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This paper describes new, simple, recursive methods of construction for orientable sequences, i.e. periodic binary sequences in which any $n$ -tuple occurs at most once in a period in either direction. As has been previously described, such sequences have potential applications in automatic position-location systems, where the sequence is encoded onto a surface and a reader needs only examine $n$ consecutive encoded bits to determine its location and orientation on the surface. The only previously described method of construction (due to Dai et al.) is somewhat complex, whereas the new techniques are simple to both describe and implement. The methods of construction cover both the standard ‘infinite periodic’ case, and also the aperiodic, finite sequence, case. Both the new methods build on the Lempel homomorphism, first introduced as a means of recursively generating de Bruijn sequences. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the additivity phenomenon in the quantum dynamic capacity region of a quantum channel for trading the resources of classical communication, quantum communication, and entanglement. Understanding such an additivity property is important if we want to optimally use a quantum channel for general communication purposes. However, in a lot of cases, the channel one will be using only has an additive single or double resource capacity region, and it is largely unknown if this could lead to a strictly superadditive double or triple resource capacity region, respectively. For example, if a channel has additive classical and quantum capacities, can the classical-quantum capacity region be strictly superadditive? In this paper, we answer such questions affirmatively. We give proof-of-principle requirements for these channels to exist. In most cases, we can provide an explicit construction of these quantum channels. The existence of these superadditive phenomena is surprising in contrast to the result that the additivity of both classical-entanglement and classical-quantum capacity regions imply the additivity of the triple resource capacity region for a given channel. [ABSTRACT FROM AUTHOR]

This paper considers the problem of communication over a discrete memoryless channel (DMC) or an additive white Gaussian noise (AWGN) channel subject to the constraint that the probability that an adversary who observes the channel outputs can detect the communication is low. In particular, the relative entropy between the output distributions when a codeword is transmitted and when no input is provided to the channel must be sufficiently small. For a DMC whose output distribution induced by the “off” input symbol is not a mixture of the output distributions induced by other input symbols, it is shown that the maximum amount of information that can be transmitted under this criterion scales like the square root of the blocklength. The same is true for the AWGN channel. Exact expressions for the scaling constant are also derived. [ABSTRACT FROM AUTHOR]

In this paper, we present two new families of APN functions. The first family is in bivariate form $\big (x^{3}+xy^{2}+ y^{3}+xy, x^{5}+x^{4}y+y^{5}+xy+x^{2}y^{2} \big)\,\,\vphantom {_{\int _{\int }}}$ over ${\mathbb F}_{2^{m}}^{2}$. It is obtained by adding certain terms of the form $\sum _{i}(a_{i}x^{2^{i}}y^{2^{i}},b_{i}x^{2^{i}}y^{2^{i}})$ to a family of APN functions recently proposed by Gölo&gcaron;lu. The $\vphantom {_{\int _{\int }}}$ second family has the form $L(z)^{2^{m}+1}+vz^{2^{m}+1}$ over ${\mathbb F}_{{2^{3m}}}$ , which generalizes a family of APN functions by Bracken et al. from 2011. By calculating the $\Gamma $ -rank of the constructed APN functions over ${\mathbb F}_{2^{8}}$ and ${\mathbb F}_{2^{9}}$ , we demonstrate that the two families are CCZ-inequivalent to all known families. In addition, the two new families cover two known sporadic APN instances over ${\mathbb F}_{2^{8}}$ and ${\mathbb F}_{2^{9}}$ , which were found by Edel and Pott in 2009 and by Beierle and Leander in 2021, respectively. [ABSTRACT FROM AUTHOR]

This paper studies variable-length (VL) source coding of general sources with side-information. Novel one-shot coding bounds for Slepian–Wolf (SW) coding, which give nonasymptotic tradeoff between the error probability and the codeword length of VL-SW coding, are established. One-shot results are applied to asymptotic analysis, and a general formula for the optimal coding rate achievable by weakly lossless VL-SW coding (i.e., VL-SW coding with vanishing error probability) is derived. Our general formula reveals how the encoder side-information and/or VL coding improve the optimal coding rate in the general setting. In addition, it is shown that if the encoder side-information is useless in weakly lossless VL coding then it is also useless even in the case where the error probability may be positive asymptotically. [ABSTRACT FROM AUTHOR]

The majority of works in distributed storage networks assume a simple network model with a collection of identical storage nodes with the same communication cost between the nodes. In this paper, we consider a realistic multi-rack distributed data storage network and present a code design framework for this model. Considering the cheaper data transmission within the racks, our code construction method is able to locally repair the nodes failure within the same rack by using only the survived nodes in the same rack. However, in the case of severe failure patterns when the information content of the survived nodes is not sufficient to repair the failures, other racks will participate in the repair process. By employing the criteria of our multi-rack storage code, we establish a linear programming bound on the size of the code in order to maximize the code rate. [ABSTRACT FROM AUTHOR]

