Repeated convolutional codes for high-error-rate channels

TitleRepeated convolutional codes for high-error-rate channels
Publication TypeJournal Article
Year of Publication1993
AuthorsWang, Q., G. Li, V. K. Bhargava, and L. J. Mason
JournalCommunications, IEEE Transactions on
Pagination852 -863
Date Publishedjun.
Keywords4-ary orthogonal codes, 8-ary orthogonal channels, approximation, binary convolutional code, binary metrics, binary symmetric channel, bit error probability, central limit theorem, channel capacity, code length, code rate, coding, convolutional codes, cutoff rate, decoding, encoding, error correction code, error correction codes, error probability, finite quantization, inner repetition code, jamming environment, Monte Carlo simulation, outer convolutional code, probability, repeated convolutional codes, soft-decision decoder, soft-decision metric, telecommunication channels

An error-correction scheme for an M-ary symmetric channel (MSC) characterized by a large error probability pe is considered. The value of pe can be near, but smaller than, 1-1/M, for which the channel capacity is zero, such as may occur in a jamming environment. The coding scheme consists of an outer convolutional code and an inner repetition code of length m that is used for each convolutional code symbol. At the receiving end, the m inner code symbols are used to form a soft-decision metric, which is passed to a soft-decision decoder for the convolutional code. The effect of finite quantization and methods to generate binary metrics for M gt;2 are investigated. Monte Carlo simulation results are presented. For the binary symmetric channel (BSC), it is shown that the overall code rate is larger than 0.6R0, where R0 is the cutoff rate of the channel. New union bounds on the bit error probability for systems with a binary convolutional code on 4-ary and 8-ary orthogonal channels are presented. For a BSC and a large m, a method is presented for BER approximation based on the central limit theorem


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