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In this paper, the NGDBF algorithm is implemented on a code that is deployed in the IEEE 802.3an Ethernet standard. The design employs a fully parallel architecture and operates in two-phases: start-up phase and decoding phase. The two phase operation keeps the high latency operations off-line, thereby reducing the decoding latency during the decoding phase. The design is bench-marked with other state-of-the-art designs on the same code that employ different algorithms and architectures. The results indicate that the NGDBF decoder has a better area efficiency and a better energy efficiency compared to other state-of-art decoders. When the design is operated in medium to high signal to noise ratios, the design is able to provide greater than the required minimum throughput of 10Gbps. The design consumes 0.81mm2 of area and has an energy efficiency of 1.7pJ/bit, which are the lowest in the reported literature. The design also provides better error performance compared to other simplified decoder implementations and consumes lesser wire-length compared to a recently proposed design., Comment: 12 pages, 14 figures, 4 tables

In this paper, we consider the performance of the Noisy Gradient Descent Bit Flipping (NGDBF) algorithm under re-decoding of failed frames. NGDBF is a recent algorithm that uses a non-deterministic gradient descent search to decode low-density parity check (LDPC) codes. The proposed re-decode procedure obtains improved performance because the perturbations are independent at each re-decoding phase, therefore increasing the likelihood of successful decoding. We examine the benefits of re-decoding for an LDPC code from the IEEE 802.3an standard, and find that only a small fraction of re-decoded frames are needed to obtain significant performance benefits. When re-decoding is used, the NGDBF performance is very close to a benchmark offset min-sum decoder for the 802.3an code., Comment: 4 pages, 8 figures

A modified Gradient Descent Bit Flipping (GDBF) algorithm is proposed for decoding Low Density Parity Check (LDPC) codes on the binary-input additive white Gaussian noise channel. The new algorithm, called Noisy GDBF (NGDBF), introduces a random perturbation into each symbol metric at each iteration. The noise perturbation allows the algorithm to escape from undesirable local maxima, resulting in improved performance. A combination of heuristic improvements to the algorithm are proposed and evaluated. When the proposed heuristics are applied, NGDBF performs better than any previously reported GDBF variant, and comes within 0.5 dB of the belief propagation algorithm for several tested codes. Unlike other previous GDBF algorithms that provide an escape from local maxima, the proposed algorithm uses only local, fully parallelizable operations and does not require computing a global objective function or a sort over symbol metrics, making it highly efficient in comparison. The proposed NGDBF algorithm requires channel state information which must be obtained from a signal to noise ratio (SNR) estimator. Architectural details are presented for implementing the NGDBF algorithm. Complexity analysis and optimizations are also discussed., Comment: 16 pages, 22 figures, 2 tables

This paper presents a stochastic algorithm for iterative error control decoding. We show that the stochastic decoding algorithm is an approximation of the sum-product algorithm. When the code's factor graph is a tree, as with trellises, the algorithm approaches maximum a-posteriori decoding. We also demonstrate a stochastic approximations to the alternative update rule known as successive relaxation. Stochastic decoders have very simple digital implementations which have almost no RAM requirements. We present example stochastic decoders for a trellis-based Hamming code, and for a Block Turbo code constructed from Hamming codes., Comment: 5 pages, 7 figures, submitted to the 2005 International Symposium on Information Theory