Low-Complexity Blind Symbol Timing Offset Estimation in OFDM Systems
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Low-Complexity Blind Symbol Timing Offset Estimation in OFDM Systems Tiejun Lv School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China Email: [email protected]
Jie Chen Division of Engineering, Brown University, Providence, RI 02912, USA Email: jie [email protected]
Hua Li Division of Engineering, Brown University, Providence, RI 02912, USA Email: hua li [email protected] Received 19 February 2004; Revised 4 October 2004; Recommended for Publication by Marc Moonen A low-complexity blind timing algorithm is proposed to estimate timing offset in OFDM systems when multiple symbols are received (the timing offset estimation is independent of the frequency offset one). Though the maximum-likelihood estimation (MLE) using two or three symbols is good in offset estimation, its performance can be significantly improved by including more symbols in our previous work. However, timing offset estimation requires exhaustive search and a priori knowledge of the probability distribution of the received data. The method we propose utilizes the second-order statistics embedded in a cyclic prefix. An information vector (IVR) with the same length as the cyclic prefix is formed based on an autocorrelation matrix (AM). The modulus of elements in the IVR is first quantized based on a threshold that is defined by the variance of OFDM symbols. The timing offset is then estimated based on the binary sequence of the IVR. Because the exhaustive search used in the MLE can be avoided, computational complexity is significantly reduced. In practice, the proposed scheme can be used as a coarse synchronization estimation that can rapidly provide a rough and contractible estimation range, which serves as the basis for a fine estimation like the MLE. The proposed estimator will be proved theoretically to be asymptotically unbiased and mean-squared consistent. Simulations and comparisons will be provided in the paper to illustrate the advantages of our design. Keywords and phrases: symbol timing offset estimation, maximum-likelihood estimation, frequency offset estimation, blind estimation in OFDM communications.
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INTRODUCTION
With the advances of wireless technologies, wireless networking has become ubiquitous due to the growing demand for pervasive mobile applications. It is projected that one-fifth of the world’s population will access the Internet by mobile phone by the end of 2004. The convergence of computing, communication, and media will allow the users to communicate with each other and access any content at any time, anywhere. Future wireless networks will support services such as high-speed access, telecommuting, interactive media, video conferencing, real-time Internet gaming, e-business ecosystems, smart homes, automated highways, and disaster relief. Yet we still have to overcome many technical challenges in order to make this vision of a wireless future into reality. For instance, the performance of 3G wireless systems is not
sufficient to meet the needs of future high-performance multimed
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