Channel Estimation Based on Subcarriers Noise Reduction and Wavelet Transform in Spectrum Pooling

Channel estimation based on subcarriers noise reduction and wavelet transform in multiple antennas spectrum pooling is proposed in the paper. The received signals of multiple antennas will bring noise, including the noise of banned subcarriers and the noise of available subcarriers. It needs to reduce the noises to depress the influences for channel estimation. The noise of banned subcarriers can be reduced in frequency domain, and the noise of available subcarriers can be reduced through the wavelet transform. Without the channel statistical characteristics, the noise reduction is done for banned subcarriers through DFT (Discrete Fourier Transform) of received signals. The channel estimation is performed through least square with low signal-to-noise in time domain, and the wavelet threshold noise reduction is achieved for the channel estimation of each branch signal. The influences of noise signals of available subcarriers for channel estimation performance are farther reduced. At last the least square channel estimation of combined signal is worked out through the MRC (Maximal Ratio Combining). The simulation and analysis shows that the channel estimation based on subcarriers noise reduction and wavelet threshold noise reduction can improve the performances for multiple antennas spectrum pooling system.