M.Z. Win

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (281)333.01 Total impact

  • Youngmin Jeong · Hyundong Shin · Moe Z. Win
    IEEE Transactions on Information Theory 07/2015; 61(7):1-1. DOI:10.1109/TIT.2015.2433264 · 2.65 Impact Factor
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    ABSTRACT: Achieving secrecy in cognitive wireless networks is challenging due to the broadcast nature of the propagation medium. This article introduces the concept of cognitive network secrecy for coexisting primary and secondary networks sharing the same radio resources. We present a framework for the design and analysis of cognitive networks with secrecy that accounts for their intrinsic properties such as node spatial distribution, wireless propagation medium, and aggregate network interference. While interference is usually considered deleterious for communications, we envision that mutual interference between primary and secondary networks can be beneficial for cognitive network secrecy. To this end, we put forth interference engineering strategies and quantify their benefits for cognitive network secrecy. Our analysis reveals the innate connection between cognitive network secrecy and intrinsic properties of the networks, opening the way to a new paradigm of cognitive network secrecy with interference engineering.
    IEEE Network 10/2014; 28(5):86-90. DOI:10.1109/MNET.2014.6915445 · 3.72 Impact Factor
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    ABSTRACT: Novel non-coherent impulse communications receivers are proposed to alleviate excessive noise collection in clustered multipath channels. To this aim, a stop-and-go strategy based on energy detection in the autocorrelation receiver or in the energy detection receiver is employed. This strategy enables the selective collection of useful signal portions only, allowing the integration interval to be kept large without noise penalty. To implement this strategy, a blind method is employed, using model order selection based on information theoretic criteria, which optimizes the performance of the proposed receiver and does not require the estimation of channel parameters. The bit error probability of the proposed stop-and-go receivers is evaluated, and our results highlight the considerable performance gain at the expense of a small increase in complexity.
    IEEE Transactions on Wireless Communications 09/2014; 13(9):4821-4835. DOI:10.1109/TWC.2014.2335196 · 2.76 Impact Factor
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    ABSTRACT: We consider the problem of localizing two devices using signals of opportunity from beacons with known positions. Beacons and devices have asynchronous local clocks or oscillators with unknown clock skews and offsets. We model clock skews as random, and analyze the biases introduced by clock asynchronism in the received signals. By deriving the equivalent Fisher information matrix for the modified Bayesian Cramér-Rao lower bound (CRLB) of device position and velocity estimation, we quantify the errors caused by clock asynchronism. We propose an algorithm based on differential time-difference-of-arrival (DTDOA) and frequency-difference-of-arrival (FDOA) that mitigates the effects of clock asynchronism to estimate the device positions and velocities. Simulation results suggest that our proposed algorithm is robust and approaches the CRLB when clock skews have small standard deviations.
    IEEE Transactions on Wireless Communications 07/2014; 13(7):3636-3649. DOI:10.1109/TWC.2014.2314096 · 2.76 Impact Factor
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    ABSTRACT: Wireless networks with navigation capability enable mobile devices to both communicate and determine their positions. Diversity navigation employing multiple sensing technologies can overcome the limitation of individual technologies, especially when operating in harsh environments such as indoors. To characterize the diversity of navigation systems in real environments, we performed an extensive measurement campaign, where data from heterogenous sensors were collected simultaneously. The performance of Bayesian navigation algorithms, relying on the particle filter implementation, is evaluated based on measured data from ultrawideband, ZigBee, and inertial sensors. This enables us to quantify the benefits of data fusion as well as the effect of statistical mobility models for real-time diversity navigation.
    IEEE Systems Journal 03/2014; 8(1):115-124. DOI:10.1109/JSYST.2013.2260638 · 1.75 Impact Factor
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    ABSTRACT: Secrecy is essential for a variety of emerging wireless applications where distributed confidential information is communicated in a multilevel network from sources to destinations. Network secrecy can be accomplished by exploiting the intrinsic properties of multilevel wireless networks (MWN). This paper introduces the concept of distributed network secrecy (DNS) and develops a framework for the design and analysis of secure, reliable, and efficient MWNs. Our framework accounts for node spatial distribution, multilevel cluster formation, propagation medium, communication protocol, and energy consumption. This research provides a foundation for DNS and offers a new perspective on the relationship between DNS and network lifetime.
