Moe Z. Win

Massachusetts Institute of Technology, Cambridge, Massachusetts, United States

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Publications (427)431.47 Total impact

  • No preview · Article · Dec 2016 · IEEE Transactions on Signal Processing
  • No preview · Article · Dec 2016 · IEEE Transactions on Communications
  • No preview · Conference Paper · Jul 2016
  • Source
    Full-text · Conference Paper · May 2016
  • No preview · Conference Paper · Mar 2016
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    [Show abstract] [Hide abstract] ABSTRACT: Asisted living (AL) technologies, enabled by technical advances such as the advent of the Internet of Things, are increasingly gaining importance in our aging society. This article discusses the potential of future high-accuracy localization systems as a key component of AL applications. Accurate location information can be tremendously useful to realize, e.g., behavioral monitoring, fall detection, and real-time assistance. Such services are expected to provide older adults and people with disabilities with more independence and thus to reduce the cost of caretaking. Total cost of ownership and ease of installation are paramount to make sensor systems for AL viable. In case of a radio-based indoor localization system, this implies that a conventional solution is unlikely to gain widespread adoption because of its requirement to install multiple fixed nodes (anchors) in each room. This article therefore places its focus on 1) discussing radiolocalization methods that reduce the required infrastructure by exploiting information from reflected multipath components (MPCs) and 2) showing that knowledge about the propagation environment enables localization with high accuracy and robustness. It is demonstrated that new millimeter-wave (mm-wave) technology, under investigation for 5G communications systems, will be able to provide centimeter (cm)-accuracy indoor localization in a robust manner, ideally suited for AL.
    Full-text · Article · Mar 2016 · IEEE Signal Processing Magazine
  • [Show abstract] [Hide abstract] ABSTRACT: Asisted living (AL) technologies, enabled by technical advances such as the advent of the Internet of Things, are increasingly gaining importance in our aging society. This article discusses the potential of future high-accuracy localization systems as a key component of AL applications. Accurate location information can be tremendously useful to realize, e.g., behavioral monitoring, fall detection, and real-time assistance. Such services are expected to provide older adults and people with disabilities with more independence and thus to reduce the cost of caretaking. Total cost of ownership and ease of installation are paramount to make sensor systems for AL viable. In case of a radio-based indoor localization system, this implies that a conventional solution is unlikely to gain widespread adoption because of its requirement to install multiple fixed nodes (anchors) in each room. This article therefore places its focus on 1) discussing radiolocalization methods that reduce the required infrastructure by exploiting information from reflected multipath components (MPCs) and 2) showing that knowledge about the propagation environment enables localization with high accuracy and robustness. It is demonstrated that new millimeter-wave (mm-wave) technology, under investigation for 5G communications systems, will be able to provide centimeter (cm)-accuracy indoor localization in a robust manner, ideally suited for AL.
    No preview · Article · Mar 2016 · IEEE Signal Processing Magazine
  • Dataset: 1570225684
    No preview · Dataset · Feb 2016
  • Dataset: 1570225684
    No preview · Dataset · Feb 2016
  • No preview · Article · Jan 2016 · IEEE Transactions on Signal Processing
  • Liangzhong Ruan · Wenhan Dai · Moe Z. Win
    No preview · Conference Paper · Dec 2015
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    [Show description] [Hide description] DESCRIPTION: Resource including power and bandwidth allocation strategies for wireless cooperative localization networks
    Full-text · Research · Oct 2015
  • [Show abstract] [Hide abstract] ABSTRACT: Massive MIMO is, in general, severely affected by pilot contamination. As opposed to traditional detectors, we propose a group-blind detector that takes into account the presence of pilot contamination. While sticking to the traditional structure of the training phase, where orthogonal pilot sequences are reused, we use the excess antennas at each base station to partially remove interference during the uplink data transmission phase. We analytically derive the asymptotic SINR achievable with group-blind detection, and confirm our findings by simulations. We show, in particular, that in an interference-limited scenario with one dominant interfering cell, the SINR can be doubled compared to non-group-blind detection.
    No preview · Article · Oct 2015
  • Wenhan Dai · Yuan Shen · Moe Z. Win
    [Show abstract] [Hide abstract] ABSTRACT: Network navigation is an emerging paradigm that enables high-accuracy location awareness in GPS-challenged environments. Two important operations of network navigation, location inference and power control, interrelate with each other, thus motivating the design of joint inference and control algorithms. In this paper, we develop efficient network navigation algorithms with optimized energy allocation. In particular, we first determine the confidence region for lzocation inference based on Fisher information analysis, and then design robust energy allocation strategies that minimize the position errors of the agents within the confidence region. Based on these strategies, both centralized and distributed energy-efficient network navigation algorithms are developed. Simulation results show that the proposed algorithms significantly reduce the position errors compared to the algorithms with uniform or non-robust power control.
    No preview · Article · Jul 2015 · IEEE Journal on Selected Areas in Communications
  • Youngmin Jeong · Hyundong Shin · Moe Z. Win
