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Efficient noise reduction for interferometric phase image via non-local non-convex low-rank regularisation

IET SIGNAL PROCESSING 2016年第7期10卷 815-824页

作者： Luo, Xiao Mei Suo, Zhi Yong Liu, Qie Gen Wang, Xiang Feng Nanchang Univ Dept Elect Informat Engn Nanchang 330031 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710017 Peoples R China East China Normal Univ Inst Software Engn Shanghai Key Lab Trustworthy Comp Shanghai 200062 Peoples R China Paul C Lauterbur Res Ctr Biomed Imaging Shenzhen Key Lab MRI Shenzhen 518055 Peoples R China

This study considers the phase noise filtering problem for interferometric phase image using sparse optimisation technique. Since the original model can be formulated as a rank minimisation problem, it is difficult to solve. One appealing approach is to use a nuclear norm (NN) regularisation to relax the rank regulariser. However, the performance of such approach is not satisfying. In this study, the authors propose to use reweighted NN regularisation to approximate the rank regulariser, which leads to the low-rank reformulation. Though this reformulation is non-convex, a new algorithm termed as spatially adaptive iterative weighted singular-value thresholding algorithm is proposed to effectively solve it. Specifically, the weight and image variables are updated alternatively by block coordinate descent iteration scheme. In addition, the corresponding computational complexity of the algorithm has been established. Simulation results based on simulated and measured data show that this new phase noise reduction method has much better performance than several existing phase filtering methods.

关键词： radar interferometry synthetic aperture radar concave programming iterative methods image filtering image denoising singular value decomposition approximation theory radar imaging efficient noise reduction interferometric phase image nonlocal nonconvex low-rank regularisation phase noise filtering problem sparse optimisation technique reweighted nuclear norm regularisation rank regulariser approximation spatial adaptive iterative weighted singular-value thresholding algorithm weight variable image variable block coordinate descent iteration scheme computational complexity phase noise reduction method

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Wireless backhaul resource allocation and user-centric clustering in ultra-dense wireless networks

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IET COMMUNICATIONS 2016年第15期10卷 1858-1864页

作者： Hua, Cunqing Luo, Yifeng Liu, Huibo Shanghai Jiao Tong Univ Sch Informat Secur Engn Shanghai 200240 Peoples R China

Wireless backhaul is a promising technology to lower the cost for connecting a large number of densely deployed access points in the emerging fifth generation wireless system. In this study, the authors consider the joint optimisation of resource allocation in wireless backhaul links and user-centric clustering in the access links. The objective is to maximise the weighted sum rate of all users under the backhaul resource constraints. To solve this intractable problem, they first adopt the (1)-norm approximation approach to convert the non-convex backhaul constraints into the solvable forms. They then reformulate the objective function as a set of second-order cone constraints based on the sequential parametric convex approximation method. An iterative algorithm is proposed to solve the transformed problem based on its special property. Simulation results show that the proposed algorithm outperforms other existing schemes under different network settings.

关键词： pattern clustering 5G mobile communication radio links approximation theory convex programming iterative methods concave programming iterative algorithm successive parametric convex approximation method second-order cone constraint set nonconvex backhaul constraint l(1)-norm approximation approach backhaul resource constraint weighted sum rate maximisation access link wireless backhaul link resource allocation joint optimisation fifth generation wireless system ultra-dense wireless network user-centric clustering wireless backhaul resource allocation

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Rank revealing-based tensor completion using improved generalized tensor multi-rank minimization

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IET SIGNAL PROCESSING 2021年第8期15卷 483-499页

作者： Sun, Wei Z. Zhang, Peng Zhao, Bo Shenzhen Univ Coll Informat Engn Shenzhen Guangdong Peoples R China

The authors address the problem of tensor completion from limited samplings. An improved generalized tubal Kronecker decomposition is first proposed to reveal the tensor structure of the targeted data, and the improved generalized tensor tubal-rank and multi-rank are also introduced. The tensor completion problem is then formulated as the improved multi-rank minimisation problem. Instead of using the singular value decomposition(SVD), this work proposes an alternating optimisation method to update all of the subspaces of the data tensor for the recovery process, and thus it is computationally inexpensive. A rank-decreasing method is derived to reveal the tensor rank in order to avoid the troublesome user defined hyper-parameter selection. Experiments are carried out on both the synthetic data and the real datasets, and it is shown that the proposed approach can get a better performance than the state-of-the-art approaches with moderate computational complexity.

