A Universal Channel Estimation Algorithm Based on DFT Smoothing Filtering

Abstract

Channel estimation is a virtual component to ensure the performance in the orthogonal frequency division multiplexing (OFDM). Smoothing filter is often used to suppress noise to improve the estimation performance. However, the conventional smoothing filtering methods have paid little attention on the virtual subcarriers, which is required in practical system but will introduce interference. Therefore, in this paper, we proposed a universal channel estimation algorithm in which the discrete Fourier transform (DFT) smoothing filtering is used when the virtual subcarriers is considered. What is more, the proposed method is applicable to the OFDM system with either block-type or comb-type pilot, and it can be easily extended to multiple input multiple output (MIMO) system. The proposed method employs windowing, extraction and adaptive filter modules one or more based on conventional DFT-based channel estimation for different pilot patterns. The simulation results show that the proposed method has better performance than the conventional DFT-based channel estimation under the same complexity.

Keywords

• Channel estimation
• discrete Fourier transform (DFT)
• orthogonal frequency division multiplexing (OFDM)
• multiple input multiple output (MIMO)