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检索条件"主题词=Concave Programming"

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Structured model identification algorithm based on constrained optimisation

Structured model identification algorithm based on constrain...

引用

European Control Conference (ECC)

作者： Vayssettes, J. Mercere, G. Bury, Y. Pommier-Budinger, V. ISAE 10 Av Edouard Belin F-31400 Toulouse France Univ Poitiers Lab Informat & Automat Syst F-86073 Poitiers France

ISBN: (纸本)9783952426937

This article presents an identification algorithm dedicated to the estimation of the coefficients of physically-structured models. This algorithm is based on a constrained gradient-based optimisation that minimises a non-convex cost function to identify a structured model, starting from an initial black-box model. The suggested method is able to handle linear relations between the model coefficients so as to identify a model with the desired physical structure. Since the minimised function is non-convex, the initial model must be in the neighbourhood of its global minimum. The initialisation issue is discussed and a total-least-squares-based solution is suggested. These new developments are evaluated on a simulation benchmark, illustrating the identification of a mechanical system.

关键词： concave programming gradient methods least squares approximations linear systems black-box model constrained gradient-based optimisation constrained optimisation linear relation mechanical system minimised function model coefficient nonconvex cost function physical structure physically-structured model structured model identification algorithm total-least-squares-based solution Cost function Estimation Frequency-domain analysis Optimization methods Reliability

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Joint Spectrum Sensing and Resource Allocation for Multi-band Cognitive Radio Systems with Heterogeneous Services

Joint Spectrum Sensing and Resource Allocation for Multi-ban...

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IEEE Global Communications Conference (GLOBECOM)

作者： Shi, Cong Wang, Ying Zhang, Ping Minist Educ Key Lab Universal Wireless Commun Beijing Peoples R China

ISBN: (纸本)9781467309219;9781467309202

In this paper, we study joint spectrum sensing and resource allocation for heterogeneous services in multi-band cognitive radio systems. Two types of services are considered: delay-sensitive (DS) services and delay-tolerant (DT) services. Considering the influence of the probabilities of miss detection and false alarm, the detection threshold, power and sub-channel allocation are jointly optimized to maximize the total data rate of DT services while satisfying the delay requirement of DS services. For the protection of primary transmission, a new criterion referred to as rate loss constraint is introduced. With the queue theory, the delay requirements of DS services are transformed into constant rate requirements. The optimization problem is formulated as a three-variable non-convex problem under constraints. Moreover, by dividing the optimization problem into two stages, an iterative dual decomposition method is proposed to solve it. The effectiveness of our proposed algorithm is evaluated by extensive simulations and compared with existing algorithms.

关键词： cognitive radio concave programming iterative methods probability queueing theory radio spectrum management signal detection

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Optimal Location and Sizing of Distributed Storage Systems in Active Distribution Networks

Optimal Location and Sizing of Distributed Storage Systems i...

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IEEE Grenoble PowerTech (POWERTECH) Conference

作者： Nick, M. Hohmann, M. Cherkaoui, R. Paolone, M. Ecole Polytech Fed Lausanne DESL Lausanne Switzerland

ISBN: (纸本)9781467356688

Energy balance and ancillary services provided by distributed storage systems to active distribution networks represent two aspects of a single problem that needs to be properly treated in view of the typical distribution networks parameters. In this context, the paper focuses on the problem of the optimal siting and sizing of distributed storage systems. In particular, the paper proposes the formulation of a problem that accounts: (i) the voltage support of storage systems to the grid, (ii) the network losses and (iii) the cost of the energy-flow towards the external grid. As the formulated problem is mixed-integer, non-convex and non-linear, its solution requires the adoption of heuristic techniques. In this respect, a two-stage iterative procedure is proposed. The first stage of the procedure utilizes a genetic algorithm to provide locations and sizes of the distributed storage systems;the second stage evaluates the fitness of the solution provided by the first part by solving a daily AC optimal power flow. An application example, referring to the IEEE 13 busses test feeder, is included in order to demonstrate and discuss the efficiency of the proposed method.

关键词： IEEE standards concave programming distributed power generation distribution networks genetic algorithms integer programming iterative methods nonlinear programming

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SAR Canonical Feature Extraction using Molecule Dictionaries

SAR Canonical Feature Extraction using Molecule Dictionaries

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IEEE Radar Conference (RADAR)

作者： Hammond, G. Barry Jackson, Julie Ann Air Force Inst Technol Dept Elect & Comp Engn Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9781467357944;9781467357920

We apply a molecule dictionary approach to synthetic aperture radar canonical feature extraction. These canonical features capture physically-relevant scattering geometry as a function of shape type, frequency, aspect, and polarization. The extraction problem is a nonlinear nonconvex optimization that includes model order selection, feature classification, and parameter estimation. Previous work used image-based initializations, gradient descent, and a hierarchical classification scheme to extract the features. The dictionary approach shifts much of the computational burden to dictionary formation which can be done offline, prior to feature extraction. We show results for cases when the true feature lies in the dictionary and when it does not. Discussion of the practical challenges of dictionary construction is given in the context of recent sparse recovery literature.

