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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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On the Exactness of Convex Relaxation for Optimal Power Flow in Tree Networks

On the Exactness of Convex Relaxation for Optimal Power Flow...

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51st IEEE Annual Conference on Decision and Control (CDC)

作者： Gan, Lingwen Li, Na Topcu, Ufuk Low, Steven CALTECH Div Engn & Appl Sci Pasadena CA 91125 USA

ISBN: (纸本)9781467320665

The optimal power flow problem is nonconvex, and a convex relaxation has been proposed to solve it. We prove that the relaxation is exact, if there are no upper bounds on the voltage, and any one of some conditions holds. One of these conditions requires that there is no reverse real power flow, and that the resistance to reactance ratio is non-decreasing as transmission lines spread out from the substation to the branch buses. This condition is likely to hold if there are no distributed generators. Besides, avoiding reverse real power flow can be used as rule of thumb for placing distributed generators.

关键词： concave programming convex programming distributed power generation power transmission lines trees (mathematics)

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Pareto-optimal radar waveform design

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IET RADAR SONAR AND NAVIGATION 2011年第4期5卷 473-482页

作者： De Maio, A. Piezzo, M. Farina, A. Wicks, M. Univ Naples Federico II Dipartimento Ingn Biomed Elettron & Telecomunicaz I-80125 Naples Italy SELEX Sistemi Integrati I-00131 Rome Italy US AFRL Sensors Directorate Rome NY 13441 USA

This study deals with the problem of Pareto-optimal waveform design in the presence of coloured Gaussian noise, under a similarity and an energy constraint. At the design stage, the authors, determine the optimal radar code according the following criterion: constrained maximisation of the detection performance and constrained minimisation of the Cramer-Rao lower bound (CRLB) on the Doppler estimation accuracy. This is tantamount to jointly maximising two quadratic forms under two quadratic constraints, so that the problem can be formulated in terms of a non-convex multi-objective optimisation problem. In order to solve it, the authors resort to the scalarisation technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, the authors assess the performance of the proposed waveform design scheme in terms of detection performance, region of achievable Doppler estimation accuracy and ambiguity function. In particular, the authors analyse the role of the Pareto weight in the optimisation process.

关键词： radar signal processing Pareto-optimal radar waveform design quadratic constraint Cramer-Rao lower bound scalarisation technique concave programming ambiguity function Gaussian noise Other topics in statistics nonconvex multi-objective optimisation problem Optimisation techniques Radar equipment, systems and applications Doppler estimation accuracy Signal processing and detection CRLB coloured Gaussian noise

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The fundamental theorem of linear programming: extensions and applications

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OPTIMIZATION 2011年第1-2期60卷 283-301页

作者： Tardella, F. Fac Econ I-00161 Rome Italy

The fundamental theorem of linear programming (LP) states that every feasible linear program that is bounded below has an optimal solution in a zero-dimensional face (a vertex) of the feasible polyhedron. We extend this result in two directions. We find a larger class of objective functions for which vertex optimality holds, and we give conditions guaranteeing the existence of an optimal solution in a larger family of faces of the feasible polyhedron. Our results also extend, with a very simple proof, the Frank-Wolfe theorem on the existence of an optimal solution to a Quadratic Program that is bounded below. We then apply our results to build up a general framework for obtaining upper and lower bounds and constant factor approximation algorithms for optimization problems. Furthermore, we show that several known results providing continuous formulations for discrete optimization problems can be easily derived and generalized with our extension of the fundamental theorem of Linear programming. Finally, by exploiting the equivalence between continuous and discrete formulations of the problem of minimizing a function on a polyhedron, we prove polynomial-time solvability and present efficient algorithms for several new classes of continuous optimization problems.

