An Improved Channel Estimation Algorithm Based on DFT in OFDM System

Abstract

In orthogonal frequency division multiplexing (OFDM) systems, the channel estimation algorithm based on discrete Fourier transform (DFT) overcomes the shortcoming of the least square (LS) channel estimation algorithm which does not consider noise in the process of channel estimation, and its performance is better than the LS channel estimation algorithm, and its computational complexity is low. However, the DFT algorithm does not take into account the processing of noise within the cyclic prefix, which affects the performance of the algorithm. In view of the shortcomings of this algorithm, this paper proposes an improved DFT channel estimation algorithm. First, the median of channel response amplitude modes of all samples in the range of cyclic prefix is taken, then the median of channel response amplitude modes of all samples outside the range of cyclic prefix is taken, and the sum of the median values of the two is used as the threshold, which preserves the data larger than the threshold and sets the data smaller than the threshold to zero. In this way, the noise within the cyclic prefix is filtered out and the performance of the algorithm is further improved. The simulation results show that the improved algorithm can effectively eliminate the influence of noise, make up for the shortcomings of the LS algorithm, have better performance than the DFT estimation algorithm, and further improve the accuracy of channel estimation.