关键词： concave programming electromagnetic wave polarisation electromagnetic wave scattering feature extraction geometry image classification nonlinear programming parameter estimation radar imaging synthetic aperture radar

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OPTIMAL RESOURCE ALLOCATION IN OFDMA DOWNLINK SYSTEMS WITH IMPERFECT CSI

OPTIMAL RESOURCE ALLOCATION IN OFDMA DOWNLINK SYSTEMS WITH I...

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12th IEEE International Workshop on Signal Processing Advances in Wireless Communications

作者： Aggarwal, Rohit Assaad, Mohamad Koksal, C. Emre Schniter, Philip Ohio State Univ Dept ECE Columbus OH 43210 USA Supelac Dept Telecom Gif Sur Yvette France

ISBN: (纸本)9781424493326

In this paper, we address the problem of joint scheduling and resource allocation in the downlink of an orthogonal frequency division multiple access (OFDMA)-based wireless network when the per-user SNR is known only in distribution. In particular, we consider sum-utility maximization over user schedules, powers, and code rates, subject to an instantaneous sum-power constraint. We consider both a "continuous" scenario where, during a time-slot, each OFDMA subchannel can be time-shared among multiple users and/or code rates, and a "discrete" scenario where no time-sharing is allowed. For the non-convex optimization problem arising in the continuous case, we propose an efficient exact solution. For the mixed-integer optimization problem arising in the discrete case, we propose a polynomial-complexity approximate solution and derive a bound on its optimality gap. We also provide a numerical study of goodput maximization for the SNR distribution that results from the use of pilot-aided MMSE channel estimation.

关键词： Channel estimation Downlink MMSE channel estimation OFDM OFDM modulation OFDMA downlink system OFDMA-based wireless network Optimization Resource management SNR distribution Signal to noise ratio Tin channel estimation concave programming frequency division multiple access integer programming least mean squares methods mixed integer optimization nonconvex optimization optimal resource allocation optimality gap orthogonal frequency division multiple access polynomial-complexity approximation radio networks resource allocation sum-utility maximization

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Optimum Transmission through the Gaussian Multiple Access Channel

Optimum Transmission through the Gaussian Multiple Access Ch...

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IEEE International Symposium on Information Theory (ISIT)

作者： Calabuig, Daniel Gohary, Ramy Yanikomeroglu, Halim Univ Politecn Valencia Inst Telecommun & Multimedia Applicat E-46022 Valencia Spain Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9781479904464

In this paper we study the optimality of particular points in the capacity region of Gaussian multiple access channels (GMACs) with various power constraints. The points of interest maximize general rate objectives that arise in practical communication scenarios. Achieving these points constitutes the task of jointly optimizing time-sharing parameters, input covariance matrices and the order of decoding used by the successive interference cancellation receiver. To approach this problem Caratheodory's theorem is invoked to represent time-sharing and decoding orders jointly as a finite-dimensional matrix variable. This variable enables us to use variational inequalities to extend results pertaining to problems with linear objectives to more general, potentially nonconvex, problems. In particular, it is shown that for arbitrary objectives, if the power constraints are convex, it suffices for each user to use only one covariance matrix in all its allocated time slots. On the other hand, for arbitrary power constraints, if the objective is linear no time-sharing is necessary. These results significantly reduce the design complexity and render optimal signalling over GMAC more amenable to implementation in various practical scenarios.

关键词： Gaussian channels channel capacity concave programming covariance matrices decoding interference suppression multi-access systems radio receivers

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Power Efficient Resource Allocation in Uplink SC-FDMA Systems

Power Efficient Resource Allocation in Uplink SC-FDMA System...

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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Ahmad, Ayaz Assaad, Mohamad SUPELEC Dept Telecommun F-91192 Gif Sur Yvette France

ISBN: (纸本)9781457713484

In this paper, we study sum-power minimization problem in SC-FDMA which is adopted as the multiple access scheme for uplink in the 3GPP-LTE standard. Unlike OFDMA, in addition to the restriction of allocating a sub-channel to one user at most, the multiple sub-channels allocated to a user in SC-FDMA should be consecutive as well. This renders the resource allocation problem prohibitively difficult and the standard optimization tools (e.g., Lagrange dual approach widely used for OFDMA, etc.) can not help towards its optimal solution. We propose a novel polynomial-complexity optimization framework that is inspired from the recently developed canonical duality theory. We first formulate the resource allocation problem as a binary-integer programming (BIP) problem and then transform the BIP problem into a continuous space canonical dual problem which is a concave maximization problem under certain conditions. Based on the solution of the canonical dual problem, we derive a joint power and sub-channels allocation algorithm that has polynomial complexity. We provide conditions under which the proposed algorithm is optimal. The proposed framework is illustrated through simulations where the results show that the proposed algorithm improves the system performance significantly.