关键词： fundamental theorem of linear programming concave programming quadratic programming approximation algorithms maximum clique pseudo-Boolean optimization

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Optimal Charging of Plug-in Hybrid Electric Vehicles in Smart Grids

Optimal Charging of Plug-in Hybrid Electric Vehicles in Smar...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Sojoudi, Somayeh Low, Steven H. CALTECH Dept Control & Dynam Syst Pasadena CA 91125 USA Comp Sci & Electr Engn Dept Pasadena CA 91125 USA

ISBN: (纸本)9781457710018

Plug-in hybrid electric vehicles (PHEVs) play an important role in making a greener future. Given a group of PHEVs distributed across a power network equipped with the smart grid technology (e. g. wireless communication devices), the objective of this paper is to study how to schedule the charging of the PHEV batteries. To this end, we assume that each battery must be fully charged by a pre-specified time, and that the charging rate can be time-varying at discrete-time instants. The scheduling problem for the PHEV charging can be augmented into the optimal power flow (OPF) problem to obtain a joint OPF-charging (dynamic) optimization. A solution to this highly nonconvex problem optimizes the network performance by minimizing the generation and charging costs while satisfying the network, physical and inelastic-load constraints. A global optimum to the joint OPF-charging optimization can be found efficiently in polynomial time by solving its convex dual problem whenever the duality gap is zero for the joint OPF-charging problem. It is shown in a recent work that the duality gap is expected to be zero for the classical OPF problem. We build on this result and prove that the duality gap is zero for the joint OPF-charging optimization if it is zero for the classical OPF problem. The results of this work are applied to the IEEE 14 bus system.

关键词： Batteries IEEE 14 bus system Joints Optimization Polynomials Pricing Smart grids battery chargers charging costs charging rate charging schedule concave programming duality gap hybrid electric vehicles inelastic-load constraints joint OPF-charging optimization load flow nonconvex problem optimal charging optimal power flow plug-in hybrid electric vehicles scheduling smart grids smart power grids

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Radar Phase-Coded Waveform Design for Extended Target Recognition Under Detection Constraints

Radar Phase-Coded Waveform Design for Extended Target Recogn...

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IEEE Radar Conference (RADAR)

作者： Wei, Yimin Meng, Huadong Liu, Yimin Wang, Xiqin Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781424489022

We address the problem of radar phase-coded waveform design for extended target recognition in the presence of colored Gaussian disturbance. Phase-coded waveforms are selected since they can fully exploit the transmit power with sufficient variability. An important constraint, target detection performance, is considered to meet the practical requirements. The waveform is designed to achieve maximum recognition performance under a control on the achievable signal-to-noise ratio (SNR) of every possible target hypothesis. We formulate the code design in terms of a nonconvex, NP-hard quadratic optimization problem. Technique based on semidefinite relaxation (SDR) and randomization is proposed to approximate the optimal solution. Simulation results show that the recognition performance and the detection requirements are well balanced and accurate approximation is achieved.

关键词： Algorithm design and analysis Approximation methods Convolution NP-hard quadratic optimization problem Optimization Receivers SDR SNR Signal to noise ratio Target recognition colored Gaussian disturbance computational complexity concave programming extend

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Linear Precoding Designs for Amplify-and-Forward Multiuser Two-Way Relay Systems

Linear Precoding Designs for Amplify-and-Forward Multiuser T...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Wang, Rui Tao, Meixia Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781424492688

We investigate the linear precoding designs for multiuser two-way relay system (MU-TWRS) where a multi-antenna base-station (BS) communicates with multiple single-antenna mobile stations (MSs) via a multi-antenna relay station (RS). The amplify-and-forward (AF) relay protocol is employed. The design goal is to optimize the precodings at BS, RS or both so as to minimize the total mean-square error (MSE) of the uplink messages while maintaining the individual signal-to-interference-plus-noise ratio (SINR) requirement for each downlink signal. We show that the BS precoding design problem can be converted to a standard second order cone programming (SOCP), while the RS precoding is non-convex for which a local optimal solution is obtained using an iterative algorithm. A joint BS-RS precoding is also obtained by alternating optimization of BS precoding and RS precoding with guaranteed convergence. Numerical results show that RS-precoding is superior to BS-precoding. Furthermore, the joint BS-RS precoding can significantly outperform the two individual precoding schemes. The implementation issues including complexity and feedback overhead are also discussed.

