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—In this paper we consider the lossy compression of a binary symmetric source. We present a scheme that provides a low complexity lossy compressor with near optimal empirical performance. The proposed scheme is based on b-reduced ultra-sparse LDPC codes over GF(q). Encoding is performed by the Reinforced Belief Propagation algorithm, a variant of Belief(More)
In this paper we discuss a novel data compression technique for binary symmetric sources based on the cavity method over GF(q), the Galois Field of order q. We present a scheme of low complexity and near-optimal empirical performance. The compression step is based on a reduction of a sparse low-density parity-check code over GF(q) and is done through the(More)
—In this paper we use a variation of simulated annealing algorithm for optimizing two-dimensional constellations with 32 signals. The main objective is to maximize the symmetric pragmatic capacity under the peak-power constraint. The method allows the joint optimization of constellation and binary labeling. We also investigate the performance of the(More)
— A key idea in coding for the broadcast channel (BC) is binning, in which the transmitter encode information by selecting a codeword from an appropriate bin (the messages are thus the bin indexes). This selection is normally done by solving an appropriate (possibly difficult) combinatorial problem.. In this paper we propose a new variation of the Belief(More)
—In this paper we introduce a variation of simulated annealing algorithm for optimizing two-dimensional constellations with finite number of signals when the objective function is the symmetric capacity. Our method also allows the joint optimization of constellation and binary labeling when the objective function is the pragmatic capacity. The algorithm can(More)