6,441 research outputs found
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
Zero-Delay Joint Source-Channel Coding in the Presence of Interference Known at the Encoder
Zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel is considered in the presence of an additive Gaussian interference signal. The mean squared error (MSE) distortion is minimized under an average power constraint assuming that the interference signal is known at the transmitter. Optimality of simple linear transmission does not hold in this setting due to the presence of the known interference signal. While the optimal encoder-decoder pair remains an open problem, various non-linear transmission schemes are proposed in this paper. In particular, interference concentration (ICO) and one-dimensional lattice (1DL) strategies, using both uniform and non-uniform quantization of the interference signal, are studied. It is shown that, in contrast to typical scalar quantization of Gaussian sources, a non-uniform quantizer, whose quantization intervals become smaller as we go further from zero, improves the performance. Given that the optimal decoder is the minimum MSE (MMSE) estimator, a necessary condition for the optimality of the encoder is derived, and the numerically optimized encoder (NOE) satisfying this condition is obtained. Based on the numerical results, it is shown that 1DL with nonuniform quantization performs closer (compared to the other schemes) to the numerically optimized encoder while requiring significantly lower complexity
Source-Channel Diversity for Parallel Channels
We consider transmitting a source across a pair of independent, non-ergodic
channels with random states (e.g., slow fading channels) so as to minimize the
average distortion. The general problem is unsolved. Hence, we focus on
comparing two commonly used source and channel encoding systems which
correspond to exploiting diversity either at the physical layer through
parallel channel coding or at the application layer through multiple
description source coding.
For on-off channel models, source coding diversity offers better performance.
For channels with a continuous range of reception quality, we show the reverse
is true. Specifically, we introduce a new figure of merit called the distortion
exponent which measures how fast the average distortion decays with SNR. For
continuous-state models such as additive white Gaussian noise channels with
multiplicative Rayleigh fading, optimal channel coding diversity at the
physical layer is more efficient than source coding diversity at the
application layer in that the former achieves a better distortion exponent.
Finally, we consider a third decoding architecture: multiple description
encoding with a joint source-channel decoding. We show that this architecture
achieves the same distortion exponent as systems with optimal channel coding
diversity for continuous-state channels, and maintains the the advantages of
multiple description systems for on-off channels. Thus, the multiple
description system with joint decoding achieves the best performance, from
among the three architectures considered, on both continuous-state and on-off
channels.Comment: 48 pages, 14 figure
Zero-delay source-channel coding
In this thesis, we investigate the zero-delay transmission of source samples over three
different types of communication channel models. First, we consider the zero-delay
transmission of a Gaussian source sample over an additive white Gaussian noise (AWGN)
channel in the presence of an additive white Gaussian (AWG) interference, which is
fully known by the transmitter. We propose three parameterized linear and non-linear
transmission schemes for this scenario, and compare the corresponding mean square
error (MSE) performances with that of a numerically optimized encoder, obtained using
the necessary optimality conditions. Next, we consider the zero-delay transmission of a
Gaussian source sample over an AWGN channel with a one-bit analog-to-digital (ADC)
front end. We study this problem under two different performance criteria, namely the
MSE distortion and the distortion outage probability (DOP), and obtain the optimal
encoder and the decoder for both criteria. As generalizations of this scenario, we consider
the performance with a K-level ADC front end as well as with multiple one-bit ADC
front ends. We derive necessary conditions for the optimal encoder and decoder, which
are then used to obtain numerically optimized encoder and decoder mappings. Finally,
we consider the transmission of a Gaussian source sample over an AWGN channel with
a one-bit ADC front end in the presence of correlated side information at the receiver.
Again, we derive the necessary optimality conditions, and using these conditions obtain
numerically optimized encoder and decoder mappings. We also consider the scenario
in which the side information is available also at the encoder, and obtain the optimal
encoder and decoder mappings. The performance of the latter scenario serves as a lower
bound on the performance of the case in which the side information is available only at
the decoder.Open Acces
Paraunitary oversampled filter bank design for channel coding
Oversampled filter banks (OSFBs) have been considered for channel coding, since their redundancy can be utilised to permit the detection and correction of channel errors. In this paper, we propose an OSFB-based channel coder for a correlated additive Gaussian noise channel, of which the noise covariance matrix is assumed to be known. Based on a suitable factorisation of this matrix, we develop a design for the decoder's synthesis filter bank in order to minimise the noise power in the decoded signal, subject to admitting perfect reconstruction through paraunitarity of the filter bank. We demonstrate that this approach can lead to a significant reduction of the noise interference by exploiting both the correlation of the channel and the redundancy of the filter banks. Simulation results providing some insight into these mechanisms are provided
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