A possibility study on wavelet packet based algorithm for wireless channel representation

Existing wireless channel models are based on statistical impulse response methods derived from empirical analyses. These algorithms are inefficient in signal representation and consume a lot of computational power. Meanwhile, the theory of wavelets and wavelet packets, which have recently found applicability in signal processing applications, hold great promise for wireless channel modeling. In this paper the use of wavelet packet, which offers localization in both frequency and time domain, will be explored to represent channels. The performance of the proposed algorithm is evaluated in a simulation platform with stochastic metrics such as Mean Square Error (MSE), correlation of data and Cumulative Distribution Function (CDF). In order to improve the performance of the proposed system, a new candidate for optimization, called coefficient-reduction is employed. Through numerical studies the efficiency of the proposed algorithm to accurately represent unknown channels with few coefficients is demonstrated.