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Information Theory Workshop (ITW), 2013 IEEE

Date 9-13 Sept. 2013

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Displaying Results 1 - 25 of 141
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    Freely Available from IEEE
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  • Polar codes with dynamic frozen symbols and their decoding by directed search

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (146 KB) |  | HTML iconHTML  

    A novel construction of polar codes with dynamic frozen symbols is proposed. The proposed codes are subcodes of extended BCH codes, which ensure sufficiently high minimum distance. Furthermore, a decoding algorithm is proposed, which employs estimates of the not-yet-processed bit channel error probabilities to perform directed search in code tree, reducing thus the total number of iterations. View full abstract»

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  • A lower bound on achievable rates by polar codes with mismatch polar decoding

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (259 KB) |  | HTML iconHTML  

    In this paper we show that mismatched polar codes over symmetric B-DMCs symmetrized under the same permutation can achieve rates of at least I(W, V) bits whenever I(W, V) > 0, where W denotes the communication channel, V the mismatched channel used in the code design including both the encoder and decoder, and I(W, V) × Σy Σx ϵ {0,1} 1/2 W(y|x) log2 (V(y|x))/(1/2V(y|0) + 1/2V(y|1)). View full abstract»

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  • Scaling exponent of list decoders with applications to polar codes

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (260 KB) |  | HTML iconHTML  

    Motivated by the significant performance gains which polar codes experience when they are decoded with successive cancellation list decoders, we study how the scaling exponent changes as a function of the list size L. In particular, we fix the block error probability Pe and we analyze the tradeoff between the blocklength N and the back-off from capacity C-R using scaling laws. By means of a Divide and Intersect procedure, we provide a lower bound on the error probability under MAP decoding with list size L for any binary-input memoryless output-symmetric channel and for any class of linear codes such that their minimum distance is unbounded as the blocklength grows large. We show that, although list decoding can significantly improve the involved constants, the scaling exponent itself, i.e., the speed at which capacity is approached, stays unaffected. This result applies in particular to polar codes, since their minimum distance tends to infinity as N increases. Some considerations are also pointed out for the genie-aided successive cancellation decoder when transmission takes place over the binary erasure channel. View full abstract»

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  • Polar coding for fading channels

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (421 KB) |  | HTML iconHTML  

    A polar coding scheme for fading channels is proposed in this paper. More specifically, the focus is on the Gaussian fading channel with a BPSK modulation, where the equivalent channel is modeled as a binary symmetric channel with varying cross-over probabilities. To deal with variable channel states, a coding scheme of hierarchically utilizing polar codes is proposed. In particular, by observing the polarization of different binary symmetric channels over different fading blocks, each channel use corresponding to a different polarization is modeled as a binary erasure channel such that polar codes could be adopted to encode over blocks. It is shown that the proposed coding scheme, without instantaneous channel state information at the transmitter, achieves the capacity of the corresponding fading binary symmetric channel. View full abstract»

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  • On symmetric multiple description coding

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (100 KB) |  | HTML iconHTML  

    We derive a single-letter lower bound on the minimum sum rate of multiple description coding with symmetric distortion constraints. For the binary uniform source with the Hamming distortion measure, this lower bound can be evaluated with the aid of a certain minimax theorem. A similar minimax theorem is established in the quadratic Gaussian setting, which is further leveraged to analyze the special case where the minimum sum rate subject to two levels of distortion constraints (with the second level imposed on the complete set of descriptions) is attained; in particular, we determine the minimum achievable distortions at the intermediate levels. View full abstract»

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  • Characterising correlation via entropy functions

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    Characterising the capacity region for a network can be extremely difficult. Even with independent sources, determining the capacity region can be as hard as the open problem of characterising all information inequalities. The majority of computable outer bounds in the literature are relaxations of the Linear Programming bound which involves entropy functions of random variables related to the sources and link messages. When sources are not independent, the problem is even more complicated. Extension of Linear Programming bounds to networks with correlated sources is largely open. Source dependence is usually specified via a joint probability distribution, and one of the main challenges in extending linear program bounds is the difficulty (or impossibility) of characterising arbitrary dependencies via entropy functions. This paper tackles the problem by answering the question of how well entropy functions can characterise correlation among sources. We show that by using carefully chosen auxiliary random variables, the characterisation can be fairly “accurate”. View full abstract»

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  • Erasure/list exponents for Slepian-Wolf decoding

