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Blind Carrier Frequency Offset Estimation for MIMO-OFDM Systems Based on the Banded Structure of Covariance Matrices for Constant Modulus Signals
Author(s) -
Liu Yang,
Hang Zhang,
Yang Cai,
Hua Yang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2870278
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper addresses the problem of blind carrier frequency offset (CFO) estimation for multi-input-multi-output orthogonal frequency division multiplexing systems. Benefiting from the banded structure of the circulant channel matrix from each transmitting antenna to each receiving antenna, the covariance matrices formulated by circular shifts of received signals also possess the banded structure in the absence of CFO for constant modulus signals. Thus, the cost function can be constructed by minimizing the elements outside the band and a closed-form CFO estimation algorithm is proposed. Since the channel length has an effect on the proposed estimator and channels with high delay spreads may deteriorate the estimation performance, an improved version of the proposed algorithm is investigated under the assumption that the channel remains constant within two consecutive OFDM symbols which is often the case. Experimental results demonstrate that the proposed algorithm shows better performance than the conventional CFO estimation schemes in frequency-selective fading channels and the improved version of the proposed algorithm can further optimize the estimation performance under long channel length conditions.

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