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# IEEE Transactions on Information Theory

Includes the top 50 most frequently accessed documents for this publication according to the usage statistics for the month of

• ### Compressed sensing

Publication Year: 2006, Page(s):1289 - 1306
Cited by:  Papers (12202)  |  Patents (164)
| | PDF (483 KB) | HTML

Suppose x is an unknown vector in Ropf<sup>m</sup> (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural... View full abstract»

• ### Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

Publication Year: 2006, Page(s):489 - 509
Cited by:  Papers (7491)  |  Patents (141)
| | PDF (1167 KB) | HTML

This paper considers the model problem of reconstructing an object from incomplete frequency samples. Consider a discrete-time signal f/spl isin/C/sup N/ and a randomly chosen set of frequencies /spl Omega/. Is it possible to reconstruct f from the partial knowledge of its Fourier coefficients on the set /spl Omega/? A typical result of this paper is as follows. Suppose that f is a superposition o... View full abstract»

• ### Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels

Publication Year: 2009, Page(s):3051 - 3073
Cited by:  Papers (1168)  |  Patents (26)
| | PDF (707 KB) | HTML

A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity I(W) of any given binary-input discrete memoryless channel (B-DMC) W. The symmetric capacity is the highest rate achievable subject to using the input letters of the channel with equal probability. Channel polarization refers to the fact that it is possible to synthesize, out of N ind... View full abstract»

• ### Speeding Up Distributed Machine Learning Using Codes

Publication Year: 2018, Page(s):1514 - 1529
Cited by:  Papers (10)
| | PDF (1461 KB) | HTML

Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems, there are several types of noise that can affect the performance of distributed machine learning algorithms-straggler nodes, system failures, or communication bottlenecks-but there has been little interaction cutting across codes, machine learning, and distributed systems. In this pape... View full abstract»

• ### A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction

Publication Year: 2018, Page(s):1845 - 1866
Cited by:  Papers (6)
| | PDF (905 KB) | HTML

Deep convolutional neural networks (DCNNs) have led to breakthrough results in numerous practical machine learning tasks, such as classification of images in the ImageNet data set, control-policy-learning to play Atari games or the board game Go, and image captioning. Many of these applications first perform feature extraction and then feed the results thereof into a classifier. The mathematical a... View full abstract»

• ### Channel Coding Rate in the Finite Blocklength Regime

Publication Year: 2010, Page(s):2307 - 2359
Cited by:  Papers (719)  |  Patents (1)
| | PDF (3873 KB) | HTML

This paper investigates the maximal channel coding rate achievable at a given blocklength and error probability. For general classes of channels new achievability and converse bounds are given, which are tighter than existing bounds for wide ranges of parameters of interest, and lead to tight approximations of the maximal achievable rate for blocklengths <i>n</i> as short as 100. It is... View full abstract»

• ### Factor graphs and the sum-product algorithm

Publication Year: 2001, Page(s):498 - 519
Cited by:  Papers (2937)  |  Patents (192)
| | PDF (458 KB) | HTML

Algorithms that must deal with complicated global functions of many variables often exploit the manner in which the given functions factor as a product of "local" functions, each of which depends on a subset of the variables. Such a factorization can be visualized with a bipartite graph that we call a factor graph, In this tutorial paper, we present a generic message-passing algorithm, the sum-pro... View full abstract»

• ### Cooperative diversity in wireless networks: Efficient protocols and outage behavior

Publication Year: 2004, Page(s):3062 - 3080
Cited by:  Papers (8797)  |  Patents (63)
| | PDF (572 KB) | HTML

We develop and analyze low-complexity cooperative diversity protocols that combat fading induced by multipath propagation in wireless networks. The underlying techniques exploit space diversity available through cooperating terminals' relaying signals for one another. We outline several strategies employed by the cooperating radios, including fixed relaying schemes such as amplify-and-forward and ... View full abstract»

• ### List Decoding of Polar Codes

Publication Year: 2015, Page(s):2213 - 2226
Cited by:  Papers (225)
| | PDF (1015 KB) | HTML

We describe a successive-cancellation list decoder for polar codes, which is a generalization of the classic successive-cancellation decoder of Arıkan. In the proposed list decoder, L decoding paths are considered concurrently at each decoding stage, where L is an integer parameter. At the end of the decoding process, the most likely among the L paths is selected as the single codeword at the deco... View full abstract»