We derive the optimal second-order rates in joint source-channel coding when the channel is a general discrete memoryless channel and the source is an irreducible and ergodic Markov process. In contrast, previous studies solved it only when the channel satisfies a certain unique-variance condition and the source is subject to an independent and identical distribution. We also compare the joint source-channel scheme with the separation scheme in the second-order regime, while a previous study made a notable comparison with numerical calculation. To discuss these two topics, we introduce two kinds of new distribution families, switched Gaussian convolution distribution and *-product distribution, which are defined by modifying the Gaussian distribution. [ABSTRACT FROM AUTHOR]

Transmissions across asynchronous communication channels are subject to delay injection attacks, which can cause an arbitrary number of skews. That is, such attacks can cause an arbitrary number of transmitted signals to arrive after the first signal of the next transmission has arrived. The (common) assumption that despite the delays, all signals from the $i$ th transmission arrive at the decoder before any signal from the (i+2){\text{nd}} transmission arrives is called a no switch assumption. This paper presents a self-synchronizing, zero-latency, zero-error coding scheme that requires no acknowledge and can decode transmissions distorted by an arbitrary number of skews that obey this no switch assumption. The rate associated with the coding scheme provides a lower bound of 0.6942 for the (zero-error) capacity of such a channel. It is further shown that zero-error channel capacity of the channel is upper bounded by 0.7248. Finally, this paper presents bounds on the (zero-error) capacity of a channel for which the number of transmissions that can mix with one another is large. [ABSTRACT FROM AUTHOR]

In a recent work, Beierle, Brinkmann and Leander presented a recursive tree search for finding APN permutations with linear self-equivalences in small dimensions. In this paper, we describe how this search can be adapted to find many new instances of quadratic APN functions. In particular, we found 12,921 new quadratic APN functions in dimension eight, 35 new quadratic APN functions in dimension nine and five new quadratic APN functions in dimension ten up to CCZ-equivalence. Remarkably, two of the 35 new APN functions in dimension nine are APN permutations. Among the 8-bit APN functions, there are three extended Walsh spectra that do not correspond to any of the previously-known quadratic 8-bit APN functions and, surprisingly, there exist at least four CCZ-inequivalent 8-bit APN functions with linearity 27, i.e., the highest possible non-trivial linearity for quadratic functions in dimension eight. [ABSTRACT FROM AUTHOR]

The $q^{t} \times (q+1)t$ ordered orthogonal arrays (OOAs) of strength $t$ over the alphabet $ \mathbb {F}_{q}$ were constructed using linear feedback shift register sequences (LFSRs) defined by primitive polynomials in $ \mathbb {F}_{q}[x]$. In this paper, we extend this result to all polynomials in $\mathbb {F}_{q}[x]$ which satisfy some fairly simple restrictions, i.e., the restrictions that are automatically satisfied by primitive polynomials. While these restrictions sometimes reduce the number of columns produced from $(q+1)t$ to a smaller multiple of $t$ , in many cases, we still obtain the maximum number of columns in the constructed OOA when using non-primitive polynomials. For $2 \le q \le 9$ and small $t$ , we generate OOAs in this manner for all permissible polynomials of degree $t$ in $ \mathbb {F}_{q}[x]$ and compare the results to the ones produced in , , and showing how close the arrays are to being “full” orthogonal arrays. Unusually for the finite fields, our arrays based on the non-primitive irreducible and even reducible polynomials are closer to the orthogonal arrays than those built from the primitive polynomials. [ABSTRACT FROM AUTHOR]

We formulate and study the problem of ON-OFF privacy. ON-OFF privacy algorithms enable a user to continuously switch his privacy between ON and OFF. An obvious example is the incognito mode in internet browsers. But beyond internet browsing, ON-OFF privacy can be a desired feature in most online applications. The challenge is that the statistical correlation over time of a user’s online behavior can lead to leakage of information. We consider the setting in which a user is interested in retrieving the latest message generated by one of $N$ sources. The user’s privacy status can change between ON and OFF over time. When privacy is ON the user wants to hide his request. Moreover, since the user’s requests depend on personal attributes such as age, gender, and political views, they are typically correlated over time. As a consequence, the user cannot simply ignore privacy when privacy is OFF. We model the correlation between user’s requests by an $N$ state Markov chain. The goal is to design query schemes with optimal download rate, that preserve privacy in an ON-OFF privacy setting. In this paper, we present inner and outer bounds on the achievable download rate for $N$ sources. We also devise an efficient algorithm to construct an ON-OFF privacy scheme achieving the inner bound and prove its optimality in the case $N=2$ sources. For $N > 2$ , finding tighter outer bounds and efficient constructions of ON-OFF privacy schemes that would achieve them remains an open question. [ABSTRACT FROM AUTHOR]