    IEEE Journal on Selected Areas in Communications 09/2013; 31(9):1889-1900. DOI:10.1109/JSAC.2013.130920 · 4.14 Impact Factor
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    ABSTRACT: Safety message dissemination in a vehicular ad-hoc network (VANET) requires vehicle-to-vehicle (V2V) communication with low latency and high reliability. The dynamics of vehicle passing and queueing as well as high mobility create distinctive propagation characteristics of wireless medium and inevitable uncertainty in space-time patterns of the vehicle density on a road. It is therefore of great importance to account for random vehicle locations in V2V communication. In this paper, we characterize intervehicle communication in a random field of vehicles, where a beacon or head vehicle (transmitter) broadcasts safety or warning messages to neighboring client vehicles (receivers) randomly located in a cluster on the road. To account for a doubly stochastic property of the VANET, we first model vehicle's random locations as a stationary Cox process with Fox's H-distributed random intensity (vehicle concentration) and derive the distributional functions of the lth nearest client's distance from the beacon in such a Fox Cox field of vehicles. We then consolidate this spatial randomness of receiving vehicles into a path loss model and develop a triply-composite Fox channel model that combines key wireless propagation effects such as the distance-dependent path loss, large-scale fading (shadowing), and small-scale fading (multipath fading). In Fox channel modeling, each constituent propagation effect is described as Fox's H-variate, culminating again in Fox's H-variate for the received power or equivalently the instantaneous signal-to-noise ratio at the lth nearest client vehicle. Due to versatility of Fox's H-functions, this stochastic channel model can encompass a variety of well-established or generalized statistical propagation models used in wireless communication; be well-fitted to measurement data in diverse propagation environments by varying parameters; and facilitate a unifying analysis for fundamental physical-layer performances, such as error probability- and channel capacity, using again the language of Fox's H-functions. This work serves to develop a unifying framework to characterize V2V communication in a doubly stochastic VANET by averaging both the small- and large-scale fading effects as well as the (random) distance-dependent path losses.
    IEEE Journal on Selected Areas in Communications 09/2013; 31(9):418-433. DOI:10.1109/JSAC.2013.SUP.0513038 · 4.14 Impact Factor
  • Santiago Mazuelas · Yuan Shen · M.Z. Win
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    ABSTRACT: Inferring a sequence of variables from observations is prevalent in a multitude of applications. Traditional techniques such as Kalman filters (KFs) and particle filters (PFs) are widely used for such inference problems. However, these techniques fail to provide satisfactory performance in many important nonlinear or non-Gaussian scenarios. In addition, there is a lack of a unified methodology for the design and analysis of different filtering techniques. To address these problems, in this paper, we propose a new filtering methodology called belief condensation (BC) filtering. First, we establish a general framework for filtering techniques and propose an optimality criterion that leads to BC filtering. We then propose efficient BC algorithms that can best represent the complex distributions arising in the filtering process. The performance of the proposed techniques is evaluated for two representative nonlinear/non-Gaussian problems, showing that the BC filtering can provide accuracy approaching the theoretical bounds and outperform existing techniques in terms of the accuracy versus complexity tradeoff.
    IEEE Transactions on Signal Processing 09/2013; 61(18):4403-4415. DOI:10.1109/TSP.2013.2261991 · 3.20 Impact Factor
  • Yuan Shen · M.Z. Win
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    ABSTRACT: The ability to exchange secret messages and protect against security attacks becomes increasingly important for providing information superiority and confidentiality in modern information systems. These systems require shared secret keys, which can be generated from common random sources with known distributions. However, the assumption on the distribution of the sources may not hold in many realistic scenarios. In this paper, we establish a mathematical framework for secret-key generation using common unknown deterministic sources (UDSs). In particular, we propose a new information measure called intrinsic information to characterize the achievable length of the secret key that can be generated from a UDS. As a case study, we consider a wideband propagation medium in mobile wireless networks as a UDS and derive its intrinsic information as a function of various network parameters. Our results provide a non-Bayesian perspective for secret-key generation as well as practical implications of this new perspective.
