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The article discusses brief profile of several awardees of the 2013 IEEE Information Theory Society Paper Award including Shrinivas Kudekar, Thomas J. Richardson and Rüdiger L. Urbanke. Kadoka has completed his bachelor's degree in electrical engineering from the Indian Institute Of Technology (IIT) in Bombay, India in 2003, Richardson is working as vice-president at Semiconductors Company Qualcomm Inc. and Urbane is involved in designing of iterative coding schemes.

The article discusses brief profile of several awardees of the 2013 IEEE Communications Society and Information Theory Society Joint Paper Award including Salman Avestimehr, Bobak Nazer and Michael Gastpar. Gastpar has served as an associate editor for shannon theory for the journal. Nazer has received various awards such as the Dean's Catalyst Award, the NSF CAREER Award and the Eli Jury Award. Gatspar is working as an adjunct associate professor at the University of California, Berkeley.

The article announces Institute of Electrical and Electronics Engineers's (IEEE) Information Theory Society Paper Award given to various authors including 2011 IEEE Information Theory Society Paper Award to Masahito Hayashi and 2008 and 2010 Best Student Paper Awards to Yury Polyanskiy.

We consider a variable-length source coding problem subject to local decodability constraints. In particular, we investigate the blocklength scaling behavior attainable by encodings of $r$ -sparse binary sequences, under the constraint that any source bit can be correctly decoded upon probing at most $d$ codeword bits. We consider both adaptive and non-adaptive access models, and derive upper and lower bounds that often coincide up to constant factors. Such a characterization for the fixed-blocklength analog of our problem, known as the bit probe complexity of static membership, remains unknown despite considerable attention from researchers over the last few decades. We also show that locally decodable schemes for sparse sequences are able to decode 0s (frequent source symbols) of the source with far fewer probes on average than they can decode 1s (infrequent source symbols), thus rigorizing the notion that infrequent symbols require high probe complexity, even on average. Connections to the fixed-blocklength model and to communication complexity are also briefly discussed. [ABSTRACT FROM AUTHOR]

The article announces 2015 IEEE Information Theory Society Paper Award given to Itzhak Tamo and Alexander Barg for the paper "A Family of Optimal Locally Recoverable Codes."

The article offers information on the 2015 IEEE Communications Society and Information Theory Society Joint Paper Awards given to Mohammad Ali Maddah-Ali and David Tse for the paper "Completely Stale Transmitter Channel State Information is Still Very Useful."

This article presents information about recipients of the 2008 IEEE Information Theory Society Paper Award. David Donoho received the award for his paper entitled "Compressed Sensing" and Emmanuel Candès and Terence Tao also received the award for their paper entitled "Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?"

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These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

The article presents the award given to Tsachy Weissman, Eric Ordentlich, Gadiel Seroussi, Sergio Verdú and Marcelo Weinberger for their paper on universal discrete denoising, which was published in the January 2005 issue of the periodical. The 2006 Institute of Electrical and Electronics Engineers, Inc. (IEEE) Communications Society and Information Theory Society Joint Paper Award consisted of a plaque and an honorarium.

The article presents information on the 2005 Communications Society and Information Theory Society Joint Paper Award, which is given annually to an outstanding paper that was published in any of the two societies' publications during the preceding year. This year the award was given to researchers Nihar Jindal, Sriram Vishwanath, and Andrea Goldsmith for their paper "On the Duality of Gaussian Multiple-Access and Broadcast Channels," which appeared in the 2004 issue of the journal "IEEE Transaction on Information Theory." Jindal has done his B.S. in electrical engineering and computer science from the University of California in Berkeley, in 1999. His research work is in the field of the applications of communication and information theory to wireless communication, with a particular focus on multiple-antenna multi-user channels, dynamic resource allocation, sensor and ad hoc networks. Vishwanath's is currently working as an assistant professor in the Department of Electrical and Computer Engineering at the University of Texas in Austin. Goldsmith works as an assistant professor of electric engineering at Stanford University. She has done research in the field of wireless communication, information theory and adaptive resource allocation in wireless networks.

