Sequential decoding of trellis codes through ISI channels

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 56-57).by Patrick M. Maurer.M.S

On the error probability of general trellis codes with applications to sequential decoding

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of randomL-branch binary trellis codes of rateR = 1/nis given which separates the effects of the tail lengthTand the memory lengthMof the code. It is shown that the bound is independent of the lengthLof the information Sequence whenM geq T + [nE_{VU}(R)]^{-1} log_{2} L. The implication that the actual error probability behaves similarly is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication which can thus be taken as a design rule for choosingMso that the error probability is reduced to its minimum value for a givenT

Optimal Sequence Estimation for Convolutionally Coded Signals With Binary Digital Modulation in ISI Channels

Decoding convolutional codes with binary digital modulation in intersymbol interference (ISI) channels is studied. The receiver structure is a whitened matched filter (WMF) whose transfer function is determined by the ISI channel. Decoding of the output sequence can be performed in two steps or one step. The two-step decoding first decodes the ISI corrupted coded sequence back to the ISI free coded sequence which is then decoded back to the uncoded message sequence. For one-step decoding, the entire encoder-channel-receiver system is modeled as a new encoder with combined memory length of the memory lengths of the original encoder and the channel, and followed by a weighted summation mapping from the binary symbols to real number symbols. The weighting coefficients are determined by the channel characteristic. In both two-step and one-step decoding, the Viterbi algorithm (VA) is used to perform the maximum likelihood decoding. Decoding error probability and complexity of both methods are analyzed, simulated and compared

Optimal Sequence Estimation for Convolutionally Coded Signals With Binary Digital Modulation in ISI Channels

Decoding convolutional codes with binary digital modulation in intersymbol interference (ISI) channels is studied. The receiver structure is a whitened matched filter (WMF) whose transfer function is determined by the ISI channel. Decoding of the output sequence can be performed in two steps or one step. The two-step decoding first decodes the ISI corrupted coded sequence back to the ISI free coded sequence which is then decoded back to the uncoded message sequence. For one-step decoding, the entire encoder-channel-receiver system is modeled as a new encoder with combined memory length of the memory lengths of the original encoder and the channel, and followed by a weighted summation mapping from the binary symbols to real number symbols. The weighting coefficients are determined by the channel characteristic. In both two-step and one-step decoding, the Viterbi algorithm (VA) is used to perform the maximum likelihood decoding. Decoding error probability and complexity of both methods are analyzed, simulated and compared

Sequential decoding on intersymbol interference channels with application to magnetic recording

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1990.Thesis (Master's) -- Bilkent University, 1990.Includes bibliographical references leaves 27-28In this work we treat sequential decoding in the problem of sequence estimation on intersymbol interference ( ISI ) channels. We consider the magnetic recording channel as the particular ISI channel and investigate the coding gains that can be achieved with sequential decoding for different information densities. Since the cutoff rate determines this quantity , we find lower bounds to the cutoff rate. The symmetric cutoff rate is computed as a theoretical lower bound and practical lower bounds are found through simulations. Since the optimum decoding metric is impractical, a sub-optimum metric has been used in the simulations. The results show that this metric can not achieve the cutoff rate in general, but still its performance is not far from that of the optimum metric. We compare the results to those of Immink[9] and see that one can achieve positive coding gains at information densities of practical interest where other practical codes used in magnetic recording show coding loss.Alanyalı, MuratM.S

Study of information transfer optimization for communication satellites

The results are presented of a study of source coding, modulation/channel coding, and systems techniques for application to teleconferencing over high data rate digital communication satellite links. Simultaneous transmission of video, voice, data, and/or graphics is possible in various teleconferencing modes and one-way, two-way, and broadcast modes are considered. A satellite channel model including filters, limiter, a TWT, detectors, and an optimized equalizer is treated in detail. A complete analysis is presented for one set of system assumptions which exclude nonlinear gain and phase distortion in the TWT. Modulation, demodulation, and channel coding are considered, based on an additive white Gaussian noise channel model which is an idealization of an equalized channel. Source coding with emphasis on video data compression is reviewed, and the experimental facility utilized to test promising techniques is fully described