Abstract-Binary message-passing decoders for low-density parity-check (LDPC) codes are studied by using extrinsic information transfer (EXIT) charts. The channel delivers hard or soft decisions and the variable node decoder performs all computations in the L-value domain. A hard decision channel results in the well-know Gallager B algorithm, and increasing the output alphabet from hard decisions to two bits yields a gain of more than 1.0 dB in the required signal to noise ratio when using optimized codes. The code optimization requires adapting the mixing property of EXIT functions to the case of binary message-passing decoders. Finally, it is shown that errors on cycles consisting only of degree two and three variable nodes cannot be corrected and a necessary and sufficient condition for the existence of a cycle-free subgraph is derived.
We present a high performance implementation of a belief propagation decoder for decoding low-density parity-check (LDPC) codes on a fixed point digital signal processor. A simplified decoding algorithm was used and a stopping criteria for the iterative decoder was implemented to reduce the average number of required iterations. This leads to an implementation with increased throughput compared to other implementations of LDPC codes or Turbo codes. This decoder is able to decode at 5.4Mbps on a Texas Instruments TMS320C64xx DSP running at 600MHz.
We consider a multi-way relay network with an orthogonal uplink and correlated sources, and we characterise reliable communication (in the usual Shannon sense) with a single-letter expression. The characterisation is obtained using a joint source-channel random-coding argument, which is based on a combination of Wyner et al.'s Cascaded Slepian-Wolf Source Coding and Tuncel's Slepian-Wolf Coding over Broadcast Channels. We prove a separation theorem for the special case of two nodes; that is, we show that a modular code architecture with separate source and channel coding functions is (asymptotically) optimal. Finally, we propose a practical coding scheme based on low-density parity-check codes, and we analyse its performance using multi-edge density evolution.
In this paper we propose a new class of spatially coupled codes based on repeat-accumulate protographs. We show that spatially coupled repeat-accumulate codes have several advantages over spatially coupled low-density parity-check codes including simpler encoders and slightly higher code rates than spatially coupled low-density parity-check codes with similar thresholds and decoding complexity (as measured by the Tanner graph edge density).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.