Abstract: A method for decoding forward error correction (FEC) encoded data. A stream of units of FEC encoded bits are received, where the units are derived from a transmitted signal, where each unit represents a one-bit data value, and where each unit includes correctness bits. Preferably, the stream of units of FEC encoded bits are decoded by using the quality level of bits to perform soft-decision convolution decoding on the stream of units of FEC bits, where the soft-decision convolution decoding produces, for block decoding, a stream of symbols made up of bits. Subsequences of units that are prone to erroneous soft-decision convolution decoding are detected by determining, for the sub-sequences whether the distribution of quality bits indicate the units are below a threshold level of correctness, and by comparing characteristics of that distribution to a given set of characteristics predetermined to be prone to result in incorrect decoding.

Abstract: A bit quality evaluator receives a sequence of bits. The bit sequence is provided to a decoding device that performs soft decision convolutional decoding on the sequence of bits. An off track event detector detects an occurrence of a trellis decode path change during the convolutional decoding operation and identifies a first symbol proximate corresponding to the occurrence of the trellis decode path change. An erasure decision circuit identifies at least the first symbol for erasure. The output of the first decoder and the erasure decision circuit are received at a second decoder, which decoder decodes the output of the first decoder after erasing at least the first symbol. The erasure decision circuit may also identify additional symbols for erasure using performance measures of the trellis decode path and using quality measures of the sequence of bits.

Abstract: A bit quality evaluator receives a sequence of bits. A quality measure is assigned to each bit within the sequence. The bit sequence and the quality measures are provided to a decoding device that performs soft decision convolutional decoding on the sequence of bits using the quality measure. An off-path detector detects an occurrence of a trellis decode path change during the convolutional decoding operation and identifies a first symbol proximate corresponding to the occurrence of the trellis decode path change. An erasure decision circuit identifies at least the first symbol for erasure. The output of the first decoder and the erasure decision circuit are received at a second decoder, which decoder decodes the output of the first decoder after erasing at least the first symbol. The erasure decision circuit may also identify additional symbols for erasure based on performance measures of the trellis decode path and the quality measure of the sequence of bits.

Abstract: A method for decoding forward error correction (FEC) encoded data. A stream of units of FEC encoded bits are received, where the units are derived from a transmitted signal, where each unit represents a one-bit data value, and where each unit includes correctness bits. Preferably, the stream of units of FEC encoded bits are decoded by using the quality level of bits to perform soft-decision convolution decoding on the stream of units of FEC bits, where the soft-decision convolution decoding produces, for block decoding, a stream of symbols made up of bits. Subsequences of units that are prone to erroneous soft-decision convolution decoding are detected by determining, for the sub-sequences whether the distribution of quality bits indicate the units are below a threshold level of correctness, and by comparing characteristics of that distribution to a given set of characteristics predetermined to be prone to result in incorrect decoding.

Abstract: A method for decoding forward error correction (FEC) encoded data. A stream of units of FEC encoded bits are received, where the units are derived from a transmitted signal, where each unit represents a one-bit data value, and where each unit includes correctness bits. Preferably, the stream of units of FEC encoded bits are decoded by using the quality level of bits to perform soft-decision convolution decoding on the stream of units of FEC bits, where the soft-decision convolution decoding produces, for block decoding, a stream of symbols made up of bits. Subsequences of units that are prone to erroneous soft-decision convolution decoding are detected by determining, for the sub-sequences whether the distribution of quality bits indicate the units are below a threshold level of correctness, and by comparing characteristics of that distribution to a given set of characteristics predetermined to be prone to result in incorrect decoding.

Abstract: Units of forward error correction (FEC) encoded bits each represent a one-bit data value and include correctness bits that together reflect a probability that the one-bit data value represented by the unit is correct. The units of FEC encoded bits are decoded by using the correctness bits to perform soft-decision convolution decoding on the units of FEC bits. Block code symbols that are prone to having been erroneously decoded via soft-decision convolution decoding are identified by determining whether the convolutional decoder “changes its mind” as indicated by a trellis decode path change during the convolutional decoding such that the last state of a lowest cost path after the path change does not agree with the penultimate state of a lowest cost path immediately prior to the path change. Such a path change indicates that the data input to the convolutional decoder is so corrupted so as to be substantially unlikely to be correctly decoded by the convolutional decoder.

Abstract: Units of forward error correction (FEC) encoded bits each represent a one-bit data value and include correctness bits that together reflect a probability that the one-bit data value represented by the unit is correct. The units of FEC encoded bits are decoded by using the correctness bits to perform soft-decision convolution decoding on the units of FEC bits. Block code symbols that are prone to having been erroneously decoded via soft-decision convolution decoding are identified by determining whether the convolutional decoder “changes its mind” as indicated by a trellis decode path change during the convolutional decoding such that the last state of a lowest cost path after the path change does not agree with the penultimate state of a lowest cost path immediately prior to the path change. Such a path change indicates that the data input to the convolutional decoder is so corrupted so as to be substantially unlikely to be correctly decoded by the convolutional decoder.

Abstract: A method for decoding forward error correction (FEC) encoded data. A stream of units of FEC encoded bits are received, where the units are derived from a transmitted signal, where each unit represents a one-bit data value, and where each unit includes correctness bits. Preferably, the stream of units of FEC encoded bits are decoded by using the quality level of bits to perform soft-decision convolution decoding on the stream of units of FEC bits, where the soft-decision convolution decoding produces, for block decoding, a stream of symbols made up of bits. Subsequences of units that are prone to erroneous soft-decision convolution decoding are detected by determining, for the sub-sequences whether the distribution of quality bits indicate the units are below a threshold level of correctness, and by comparing characteristics of that distribution to a given set of characteristics predetermined to be prone to result in incorrect decoding.

Abstract: A method and apparatus for decoding forward error correction (FEC) encoded data. A stream of units of FEC encoded bits are received, where the units are derived from a transmitted signal, where each unit represents a one-bit data value, and where each unit includes correctness bits that together reflect a level of probability that the one-bit data value represented by the unit differs from corresponding bits in the signal before it was transmitted. The stream of units of FEC encoded bits are decoded by using the quality level of bits to perform soft-decision convolution decoding on the stream of units of FEC bits, where the soft-decision convolution decoding produces, for block decoding, a stream of symbols made up of bits.