This paper proposes a new structure of single parity check (SPC) product codes, which are inherently embedded with an interleaver. The complexity of decoding of the new SPC product codes is the same as the one of the ...
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ISBN:
(纸本)0780386051
This paper proposes a new structure of single parity check (SPC) product codes, which are inherently embedded with an interleaver. The complexity of decoding of the new SPC product codes is the same as the one of the existing single parity check product codes by use of message passing algorithm. Simulation results and bound analysis demonstrate a significant BER performance improvement compared to the existing single parity check product codes for high code rate at medium SNRs.
Like turbo codes, repeat-accumulate codes have remarkably good performance when r greater than or equal to 3, where r is the number of repetition times. In this letter, we present space-time codes with full antenna di...
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Like turbo codes, repeat-accumulate codes have remarkably good performance when r greater than or equal to 3, where r is the number of repetition times. In this letter, we present space-time codes with full antenna diversity using "weighted" nonbinary repeat-accumulate codes. Compared with the space-time turbo codes in Liu et al. and So et al., the main advantage of this new scheme is to construct space-time codes with full diversity for any m less than or equal to r and any length of frame without searching for interleavers, where m is the number of transmit antennas. These space-time codes have rate m/r and so, have full rate when m = r. Furthermore, they have an efficient decoding based on the message passing algorithm.
Bayesian networks compute marginal distributions through the "messagepassing" algorithm-a series of local calculations involving neighboring cliques of variables in a clique tree. In this work, these messag...
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Bayesian networks compute marginal distributions through the "messagepassing" algorithm-a series of local calculations involving neighboring cliques of variables in a clique tree. In this work, these messagepassing computations are extended to the case of degenerate Gaussian potentials which are multivariate Gaussian densities that can have two different kinds of degeneracies corresponding to projections with zero variance and projections with infinite variance. The basic operations of the message passing algorithm, such as representing conditional distributions, extending potentials, and conditioning on observations, create or operate on potentials with various kinds of degeneracies thereby demonstrating the need for such methodology. Computer implementation of this scheme follows easily from the details within and some computational aspects are discussed. We also demonstrate an application of our methodology to automatic musical accompaniment.
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