Estimation of Wiener phase noise by the autocorrelation of the ICI weighting function in OFDM systems

Performance degradation due to Wiener phase noise, which causes both common phase error (CPE) and inter-carrier interference (ICI), is a crucial challenge to the implementation of OFDM systems. In this paper, we theoretically employ the Lorentzian model to investigate the autocorrelation function of the ICI weighting function, which is the discrete Fourier transform of the exponential phase noise process. This autocorrelation function can be shown to be the kernel of the covariance of the ICI. Based on this kernel, a pilot-aided decision-directed CPE estimator is proposed according to maximum-likelihood criterion. Different from conventional maximum likelihood approach which ideally assumes the ICI observed on different subcarriers to be independent identically distributed, we systematically derive the covariances among carriers and practically utilize them to enhance the estimation. Finally, three conventional CPE estimators are compared with the proposed scheme by computer simulation, the numerical results illustrate the effectiveness of the proposed algorithm