Channel Estimation Based on Statistical Frames and Confidence Level in OFDM Systems

Abstract

Channel estimation is an important module for improving the performance of the orthogonal frequency division multiplexing (OFDM) system. The pilot-based least square (LS) algorithm can improve the channel estimation accuracy and the symbol error rate (SER) performance of the communication system. In pilot-based channel estimation, a certain number of pilots are inserted at fixed intervals between OFDM symbols to estimate the initial channel information, and channel estimation results can be obtained by one-dimensional linear interpolation. The minimum mean square error (MMSE) and linear minimum mean square error (LMMSE) algorithms involve the inverse operation of the channel matrix. If the number of subcarriers increases, the dimension of the matrix becomes large. Therefore, the inverse operation is more complex. To overcome the disadvantages of the conventional channel estimation methods, this paper proposes a novel OFDM channel estimation method based on statistical frames and the confidence level. The noise variance in the estimated channel impulse response (CIR) can be largely reduced under statistical frames and the confidence level; therefore, it reduces the computational complexity and improves the accuracy of channel estimation. Simulation results verify the effectiveness of the proposed channel estimation method based on the confidence level in time-varying dynamic wireless channels.

A Novel Noise Suppression Channel Estimation Method Based on Adaptive Weighted Averaging for OFDM Systems

“…Third, it combines the proposed method with the threshold value method to further suppress the noise in the MSTs. In [37], researchers committed to determine the positions of the MSTs by counting the number of positive and negative CIR coefficients of multiple frames, which was consistent with the goal of the threshold value method. Therefore, the proposed method is different from the multi-frame statistical channel estimation method in [37].…”

“…In [37], researchers committed to determine the positions of the MSTs by counting the number of positive and negative CIR coefficients of multiple frames, which was consistent with the goal of the threshold value method. Therefore, the proposed method is different from the multi-frame statistical channel estimation method in [37]. Moreover, the proposed method can be further improved by combining the multi-frame statistical channel estimation method.…”

“…Moreover, the proposed method can be further improved by combining the multi-frame statistical channel estimation method. To facilitate further research, channel model and some simulation parameters, the same as [37], are selected in this paper.…”

“…A CP-OFDM system [37] with N subcarriers and utilizing the proposed channel estimation method, is presented in Figure 1, where N P ≤ N uniformly spaced subcarriers are used as comb-type pilots. The pilots position arranged in ascending order is denoted as P 1 , P 2 , · · · , P N P .…”

“…where A = max 0≤N≤N P ( ĥ LS (n) ) and α is the suppression factor, which is usually selected in the region of [0.99, 1] [37]. The main disadvantage of the IMMSE method is that it suffers from a loss of the partial path energy while suppressing the noise effect, which decreases the estimation accuracy at high SNR scenarios.…”