Particle filter for joint frequency offset and channel estimation in MIMO-OFDM systems

Abstract

A particle filter is proposed to perform joint estimation of the carrier frequency offset (CFO) and the channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) wireless communication systems. It marginalizes out the channel parameters from the sampling space in sequential importance sampling (SIS), and propagates them with the Kalman filter. Then the importance weights of the CFO particles are evaluated according to the imaginary part of the error between measurement and estimation. The varieties of particles are maintained by sequential importance resampling (SIR). Simulation results demonstrate this algorithm can estimate the CFO and the channel parameters with high accuracy. At the same time, some robustness is kept when the channel model has small variations.