A locally recoverable code (LRC code) is a code over a finite alphabet, such that every symbol in the encoding is a function of a small number of other symbols that form a recovering set. In this paper, we derive new finite-length and asymptotic bounds on the parameters of LRC codes. For LRC codes with a single recovering set for every coordinate, we derive an asymptotic Gilbert–Varshamov type bound for LRC codes and find the maximum attainable relative distance of asymptotically good LRC codes. Similar results are established for LRC codes with two disjoint recovering sets for every coordinate. For the case of multiple recovering sets (the availability problem), we derive a lower bound on the parameters using expander graph arguments. Finally, we also derive finite-length upper bounds on the rate and the distance of LRC codes with multiple recovering sets. [ABSTRACT FROM AUTHOR]

An involution is a permutation, such that its inverse is itself (i.e., cycle length ≤ 2). Due to this property, involutions have been used in many applications, including cryptography and coding theory. In this paper, we provide a systematic study of involutions that are defined over a finite field of characteristic 2. We characterize the involution property of several classes of polynomials and propose several constructions. Furthermore, we study the number of fixed points of involutions, which is a pertinent question related to permutations with short cycle. In this paper, we mostly have used combinatorial techniques. [ABSTRACT FROM AUTHOR]

Switch codes, first proposed by Wang et al., are codes that are designed to increase the parallelism of data writing and reading processes in network switches. A network switch is required to write $n$ incoming packets and read $k$ outgoing packets while using $m$ memory banks, each able to write and read one packet per time unit. Each set of $n$ packets written to the switch simultaneously is called a generation. The objective is to store the packets in the banks such that every request of $k$ packets, which can belong to previous generations, can be handled by reading at most one packet from every bank. In this paper, we study a new type of switch codes that can simultaneously deliver large packet request and good coding rate. These attractive features are achieved by relaxing the request model to a natural sub-class we call consecutive requests. For this new request model, we define a new type of codes called consecutive switch codes. These codes are studied in both the computational and combinatorial models, corresponding to whether the data can be encoded or not. For binary codes, we also study an intermediate model in which a coded packet is formed by the XOR operations of at most two input packets. We present several code constructions and prove the optimality of one family of these codes by providing the corresponding lower bound. Finally, we introduce a construction of conventional switch codes, which improves upon the best known results for the case $n=k$ . [ABSTRACT FROM AUTHOR]

Network switches and routers scale in rate by distributing the packet read/write operations across multiple memory banks. Rate scaling is achieved so long as sufficiently many packets can be written and read in parallel. However, due to the non-determinism of the read process, parallel pending read requests may contend on memory banks, and thus significantly lower the switching rate. In this paper, we provide a constructive study of codes that guarantee fully parallel data reconstruction without contention. We call these codes “switch codes,” and construct three optimal switch-code families with different parameters. All the constructions use only simple XOR-based encoding and decoding operations, an important advantage when operated in ultra-high speeds. Switch codes achieve their good performance by spanning simultaneous disjoint local-decoding sets for all their information symbols. Switch codes may be regarded as an extreme version of the previously studied batch codes, where the switch version requires parallel reconstruction of all the information symbols. [ABSTRACT FROM PUBLISHER]

The large majority of commercially available multiple-input multiple-output (MIMO) radio channel measurement devices (sounders) is based on time-division multiplexed switching (TDMS) of a single transmit/receive radio frequency chain into the elements of a transmit/receive antenna array. While being cost-effective, such a solution can cause significant measurement errors due to phase noise and frequency offset in the local oscillators. In this paper, we systematically analyze the resulting errors and show that, in practice, overestimation of channel capacity by several hundred percent can occur. Overestimation is caused by phase noise (and to a lesser extent by frequency offset), leading to an increase of the MIMO channel rank. Our analysis furthermore reveals that the impact of phase errors is, in general, most pronounced if the physical channel has low rank (typical for line-of-sight or poor scattering scenarios). The extreme case of a rank-1 physical channel is analyzed in detail. The capacity bounds derived in this paper show excellent agreement with measurement results. In light of the findings of this paper, the results obtained through MIMO channel measurement campaigns using TDMS-based channel sounders should be interpreted with great care. [ABSTRACT FROM AUTHOR]

Hilberg’s conjecture about natural language states that the mutual information between two adjacent long blocks of text grows like a power of the block length. The exponent in this statement can be upper bounded using the pointwise mutual information estimate computed for a carefully chosen code. The bound is the better, the lower the compression rate is, but there is a requirement that the code be universal. So as to improve a received upper bound for Hilberg’s exponent, in this paper, we introduce two novel universal codes, called the plain switch distribution and the preadapted switch distribution. Generally speaking, switch distributions are certain mixtures of adaptive Markov chains of varying orders with some additional communication to avoid the so-called catch-up phenomenon. The advantage of these distributions is that they both achieve a low compression rate and are guaranteed to be universal. Using the switch distributions, we obtain that a sample of a text in English is non-Markovian with Hilberg’s exponent being ≤0.83, which improves over the previous bound ≤0.94 obtained using the Lempel–Ziv code. [ABSTRACT FROM PUBLISHER]

