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Transmit waveform and receive filter design for multiple-input multiple-output radar with one-bit digital-to-analogue converters

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IET SIGNAL PROCESSING 2022年第7期16卷 873-881页

作者： Wan, Huan Quan, Zhi Liao, Bin Shenzhen Univ Coll Elect & Informat Engn Guangdong Key Lab Intelligent Informat Proc Shenzhen 518060 Peoples R China Shenzhen Polytech Sch Artificial Intelligence Shenzhen Peoples R China

In this paper, we investigate the joint design of transmit waveform and receive filter for colocated Multiple-Input Multiple-Output radar equipped with one-bit digital-to-analogue converters (DACs). The problem is formulated as maximising the output signal-to-interference-plus-noise ratio in the presence of signal-dependent interferences, subject to a discrete constraint imposed by the waveform quantised with one-bit DACs. To cope with the challenging non-convex problem, an alternating maximisation framework is developed to optimise the transmit waveform and receive filter vectors in an iterative manner. More specifically, for a given transmit waveform vector, the analytical expression of the receive filter vector is first derived. Then, by fixing the receive filter, a biconvex relaxation method is employed to tackle the non-convex problem with respect to the transmit waveform vector. The performance of the proposed approach is demonstrated by numerical simulations in different circumstances.

关键词： filter design filter vector receive filter design MIMO radar colocated multiple-input multiple-output radar convex programming iterative methods transmit waveform vector output signal-to-interference-plus-noise ratio concave programming iterative manner numerical simulations discrete constraint digital-analogue conversion one-bit digital-to-analogue converters alternating maximisation framework one-bit DAC biconvex relaxation method signal-dependent interferences nonconvex problem

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k-sparse signal recovery via unrestricted l1-2$\ell _{1-2}$-minimization

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ELECTRONICS LETTERS 2022年第17期58卷 669-671页

作者： Xie, Shaohua Liang, Kaihao Sun Yat Sen Univ Sch Math Guangzhou Peoples R China Zhongkai Univ Agr & Engn Coll Computat Sci Guangzhou Peoples R China

In the field of compressed sensing, l1-2$\ell _{1-2}$-minimization model can recover the sparse signal well. In dealing with the l1-2$\ell _{1-2}$-minimization problem, most of the existing literature uses the difference of convex algorithm (DCA) to solve the unrestricted l1-2$\ell _{1-2}$-minimization model, that is, model (4). Although experiments have proved that the unrestricted l1-2$\ell _{1-2}$-minimization model can recover the original sparse signal, the theoretical proof has not been established yet. This paper mainly proves theoretically that the unrestricted l1-2$\ell _{1-2}$-minimization model can recover the sparse signal well, and makes an experimental study on the parameter lambda in the unrestricted minimization model. The experimental results show that increasing the size of parameter lambda in (4) appropriately can improve the recovery success rate. However, when lambda is sufficiently large, increasing lambda will not increase the recovery success rate.

关键词： unrestricted minimization model compressed sensing convex programming recovery success rate k-sparse signal recovery convex algorithm minimisation signal reconstruction

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Joint offloading and beamforming design in full-duplex multi-hop SWIPT MEC systems under non-linear energy harvesting model

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IET COMMUNICATIONS 2022年第18期16卷 2171-2182页

作者： Xu, Zhiguo Lv, You Liu, Jianxin Zou, Junwei Wen, Zhigang Beijing Univ Posts & Telecommun Dept Elect Engn Beijing Key Lab Work Safety Intelligent Monitorin Beijing Peoples R China

In Internet of Things scenarios, the problem of restricted energy and limited computation capability of user node usually exists. To address the problem, a multiple-input-multiple-output full-duplex multi-hop relay simultaneous wireless information and power transfer (SWIPT) mobile-edge computing (MEC) system is proposed in this paper, where energy harvesting model is non-linear. With the aid of MEC and SWIPT, user node equipped with power splitting receiver can locally execute computation tasks or offload partial or all of it to access point associated with an MEC server by using its battery energy, and harvest energy to replenish its battery while downloading the computation results. In addition, the system introduces full-duplex multi-hop relay and non-linear energy model to improve network coverage and model practical energy harvesting circuit. Aiming at minimising the system energy consumption, an energy efficient optimisation problem is formulated while satisfying the latency and energy constraints. Since the original problem is non-linear and non-convex, it is converted into two subproblems and successive convex approximation-based algorithm and geometric programming-based algorithm based alternating optimisation technique are adopted to solve them. Numerical results verify the superiority of the proposed optimisation scheme compared with other benchmark schemes.