• ### Decoding by linear programming

Publication Year: 2005, Page(s):4203 - 4215
Cited by:  Papers (3192)  |  Patents (43)
| | PDF (375 KB) | HTML

This paper considers a natural error correcting problem with real valued input/output. We wish to recover an input vector f/spl isin/R/sup n/ from corrupted measurements y=Af+e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible to recover f exactly from the data y? We prove that under suitable conditions on the coding matrix A, the input f is t... View full abstract»

• ### Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit

Publication Year: 2012, Page(s):1094 - 1121
Cited by:  Papers (596)  |  Patents (2)
| | PDF (6565 KB) | HTML

Finding the sparsest solution to underdetermined systems of linear equationsy= Φxis NP-hard in general. We show here that for systems with “typical”/“random” Φ, a good approximation to the sparsest solution is obtained by applying a fixed number of standard operations from linear algebra. Our proposal, Stagewise Orthogonal Matching Pursuit (StOMP), successively transforms the sig... View full abstract»

• ### Joint Spatial Division and Multiplexing—The Large-Scale Array Regime

Publication Year: 2013, Page(s):6441 - 6463
Cited by:  Papers (488)  |  Patents (4)
| | PDF (6169 KB) | HTML

We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional channel state information at the transmitter (CSIT). JSDM achieves significant savings both in the downlink training and in the... View full abstract»

• ### Nearest neighbor pattern classification

Publication Year: 1967, Page(s):21 - 27
Cited by:  Papers (1843)  |  Patents (98)
| | PDF (1019 KB)

The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points. This rule is independent of the underlying joint distribution on the sample points and their classifications, and hence the probability of error<tex>R</tex>of such a rule must be at least as great as the Bayes probability of error<tex... View full abstract»

• ### Subspace Pursuit for Compressive Sensing Signal Reconstruction

Publication Year: 2009, Page(s):2230 - 2249
Cited by:  Papers (1044)  |  Patents (8)
| | PDF (976 KB) | HTML

We propose a new method for reconstruction of sparse signals with and without noisy perturbations, termed the subspace pursuit algorithm. The algorithm has two important characteristics: low computational complexity, comparable to that of orthogonal matching pursuit techniques when applied to very sparse signals, and reconstruction accuracy of the same order as that of linear programming (LP) opti... View full abstract»

• ### Fundamental Limits of Caching

Publication Year: 2014, Page(s):2856 - 2867
Cited by:  Papers (506)
| | PDF (783 KB) | HTML

Caching is a technique to reduce peak traffic rates by prefetching popular content into memories at the end users. Conventionally, these memories are used to deliver requested content in part from a locally cached copy rather than through the network. The gain offered by this approach, which we term local caching gain, depends on the local cache size (i.e., the memory available at each individual ... View full abstract»

• ### Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

Publication Year: 2007, Page(s):4655 - 4666
Cited by:  Papers (4117)  |  Patents (39)
| | PDF (936 KB) | HTML

This paper demonstrates theoretically and empirically that a greedy algorithm called orthogonal matching pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m ln d) random linear measurements of that signal. This is a massive improvement over previous results, which require <i>O</i>(m<sup>2</sup>) measurements. The new results for OMP a... View full abstract»

• ### Design of capacity-approaching irregular low-density parity-check codes

Publication Year: 2001, Page(s):619 - 637
Cited by:  Papers (2009)  |  Patents (106)
| | PDF (510 KB) | HTML

We design low-density parity-check (LDPC) codes that perform at rates extremely close to the Shannon capacity. The codes are built from highly irregular bipartite graphs with carefully chosen degree patterns on both sides. Our theoretical analysis of the codes is based on the work of Richardson and Urbanke (see ibid., vol.47, no.2, p.599-618, 2000). Assuming that the underlying communication chann... View full abstract»

• ### Network Coding for Distributed Storage Systems

Publication Year: 2010, Page(s):4539 - 4551
Cited by:  Papers (764)  |  Patents (24)
| | PDF (739 KB) | HTML

