Soft-output decoding algorithms for continuous decoding of parallel concatenated convolutional codes

We propose new decoding algorithms to be embedded in the iterative decoding strategy of parallel concatenated convolutional codes. They are derived from the optimum maximum-a-posteriori algorithm and permit a continuous decoding of the coded sequence without requiring trellis termination of the constituent codes. Two basic versions of the continuous algorithm and their suboptimum simplifications are described. Simulation results refer to the applications of the new algorithms to a highly efficient rate 1/3 concatenated code; they show performance only 0.6 dB worse than the Shannon limit.