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Distributed gradient descent method with edge-based event-driven communication for non-convex optimization

IET CONTROL THEORY AND APPLICATIONS 2021年第12期15卷 1588-1598页

作者： Adachi, T. Hayashi, N. Takai, S. Osaka Univ Grad Sch Engn 2-1 Yamada Oka Suita Osaka 5650871 Japan Osaka Univ Grad Sch Engn Sci Toyonaka Osaka Japan

This paper considers an event-driven distributed non-convex optimization algorithm for a multi-agent system, where each agent has a non-convex cost function. The goal of the multi-agent system is to minimize the global objective function, which is the sum of these local cost functions, in a distributed manner. To this end, each agent updates the own state by a consensus-based gradient descent algorithm. The local information exchange among neighbor agents is carried out with an event-triggered scheme to achieve consensus with less inter-agent communication. Convergence to a critical point of the objective function and the validity of the proposed algorithm in numerical examples are shown.

关键词： distributed gradient descent method global objective function Optimisation techniques event-triggered scheme local cost functions inter-agent communication nonconvex cost function gradient methods neighbor agents multi-agent systems edge-based event-driven communication consensus-based gradient descent algorithm concave programming multiagent system Interpolation and function approximation (numerical analysis) nonconvex optimization algorithm local information exchange critical point convergence

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Optimal design for the artificial-noise-aided IRS-MIMO-OFDM secure communications

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IET COMMUNICATIONS 2022年第13期16卷 1570-1581页

作者： Ren, Jingya Yuan, Yuanli Huang, Tiancong Jiang, Weiheng Feng, Wenjiang Chongqing Univ Sch Microelect & Commun Engn Chongqing Peoples R China Singapore Univ Technol & Design Informat Syst Technol & Design Pillar Singapore Singapore

This paper discusses an artificial noise-aided intelligent reflecting surface-MIMO-OFDM system physical layer secure communication, in which two cases for the intelligent reflecting surface reflection coefficient models are considered separately, that is unit modulus constraint for the reflection coefficients and the more practical situation of amplitude phase-shift dependence. Then the problem of joint optimisation for the precoding matrix, artificial noise covariance matrix and intelligent reflecting surface reflection coefficient matrix to maximise the sum secrecy rate under the power constraint at the transmitter is formulated, and then an alternate optimisation-based inexact block coordinate descent algorithm is proposed to tackle the formulated non-convexity problem. For the problem with unit modulus constraint for the intelligent reflecting surface reflection coefficients, closed-form solutions of the optimisation variables are obtained by utilising the Lagrange multiplier method and the complex circular manifold method. For the problem with intelligent reflecting surface reflection coefficient amplitude phase-shift dependence, alternate optimisation-based penalty method is used to obtain the intelligent reflecting surface optimal reflection matrix. Numerical results indicate that the algorithm for the intelligent reflecting surface reflection coefficient unit modulus constraint achieves the maximum secrecy rate, and the algorithm for the intelligent reflecting surface reflection coefficient of amplitude phase-shift dependence has the sub-optimal performance, and the benchmark schemes such as no intelligent reflecting surface and intelligent reflecting surface random phase shift strategies have the worst and similar performance.

关键词： matrix algebra intelligent reflecting surface optimal reflection matrix precoding matrix sum secrecy rate MIMO communication artificial noise-aided intelligent reflecting surface-MIMO-OFDM system physical layer secure communication intelligent reflecting surface reflection coefficient amplitude phase-shift dependence concave programming intelligent reflecting surface reflection coefficient unit modulus constraint intelligent reflecting surface reflection coefficient matrix precoding electromagnetic wave reflection power constraint nonconvexity problem intelligent reflecting surface reflection coefficient models intelligent reflecting surface random phase shift strategies telecommunication security covariance matrices complex circular manifold method Lagrange multiplier method alternate optimisation-based penalty method OFDM modulation artificial-noise-aided IRS-MIMO-OFDM artificial noise covariance matrix alternate optimisation-based inexact block coordinate descent algorithm

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Energy efficient joint energy cooperation and power allocation in multiuser distributed antenna systems with hybrid energy supply

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IET COMMUNICATIONS 2019年第2期13卷 153-161页

作者： Zhu, Pengcheng Mao, Huanhuan Li, Jiamin You, Xiaohu Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China

