523 research outputs found
Disjoint LDPC Coding for Gaussian Broadcast Channels
Low-density parity-check (LDPC) codes have been used for communication over a
two-user Gaussian broadcast channel. It has been shown in the literature that
the optimal decoding of such system requires joint decoding of both user
messages at each user. Also, a joint code design procedure should be performed.
We propose a method which uses a novel labeling strategy and is based on the
idea behind the bit-interleaved coded modulation. This method does not require
joint decoding and/or joint code optimization. Thus, it reduces the overall
complexity of near-capacity coding in broadcast channels. For different rate
pairs on the boundary of the capacity region, pairs of LDPC codes are designed
to demonstrate the success of this technique.Comment: 5 pages, 1 figure, 3 tables, To appear in Proc. IEEE International
Symposium on Information Theory (ISIT 2009), Seoul, Korea, June-July 200
Hiding Symbols and Functions: New Metrics and Constructions for Information-Theoretic Security
We present information-theoretic definitions and results for analyzing
symmetric-key encryption schemes beyond the perfect secrecy regime, i.e. when
perfect secrecy is not attained. We adopt two lines of analysis, one based on
lossless source coding, and another akin to rate-distortion theory. We start by
presenting a new information-theoretic metric for security, called symbol
secrecy, and derive associated fundamental bounds. We then introduce
list-source codes (LSCs), which are a general framework for mapping a key
length (entropy) to a list size that an eavesdropper has to resolve in order to
recover a secret message. We provide explicit constructions of LSCs, and
demonstrate that, when the source is uniformly distributed, the highest level
of symbol secrecy for a fixed key length can be achieved through a construction
based on minimum-distance separable (MDS) codes. Using an analysis related to
rate-distortion theory, we then show how symbol secrecy can be used to
determine the probability that an eavesdropper correctly reconstructs functions
of the original plaintext. We illustrate how these bounds can be applied to
characterize security properties of symmetric-key encryption schemes, and, in
particular, extend security claims based on symbol secrecy to a functional
setting.Comment: Submitted to IEEE Transactions on Information Theor
Trellis phase codes for power-bandwith efficient satellite communications
Support work on improved power and spectrum utilization on digital satellite channels was performed. Specific attention is given to the class of signalling schemes known as continuous phase modulation (CPM). The specific work described in this report addresses: analytical bounds on error probability for multi-h phase codes, power and bandwidth characterization of 4-ary multi-h codes, and initial results of channel simulation to assess the impact of band limiting filters and nonlinear amplifiers on CPM performance
Context-Aware Generative Adversarial Privacy
Preserving the utility of published datasets while simultaneously providing
provable privacy guarantees is a well-known challenge. On the one hand,
context-free privacy solutions, such as differential privacy, provide strong
privacy guarantees, but often lead to a significant reduction in utility. On
the other hand, context-aware privacy solutions, such as information theoretic
privacy, achieve an improved privacy-utility tradeoff, but assume that the data
holder has access to dataset statistics. We circumvent these limitations by
introducing a novel context-aware privacy framework called generative
adversarial privacy (GAP). GAP leverages recent advancements in generative
adversarial networks (GANs) to allow the data holder to learn privatization
schemes from the dataset itself. Under GAP, learning the privacy mechanism is
formulated as a constrained minimax game between two players: a privatizer that
sanitizes the dataset in a way that limits the risk of inference attacks on the
individuals' private variables, and an adversary that tries to infer the
private variables from the sanitized dataset. To evaluate GAP's performance, we
investigate two simple (yet canonical) statistical dataset models: (a) the
binary data model, and (b) the binary Gaussian mixture model. For both models,
we derive game-theoretically optimal minimax privacy mechanisms, and show that
the privacy mechanisms learned from data (in a generative adversarial fashion)
match the theoretically optimal ones. This demonstrates that our framework can
be easily applied in practice, even in the absence of dataset statistics.Comment: Improved version of a paper accepted by Entropy Journal, Special
Issue on Information Theory in Machine Learning and Data Scienc
Variations on a theme by Schalkwijk and Kailath
Schalkwijk and Kailath (1966) developed a class of block codes for Gaussian
channels with ideal feedback for which the probability of decoding error
decreases as a second-order exponent in block length for rates below capacity.