关键词： Internet of Things restricted energy beamforming design energy efficient optimisation problem battery energy computation results Things scenarios radiofrequency power transmission mobile-edge computing system power splitting receiver energy harvesting MIMO communication convex programming relay networks (telecommunication) resource allocation energy constraints edge computing concave programming energy consumption optimisation telecommunication power management nonlinear energy model nonconvex array signal processing limited computation capability network coverage system energy consumption computation tasks nonorthogonal multiple access mobile computing energy conservation joint offloading nonlinear energy harvesting model user node geometric programming full-duplex multihop relay power transfer MEC server model practical energy harvesting circuit full-duplex multihop SWIPT MEC systems

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Optimal gain-scheduling control of proton exchange membrane fuel cell: An LMI approach

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IET RENEWABLE POWER GENERATION 2022年第3期16卷 459-469页

作者： Afsharinejad, Amir Asemani, Mohammad Hassan Dehghani, Maryam Abolpour, Roozbeh Vafamand, Navid Shiraz Univ Sch Elect & Comp Engn Shiraz Iran

Here, an optimal linear parameter varying (LPV) controller is developed for non-linear proton exchange membrane fuel cell (PEMFC) systems. Two performance criteria are involved in the optimal controller, including the membrane pressure and the power of the PEMFC. The former should be minimized;and, the latter should be maximized. Since the goal is to derive sufficient conditions in terms of linear matrix inequality (LMI) constraints, both performances are re-formulated and augmented in a unique convex optimization problem. Further, the non-linear PEMFC with the equilibrium profile dependent on time-varying parameters, that is, current and temperature, is represented by an LPV model. Using the LMI constraints and the obtained LPV model, the gains of the controller are derived. Comparing with the state-of-the-art methods, the proposed approach offers an optimal control approach with a systematic design method, in which both practical issues are treated, simultaneously. To show the advantages of the developed approach, six typical controllers, including the proposed and existing approaches, are considered and several numerical simulation results are conducted.

关键词： performance criteria nonlinear PEMFC optimal control approach LMI approach optimal controller time-varying parameters LPV model convex programming optimisation typical controllers membrane pressure control system synthesis optimal control unique convex optimization problem linear matrix inequality constraints linear parameter varying systems optimal gain-scheduling control LMI constraints linear matrix inequalities optimal linear parameter nonlinear proton exchange membrane fuel cell systems time-varying systems proton exchange membrane fuel cells

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AC Network-Constrained Unit Commitment via Relaxation and Decomposition

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IEEE TRANSACTIONS ON POWER SYSTEMS 2022年第3期37卷 2187-2196页

作者： Constante-Flores, Gonzalo E. Conejo, Antonio J. Qiu, Feng Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA Ohio State Univ Dept Integrated Syst Engn Columbus OH 43210 USA Argonne Natl Lab Div Energy Syst Lemont IL 60439 USA

We propose an approach to solving the AC network-constrained unit commitment problem (AC-NCUC) of large-scale power systems. This approach relies on solving convex (continuous and mixed-integer) optimization problems. First, we formulate a second-order conic relaxation of the original optimization problem, which renders a mixed-integer second-order conic optimization problem. To solve this problem, we use Benders' decomposition, which decomposes it into a master problem, which is mixed-integer linear, and a subproblem, which is continuous and second-order conic. To improve the convergence of the Benders' algorithm, we add several linear feasibility constraints to the master problem. Since the second-order relaxation of the original problem cannot guarantee AC feasibility of the solution found, we ensure such feasibility by solving a sequence of continuous convex optimization problems. We numerically validate the proposed approach using a Texas 2000-bus system.

关键词： Optimization Reactive power Turbines Mathematical models programming Costs Convergence Benders' decomposition conic relaxation convex programming unit commitment

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Multicasting in NOMA-based UAV networks: Path design and throughput maximisation

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IET COMMUNICATIONS 2022年第14期16卷 1708-1723页

作者： Hosseini, Shima Salar Javan, Mohammad Reza Nazari, Ali Shahrood Univ Technol Dept Elect Engn Shahrood Iran

In this paper, a new resource allocation framework for unmanned aerial vehicle (UAV) assisted multicast wireless networks is proposed in which the network users according to their request are divided into several multicast groups. Power domain non-orthogonal multiple access is adopted as the transmission technology using which the dedicated signals of multicast groups are superimposed and transmitted simultaneously as the UAV passes over the communication area for fixed and mobile users. The proposed scenarios are discussed from two perspectives, offline and online modes. In offline mode, the problem is implemented for fixed and mobile users whose locations are predictable (the location of users, over the communication time, is known at the beginning of the communication time) and in online mode for mobile users whose locations are unpredictable (the location of users, over the communication time, is unknown at the beginning of the communication time). Also, a scenario is proposed in which the online mode the number of mobile users can grow in each time slot. The problem of joint power allocation and UAV trajectory design as an optimisation problem that is non-linear and non-convex for two proposed scenarios is formulated. To solve the problem, an alternate search method, successive convex approximation, and geometric programming are adopted. Using simulation results, the performance of the proposed scheme is evaluated for different values of the network parameters.

