472 research outputs found
Nested turbo codes for the costa problem
Driven by applications in data-hiding, MIMO broadcast channel coding, precoding for interference cancellation, and transmitter cooperation in wireless networks, Costa coding has lately become a very active research area. In this paper, we first offer code design guidelines in terms of source- channel coding for algebraic binning. We then address practical code design based on nested lattice codes and propose nested turbo codes using turbo-like trellis-coded quantization (TCQ) for source coding and turbo trellis-coded modulation (TTCM) for channel coding. Compared to TCQ, turbo-like TCQ offers structural similarity between the source and channel coding components, leading to more efficient nesting with TTCM and better source coding performance. Due to the difference in effective dimensionality between turbo-like TCQ and TTCM, there is a performance tradeoff between these two components when they are nested together, meaning that the performance of turbo-like TCQ worsens as the TTCM code becomes stronger and vice versa. Optimization of this performance tradeoff leads to our code design that outperforms existing TCQ/TCM and TCQ/TTCM constructions and exhibits a gap of 0.94, 1.42 and 2.65 dB to the Costa capacity at 2.0, 1.0, and 0.5 bits/sample, respectively
Authentication with Distortion Criteria
In a variety of applications, there is a need to authenticate content that
has experienced legitimate editing in addition to potential tampering attacks.
We develop one formulation of this problem based on a strict notion of
security, and characterize and interpret the associated information-theoretic
performance limits. The results can be viewed as a natural generalization of
classical approaches to traditional authentication. Additional insights into
the structure of such systems and their behavior are obtained by further
specializing the results to Bernoulli and Gaussian cases. The associated
systems are shown to be substantially better in terms of performance and/or
security than commonly advocated approaches based on data hiding and digital
watermarking. Finally, the formulation is extended to obtain efficient layered
authentication system constructions.Comment: 22 pages, 10 figure
Perfectly Secure Steganography: Capacity, Error Exponents, and Code Constructions
An analysis of steganographic systems subject to the following perfect
undetectability condition is presented in this paper. Following embedding of
the message into the covertext, the resulting stegotext is required to have
exactly the same probability distribution as the covertext. Then no statistical
test can reliably detect the presence of the hidden message. We refer to such
steganographic schemes as perfectly secure. A few such schemes have been
proposed in recent literature, but they have vanishing rate. We prove that
communication performance can potentially be vastly improved; specifically, our
basic setup assumes independently and identically distributed (i.i.d.)
covertext, and we construct perfectly secure steganographic codes from public
watermarking codes using binning methods and randomized permutations of the
code. The permutation is a secret key shared between encoder and decoder. We
derive (positive) capacity and random-coding exponents for perfectly-secure
steganographic systems. The error exponents provide estimates of the code
length required to achieve a target low error probability. We address the
potential loss in communication performance due to the perfect-security
requirement. This loss is the same as the loss obtained under a weaker order-1
steganographic requirement that would just require matching of first-order
marginals of the covertext and stegotext distributions. Furthermore, no loss
occurs if the covertext distribution is uniform and the distortion metric is
cyclically symmetric; steganographic capacity is then achieved by randomized
linear codes. Our framework may also be useful for developing computationally
secure steganographic systems that have near-optimal communication performance.Comment: To appear in IEEE Trans. on Information Theory, June 2008; ignore
Version 2 as the file was corrupte
Perfectly Secure Steganography: Capacity, Error Exponents, and Code Constructions
An analysis of steganographic systems subject to the following perfect
undetectability condition is presented in this paper. Following embedding of
the message into the covertext, the resulting stegotext is required to have
exactly the same probability distribution as the covertext. Then no statistical
test can reliably detect the presence of the hidden message. We refer to such
steganographic schemes as perfectly secure. A few such schemes have been
proposed in recent literature, but they have vanishing rate. We prove that
communication performance can potentially be vastly improved; specifically, our
basic setup assumes independently and identically distributed (i.i.d.)
