PROBABILISTIC CONSTRUCTION OF LARGE CONSTRAINT LENGTH TRELLIS CODES FOR SEQUENTIAL-DECODING

Probabilistic algorithms are given for constructing good large constra int length trellis codes for use with sequential decoding that can ach ieve the channel cutoff rate bound at a bit error rate (BER) of 10(-5) - 10(-6), The algorithms are motivated by the random coding principle that an arbitrary selection of code symbols will produce a good code with high probability, One algorithm begins by choosing a relatively s mall set of codes randomly. The error performance of each of these cod es is evaluated using sequential decoding and the code with the best p erformance among the chosen set is retained. Another algorithm treats the code Construction as a combinatorial optimization problem and uses simulated annealing to direct the code search. Trellis codes for 8 PS K and 16 QAM constellations,vith constraint lengths upsilon up to 20 a re obtained. Simulation results with sequential decoding show that the se codes reach the channel cutoff rate bound at a BER of 10(-5) - 10(- 6) and achieve 5.0-6.35 dB real coding gains over uncoded systems with the same spectral efficiency and up to 2.0 dB real coding gains over 64 state trellis codes using Viterbi decoding.