Distributed storage systems provide reliable access to data through redundancy spread over individually unreliable nodes. Application scenarios include data centers, peer-to-peer storage systems, and storage in wireless networks. Storing data using an erasure code, in fragments spread across nodes, requires less redundancy than simple replication for the same level of reliability. However, since f... View full abstract»

• ### New directions in cryptography

Publication Year: 1976, Page(s):644 - 654
Cited by:  Papers (4540)  |  Patents (345)
| | PDF (2164 KB)

Two kinds of contemporary developments in cryptography are examined. Widening applications of teleprocessing have given rise to a need for new types of cryptographic systems, which minimize the need for secure key distribution channels and supply the equivalent of a written signature. This paper suggests ways to solve these currently open problems. It also discusses how the theories of communicati... View full abstract»

• ### Orthogonal Matching Pursuit for Sparse Signal Recovery With Noise

Publication Year: 2011, Page(s):4680 - 4688
Cited by:  Papers (346)  |  Patents (5)
| | PDF (201 KB) | HTML

We consider the orthogonal matching pursuit (OMP) algorithm for the recovery of a high-dimensional sparse signal based on a small number of noisy linear measurements. OMP is an iterative greedy algorithm that selects at each step the column, which is most correlated with the current residuals. In this paper, we present a fully data driven OMP algorithm with explicit stopping rules. It is shown tha... View full abstract»

• ### Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels

Publication Year: 2003, Page(s):1073 - 1096
Cited by:  Papers (2527)  |  Patents (51)
| | PDF (1620 KB) | HTML

Multiple antennas can be used for increasing the amount of diversity or the number of degrees of freedom in wireless communication systems. We propose the point of view that both types of gains can be simultaneously obtained for a given multiple-antenna channel, but there is a fundamental tradeoff between how much of each any coding scheme can get. For the richly scattered Rayleigh-fading channel,... View full abstract»

• ### Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using$\ell _{1}$-Constrained Quadratic Programming (Lasso)

Publication Year: 2009, Page(s):2183 - 2202
Cited by:  Papers (298)  |  Patents (1)
| | PDF (744 KB) | HTML

The problem of consistently estimating the sparsity pattern of a vector beta* isin Rpbased on observations contaminated by noise arises in various contexts, including signal denoising, sparse approximation, compressed sensing, and model selection. We analyze the behavior of l1-constrained quadratic programming (QP), also referred to as the Lasso, for recovering the sparsity p... View full abstract»

• ### Tensor SVD: Statistical and Computational Limits

Publication Year: 2018, Page(s):7311 - 7338
| | PDF (838 KB) | HTML

In this paper, we propose a general framework for tensor singular value decomposition (tensor singular value decomposition (SVD)), which focuses on the methodology and theory for extracting the hidden low-rank structure from high-dimensional tensor data. Comprehensive results are developed on both the statistical and computational limits for tensor SVD. This problem exhibits three different phases... View full abstract»

• ### Mutual information and minimum mean-square error in Gaussian channels

Publication Year: 2005, Page(s):1261 - 1282
Cited by:  Papers (526)  |  Patents (5)
| | PDF (594 KB) | HTML

This paper deals with arbitrarily distributed finite-power input signals observed through an additive Gaussian noise channel. It shows a new formula that connects the input-output mutual information and the minimum mean-square error (MMSE) achievable by optimal estimation of the input given the output. That is, the derivative of the mutual information (nats) with respect to the signal-to-noise rat... View full abstract»

• ### The Optimal Hard Threshold for Singular Values is$4/\sqrt {3}$

Publication Year: 2014, Page(s):5040 - 5053
Cited by:  Papers (55)
| | PDF (2730 KB) | HTML

We consider recovery of low-rank matrices from noisy data by hard thresholding of singular values, in which empirical singular values below a threshold λ are set to 0. We study the asymptotic mean squared error (AMSE) in a framework, where the matrix size is large compared with the rank of the matrix to be recovered, and the signal-to-noise ratio of the low-rank piece stays constant. The AMSE-opti... View full abstract»

• ### Greed is good: algorithmic results for sparse approximation

Publication Year: 2004, Page(s):2231 - 2242
Cited by:  Papers (1638)  |  Patents (12)
| | PDF (291 KB) | HTML

