M.Z. Win

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (388)446.6 Total impact

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    ABSTRACT: Sensor radar networks enable important new applications based on accurate localization. They rely on the quality of range measurements, which serve as observations for inferring a target location. In harsh propagation environments (e.g., indoors), such observations can be nonrepresentative of the target due to noise, multipath, clutter, and non-line-of-sight conditions leading to target misdetection, false-alarm events, and inaccurate localization. These conditions can be mitigated by selecting and processing a subset of representative observations. We introduce blind techniques for the selection of representative observations gathered by sensor radars operating in harsh environments. A methodology for the design and analysis of sensor radar networks is developed, taking into account the aforementioned impairments and observation selection. Results are obtained for noncoherent ultra-wideband sensor radars in a typical indoor environment (with obstructions, multipath, and clutter) to enable a clear understanding of how observation selection improves the localization accuracy.
    IEEE Transactions on Vehicular Technology 04/2015; 64(4):1388-1400. DOI:10.1109/TVT.2015.2397312 · 2.64 Impact Factor
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    ABSTRACT: Location awareness is becoming essential for emerging wireless applications where most network activities require the location information of network nodes, e.g., routing between nodes in ad-hoc sensor networks, positioning vehicles on the road, or tracking targets in underwater acoustic sensor networks. In particular, cooperation among nodes is highly beneficial for the localization accuracy and coverage in harsh environments. In this paper, we study least square (LS) cooperative localization in the presence of arbitrary non-line-of-sight (NLOS) ranging bias. To develop the network position error bound (PEB), we first derive the Fisher information matrix (FIM) for a general NLOS bias model and show that a Gaussian bias due to NLOS effects is the worst case that produces the extremal FIM, whereas a constant bias or equivalently full line-of-sight is the best situation leading to the largest FIM in a sense of Löwner partial ordering. We then analyze the asymptotic performance, such as uniform convergence, consistency, and efficiency, of LS cooperative localization to quantify the deviations of localization accuracy for LS, squared-range LS, and squared-range weighted LS solutions from the fundamental limit (i.e., Cramér–Rao lower bound) due to their practical tractability. We also propose a simple distributed algorithm for LS cooperative localization by integrating squared-range relaxation into Gaussian variational message passing on the localization network. To account for stochastic natures of node locations and populations, we further characterize the network PEB for Gilbert's disk localization network, where anchors and/or agents are randomly distributed in the network according to point processes.
    IEEE Transactions on Vehicular Technology 04/2015; 64(4):1-1. DOI:10.1109/TVT.2015.2398874 · 2.64 Impact Factor
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    ABSTRACT: Increasing sources of sensor measurements and prior knowledge have become available for indoor localization on smartphones. How to effectively utilize these sources for enhancing localization accuracy is an important yet challenging problem. In this paper, we present an area state-aided localization algorithm that exploits various sources of information. Specifically, we introduce the concept of area state to indicate the area where the user is on an indoor map. The position of the user is then estimated using inertial measurement unit (IMU) measurements with the aid of area states. The area states are in turn updated based on the position estimates. To avoid accumulated errors of IMU measurements, our algorithm uses WiFi received signal strength indicator (RSSI) to indicate the vicinity of the user to the routers. The experiment results show that our system can achieve satisfactory localization accuracy in a typical indoor environment.
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    ABSTRACT: In contrast to its wired counterpart, wireless communication is highly susceptible to eavesdropping due to the broadcast nature of the wireless propagation medium. Recent works have proposed the use of interference to reduce eavesdropping capabilities in wireless wiretap networks. However, the concurrent effect of interference on both eavesdropping receivers (ERs) and legitimate receivers (LRs) has not been thoroughly investigated, and carefully engineering the network interference is required to harness the full potential of interference for wireless secrecy. This two part paper addresses this issue by proposing a generalized interference alignment (GIA) technique, which jointly designs the transceivers at the legitimate partners to impede the ERs without interfering with LRs. In Part I, we have established a theoretical framework for the GIA technique. In Part II, we will first propose an efficient GIA algorithm that is applicable to large-scale networks and then evaluate the performance of this algorithm in stochastic wireless wiretap network via both analysis and simulation. These results reveal insights into when and how GIA contributes to wireless secrecy.
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    ABSTRACT: Interference alignment (IA) has attracted enormous research interest as it achieves optimal capacity scaling with respect to signal to noise ratio on interference networks. IA has also recently emerged as an effective tool in engineering interference for secrecy protection on wireless wiretap networks. However, despite the numerous works dedicated to IA, two of its fundamental issues, i.e., feasibility conditions and transceiver design, are not completely addressed in the literature. In this two part paper, a generalised interference alignment (GIA) technique is proposed to enhance the IA's capability in secrecy protection. A theoretical framework is established to analyze the two fundamental issues of GIA in Part I and then the performance of GIA in large-scale stochastic networks is characterized to illustrate how GIA benefits secrecy protection in Part II. The theoretical framework for GIA adopts methodologies from algebraic geometry, determines the necessary and sufficient feasibility conditions of GIA, and generates a set of algorithms that can solve the GIA problem. This framework sets up a foundation for the development and implementation of GIA.