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (173 KB) |  | HTML iconHTML  

    We analyze random coding error exponents associated with erasure/list Slepian-Wolf decoding using two different methods and then compare the resulting bounds. The first method follows the well known techniques of Gallager and Forney and the second method is based on a technique of distance enumeration, or more generally, type class enumeration, which is rooted in the statistical mechanics of a disordered system that is related to the random energy model (REM). The second method is guaranteed to yield exponent functions which are at least as tight as those of the first method, and it is demonstrated that for certain combinations of coding rates and thresholds, the bounds of the second method are strictly tighter than those of the first method, by an arbitrarily large factor. In fact, the second method may even yield an infinite exponent at regions where the first method gives finite values. We also discuss the option of variable-rate Slepian-Wolf encoding and demonstrate how it can improve on the resulting exponents. View full abstract»

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  • Operational extremality of Gaussianity in network compression, communication, and coding

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (100 KB) |  | HTML iconHTML  

    Summary form only given. Among other extremal properties, Gaussian sources are hardest to compress and communicate over. We review the main results of and exhibiting the generality in which such extremal properties hold in compression, communication and coding over networks. These properties are established via operational arguments, bypassing elusive characterizations of fundamental performance limits: schemes tailored for the Gaussian case are harnessed for constructions of schemes that provably do essentially as well under any other source of the same covariance. The talk will highlight the main ideas behind these constructions and how the results, which were established for memoryless sources and channels, carry over to the presence of memory. View full abstract»

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  • Spectrum bandit optimization

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (290 KB) |  | HTML iconHTML  

    We consider the problem of allocating radio channels to links in a wireless network. Links interact through interference, modelled as a conflict graph (i.e., two interfering links cannot be simultaneously active on the same channel). We aim at identifying the channel allocation maximizing the total network throughput over a finite time horizon. Should we know the average radio conditions on each channel and on each link, an optimal allocation would be obtained by solving an Integer Linear Program (ILP). When radio conditions are unknown a priori, we look for a sequential channel allocation policy that converges to the optimal allocation while minimizing on the way the throughput loss or regret due to the need for exploring suboptimal allocations. We formulate this problem as a generic linear bandit problem, and analyze it in a stochastic setting where radio conditions are driven by a i.i.d. stochastic process, and in an adversarial setting where radio conditions can evolve arbitrarily. We provide, in both settings, algorithms whose regret upper bounds outperform those of existing algorithms. View full abstract»

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  • Physical-layer cryptography through massive MIMO

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (183 KB) |  | HTML iconHTML  

    We propose the new technique of physical-layer cryptography based on using a massive MIMO channel as a key between the sender and desired receiver, which need not be secret. The goal is for low-complexity encoding and decoding by the desired transmitter-receiver pair, whereas decoding by an eavesdropper is hard in terms of prohibitive complexity. The massive MIMO system has a channel gain matrix that is drawn i.i.d. according to a Gaussian distribution, subject to additive white Gaussian noise. The decoding complexity is analyzed by mapping the massive MIMO system to a lattice. We show that the eavesdropper's decoder for the MIMO system with M-PAM modulation is equivalent to solving standard lattice problems that are conjectured to be of exponential complexity for both classical and quantum computers. Hence, under the widely-held conjecture that standard lattice problems are of worst-case complexity, the proposed encryption scheme has security that exceeds that of the most common encryption methods used today such as RSA and Diffie-Hellman. Additionally, we show that this scheme could be used to securely communicate without a pre-shared secret key and little computational overhead. In particular, a standard parallel channel decomposition allows the desired transmitter-receiver pair to encode and decode transmissions over the MIMO channel based on the singular value decomposition of the channel, while decoding remains computationally hard for an eavesdropper with an independent channel gain matrix, even if it knows the channel gain matrix between the desired transmitter and receiver. Thus, the massive MIMO system provides for low-complexity encryption commensurate with the most sophisticated forms of application-layer encryption by exploiting the physical layer properties of the radio channel. View full abstract»

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  • Secrecy & Rate Adaptation for secure HARQ protocols

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (215 KB) |  | HTML iconHTML  

    This paper is dedicated to the study of HARQ protocols under a secrecy constraint. An encoder sends information to a legitimate decoder while keeping it secret from the eavesdropper. Our objective is to provide a coding scheme that satisfies both reliability and confidentiality conditions. This problem has been investigated in the literature using a coding scheme that involves a unique secrecy parameter. The uniqueness of this parameter is sub-optimal for the throughput criteria and we propose a new coding scheme that introduces additional degrees of freedom. Our code involves Secrecy Adaptation and Rate Adaptation and we called it SARA-code. The first contribution is to prove that the SARA-code has small error probability and small information leakage rate. The second contribution is to show, over a numerical example, that the SARA-code improves the secrecy throughput. View full abstract»

