Channel, phase noise, and frequency offset in OFDM systems: joint estimation, data detection, and hybrid Cramer-Rao lower bound
Article
Article Title | Channel, phase noise, and frequency offset in OFDM systems: joint estimation, data detection, and hybrid Cramer-Rao lower bound |
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ERA Journal ID | 4446 |
Article Category | Article |
Authors | Salim, Omar Hazim (Author), Nasir, Ali A. (Author), Mehrpouyan, Hani (Author), Xiang, Wei (Author), Durrani, Salman (Author) and Kennedy, Rodney A. (Author) |
Journal Title | IEEE Transactions on Communications |
Journal Citation | 62 (9), pp. 3311-3325 |
Number of Pages | 15 |
Year | 2014 |
Place of Publication | United States |
ISSN | 0090-6778 |
1558-0857 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TCOMM.2014.2345056 |
Web Address (URL) | https://ieeexplore.ieee.org/document/6868950 |
Abstract | Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramer-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance. |
Keywords | OFDM; channel estimation; phase noise; frequency offset; Bayesian; hybrid Cramer-Rao lower bound; Kalman filter; data detection |
ANZSRC Field of Research 2020 | 400607. Signal processing |
461301. Coding, information theory and compression | |
400608. Wireless communication systems and technologies (incl. microwave and millimetrewave) | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Institution of Origin | University of Southern Queensland |
Byline Affiliations | School of Mechanical and Electrical Engineering |
Australian National University | |
California State University Bakersfield, United States |
https://research.usq.edu.au/item/q2919/channel-phase-noise-and-frequency-offset-in-ofdm-systems-joint-estimation-data-detection-and-hybrid-cramer-rao-lower-bound
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