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    ABSTRACT: Wideband ranging is essential for numerous emerging applications that rely on accurate location awareness. The quality of range information, which depends on network intrinsic properties and signal processing techniques, affects the localization accuracy. A popular class of ranging techniques is based on energy detection owing to its low-complexity implementation. This paper establishes a tractable model for the range information as a function of wireless environment, signal features, and energy detection techniques. Such a model serves as a cornerstone for the design and analysis of wideband ranging systems. Based on the proposed model, we develop practical soft-decision and hard-decision algorithms. A case study for ranging and localization systems operating in a wireless environment is presented. Sample-level simulations validate our theoretical results.
    IEEE Journal of Selected Topics in Signal Processing 02/2015; 9(2):216-228. DOI:10.1109/JSTSP.2014.2370934 · 3.63 Impact Factor
  • Wenhan Dai, Yuan Shen, Moe Win
    IEEE Journal on Selected Areas in Communications 01/2015; DOI:10.1109/JSAC.2015.2430271 · 4.14 Impact Factor
  • IEEE Journal on Selected Areas in Communications 01/2015; DOI:10.1109/JSAC.2015.2430191 · 4.14 Impact Factor
  • Wenhan Dai, Yuan Shen, Moe Z. Win
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    ABSTRACT: Device-to-device (D2D) communication in cellular networks is a promising concept that permits cooperation among mobile devices not only to increase data throughput but also to enhance localization services. In those networks, the allocation of transmitting power plays a critical role in determining network lifetime and localization accuracy. Meanwhile, it is a challenging task for implementation in cooperative D2D networks, since each device has only imperfect estimates of local network parameters in distributed settings. In this paper, we establish an optimization framework for robust power allocation in cooperative wireless network localization, and develop distributed power allocation strategies. In particular, we decompose the power allocation problem into infrastructure and cooperation phases, show the sparsity property of the optimal power allocation, and develop efficient power allocation strategies. Simulation results show that these strategies can achieve significant performance improvement in localization accuracy compared to the uniform strategies.
    IEEE Journal on Selected Areas in Communications 01/2015; 33(1):28-40. DOI:10.1109/JSAC.2014.2369631 · 4.14 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
  • 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: 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
  • 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
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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
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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: 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.
    01/2014; 3(2):157-160. DOI:10.1109/WCL.2013.120513.130760
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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
  • Tianheng Wang, Yuan Shen, Moe Z. Win
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    ABSTRACT: Wireless navigation networks enable location-awareness in GPS-challenged environments. For such networks, scheduling algorithms are needed to improve the navigation accuracy through measurement pair selections under limited communication resource. In this paper, we develop an analytical framework to determine the location error evolution for different scheduling algorithms and network settings. Under this framework, we provide sufficient conditions for the stability of the location error evolution, and we quantify the time-averaged network location errors (NLEs) for scheduling algorithms with and without exploiting the network states. Furthermore, we show the optimality of the proposed scheduling algorithms in terms of the error scaling with respect to the agent density. These results provide fundamental insights into the effects of scheduling algorithms and network settings on the location error evolution, leading to efficient scheduling algorithms for navigation networks.
    GLOBECOM 2013 - 2013 IEEE Global Communications Conference; 12/2013

Publication Stats

19k Citations
446.60 Total Impact Points

Institutions

  • 2003–2014
    • 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
      Sŏul, 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
      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
      • • Erik Jonsson School of Engineering and Computer Science
      Dallas, TX, United States
  • 2007
    • Università degli Studi dell'Aquila
      Aquila, Abruzzo, Italy
    • University of Oulu
      • Centre for Wireless Communications (CWC)
      Uleoborg, Oulu, Finland
    • 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
  • 2004–2006
    • Mitsubishi Electric Research Laboratories
      Cambridge, Massachusetts, United States
  • 2002–2006
    • University of Alberta
      • Department of Electrical and Computer Engineering
      Edmonton, Alberta, Canada
    • The American University of Rome
      Roma, Latium, Italy
    • University of California, Los Angeles
      • Department of Electrical Engineering
      Los Ángeles, California, United States
    • 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
  • 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