This paper examines a joint source and channel coding (JSCC) technique based on oversampled filter banks (OFB). We consider an image compression system with an OFB based signal decomposition followed by scalar quantization and a redundant entropy coding scheme. This encoding chain can be viewed as a concatenation of an OFB code and an error correcting entropy code. The error correcting ability of an OFB comes from the explicit redundancy introduced into the transmitted signal by oversampling while the error correcting ability of the entropy code comes from the implicit redundancy due to the Markov property of the OFB outputs. The decoder consists of the soft-input soft-output entropy decoder and a syndrome decoder for the OFB code. The soft information at the output of the entropy decoder is utilized in the error localization procedure of the OFB syndrome decoder. The performance of the algorithm is examined for an image coding system with a wavelet filter bank.

This paper examines erasure resilience of oversampled filter bank (OFB) codes focusing on two families of codes based on cosine modulated filter banks (CMFB). We discuss frame properties of the CMFB based OFB codes and prove perfect reconstruction (PR) for erasure patterns for which PR depends only on the general structure of the code and not on the prototype filter coefficients. For some of these erasure patterns the expression for the mean square reconstruction error is also independent of filter coefficients and can be expressed in terms of the number of erasures, and of parameters such as number of channels and oversampling ratio. We further take an image coding system as an example and verify the performance of a particular OCMFB code for all possible erasure patterns by simulation.

This paper presents a new coding technique based on a mixed contourlet and wavelet transform. The redundancy of the transform is controlled by using the contourlet at fine scales and by switching to a separable wavelet transform at coarse scales. The transform is then optimized through an iterative projection process in the transform domain in order to minimize the quantization error in the image domain. A gain of respectively up to 0.5 dB and to 1 dB over respectively contourlet and wavelet based coding has been observed for images with directional features.

Multiple antenna systems have the potential to provide a high capacity wireless communication system. The spectral efficiency of space time trellis coding (STTC) is limited by the encoder structure. The layered space time (LST) architecture can overcome this problem. Three different LST schemes are presented. An improved iterative parallel interference canceller (PIC) method is applied at the receiver. A significant performance improvement is achieved compared to the standard PIC. Simulation results of three various layer structures are compared with low density parity check (LDPC) and convolutional codes as component codes.

We propose novel space-time multistage and iterative receiver structures and examine their application in code division multiple access (CDMA) mobile communication systems. In particular we derive an expression for weighting coefficients in parallel interference cancellers (PICs) in a system with a large number of users, where decision statistics bias is pronounced. We further examine the parameters in this expression and show how to obtain a practical partial cancellation method that allows on-line estimation of the weighting coefficients. In the proposed multistage PIC, the coefficients are calculated by using only the variances of the detector outputs. We also examine an iterative PIC and observe that this receiver has similar limitations as the multistage PIC. The application of the novel parallel interference cancellation strategy in the iterative receiver structure results in a spectacular system capacity improvement with a negligible complexity increase relative to the standard iterative receiver. The performance of the proposed receivers is further enhanced by receiver adaptive array antennas and space-time processing.