This article presents new results on using a greedy algorithm, orthogonal matching pursuit (OMP), to solve the sparse approximation problem over redundant dictionaries. It provides a sufficient condition under which both OMP and Donoho's basis pursuit (BP) paradigm can recover the optimal representation of an exactly sparse signal. It leverages this theory to show that both OMP and BP succeed for ... View full abstract»

• ### Capacity Results on Multiple-Input Single-Output Wireless Optical Channels

Publication Year: 2018, Page(s):6954 - 6966
Cited by:  Papers (1)
| | PDF (604 KB) | HTML

This paper derives upper and lower bounds on the capacity of the multiple-input single-output free-space optical intensity channel with signal-independent additive Gaussian noise subject to both an average-intensity and a peak-intensity constraint. In the limit where the signal-to-noise ratio (SNR) tends to infinity, the asymptotic capacity is specified, while in the limit where the SNR tends to z... View full abstract»

• ### OptShrink: An Algorithm for Improved Low-Rank Signal Matrix Denoising by Optimal, Data-Driven Singular Value Shrinkage

Publication Year: 2014, Page(s):3002 - 3018
Cited by:  Papers (31)
| | PDF (1803 KB) | HTML

The truncated singular value decomposition of the measurement matrix is the optimal solution to the representation problem of how to best approximate a noisy measurement matrix using a low-rank matrix. Here, we consider the (unobservable) denoising problem of how to best approximate a low-rank signal matrix buried in noise by optimal (re)weighting of the singular vectors of the measurement matrix.... View full abstract»

• ### Update or Wait: How to Keep Your Data Fresh

Publication Year: 2017, Page(s):7492 - 7508
Cited by:  Papers (24)
| | PDF (1178 KB) | HTML

In this paper, we study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel. A proper metric for data freshness at the destination is the age-of-information, or simply age, which is defined as how old the freshest received update is, since the moment that this update was generated at the source node (e.g., a sensor). A reasonable upda... View full abstract»

• ### Information Transmission Using the Nonlinear Fourier Transform, Part I: Mathematical Tools

Publication Year: 2014, Page(s):4312 - 4328
Cited by:  Papers (29)  |  Patents (2)
| | PDF (664 KB) | HTML

The nonlinear Fourier transform (NFT), a powerful tool in soliton theory and exactly solvable models, is a method for solving integrable partial differential equations governing wave propagation in certain nonlinear media. The NFT decorrelates signal degrees-of-freedom in such models, in much the same way that the Fourier transform does for linear systems. In this three-part series of papers, this... View full abstract»

• ### Massive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits

Publication Year: 2014, Page(s):7112 - 7139
Cited by:  Papers (288)
| | PDF (2212 KB) | HTML

The use of large-scale antenna arrays can bring substantial improvements in energy and/or spectral efficiency to wireless systems due to the greatly improved spatial resolution and array gain. Recent works in the field of massive multiple-input multiple-output (MIMO) show that the user channels decorrelate when the number of antennas at the base stations (BSs) increases, thus strong signal gains a... View full abstract»

• ### The wavelet transform, time-frequency localization and signal analysis

Publication Year: 1990, Page(s):961 - 1005
Cited by:  Papers (3076)  |  Patents (30)
| | PDF (3699 KB)

Two different procedures for effecting a frequency analysis of a time-dependent signal locally in time are studied. The first procedure is the short-time or windowed Fourier transform; the second is the wavelet transform, in which high-frequency components are studied with sharper time resolution than low-frequency components. The similarities and the differences between these two methods are disc... View full abstract»

• ### Model-Based Compressive Sensing

Publication Year: 2010, Page(s):1982 - 2001
Cited by:  Papers (770)  |  Patents (4)
| | PDF (966 KB) | HTML

Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for the acquisition of sparse or compressible signals that can be well approximated by just K ¿ N elements from an N -dimensional basis. Instead of taking periodic samples, CS measures inner products with M &lt; N random vectors and then recovers the signal via a sparsity-seeking optimization or greedy algorithm. Standard C... View full abstract»

• ### Interference Alignment and Degrees of Freedom of the$K$-User Interference Channel

Publication Year: 2008, Page(s):3425 - 3441
Cited by:  Papers (2067)  |  Patents (39)
| | PDF (422 KB) | HTML

