering the received signal structure, the new method first constructs a measurement matrix associated with a sparse signal matrix weight, which sets up the stage for the application of CS theory in tackling the original estimation problem. Then, the DBCS theory that exploits a common sparse profile of the sparse signal matrix weight is employed to distributively estimate a sparse hyperparameter vector, whose significant peaks are linked to the correct estimation of the multiple CFOs. Compared with the existing subspace theory based methods, the proposed scheme offers a significant enhancement in estimation accuracy, in specific in the low signal-to-noise ratio (SNR) region. The numerical results validate the effectiveness of the proposed scheme. © 2013 IEEE.
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