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EM-based ML channel estimation in OFDM systems with phase distortion using RB-EKF | IEEE Conference Publication | IEEE Xplore

EM-based ML channel estimation in OFDM systems with phase distortion using RB-EKF


Abstract:

In this paper we address the joint estimation of the channel impulse response in orthogonal frequency division multiplexing systems with phase distortion, namely phase no...Show More

Abstract:

In this paper we address the joint estimation of the channel impulse response in orthogonal frequency division multiplexing systems with phase distortion, namely phase noise and carrier frequency offset, phase noise bandwidth and the additive noise variance. The estimation algorithm is based on an implementation of the Extended Kalman Filter within the general framework of the Expectation-Maximization algorithm. We focus on the partial training case, where the transmitted signal is not fully known. To tackle this problem, we utilize a Rao-Blackwellized Extended Kalman Filter. We also compare our results with another nonlinear filtering technique, namely Rao-Blackwellized Particle Filtering, applied to this joint estimation problem. The performance of the two filtering techniques considered in this paper is evaluated in terms of the mean square error of the channel estimates and the numerical complexity introduced by each of these techniques.
Date of Conference: 07-10 September 2014
Date Added to IEEE Xplore: 22 January 2015
Electronic ISBN:978-9860-3-3407-4

ISSN Information:

Conference Location: Sydney, NSW, Australia

References

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