关键词： computational complexity concave programming matrix algebra minimisation optimisation singular value decomposition tensors

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Optimisation of secrecy rate in cooperative device to device communications underlaying cellular networks

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IET COMMUNICATIONS 2019年第5期13卷 512-519页

作者： Alibeigi, Maryam Taherpour, Abbas Imam Khomeini Int Univ Dept Elect Engn Qazvin Iran

In this study, the optimisation of cooperation level and uplink spectrum sharing are analysed by employing physical layer security concept in the device to device communications underlaying cellular networks. It is assumed that two transmitting devices communicate with the same receiving device in the presence of a passive eavesdropper. Also, it is assumed that one of the two transmitting devices aids the other one as a relay node. The optimum cooperation level and channel assignment schemes are obtained through maximizing the secrecy rate under constraints of satisfying the quality of services for cellular users (CUs) and the receiving device. In this sense, the selected CU which shares its resource block acts as a friendly jammer to interfere the eavesdropper. Although the proposed approach initially leads to a non-convex optimization problem, it can be solved efficiently by using GloptiPloy (global optimum polynomial) and SeDuMi software packages. Simulation results are provided to evaluate the performance of the proposed optimum cooperation level scheme and demonstrate the superiority of the proposed approach compared to the conventional fixed cooperation level schemes.

关键词： cellular radio channel allocation concave programming convex programming jamming optimisation radio spectrum management radiofrequency interference telecommunication security wireless channels

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Cooperative MIMO relay beamforming in overloaded DS/CDMA multicast networks

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IET COMMUNICATIONS 2017年第3期11卷 344-354页

作者： Mehrizi, Sajad Mahboobi, Behrad Islamic Azad Univ Sci & Res Branch Dept Engn Tehran Iran

A new beamforming scheme is proposed for multi-input multi-output (MIMO) non-regenerative relays in an overloaded synchronous direct sequence code division multiple access (DS-CDMA) network in which the number of users is larger than the processing gain. In this scheme, several transmitters multicast their data to their groups of receivers through MIMO relays and DS-CDMA technique is utilised to decrease the level of multiple access interference (MAI) at the relays and the receivers. At the relays, the data of transmitters are despread, beamformed and re-spread. The aim of the beamformer is to minimise the total relays transmission power subject to the signal to interference and noise ratio (SINR) constraints at the receivers. This optimisation problem is an indefinite quadratic (non-convex) programming. Semi-definite programming (SDP) and second-order cone programming (SOCP) are two existing methods to solve the problem. However, they, respectively, suffer from high computational complexity and performance degradation when the number of antennas or users increase. To effectively mitigate these deficiencies, we propose a novel DC (difference of two convex functions) programming method. Our simulation results demonstrate the computational advantage of the proposed DC programming over SDP, while a better performance over SOCP is achieved. Moreover, the superiority of the proposed MIMO-CDMA scheme over other multiplexing schemes is shown by several scenarios.