We study the problem of off-policy evaluation in the multi-armed bandit model with bounded rewards, and develop minimax rate-optimal procedures under three settings. First, when the behavior policy is known, we show that the Switch estimator, a method that alternates between the plug-in and importance sampling estimators, is minimax rate-optimal for all sample sizes. Second, when the behavior policy is unknown, we analyze performance in terms of the competitive ratio, thereby revealing a fundamental gap between the settings of known and unknown behavior policies. When the behavior policy is unknown, any estimator must have mean-squared error larger—relative to the oracle estimator equipped with the knowledge of the behavior policy— by a multiplicative factor proportional to the support size of the target policy. Moreover, we demonstrate that the plug-in approach achieves this worst-case competitive ratio up to a logarithmic factor. Third, we initiate the study of the partial knowledge setting in which it is assumed that the minimum probability taken by the behavior policy is known. We show that the plug-in estimator is optimal for relatively large values of the minimum probability, but is sub-optimal when the minimum probability is low. In order to remedy this gap, we propose a new estimator based on approximation by Chebyshev polynomials that provably achieves the optimal estimation error. Numerical experiments on both simulated and real data corroborate our theoretical findings. [ABSTRACT FROM AUTHOR]

Lossy coding of correlated sources over a multiple access channel (MAC) is studied. First, a joint source-channel coding scheme is presented when the decoder has correlated side information. Next, the optimality of separate source and channel coding that emerges from the availability of a common observation at the encoders or side information at the encoders and the decoder is investigated. It is shown that separation is optimal when the encoders have access to a common observation whose lossless recovery is required at the decoder, and the two sources are independent conditioned on this common observation. Optimality of separation is also proved when the encoder and the decoder have access to shared side information conditioned on which the two sources are independent. These separation results obtained in the presence of side information are then utilized to provide a set of necessary conditions for the transmission of correlated sources over a MAC without side information. Finally, by specializing the obtained necessary conditions to the transmission of binary and Gaussian sources over a MAC, it is shown that they can potentially be tighter than the existing results in the literature, providing a novel converse for this fundamental problem. [ABSTRACT FROM AUTHOR]

This paper considers the Gaussian half-duplex relay channel (G-HD-RC): a channel model where a source transmits a message to a destination with the help of a relay that cannot transmit and receive at the same time. It is shown that the cut-set upper bound on the capacity can be achieved to within a constant gap, regardless of the actual value of the channel parameters, by either partial-decode-and-forward or compress-and-forward. The performance of these coding strategies is evaluated with both random and deterministic switch at the relay. Numerical evaluations show that the actual gap is less than what analytically obtained, and that random switch achieves higher rates than deterministic switch. As a result of this analysis, the generalized degrees-of-freedom of the G-HD-RC is exactly characterized for this channel. In order to get insights into practical schemes for the G-HD-RC that are less complex than partial-decode-and-forward or compress-and-forward, the exact capacity of the linear deterministic approximation (LDA) of the G-HD-RC at high signal-to-noise-ratio is determined. It is shown that random switch and correlated nonuniform inputs bits are optimal for the LDA. It is then demonstrated that deterministic switch is to within one bit from the capacity. This latter scheme is translated into a coding strategy for the original G-HD-RC and its optimality to within a constant gap is proved. The gap attained by this scheme is larger than that of partial-decode-and-forward, thereby pointing to an interesting practical tradeoff between gap to capacity and complexity. [ABSTRACT FROM AUTHOR]

Rare events can potentially occur in many applications. When manifested as opportunities to be exploited, risks to be ameliorated, or certain features to be extracted, such events become of paramount significance. Due to their sporadic nature, the information-bearing signals associated with rare events often lie in a large set of irrelevant signals and are not easily accessible. This paper provides a statistical framework for detecting such events so that an optimal balance between detection reliability and agility, as two opposing performance measures, is established. The core component of this framework is a sampling procedure that adaptively and quickly focuses the information-gathering resources on the segments of the dataset that bear the information pertinent to the rare events. Particular focus is placed on Gaussian signals with the aim of detecting signals with rare mean and variance values. [ABSTRACT FROM AUTHOR]

In the framework of prediction of individual sequences, sequential prediction methods are to be constructed that perform nearly as well as the best expert from a given class. We consider prediction strategies that compete with the class of switching strategies that can segment a given sequence into several blocks, and follow the advice of a different “base” expert in each block. As usual, the performance of the algorithm is measured by the regret defined as the excess loss relative to the best switching strategy selected in hindsight for the particular sequence to be predicted. In this paper, we construct prediction strategies of low computational cost for the case where the set of base experts is large. In particular, we provide a method that can transform any prediction algorithm \cal A that is designed for the base class into a tracking algorithm. The resulting tracking algorithm can take advantage of the prediction performance and potential computational efficiency of \cal A in the sense that it can be implemented with time and space complexity only O(n^\gamma \ln n) times larger than that of \cal A, where n is the time horizon and \gamma \geq 0 is a parameter of the algorithm. With \cal A properly chosen, our algorithm achieves a regret bound of optimal order for \gamma > 0, and only O(\ln n) times larger than the optimal order for \gamma =0 for all typical regret bound types we examined. For example, for predicting binary sequences with switching parameters under the logarithmic loss, our method achieves the optimal O(\ln n) regret rate with time complexity O(n^1+\gamma \ln n) for any \gamma \in (0,1). [ABSTRACT FROM PUBLISHER]