This study investigates the joint power allocation and energy cooperation problem in a multiuser downlink distributed antenna system with hybrid energy supply. The authors focus on the energy efficiency (EE) maximization problem for three different types of precoding, zero-forcing (ZF), general beamforming method and conjugate-beamforming. For ZF precoding, they apply fractional programming and reform the optimization problem to a convex one. An iterative algorithm to deal with the fractional objective function is presented. Whereas the problem is non-convex for general beamforming with user interference, they take maximum ratio transmission as an example and adopt a set of transformation and approximation based on the difference of convex (DC) programming. Furthermore, for conjugate-beamforming, they first transform the quadratic signal to interference plus noise power ratio into a trackable form and then DC programming is applied. A two-loop algorithm for the general beamforming and conjugate-beamforming is presented with fractional programming in the inner loop and DC programming in the outer loop. Simulations show that the proposed algorithm improved EE significantly and indicate that energy cooperation can contribute to a higher EE. It also reveals that ZF achieves better EE with small noise variance while conjugate beamforming in high noise circumstance.

关键词： telecommunication power management precoding concave programming convex programming radiofrequency interference energy conservation antenna arrays iterative methods array signal processing multi-access systems approximation theory noise variance while conjugate beamforming energy efficient joint energy cooperation hybrid energy supply multiuser downlink energy efficiency maximisation problem general beamforming method conjugate-beamforming ZF precoding user interference fractional programming optimisation problem fractional objective function convex programming interference plus noise power ratio DC programming multiuser distributed antenna systems smart grid joint power allocation and energy cooperation problem iterative algorithm nonconvex problem maximum ratio transmission quadratic signal to interference plus noise power ratio two-loop algorithm

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Equivalence of non-linear model structures based on Pareto uncertainty

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IET CONTROL THEORY AND APPLICATIONS 2015年第16期9卷 2423-2429页

作者： Barbosa, Alipio Monteiro Caldeira Takahashi, Ricardo Hiroshi Aguirre, Luis Antonio Univ Fed Minas Gerais Programa Posgrad Engn Eletr BR-31270901 Belo Horizonte MG Brazil Univ Fed Minas Gerais Dept Matemat BR-31270901 Belo Horizonte MG Brazil

In view of practical limitations, it is not always feasible to find the best model structure. In such situations, a more realistic problem to address seems to be the choice of a set of model structures that are not clearly distinguishable in view of the available data. This study proposes a procedure based on the bi-objective optimisation and hypothesis testing that, given a pool of candidate model structures, will select a subset that is consistent with the data given a user-defined confidence level. Such a subset carries an important information that no single most likely model structure can deliver: the unmodelled component of system behaviour, given the model structure uncertainty. The procedure is illustrated using simulated and measured data. For the sake of argument convex optimisation has been considered, although the procedure also applies to non-convex problems.

关键词： Pareto optimisation nonlinear systems statistical testing convex programming concave programming nonlinear model structure equivalence Pareto uncertainty biobjective optimisation hypothesis testing user defined confidence level argument convex optimisation nonconvex problems

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Transmission expansion planning using AC-based differential evolution algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2014年第10期8卷 1637-1644页

作者： Alhamrouni, Ibrahim Khairuddin, Azhar Ferdavani, Ali Khorasani Salem, Mohamed Univ Teknol Malaysia Fac Elect Engn Johor Baharu 81310 Malaysia

The rapid growth of the transmission networks has brought more uncertainties and new requirements in the transmission expansion planning (TEP) to the planners. The existing methods of solving TEP problem have a drawback since the DC load flow and the relaxed load flow models have been utilized to solve TEP problem. In this work, the TEP problem is solved based on mixed integer nonlinear non-convex programming model. A meta-heuristic algorithm by the means of differential evolution algorithm (DEA) is employed as an optimisation tool. An AC load flow model is used in solving the TEP problem, where accurate and realistic results can be obtained. Furthermore, the work considers the constraints checking and system violation such as real and power generation limits, possible number of lines added and bus voltage limits. The proposed technique is tested on Garver's 6 bus system and IEEE 24 bus system and has shown high capability in considering the active and reactive power in the same manner and solving the TEP problem. The method produced improved results for the test systems. In terms of minimising the cost and the solution quality, the proposed method obtained good and challenging results comparing to the previous works.

