DECODING ALGORITHMS FOR NONCOHERENT TRELLIS-CODED MODULATION

Noncoherent decoding of trellis codes using multiple-symbol overlapped observations was shown previously to achieve close to the coherent pe rformance, Optimal decoding by the Viterbi algorithm for L-symbol obse rvations requires a number of states which grows exponentially with L. In this paper, two novel suboptimal algorithms are presented, for whi ch the number of states is the same as the original code, yielding com plexity depending weakly on L. For practical values of L, both algorit hms are substantially less complex than the optimal algorithm, The fir st algorithm, the basic decision feedback algorithm (BDFA), is a low c omplexity feedback decoding scheme, based on the Viterbi algorithm, Th is algorithm is shown to suffer from increased error probability and f rom error propagation. A slight modification to this algorithm can, in most cases, reduce these effects significantly, The second algorithm uses the BDFA as a basic building block, This algorithm is based on a novel concept called ''estimated future'' and its performance is very close to optimum for most practical cases with some additional complex ity and memory requirements as compared to the first algorithm, Perfor mance analysis and simulation results are also given.