    IEEE Journal on Selected Areas in Communications 09/2013; 31(9):1875-1888. DOI:10.1109/JSAC.2013.130919 · 4.14 Impact Factor
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    ABSTRACT: Establishing bounds on the accuracy achievable by localization techniques represents a fundamental technical issue. Bounds on localization accuracy have been derived for cases in which the position of an agent is estimated on the basis of a set of observations and, possibly, of some a priori information related to them (e.g., information about anchor positions and properties of the communication channel). In this paper, new bounds are derived under the assumption that the localization system is map-aware, i.e., it can benefit not only from the availability of observations, but also from the a priori knowledge provided by the map of the environment where it operates. Our results show that: a) map-aware estimation accuracy can be related to some features of the map (e.g., its shape and area) even though, in general, the relation is complicated; b) maps are really useful in the presence of some combination of low SNRs and specific geometrical features of the map (e.g., the size of obstructions); c) in most cases, there is no need of refined maps since additional details do not improve estimation accuracy.
    IEEE Transactions on Information Theory 08/2013; 59(8):5023-5038. DOI:10.1109/TIT.2013.2257915 · 2.65 Impact Factor
  • Youngmin Jeong · Hyundong Shin · M.Z. Win
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    ABSTRACT: In this paper, we integrate key wireless propagation effects such as the path loss, shadowing, and multipath fading into a single Fox's H-variate using the H-preserving property under products, powers, quotients, and their combinations. We then establish a unifying framework to analyze the error probability and channel capacity for V2V communication in a Cox field of vehicles, using again the language of Fox's H-functions. This framework enables us to characterize intervehicle communication in the doubly stochastic vehicular ad-hoc network (VANET) by averaging both small- and large-scale fading processes in time and (random) distance-dependent path losses in space.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
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    W.W.-L. Li · R.A. Iltis · M.Z. Win
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    ABSTRACT: In this paper, we develop a cooperative IMU/radio-location-based navigation system, where each node tracks the location not only based on its own measurements, but also via collaboration with neighbor nodes. The key problem is to design a nonlinear filter to fuse IMU and radiolocation information. We apply the Rao-Blackwellization method by using a particle filter and parallel Kalman filters for the estimation of orientation and other states (i.e., position, velocity, etc.), respectively. The proposed method significantly outperforms the extended Kalman filter (EKF) in the set of simulations here.
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on; 01/2013
  • Wenhan Dai · Yuan Shen · M.Z. Win
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    ABSTRACT: High-accuracy localization is essential for many location-based applications. The position of an object can be obtained from range measurements based on wireless transmissions. Transmitting power allocation not only affects network lifetime and throughput, but also determines localization accuracy. The number of active transmitting nodes is also crucial since it is related to communication load and computation complexity. In this paper, we formulate the power optimization problem that provides the best localization accuracy under power constraints. We first prove the sparsity of the optimal power allocation, i.e., the optimal localization accuracy can be achieved by activating no more than (J) transmitting nodes in d-dimensional networks. Inspired by such sparsity, we derive the expressions of the optimal power allocation in 2-D networks. We also put forth a near-optimal algorithm for the power allocation problem with individual power constraints. Our results provide a theoretical basis for designing transmitting node selection and power allocation algorithms for network localization.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
  • A. Rabbachin · A. Conti · M.Z. Win
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    ABSTRACT: The demand of communication confidentiality in wireless network is rapidly increasing. The level of confidentiality can be enhanced by physical layer techniques exploiting intrinsic properties of a wireless network. We develop a framework for design and analysis of wireless network with secrecy that accounts for node distribution, propagation medium, and intentional interference. The framework enables the quantification of how intentional interference generated via legitimate network resources engineering mitigates the capability of the eavesdropping network. This research provides insight on the opportunistic use of legitimate network resources for enhancing network secrecy.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