This paper investigates the following general problem relating to ordered random processes: given n independent but not necessarily identical random processes, how frequently, on average, does any given process become one of the pth (p=1,2,\ldots, n-1) largest processes? This is a fundamental problem arising in the design and analysis of contemporary multidimensional wireless communication systems (e.g., multiantenna, multiuser) employing opportunistic selection. We formulate this problem as one involving the level crossing rate (LCR) of a carefully defined ordered random process across the zero threshold, which we solve by developing a new mathematical framework based on the theory of permanents. For the case where the processes correspond to time-varying Rayleigh fading channels, we present exact closed-form formulas for the LCR, simplified tight upper bounds, as well as asymptotic results for n and p approaching infinity but with fixed ratio. These results reveal interesting fundamental limits for the LCR, and are shown to given meaningful insight even for small values of n and p. We further use our mathematical framework to characterize the required per-branch and overall switching rate of a generalized selection combining diversity receiver, allowing for different average powers for each branch. With the aid of majorization theory, we demonstrate that the overall switching rate is maximized when the power delay profile is uniform. [ABSTRACT FROM PUBLISHER]

Cross-bifix-free sets are sets of words such that no prefix of any word is a suffix of any other word. In this paper, we introduce a general constructive method for the sets of cross-bifix-free binary words of fixed length. It enables us to determine a cross-bifix-free words subset which has the property to be non-expandable. [ABSTRACT FROM PUBLISHER]

The problem of finding the rate-distortion function of an arbitrarily varying source (AVS) composed of a finite number of memoryless subsources is revisited. Berger's 1971 paper “The Source Coding Game” solves this problem when the adversary is allowed only strictly causal access to the subsource realizations. The case when the adversary has access to the subsource realizations non-causally is considered. This new rate-distortion function is determined to be the maximum of the rate-distortion function over a set of independent and identically distributed (IID) random variables that can be simulated by the adversary. The results are extended to allow for partial or noisy observations of subsource realizations. The model is further explored by attempting to find the rate-distortion function when the ‘adversary’ is actually helpful. Finally, a bound is developed on the uniform continuity of the IID rate-distortion function for finite-alphabet sources. The bound is used to give a sufficient number of distributions that need to be sampled to compute the rate-distortion function of an AVS to within a desired accuracy. The bound is also used to give a rate of convergence for the estimate of the rate-distortion function for an unknown IID source. [ABSTRACT FROM AUTHOR]

Neuroscientists have recently shown that images that are difficult to find in visual search elicit similar patterns of firing across a population of recorded neurons. The L^1 distance between firing rate vectors associated with two images was strongly correlated with the inverse of decision time in behavior. But why should decision times be correlated with L^1 distance? What is the decision-theoretic basis? In our decision theoretic formulation, we model visual search as an active sequential hypothesis testing problem with switching costs. Our analysis suggests an appropriate neuronal dissimilarity index, which correlates equally strongly with the inverse of decision time as the L^1 distance. We also consider a number of other possibilities, such as the relative entropy (Kullback–Leibler divergence) and the Chernoff entropy of the firing rate distributions. A more stringent test of equality of means, which would have provided a strong backing for our modeling, fails for our proposed as well as the other already discussed dissimilarity indices. However, test statistics from the equality of means test, when used to rank the indices in terms of their ability to explain the observed results, places our proposed dissimilarity index at the top followed by relative entropy, Chernoff entropy, and the L^1 indices. Computations of the different indices require an estimate of the relative entropy between two Poisson point processes. An estimator is developed and is shown to have near unbiased performance for almost all operating regions. [ABSTRACT FROM AUTHOR]

We introduce a new family of codes, termed asymmetric Lee distance (ALD) codes, designed to correct errors arising in DNA-based storage systems and systems with parallel string transmission protocols. ALD codes are defined over a quaternary alphabet and analyzed in this particular setting, but the derived results hold for other alphabet sizes as well. Our technical contributions are twofold. First, we derive upper bounds on the size of the codes under the ALD metric based on linear programming techniques. Second, we propose a number of code constructions, which imply lower bounds. [ABSTRACT FROM AUTHOR]

The $K$ -user multiple-input and multiple-output (MIMO) broadcast channel (BC) with no channel state information at the transmitter is considered, where each receiver is assumed to be equipped with either conventional antennas or reconfigurable antennas in which each reconfigurable antenna is capable of choosing a subset of receiving modes from several preset modes. Under general antenna configurations, the sum linear degrees of freedom (DoFs) of the $K$ -user MIMO BC with reconfigurable antennas are completely characterized, which corresponds to the maximum sum DoF achievable by linear coding strategies. [ABSTRACT FROM PUBLISHER]