The article presents information on the 2005 Information Theory Society Paper Award, which is given annually to for a valuable publication in the field of information theory. This year the award was jointly awarded to researchers Shuo-Yen Robert Li, Raymond W. Yeung, and Ning Cai for their paper "Linear Network Coding" which appeared in the February 2003 issue of the journal "IEEE Transactions on Information Theory." Shuo-Yen Robert Li has done his B.S. in mathematics from National Taiwan University in 1970 and Ph.D. in mathematics from the University of California, Berkeley, in 1974. Yeung was born in Hong Kong on June 3, 1962. He has done B.S., M.Eng., Ph.D. in electrical engineering from Cornell University in Ithaca, New York. His research work include information theory and network coding. Ning Cai has done his B.S. in mathematics from the Normal College of Beijing in Beijing, China in 1982. He completed his Ph.D. in mathematics from the University of Bielefeld in Bielefeld, Germany in 1988. He has done research in the field of combinatorics, information theory and their applications.

The article presents information about the 2004 IEEE Information Theory Society Paper Award. The award was given to Ralf Koetter and Alexander Vardy for their paper "Algebraic Soft-Decision Decoding of Reed-Solomon Codes," which appeared in the IEEE Transactions on Information Theory, vol. 49, pp. 2809-2825, November 2003. The IEEE Information Theory Society Paper award, consisting of a plaque and an honorarium, is given annually for an outstanding publication in the field of information theory published anywhere during the preceding two-year period. Its purpose is to recognize exceptional publications in the field and to stimulate interest in, and encourage contributions to, the discipline. The award winner Ralf Koetter received the diploma degree in electrical engineering from the Technical University of Darmstadt, Germany, in 1990 and the Ph.D. degree from Sweden. Another winner Alexander Vardy was born in Moscow in 1963. He received the B.Sc. degree from the Technion, Haifa, Israel, in 1985 and the Ph.D. degree from the Tel-Aviv University, Israel, in 1991.

This paper studies the effectiveness of relaying for interference mitigation in an interference-limited communication scenario. We are motivated by the observation that in a cellular network, a relay node placed at the cell edge observes a combination of intended signal and inter-cell interference that is correlated with the received signal at a nearby destination, so a relaying link can effectively allow the antennas at the relay and at the destination to be pooled together for both signal enhancement and interference mitigation. We model this scenario by a multiple-input multiple-output (MIMO) Gaussian relay channel with a digital relay-to-destination link of finite capacity, and with correlated noise across the relay and destination antennas. Assuming a compress-and-forward strategy with Gaussian input distribution and quantization noise, we propose a coordinate ascent algorithm for obtaining a stationary point of the non-convex joint optimization of the transmit and quantization covariance matrices. For fixed input distribution, the globally optimum quantization noise covariance matrix can be found in closed-form using a transformation for the relay’s observation that simultaneously diagonalizes two conditional covariance matrices by congruence. For fixed quantization, the globally optimum transmit covariance matrix can be found via convex optimization. This paper further shows that such an optimized achievable rate is within a constant additive gap of the MIMO relay channel capacity. The optimal structure of the quantization noise covariance enables a characterization of the slope of the achievable rate as a function of the relaying link capacity. Moreover, this paper shows that the improvement in spatial degrees of freedom by MIMO relaying in the presence of noise correlation is related to the aforementioned slope via a connection to the deterministic relay channel. [ABSTRACT FROM AUTHOR]

This paper studies the problem of estimating the covariance of a collection of vectors using only highly compressed measurements of each vector. An estimator based on back-projections of these compressive samples is proposed and analyzed. A distribution-free analysis shows that by observing just a single linear measurement of each vector, one can consistently estimate the covariance matrix, in both infinity and spectral norm, and this analysis leads to precise rates of convergence in both norms. Through information-theoretic techniques, lower bounds showing that this estimator is minimax-optimal for both infinity and spectral norm estimation problems are established. These results are also specialized to give matching upper and lower bounds for estimating the population covariance of a collection of Gaussian vectors, again in the compressive measurement model. The analysis conducted in this paper shows that the effective sample complexity for this problem is scaled by a factor of $m^{2}/d^{2}$ , where $m$ is the compression dimension and $d$ is the ambient dimension. Applications to subspace learning (principal components analysis) and learning over distributed sensor networks are also discussed. [ABSTRACT FROM AUTHOR]

