Accurate characterization and compensation of phase noise in OFDM receiver

Phase noise compensation for OFDM based wireless systems is a necessary task to be performed in order to achieve good performance using cheap components in the transceiver electronics. In this paper, we propose a decision-feedback-frequency-domain compensation method that utilizes Bayesian a priori information of the phase noise process. The a priori information is characterized in terms of the probability density functions of the spectral components of the phase noise process. We show in this work that, for reasonable ratios of phase noise 3dB bandwidth to OFDM subcarrier spacing, the density functions can be expressed as a sum of two independent random variables: The first variable follows a Gaussian distribution while the second variable has a distribution which is a weighted sum of gamma distributions. With this prior knowledge of the probability density functions, we derive the minimum mean square error estimator for spectral components of phase noise which is then used for phase noise compensation.