19,023 research outputs found

    Efficient hash-driven Wyner-Ziv video coding for visual sensors

    Get PDF

    Improved Modeling of the Correlation Between Continuous-Valued Sources in LDPC-Based DSC

    Full text link
    Accurate modeling of the correlation between the sources plays a crucial role in the efficiency of distributed source coding (DSC) systems. This correlation is commonly modeled in the binary domain by using a single binary symmetric channel (BSC), both for binary and continuous-valued sources. We show that "one" BSC cannot accurately capture the correlation between continuous-valued sources; a more accurate model requires "multiple" BSCs, as many as the number of bits used to represent each sample. We incorporate this new model into the DSC system that uses low-density parity-check (LDPC) codes for compression. The standard Slepian-Wolf LDPC decoder requires a slight modification so that the parameters of all BSCs are integrated in the log-likelihood ratios (LLRs). Further, using an interleaver the data belonging to different bit-planes are shuffled to introduce randomness in the binary domain. The new system has the same complexity and delay as the standard one. Simulation results prove the effectiveness of the proposed model and system.Comment: 5 Pages, 4 figures; presented at the Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 201

    Investigation of punctured LDPC codes and time-diversity on free-space optical links

    Get PDF
    In this paper, we analyze the behavior of DVB-S2 un-punctured/punctured low-density parity-check (LDPC) coded on-off-keying (OOK) under atmospheric turbulence conditions by utilizing time diversity. A performance characterization between these schemes is evaluated, where punctured LDPC code provides a penalty of around 0.1 to 0.2 dB against unpunctured LDPC codes but still provides a coding gain of several dB against uncoded OOK. The combination of channel coding and a bit interleaver results in performance improvements in turbulence conditions. For example, such a system can achieve a coding gain of 16.7 dB in moderate turbulence conditions compared to uncoded OOK

    Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

    Get PDF
    Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations
    corecore