Sequence MAP decoding of trellis codes for Gaussian and Rayleigh channels

This paper considers the use of sequence maximum a posteriori (MAP) decodin g of trellis codes, A MAP receiver can exploit any "residual redundancy" th at may exist in the channel-encoded signal in the form of memory and/or a n onuniform distribution, thereby providing enhanced performance over very no isy channels, relative to maximum likelihood (ML) decoding. The paper begins with a first-order two-state Markov model for the channel encoder input, A variety of different systems with different source paramet ers, different modulation schemes, and different encoder complexities are s imulated, Sequence MAP decoding Is shown to substantially improve performan ce under very noisy channel conditions for systems with low-to-moderate red undancy, with relative gain increasing as the rate increases. As a result, coding schemes with multidimensional constellations are shown to have highe r MAP gains than comparable schemes with two-dimensional (2-D) constellatio ns, The second part of the paper considers trellis encoding of the code-excited linear predictive (CELP) speech coder's line spectral parameters (LSP's) w ith four-dimensional (4-D) QPSK modulation. Two source LSP models are used, One assumes only intraframe correlation of LSP's while the second one mode ls both intraframe and interframe correlation. MAP decoding gains (over ML decoding) as much as 4 dB are achieved, Also, a comparison between the conv entionally designed codes and an I-Q QPSK scheme shows that the I-Q scheme achieves better performance even though the first (simpler) LSP model is us ed.