38 research outputs found
Reduced Complexity Super-Trellis Decoding for Convolutionally Encoded Transmission Over ISI-Channels
In this paper we propose a matched encoding (ME) scheme for convolutionally
encoded transmission over intersymbol interference (usually called ISI)
channels. A novel trellis description enables to perform equalization and
decoding jointly, i.e., enables efficient super-trellis decoding. By means of
this matched non-linear trellis description we can significantly reduce the
number of states needed for the receiver-side Viterbi algorithm to perform
maximum-likelihood sequence estimation. Further complexity reduction is
achieved using the concept of reduced-state sequence estimation.Comment: 6 pages, 8 figures, accepted for ICNC'13. (see also: arXiv:1205.7031
Low Complexity Decoding for Higher Order Punctured Trellis-Coded Modulation Over Intersymbol Interference Channels
Trellis-coded modulation (TCM) is a power and bandwidth efficient digital
transmission scheme which offers very low structural delay of the data stream.
Classical TCM uses a signal constellation of twice the cardinality compared to
an uncoded transmission with one bit of redundancy per PAM symbol, i.e.,
application of codes with rates when denotes the
cardinality of the signal constellation.
Recently published work allows rate adjustment for TCM by means of puncturing
the convolutional code (CC) on which a TCM scheme is based on.
In this paper it is shown how punctured TCM-signals transmitted over
intersymbol interference (ISI) channels can favorably be decoded. Significant
complexity reductions at only minor performance loss can be achieved by means
of reduced state sequence estimation.Comment: 4 pages, 5 figures, 3 algorithms, accepted and published at 6th
International Symposium on Communications, Control, and Signal Processing
(ISCCSP 2014
Low Complexity Decoding for Punctured Trellis-Coded Modulation Over Intersymbol Interference Channels
Classical trellis-coded modulation (TCM) as introduced by Ungerboeck in
1976/1983 uses a signal constellation of twice the cardinality compared to an
uncoded transmission with one bit of redundancy per PAM symbol, i.e.,
application of codes with rates when denotes the
cardinality of the signal constellation. The original approach therefore only
comprises integer transmission rates, i.e., , additionally, when transmitting over an intersymbol interference
(ISI) channel an optimum decoding scheme would perform equalization and
decoding of the channel code jointly. In this paper, we allow rate adjustment
for TCM by means of puncturing the convolutional code (CC) on which a TCM
scheme is based on. In this case a nontrivial mapping of the output symbols of
the CC to signal points results in a time-variant trellis. We propose an
efficient technique to integrate an ISI-channel into this trellis and show that
the computational complexity can be significantly reduced by means of a reduced
state sequence estimation (RSSE) algorithm for time-variant trellises.Comment: 4 pages, 7 pictured, accepted for 2014 International Zurich Seminar
on Communication
Punctured Trellis-Coded Modulation
In classic trellis-coded modulation (TCM) signal constellations of twice the
cardinality are applied when compared to an uncoded transmission enabling
transmission of one bit of redundancy per PAM-symbol, i.e., rates of
when denotes the cardinality of the signal
constellation. In order to support different rates, multi-dimensional (i.e.,
-dimensional) constellations had been proposed by means of
combining subsequent one- or two-dimensional modulation steps, resulting in
TCM-schemes with bit redundancy per real dimension. In
contrast, in this paper we propose to perform rate adjustment for TCM by means
of puncturing the convolutional code (CC) on which a TCM-scheme is based on. It
is shown, that due to the nontrivial mapping of the output symbols of the CC to
signal points in the case of puncturing, a modification of the corresponding
Viterbi-decoder algorithm and an optimization of the CC and the puncturing
scheme are necessary.Comment: 5 pages, 10 figures, submitted to IEEE International Symposium on
Information Theory 2013 (ISIT
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
Near far resistant detection for CDMA personal communication systems.
The growth of Personal Communications, the keyword of the 90s, has already the signs of a technological revolution. The foundations of this revolution are currently set through the standardization of the Universal Mobile Telecommunication System (UMTS), a communication system with synergistic terrestrial and satellite segments. The main characteristic of the UMTS radio interface, is the provision of ISDN services. Services with higher than voice data rates require more spectrum, thus techniques that utilize spectrum as efficiently as possible are currently at the forefront of the research community interests. Two of the most spectrally efficient multiple access technologies, namely. Code Division Multiple Access (CDMA) and Time Division Multiple Access (TDMA) concentrate the efforts of the European telecommunity.This thesis addresses problems and. proposes solutions for CDMA systems that must comply with the UMTS requirements. Prompted by Viterbi's call for further extending the potential of CDMA through signal processing at the receiving end, we propose new Minimum Mean Square Error receiver architectures. MMSE detection schemes offer significant advantages compared to the conventional correlation based receivers as they are NEar FAr Resistant (NEFAR) over a wide range of interfering power levels. The NEFAR characteristic of these detectors reduces considerably the requirements of the power control loops currently found in commercial CDMA systems. MMSE detectors are also found, to have significant performance gains over other well established interference cancellation techniques like the decorrelating detector, especially in heavily loaded system conditions. The implementation architecture of MMSE receivers can be either Multiple-Input Multiple Output (MIMO) or Single-Input Single-Output. The later offers not only complexity that is comparable to the conventional detector, but also has the inherent advantage of employing adaptive algorithms which can be used to provide both the dispreading and the interference cancellation function, without the knowledge of the codes of interfering users. Furthermore, in multipath fading channels, adaptive MMSE detectors can exploit the multipath diversity acting as RAKE combiners. The later ability is distinctive to MMSE based receivers, and it is achieved in an autonomous fashion, without the knowledge of the multipath intensity profile. The communicator achieves its performance objectives by the synergy of the signal processor and the channel decoder. According to the propositions of this thesis, the form of the signal processor needs to be changed, in order to exploit the horizons of spread spectrum signaling. However, maximum likelihood channel decoding algorithms need not change. It is the way that these algorithms are utilized that needs to be revis ed. In this respect, we identify three major utilization scenarios and an attempt is made to quantify which of the three best matches the requirements of a UMTS oriented CDMA radio interface. Based on our findings, channel coding can be used as a mapping technique from the information bit to a more ''intelligent" chip, matching the ''intelligence" of the signal processor
Multi-carrier CDMA using convolutional coding and interference cancellation
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