Iterative decoding of generalized concatenated convolutional codes

The aim of this article is first to generalize the principle of iterative decoding algorithm for the generalized concatenated convolutional codes by using a modified decoding strategy and to look deeply at their performance. The code construction is based on the Blokh-Zyablov (BZ) code construction method, where as outer codes components non-systematic and nonrecursive convolutional codes will be used. In addition, this study will allow us to examine in detail the performance of this code construction method compared with different coding and decoding approaches: Turbo-coding and a single convolutional code. The results showed that the coding gain at BER of 10^-4 for the iterative BZ-code and for Turbo coding is quite the same compared to convolutional coding, where the complexity of the BZ-code will be much lower than the Turbo-code. This gain for both coding schemes (BZ and Turbo) using soft-output Viterbi-decoding algorithm in AWGN channel is about 1.3 dB. Compared to uncoded BPSK, the coding gain for both schemes will be much higher: 6.3 dB