This paper presents a neural decoder for trellis coded modulation (TCM) schemes. Decoding is performed with Radial Basis Function Networks and Multi-Layer Perceptrons. The neural decoder effectively implements an adaptive Viterbi algorithm for TCM which learns communication channel imperfections. The implementation and performance of the neural decoder for trellis encoded 16-QAM with amplitude imbalance are analyzed.
Engineering Applications of Artificial Intelligence
Kaminsky, Edit J., and Nikhil Deshpande, “TCM Decoding using Neural Networks,” Engineering Applications of Artificial Intelligence, Vol 16, no. 5-6, Aug.-Sept., 2003, pp. 473-489.