Study and Analysis of Carrier Frequency Offset (CFO) in OFDM

Abstract

A demand for high speed mobile wireless communications is quickly mounting. Wireless communication is the key part of research with growing demand of high data rate applications at a low cost. Orthogonal Frequency Division Multiplexing (OFDM) is a promising answer for this problem. It is a multi-carrier modulation and as well as a multiplexing technique proposed for 3G, 4G, LTE; a systems to support high data rate applications in a fading environment. There are many problems linked with the multicarrier transmission like phase variations, timing offset, large peak to average power ratio (PAPR), frequency offset etc. in which Carrier Frequency Offset (CFO) is one of the major issues. This frequency offset breaks the orthogonality among the sub-carriers and hence causes inter-carrier interference (ICI) in the OFDM symbol, which seriously degrades the overall system performance. In this thesis; we have studied and analyzed CFO upon signal to noise ratio (SNR), different techniques to estimate CFO and its effect in detailed for OFDM symbol. The estimation techniques cover both domains; time and frequency for OFDM system. The three types of CFO methods as: CP, Moose, and Classen are compared in MATLAB simulation. In Cyclic Prefix (CP) method, the CFO can be found from the phase angle of the product of CP and corresponding rear part of the OFDM symbol. In CFO estimation using Classen method, the CFO estimation range can be increased by reducing the distance between two blocks of samples for correlation. This was made possible using training symbol that are repetitive with shorter period. The principles of the eight different methods are reviewed; but among these, three methods has been compared in term of Mean Square Error (MSE) which is verified through MATLAB simulation. From simulation results, the Classen method has best performance and CP method has worst performance because of easy implementation and no loss of bandwidth efficiency. Although, Moose method has similar performance as Classen method in terms of MSE.