关键词： cooperative communication MIMO communication relay networks (telecommunication) array signal processing code division multiple access spread spectrum communication radiofrequency interference concave programming computational complexity cooperative MIMO relay beamforming overloaded synchronous DS-CDMA multicast networks multiinput multioutput nonregenerative relays direct sequence code division multiple access network multiple-access interference total relay transmission power minimization SINR constraint optimisation problem indefinite quadratic programming nonconvex programming computational complexity antenna number DC programming method difference-of-two convex functions SDP SOCP MIMO-CDMA scheme

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Real coded genetic algorithm approach with random transfer vectors-based mutation for short-term hydro-thermal scheduling

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IET Generation Transmission & Distribution 2015年第1期9卷 75-89页

作者： Haghrah, Amirarslan Mohammadi-ivatloo, Behnam Seyedmonir, Seyedehnegar Univ Tabriz Fac Elect & Comp Engn Tabriz Iran

The short-term hydro-thermal scheduling involves scheduling of hydro and thermal generations to minimise the fuel cost of thermal plants in a horizon of planning time while meeting various hydraulic and electric system constraints. The problem is considered as a non-linear and non-convex problem involving valve-points effects and transmission losses with a set of equality and inequality constraints. In this study, a novel promising approach is represented with an innovated mutation method utilising genetic algorithm (GA). The proposed real coded GA approach with random transfer vectors-based mutation (RCGA-RTVM) is applied to two test systems with different characteristics. The effectiveness of the proposed RCGA-RTVM is validated by the obtained results. Comparison of the obtained results with recently developed methods shows the superiority of the proposed algorithm.

关键词： genetic algorithms hydrothermal power systems power generation scheduling nonlinear programming concave programming real coded genetic algorithm approach random transfer vectors-based mutation short-term hydrothermal scheduling thermal plants hydraulic system constraints electric system constraints nonlinear problem nonconvex problem valve-point effects transmission losses GA approach RCGA-RTVM

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Maximization of a PSD quadratic form and factorization

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OPTIMIZATION LETTERS 2021年第7期15卷 2515-2528页

作者： Hladik, Milan Hartman, David Zamani, Moslem Charles Univ Prague Dept Appl Math Fac Math & Phys Malostranske Nam 25 Prague 11800 Czech Republic Czech Acad Sci Inst Comp Sci Prague Czech Republic Ferdowsi Univ Mashhad Dept Appl Math Fac Math Sci Mashhad Razavi Khorasan Iran Charles Univ Prague Inst Comp Sci Fac Math & Phys Prague 11800 Czech Republic

We consider the problem of maximization of a convex quadratic form on a convex polyhedral set, which is known to be NP-hard. In particular, we focus on upper bounds on the maximum value. We investigate utilization of different vector norms (estimating the Euclidean one) and different objective matrix factorizations. We arrive at some kind of duality with positive duality gap in general, but with possibly tight bounds. We discuss theoretical properties of these bounds and also extensions to generally preconditioned factors. We employ mainly the maximum vector norm since it yields efficiently computable bounds, however, we study other norms, too. Eventually, we leave many challenging open problems that arose during the research.

关键词： Convex quadratic form concave programming NP-hardness Upper bound Maximum norm Preconditioning

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Communication-awareness joint beams and power allocation scheme of radar network for manoeuvring targets tracking

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IET RADAR SONAR AND NAVIGATION 2020年第2期14卷 207-215页

作者： Lu, Yanxi He, Zishu Liu, Shuangli Sun, GuoHao Univ Elect Sci & Technol China Chengdu Sichuan Peoples R China

The coexistence of radar and communication system is a crucial task owing to the shortage of spectrum resources. In this study, the authors consider a multiple manoeuvring targets tracking problem via a radar network in the presence of several non-cooperative, spatially random, and spectral overlapped communication areas (CAs). Instead of costly inner pattern optimisation, a communication awareness joint beam and power allocation (CJBPA) scheme of radar network is proposed to achieve high flexibility in coexistence. In CJBPA, radars and CAs treat the signals from each other as interference, which are formulated and discussed from the perspective of spectrum and space. The CJBPA optimises the overall tracking performance, which is characterised by the posterior Cramer-Rao lower bound under the consideration of coexistence. The resultant non-convex problem is relaxed and decoupled as an integrated two-staged optimisation. To accelerate the numerical procedures of the optimisations, custom-built primal dual interior point methods are derived by the structure information of the problems. The effectiveness of the proposed CJBPA scheme is assessed through simulations, showing that by using spatial and spectral information of undesired signals, the tracking performance can be optimised while the impacts of interference on both radars and CAs are restricted.

