Research Article A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2009 Article ID821819 9 pages doi 2009 821819 Research Article A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems Michele Morelli Marco Moretti and Giuseppe Imbarlina Dipartimento di Ingegneria dell Informazione University of Pisa Via Caruso 16 56122 Pisa Italy Correspondence should be addressed to Marco Moretti Received 27 June 2008 Revised 3 October 2008 Accepted 25 December 2008 Recommended by Mounir Ghogho This paper deals with training-assisted carrier frequency offset CFO estimation in multiple-input multiple-output MIMO orthogonal frequency-division multiplexing OFDM systems. The exact maximum likelihood ML solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way the fractional CFO is efficiently computed through a correlation-based approach while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load. Copyright 2009 Michele Morelli et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction Orthogonal frequency-division multiplexing OFDM is an attractive modulation technique for wideband wireless communications due to its robustness against multipath distortions and flexibility in allocating power and data rate over distinct subchannels. For these reasons it is adopted in a variety of applications including digital audio .
