Study and Analysis of Timing Offset Estimation Methods in OFDM Systems

Abstract

OFDM is a multi-carrier transmission technique. It converts the frequency selective fading channel into a collection of parallel flat fading sub-channels which simplifies the structure of a receiver. OFDM has been widely used in communication system and is the key technology of 4G in the field of mobile communication because of its excellent performance in overcoming multipath channel and narrow band interference. However, wireless environment causes ISI and ICI. Synchronization is one of the major problems that affect the system performance in OFDM system. We basically focus on symbol timing. Finding the symbol timing for OFDM means finding an estimate of where the symbol starts. OFDM requires timing synchronization to preserve the orthogonality. The receiver will obtain the timing information from the received OFDM signal, but the information obtained comprises of offsets as well as the estimation errors. Synchronization techniques consists of data aided and non-data aided. Data aided makes the use of additional data which consists of pilot and preamble. Non data aided make the use of correlation between the CP and the end of the Symbols. The correction of timing and frequency offset plays the significant role in OFDM system. Estimating the starting point of an OFDM system must be handled efficiently and effectively to reduce errors. In data aided technique, the most common synchronization technique is the Schmidl and Cox which has been followed by different researchers trying to get the better results based on this algorithm. Schmidl and Cox used a special structure having the two symbol preamble to estimate the timing offsets. They constructed the first training symbol with two identical halves but this technique shows the disadvantage in large plateau. To overcome these problems, Minn proposed a new training sequence consisting of four symbols which uses the concept of negative samples. Plateau uncertainty is removed. Park also modified the preamble taking the reference of Minn’s algorithm in order to increase the sharpness of peaks but still had some problem occurring of to many side lobes. The problem faced in park’s algorithm is removed by K. Shi and E. Serpedin algorithm but this algorithm also has the main problem on complexity which produces the better peak than that of Schmidl and Minn but not that of park. Many of the methods were investigated and analysed. We have proposed a new timing synchronization based on CP STO estimation technique and the training symbol based which helps in finding the performance of STO estimation. Correlation technique is affected when using CFO as well as the minimum difference is not affected when adding CFO when simulating.