关键词： power transmission planning power transmission lines load forecasting power transmission economics cost reduction load flow integer programming nonlinear programming concave programming reactive power transmission expansion planning network AC-based differential evolution algorithm TEP transmission line load forecasting DC load flow model relaxed load flow model mixed integer nonlinear non-convex programming model metaheuristic algorithm optimisation tool AC load flow model thermal limit bus voltage limit modified Garver 6-bus system IEEE 24 bus system reactive power active power cost minimisation

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Joint trajectory design and power allocation for unmanned aerial vehicles aided secure transmission in the presence of no-fly zone

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IET COMMUNICATIONS 2022年第2期16卷 172-186页

作者： Yin, Guoxiao Zhou, Xiaotian Ma, Piming Fang, Fang Zhao, Peng Shandong Univ Sch Control Sci & Engn Jinan Peoples R China Shandong Univ Shandong Key Lab Wireless Commun Technol Jinan Peoples R China Shandong Univ Sch Informat Sci & Engn Jinan Peoples R China Univ Durham Dept Engn Durham England

Unmanned aerial vehicles (UAVs) are widely considered as key enablers for future wireless networks due to their advantages, such as high mobility and flexible deployment. In this paper, the UAV assisted secure communication system is investigated, where the UAV is deployed as the mobile jammer to prevent the eavesdropper from overhearing the confidential message. With the objective of maximizing the secrecy rate, a joint optimization problem involving the trajectory and transmit power of UAV, as well as the transmit power of source node is formulated. Moreover, the effects of Non-Fly Zone (NFZ) and imperfect estimation on the location of eavesdropper are also taken into consideration. As the original problem is hardly trackable, the worst case secrecy rate (WCSR) assumption is first employed to bypass the uncertainty brought by the estimation error. Then a block coordinate descent (BCD) based algorithm is proposed to decompose the problem into three sub-ones, where the trajectory of UAV, the transmit power of UAV and the transmit power of source can be obtained in an iterative manner. Simulation results reveal that the proposed algorithm can improve the secrecy performance significantly. In addition, the robustness of the proposed algorithm under the estimation error can also be verified.

关键词： autonomous aerial vehicles mobile jammer BCD based algorithm wireless channels secure transmission joint trajectory design NFZ joint optimization problem no-fly zone eavesdropper optimisation concave programming worst case secrecy rate assumption UAV unmanned aerial vehicle aided secure transmission power allocation WCSR secure communication system worst case secrecy rate high mobility block coordinate descent flexible deployment cooperative communication wireless networks jamming imperfect estimation estimation error

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Secure communication design for multi-user peer-to-peer wireless relay networks

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IET COMMUNICATIONS 2016年第7期10卷 770-777页

作者： Gong, Xiangwu Long, Hang Dong, Feihong Yin, Hao PLA Univ Sci & Technol Coll Commun Engn Nanjing Jiangsu Peoples R China PLAAF Unit 95899 Beijing 100000 Peoples R China Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China Inst China Elect Syst Engn Corp Beijing 100141 Peoples R China

In this study, physical layer security techniques are studied for multi-user peer-to-peer relay networks using amplify-and-forward protocol in the presence of an eavesdropper. Two system designs are considered: the minimum achievable secrecy rate maximisation and the total transmit power minimisation. First, considering user fairness, the authors study the max-min achievable secrecy rate problem subject to a total transmit power constraint. Mathematically, the optimisation problem is non-linear and non-convex. They propose a polynomial time algorithm based on the bisection technique to solve it. Second, they study the total transmit power minimisation problem which aims at minimising the total transmit power at relays such that individual secrecy rate for each user is satisfied. The total power optimisation problem is also non-convex, so they use the relaxation technique to transform it into a convex problem which can be efficiently solved by the gradient-based algorithms. Numerical evaluation of the obtained secrecy rate and transmit power results shows that the proposed designs can significantly improve the performance of secure wireless communications.

关键词： relay networks (telecommunication) radio networks peer-to-peer computing amplify and forward communication protocols minimisation minimax techniques nonlinear programming concave programming polynomials relaxation theory convex programming gradient methods computer network security secure wireless communication design multiuser peer-to-peer wireless relay network physical layer security technique amplify-and-forward protocol secrecy rate maximisation max-min achievable secrecy rate problem nonlinear optimisation problem nonconvex optimisation problem mathematical analysis polynomial time algorithm power minimisation problem total power optimisation problem relaxation technique convex problem gradient-based algorithm numerical evaluation

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Max-min fair wireless energy transfer for multiple-input multiple-output wiretap channels

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IET COMMUNICATIONS 2016年第7期10卷 739-744页

作者： Wu, Wei Zhang, Xueqi Wang, Shaohang Wang, Baoyun Nanjing Univ Posts & Telecommun Coll Commun & Informat Nanjing 210003 Jiangsu Peoples R China

In this study, the authors study the max-min fairness for wireless energy transfer in a multiuser multiple-input multiple-output communication system with simultaneous wireless information and power transfer. In particular, they aim to maximise the minimum harvested energy among the multiple multi-antenna energy receivers while guaranteeing secure communication for multi-antenna information receiver. The dual use of artificial noise to facilitate both wireless energy transfer and secure communication is exploited in the authors' proposed problem. Both scenarios of perfect and imperfect channel state information (CSI) known at the transmitter are considered. For the perfect CSI case, the formulated max-min energy harvesting (MM-EH) problem is non-convex and intractable. To circumvent it, an iterative optimisation algorithm based on Taylor series expansion is proposed. Then, they turn their attention to the imperfect CSI case, where a max-min robust energy harvesting (MMR-EH) problem is considered. Though the MMR-EH problem is more complicated than the MM-EH problem, they reveal that the iterative optimisation method can be extended to the solution of the former, wherein the S-procedure is introduced. Simulation results show the efficiency of their proposed solutions in terms of energy harvesting.