  • Henghui Lu · S. Mazuelas · M.Z. Win
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    ABSTRACT: High-accuracy localization in harsh environments is a challenging research problem, mainly due to non-line-of-sight (NLOS) propagation, multipath effect, and multiuser interference. Many techniques have been proposed to address this problem; most of them focus on improving the accuracy of ranging estimation, e.g., NLOS identification and mitigation. In this paper, we take ranging one step further by introducing the concept of ranging likelihood (RL), showing that RL is the essential element for localization. Moreover, we present effective techniques for real-time RL estimation. We focus on ultra-wide bandwidth (UWB) localization systems and assess the performance of the proposed approach by using the data from an extensive indoor measurement campaign. The results show that the proposed approach can significantly improve the performance of wireless localization in harsh environments.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
  • Jemin Lee · A. Conti · A. Rabbachin · M.Z. Win
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    ABSTRACT: Secrecy is a key enabler for various wireless applications in which distributed confidential information is communicated in a multilevel network from sources to destinations. Network secrecy can be accomplished by exploiting the intrinsic properties of multilevel wireless networks (MWNs). This paper introduces the concept of distributed network secrecy (DNS) and develops a framework for design and analysis of confidential MWNs. Our framework accounts for node distribution, network configuration, propagation medium, and communication protocol. This research offers the foundation of DNS and quantifies the impact of network configuration on DNS for self-organizing MWNs.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
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    ABSTRACT: Accuracy and complexity represent fundamental aspects of localization and tracking systems. In this manuscript the impact of a priori knowledge about agent position on the accuracy and the complexity of localization algorithms is investigated. In particular, first Cramer-Rao bounds on localization accuracy are derived under the assumption that a priori information is described by a map restricting the agent position to a specific region. Then, the computational complexity of optimal map-aware and map-unaware localization techniques is assessed. Our results evidence that: a) map-aware localization accuracy can be related to some geometrical features of the map but usually exhibits a complicated dependence on them; b) in some scenarios map-aware localization algorithms provide better accuracy than their map-unaware counterparts at comparable computational complexity.
    Communications (ICC), 2013 IEEE International Conference on; 01/2013
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    Yuan Shen · Santiago Mazuelas · M.Z. Win
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    ABSTRACT: Real-time and reliable location information of mobile nodes is a key enabler for many emerging wireless network applications. Such information can be obtained via network navigation, a new paradigm in which nodes exploit both spatial and temporal cooperation to infer their positions. In this paper, we establish a theoretical foundation for network navigation and determine the fundamental limits of navigation accuracy using equivalent Fisher information analysis. We then introduce the notion of carry-over information and provide a geometrical interpretation for the evolution of navigation information. Our framework unifies the navigation information obtained from spatial and temporal cooperation, leading to a deep understanding of information evolution and cooperation benefits in navigation networks.
    IEEE Journal on Selected Areas in Communications 10/2012; 30(9):1823-1834. DOI:10.1109/JSAC.2012.121028 · 4.14 Impact Factor
  • Santiago Mazuelas · Yuan Shen · M.Z. Win
    [Show abstract] [Hide abstract]
    ABSTRACT: Inferring a sequence of variables from observations is a prevalent task in a multitude of applications. However, in some nonlinear or non-Gaussian scenarios, traditional techniques such as Kalman filters (KFs) and particle filters (PFs) fail to provide satisfactory performance. Moreover, there is a lack of a unifying framework for the analysis and development of different filtering techniques. In this paper, we present a general framework for filtering that allows to formulate an optimality criterium leading to the concept of belief condensation filtering (BCF). Moreover, we develop discrete BCFs that are optimal under such framework. Finally, simulation results are presented for the important filtering task that arises in ultrawide bandwidth (UWB) ranging. We show that BCF can obtain accuracies approaching the theoretical benchmark but with a smaller complexity than PFs.
