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Consistent distributed state estimation with global observability over sensor network

AUTOMATICA 2018年 92卷 162-172页

作者： He, Xingkang Xue, Wenchao Fang, Haitao Chinese Acad Sci Acad Math & Syst Sci NCMIS LSC Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China

This paper studies the distributed state estimation problem for a class of discrete time-varying systems over sensor networks. Firstly, it is shown that the gain parameter optimization in a networked Kalman filter requires a centralized framework. Then, a sub-optimal distributed Kalman filter (DKF) is proposed by employing the covariance intersection (CI) fusion strategy. It is proven that the proposed DKF is of consistency, that is, an upper bound of error covariance matrix can be provided by the filter in real time. The consistency also enables the design of adaptive CI weights for better filter precision. Furthermore, the boundedness of covariance matrix and the convergence of the proposed filter are proven based on the strong connectivity of directed network topology and the global observability which permits the subsystem with local sensor's measurements to be unobservable. Meanwhile, to keep the covariance of the estimation error bounded, the proposed DKF does not require the system matrix to be nonsingular at each moment, which seems to be a necessary condition in the main DKF designs under global observability. Finally, simulation results of two examples show the effectiveness of the algorithm in the considered scenarios. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Wireless sensor networks Time-varying systems State estimation Covariance intersection Distributed Kalman filter Global observability semi-definite programming

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Yield design-based numerical analysis of three-dimensional reinforced concrete structures

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INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS 2018年第18期42卷 2177-2192页

作者： Vincent, Hugues Arquier, Mathieu Bleyer, Jeremy de Buhan, Patrick Strains Paris France UPE Ecole Ponts ParisTech Lab Navier CNRSUMR 8205IFSTTAR Champs Sur Marne France

The objective of this contribution is to present some new recent developments regarding the evaluation of the ultimate bearing capacity of massive three-dimensional reinforced concrete structures which cannot be modeled as 1D (beams) or 2D (plates) structural members. The approach is based upon the implementation of the lower bound static approach of yield design through a discretization of the three-dimensional structure into tetrahedral finite elements, on the one hand, the formulation of the corresponding optimization problem in the context of semi-definite programming techniques, on the other hand. Another key feature of the method lies in the treatment of the concrete-embedded reinforcing bars not as individual elements, but by resorting to an extension of the yield design homogenization approach. The whole procedure is first validated on the rather simple illustrative problem of a uniformly loaded simply supported beam, then applied to the design of a bridge pier cap taken as an example of more complex and realistic structure.

关键词： finite element method homogenization reinforced concrete structures semi-definite programming yield design

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Resilient hybrid optical-RF backhauling for tiered networks

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PHYSICAL COMMUNICATION 2019年 36卷 100814-000页

作者： Al-mekhlafi, Mohammed H. Ibrahim, Ahmed S. Fahmy, Yasmine A. Khairy, Mohamed M. Cairo Univ Elect & Elect Commun Dept Giza Egypt Florida Int Univ Dept Elect & Comp Engn Miami FL 33199 USA

To meet the huge demand in 5G data services, it is expected to have an enormous number of small cells along the conventional base stations. Various backhaul links including Optical Fiber (OF), Free Space Optics (FSO) and Radio Frequency (RF) are used to support the backhaul demand of such tiered network. The objective of this paper is to improve the connectivity of tiered networks by obtaining the optimal combinations of backhauling technologies (OF, FSO, RF or hybrid FSO/RF). In this paper, optimization of two-tier networks connectivity and resilience is performed, under the constraints of minimum data rate, cost, and reliability of different links. Under realistic cost assumptions and linear relaxation, it was shown that the problem can be formulated as a convex optimization problem. In this paper, an iterative solution is proposed. The proposed solution iterates between two computationally efficient methods to successively maximize the algebraic connectivity and resilience. The simulation results show that the proposed algorithm can achieve gains of 240% - 600% in terms of the network algebraic connectivity, depending on the rate constraint range. Similarly, it can achieve gains of 60% - 100% enhancement in terms of the network resilience. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Algebraic connectivity Integer linear programming Min-cut semi-definite programming

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Consensus control for linear systems with optimal energy cost

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AUTOMATICA 2018年 93卷 83-91页

作者： Zhang, Han Hu, Xiaoming KTH Royal Inst Technol Dept Math SE-10044 Stockholm Sweden

In this paper, we design an optimal energy cost controller for linear systems asymptotic consensus given the topology of the graph. The controller depends only on relative information of the agents. Since finding the control gain for such controller is hard, we focus on finding an optimal controller among a classical family of controllers which is based on Algebraic Riccati Equation (ARE) and guarantees asymptotic consensus. Through analysis, we find that the energy cost is bounded by an interval and hence we minimize the upper bound. In order to do that, there are two classes of variables that need to be optimized: the control gain and the edge weights of the graph and are hence designed from two perspectives. A suboptimal control gain is obtained by choosing Q = 0 in the ARE. Negative edge weights are allowed, and the problem is formulated as a semi-definite programming (SDP) problem. Having negative edge weights means that "competitions" between the agents are allowed. The motivation behind this setting is to have a better system performance. We provide a different proof compared to Thunberg and Hu (2016) from the angle of optimization and show that the lowest control energy cost is reached when the graph is complete and with equal edge weights. Furthermore, two sufficient conditions for the existence of negative optimal edge weights realization are given. In addition, we provide a distributed way of solving the SDP problem when the graph topology is regular. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Consensus control Multi-agent systems Optimal control semi-definite programming Distributed optimization