The problem of universal source coding for binary trees is considered. Zhang, Yang, and Kieffer derived upper bounds on the average-case redundancy of codes based on directed acyclic graph (DAG) compression for binary tree sources with certain properties. In this paper, a natural class of binary tree sources is presented such that the demanded properties are fulfilled. Moreover, for both subclasses considered in the paper of Zhang, Yang, and Kieffer, their result is improved by deriving bounds on the maximal pointwise redundancy (or worst-case redundancy) instead of the average-case redundancy. Finally, using context-free tree grammars instead of DAGs, upper bounds on the maximal pointwise redundancy for certain binary tree sources are derived. This yields universal codes for new classes of binary tree sources. [ABSTRACT FROM AUTHOR]

For memoryless sources, delayed side information at the decoder does not improve the rate-distortion function. However, this is not the case for sources with memory, as demonstrated by a number of works focusing on the special case of (delayed) feedforward. In this paper, a setting is studied in which the encoder is potentially uncertain about the delay with which measurements of the side information, which is available at the encoder, are acquired at the decoder. Assuming a hidden Markov model for the source sequences, at first, a single-letter characterization is given for the setup where the side information delay is arbitrary and known at the encoder, and the reconstruction at the destination is required to be asymptotically lossless. Then, with delay equal to zero or one source symbol, a single-letter characterization of the rate-distortion region is given for the case where, unbeknownst to the encoder, the side information may be delayed or not. Finally, examples for binary and Gaussian sources are provided. [ABSTRACT FROM PUBLISHER]

The article announces that Aliazam Abbasfar, Dariush Divsalar, and Kung Yao have received the 2008 IEEE Communications Society and Information Theory Society Joint Paper Award.

The article reports on the presentation of the 2007 IEEE Information Theory Society Paper Award to Hanan Weingarten, Yossef Steinberg and Shlomo Shamai for their article "The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel," published in the September 2006 issue of the periodical "IEEE Transactions on Information Theory".

The article announces that Marco Dalai, electronic engineer, has received the 2014 Institute of Electrical and Electronics Engineers (IEEE) Information Theory Society Paper Award, for the paper "Lower Bounds on the Probability of Error for Classical and Classical-Quantum Channels" in December 2013.

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This paper provides a link between matroid theory and locally repairable codes (LRCs) that are either linear or more generally almost affine. Using this link, new results on both LRCs and matroid theory are derived. The parameters $(n,k,d,r,\delta )$ of LRCs are generalized to matroids, and the matroid analog of the generalized singleton bound by Gopalan et al. for linear LRCs is given for matroids. It is shown that the given bound is not tight for certain classes of parameters, implying a nonexistence result for the corresponding locally repairable almost affine codes that are coined perfect in this paper. Constructions of classes of matroids with a large span of the parameters $(n,k,d,r,\delta )$ and the corresponding local repair sets are given. Using these matroid constructions, new LRCs are constructed with prescribed parameters. The existence results on linear LRCs and the nonexistence results on almost affine LRCs given in this paper strengthen the nonexistence and existence results on perfect linear LRCs given by Song et al. [ABSTRACT FROM AUTHOR]

The article lists the recipients of the 2014 Institute of Electrical and Electronics Engineers (IEEE) Communications Society and Information Theory Society Joint Paper Award including software developer Huseyin Simitci, electrical engineer Cheng Huang and researcher Parikshit Gopalan.

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

This paper investigates the Gaussian state-dependent interference channel (IC) and Z-IC, in which two receivers are corrupted respectively by two different but correlated states that are noncausally known to two transmitters but are unknown to the receivers. Three interference regimes are studied, and the capacity region boundary or the sum capacity boundary is characterized either fully or partially under various channel parameters. In particular, the impact of the correlation between states on cancellation of state and interference as well as achievability of capacity is explored with numerical illustrations. For the very strong interference regime, the capacity region is achieved by the scheme where the two transmitters implement a cooperative dirty paper coding. For the strong but not very strong interference regime, the sum-rate capacity is characterized by rate splitting, layered dirty paper coding, and successive cancellation. For the weak interference regime, the sum-rate capacity is achieved via dirty paper coding individually at two receivers as well as treating interference as noise. This paper also provides the achievable region for the state-dependent IC with each state known at its corresponding transmitter. [ABSTRACT FROM AUTHOR]

