2,657 research outputs found
Two remarks to noiseless coding
An inequality concerning Kullback's I-divergence is applied to obtain a necessary condition for the possibility of encoding symbols of the alphabet of a discrete memoryless source of entropy H by sequences of symbols of another alphabet of size D in such a way that the average code length be close to the optimum H/log D. The same idea is applied to the problem of maximizing entropy per second for unequal symbol lenghts, too
Multiaccess Channels with State Known to Some Encoders and Independent Messages
We consider a state-dependent multiaccess channel (MAC) with state
non-causally known to some encoders. We derive an inner bound for the capacity
region in the general discrete memoryless case and specialize to a binary
noiseless case. In the case of maximum entropy channel state, we obtain the
capacity region for binary noiseless MAC with one informed encoder by deriving
a non-trivial outer bound for this case. For a Gaussian state-dependent MAC
with one encoder being informed of the channel state, we present an inner bound
by applying a slightly generalized dirty paper coding (GDPC) at the informed
encoder that allows for partial state cancellation, and a trivial outer bound
by providing channel state to the decoder also. The uninformed encoders benefit
from the state cancellation in terms of achievable rates, however, appears that
GDPC cannot completely eliminate the effect of the channel state on the
achievable rate region, in contrast to the case of all encoders being informed.
In the case of infinite state variance, we analyze how the uninformed encoder
benefits from the informed encoder's actions using the inner bound and also
provide a non-trivial outer bound for this case which is better than the
trivial outer bound.Comment: Accepted to EURASIP Journal on Wireless Communication and Networking,
Feb. 200
Lecture Notes on Network Information Theory
These lecture notes have been converted to a book titled Network Information
Theory published recently by Cambridge University Press. This book provides a
significantly expanded exposition of the material in the lecture notes as well
as problems and bibliographic notes at the end of each chapter. The authors are
currently preparing a set of slides based on the book that will be posted in
the second half of 2012. More information about the book can be found at
http://www.cambridge.org/9781107008731/. The previous (and obsolete) version of
the lecture notes can be found at http://arxiv.org/abs/1001.3404v4/
Broadcast Channels with Cooperating Decoders
We consider the problem of communicating over the general discrete memoryless
broadcast channel (BC) with partially cooperating receivers. In our setup,
receivers are able to exchange messages over noiseless conference links of
finite capacities, prior to decoding the messages sent from the transmitter. In
this paper we formulate the general problem of broadcast with cooperation. We
first find the capacity region for the case where the BC is physically
degraded. Then, we give achievability results for the general broadcast
channel, for both the two independent messages case and the single common
message case.Comment: Final version, to appear in the IEEE Transactions on Information
Theory -- contains (very) minor changes based on the last round of review
Capacity of a Class of Deterministic Relay Channels
The capacity of a class of deterministic relay channels with the transmitter
input X, the receiver output Y, the relay output Y_1 = f(X, Y), and a separate
communication link from the relay to the receiver with capacity R_0, is shown
to be
C(R_0) = \max_{p(x)} \min \{I(X;Y)+R_0, I(X;Y, Y_1) \}.
Thus every bit from the relay is worth exactly one bit to the receiver. Two
alternative coding schemes are presented that achieve this capacity. The first
scheme, ``hash-and-forward'', is based on a simple yet novel use of random
binning on the space of relay outputs, while the second scheme uses the usual
``compress-and-forward''. In fact, these two schemes can be combined together
to give a class of optimal coding schemes. As a corollary, this relay capacity
result confirms a conjecture by Ahlswede and Han on the capacity of a channel
with rate-limited state information at the decoder in the special case when the
channel state is recoverable from the channel input and the output.Comment: 17 pages, submitted to IEEE Transactions on Information Theor
Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
The paper proposes Monte Carlo algorithms for the computation of the
information rate of two-dimensional source/channel models. The focus of the
paper is on binary-input channels with constraints on the allowed input
configurations. The problem of numerically computing the information rate, and
even the noiseless capacity, of such channels has so far remained largely
unsolved. Both problems can be reduced to computing a Monte Carlo estimate of a
partition function. The proposed algorithms use tree-based Gibbs sampling and
multilayer (multitemperature) importance sampling. The viability of the
proposed algorithms is demonstrated by simulation results
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