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A New and Flexible Approach to the Analysis of Paired Comparison Data

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JOURNAL OF MACHINE LEARNING RESEARCH 2018年第1期19卷 2458-2486页

作者： Oliveira, Ivo F. D. Ailon, Nir Davidov, Ori UFVJM Fed Univ Valleys Jequitinhonha & Mucuri Dept Sci Engn & Technol Teofilo Otoni MG Brazil Technion Israel Inst Technol Dept Comp Sci Haifa Israel Univ Haifa Dept Stat Haifa Israel

We consider the situation where I items are ranked by paired comparisons. It is usually assumed that the probability that item i is preferred over item j is p(ij) = F(mu(i) - mu(j)) where F is a symmetric distribution function, which we refer to as the comparison function, and mu(i) and mu(j) are the merits or scores of the compared items. This modelling framework, which is ubiquitous in the paired comparison literature, strongly depends on the assumption that the comparison function F is known. In practice, however, this assumption is often unrealistic and may result in poor fit and erroneous inferences. This limitation has motivated us to relax the assumption that F is fully known and simultaneously estimate the merits of the objects and the underlying comparison function. Our formulation yields a flexible semi-definite programming problem that we use as a refinement step for estimating the paired comparison probability matrix. We provide a detailed sensitivity analysis and, as a result, we establish the consistency of the resulting estimators and provide bounds on the estimation and approximation errors. Some statistical properties of the resulting estimators as well as model selection criteria are investigated. Finally, using a large data-set of computer chess matches, we estimate the comparison function and find that the model used by the International Chess Federation does not seem to apply to computer chess.

关键词： linear stochastic transitivity statistical ranking semi-definite programming model selection sensitivity analysis chess

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How to manage resources to provide physical layer security: Active versus passive adversary?

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PHYSICAL COMMUNICATION 2018年第Apr.期27卷 143-149页

作者： Abedi, Mohammad Reza Mokari, Nader Saeedi, Hamid Tarbiat Modares Univ Tehran Iran

This paper studies the required physical (e.g. relays and jammers) and radio resources (e.g. power) to provide physical layer security for relay and friendly jammer assisted multiple-input and single-output transmissions in the presence of multiple active and passive adversaries. The passive adversaries are half duplex and only able to overhear the transmissions from the legitimate transmitter to the legitimate receiver, while the active adversaries are full duplex and able to jam and eavesdrop simultaneously. Since the channel information between adversaries and other nodes are uncertain, robust optimization methods are considered. In this regard, the main aim is to maximize the worst case secrecy rate subject to the normalized transmit power constraints of legitimate transmitter, friendly jammer and relay, and channel state information uncertainty constraints. Through several examples, we then investigate the required increase in physical and radio resources to maintain secure communication when passive adversaries upgrades themselves to active adversaries. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Cooperative jamming Imperfect channel state information Physical layer security Active and passive adversary semi-definite programming

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Received signal strength-based target localization under spatially correlated shadowing via convex optimization relaxation

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第6期14卷

作者： Chang, Shengming Li, Youming Wang, Hui Wang, Gang Ningbo Univ Fac Elect Engn & Comp Sci Ningbo 315211 Zhejiang Peoples R China

Received signal strength-based target localization methods normally employ radio propagation path loss model, in which the log-normal shadowing noise is generally assumed to follow a zero-mean Gaussian distribution and is uncorrelated. In this article, however, we represent the simplified additive noise by the spatially correlated log-normal shadowing noise. We propose a new convex localization estimator in wireless sensor networks by using received signal strength measurements under spatially correlated shadowing environment. First, we derive a new non-convex estimator based on weighted least squares criterion. Second, by using the equivalence of norm, the derived estimator can be reformulated as its equivalent form which has no logarithm in the objective function. Then, the new estimator is relaxed by applying efficient convex relaxation that is based on second-order cone programming and semi-definite programming technique. Finally, the convex optimization problem can be efficiently solved by a standard interior-point method, thus to obtain the globally optimal solution. Simulation results show that the proposed estimator solves the localization problem efficiently and is close to Cramer-Rao lower bound compared with the state-of-the-art approach under correlated shadowing environment.