We consider a multi-hypothesis testing problem involving a $K$ -armed bandit. Each arm’s signal follows a distribution from a vector exponential family. The actual parameters of the arms are unknown to the decision maker. The decision maker incurs a delay cost for delay until a decision and a switching cost whenever he switches from one arm to another. His goal is to minimise the overall cost until a decision is reached on the true hypothesis. Of interest are policies that satisfy a given constraint on the probability of false detection. This is a sequential decision making problem where the decision maker gets only a limited view of the true state of nature at each stage, but can control his view by choosing the arm to observe at each stage. An information-theoretic lower bound on the total cost (expected time for a reliable decision plus total switching cost) is first identified, and a variation on a sequential policy based on the generalised likelihood ratio statistic is then studied. Due to the vector exponential family assumption, the signal processing at each stage is simple; the associated conjugate prior distribution on the unknown model parameters enables easy updates of the posterior distribution. The proposed policy, with a suitable threshold for stopping, is shown to satisfy the given constraint on the probability of false detection. Under a continuous selection assumption, the policy is also shown to be asymptotically optimal in terms of the total cost among all policies that satisfy the constraint on the probability of false detection. [ABSTRACT FROM AUTHOR]

We study online combinatorial optimization problems that a learner is interested in minimizing its cumulative regret in the presence of switching costs. To solve such problems, we propose a version of the follow-the-perturbed-leader algorithm in which the cumulative losses are perturbed by independent symmetric random walks. In the general setting, our forecaster is shown to enjoy near-optimal guarantees on both quantities of interest, making it the best known efficient algorithm for the studied problem. In the special case of prediction with expert advice, we show that the forecaster achieves an expected regret of the optimal order $O{{(n\log N)}^{1/2})}$ , where $n$ is the time horizon and $N$ is the number of experts, while guaranteeing that the predictions are switched at most $O{{(n\log N)}^{1/2})}$ times, in expectation. [ABSTRACT FROM PUBLISHER]

In a fault tolerant quantum computer, quantum codes are expected to serve the conflicting purposes of protecting quantum information while also allowing that information to be manipulated by fault-tolerant gates. We introduce a new technique for placing limitations on such gates, and apply this technique to a class of quantum codes known as hypergraph product codes contained within the vertical sector. These codes are constructed from input which is a pair of classical linear codes, and generalize the Kitaev surface code which is the hypergraph product of classical repetition codes. We provide a necessary condition on these input codes, under which the resulting hypergraph product code has transversal gates limited to the Clifford group. We conjecture that this condition is satisfied by all $[n,k,d]$ Gallagher codes with $d\ge 3$ and $k\le n/2$. This work is a generalization of an argument due to Bravyi and König, and we also conjecture this is a refinement of the recent notion of disjointness due to Jochym-O’Connor et al. [ABSTRACT FROM AUTHOR]

We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalization of the concept of universal coding. We describe a graphical language based on hidden Markov models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical contributions, we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analyzing the individual sequence regret of parameterized models. [ABSTRACT FROM AUTHOR]

We consider multiterminal source coding with a single encoder and multiple decoders where either the encoder or the decoders can take cost-constrained actions which affect the quality of the side information present at the decoders. For the scenario where decoders take actions, we characterize the rate–cost tradeoff region for lossless source coding, and give an achievability scheme for lossy source coding for two decoders which is optimum for a variety of special cases of interest. For the case where the encoder takes actions, we characterize the rate–cost tradeoff for a class of lossless source coding scenarios with multiple decoders. Finally, we also consider extensions to other multiterminal source coding settings with actions, and characterize the rate–distortion–cost tradeoff for a case of successive refinement with actions. [ABSTRACT FROM PUBLISHER]

We consider the cascade and triangular rate-distortion problem where side information is known to the source encoder and to the first user but not to the second user. We characterize the rate-distortion region for these problems, as well as some of their extensions. For the quadratic Gaussian case, we show that it is sufficient to consider jointly Gaussian distributions, which leads to an explicit solution. [ABSTRACT FROM PUBLISHER]

In multi-stream sequential change-point detection it is assumed that there are $M$ processes in a system and at some unknown time, an occurring event changes the distribution of the samples of a particular process. In this article, we consider this problem under a sampling control constraint when one is allowed, at each point in time, to sample a single process. The objective is to raise an alarm as quickly as possible subject to a proper false alarm constraint. We show that under sampling control, a simple myopic-sampling-based sequential change-point detection strategy is second-order asymptotically optimal when the number $M$ of processes is fixed. This means that the proposed detector, even by sampling with a rate $1/M$ of the full rate, enjoys the same detection delay, up to some additive finite constant, as the optimal procedure. Simulation experiments corroborate our theoretical results. [ABSTRACT FROM AUTHOR]

