1,359 research outputs found
Multiaccess Channels with State Known to One Encoder: Another Case of Degraded Message Sets
We consider a two-user state-dependent multiaccess channel in which only one
of the encoders is informed, non-causally, of the channel states. Two
independent messages are transmitted: a common message transmitted by both the
informed and uninformed encoders, and an individual message transmitted by only
the uninformed encoder. We derive inner and outer bounds on the capacity region
of this model in the discrete memoryless case as well as the Gaussian case.
Further, we show that the bounds for the Gaussian case are tight in some
special cases.Comment: 5 pages, Proc. of IEEE International Symposium on Information theory,
ISIT 2009, Seoul, Kore
Properties of Noncommutative Renyi and Augustin Information
The scaled R\'enyi information plays a significant role in evaluating the
performance of information processing tasks by virtue of its connection to the
error exponent analysis. In quantum information theory, there are three
generalizations of the classical R\'enyi divergence---the Petz's, sandwiched,
and log-Euclidean versions, that possess meaningful operational interpretation.
However, these scaled noncommutative R\'enyi informations are much less
explored compared with their classical counterpart, and lacking crucial
properties hinders applications of these quantities to refined performance
analysis. The goal of this paper is thus to analyze fundamental properties of
scaled R\'enyi information from a noncommutative measure-theoretic perspective.
Firstly, we prove the uniform equicontinuity for all three quantum versions of
R\'enyi information, hence it yields the joint continuity of these quantities
in the orders and priors. Secondly, we establish the concavity in the region of
for both Petz's and the sandwiched versions. This completes the
open questions raised by Holevo
[\href{https://ieeexplore.ieee.org/document/868501/}{\textit{IEEE
Trans.~Inf.~Theory}, \textbf{46}(6):2256--2261, 2000}], Mosonyi and Ogawa
[\href{https://doi.org/10.1007/s00220-017-2928-4/}{\textit{Commun.~Math.~Phys},
\textbf{355}(1):373--426, 2017}]. For the applications, we show that the strong
converse exponent in classical-quantum channel coding satisfies a minimax
identity. The established concavity is further employed to prove an entropic
duality between classical data compression with quantum side information and
classical-quantum channel coding, and a Fenchel duality in joint source-channel
coding with quantum side information in the forthcoming papers
Memory effects can make the transmission capability of a communication channel uncomputable
Most communication channels are subjected to noise. One of the goals of
Information Theory is to add redundancy in the transmission of information so
that the information is transmitted reliably and the amount of information
transmitted through the channel is as large as possible. The maximum rate at
which reliable transmission is possible is called the capacity. If the channel
does not keep memory of its past, the capacity is given by a simple
optimization problem and can be efficiently computed. The situation of channels
with memory is less clear. Here we show that for channels with memory the
capacity cannot be computed to within precision 1/5. Our result holds even if
we consider one of the simplest families of such channels -information-stable
finite state machine channels-, restrict the input and output of the channel to
4 and 1 bit respectively and allow 6 bits of memory.Comment: Improved presentation and clarified claim
Re-proving Channel Polarization Theorems: An Extremality and Robustness Analysis
The general subject considered in this thesis is a recently discovered coding
technique, polar coding, which is used to construct a class of error correction
codes with unique properties. In his ground-breaking work, Ar{\i}kan proved
that this class of codes, called polar codes, achieve the symmetric capacity
--- the mutual information evaluated at the uniform input distribution ---of
any stationary binary discrete memoryless channel with low complexity encoders
and decoders requiring in the order of operations in the
block-length . This discovery settled the long standing open problem left by
Shannon of finding low complexity codes achieving the channel capacity.