This well-known but surprising result is explained and simply derived here in
terms of a result by Elias (1956) concerning the minimum mean-square distortion
achievable in transmitting a single Gaussian random variable over multiple uses
of the same Gaussian channel. A simple modification of the Schalkwijk-Kailath
scheme is then shown to have an error probability that decreases with an
exponential order which is linearly increasing with block length. In the
infinite bandwidth limit, this scheme produces zero error probability using
bounded expected energy at all rates below capacity. A lower bound on error
probability for the finite bandwidth case is then derived in which the error
probability decreases with an exponential order which is linearly increasing in
block length at the same rate as the upper bound.Comment: 18 Pages, 4 figures (added reference
Successive Cancellation Ordered Search Decoding of Modified -Coset Codes
A tree search algorithm called successive cancellation ordered search (SCOS)
is proposed for -coset codes that implements
maximum-likelihood (ML) decoding with an adaptive complexity for transmission
over binary-input AWGN channels. Unlike bit-flip decoders, no outer code is
needed to terminate decoding; therefore, SCOS also applies to
-coset codes modified with dynamic frozen bits. The average
complexity is close to that of successive cancellation (SC) decoding at
practical frame error rates (FERs) for codes with wide ranges of rate and
lengths up to bits, which perform within dB or less from the
random coding union bound and outperform Reed--Muller codes under ML decoding
by up to dB. Simulations illustrate simultaneous gains for SCOS over
SC-Fano, SC stack (SCS) and SC list (SCL) decoding in FER and the average
complexity at various SNR regimes. SCOS is further extended by forcing it to
look for candidates satisfying a threshold on the likelihood, thereby
outperforming basic SCOS under complexity constraints. The modified SCOS
enables strong error-detection capability without the need for an outer code.
In particular, the PAC code under modified SCOS provides gains in
overall and undetected FER compared to CRC-aided polar codes under SCL/dynamic
SC flip decoding at high SNR.Comment: 14 pages, 9 figures, 3 tables. Submitted to IEEE journal. The revised
version of the first submission. Major changes: 1) No dedicated section for
numerical results. Instead, simulations are provided right after the relevant
section. 2) More simulation results are added to compare all the state of art
polar decoders in terms of the number of arithmetic operations. arXiv admin
note: text overlap with arXiv:2105.0404
Decoupling trust and wireless channel induced effects on collaborative sensing attacks
One of the most crucial functionalities of cognitive radio networks is spectrum sensing. Completing this task in an accurate manner requires opportunistic spectrum access. Traditionally, sensing has been performed through energy detection by each individual secondary user. In order to increase accuracy, individual measurements are aggregated using different fusion functions. However, even though collaborative spectrum sensing can increase accuracy under benign settings, it is prone to falsification attacks, where malicious secondary users report fake sensings. Previous studies have designed trust (reputation) based systems to contain the effect of the adversaries, ignoring to a large extent the wireless channel irregularities when performing the computation. In this paper, we decouple the reasons behind an incorrect sensing report and propose the Decoupling Trust and Capability Spectrum Sensing System (DTCS3). DTCS3 is a collaborative spectrum sensing system that takes into account both a secondary sensor node's trust and its capability to sense the channel. Through thorough evaluations that consider a large variety of attack strategies, we show that by accounting for wireless induced effects while calculating the reporting trust of a secondary user, we can significantly improve the performance of a collaborative spectrum sensing system as compared to existing schemes in the literature. In particular, the true positive/negative rates can be improved by as much as 38%, while DTCS 3 is able to track and respond to dynamic changes in the adversaries' behavior. © 2014 IEEE
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