17,162 research outputs found
Space-Time Signal Design for Multilevel Polar Coding in Slow Fading Broadcast Channels
Slow fading broadcast channels can model a wide range of applications in
wireless networks. Due to delay requirements and the unavailability of the
channel state information at the transmitter (CSIT), these channels for many
applications are non-ergodic. The appropriate measure for designing signals in
non-ergodic channels is the outage probability. In this paper, we provide a
method to optimize STBCs based on the outage probability at moderate SNRs.
Multilevel polar coded-modulation is a new class of coded-modulation techniques
that benefits from low complexity decoders and simple rate matching. In this
paper, we derive the outage optimality condition for multistage decoding and
propose a rule for determining component code rates. We also derive an upper
bound on the outage probability of STBCs for designing the
set-partitioning-based labelling. Finally, due to the optimality of the
outage-minimized STBCs for long codes, we introduce a novel method for the
joint optimization of short-to-moderate length polar codes and STBCs
A Universal Scheme for Wyner–Ziv Coding of Discrete Sources
We consider the Wyner–Ziv (WZ) problem of lossy compression where the decompressor observes a noisy version of the source, whose statistics are unknown. A new family of WZ coding algorithms is proposed and their universal optimality is proven. Compression consists of sliding-window processing followed by Lempel–Ziv (LZ) compression, while the decompressor is based on a modification of the discrete universal denoiser (DUDE) algorithm to take advantage of side information. The new algorithms not only universally attain the fundamental limits, but also suggest a paradigm for practical WZ coding. The effectiveness of our approach is illustrated with experiments on binary images, and English text using a low complexity algorithm motivated by our class of universally optimal WZ codes
Models, Statistics, and Rates of Binary Correlated Sources
This paper discusses and analyzes various models of binary correlated
sources, which may be relevant in several distributed communication scenarios.
These models are statistically characterized in terms of joint Probability Mass
Function (PMF) and covariance. Closed-form expressions for the joint entropy of
the sources are also presented. The asymptotic entropy rate for very large
number of sources is shown to converge to a common limit for all the considered
models. This fact generalizes recent results on the information-theoretic
performance limit of communication schemes which exploit the correlation among
sources at the receiver.Comment: submitted for publicatio
Optimal modeling for complex system design
The article begins with a brief introduction to the theory describing optimal data compression systems and their performance. A brief outline is then given of a representative algorithm that employs these lessons for optimal data compression system design. The implications of rate-distortion theory for practical data compression system design is then described, followed by a description of the tensions between theoretical optimality and system practicality and a discussion of common tools used in current algorithms to resolve these tensions. Next, the generalization of rate-distortion principles to the design of optimal collections of models is presented. The discussion focuses initially on data compression systems, but later widens to describe how rate-distortion theory principles generalize to model design for a wide variety of modeling applications. The article ends with a discussion of the performance benefits to be achieved using the multiple-model design algorithms
On some new approaches to practical Slepian-Wolf compression inspired by channel coding
This paper considers the problem, first introduced by Ahlswede and Körner in 1975, of lossless source coding with coded side information. Specifically, let X and Y be two random variables such that X is desired losslessly at the decoder while Y serves as side information. The random variables are encoded independently, and both descriptions are used by the decoder to reconstruct X. Ahlswede and Körner describe the achievable rate region in terms of an auxiliary random variable. This paper gives a partial solution for the optimal auxiliary random variable, thereby describing part of the rate region explicitly in terms of the distribution of X and Y
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