For the fully connected K user wireless interference channel where the channel coefficients are time-varying and are drawn from a continuous distribution, the sum capacity is characterized as C(SNR)=K/2log(SNR)+o(log(SNR)) . Thus, the K user time-varying interference channel almost surely has K/2 degrees of freedom. Achievability is based on the idea of interference alignment. Examples are also pr... View full abstract»

• ### The capacity of low-density parity-check codes under message-passing decoding

Publication Year: 2001, Page(s):599 - 618
Cited by:  Papers (1751)  |  Patents (154)
| | PDF (475 KB) | HTML

We present a general method for determining the capacity of low-density parity-check (LDPC) codes under message-passing decoding when used over any binary-input memoryless channel with discrete or continuous output alphabets. Transmitting at rates below this capacity, a randomly chosen element of the given ensemble will achieve an arbitrarily small target probability of error with a probability th... View full abstract»

• ### FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers

Publication Year: 2013, Page(s):8402 - 8413
Cited by:  Papers (389)
| | PDF (2158 KB) | HTML

Video on-demand streaming from Internet-based servers is becoming one of the most important services offered by wireless networks today. In order to improve the area spectral efficiency of video transmission in cellular systems, small cells heterogeneous architectures (e.g., femtocells, WiFi off-loading) are being proposed, such that video traffic to nomadic users can be handled by short-range lin... View full abstract»

• ### A Variational Characterization of Rényi Divergences

Publication Year: 2018, Page(s):6979 - 6989
| | PDF (270 KB) | HTML

Atar, Chowdhary and Dupuis have recently exhibited a variational formula for exponential integrals of bounded measurable functions in terms of Rényi divergences. We show that a variational characterization of the Rényi divergences between two probability distributions on a measurable space in terms of relative entropies, when combined with the elementary variational formula for exponential integra... View full abstract»

• ### How to Construct Polar Codes

Publication Year: 2013, Page(s):6562 - 6582
Cited by:  Papers (219)  |  Patents (4)
| | PDF (5879 KB) | HTML

A method for efficiently constructing polar codes is presented and analyzed. Although polar codes are explicitly defined, straightforward construction is intractable since the resulting polar bit-channels have an output alphabet that grows exponentially with the code length. Thus, the core problem that needs to be solved is that of faithfully approximating a bit-channel with an intractably large a... View full abstract»

• ### Wireless Information-Theoretic Security

Publication Year: 2008, Page(s):2515 - 2534
Cited by:  Papers (925)  |  Patents (1)
| | PDF (1341 KB) | HTML

This paper considers the transmission of confidential data over wireless channels. Based on an information-theoretic formulation of the problem, in which two legitimates partners communicate over a quasi-static fading channel and an eavesdropper observes their transmissions through a second independent quasi-static fading channel, the important role of fading is characterized in terms of average s... View full abstract»

• ### A Fundamental Tradeoff Between Computation and Communication in Distributed Computing

Publication Year: 2018, Page(s):109 - 128
Cited by:  Papers (16)
| | PDF (1566 KB) | HTML

How can we optimally trade extra computing power to reduce the communication load in distributed computing? We answer this question by characterizing a fundamental tradeoff between computation and communication in distributed computing, i.e., the two are inversely proportional to each other. More specifically, a general distributed computing framework, motivated by commonly used structures like Ma... View full abstract»

• ### Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?

Publication Year: 2006, Page(s):5406 - 5425
Cited by:  Papers (3300)  |  Patents (46)
| | PDF (458 KB) | HTML

Suppose we are given a vector f in a class FsubeRopf<sup>N </sup>, e.g., a class of digital signals or digital images. How many linear measurements do we need to make about f to be able to recover f to within precision epsi in the Euclidean (lscr<sub>2</sub>) metric? This paper shows that if the objects of interest are sparse in a fixed basis or compressible, then it is pos... View full abstract»

• ### Performance Analysis of ZF and MMSE Equalizers for MIMO Systems: An In-Depth Study of the High SNR Regime

Publication Year: 2011, Page(s):2008 - 2026
Cited by:  Papers (166)
| | PDF (912 KB) | HTML

