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125
Structured compressed sensing: From theory to applications
 IEEE TRANS. SIGNAL PROCESS
, 2011
"... Compressed sensing (CS) is an emerging field that has attracted considerable research interest over the past few years. Previous review articles in CS limit their scope to standard discretetodiscrete measurement architectures using matrices of randomized nature and signal models based on standard ..."
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Cited by 104 (16 self)
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Compressed sensing (CS) is an emerging field that has attracted considerable research interest over the past few years. Previous review articles in CS limit their scope to standard discretetodiscrete measurement architectures using matrices of randomized nature and signal models based on standard sparsity. In recent years, CS has worked its way into several new application areas. This, in turn, necessitates a fresh look on many of the basics of CS. The random matrix measurement operator must be replaced by more structured sensing architectures that correspond to the characteristics of feasible acquisition hardware. The standard sparsity prior has to be extended to include a much richer class of signals and to encode broader data models, including continuoustime signals. In our overview, the theme is exploiting signal and measurement structure in compressive sensing. The prime focus is bridging theory and practice; that is, to pinpoint the potential of structured CS strategies to emerge from the math to the hardware. Our summary highlights new directions as well as relations to more traditional CS, with the hope of serving both as a review to practitioners wanting to join this emerging field, and as a reference for researchers that attempts to put some of the existing ideas in perspective of practical applications.
A mathematical theory of network interference and its applications,
 Proc. IEEE 97
, 2009
"... A unifying framework is developed to characterize the aggregate interference in wireless networks, and several applications are presented. By Moe Z. Win, Fellow IEEE, Pedro C. Pinto, Student Member IEEE, and Lawrence A. Shepp ABSTRACT  In this paper, we introduce a mathematical framework for the c ..."
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Cited by 101 (13 self)
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A unifying framework is developed to characterize the aggregate interference in wireless networks, and several applications are presented. By Moe Z. Win, Fellow IEEE, Pedro C. Pinto, Student Member IEEE, and Lawrence A. Shepp ABSTRACT  In this paper, we introduce a mathematical framework for the characterization of network interference in wireless systems. We consider a network in which the interferers are scattered according to a spatial Poisson process and are operating asynchronously in a wireless environment subject to path loss, shadowing, and multipath fading. We start by determining the statistical distribution of the aggregate network interference. We then investigate four applications of the proposed model: 1) interference in cognitive radio networks; 2) interference in wireless packet networks; 3) spectrum of the aggregate radiofrequency emission of wireless networks; and 4) coexistence between ultrawideband and narrowband systems. Our framework accounts for all the essential physical parameters that affect network interference, such as the wireless propagation effects, the transmission technology, the spatial density of interferers, and the transmitted power of the interferers.
On the Tradeoff between Two Types of Processing Gain
 IEEE Transactions on Communications
, 2002
"... One of the features characterizing almost every multiple access (MA) communication system is the processing gain. Through the use of spreading sequences, the processing gain of random direct sequence code division multiple access (RCDMA) systems, or any other CDMA systems, is devoted to both bandwid ..."
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Cited by 43 (27 self)
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One of the features characterizing almost every multiple access (MA) communication system is the processing gain. Through the use of spreading sequences, the processing gain of random direct sequence code division multiple access (RCDMA) systems, or any other CDMA systems, is devoted to both bandwidth expansion and orthogonalization of the signals transmitted by different users. Another type of multiple access systems is Impulse Radio (IR). In many aspects, IR systems are similar to time division multiple access (TDMA) systems, and the processing gain of IR systems represents the ratio between the actual transmission time and the total time between two consecutive transmissions (onplusoff to on ratio). While CDMA systems, which constantly excite the channel, rely on spreading sequences to orthogonalize the signals transmitted by different users, IR systems transmit a series of short pulses and the orthogonalization between the signals transmitted by different users is achieved by the fact that at the receiver most of the pulses do not collide with each other.
Timedelay estimation from lowrate samples: a union of subspaces approach
 IEEE TRANS. SIGNAL PROCESS
, 2010
"... Timedelay estimation arises in many applications in which a multipath medium has to be identified from pulses transmitted through the channel. Previous methods for time delay recovery either operate on the analog received signal, or require sampling at the Nyquist rate of the transmitted pulse. In ..."
