Abstract
In this paper, we address the problem of OFDM channel estimation in the presence of phase noise (PHN) and carrier frequency offset (CFO). For OFDM systems, PHN and CFO cause two effects: the common phase error (CPE) and the intercarrier interference (ICI) which severely degrade the accuracy of the channel estimate. In literature, several algorithms have been proposed to solve this problem. Here, we propose the joint estimation of channel impulse response (CIR), CFO and PHN with no prior statistical knowledge of PHN and SNR. The proposed approach uses a training OFDM symbol to track and estimate these many unknowns in the time domain by particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and the hybrid importance function which encompasses the advantages of both the optimal and the prior importance functions. Simulation results are provided to illustrate the effectiveness of the proposed algorithm.
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