关键词： inductive power transmission MIMO communication telecommunication security energy harvesting antenna arrays receiving antennas concave programming iterative methods multiuser channels wireless channels transmitting antennas max-min fair wireless energy transfer multiple-input multiple-output wiretap channels multiuser multiple-input multiple-output communication system simultaneous wireless information transfer simultaneous wireless power transfer multiple multiantenna energy receivers secure communication multiantenna information receiver perfect channel state information imperfect channel state information max-min robust energy harvesting problem nonconvex problem iterative optimisation algorithm Taylor series expansion MM-EH problem S-procedure

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Algorithm for energy-efficiency optimisation in secure MIMO systems

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IET COMMUNICATIONS 2016年第15期10卷 1995-2000页

作者： Liu, Jian Hu, Bing Fang, Lulu Nanjing Univ Posts & Telecommun Coll Commun & Informat Engn Nanjing 210003 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Coll Internet Things Nanjing 210003 Jiangsu Peoples R China Michigan State Univ Coll Math E Lansing MI 48824 USA

In this study, the authors study energy-efficiency (EE) optimisation of three-node multiple-input-multiple-output wiretap channels. In particular, they aim to maximise EE by optimising the transmit covariance under the constraint of transmit power consumption. Such optimisation problems are non-convex and difficult to solve. Here, they propose a novel optimisation algorithm, which is very different from previous approaches, with guaranteed convergence to the Karush-Kuhn-Tucker point. In particular, through a channel improvement argument and an intelligent bounding technique, they first obtain a min-max reformulation of their original problem. Then, based on the idea of alternative optimisation, they derive two sub-problems from it. To solve these two problems, they used the efficient barrier Newton and the gradient projection methods. The outcome from this last step is a semi-closed-form solution for the two sub-problems. The numerical results obtained from the proposed algorithm represent better performances than the existing methods.

关键词： MIMO communication telecommunication security energy conservation telecommunication power management concave programming wireless channels power consumption minimax techniques Newton method gradient methods energy-efficiency optimisation secure MIMO system EE optimisation three-node multiple-input-multiple-output wiretap channels transmit covariance optimization transmit power consumption constraint nonconvex optimisation problems Karush-Kuhn-Tucker point intelligent bounding technique channel improvement argument min-max reformulation gradient projection methods efficient barrier Newton methods semiclosed-form solution

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Tight convex relaxation for TEP problem: a multiparametric disaggregation approach

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第14期14卷 2810-2817页

作者： Goodarzi, Shahin Gitizadeh, Mohsen Abbasi, Ali Reza Lehtonen, Matti Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Fasa Univ Dept Elect & Elect Engn Fasa Iran Alto Univ Dept Elect Engn & Automat Espoo 02150 Finland

In recent years, there has been an increasing interest in using AC power flow equations for the transmission expansion planning (TEP) studies. The AC power flow equations are quadratic and hence the TEP problem can be formulated as a mixed-integer quadratically constrained programme. Therefore, the complexity of the TEP problem lies in the non-convexity of AC power flow equations in which the global optimal solution is not guaranteed to be found. This study aims at proposing a tight convex relaxation for the TEP problem. In this context, first, the TEP problem is formulated as a mixed-integer bilinear problem by representing the complex bus voltage in its rectangular coordinates. Second, the multiparametric disaggregation technique (MDT) and piecewise McCormick relaxation are employed to generate a mixed-integer linear relaxation. MDT is based on the discretisation of the domain of one of the variables in every bilinear term. The method presented is much more precise compared with the DC or other linearisation approaches, while the optimal solution is of high quality. The results of the case studies show the tractability and exactness of the proposed model as well as its superiority over the state-of-the-art schemes.

关键词： integer programming quadratic programming convex programming linear programming concave programming load flow power transmission planning nonlinear programming tight convex relaxation TEP problem AC power flow equations transmission expansion planning studies mixed-integer bilinear problem mixed-integer linear relaxation

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