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Cited by 33 (19 self)
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Timedelay estimation arises in many applications in which a multipath medium has to be identified from pulses transmitted through the channel. Previous methods for time delay recovery either operate on the analog received signal, or require sampling at the Nyquist rate of the transmitted pulse. In this paper, we develop a unified approach to time delay estimation from lowrate samples. This problem can be formulated in the broader context of sampling over an infinite union of subspaces. Although sampling over unions of subspaces has been receiving growing interest, previous results either focus on unions of finitedimensional subspaces, or finite unions. The framework we develop here leads to perfect recovery of the multipath delays from samples of the channel output at the lowest possible rate, even in the presence of overlapping transmitted pulses, and allows for a variety of different sampling methods. The sampling rate depends only on the number of multipath components and the transmission rate, but not on the bandwidth of the probing signal. This result can be viewed as a sampling theorem over an infinite union of infinite dimensional subspaces. By properly manipulating the lowrate samples, we show that the time delays can be recovered using the wellknown ESPRIT algorithm. Combining results from sampling theory with those obtained in the context of direction of arrival estimation, we develop sufficient conditions on the transmitted pulse and the sampling functions in order to ensure perfect recovery of the channel parameters at the minimal possible rate.
NLOS Identification and Mitigation for Localization Based on UWB Experimental Data
, 2010
"... Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultrawide bandwidth (UWB) transmission is a promising technology for locationaware sensor networks, due to its power efficiency, fine delay reso ..."
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Cited by 29 (1 self)
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Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultrawide bandwidth (UWB) transmission is a promising technology for locationaware sensor networks, due to its power efficiency, fine delay resolution, and robust operation in harsh environments. However, the presence of walls and other obstacles presents a significant challenge in terms of localization, as they can result in positively biased distance estimates. We have performed an extensive indoor measurement campaign with FCCcompliant UWB radios to quantify the effect of nonlineofsight (NLOS) propagation. From these channel pulse responses, we extract features that are representative of the propagation conditions. We then develop classification and regression algorithms based on machine learning techniques, which are capable of: (i) assessing whether a signal was transmitted in LOS or NLOS conditions; and (ii) reducing ranging error caused by NLOS conditions. We evaluate the resulting performance through Monte Carlo simulations and compare with existing techniques. In contrast to common probabilistic approaches that require statistical models of the features, the proposed optimizationbased approach is more robust against modeling errors.
Time Delay Estimation from Low Rate Samples: A Union of Subspaces Approach
, 2010
"... Time delay estimation arises in many applications in which a multipath medium has to be identified from pulses transmitted through the channel. Previous methods for time delay recovery either operate on the analog received signal, or require sampling at the Nyquist rate of the transmitted pulse. In ..."
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Cited by 24 (22 self)
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Time delay estimation arises in many applications in which a multipath medium has to be identified from pulses transmitted through the channel. Previous methods for time delay recovery either operate on the analog received signal, or require sampling at the Nyquist rate of the transmitted pulse. In this paper, we develop a unified approach to time delay estimation from low rate samples. This problem can be formulated in the broader context of sampling over an infinite union of subspaces. Although sampling over unions of subspaces has been receiving growing interest, previous results either focus on unions of finitedimensional subspaces, or finite unions. The framework we develop here leads to perfect recovery of the multipath delays from samples of the channel output at the lowest possible rate, even in the presence of overlapping transmitted pulses, and allows for a variety of different sampling methods. The sampling rate depends only on the number of multipath components and the transmission rate, but not on the bandwidth of the probing signal. This result can be viewed as a sampling theorem over an infinite union of infinite dimensional subspaces. By properly manipulating the lowrate samples, we show that the time delays can be recovered using the wellknown ESPRIT algorithm. Combining results from sampling theory with those obtained in the context of direction of arrival estimation, we develop sufficient conditions on the transmitted pulse and the sampling functions in order to ensure perfect recovery of the channel parameters at the minimal possible rate.
Low Complexity Rake Receivers in UltraWideband Channels
 IEEE Trans. Wireless Commun
, 2007
"... One of the major issues for the design of ultrawideband (UWB) receivers is the need to recover the signal energy dispersed over many multipath components, while keeping the receiver complexity low. To this aim we consider two schemes for reducescomplexity UWB Rake receivers, both of which combine ..."
