Cisco Technology, Inc.

Mohammad Ali Sedaghat

Andreas Bernhard Bisplinghoff

Christopher R Fludger

Gregory Alan Bryant

Glenn Elliot Cooper

A random noise generator for generating a plurality of random noise samples per clock cycle, the noise samples having a distribution. The random noise generator comprises at least a first comparator unit and a second comparator unit, the first comparator unit configured to generate a first plurality of samples representing a high-probability part of the distribution and the second comparator unit configured to generate a second plurality of samples representing a low-probability part of the distribution; and a random selection unit connected to at least the first comparator unit and the second comparator unit. The random selection unit is configured to receive the first plurality of samples generated by the first comparator unit and the second plurality of samples generated by the second comparator unit, to output a random selection of samples from the first plurality of samples and the second plurality of samples.

Random noise generation

A decoder decodes a soft information input vector represented by an input vector that is binary and that is constructed from the soft information input vector. The decoder stores even parity error vectors that are binary and odd parity error vectors that are binary for L least reliable bits (LRBs) of the input vector. The decoder computes a parity check of the input vector, and selects as error vectors either the even parity error vectors or the odd parity error vectors based at least in part on the parity check. The decoder hard decodes test vectors, representing respective sums of the input vector and respective ones of the error vectors, based on the L LRBs, to produce codewords that are binary for corresponding ones of the test vectors, and metrics associated with the codewords. The decoder updates the soft information input vector based on the codewords and the metrics.

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Erlangen, Germany

Mohammad Ali Sedaghat