A functional k-Private Information Retrieval (k-PIR) code of dimension s consists of $n$ servers storing linear combinations of s linearly independent information symbols. Any linear combination of the s information symbols can be recovered by k disjoint subsets of servers. The goal is to find the minimum number of servers for given k and s. We provide lower bounds on the minimum number of servers and constructions which yield upper bounds on this number. For k ≤ 4, exact bounds on this number are proved. Furthermore, we provide some asymptotic bounds. The problem coincides with the well known PIR problem based on a coded database to reduce the storage overhead, when each linear combination contains exactly one information symbol. If any multiset of size k of linear combinations from the linearly independent information symbols can be recovered by k disjoint subset of servers, then the servers form a functional k -batch code. A functional k-batch code is a functional k-PIR code, where all the k linear combinations in the multiset are equal. We provide some bounds on the minimum number of servers for functional k-batch codes. In particular we present a random construction and a construction based on simplex codes, Write-Once Memory (WOM) codes, and Random I/O (RIO) codes. [ABSTRACT FROM AUTHOR]

Secure communication over a wiretap channel is investigated, in which an active adversary modifies the state of the channel and the legitimate transmitter has the opportunity to sense and learn the adversary’s actions. The adversary has the ability to switch the channel state and observe the corresponding output at every channel use while the encoder has causal access to observations that depend on the adversary’s actions. A joint learning/transmission scheme is developed in which the legitimate users learn and adapt to the adversary’s actions. For some channel models, it is shown that the achievable rates, defined precisely for the problem, are arbitrarily close to those obtained with hindsight, had the transmitter known the actions ahead of time. This initial study suggests that there is much to exploit and gain in physical-layer security by learning the adversary, e.g., monitoring the environment. [ABSTRACT FROM AUTHOR]

We consider authentication of messages sent from transmitters to a receiver over a multiple access channel, where each transmitter shares a secret key with the legitimate receiver. Additionally, there exists a computationally unbounded opponent who has access to noisy observations of the messages transmitted and can initiate impersonation or substitution attacks. We require that the legitimate receiver must be able to authenticate the messages he receives with respect to predetermined groups of transmitters, but at the same time must be kept ignorant of the transmitter’s identity of a given message in a given group. We propose an information-theoretic formulation of these anonymity constraints as well as an authentication coding scheme for which the asymptotic probability of successful attack is shown to optimally scale with the length of the secret keys shared between each transmitter and the legitimate receiver. Our results quantify the positive impact of the multiple access setting compared to the single-user setting on the probability of successful attack. [ABSTRACT FROM AUTHOR]

We consider a discrete-time distributed averaging algorithm over multi-agent networks with measurement noises and time-varying random graphs. Each agent updates its state by a weighted sum of pairwise state differences between its neighbors and itself with both additive and multiplicative measurement noises. The network structure is modeled by a sequence of time-varying random digraphs, which may be spatially and temporally dependent. By stochastic Lyapunov method and the combination of algebraic graph theory and martingale convergence theory, we obtain sufficient conditions for stochastic approximation type algorithms to achieve mean square and almost sure average consensus. We prove that all states of the agents converge to a common random variable, whose mathematical expectation is the average of initial values, in mean square and almost surely if the sequence of digraphs is conditionally balanced and uniformly conditionally jointly connected. An upper bound of the variance of the limit random variable, that is, the mean square steady-state error for stochastic average consensus is given quantitatively related to the weights, the algorithm gain and the energy level of the noises. [ABSTRACT FROM AUTHOR]

Complex information-processing systems, for example, quantum circuits, cryptographic protocols, or multi-player games, are naturally described as networks composed of more basic information-processing systems. A modular analysis of such systems requires a mathematical model of systems that is closed under composition, i.e., a network of these objects is again an object of the same type. We propose such a model and call the corresponding systems causal boxes. Causal boxes capture superpositions of causal structures, e.g., messages sent by a causal box $A$ can be in a superposition of different orders or in a superposition of being sent to box $B$ and box $C$ . Furthermore, causal boxes can model systems whose behavior depends on time. By instantiating the abstract cryptography framework with causal boxes, we obtain the first composable security framework that can handle arbitrary quantum protocols and relativistic protocols. [ABSTRACT FROM AUTHOR]

We address the task of switching off the Hamiltonian of a system by removing all internal and system-environment couplings. We propose dynamical decoupling schemes that use only bounded-strength controls for quantum many-body systems with local system Hamiltonians and local environmental couplings. To do so, we introduce the combinatorial concept of balanced-cycle orthogonal arrays (BOAs) and show how to construct them from classical error-correcting codes. The derived decoupling schemes may be useful as a primitive for more complex schemes, e.g., for Hamiltonian simulation. For the case of $n$ qubits and a two-local Hamiltonian, the length of the resulting decoupling scheme scales as O(n \log n)$ , improving over the previously best-known schemes that scaled quadratically with n$ . More generally, using BOAs constructed from families of Bose-Chaudhuri-Hocquenghem (BCH) codes, we show that bounded-strength decoupling for any \ell , can be achieved using decoupling schemes of length at most O(n^{\ell -1} \log n) . [ABSTRACT FROM AUTHOR]

