630 research outputs found
Asymptotically Optimal Joint Source-Channel Coding with Minimal Delay
We present and analyze a joint source-channel coding strategy for the
transmission of a Gaussian source across a Gaussian channel in n channel uses
per source symbol. Among all such strategies, our scheme has the following
properties: i) the resulting mean-squared error scales optimally with the
signal-to-noise ratio, and ii) the scheme is easy to implement and the incurred
delay is minimal, in the sense that a single source symbol is encoded at a
time.Comment: 5 pages, 1 figure, final version accepted at IEEE Globecom 2009
(Communication Theory Symposium
Side information aware source and channel coding in wireless networks
Signals in communication networks exhibit significant correlation, which can stem from the physical nature of the underlying sources, or can be created within the system. Current layered network architectures, in which, based on Shannon’s separation theorem, data is compressed and transmitted over independent bit-pipes, are in general not able to exploit such correlation efficiently. Moreover, this strictly layered architecture was developed for wired networks and ignore the broadcast and highly dynamic nature of the wireless medium, creating a bottleneck in the wireless network design. Technologies that exploit correlated information and go beyond the layered network architecture can become a key feature of future wireless networks, as information theory promises significant gains. In this thesis, we study from an information theoretic perspective, three distinct, yet fundamental, problems involving the availability of correlated information in wireless networks and develop novel communication techniques to exploit it efficiently. We first look at two joint source-channel coding problems involving the lossy transmission of Gaussian sources in a multi-terminal and a time-varying setting in which correlated side information is present in the network. In these two problems, the optimality of Shannon’s separation breaks down and separate source and channel coding is shown to perform poorly compared to the proposed joint source-channel coding designs, which are shown to achieve the optimal performance in some setups. Then, we characterize the capacity of a class of orthogonal relay channels in the presence of channel side information at the destination, and show that joint decoding and compression of the received signal at the relay is required to optimally exploit the available side information. Our results in these three different scenarios emphasize the benefits of exploiting correlated side information at the destination when designing a communication system, even though the nature of the side information and the performance measure in the three scenarios are quite different.Open Acces
Study and simulation of low rate video coding schemes
The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design
Cross Layer Coding Schemes for Broadcasting and Relaying
This dissertation is divided into two main topics. In the first topic, we study the
joint source-channel coding problem of transmitting an analog source over a Gaussian
channel in two cases - (i) the presence of interference known only to the transmitter and (ii) in the presence of side information about the source known only to the
receiver. We introduce hybrid digital analog forms of the Costa and Wyner-Ziv coding schemes. We present random coding based schemes in contrast to lattice based
schemes proposed by Kochman and Zamir. We also discuss superimposed digital and
analog schemes for the above problems which show that there are infinitely many
schemes for achieving the optimal distortion for these problems. This provides an
extension of the schemes proposed by Bross and others to the interference/source
side information case. The result of this study shows that the proposed hybrid digital analog schemes are more robust to a mismatch in channel signal-to-noise ratio
(SNR), than pure separate source coding followed by channel coding solutions. We
then discuss applications of the hybrid digital analog schemes for transmitting under
a channel SNR mismatch and for broadcasting a Gaussian source with bandwidth
compression. We also study applications of joint source-channel coding schemes for
a cognitive setup and also for the setup of transmitting an analog Gaussian source
over a Gaussian channel, in the presence of an eavesdropper.
In the next topic, we consider joint physical layer coding and network coding
solutions for bi-directional relaying. We consider a communication system where two transmitters wish to exchange information through a central relay. The transmitter
and relay nodes exchange data over synchronized, average power constrained additive
white Gaussian noise channels. We propose structured coding schemes using lattices
for this problem. We study two decoding approaches, namely lattice decoding and
minimum angle decoding. Both the decoding schemes can be shown to achieve the
upper bound at high SNRs. The proposed scheme can be thought of as a joint physical
layer, network layer code which outperforms other recently proposed analog network
coding schemes. We also study extensions of the bi-directional relay for the case with
asymmetric channel links and also for the multi-hop case. The result of this study
shows that structured coding schemes using lattices perform close to the upper bound
for the above communication system models
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