DFT-Based Channel Estimation with Iterative Denoising for OFDM-IM System

In this paper, we propose an improved iterative denoising channel estimation algorithm based on the conventional discrete Fourier transform (DFT) algorithm. The improved algorithm constantly iterates to find the useful taps of channels within the cyclic prefix (CP) and eliminates the noise within the CP. We apply this novel algorithm to orthogonal frequency division multiplexing with index modulation (OFDM-IM) system. Furthermore, the performance of bit error rate (BER) and mean square error (MSE) in the OFDM-IM system using this novel algorithm is theoretically analyzed under the condition of known channel estimation error. In the meanwhile, the performance of MSE and BER in the OFDM-IM system are simulated and compared with the conventional DFT algorithm. The simulation results have shown that the theoretical analysis is in good agreement with the simulation results at high signal-to-noise ratio and the BER and MSE of the proposed algorithm are significantly better than the conventional DFT algorithm.