In this paper, we establish some criteria to decide when a discrete memoryless channel admits a metric in such a way that the maximum likelihood decoding coincides with the nearest neighbor decoding. In particular, we prove a conjecture presented by M. Firer and J. L. Walker, establishing that every binary asymmetric channel admits a matched metric. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to construct pliable fractional repetition (FR) codes that are locally recoverable for distributed storage systems (DSSs). FR codes are integral in constructing a class of distributed storage codes with exact repair by transfer. Pliable FR codes are a new type of FR codes in which both the per-node storage and repetition degree can easily be adjusted simultaneously; thus, pliable FR codes are vital for DSSs in which parameters can dynamically change over time. However, the constructions of pliable FR codes with repair locality remain unknown. In addition, the tradeoffs between the code minimum distance of an FR code and its repair locality are not fully understood. To address these problems, this paper first presents general results regarding FR codes. Subsequently, this paper presents an improved Singleton-like bound for locally recoverable FR codes under an additional requirement that each node must be part of a local structure that, upon failure, allows it to be exactly recovered by a simple download process. Moreover, this paper proposes a construction of locally recoverable FR codes that can achieve the proposed Singleton-like bound; this construction is based on bipartite graphs with a given girth. In particular, this paper also proposes a general bipartite-graph-based approach to constructing optimal pliable FR codes with and without repair localities; in this approach, a new family of bipartite graphs, called matching-feasible graphs, is introduced. Finally, this paper proposes the explicit constructions of optimal pliable FR codes by using a family of matching-feasible graphs with arbitrary large girth. Notably, in addition to attaining a Singleton-like bound for FR codes, the explicit pliable FR codes are optimal locally recoverable FR codes from two perspectives of repair locality. The explicit pliable FR codes can also be used as FR batch codes to provide load balancing in DSSs. [ABSTRACT FROM AUTHOR]

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These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

Linear codes achieving or nearly achieving the Singleton bound are interesting in both theory and practice. The objective of this paper is to construct several infinite families of MDS, near MDS and almost MDS codes from some special cyclic subgroups of ${\mathbb {F}}_{q^{2}}^{*}$. To this end, the augmentation and extension techniques are used. The codes in this paper have flexible parameters and their lengths could be large. The minimum linear locality of the codes constructed in this paper is also studied. Some infinite families of optimal linearly locally recoverable codes are obtained. Besides, some codes in this paper are proved to be proper for error detection. [ABSTRACT FROM AUTHOR]

A functional $k$ -batch code of dimension $s$ consists of $n$ servers storing linear combinations of $s$ linearly independent information bits. Any multiset request of size $k$ of linear combinations (or requests) of the information bits can be recovered by $k$ disjoint subsets of the servers. The goal under this paradigm is to find the minimum number of servers for given values of $s$ and $k$. A recent conjecture states that for any $k=2^{s-1}$ requests the optimal solution requires $2^{s}-1$ servers. This conjecture is verified for $s \leqslant 5$ but previous work could only show that codes with $n=2^{s}-1$ servers can support a solution for $k=2^{s-2} + 2^{s-4} + \left \lfloor{ \frac { 2^{s/2}}{\sqrt {24}} }\right \rfloor $ requests. This paper reduces this gap and shows the existence of codes for $k=\lfloor \frac {5}{6}2^{s-1} \rfloor - s$ requests with the same number of servers. Another construction in the paper provides a code with $n=2^{s+1}-2$ servers and $k=2^{s}$ requests, which is an optimal result. These constructions are mainly based on extended Simplex codes and equivalently provide constructions for parallel Random I/O (RIO) codes. [ABSTRACT FROM AUTHOR]

