Parallel concatenation of recursive systematic convolutional codes with transmission of interleaved set

In this work, a scheme for the parallel concatenation of convolutional codes is proposed. The systematic and interleaved sets are encoded. Unlike conventional turbo codes, however, both encoded sequences are concatenated and transmitted. At the receiving side, the first half of the corrupted sequence (corresponding to its encoded counterpart at the transmission side) is used as input to a soft-in soft-out (SISO) decoder. The second half is, in a similar manner, used by a second SISO decoder. These two decoders then use the maximum a-posteriori (MAP) algorithm for decoding. The key difference, however, with conventional turbo schemes, is that the channel metric is not removed when computing the extrinsic information for the first iteration. This is made possible since both decoders have access to an independently corrupted set. In the sequel, there is almost no gap in the performance with increased signal to noise ratio. In addition, for the remaining iterations, the proposed scheme employs conventional decoding and makes use of an inherent stopping criterion that enables the decoding procedure to be stopped once both decoders converge to the same sequence. Thus, the system makes an efficient use of iterations while reducing the computing resources required for decoding.