A theoretical foundation for any turbo interleaver to be a contention-free interleaver to access data in parallel by a butterfly network is presented. A contention-free parallel access of multiple memories in parallel plays a crucial role for implementing high speed turbo decoders for high data rate applications. The presented theoretical analysis shows that a butterfly network has a sufficiently rich permutation structure to be a routing network between parallel decoder units and multiple memories. Thus turbo code design is independent of the designing of a contention-free parallel access by butterfly networks. In particular, a turbo interleaver needs not to provide a built-in contention-free parallel access for any parallel access by butterfly networks. We demonstrate how to apply this theory to turbo interleavers widely used in commercial telecommunication standards. [ABSTRACT FROM PUBLISHER]

We study the problem of deinterleaving a set of finite-memory (Markov) processes over disjoint finite alphabets, which have been randomly interleaved by a finite-memory switch. The deinterleaver has access to a sample of the resulting interleaved process, but no knowledge of the number or structure of the component Markov processes, or of the switch. We study conditions for uniqueness of the interleaved representation of a process, showing that certain switch configurations, as well as memoryless component processes, can cause ambiguities in the representation. We show that a deinterleaving scheme based on minimizing a penalized maximum-likelihood cost function is strongly consistent, in the sense of reconstructing, almost surely as the observed sequence length tends to infinity, a set of component and switch Markov processes compatible with the original interleaved process. Furthermore, under certain conditions on the structure of the switch (including the special case of a memoryless switch), we show that the scheme recovers all possible interleaved representations of the original process. Experimental results are presented demonstrating that the proposed scheme performs well in practice, even for relatively short input samples. [ABSTRACT FROM AUTHOR]

The Bayesian formulation of sequentially testing M \geq 3 hypotheses is studied in the context of a decentralized sensor network system. In such a system, local sensors observe raw observations and send quantized sensor messages to a fusion center which makes a final decision when stopping taking observations. Asymptotically optimal decentralized sequential tests are developed from a class of “two-stage” tests that allows the sensor network system to make a preliminary decision in the first stage and then optimize each local sensor quantizer accordingly in the second stage. It is shown that the optimal local quantizer at each local sensor in the second stage can be defined as a maximin quantizer which turns out to be a randomization of at most M-1 unambiguous likelihood quantizers (ULQ). We first present in detail our results for the system with a single sensor and binary sensor messages, and then extend to more general cases involving any finite alphabet sensor messages, multiple sensors, or composite hypotheses. [ABSTRACT FROM AUTHOR]

The problem of serving multicast flows in a crossbar switch is considered. Intraflow linear network coding is shown to achieve a larger rate region than the case without coding. A traffic pattern is presented which is achievable with coding but requires a switch speedup when coding is not allowed. The rate region with coding can be characterized in a simple graph-theoretic manner, in terms of the stable set polytope of the “enhanced conflict graph”. No such graph-theoretic characterization is known for the case of fanout-splitting without coding. The minimum speedup needed to achieve 100% throughput with coding is shown to be upper bounded by the imperfection ratio of the enhanced conflict graph, where the imperfection ratio measures a certain graph theoretic property of the given graph. When applied to K \times N switches with unicasts and broadcasts only, this gives a bound of \min (2K-1\overK,2N\overN+1) on the speedup. This shows that speedup, which is usually implemented in hardware, can often be substituted by network coding, which can be done in software. Computing an offline schedule (using prior knowledge of the flow rates) is reduced to fractional weighted graph coloring. A graph-theoretic online scheduling algorithm (using only queue occupancy information) is also proposed, that stabilizes the queues for all rates within the rate region. [ABSTRACT FROM AUTHOR]

We formally define the gradual removal problem in wireless networks, where the smallest number of users should be removed due to infeasibility of the target-SIR requirements for all users, and present a distributed power-control algorithm with temporary removal and feasibility check (DFC) to address it. The basic idea is that any transmitting user whose required transmit power for reaching its target-SIR exceeds its maximum power is temporarily removed, but resumes its transmission if its required transmit power goes below a given threshold obtained in a distributed manner. This enables users to check the feasibility of system in a distributed manner. The existence of at least one fixed-point in DFC is guaranteed, and at each equilibrium, all transmitting users reach their target-SIRs consuming the minimum aggregate transmit power. Furthermore, in contrast to the existing algorithms, no user is unnecessarily removed by DFC, i.e., DFC is Pareto and energy-efficient. We also show that when target-SIRs are the same for all users, DFC minimizes the outage probability. Simulation results confirm our analytical developments and show that DFC significantly outperforms the existing schemes in addressing the gradual removal problem in terms of convergence, outage probability, and power consumption. [ABSTRACT FROM AUTHOR]