This paper presents an in-depth analysis of the zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to wireless multiinput multioutput (MIMO) systems with no fewer receive than transmit antennas. In spite of much prior work on this subject, we reveal several new and surprising analytical results in terms of output signal-to-noise ratio (SNR), uncoded error and outage probabi... View full abstract»

• ### Uncertainty principles and ideal atomic decomposition

Publication Year: 2001, Page(s):2845 - 2862
Cited by:  Papers (904)  |  Patents (30)
| | PDF (624 KB) | HTML

Suppose a discrete-time signal S(t), 0/spl les/t<N, is a superposition of atoms taken from a combined time-frequency dictionary made of spike sequences 1/sub {t=/spl tau/}/ and sinusoids exp{2/spl pi/iwt/N}//spl radic/N. Can one recover, from knowledge of S alone, the precise collection of atoms going to make up S? Because every discrete-time signal can be represented as a superposition of spik... View full abstract»

• ### Least squares quantization in PCM

Publication Year: 1982, Page(s):129 - 137
Cited by:  Papers (3816)  |  Patents (104)
| | PDF (1227 KB)

It has long been realized that in pulse-code modulation (PCM), with a given ensemble of signals to handle, the quantum values should be spaced more closely in the voltage regions where the signal amplitude is more likely to fall. It has been shown by Panter and Dite that, in the limit as the number of quanta becomes infinite, the asymptotic fractional density of quanta per unit voltage should vary... View full abstract»

• ### Channel coding with multilevel/phase signals

Publication Year: 1982, Page(s):55 - 67
Cited by:  Papers (2526)  |  Patents (296)
| | PDF (1807 KB)

A coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth. This is achieved by channel coding with expanded sets of multilevel/phase signals in a manner which increases free Euclidean distance. Soft maximum--likelihood (ML) decoding using the Viterbi algorithm is assumed. Following a discussion of channel ca... View full abstract»

• ### Raptor codes

Publication Year: 2006, Page(s):2551 - 2567
Cited by:  Papers (1526)  |  Patents (60)
| | PDF (529 KB) | HTML

LT-codes are a new class of codes introduced by Luby for the purpose of scalable and fault-tolerant distribution of data over computer networks. In this paper, we introduce Raptor codes, an extension of LT-codes with linear time encoding and decoding. We will exhibit a class of universal Raptor codes: for a given integer k and any real epsiv&gt;0, Raptor codes in this class produce a potential... View full abstract»

• ### On the achievable throughput of a multiantenna Gaussian broadcast channel

Publication Year: 2003, Page(s):1691 - 1706
Cited by:  Papers (1587)  |  Patents (64)
| | PDF (1010 KB) | HTML

A Gaussian broadcast channel (GBC) with r single-antenna receivers and t antennas at the transmitter is considered. Both transmitter and receivers have perfect knowledge of the channel. Despite its apparent simplicity, this model is, in general, a nondegraded broadcast channel (BC), for which the capacity region is not fully known. For the two-user case, we find a special case of Marton's (1979) r... View full abstract»

• ### From Denoising to Compressed Sensing

Publication Year: 2016, Page(s):5117 - 5144
Cited by:  Papers (66)
| | PDF (2753 KB) | HTML

A denoising algorithm seeks to remove noise, errors, or perturbations from a signal. Extensive research has been devoted to this arena over the last several decades, and as a result, todays denoisers can effectively remove large amounts of additive white Gaussian noise. A compressed sensing (CS) reconstruction algorithm seeks to recover a structured signal acquired using a small number of randomiz... View full abstract»

• ### Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting

Publication Year: 2012, Page(s):3250 - 3265
Cited by:  Papers (69)
| | PDF (963 KB) | HTML

Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is either sampled from a Gaussian process (GP) or has low norm in a reproducing kernel Hilbert space. We resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for ... View full abstract»

• ### Randomized gossip algorithms

Publication Year: 2006, Page(s):2508 - 2530
Cited by:  Papers (1070)
| | PDF (577 KB) | HTML

Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join and old nodes leave the network. Algorithms for such networks need to be robust against changes in top... View full abstract»

## Aims & Scope

IEEE Transactions on Information Theory publishes papers concerned with the transmission, processing, and utilization of information.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Alexander Barg

Department of Electrical and Computer Engineering and the Institute for Systems Research, University of Maryland

email: abarg-ittrans@ece.umd.edu