关键词： Target localization spatially correlated shadowing received signal strength convex optimization second-order cone programming semi-definite programming wireless sensor networks

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UAV positioning for out-of-band integrated access and backhaul millimeter wave network

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PHYSICAL COMMUNICATION 2019年 35卷 100721-000页

作者： Abdel-Malek, Mai A. Ibrahim, Ahmed S. Mokhtar, Mohamed Akkaya, Kemal Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA Interdigital Inc Philadelphia PA 19428 USA

Unmanned Aerial Vehicles (UAVs) can play a major role in enhancing both the access and backhaul networks of the next generation of mobile networks. In this paper, we propose a novel positioning scheme that finds the optimum 3-dimensional flying locations for the UAVs to enhance the connectivity of the backhaul network, while providing the desired quality of service (QoS) for the served users in the access network. The backhaul network connectivity is represented by the algebraic connectivity (or Fiedler value), while the user equipments (UEs) signal reception quality is represented by the signal-to-interference-and-noise-ratio (SINR). We consider an out-of-band integrated access and backhaul (IAB) network, in which we consider the interference that is generated from the deployed UAVs within the access network. The formulated UAV positioning problem is modeled as a low-complexity semi-definite programming (SDP) optimization problem, which can be solved numerically with low complexity. We also consider the access network to experience the propagation modeling of millimeter wave (mm-wave) frequency band. Finally, computer simulations are conducted to show the improvement of the proposed algorithm, in terms of the backhaul algebraic connectivity, while guaranteeing the desired SINR threshold for all the UEs in the access network. (C) 2019 Elsevier B.V. All rights reserved.

关键词： 3-D positioning Connectivity Fiedler value Integrated access and backhaul network Millimeter wave semi-definite programming Unmanned aerial vehicle

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Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2018年第8期17卷 5338-5352页

作者： Du, Rong Ozcelikkale, Ayca Fischione, Carlo Xiao, Ming KTH Royal Inst Technol Dept Network & Syst Engn S-10044 Stockholm Sweden Uppsala Univ Div Signals & Syst S-75121 Uppsala Sweden KTH Royal Inst Technol Dept Informat Sci & Engn S-10044 Stockholm Sweden

The lifetime of a wireless sensor network (WSN) determines how long the network can be used to monitor the area of interest. Hence, it is one of the most important performance metrics for WSN. The approaches used to prolong the lifetime can be briefly divided into two categories: reducing the energy consumption, such as designing an efficient routing, and providing extra energy, such as using wireless energy transfer (WET) to charge the nodes. Contrary to the previous line of work where only one of those two aspects is considered, we investigate these two together. In particular, we consider a scenario where dedicated wireless chargers transfer energy wirelessly to sensors. The overall goal is to maximize the minimum sampling rate of the nodes while keeping the energy consumption of each node smaller than the energy it receives. This is done by properly designing the routing of the sensors and the WET strategy of the chargers. Although such a joint routing and energy beamforming problem is non-convex, we show that it can be transformed into a semi-definite optimization problem (SDP). We then prove that the strong duality of the SDP problem holds, and hence, the optimal solution of the SDP problem is attained. Accordingly, the optimal solution for the original problem is achieved by a simple transformation. We also propose a lowcomplexity approach based on pre-determined beamforming directions. Moreover, based on the alternating direction method of multipliers, the distributed implementations of the proposed approaches are studied. The simulation results illustrate the significant performance improvement achieved by the proposed methods. In particular, the proposed energy beamforming scheme significantly outperforms the schemes where one does not use energy beamforming, or one does not use optimized routing. A thorough investigation of the effect of system parameters, including the number of antennas, the number of nodes, and the number of chargers, on the system per

关键词： RF energy transmission energy beamforming WPSN semi-definite programming

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Projected primal-dual gradient flow of augmented Lagrangian with application to distributed maximization of the algebraic connectivity of a network

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AUTOMATICA 2018年 98卷 34-41页

作者： Zhang, Han Wei, Jieqiang Yi, Peng Hu, Xiaoming KTH Royal Inst Technol Dept Math SE-10044 Stockholm Sweden KTH Royal Inst Technol Dept Automat Control SE-10044 Stockholm Sweden Washington Univ Dept Elect & Syst Engn St Louis MO USA

In this paper, a projected primal-dual gradient flow of augmented Lagrangian is presented to solve convex optimization problems that are not necessarily strictly convex. The optimization variables are restricted by a convex set with computable projection operation on its tangent cone as well as equality constraints. As a supplement of the analysis in Niederlander and Cortes (2016), we show that the projected dynamical system converges to one of the saddle points and hence finding an optimal solution. Moreover, the problem of distributedly maximizing the algebraic connectivity of an undirected network by optimizing the port gains of each nodes (base stations) is considered. The original semi-definite programming (SDP) problem is relaxed into a nonlinear programming (NP) problem that will be solved by the aforementioned projected dynamical system. Numerical examples show the convergence of the aforementioned algorithm to one of the optimal solutions. The effect of the relaxation is illustrated empirically with numerical examples. A methodology is presented so that the number of iterations needed to reach the equilibrium is suppressed. Complexity per iteration of the algorithm is illustrated with numerical examples. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Projected dynamical systems semi-definite programming Distributed optimization

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