A Subspace-Based CFO Estimation Algorithm for General ICI Self-Cancellation Precoded OFDM Systems

This paper presents a carrier-frequency-offset (CFO) estimation algorithm for time-dispersive orthogonal frequency division multiplexing (OFDM) system using a general inter-carrier interference (ICI) self-cancellation scheme. This study uses the time shift invariant property in the precoded signal to estimate the CFO. To achieve this, the proposed algorithm first collects the highly correlated receive time samples into snapshot vectors. The snapshot vectors can be expressed in a form having a CFO-directed response structure, which enables the proposed approach to estimate the CFO by using the multiple signal classfication (MUSIC) algorithm in the time domian. This study also develops a time sample selection scheme to mitigate the noise enhancement caused in the equalization process before the MUSIC algorithm. As compared to conventional algorithms, in addition to having an estimation error approaching to the Cramer-Rao lower bound (CRLB), the proposed algorithm has an adjustable CFO estimation range linearly proportional to the order of the ICI self-cancellation scheme.