56,699 research outputs found
Successive Refinement with Decoder Cooperation and its Channel Coding Duals
We study cooperation in multi terminal source coding models involving
successive refinement. Specifically, we study the case of a single encoder and
two decoders, where the encoder provides a common description to both the
decoders and a private description to only one of the decoders. The decoders
cooperate via cribbing, i.e., the decoder with access only to the common
description is allowed to observe, in addition, a deterministic function of the
reconstruction symbols produced by the other. We characterize the fundamental
performance limits in the respective settings of non-causal, strictly-causal
and causal cribbing. We use a new coding scheme, referred to as Forward
Encoding and Block Markov Decoding, which is a variant of one recently used by
Cuff and Zhao for coordination via implicit communication. Finally, we use the
insight gained to introduce and solve some dual channel coding scenarios
involving Multiple Access Channels with cribbing.Comment: 55 pages, 15 figures, 8 tables, submitted to IEEE Transactions on
Information Theory. A shorter version submitted to ISIT 201
On the Throughput of Channels that Wear Out
This work investigates the fundamental limits of communication over a noisy
discrete memoryless channel that wears out, in the sense of signal-dependent
catastrophic failure. In particular, we consider a channel that starts as a
memoryless binary-input channel and when the number of transmitted ones causes
a sufficient amount of damage, the channel ceases to convey signals. Constant
composition codes are adopted to obtain an achievability bound and the
left-concave right-convex inequality is then refined to obtain a converse bound
on the log-volume throughput for channels that wear out. Since infinite
blocklength codes will always wear out the channel for any finite threshold of
failure and therefore cannot convey information at positive rates, we analyze
the performance of finite blocklength codes to determine the maximum expected
transmission volume at a given level of average error probability. We show that
this maximization problem has a recursive form and can be solved by dynamic
programming. Numerical results demonstrate that a sequence of block codes is
preferred to a single block code for streaming sources.Comment: 23 pages, 1 table, 11 figures, submitted to IEEE Transactions on
Communication
Dynamic algorithms for multicast with intra-session network coding
The problem of multiple multicast sessions with
intra-session network coding in time-varying networks is considered.
The network-layer capacity region of input rates that can be
stably supported is established. Dynamic algorithms for multicast
routing, network coding, power allocation, session scheduling, and
rate allocation across correlated sources, which achieve stability
for rates within the capacity region, are presented. This work
builds on the back-pressure approach introduced by Tassiulas
et al., extending it to network coding and correlated sources. In
the proposed algorithms, decisions on routing, network coding,
and scheduling between different sessions at a node are made
locally at each node based on virtual queues for different sinks.
For correlated sources, the sinks locally determine and control
transmission rates across the sources. The proposed approach
yields a completely distributed algorithm for wired networks.
In the wireless case, power control among different transmitters
is centralized while routing, network coding, and scheduling
between different sessions at a given node are distributed
Finite-Block-Length Analysis in Classical and Quantum Information Theory
Coding technology is used in several information processing tasks. In
particular, when noise during transmission disturbs communications, coding
technology is employed to protect the information. However, there are two types
of coding technology: coding in classical information theory and coding in
quantum information theory. Although the physical media used to transmit
information ultimately obey quantum mechanics, we need to choose the type of
coding depending on the kind of information device, classical or quantum, that
is being used. In both branches of information theory, there are many elegant
theoretical results under the ideal assumption that an infinitely large system
is available. In a realistic situation, we need to account for finite size
effects. The present paper reviews finite size effects in classical and quantum
information theory with respect to various topics, including applied aspects
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