    [Show abstract] [Hide abstract] ABSTRACT: The H-transforms are integral transforms that involve Fox's H-functions as kernels. A large variety of integral transforms can be put into particular forms of the H-transform since H-functions subsume most of the known special functions including Meijer's G-functions. In this paper, we embody the H-transform theory into a unifying framework for modeling and analysis in wireless communication. First, we systematize the use of elementary identities and properties of the H-transform by introducing operations on parameter sequences of H-functions. We then put forth H-fading and degree-2 irregular H-fading to model radio propagation under composite, specular, and/or inhomogeneous conditions. The H-fading describes composite effects of multipath fading and shadowing as a single H-variate, including most of typical models such as Rayleigh, Nakagami-m, Weibull, α-μ, N∗ Nakagami-m, (generalized) K-fading, and Weibull/gamma fading as its special cases. As a new class of H-variates (called the degree-ζ irregular H-variate), the degree-2 irregular H-fading characterizes specular and/or inhomogeneous radio propagation in which the multipath component consists of a strong specularly reflected or line-of-sight (LOS) wave as well as unequal-power or correlated in-phase and quadrature scattered waves. This fading includes a variety of typical models such as Rician, Nakagami-q, κ-μ, η-μ, Rician/LOS gamma, and κ-μ/LOS gamma fading as its special cases. Finally, we develop a unifying H-transform analysis for the amount of fading, error probability, channel capacity, and error exponent in wireless communication using the new systematic language of transcendental H-functions. By virtue of two essential operations - called Mellin and convolution operations - involved in the Mellin transform and Mellin convolution of two H-functions, the H-transforms for these performance measures culminate in H-functions. Using the algebraic asymptotic expansions of the H-transform, we further analyze the error probability and capacity at high and low signal-to-noise ratios in a unified fashion.
    No preview · Article · Jul 2015 · IEEE Transactions on Information Theory
  • [Show abstract] [Hide abstract] ABSTRACT: Wireless localization has a great importance in a variety of areas including commercial, service, and military positioning and tracking systems. In harsh indoor environments, it is hard to localize an agent with high accuracy due to non-line-of-sight (NLOS) radio blockage or insufficient information from anchors. Therefore, NLOS identification and mitigation are highlighted as an effective way to improve the localization accuracy. In this paper, we develop a robust and efficient algorithm to enhance the accuracy for (ultrawide bandwidth) time-of-arrival localization through identifying and mitigating NLOS signals with relevance vector machine (RVM) techniques. We also propose a new localization algorithm, called the two-step iterative (TSI) algorithm, which converges fast with a finite number of iterations. To enhance the localization accuracy as well as expand the coverage of a localizable area, we continue to exploit the benefits of RVM in both classification and regression for cooperative localization by extending the TSI algorithm to a centralized cooperation case. For self-localization setting, we then develop a distributed cooperative algorithm based on variational Bayesian inference to simplify message representations on factor graphs and reduce communication overheads between agents. In particular, we build a refined version of Gaussian variational message passing to reduce the computational complexity while maintaining the localization accuracy. Finally, we introduce the notion of a stochastic localization network to verify proposed cooperative localization algorithms.
    No preview · Article · Jul 2015 · IEEE Journal on Selected Areas in Communications
  • Wenhan Dai · Yuan Shen · Moe Z. Win
    [Show abstract] [Hide abstract] ABSTRACT: Network navigation is an emerging paradigm that enables high-accuracy location awareness in GPS-challenged environments via spatiotemporal cooperation. Two important operations of network navigation, location inference and power control, interrelate with each other, thus motivating the joint design of inference and control algorithms. In this paper, we develop efficient algorithms for network navigation with power control. In particular, we first determine the confidence region for location inference based on Fisher information analysis, and then design robust power control that minimizes the location inference errors of the agents within the confidence region. Both centralized and distributed algorithms are developed for energy-efficient network navigation. Simulation results show that the proposed algorithms significantly reduce the location inference errors compared to those without power control.
    No preview · Article · Jun 2015
  • W. Dai · Y. Shen · M.Z. Win
    [Show abstract] [Hide abstract] ABSTRACT: Wireless network localization (WNL) is an emerging paradigm for providing high-accuracy positional information in GPS-challenged environments. The localization performance of a node in WNL is determined by the allocation of transmit resources among its neighboring nodes. To achieve the best localization performance, we develop a computational geometry framework for optimal resource allocation in WNL. We first determine an affine map that transforms each resource allocation strategy into a point in 3-D Euclidian space. By exploiting geometric properties of these image points, we prove the sparsity property of the optimal resource allocation vector, i.e., the optimal localization performance can be achieved by allocating resources to only a small subset of neighboring nodes. Moreover, these geometric properties enable the reduction of the search space for optimal solutions, based on which we design efficient resource allocation strategies. Numerical results show that the proposed strategies can achieve significant improvements in both localization performance and computation efficiency. Our approach provides a new methodology for resource allocation in network localization, yielding exact optimal solutions rather than -approximate solutions.
    No preview · Article · Jun 2015
  • Source
    Alberto Rabbachin · Andrea Conti · Moe Z. Win
    [Show abstract] [Hide abstract] ABSTRACT: Wireless secrecy is essential for communication confidentiality, health privacy, public safety, information superiority, and economic advantage in the modern information society. Contemporary security systems are based on cryptographic primitives and can be complemented by techniques that exploit the intrinsic properties of a wireless environment. This paper develops a foundation for design and analysis of wireless networks with secrecy provided by intrinsic properties such as node spatial distribution, wireless propagation medium, and aggregate network interference. We further propose strategies that mitigate eavesdropping capabilities, and we quantify their benefits in terms of network secrecy metrics. This research provides insights into the essence of wireless network intrinsic secrecy and offers a new perspective on the role of network interference in communication confidentiality.
    Full-text · Article · Jun 2015
  • Wenhan Dai · Yuan Shen · Moe Z. Win
    [Show abstract] [Hide abstract] 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.
    No preview · Article · Jun 2015 · IEEE Journal on Selected Areas in Communications

