Joint Interference Mitigation, Channel Estimation and Data Detection in OFDM Communications

In this paper, we investigate the orthogonal frequency division multiplexing (OFDM) system in the presence of impulsive noise (IN) and narrowband interference (NBI). To overcome the performance degradation caused by the IN and NBI, we develop a novel joint estimation scheme based on an iterative processing framework at the receiver, where the modules in this framework incorporate the NBI and IN estimation, channel estimation, and data decoding. In the receiver processing, the linear estimator is first employed to jointly obtain the minimum mean-square error (MMSE) estimates. Then the denoisers are used for further correction of the estimates. Concretely, we adopt a gridless variational line spectral estimation (VALSE) method to refine the estimate of NBI in the NBI denoiser. Furthermore, we exploit the sparsity of IN in the time domain for accurate estimation in the IN denoiser. After channel estimation, the valid data is forwarded to the soft demodulator for data decoding. All the modules are operated within a turbo iteration framework until the algorithm convergence. Simulation results validate the superiority and robustness of the proposed method.