    Ultra-Wideband (ICUWB), 2012 IEEE International Conference on; 09/2012
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    ABSTRACT: Location-awareness is becoming increasingly important in wireless networks. Indoor localization can be enabled through wideband or ultra-wide bandwidth (UWB) transmission, due to its fine delay resolution and obstacle-penetration capabilities. A major hurdle is the presence of obstacles that block the line-of-sight (LOS) path between devices, affecting ranging performance and, in turn, localization accuracy. Many techniques have been proposed to address this issue, most of which make modifications to the localization algorithm. Since many localization algorithms work with distance or angle estimates, rather than received waveforms, information inherent in the wideband waveform is lost, leading to sub-optimal ranging error mitigation. To avoid this information loss, we present a novel approach to mitigate ranging errors directly in the physical layer. In contrast to existing techniques, which detect the non-line-of-sight (NLOS) condition, our approach directly mitigates the bias incurred in both LOS and non-LOS conditions. In particular, we apply two classes of non-parametric regressors to form an estimate of the ranging error. Our work is based on, and validated by, an extensive indoor measurement campaign with FCC-compliant UWB radios. The results show that the proposed regressors provide significant performance improvements in various practical localization scenarios, compared to conventional approaches.
    IEEE Transactions on Communications 06/2012; 60(6):1719-1728. DOI:10.1109/TCOMM.2012.042712.110035 · 1.98 Impact Factor

Publication Stats

17k Citations
333.01 Total Impact Points

Institutions

  • 2003–2013
    • Massachusetts Institute of Technology
      • Laboratory for Information and Decision Systems
      Cambridge, Massachusetts, United States
    • Broadcom Corporation
      Irvine, California, United States
  • 2009–2011
    • The Chinese University of Hong Kong
      • Department of Information Engineering
      Hong Kong, Hong Kong
    • Bilkent University
      • Department of Electrical & Electronic Engineering
      Ankara, Ankara, Turkey
  • 2008–2011
    • Kyung Hee University
      • Electronics and Radio Engineering Division
      Seoul, Seoul, South Korea
  • 2001–2011
    • University of Bologna
      • "Guglielmo Marconi" Department of Electrical, Electronic and Information Engineering DEI
      Bolonia, Emilia-Romagna, Italy
    • University of Rome Tor Vergata
      • Dipartimento di Ingegneria Elettronica
      Roma, Latium, Italy
  • 2010
    • Institute for Environmental Protection and Research (ISPRA)
      Roma, Latium, Italy
  • 2008–2009
    • University of Ferrara
      • Department of Engineering
      Ferrare, Emilia-Romagna, Italy
  • 2004–2008
    • University of Texas at Dallas
      • Department of Electrical Engineering
      Dallas, TX, United States
  • 2007
    • University of Oulu
      • Centre for Wireless Communications (CWC)
      Uleoborg, Oulu, Finland
    • Università degli Studi dell'Aquila
      Aquila, Abruzzo, Italy
    • Aristotle University of Thessaloniki
      Saloníki, Central Macedonia, Greece
  • 2006
    • Mitsubishi Electric Research Laboratories
      Cambridge, Massachusetts, United States
    • École Polytechnique Fédérale de Lausanne
      • School of Computer and Communication Sciences
      Lausanne, Vaud, Switzerland
    • University of Florence
      Florens, Tuscany, Italy
  • 2002–2006
    • University of Alberta
      • Department of Electrical and Computer Engineering
      Edmonton, Alberta, Canada
    • The American University of Rome
      Roma, Latium, Italy
  • 1998–2005
    • AT&T Labs
      Austin, Texas, United States
  • 2000–2004
    • Indian Institute of Technology Delhi
      • Department of Electrical Engineering
      New Delhi, NCT, India
  • 1997–2003
    • University of Southern California
      • Department of Electrical Engineering
      Los Angeles, California, United States
  • 2001–2002
    • Indian Institute of Technology Ropar
      • Department of Electrical Engineering
      Rūpar, Punjab, India
  • 1990–1995
    • California Institute of Technology
      • Jet Propulsion Laboratory
      Pasadena, California, United States