Publication Stats

22k Citations
431.47 Total Impact Points

Institutions

  • 2003-2014
    • Massachusetts Institute of Technology
      • Laboratory for Information and Decision Systems
      Cambridge, Massachusetts, United States
  • 2001-2013
    • 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
  • 2009-2011
    • The Chinese University of Hong Kong
      • Department of Information Engineering
      Hong Kong, Hong Kong
  • 2008-2011
    • Kyung Hee University
      • Electronics and Radio Engineering Division
      Sŏul, Seoul, South Korea
    • University of Ferrara
      • Department of Engineering
      Ferrare, Emilia-Romagna, Italy
  • 2007
    • Aristotle University of Thessaloniki
      Saloníki, Central Macedonia, Greece
    • University of Oulu
      • Centre for Wireless Communications (CWC)
      Uleoborg, Oulu, Finland
  • 2006
    • University of Florence
      Florens, Tuscany, Italy
  • 2004-2006
    • Mitsubishi Electric Research Laboratories
      Cambridge, Massachusetts, United States
    • University of Texas at Dallas
      • Department of Electrical Engineering
      Richardson, Texas, 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
  • 2002-2003
    • University of Alberta
      • Department of Electrical and Computer Engineering
      Edmonton, Alberta, Canada
    • The American University of Rome
      Roma, Latium, Italy
    • Indian Institute of Technology Ropar
      • Department of Electrical Engineering
      Rūpar, Punjab, India
  • 1997-2003
    • University of Southern California
      • Department of Electrical Engineering
      Los Angeles, California, United States
    • University of California, Los Angeles
      • Department of Electrical Engineering
      Los Angeles, California, United States
  • 1990-1995
    • California Institute of Technology
      • Jet Propulsion Laboratory
      Pasadena, California, United States