关键词： BS-precoding Downlink Interference Joints Optimization RS-precoding Relays Signal to noise ratio Vectors amplify and forward communication amplify and forward protocol concave programming cone programming interference suppression iterative algorithm iterative methods linear codes linear precoding design mean square error method mean square error methods mobile stations multi-antenna base station multi-antenna relay station multifrequency antennas multiuser channels multiuser two-way relay system nonconvex programming optimization precoding protocols signal to interference plus noise ratio uplink messages

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Optimal Transmission over a Fading Channel with Imperfect Channel State Information

Optimal Transmission over a Fading Channel with Imperfect Ch...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Hu, Yichuan Ribeiro, Alejandro Univ Penn Dept Elect & Syst Engn Philadelphia PA 19104 USA

ISBN: (纸本)9781424492688

This paper considers a wireless channel when the probability distribution of fading is unknown and the transmitter has access to imperfect channel state information (CSI). Transmitted power and coding mode are adapted to the available imperfect CSI through the use of a backoff function in order to maximize the expected transmission rate subject to an average power constraint. Determination of the optimal power allocation and backoff function is a non-convex stochastic optimization problem with infinitely many variables. Despite its non-convexity, the duality gap of this problem has been shown to be null. Exploiting this property, we show that the optimal power allocation and channel backoff functions are uniquely determined by the optimal dual variable. This affords considerable simplification because the dual optimization problem is convex and one-dimensional - whereas the original primal problem is non-convex and infinite-dimensional. Iterative algorithms that find the optimal power and backoff function based on imperfect CSI without having access to the channel probability distribution are further developed. Numerical results are provided to corroborate theoretical findings.

关键词： Ad hoc networks CSI Channel estimation Fading Optimization Resource management Transmitters Wireless communication average power constraint channel coding channel probability distribution coding mode concave programming dual optimization problem fading channel fading channels imperfect channel state information iterative algorithms iterative methods nonconvex stochastic optimization problem optimal power allocation optimal transmission stochastic programming wireless channel

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Closed-form Linear Transceiver Designs for MIMO AF Relaying Systems with Direct Link

Closed-form Linear Transceiver Designs for MIMO AF Relaying ...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Song, Changick Lee, Kyoung-Jae Lee, Inkyu Korea Univ Sch Elect Eng Seoul South Korea

ISBN: (纸本)9781424492688

In this paper, we investigate the minimum mean squared error based relay transceiver design in amplify-and-forward multiple antenna relay systems in the presence of direct link. Instead of the conventional optimal design which requires iterative methods, we propose a simple and near optimal closed-form solution. The proposed method exploits the decomposable property of the error covariance matrix to simplify the problem. Then, we impose a structural constraint on the non-convex problem to attain a simple closed-form solution. Through numerical simulations, we confirm that the proposed solution has almost no performance loss compared to the optimal iterative design with much reduced complexity.

关键词： Bit error rate Closed-form solutions Covariance matrix MIMO MIMO AF relaying systems MIMO communication Peer to peer computing Relays Transceivers amplify and forward communication amplify-and-forward multiple antenna relay systems antenna arrays closed-form linear transceiver designs concave programming covariance matrices error covariance matrix decomposition iterative methods iterative methods least mean squares methods matrix decomposition minimum mean squared error near optimal closed-form solution nonconvex problem numerical simulations radio links radio transceivers relay transceiver design structural constraint

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Linear Successive User Allocation in the Multi-Cell MIMO Environment

Linear Successive User Allocation in the Multi-Cell MIMO Env...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Dotzler, Andreas Utschick, Wolfgang Dietl, Guido Tech Univ Munich Associate Inst Signal Proc D-80290 Munich Germany DOCOMO Commun Labs Europe GmbH D-80687 Munich Germany

ISBN: (纸本)9781612842547

An interference management method for coordinating downlink transmission in a Multiple-Input MultipleOutput (MIMO) cellular network is proposed. The problem is to efficiently manage inter-cell interference in a multi-cell environment, by so-called transmitter cooperation, in order to reduce the diminishing effects of interference on the networks performance. To allow for application in deployable networks, an utmost concern of the presented algorithm is to provide a low-complexity solution avoiding costly combinatorial or non-convex optimization problems. The problem is solved by a network wide successive allocation of data streams and choosing linear transmit and receive filters for each data stream, such that interference is completely avoided. By embedding our new algorithm in a more general framework for interference coordination, we can show relevant gains for network performance where especially the cell-edge users profit.

关键词： Complexity theory Interference MIMO MIMO communication Receiving antennas Resource management Signal processing algorithms Transmitters cell-edge users profit cellular radio combinatorial mathematics combinatorial optimization problem concave programming deployable network downlink transmission inter-cell interference management interference (signal) interference coordination interference management method linear successive user allocation linear transmit multicell MIMO environment multiple-input multiple-output cellular network nonconvex optimization problem radio links radio transmitters receive filter telecommunication network management transmitter cooperation

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