480,252 research outputs found
Joint Source-Channel Coding with Time-Varying Channel and Side-Information
Transmission of a Gaussian source over a time-varying Gaussian channel is
studied in the presence of time-varying correlated side information at the
receiver. A block fading model is considered for both the channel and the side
information, whose states are assumed to be known only at the receiver. The
optimality of separate source and channel coding in terms of average end-to-end
distortion is shown when the channel is static while the side information state
follows a discrete or a continuous and quasiconcave distribution. When both the
channel and side information states are time-varying, separate source and
channel coding is suboptimal in general. A partially informed encoder lower
bound is studied by providing the channel state information to the encoder.
Several achievable transmission schemes are proposed based on uncoded
transmission, separate source and channel coding, joint decoding as well as
hybrid digital-analog transmission. Uncoded transmission is shown to be optimal
for a class of continuous and quasiconcave side information state
distributions, while the channel gain may have an arbitrary distribution. To
the best of our knowledge, this is the first example in which the uncoded
transmission achieves the optimal performance thanks to the time-varying nature
of the states, while it is suboptimal in the static version of the same
problem. Then, the optimal \emph{distortion exponent}, that quantifies the
exponential decay rate of the expected distortion in the high SNR regime, is
characterized for Nakagami distributed channel and side information states, and
it is shown to be achieved by hybrid digital-analog and joint decoding schemes
in certain cases, illustrating the suboptimality of pure digital or analog
transmission in general.Comment: Submitted to IEEE Transactions on Information Theor
Multiuser Successive Refinement and Multiple Description Coding
We consider the multiuser successive refinement (MSR) problem, where the
users are connected to a central server via links with different noiseless
capacities, and each user wishes to reconstruct in a successive-refinement
fashion. An achievable region is given for the two-user two-layer case and it
provides the complete rate-distortion region for the Gaussian source under the
MSE distortion measure. The key observation is that this problem includes the
multiple description (MD) problem (with two descriptions) as a subsystem, and
the techniques useful in the MD problem can be extended to this case. We show
that the coding scheme based on the universality of random binning is
sub-optimal, because multiple Gaussian side informations only at the decoders
do incur performance loss, in contrast to the case of single side information
at the decoder. We further show that unlike the single user case, when there
are multiple users, the loss of performance by a multistage coding approach can
be unbounded for the Gaussian source. The result suggests that in such a
setting, the benefit of using successive refinement is not likely to justify
the accompanying performance loss. The MSR problem is also related to the
source coding problem where each decoder has its individual side information,
while the encoder has the complete set of the side informations. The MSR
problem further includes several variations of the MD problem, for which the
specialization of the general result is investigated and the implication is
discussed.Comment: 10 pages, 5 figures. To appear in IEEE Transaction on Information
Theory. References updated and typos correcte
Distributed Successive Approximation Coding using Broadcast Advantage: The Two-Encoder Case
Traditional distributed source coding rarely considers the possible link
between separate encoders. However, the broadcast nature of wireless
communication in sensor networks provides a free gossip mechanism which can be
used to simplify encoding/decoding and reduce transmission power. Using this
broadcast advantage, we present a new two-encoder scheme which imitates the
ping-pong game and has a successive approximation structure. For the quadratic
Gaussian case, we prove that this scheme is successively refinable on the
{sum-rate, distortion pair} surface, which is characterized by the
rate-distortion region of the distributed two-encoder source coding. A
potential energy saving over conventional distributed coding is also
illustrated. This ping-pong distributed coding idea can be extended to the
multiple encoder case and provides the theoretical foundation for a new class
of distributed image coding method in wireless scenarios.Comment: In Proceedings of the 48th Annual Allerton Conference on
Communication, Control and Computing, University of Illinois, Monticello, IL,
September 29 - October 1, 201
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