Sun Jiancheng,Zhang Taiyi,Liu Feng
(School of Electronics and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China)
Abstract:To solve the problem of fast fading channel prediction,the mobile multipath fading channel coefficient was decomposed as the measurement coefficients and wavelet coefficients based on the discrete stationary wavelet transform algorithms.For the chaotic behavior of the mobile multipath fading channel,the phase space of these coefficients was reconstructed by the theory of time delays.Based on the stability and the fractal of the chaotic attractor,the measurement coefficients and wavelet coefficients were predicted in their phase space.Finally the prediction of the fading channel coefficients were acquired by the inverse discrete stationary wavelet transform.Compared with the algorithm without wavelet,the proposed algorithm is a better candidate for long range prediction of the fading channel in the noise context.The experiment was carried out by utilizing fading channel data which spaned 65.9 milliseconds.The simulation results shows that the better prediction performance is acquired than the method without wavelet transform when the signal to noise ratio is 10 dB.
Keywords:fading channel;prediction;phase space;chaotic attractor