The Studyof Carrier Frequency Offset Estimation Algorithm For OFDM Systems

OFDM, multi-carrier transmission solution, has been widely utilized in high speed wireless data transmission systems such as wireless local area network (WLAN) due to its fairly strong anti- multipath delay capability and quite high utilization efficiency for frequency spectrum. It is also been regarded as the core technology for the fourth generation mobile communication technology. While its sensitivity to a frequency offset. How to eliminate the problem is a main task of the research of OFDM.In this paper, the characteristic of wireless channel, the basic principles and the core technologies firstly are introduced. The effect of carrier frequency offset and offset of timing symbol is proposed. Secondly, the paper focuses on and analyzes the data aided and non data-aided OFDM frequency offset estimation algorithms. To the data-aided method, the Moose, Sch&Cox and M&M methods of the frequency offset estimation are mostly researched. From simulation and analysis of complex algorithms, it is found: the estimated range of Moose frequency offset estimation algorithm attain half of a sub-carrier interval while a sub-carrier can be achieved for the Sch&Cox frequency offset estimation algorithm and L / 2sub-carriers interval for M&M frequency offset estimation algorithm. For each of these methods, the length of their own training symbols is related to the estimated range closely. Thus, for the algorithm which has shorter training symbols has bigger estimated range and lower estimation accuracy. And the reason of this is the decline of the system transmission efficiency. At the same time, the non-data aided frequency offset estimation algorithm solves this problem by other means. Such algorithms theses refer to maximum likelihood estimation algorithm which is cyclic prefix-based, virtual-carrier-based frequency offset estimation algorithm and a new blind frequency offset estimation algorithm. And for the three algorithms referred above, the first one has smallest complexity and least estimate range, while the middle one has largest estimate range, highest accuracy and biggest complexity, for in this kind of algorithms, some sub-carriers cannot be distributed freely. Compared to the second, the last one has smaller complexity and higher accuracy for its sub-carriers can be distributed freely. Generally speaking, non-data aided algorithm own better bandwidth efficiency and higher complexity.