M.Z. Win

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (378)423.81 Total impact

  • [Show abstract] [Hide abstract]
    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. · 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. · 2.76 Impact Factor
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    ABSTRACT: Localization of wireless node is a key feature in many applications. Traditional localization has exploited the signal runtime between “agent” nodes that are to be localized and a set of “anchor” nodes with known position. Recently, cooperative localization that also uses runtime measurement between agent nodes has been shown to provide superior performance. This paper analyzes the optimum power and bandwidth allocation in such systems. We first formulate the general optimization problem and show that it is non-convex. We then develop an approximate algorithm based on Taylor expansion and iterative optimization of power and bandwidth separately to find an approximate solution; simulations show that results are close to the optimum solution (which is NP-hard). We also find that the importance of cooperative localization increases (and agents get assigned more resources) if the anchor deployment is bad in the sense that it provides high geometric dilution of precision and/or suffers from significant blockage between anchors and agents.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
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    ABSTRACT: Passive radars relying on signals of opportunity enable new applications based on stealth tracking of targets without the need of radar signals emissions. Long term evolution (LTE) base stations employing orthogonal frequency division multiplexing (OFDM) signals are excellent candidates as illuminators of opportunity thanks to their wide availability. The tracking accuracy of such passive radars depends on prior knowledge (e.g., the wireless environment) and signal processing (e.g., clutter mitigation and tracking algorithm). This paper proposes passive radar systems exploiting LTE base stations as illuminators of opportunity to detect and track moving targets in a monitored environment. We analyze such systems based on a Bayesian framework for detection of moving targets and estimation of their position and velocity. A case study accounting for the LTE extended pedestrian model is presented, with various settings in terms of network configuration, wireless propagation, and signal processing.
    2014 ICC - 2014 IEEE International Conference on Communication Workshop (ICC); 06/2014
  • We nhan Dai, Yuan Shen, Moe Z. Win
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    ABSTRACT: Accurate position information enables numerous location-based applications. Wireless network localization is a promising localization technique that permits cooperation among mobile objects to enhance localization services. The allocation of transmitting power for such networks plays a critical role since it determines network lifetime, throughput, as well as the localization accuracy. In this paper, we establish an optimization framework for power allocation in cooperative localization networks. We first show that the optimal solution for the power allocation problem can be obtained by semi-definite programs (SDPs). For implementation in cooperative localization networks, we develop efficient and distributed power allocation strategies via relaxation of the original problem. In particular, we decompose the power allocation problem into infrastructure and cooperation parts. We transform the former into SDPs and derive upper bounds for the localization accuracy of the latter. These bounds enable us to develop efficient distributed strategies. Simulation results show that these strategies can achieve significant performance improvement compared to the unoptimized strategies in terms of localization accuracy.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
  • Tianheng Wang, Yuan Shen, Moe Z. Win
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    ABSTRACT: Location-awareness plays a key role in various applications in future wireless networks. In GPS-challenged environments, location-awareness can be achieved via wireless navigation networks, which call for an efficient scheduling algorithm to optimize the navigation performance under communication constraints. In this paper, we develop a general framework for the design and analysis of scheduling algorithms for navigation networks with multiple measurement pairs per time slot. In particular, we provide sufficient and necessary conditions for the stability of the error evolution, and derive bounds on the time-averaged network localization errors (NLEs) for opportunistic and random scheduling. Furthermore, we show that the two scheduling algorithms are optimal in terms of the error scaling with respect to the number of agents, and we quantify the performance gain from measurement pair selections exploiting the network states. These results provide guidelines for designing efficient scheduling algorithms for network navigation.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
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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. · 1.75 Impact Factor
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    ABSTRACT: Sensor radars (SRs) are important for a variety of applications requiring passive tracking of moving targets. The accuracy of passive tracking is severely degraded by wireless propagation impairments such as multipath, clutter, and non line-of-sight conditions, especially in indoor environments. These impairments can be alleviated by exploiting the multiple sensing and smart processing of radar signals. In this letter, we aim to illustrate the dependence of sensor topologies, waveform processing methods, and tracking algorithm parameters on SR performance. A case study involving both monostatic and multistatic ultra-wideband SRs for indoor environments is presented by jointly considering the wireless medium, ranging technique, and tracking algorithm.
    Wireless Communications Letters, IEEE. 01/2014; 3(2):157-160.
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    ABSTRACT: Indoor navigation using the existing wireless infrastructure and mobile devices is a very active research area. The major challenge is to leverage the extensive smartphone sensor suite to achieve location tracking with high accuracy. In this paper, we develop a navigation algorithm which fuses the WiFi received signal strength indicator (RSSI) and smartphone inertial sensor measurements. A sequential Monte Carlo filter is developed for inertial sensor based tracking, and a radiolocation algorithm is developed to infer mobile location based on RSSI measurements. The simulation results show that the proposed algorithm significantly outperforms the extended Kalman filter (EKF), and achieves competitive location accuracy compared with the round trip time (RTT) based ultra-wideband (UWB) system.
    GLOBECOM 2013 - 2013 IEEE Global Communications Conference; 12/2013
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    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.
    IEEE/ACM Transactions on Networking 09/2013; 22(4). · 1.99 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. · 4.14 Impact Factor
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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. · 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. · 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. · 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. · 2.65 Impact Factor
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    ABSTRACT: We consider the problem of localizing two sensors using signals of opportunity from beacons with known positions. Beacons and sensors 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 Cram\'er-Rao lower bound (CRLB) of sensor position and velocity estimation, we quantify the errors caused by clock asynchronism.
  • Source
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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; · 1.99 Impact Factor
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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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    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
  • 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

Publication Stats

15k Citations
423.81 Total Impact Points


  • 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
      Bologna, Emilia-Romagna, Italy
    • University of Rome Tor Vergata
      Roma, Latium, Italy
  • 2008–2009
    • University of Ferrara
      Ferrare, Emilia-Romagna, Italy
  • 2003–2008
    • University of Texas at Dallas
      • • Department of Electrical Engineering
      • • Erik Jonsson School of Engineering and Computer Science
      Dallas, TX, United States
  • 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
  • 1990–1995
    • California Institute of Technology
      • Jet Propulsion Laboratory
      Pasadena, CA, United States