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  • Protecting data against unwanted inferences

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (307 KB) |  | HTML iconHTML  

    We study the competing goals of utility and privacy as they arise when a provider delegates the processing of its personal information to a recipient who is better able to handle this data. We formulate our goals in terms of the inferences which can be drawn using the shared data. A whitelist describes the inferences that are desirable, i.e., providing utility. A blacklist describes the unwanted inferences which the provider wants to keep private. We formally define utility and privacy parameters using elementary information-theoretic notions and derive a bound on the region spanned by these parameters. We provide constructive schemes for achieving certain boundary points of this region. Finally, we improve the region by sharing data over aggregated time slots. View full abstract»

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  • Polar coding for secret-key generation

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (621 KB) |  | HTML iconHTML  

    Practical implementations of secret-key generation are often based on sequential strategies, which handle reliability and secrecy in two successive steps, called reconciliation and privacy amplification. In this paper, we propose an alternative scheme based on polar coding that jointly deals with reliability and secrecy. We study a binary degraded symmetric discrete memoryless source model with uniform marginals, and assume one-way rate-limited public communication between two legitimate users. Specifically, we propose secret-key capacity-achieving polar coding schemes, in which users rely on pre-shared secret seed of negligible rate. For the model studied, we thus provide the first example of low-complexity secret-key capacity-achieving scheme that handles vector quantization, for rate-limited public communication. Furthermore, we provide examples for which no seed is required. View full abstract»

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  • On polarization for the linear operator channel

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB) |  | HTML iconHTML  

    We address the problem of reliably transmitting information through a network where the nodes perform random linear network coding and where an adversary potentially injects malicious packets into the network. A good model for such a channel is a linear operator channel, where in this work we employ a combined multiplicative and additive matrix channel. We show that this adversarial channel behaves like a subspace-based symmetric discrete memoryless channel (DMC) under subspace insertions and deletions and typically has an input alphabet with non-prime cardinality. This facilitates the recent application of channel polarization results for DMCs with arbitrary input alphabets by providing a suitable one-to-one mapping from input matrices to subspaces. As a consequence, we show that polarization for this adversarial linear operator channel can be obtained via an element-wise encoder mapping for the input matrices, which replaces the finite field summation in the channel combining step for Arikan's classical polar codes. View full abstract»

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  • Channel polarization with higher order memory

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (267 KB) |  | HTML iconHTML  

    We introduce the design of a class of code sequences {en(m), n = 1, 2,... } with memory level m = 1,2,... based on the channel polarization idea, where {en(1)} coincides with the polar codes presented by Arıkan in [1]. The new codes achieve the symmetric capacity of arbitrary binary-input discrete memoryless channels. We derive bounds on the polarization performance as scaled with m. We show that {en(m)} offers monotonically decreasing encoding and decoding complexity with growing m. View full abstract»

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  • Some coding and information theoretic problems in contemporary (video) content delivery

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    Information and coding theory have traditionally been used in point-to-point scenarios, to compute and achieve the transmission channel capacity as well as to compute and achieve the optimal compression rate vs. source distortion tradeoff. In today's networks, the same (video) data is often transmitted to multiple users, simultaneously over diverse channels. The users may differ not only in the size and resolution of their displays and computing power, but may also be interested in different video scenes, with different levels of distortion, or even with different distortion measures. This paper describes several transmission and compression problems that arise in such heterogeneous network scenarios, and discusses how information and coding theory could be used to address them. View full abstract»

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  • Source broadcasting over erasure channels: Distortion bounds and code design

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (127 KB) |  | HTML iconHTML  

    We study a lossy source-broadcasting problem involving the transmission of a binary source over a two-receiver erasure broadcast channel. The motivation of our work stems from the problem faced by a server that wishes to singly broadcast content to a diverse set of users with fractional source reconstruction requirements. In this problem, the server wishes to minimize the overall network latency incurred (measured by the number of channel uses per source symbol) when faced with users of heterogeneous channel qualities, computing capabilities, content demand etc. We provide two complementary approaches to this problem. The first approach is to consider the problem from a joint source-channel coding formulation. Under this formulation, we provide both inner and outer bounds for the network latency under an erasure distortion criterion. Alternatively, the second approach employs rateless coding and formulates an optimization problem so as to find a degree distribution that minimizes the network latency. We compare both approaches with numerical simulations. View full abstract»