关键词： target tracking phased array radar concave programming radar tracking radar interference CA spectrum resource allocation phased array radar network spectral overlapped communication areas resultant nonconvex problem custom-built primal dual interior point methods CJBPA scheme complicated inner pattern optimisation posterior Cramer-Rao lower bound communication-awareness joint beam and power allocation scheme multiple manoeuvring target tracking performance integrated two-staged optimisation

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A robust active distribution network defensive strategy against cyber-attack considering multi-uncertainties

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第8期16卷 1476-1488页

作者： Yang, Jie Guo, Yihao Guo, Chuangxin Chen, Zhe Wang, Shenghan Jiang, Boyou Zhejiang Univ Coll Elect Engn 38 Zheda Rd Hangzhou 310027 Zhejiang Peoples R China Elect Power Res Inst State Grid Zhejiang Elect Po 1 Huadian Lane Hangzhou 310000 Zhejiang Peoples R China

A robust defensive strategy for active distribution networks considering multi-uncertainties and island restoration is studied. Firstly, the authors take triple uncertainties into consideration, that is, the attack strategy, the amount of wind power generation and solar irradiation. Next, a trilevel defender-attacker-defender (DAD) two-stage robust mathematical model is established to make full use of the energy storage support capacity and reduce the load shedding. The first stage is to pre-allocate defensive resources, and the second stage is to dispatch emergent defensive resources in the worst scenario to minimize the load shedding. Using column and constraint generation (C&CG) algorithm to solve the model, the original problem is converted into the min main problem and max-min sub-problem. The non-convexity of the sub-problem is relaxed by using the second order cone programming (SOCP) model, and converted to the max problem according to the strong duality theory. Solving the model with returned cuttings iteratively. The simulation results show that the proposed method is effective and the defensive strategy can adapt to multi-uncertainties.

关键词： computer crime duality (mathematics) wind power plants strong duality theory resource allocation solar power stations trilevel defender-attacker-defender two-stage robust mathematical model iterative methods max-min sub-problem energy storage support capacity wind power generation cyber-attack minimax techniques min main problem trilevel DAD two-stage robust mathematical model distributed power generation SOCP model distribution networks robust active distribution network defensive strategy C&CG algorithm solar irradiation second order cone programming model robust defensive strategy power system security load shedding island restoration column and constraint generation algorithm concave programming active distribution networks power engineering computing

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Multi-loop PI/PID controllers design for disturbance rejection based on non-parametric effective model and non-convex optimisation

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IET CONTROL THEORY AND APPLICATIONS 2014年第15期8卷 1499-1512页

作者： Jin, Qibing Liu, Qie Beijing Univ Chem Technol Coll Informat Sci & Technol Inst Automat Beijing 100029 Peoples R China

In this study, the authors address the design of the multi-loop controllers for multi-input and multi-output (MIMO) processes for disturbance rejection. Three types of disturbance rejection are analysed, and they demonstrate that those disturbance responses are directly related to the integral terms of the controllers. A concept of non-parametric effective model is introduced here to decompose a MIMO control system into several equivalent single-input and single-output control systems. Based on the effective model in each loop, a non-convex optimisation problem is established to obtain the optimal controller parameters with certain robustness indices. Considering the drawbacks of using random search algorithm, they develop a numerical algorithm to solve this non-convex optimisation problem. Simulation studies demonstrate that the proposed method improves the disturbance rejection compared with other decentralised controllers.

关键词： MIMO systems three-term control PI control control system synthesis concave programming optimal control search problems numerical analysis multiloop PI-PID controllers design disturbance rejection nonparametric effective model multi-input and multi-output processes disturbance responses MIMO control system nonconvex optimisation problem equivalent single-input and single-output control systems optimal controller parameters certain robustness indices random search algorithm numerical algorithm decentralised controllers

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