Many wireless channel behavior exhibits approximate sparse modeling in time domain, therefore compressive sensing (CS) approaches are applied for more accurate wireless channel estimation than traditional least squares approach. However, the CS approach is not applied for multicarrier data information recovery because the transmitted symbol can be sparse neither in time domain nor in frequency domain. In this paper, a new Sparse Frequency Division Multiplexing (SFDM) approach is suggested to generate sparse multicarrier mapping in frequency domain based on the huge combinatorial domain. The subcarriers will be mapped in sparse manner according to data stream for taking advantages of multicarrier modulation with lower number of subcarriers. The number of activated subcarriers is designed to achieve the same as Orthogonal Frequency–Division Multiplexing data rate under lower signal-to-noise ratio. The proposed approach exploits the double sparsity of data symbol in the frequency domain, and channel sparsity in the time domain. The same CS approach for both data recovery and adaptive channel estimation in a unified sparsely manner is used. The suggested framework can be used with any non-orthogonal waveform shaping and can work efficiently without any prior information about neither the channel sparsity order nor searching for the optimum pilot patterns.

In this paper, a novel technique to blind signal separation based on combination of the second order and the higher order approach is introduced. We transfer the problem of blind signal separation to the wavelet domain. The main idea behind this approach is that the mixing signal can be decomposed into sum of uncorrelated and/or independent subbands using the wavelet transform. In the beginning, the observed signal is pre-whitened in the time domain then, the initial separation matrix will be estimated from second order statistics decorrelation method in the wavelet domain. The estimating matrix will be used as initial separating matrix in the higher order statistics method to estimate the final separation matrix. The algorithm is tested using different examples different examples (chirp signals, sound signals and natural images). Our extensive experiments have confirmed that the use of the proposed procedure provides promising results in separating the image from noisy mixtures of image.

This paper describes a computationally efficient hybrid video codingscheme. The proposed hybrid coding scheme combines the advantages ofsimple hardware complexity of the 3-D discrete cosine transform codingand the high performance of the 3-D set partitioning in hierarchical tree(3-D SPIHT) coding. The modification of the subband video data in thewavelet domain is done based on the DCT transformation and theclassification of the coefficient in the low-frequency video subband (LL).The modification process provides a new subband video data containingalmost the same information of the original one but having smallervalues of the wavelet coefficient. Simulation results of the proposedmethod demonstrate that, with a small addition in the computationalcomplexity of the coding process, the PSNR performance of the proposedalgorithm is much higher than that of the 3-D SPIHT test coder.

In this paper, a novel video transmission scheme for transmission of three dimensional set partitioning in hierarchical trees (3D-SPIHT) video coding streams over the CDMA channels is proposed. The main idea behind this scheme is that the output of the 3D-SPIHT video coding will be send related to its significant information. The modified 3D-SPIHT coder will generate three groups of bitstream. The significant bits, the sign bits, and the refinement bits are transmitted in three different groups. The optimal unequal error protection (UEP) of these groups is proposed. The RS code is used to test the effectiveness of the proposed scheme. In addition to UEP, the power optimization over the Code–division multiple access channels (CDMA) is done which increases the performance of our system. The simulation results indicate that the proposed scheme provides significantly better PSNR performance in comparison with the well-known robust coding schemes.