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  • Impact of random and burst packet losses on H.264 scalable video coding

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (363 KB) |  | HTML iconHTML  

    This paper studies the impact of packet loss on H.264 scalable video coding (SVC). A Markov Chain (MC) with 2N states is developed to describe the error propagation process inside a group of pictures (GOP). The characteristic of different packet loss events is captured by the initial state vector of the MC. Based on the proposed model, the performance of different GOP structures can be evaluated under both random and burst packet losses. View full abstract»

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  • Network coding designs suited for the real world: What works, what doesn't, what's promising

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (225 KB) |  | HTML iconHTML  

    Network coding (NC) has attracted tremendous attention from the research community due to its potential to significantly improve networks' throughput, delay, and energy performance as well as a means to simplify protocol design and naturally providing security support. The possibilities in code design have produced a large influx of new ideas and approaches to harness the power of NC. But, which of these designs are truly successful in practice? and which designs will not live up to their promised theoretical gains due to real-world constraints? Without attempting a comprehensive view of all practical pitfalls, this paper seeks to identify key ingredients to a successful design, critical and common limitations to most intra-session NC systems as well as promising techniques and ideas to guide future models and research problems grounded on practical concerns. View full abstract»

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  • Exploiting common randomness: A resource for network secrecy

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (128 KB) |  | HTML iconHTML  

    We investigate the problem of secure communication in a simple network with three communicating parties, two distributed sources who communicate over orthogonal channels to one destination node. The cooperation between the sources is restricted to a rate limited common random source they both observe. The communication channels are erasure channels with strictly causal channel state information of the destination available publicly. A passive adversary is present in the system eavesdropping on any one of the channels. We design a linear scheme that ensures secrecy against the eavesdropper. By deriving an outer bound for the problem we prove that the scheme is optimal in certain special cases. View full abstract»

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  • Secrecy in cascade networks

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (230 KB) |  | HTML iconHTML  

    We consider a cascade network where a sequence of nodes each send a message to their downstream neighbor to enable coordination, the first node having access to an information signal. An adversary also receives all the communication as well as additional side-information. The performance of the system is measured by a payoff function over all actions produced by the nodes as well as the adversary. The challenge is to maintain secrecy from the adversary in order thwart his attempt to reduce the payoff. We obtain inner and outer bounds on performance, and give examples where they are tight. From these bounds, we also derive the optimal equivocation that can be achieved in this setting, as a special case. View full abstract»

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  • Secure degrees of freedom of MIMO X-channels with output feedback and delayed CSI

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (183 KB) |  | HTML iconHTML  

    We investigate the problem of secure transmission over a two-user multi-input multi-output (MIMO) X-channel with noiseless local feedback and delayed channel state information (CSI) available at transmitters. The transmitters are equipped with M antennas each, and the receivers are equipped with N antennas each. For this model, we characterize the optimal sum secure degrees of freedom (SDoF) region. We show that, in presence of local feedback and delayed CSI, the sum SDoF region of the MIMO X-channel is same as the SDoF region of a two-user MIMO BC with 2M antennas at the transmitter and N antennas at each receiver. This result shows that, upon availability of feedback and delayed CSI, there is no performance loss in sum SDoF due to the distributed nature of the transmitters. Next, we show that this result also holds if only global feedback is conveyed to the transmitters. We also study the case in which only local feedback is provided to the transmitters, i.e., without CSI, and derive a lower bound on the sum SDoF for this model. Furthermore, we specialize our results to the case in which there are no security constraints. In particular, similar to the setting with security constraints, we show that the optimal sum degrees of freedom (sum DoF) region of the (M, M, N, N)-MIMO X-channel is same of the DoF region of a two-user MIMO BC with 2M antennas at the transmitter and N antennas at each receiver. We illustrate our results with some numerical examples. View full abstract»

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  • The secrecy capacity of a compound MIMO Gaussian channel

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (242 KB) |  | HTML iconHTML  

    The compound MIMO Gaussian wiretap channel is studied, where the channel to the legitimate receiver is known and the eavesdropper channel is not known to the transmitter but is known to have a bounded spectral norm (channel gain). The compound secrecy capacity is established without the de-gradedness assumption and the optimal signaling is identified: the compound capacity equals the worst-case channel capacity thus establishing the saddle-point property, the optimal signaling is Gaussian and on the eigenvectors of the legitimate channel and the worst-case eavesdropper is isotropic. The eigenmode power allocation somewhat resembles the standard water-filling but is not identical to it. View full abstract»

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