Least Squares Channel Estimation Method Based on Minimum Energy Wavelet Framework

Abstract

The least squares channel estimation method based on the minimum energy wavelet framework, the steps are as follows: use the LS algorithm for preliminary channel estimation; perform energy normalization processing on the preliminary channel estimation results to obtain a normalized sequence; use the minimum energy wavelet framework to normalize The decomposed sequence is decomposed into the first layer and the second layer to obtain the decomposed sequence; based on the hard threshold function, the decomposed sequence is denoised; the wavelet tower reconstruction algorithm is used to reconstruct the signal, and the reconstructed new signal is reversed. The energy is normalized and calculated to obtain the final estimated value. The present invention adds a signal processing link based on the minimum energy wavelet frame on the basis of the preliminary channel estimation result obtained by the traditional LS algorithm, and can eliminate the error components in the estimation result obtained by the LS algorithm, thereby improving the accuracy of channel estimation. Moreover, the wavelet tower decomposition and reconstruction algorithm has low computational complexity and is easy to implement in engineering, laying the foundation for subsequent channel equalization and decoding performance improvement.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a channel estimation method of an OFDM system. Background technique [0002] The wireless mobile channel has the characteristics of frequency and time selective fading, which will cause inter-symbol interference in information transmission, and the bit error characteristics will deteriorate. Therefore, to achieve coherent demodulation at the receiving end, channel estimation must be performed. Channel estimation using pilot signals is the most commonly used technical means at present. For the receiving end, although the transmitted signal is known, the received signal will inevitably be interfered by noise, and the randomness and unknowability of noise make the channel estimation result have a certain estimation error no matter what method is used. [0003] One of the characteristics of the OFDM system is that the signal is processed in the frequency domain. Th...

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Problems solved by technology

The MMSE algorithm makes use of the statistical characteristics of noise and channel, and has a good suppression effect on ICI and Gaussian white noise, and can obtain better channel estimation performance. Due to the statistical characteristics of the channel, the amount of calculation is relatively large. When the number of subcarriers is large, the dimension of the matrix will increase correspondingly, and the inversion operation will be more complicated, making engineering implementation difficult.

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