M.Z. Win

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (359)337.36 Total impact

  • [show abstract] [hide abstract]
    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 01/2014; 8(1):115-124. · 1.27 Impact Factor
  • Yuan Shen, Wenhan Dai, Moe Z. Win
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    ABSTRACT: Reliable and accurate localization of mobile objects is essential for many applications in wireless networks. In range-based localization, the position of the object can be inferred using the distance measurements from wireless signals exchanged with active objects or reflected by passive ones. Power allocation for ranging signals is important since it affects not only network lifetime and throughput but also localization accuracy. In this paper, we establish a unifying optimization framework for power allocation in both active and passive localization networks. In particular, we first determine the functional properties of the localization accuracy metric, which enable us to transform the power allocation problems into second-order cone programs (SOCPs). We then propose the robust counterparts of the problems in the presence of parameter uncertainty and develop asymptotically optimal and efficient near-optimal SOCP-based algorithms. Our simulation results validate the efficiency and robustness of the proposed algorithms.
    09/2013;
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    ABSTRACT: In wireless location-aware networks, mobile nodes (agents) typically obtain their positions through ranging with respect to nodes with known positions (anchors). Transmit power allocation not only affects network lifetime, throughput, and interference, but also determines localization accuracy. In this paper, we present an optimization framework for robust power allocation in network localization to tackle imperfect knowledge of network parameters. In particular, we formulate power allocation problems to minimize the squared position error bound (SPEB) and the maximum directional position error bound (mDPEB), respectively, for a given power budget. We show that such formulations can be efficiently solved via conic programming. Moreover, we design an efficient power allocation scheme that allows distributed computations among agents. The simulation results show that the proposed schemes significantly outperform uniform power allocation, and the robust schemes outperform their non-robust counterparts when the network parameters are subject to uncertainty.
    IEEE/ACM Transactions on Networking 05/2013; · 2.01 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 manuscript 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 signal-to-noise ratios 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.
    03/2013;
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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 01/2013; 59(8):5023-5038. · 2.62 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 01/2013; 31(9):1875-1888. · 3.12 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 01/2013; 31(9):418-433. · 3.12 Impact Factor
  • 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
  • S. 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 01/2013; 61(18):4403-4415. · 2.81 Impact Factor
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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
  • 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
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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
  • [show abstract] [hide abstract]
    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 01/2013; 31(9):1889-1900. · 3.12 Impact Factor
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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
  • 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
  • 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 · 4.63 Impact Factor
  • Source
    P. C. Pinto, J. Barros, M. Z. Win
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    ABSTRACT: The ability to exchange secret information is critical to many commercial, governmental, and military networks. Information-theoretic security—widely accepted as the strictest notion of security—relies on channel coding techniques that exploit the inherent randomness of the propagation channels to strengthen the security of digital communications systems. Motivated by recent developments in the field, we aim to characterize the fundamental secrecy limits of wireless networks. The paper is comprised of two separate parts. In Part I, we define the intrinsically secure communications graph ( $i{cal S}$ -graph), a random graph which describes the connections that can be securely established over a large-scale network. We provide conclusive results for the local connectivity of the Poisson $i{cal S}$ -graph, in terms of node degrees and isolation probabilities. We show how the secure connectivity of the network varies with the wireless propagation effects, the secrecy rate threshold of each link, and the noise powers of legitimate nodes and eavesdroppers. We then propose sectorized transmission and eavesdropper neutralization as viable strategies for improving the secure connectivity. Our results help clarify how the spatial density of eavesdroppers can compromise the intrinsic security of wireless networks. In Part II of the paper, we study the achievable secrecy rates and the effect of eavesdropper collusion.
    IEEE Transactions on Information Forensics and Security 03/2012; · 1.90 Impact Factor
  • Source
    P.C. Pinto, M.Z. Win
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    ABSTRACT: The ability to exchange secret information is critical to many commercial, governmental, and military networks. The intrinsically secure communications graph (iS-graph) is a random graph which describes the connections that can be securely established over a large-scale network, by exploiting the physical properties of the wireless medium. This paper aims to characterize the global properties of the iS-graph in terms of (1) percolation on the infinite plane, and (2) full connectivity on a finite region. First, for the Poisson iS-graph defined on the infinite plane, the existence of a phase transition is proven, whereby an unbounded component of connected nodes suddenly arises as the density of legitimate nodes is increased. This shows that long-range secure communication is still possible in the presence of eavesdroppers. Second, full connectivity on a finite region of the Poisson iS-graph is considered. The exact asymptotic behavior of full connectivity in the limit of a large density of legitimate nodes is characterized. Then, simple, explicit expressions are derived in order to closely approximate the probability of full connectivity for a finite density of legitimate nodes. These results help clarify how the presence of eavesdroppers can compromise long-range secure communication.
    IEEE Transactions on Information Theory 01/2012; 58(3):1716-1730. · 2.62 Impact Factor
  • S. 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; 01/2012
  • Yuan Shen, Tao Luo, Moe Z. Win
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    ABSTRACT: Long term evolution (LTE) is considered to be a key technology for the next generation of cellular telecommunications. In LTE systems, each user equipment (UE) detects the surrounding cells by searching their identities (IDs) in the synchronization channels of the received waveform. Searching and tracking neighboring cells is important for cellular network management, such as handover and base station cooperation. In this paper, we establish a general framework for neighboring cell search (NCS) in LTE systems. In particular, we derive sufficient signal metrics (SSMs) for NCS under various channel conditions, and develop NCS algorithms based on the SSMs, which optimally combine multiple observations over space and/or time. Moreover, we develop a statistical model for NCS using probability analysis. The performance of NCS algorithms is characterized in terms of the number of detected cells and the cell detection probability, and simulation results validate the effectiveness of the proposed algorithms.
    IEEE Transactions on Wireless Communications 01/2012; 11(3):0908-919. · 2.42 Impact Factor

Publication Stats

12k Citations
337.36 Total Impact Points

Institutions

  • 2003–2012
    • 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
      Bologna, Emilia-Romagna, Italy
    • University of Rome Tor Vergata
      Roma, Latium, Italy
  • 2008–2009
    • University of Ferrara
      Ferrare, Emilia-Romagna, Italy
  • 2007
    • University of Oulu
      Uleoborg, Oulu, Finland
    • Università degli Studi dell'Aquila
      Aquila, Abruzzo, Italy
    • Aristotle University of Thessaloniki
      Saloníki, Central Macedonia, Greece
  • 2006
    • 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
    • University of Massachusetts Amherst
      • Department of Electrical and Computer Engineering
      Amherst Center, MA, United States
  • 1998–2005
    • AT&T Labs
      Austin, Texas, United States
  • 2000–2004
    • Indian Institute of Technology Delhi
      • Department of Electrical Engineering
      New Delhi, NCT, India
  • 1996–2003
    • University of Southern California
      • Department of Electrical Engineering
      Los Angeles, CA, United States
  • 1995
    • California Institute of Technology
      • Jet Propulsion Laboratory
      Pasadena, CA, United States