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Cited by 23 (1 self)
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One of the major issues for the design of ultrawideband (UWB) receivers is the need to recover the signal energy dispersed over many multipath components, while keeping the receiver complexity low. To this aim we consider two schemes for reducescomplexity UWB Rake receivers, both of which combine a subset of the available resolved multipath components. The first method, called partial Rake (PRake), combines theirs/arriving multipath components. the second is known as selective Rake (SRake) and combines the instantaneously strongest multipath components. We evaluate and compare the link performance of these Rake receivers in different UWB channels, whose models are based on extensive propagation measurements. We quantify the effect of the channel characteristics on the receiver performance, analyzing in particular the influence of smallscale fading statistics. We find that for dense channels the performance of the simpler PRake receiver is almost as food as that of the SRake receiver, even for a small number of fingers. In sparse channels, however, the SRake outperforms the PRake significantly. We also show that for a fixed transmitted energy there is an optimum transmission bandwidth.
NLOS Identification and Weighted LeastSquares Localization for UWB Systems Using Multipath Channel Statistics
, 2008
"... Nonlineofsight (NLOS) identification and mitigation carry significant importance in wireless localization systems. In this paper, we propose a novel NLOS identification technique based on the multipath channel statistics such as the kurtosis, the mean excess delay spread, and the rootmeansquare ..."
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Cited by 22 (1 self)
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Nonlineofsight (NLOS) identification and mitigation carry significant importance in wireless localization systems. In this paper, we propose a novel NLOS identification technique based on the multipath channel statistics such as the kurtosis, the mean excess delay spread, and the rootmeansquare delay spread. In particular, the IEEE 802.15.4a ultrawideband channel models are used as examples and the above statistics are found to be well modeled by lognormal random variables. Subsequently, a joint likelihood ratio test is developed for lineofsight (LOS) or NLOS identification. Three different weighted leastsquares (WLSs) localization techniques that exploit the statistics of multipath components (MPCs) are analyzed. The basic idea behind the proposed WLS approaches is that smaller weights are given to the measurements which are likely to be biased (based on the MPC information), as opposed to variancebased WLS techniques in the literature. Accuracy gains with respect to the conventional leastsquares algorithm are demonstrated via MonteCarlo simulations and verified by theoretical derivations.
Timing acquisition in ultrawideband communication systems
 IEEE TRANS. ON VEHICULAR TECHNOLOGY
, 2005
"... The goal of this paper is to highlight the significance of the timing acquisition problem in ultrawideband (UWB) communication systems and discuss efficient solutions to the problem. We discuss how the distinguishing features of UWB communication systems, such as their wide bandwidth and low trans ..."
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Cited by 22 (1 self)
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The goal of this paper is to highlight the significance of the timing acquisition problem in ultrawideband (UWB) communication systems and discuss efficient solutions to the problem. We discuss how the distinguishing features of UWB communication systems, such as their wide bandwidth and low transmission power constraints, are responsible for making the acquisition of UWB signals a difficult task. A survey of the current approaches to UWB signal acquisition is also given. In addition, we discuss some of the issues and challenges in UWB signal acquisition which may not have received sufficient attention in existing literature.
Comparisons of analog and digital impulse radio for multipleaccess communications
 in Proc. IEEE Int. Conf. on Comm
, 1997
"... Abstract  Attractive features of timehopping spreadspectrum multiple access systems employing impulse signal technology are outlined and emerging design issues are described. Performance of such communications systems in terms of multipleaccess capability is estimated for both analog and digit ..."
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Cited by 21 (6 self)
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Abstract  Attractive features of timehopping spreadspectrum multiple access systems employing impulse signal technology are outlined and emerging design issues are described. Performance of such communications systems in terms of multipleaccess capability is estimated for both analog and digital data modulation formats under ideal multiple access channel conditions. I. Introduction to Impulse Radio Systems THE term wideband, as applied to communication systems, can have di®erent meanings. When applied to conventional systems, it refers to the data modulation bandwidth. In that case, the more wideband a system is, the higher its data transmission rate. In this paper,