关键词： 3G mobile communication 3GPP-LTE standard BIP problem Complexity theory Fading Frequency division multiaccess Long Term Evolution OFDMA Optimization Resource management Signal to noise ratio Transforms binary-integer programming problem concave maximization problem concave programming continuous space canonical dual problem frequency division multiple access integer programming minimisation multiple access scheme optimization tools polynomial-complexity optimization framework power efficient resource allocation subchannel allocation algorithm sum-power minimization problem uplink SC-FDMA systems wireless channels

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Multi-Pair Cognitive Two-Way Relaying and Power Allocation under Imperfect CSI

Multi-Pair Cognitive Two-Way Relaying and Power Allocation u...

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77th IEEE Vehicular Technology Conference (VTC)

作者： Ubaidulla, P. Alouini, Mohamed-Slim Aissa, Sonia King Abdullah Univ Sci & Technol Comp Elect & Math Sci & Engn Div Thuwal Makkah Province Saudi Arabia Univ Quebec Inst Nat Rech Sci Montreal PQ Canada

ISBN: (纸本)9781467363372

In this paper, we present a robust joint relay precoder design and transceiver power allocation for a cognitive radio network under imperfect channel state information. The secondary (or cognitive) network consists of multiple pairs of single-antenna transceiver nodes and a non-regenerative two-way relay with multiple antennas which aids the intra-pair communication process of the transceiver nodes. The secondary nodes share the spectrum with a licensed primary user (PU) while guaranteeing that the interference to the PU receiver is maintained below a specified threshold. The proposed robust design is based on the minimization of the sum mean-square error (MSE) of the transceiver nodes under constraints on the secondary users' transmit powers and interference to PU the receiver. Though the original problem is non-convex, we show that the proposed design can be solved using alternating optimization of convex subproblems which have analytic or efficient numerical solutions. We illustrate the performance of the proposed designs through some selected numerical simulations.

关键词： antenna arrays cognitive radio concave programming convex programming mean square error methods radio spectrum management radio transceivers radiofrequency interference relay networks (telecommunication)

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Distributed Optimal Power and Rate Control In Single-Hop Wireless Interference Networks

Distributed Optimal Power and Rate Control In Single-Hop Wir...

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46th Asilomar Conference on Signals, Systems and Computers

作者： Cui, Ying Hanly, Stephen V. Macquarie Univ Dept Elect Engn Sydney NSW 2109 Australia

ISBN: (纸本)9781467350518

We study distributed optimal control in general single-hop wireless interference networks. We take into account the decoding errors due to ehannel outage by introducing "effective utility" associated with the average eorrectly received data rate, and formulate the effective network utility maximization (ENUM) w.r.t. power and rate control. The ENUM is a non-convex stochastic NUM. By introducing "average SINR", we approximate the ENUM by a eonvex problem. The approximation error is asymptotieally negligible. Borrowing the load-spillage characterization of the average SINR, we obtain a distributed stochastic algorithm to solve the approximated problem. Using stoehastic approximation, we show that the proposed algorithm eonverges almost surely.

关键词： approximation theory concave programming convex programming decoding distributed control network coding optimal control power control radio networks radiofrequency interference stochastic processes stochastic programming telecommunication control wireless channels

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Further results on cooperative localization via semidefinite programming

Further results on cooperative localization via semidefinite...

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Annual Conference on Information Sciences and Systems

作者： Wang, Ning Yang, Liuqing Department of Electrical and Computer Engineering University of Florida Gainesville FL 32611 United States Department of Electrical and Computer Engineering Colorado State University Fort Collins CO 80523 United States

ISBN: (纸本)9781424498475

As a powerful tool to convert nonconvex problems into convex ones, semidefinite programing (SDP) has been introduced to both cooperative and non-cooperative localization systems. In this paper, we derive the Cramér-Rao Lower Bound (CRLB) for several scenarios to show the advantage of cooperative localization. We then consider cooperative localization via SDP using various semidefinite relaxations, including existing Standard SDP (SSDP), Edge-based SDP (ESDP), Node-based SDP (NSDP) and our proposed Component-wise SDP (CSDP). We analyze their performances and complexity and find that CSDP has advantages in both aspects. Simulations will also be carried out to corroborate our analyses. © 2011 IEEE.

关键词： Cooperative Localization CrameÌr-Rao lower bound Gold Manganese Semidefinite programming (SDP) component-wise SDP concave programming convex programming convex programming cooperative communication cooperative localization edge-based SDP node-based SDP nonconvex programming problems noncooperative localization systems semidefinite programming

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