Two Dimensional Wavelet Transform Model for OFDM System
In this paper, a proposed structure was suggested by replacing the blocks of the fast Haar Wavelet Transform (WT) with a two dimensional wavelet transform at the transmitter and the receiver sides in the Orthogonal Frequency Division Multiplexing (OFDM) model. This can be done by converting a 1-Dimensional vector into a 2-Dimensional matrix and process it by 2-Dimensional Wavelet Transform (2D-WT). The proposed method was applied on the OFDM in Additive White Gaussian Noise (AWGN) and flat fading channel. It was concluded that the proposed method gives much better Bit Error Rate (BER) performance than the conventional OFDM model based on WT. The simulation results showed that the proposd structure outperforms the other scheme in the carried tests at the AWGN and flat fading channels.
A weightedL2 norm is introduced in which Markov operators, e.g., associated with noisy maps, are contracting provided the kernel (i.e., the transitional distribution) is smooth enough. This results in strong relaxational properties of noisy maps. Similar to this norm, integral functionals appear useful when studying spatiotemporal chaos and random fields.