REPEATED CONVOLUTIONAL-CODES FOR HIGH-ERROR-RATE CHANNELS

In this paper we consider an error-correction scheme for an M-ary symm etric channel (MSC) characterized by a large error probability p(e). T he value of p(e) can be near, but smaller than, 1 - 1/M, for which the channel capacity is zero. Such a large p(e) may occur, for example, i n a jamming environment. The coding scheme considered consists of an o uter convolutional code and an inner repetition code of length m which 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 i s subsequently passed to a soft-decision decoder for the convolutional code. Emphasis is placed on using a binary convolutional code due to the consideration that there exist commercial codecs for such a code. The effect of finite quantization and methods to generate binary metri cs for M > 2 are investigated. Monte Carlo simulation results are pres ented. For the binary symmetric channel (BSC), it is shown that the ov erall code rate is larger than 0.6 R0, 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 channe ls are presented. Owing to the variable m which has no effect on the d ecoding procedure, this scheme has a clear operational advantage over some other schemes. For a BSC and a large m, a method is presented for BER approximation based on the central limit theorem.