In general coding theory, we often assume that error is observed in transferring or storing encoded symbols, while the process of encoding itself is error-free. Motivated by recent applications of coding theory, in this paper, we consider the case where the process of encoding is distributed and prone to error. We introduce the problem of distributed encoding, comprised of a set of $K \in \mathbb {N}$ isolated source nodes and $N \in \mathbb {N}$ encoding nodes. Each source node has one symbol from a finite field, which is sent to each of the encoding nodes. Each encoding node stores an encoded symbol from the same field, as a function of the received symbols. However, some of the source nodes are controlled by the adversary and may send different symbols to different encoding nodes. Depending on the number of the adversarial nodes, denoted by $\beta \in \mathbb {N}$ , and the cardinality of the set of symbols that each one generates, denoted by $v \in \mathbb {N}$ , the process of decoding from the encoded symbols could be impossible. Assume that a decoder connects to an arbitrary subset of $t \in \mathbb {N}$ encoding nodes and wants to decode the symbols of the honest nodes correctly, without necessarily identifying the sets of honest and adversarial nodes. An important characteristic of a distributed encoding system is $t^{*} \in \mathbb {N}$ , the minimum of such $t$ , which is a function of $K$ , $N$ , $\beta $ , and $v$. In this paper, we study the distributed linear encoding system, i.e. one in which the encoding nodes use linear coding. We show that $t^{*}_{\textrm {Linear}}=K+2\beta (v-1)$ , if $N\ge K+2\beta (v-1)$ , and $t^{*}_{\textrm {Linear}}=N$ , if $N\le K+2\beta (v-1)$. In order to achieve $t^{*}_{\textrm {Linear}}$ , we use random linear coding and show that in any feasible solution that the decoder finds, the messages of the honest nodes are decoded correctly. In order to prove the converse of the fundamental limit, we show that when the adversary behaves in a particular way, it can always confuse the decoder between two feasible solutions that differ in the message of at least one honest node. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the convergence speed of the Arimoto-Blahut algorithm. For many channel matrices, the convergence speed is exponential, but for some channel matrices it is slower than exponential. By analyzing the Taylor expansion of the defining function of the Arimoto-Blahut algorithm, we will make the conditions clear for the exponential or slower convergence. The analysis of the slow convergence in this paper is new. Based on this analysis, we will compare the convergence speeds of the Arimoto-Blahut algorithm numerically with the values obtained in our theorems for several channel matrices. The purpose of this paper is to obtain a complete understanding of the convergence speed of the Arimoto-Blahut algorithm. [ABSTRACT FROM AUTHOR]

The state-dependent Gaussian interference channel (IC) and Z-IC are investigated, in which two receivers are corrupted by the same but differently scaled states. The state sequence is noncausally known at both transmitters, but not known at either receiver. Three interference regimes are studied, i.e., the very strong, strong, and weak regimes. In the very strong regime, the capacity region is characterized under certain channel parameters by designing a cooperative dirty paper coding between the two transmitters to fully cancel the state. In the strong regime, points on the capacity region boundary are characterized under certain channel parameters by designing an achievable scheme based on rate splitting, layered dirty paper coding, and successive state cancellation. In the weak regime, the sum capacity is obtained by independent dirty paper coding at two transmitters. For all the above regimes, the capacity achieves that of the IC/Z-IC without state. Comparison between the state-dependent regular IC and the Z-IC suggests that even with one interference-free link, the Z-IC does not necessarily perform better, because dirty paper coded interference in the regular IC facilitates to cancel the state through the cooperative dirty paper coding between the transmitters. [ABSTRACT FROM AUTHOR]

We investigate the state-dependent Gaussian wiretap channel with noncausal channel state information at the transmitter (GWTC-N-CSIT), and explore whether three strategies (i.e., taking action on the state, legitimate receiver’s channel output feedback, and combining the former two strategies together) help to enhance the secrecy capacity of the GWTC-N-CSIT. To be specific, we first determine the secrecy capacity of the GWTC-N-CSIT with noiseless feedback. Next, we derive lower and upper bounds on the secrecy capacity of the GWTC-N-CSIT with action-dependent state. Finally, we derive lower and upper bounds on the secrecy capacity of the GWTC-N-CSIT with both action-dependent state and noiseless feedback, and show that these bounds meet for a special case. Numerical results of this paper indicate that all three strategies enhance the secrecy capacity of the GWTC-N-CSIT. The study of this paper offers new options for enhancing the secrecy rates of the state-dependent wiretap channel models. [ABSTRACT FROM AUTHOR]

The paper is devoted to the problem of erasure coding in distributed storage. We consider a model of storage that assumes that nodes are organized into equally sized groups, called racks, that within each group the nodes can communicate freely without taxing the system bandwidth, and that the only information transmission that counts is the one between the racks. This assumption implies that the nodes within each of the racks can collaborate before providing information to the failed node. The main emphasis of the paper is on code construction for this storage model. We present an explicit family of maximum distance separable (MDS) array codes that support recovery of a single failed node from any number of helper racks using the minimum possible amount of inter-rack communication(such codes are said to provide optimal repair). The codes are constructed over finite fields of size comparable to the code length. We also derive a bound on the number of symbols accessed at helper nodes for the purposes of repair, and construct a code family that approaches this bound, while still maintaining the optimal repair property. Finally, we present a construction of scalar Reed-Solomon codes that support optimal repair for the rack-oriented storage model. [ABSTRACT FROM AUTHOR]