Polar coding settled an open problem in information theory, yet opened plenty
of challenging problems that need to be addressed. A significant part of this
thesis is dedicated to advancing the knowledge about this technique in two
directions. The first one provides a better understanding of polar coding by
generalizing some of the existing results and discussing their implications,
and the second one studies the robustness of the theory over communication
models introducing various forms of uncertainty or variations into the
probabilistic model of the channel.Comment: Preview of my PhD Thesis, EPFL, Lausanne, 2014. For the full version,
see http://people.epfl.ch/mine.alsan/publication
Reliable Physical Layer Network Coding
When two or more users in a wireless network transmit simultaneously, their
electromagnetic signals are linearly superimposed on the channel. As a result,
a receiver that is interested in one of these signals sees the others as
unwanted interference. This property of the wireless medium is typically viewed
as a hindrance to reliable communication over a network. However, using a
recently developed coding strategy, interference can in fact be harnessed for
network coding. In a wired network, (linear) network coding refers to each
intermediate node taking its received packets, computing a linear combination
over a finite field, and forwarding the outcome towards the destinations. Then,
given an appropriate set of linear combinations, a destination can solve for
its desired packets. For certain topologies, this strategy can attain
significantly higher throughputs over routing-based strategies. Reliable
physical layer network coding takes this idea one step further: using
judiciously chosen linear error-correcting codes, intermediate nodes in a
wireless network can directly recover linear combinations of the packets from
the observed noisy superpositions of transmitted signals. Starting with some
simple examples, this survey explores the core ideas behind this new technique
and the possibilities it offers for communication over interference-limited
wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the
IEE
Bit-Interleaved Coded Modulation Revisited: A Mismatched Decoding Perspective
We revisit the information-theoretic analysis of bit-interleaved coded
modulation (BICM) by modeling the BICM decoder as a mismatched decoder. The
mismatched decoding model is well-defined for finite, yet arbitrary, block
lengths, and naturally captures the channel memory among the bits belonging to
the same symbol. We give two independent proofs of the achievability of the
BICM capacity calculated by Caire et al. where BICM was modeled as a set of
independent parallel binary-input channels whose output is the bitwise
log-likelihood ratio. Our first achievability proof uses typical sequences, and
shows that due to the random coding construction, the interleaver is not
required. The second proof is based on the random coding error exponents with
mismatched decoding, where the largest achievable rate is the generalized
mutual information. We show that the generalized mutual information of the
mismatched decoder coincides with the infinite-interleaver BICM capacity. We
also show that the error exponent -and hence the cutoff rate- of the BICM
mismatched decoder is upper bounded by that of coded modulation and may thus be
lower than in the infinite-interleaved model. We also consider the mutual
information appearing in the analysis of iterative decoding of BICM with EXIT
charts. We show that the corresponding symbol metric has knowledge of the
transmitted symbol and the EXIT mutual information admits a representation as a
pseudo-generalized mutual information, which is in general not achievable. A
different symbol decoding metric, for which the extrinsic side information
refers to the hypothesized symbol, induces a generalized mutual information
lower than the coded modulation capacity.Comment: submitted to the IEEE Transactions on Information Theory. Conference
version in 2008 IEEE International Symposium on Information Theory, Toronto,
Canada, July 200
Information Theory based on Non-additive Information Content
We generalize the Shannon's information theory in a nonadditive way by
focusing on the source coding theorem. The nonadditive information content we
adopted is consistent with the concept of the form invariance structure of the
nonextensive entropy. Some general properties of the nonadditive information
entropy are studied, in addition, the relation between the nonadditivity
and the codeword length is pointed out.Comment: 9 pages, no figures, RevTex, accepted for publication in Phys. Rev.
E(an error in proof of theorem 1 was corrected, typos corrected
Low-latency Ultra Reliable 5G Communications: Finite-Blocklength Bounds and Coding Schemes
Future autonomous systems require wireless connectivity able to support
extremely stringent requirements on both latency and reliability. In this
paper, we leverage recent developments in the field of finite-blocklength
information theory to illustrate how to optimally design wireless systems in
the presence of such stringent constraints. Focusing on a multi-antenna
Rayleigh block-fading channel, we obtain bounds on the maximum number of bits
that can be transmitted within given bandwidth, latency, and reliability
constraints, using an orthogonal frequency-division multiplexing system similar
to LTE. These bounds unveil the fundamental interplay between latency,
bandwidth, rate, and reliability. Furthermore, they suggest how to optimally
use the available spatial and frequency diversity. Finally, we use our bounds
to benchmark the performance of an actual coding scheme involving the
transmission of short packets
On the Performance of Short Block Codes over Finite-State Channels in the Rare-Transition Regime
As the mobile application landscape expands, wireless networks are tasked
with supporting different connection profiles, including real-time traffic and
delay-sensitive communications. Among many ensuing engineering challenges is
the need to better understand the fundamental limits of forward error
correction in non-asymptotic regimes. This article characterizes the
performance of random block codes over finite-state channels and evaluates
their queueing performance under maximum-likelihood decoding. In particular,
classical results from information theory are revisited in the context of
channels with rare transitions, and bounds on the probabilities of decoding
failure are derived for random codes. This creates an analysis framework where
channel dependencies within and across codewords are preserved. Such results
are subsequently integrated into a queueing problem formulation. For instance,
it is shown that, for random coding on the Gilbert-Elliott channel, the
performance analysis based on upper bounds on error probability provides very
good estimates of system performance and optimum code parameters. Overall, this
study offers new insights about the impact of channel correlation on the
performance of delay-aware, point-to-point communication links. It also
provides novel guidelines on how to select code rates and block lengths for
real-time traffic over wireless communication infrastructures
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