covertext, and we construct perfectly secure steganographic codes from public
watermarking codes using binning methods and randomized permutations of the
code. The permutation is a secret key shared between encoder and decoder. We
derive (positive) capacity and random-coding exponents for perfectly-secure
steganographic systems. The error exponents provide estimates of the code
length required to achieve a target low error probability. We address the
potential loss in communication performance due to the perfect-security
requirement. This loss is the same as the loss obtained under a weaker order-1
steganographic requirement that would just require matching of first-order
marginals of the covertext and stegotext distributions. Furthermore, no loss
occurs if the covertext distribution is uniform and the distortion metric is
cyclically symmetric; steganographic capacity is then achieved by randomized
linear codes. Our framework may also be useful for developing computationally
secure steganographic systems that have near-optimal communication performance.Comment: To appear in IEEE Trans. on Information Theory, June 2008; ignore
Version 2 as the file was corrupte
Capacity and Random-Coding Exponents for Channel Coding with Side Information
Capacity formulas and random-coding exponents are derived for a generalized
family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic
upper bounds on the achievable log probability of error. In our model,
information is to be reliably transmitted through a noisy channel with finite
input and output alphabets and random state sequence, and the channel is
selected by a hypothetical adversary. Partial information about the state
sequence is available to the encoder, adversary, and decoder. The design of the
transmitter is subject to a cost constraint. Two families of channels are
considered: 1) compound discrete memoryless channels (CDMC), and 2) channels
with arbitrary memory, subject to an additive cost constraint, or more
generally to a hard constraint on the conditional type of the channel output
given the input. Both problems are closely connected. The random-coding
exponent is achieved using a stacked binning scheme and a maximum penalized
mutual information decoder, which may be thought of as an empirical generalized
Maximum a Posteriori decoder. For channels with arbitrary memory, the
random-coding exponents are larger than their CDMC counterparts. Applications
of this study include watermarking, data hiding, communication in presence of
partially known interferers, and problems such as broadcast channels, all of
which involve the fundamental idea of binning.Comment: to appear in IEEE Transactions on Information Theory, without
Appendices G and
State Amplification
We consider the problem of transmitting data at rate R over a state dependent
channel p(y|x,s) with the state information available at the sender and at the
same time conveying the information about the channel state itself to the
receiver. The amount of state information that can be learned at the receiver
is captured by the mutual information I(S^n; Y^n) between the state sequence
S^n and the channel output Y^n. The optimal tradeoff is characterized between
the information transmission rate R and the state uncertainty reduction rate
\Delta, when the state information is either causally or noncausally available
at the sender. This result is closely related and in a sense dual to a recent
study by Merhav and Shamai, which solves the problem of masking the state
information from the receiver rather than conveying it.Comment: 9 pages, 4 figures, submitted to IEEE Trans. Inform. Theory, revise
Sparse Regression Codes for Multi-terminal Source and Channel Coding
We study a new class of codes for Gaussian multi-terminal source and channel
coding. These codes are designed using the statistical framework of
high-dimensional linear regression and are called Sparse Superposition or
Sparse Regression codes. Codewords are linear combinations of subsets of
columns of a design matrix. These codes were recently introduced by Barron and
Joseph and shown to achieve the channel capacity of AWGN channels with
computationally feasible decoding. They have also recently been shown to
achieve the optimal rate-distortion function for Gaussian sources. In this
paper, we demonstrate how to implement random binning and superposition coding
using sparse regression codes. In particular, with minimum-distance
encoding/decoding it is shown that sparse regression codes attain the optimal
information-theoretic limits for a variety of multi-terminal source and channel
coding problems.Comment: 9 pages, appeared in the Proceedings of the 50th Annual Allerton
Conference on Communication, Control, and Computing - 201
Near-capacity dirty-paper code design : a source-channel coding approach
This paper examines near-capacity dirty-paper code designs based on source-channel coding. We first point out that the performance loss in signal-to-noise ratio (SNR) in our code designs can be broken into the sum of the packing loss from channel coding and a modulo loss, which is a function of the granular loss from source coding and the target dirty-paper coding rate (or SNR). We then examine practical designs by combining trellis-coded quantization (TCQ) with both systematic and nonsystematic irregular repeat-accumulate (IRA) codes. Like previous approaches, we exploit the extrinsic information transfer (EXIT) chart technique for capacity-approaching IRA code design; but unlike previous approaches, we emphasize the role of strong source coding to achieve as much granular gain as possible using TCQ. Instead of systematic doping, we employ two relatively shifted TCQ codebooks, where the shift is optimized (via tuning the EXIT charts) to facilitate the IRA code design. Our designs synergistically combine TCQ with IRA codes so that they work together as well as they do individually. By bringing together TCQ (the best quantizer from the source coding community) and EXIT chart-based IRA code designs (the best from the channel coding community), we are able to approach the theoretical limit of dirty-paper coding. For example, at 0.25 bit per symbol (b/s), our best code design (with 2048-state TCQ) performs only 0.630 dB away from the Shannon capacity
Quantization Watermarking for Joint Compression and Data Hiding Schemes
International audienceEnrichment and protection of JPEG2000 images is an important issue. Data hiding techniques are a good solution to solve these problems. In this context, we can consider the joint approach to introduce data hiding technique into JPEG2000 coding pipeline. Data hiding consists of imperceptibly altering multimedia content, to convey some information. This process is done in such a way that the hidden data is not perceptible to an observer. Digital watermarking is one type of data hiding. In addition to the imperceptibility and payload constraints, the watermark should be robust against a variety of manipulations or attacks. We focus on trellis coded quantization (TCQ) data hiding techniques and propose two JPEG2000 compression and data hiding schemes. The properties of TCQ quantization, defined in JPEG2000 part 2, are used to perform quantization and information embedding during the same time. The first scheme is designed for content description and management applications with the objective of achieving high payloads. The compression rate/imperceptibility/payload trade off is our main concern. The second joint scheme has been developed for robust watermarking and can have consequently many applications. We achieve the better imperceptibility/robustness trade off in the context of JPEG2000 compression. We provide some experimental results on the implementation of these two schemes
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