The variable-length source coding problem allowing the error probability up to some constant is considered for general sources. In this problem, the optimum mean codeword length of variable-length codes has already been determined. On the other hand, in this paper, we focus on the overflow (or excess codeword length) probability instead of the mean codeword length. The infimum of overflow thresholds under the constraint that both of the error probability and the overflow probability are smaller than or equal to some constant is called the optimum overflow threshold. In this paper, we first derive finite-length upper and lower bounds on these probabilities so as to analyze the optimum overflow thresholds. Then, by using these bounds, we determine the general formula of the optimum overflow thresholds in both of the first-order and second-order forms. Next, we consider another expression of the derived general formula so as to reveal the relationship with the optimum coding rate in the fixed-length source coding problem. Finally, we apply the general formula derived in this paper to the case of stationary memoryless sources. [ABSTRACT FROM AUTHOR]

Mean hitting time for random walks on a network, defined as the average of hitting times over all possible pairs of nodes, has found a large variety of applications in many areas. In this paper, we first prove that among all $N$ -node networks, the complete graph has the minimum mean hitting time $N-1$ , which scales linearly with network size. We then study a random walk mobility model with location heterogeneity, modeled by scale-free networks, which are ubiquitous in realistic systems such as P2P networks. For this purpose, we consider random walks on two sparse scale-free small-world networks. By using the connection between random walks and electrical networks, we derive explicit formulas about mean hitting time for both networks, the dominant scaling of which exhibits the same behavior as that of complete graphs. This paper demonstrates that heterogeneous sparse networks can have low-mean hitting time with a behavior similar to that of dense complete graphs, which is instrumental in designing networks, where search is fast between any pair of nodes. [ABSTRACT FROM AUTHOR]

This paper investigates the construction of rank-metric codes with specified Ferrers diagram shapes. These codes play a role in the multilevel construction for subspace codes. A conjecture from 2009 provides an upper bound for the dimension of a rank-metric code with given specified Ferrers diagram shape and rank distance. While the conjecture in its generality is wide open, several cases have been established in the literature. This paper contributes further cases of Ferrers diagrams and ranks for which the conjecture holds true. In addition, the proportion of maximal Ferrers diagram codes within the space of all rank-metric codes with the same shape and dimension is investigated. Special attention is being paid to MRD codes. It is shown that for growing field size the limiting proportion depends highly on the Ferrers diagram. For instance, for $[m\times 2]$ -MRD codes with rank 2 this limiting proportion is close to $1/e$. [ABSTRACT FROM AUTHOR]

There has been much recent interest in private information retrieval (PIR) in models where a database is stored across several servers using coding techniques from distributed storage, rather than being a simply replicated. In particular, a recent breakthrough result of Fazelli, Vardy, and Yaakobi introduces the notion of a PIR code and a PIR array code, and uses this notion to produce efficient PIR protocols. In this paper, we are interested in designing PIR array codes. We consider the case when we have $m$ servers, with each server storing a fraction $(1/s)$ of the bits of the database; here $s$ is a fixed rational number with $s > 1$. A PIR array code with the $k$ -PIR property enables a $k$ -server PIR protocol (with $k\leq m$) to be emulated on $m$ servers, with the overall storage requirements of the protocol being reduced. The communication complexity of a PIR protocol reduces as $k$ grows, so the virtual server rate, defined to be $k/m$ , is an important parameter. We study the maximum virtual server rate of a PIR array code with the $k$ -PIR property. We present upper bounds on the achievable virtual server rate, some constructions, and ideas how to obtain the PIR array codes with the highest possible virtual server rate. In particular, we present constructions that asymptotically meet our upper bounds and the exact largest virtual server rate is obtained when $1 < s \leq 2$. A $k$ -PIR code (and similarly a $k$ -PIR array code) is also a locally repairable code with symbol availability $k-1$. Such a code ensures $k$ parallel reads for each information symbol. So the virtual server rate is very closely related to the symbol availability of the code when used as a locally repairable code. The results of this paper are discussed also in this context where subspace codes also have an important role. [ABSTRACT FROM AUTHOR]

The article announces that Viveck R. Cadambe and Syed Ali Jafar have been awarded with the 2009 IEEE Information Theory Society Paper award for their paper "Interference Alignment and Degrees of Freedom of the K-User Interference Channel," which appeared in the August 2008 issue of "IEEE Transactions of Information Theory."