关键词： network users time slot autonomous aerial vehicles network parameters UAV trajectory design multicasting wireless channels communication area throughput maximisation convex programming resource allocation communication time optimisation concave programming telecommunication power management NOMA-based UAV networks approximation theory free-space optical communication multicast groups unmanned aerial vehicle offline mode nonorthogonal multiple access mobile users power domain nonorthogonal telecommunication control online mode wireless networks geometric programming joint power allocation online modes fixed users resource allocation framework

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Secrecy-oriented user association in ultra dense heterogeneous networks against strategically colluding adversaries

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IET COMMUNICATIONS 2022年第6期16卷 695-709页

作者： Su, Gongchao Dai, Mingjun Chen, Bin Lin, Xiaohui Wang, Hui Shenzhen Univ Coll Elect & Informat Engn Shenzhen Guangdong Peoples R China

Network densification is recognized as the key technology to meet the ever growing demand of data traffic in next generation wireless networks. However the proliferation of small cell base stations (SCBSs) introduces vulnerabilities to information security, as they are prone to eavesdropping attacks. In this paper, it is studied how user association strategies can be specifically tailored to meet this security challenge in a ultra dense heterogeneous cellular network(UDHCN) with a group of colluding eavesdroppers. In particular, the situation is considered where eavesdroppers may have limited capabilities in intercepting and decoding data traffic. In this setting each eavesdropper has to make its own decision on eavesdropping targets, and they are able to take concerted actions to sabotage information security. To address this challenge, a zero sum game framework to reflect the conflicting interests of users and eavesdroppers is proposed and a user association scheme is devised that aims to maximize system sum secrecy rate against these adversaries whose actions intend to minimize sum secrecy rate. The case that all adversaries have limited eavesdropping capabilities is first considered, and it is shown that the corresponding zero sum game is indeed a bilinear game, and its Nash equilibrium solution can be readily approximated using a saddle point Frank Wolfe(SP-FW)algorithm. Then the framework is extended to the case where adversaries with a diverse configuration of eavesdropping capabilities exist. In this case, it is shown that the underlying minimax optimization problem is indeed a nonsmooth convex-nonconcave one. A two stage method is proposed by first smoothing the objective function with a Hermite cubic polynomial approximation, and then obtaining a nearly stationary solution via a recently proposed proximal point gradient descent method. Simulation results show that the proposed framework leads to significant increases in sum secrecy rate and secrecy probabi

关键词： bilinear game eavesdropping targets user association scheme wireless channels secrecy-oriented user association eavesdropping attacks concerted actions convex programming optimisation decoding data traffic minimax techniques security challenge information security network densification zero sum game framework secrecy probability cellular radio cell base stations telecommunication security ultra dense heterogeneous networks 5G mobile communication setting each eavesdropper corresponding zero sum game user association strategies system sum secrecy rate polynomial approximation gradient methods eavesdropping capabilities probability colluding eavesdroppers intercepting game theory

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Robust multi-model controllers design without impulse in switching times for non-linear vibrations suppression of sandwich plate

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IET CONTROL THEORY AND APPLICATIONS 2022年第15期16卷 1548-1559页

作者： Zazerani, Amir Amini Faraji, Alireza Mohammadimehr, Mahdi Univ Kashan Fac Elect Engn & Comp Dept Control Kashan Iran Inst Mat & Energy Fleat Control Grp Esfahan Iran Univ Kashan Fac Mech Engn Dept Solid Mech Kashan Iran

Generally multi-model controllers design has three stages: Decomposition of complicated non-linear systems into local linear models, designing the local controllers, and composition of them in sub-regions. In the present paper an algorithm is proposed in which all the three stages are simultaneously done to decrease the number of controllers. Determining a specific threshold based on non-linear model characteristics is a good criterion for this purpose. The threshold depends on the knowledge of the system features and designing method, and the improper selection of the threshold will increase the number of local models and the complexity of the global controller structure. This non-convex optimization problem is solved by the genetic algorithm whose cost function is defined by the complementary sensitivity function to guarantee the robust stability and optimal performance of the close loop the system, respectively. Another challenge in designing multi-model controllers is the transient performance degradation when switching from one local model to another. In the present research, the problem is solved by the system input generated by the online controller error signal and the feedback coefficient of the offline controller. The proposed robust controller in the presence of the uncertainties is evaluated for vibration suppression of a sandwich plate.

