ML Estimation of Integer Frequency Offset in OFDM Systems

Carrier frequency offset (CFO) estimation in an OFDM system is usually divided into fractional frequency offset (FFO) estimation and integer frequency offset (IFO) estimation. The former is generally done in the time domain while the latter in the frequency domain. We propose a maximum likelihood estimation algorithm for IFO estimation which works in the time domain using two FFOs with different estimation ranges. After introducing the concepts of frequency offset diagram, solution subset and minimum distance, we reveal the close relationship between the minimum distance and the error rate of the ML estimation result. Our further analysis exhibits a performance-range tradeoff which is tunable by the choice of the greatest common divisor (GCD) of two integers.