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

The article presents information about the 2004 IEEE Communications Society and Information Theory Society Joint Paper Award. The award was presented to Giuseppe Caire and Shlomo Shamai for their paper "On the Achievable Throughput of a Multiantenna Gaussian Broadcast Channel," which appeared in the IEEE Transactions on Information Theory's July 2003 issue. The award consisting of a plaque and an honorarium, is given annually for an outstanding paper that appeared in any of the two societies' publications during the preceding year. The purpose of the award, established in 1999, is to recognize exceptional published works in research areas of common interest to the two societies. The award winner Guseppe Caire was born in Torino in Italy in 1965. He received the B.Sc. degree in electrical engineering from the Princeton University in 1992. He did his Ph.D.degree from Politecnino di Torino in 1994. The other winner Shlomo Shamai received the B.Sc., M.Sc. and Ph.D. degrees in electrical engineering from the Tecnion-Israel Institute of Technology, Haifa, 1975, 1981 and 1986 respectively.

One objective of this paper is to propose a novel class of sequence pairs, called “quasi-orthogonal Z-complementary pairs (QOZCPs)”, each depicting Z-complementary property for their aperiodic auto-correlation sums and also having a low correlation zone when their aperiodic cross-correlation is considered. Construction of QOZCPs based on Successively Distributed Algorithms under Majorization Minimization (SDAMM) is presented. Another objective of this paper is to apply the proposed QOZCPs in fully polarimetric radar systems and analyse the corresponding ambiguity functions. It turns out that QOZCP waveforms are much more Doppler resilient than the known Golay complementary waveforms. [ABSTRACT FROM AUTHOR]

It is known that there exist mathematical problems of practical relevance which cannot be computed on a Turing machine. An important example is the calculation of the first derivative of continuously differentiable functions. This paper precisely classifies the non-computability of the first derivative, and of the maximum-norm of the first derivative in the Zheng-Weihrauch hierarchy. Based on this classification, the paper investigates whether it is possible that a Turing machine detects this non-computability of the first derivative by observing the data of the problem, and whether it is possible to detect upper bounds for the peak value of the first derivative of continuously differentiable functions. So from a practical point of view, the question is whether it is possible to implement an exit-flag functionality for observing non-computability of the first derivative. This paper even studies two different types of exit-flag functionality. A strong one, where the Turing machine always has to stop, and a weak one, where the Turing machine stops if and only if the input lies within the corresponding set of interest. It will be shown that non-computability of the first derivative is not detectable by a Turing machine for two concrete examples, namely for the problem of computing the input–output behavior of simple analog circuits and for solutions of the three-dimensional wave equation. In addition, it is shown that it is even impossible to detect an upper bound for the maximum norm of the first derivative. In particular, it is shown that all three problems are not even semidecidable. Finally, we briefly discuss implications of these results for analog and quantum computing. [ABSTRACT FROM AUTHOR]

Quantum readout provides a general framework for formulating statistical discrimination of quantum channels. Several paths have been taken for such this problem. However, there is much to be done in the avenue of optimizing channel discrimination using classical codes. At least two open questions can be pointed out: how to construct low complexity encoding schemes that are interesting for channel discrimination and, more importantly, how to develop capacity-achieving protocols. This paper aims at presenting a solution to these questions using polar codes. Firstly, we characterize the information rate and reliability parameter of the channels under polar encoding. We also show that the error probability of the scheme proposed decays exponentially with the square root of the code length. Secondly, an analysis of the optimal quantum states to be used as probes is given. [ABSTRACT FROM AUTHOR]

Coded caching is a promising technique to smooth out network traffic by storing part of the library content at the users’ local caches. The seminal work on coded caching for single file retrieval by Maddah-Ali and Niesen (MAN) showed the existence of a global caching gain that scales with the total memory in the system, in addition to the known local caching gain in uncoded systems. This paper formulates a novel cache-aided matrix multiplication retrieval problem, relevant for data analytics and machine learning applications. In the considered problem, each cache-aided user requests the product of two matrices from the library. A structure-agnostic solution is to treat each possible matrix product as an independent file and use the MAN coded caching scheme for single file retrieval. This paper proposes two structure-aware schemes, which partition each matrix in the library by either rows or columns and let a subset of users cache some sub-matrices, that improve on the structure-agnostic scheme. For the case where the library matrices are “fat” matrices, the structure-aware row-partition scheme is shown to be order optimal under some constraint. [ABSTRACT FROM AUTHOR]