关键词： nonconvex optimization problem local controllers nonlinear vibrations suppression online controller error signal robust controller genetic algorithms vibration suppression convex programming robust control robust stability robust multimodel controllers design genetic algorithm optimal control nonlinear systems nonlinear control systems linear systems offline controller sandwich plate system input nonlinear model characteristics local model switching times feedback vibration control control system synthesis global controller structure local linear models system features

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Joint transmit filter and sparse array design with transmit subaperturing FDA-MIMO radar

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IET SIGNAL PROCESSING 2022年第2期16卷 132-140页

作者： Ding, Zihang Xie, Junwei Air Force Engn Univ Air & Missile Def Coll Xian 710038 Shaanxi Peoples R China

Increasingly complex electromagnetic environment makes some troubles for a radar system. Improving the performance of the radar detection and suppressing the interferences are important challenges. In this study, joint transmit filters and sparse array design enabling the maximum signal to interference plus the noise ratio (SINR) beamforming at the transmit subaperturing frequency diverse array multiple-input multiple-output (TS-FDA-MIMO) radar is examined. However, the optimisation problem is non-convex. A cycle iteration algorithm is proposed to obtain the optimal transmit filters and sparse array. The total problem is divided into two sub-problems. The first optimisation sub-problem is the sparse design and the Successive convex Approximation (SCA) with two-dimensional reweighted mixed l1, 2-norm method is introduced to solve the sub-problem. In addition, the transmit filters design is the second optimisation problem. The sub-problem is changed to the semi-definite relaxation (SDR) problem and the Gaussian random method is utilised to obtain the optimal transmit filters. Through the cycle iteration of the two sub-problems, the optimal solutions are obtained. Finally, the simulation results verified the effectiveness of the proposed method.

关键词： sparse design transmit subaperturing frequency diverse array multiple-input multiple-output radar semidefinite relaxation problem TS-FDA-MIMO complex electromagnetic environment optimisation problem MIMO radar approximation theory total problem 2-norm method filtering theory convex programming iterative methods radar signal processing optimisation sub-problem optimal transmit filters transmit subaperturing FDA-MIMO radar Gaussian processes sparse array design radar detection array signal processing joint transmit filter radar system

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Active vibration on offshore steel jacket platforms including delayed probabilistic actuator failures and resilient reliable sampled-data control

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IET CONTROL THEORY AND APPLICATIONS 2022年第15期16卷 1531-1547页

作者： Manivannan, R. Cao, Yang Chong, Kil To SASTRA Deemed Univ Sch Arts Sci & Humanities SASH Dept Math Thanjavur 613401 Tamil Nadu India Southeast Univ Sch Cyber Sci & Engn Nanjing 211189 Peoples R China Jeonbuk Natl Univ Dept Elect & Informat Engn Jeonju 54896 South Korea Jeonbuk Natl Univ Adv Elect & Informat Res Ctr Jeonju South Korea

This paper examines the unified dissipative performance of Offshore Steel Jacket Platforms (OSJPs) which include actuator failures and probabilistic delays, through a resilient and reliable sampled-data controller. In detail, random variables fetching the Bernoulli distribution are treated in particular for the stochastic time-delays. By implementing the Lyapunov-Krasovskii functions(LKF) together with the Second Order Bessel-Legendre Inequality Technique (SOBLIT) and an improved Reciprocally convex Inequality (RCI) approach, which provides impressive information about sampling to guarantee that the OSJP is unified dissipative. The proposed criterion is exhibited in the sort of linear matrix inequalities (LMIs) and highlights of this study is to examine the multi-dynamic interpretation of OSJP with extended dissipativity indices. The advantage of the established methodology is explored for OSJPs with the existing results, which is carried out along with the proposed control law, using their values of the experimental parameters.

关键词： linear matrix inequalities sampled data systems delay systems resilient data controller reliable sampled-data controller control law active vibration Lyapunov-Krasovskii functions convex programming improved Reciprocally convex Inequality approach sampled-data control actuators nonlinear control systems asymptotic stability time-varying systems unified dissipative performance offshore steel jacket platforms Second Order Bessel-Legendre Inequality Technique offshore installations probabilistic actuator failures Lyapunov methods control system synthesis extended dissipativity indices stochastic time-delays delays probabilistic delays OSJP

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