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User scheduling and power allocation for downlink multi-cell multi-carrier NOMA systems

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Digital Communications and Networks 2023年第1期9卷 252-263页

作者： Abuzar B.M.Adam Xiaoyu Wan Zhengqiang Wang School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

In Non-Orthogonal Multiple Access(NOMA),the best way to fully exploit the benefits of the system is the efficient resource allocation.For the NOMA power domain,the allocation of power and spectrum require solving the mixed-integer nonlinear programming NP-hard problem.In this paper,we investigate user scheduling and power allocation in Multi-Cell Multi-Carrier NOMA(MCMC-NOMA)networks.To achieve that,we consider Weighted Sum Rate Maximization(WSRM)and Weighted Sum Energy Efficiency Maximization(WSEEM)problems.First,we tackle the problem of user scheduling for fixed power using fractional programming(FP),the Lagrange dual method,and the decomposition method.Then,we consider Successive Pseudo-Convex Approximation(SPCA)to deal with the WSRM problem.Finally,for the WSEEM problem,SPCA is utilized to convert the problem into separable scalar problems,which can be parallelly solved.Thus,the Dinkelbach algorithm and constraints relaxation are used to characterize the closed-form solution for power allocation.Extensive simulations have been implemented to show the efficiency of the proposed framework and its superiority over other existing schemes.

关键词： Weighted sum rate Weighted energy efficiency Non-orthogonal multiple access Successive pseudo-convex approximation fractional programming

A Convex Approximation for a PDE Constrained fractional Optimization Problem with an Application to Photonic Crystal Design

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Advances in Applied Mathematics and Mechanics 2023年第6期15卷 1540-1561页

作者： Mengyue Wu Jianhua Yuan Jianxin Zhang School of Science Beijing University of Post and TelecommunicationsBeijing 100876China

Based on a subspace method and a linear approximation method,a convex algorithm is designed to solve a kind of non-convex PDE constrained fractional optimization problem in this paper.This PDE constrained problem is an infinitedimensional Hermitian eigenvalue optimization problem with non-convex and low regularity.Usually,such a continuous optimization problem can be transformed into a large-scale discrete optimization problem by using the finite element methods.We use a subspace technique to reduce the scale of discrete problem,which is really effective to deal with the large-scale problem.To overcome the difficulties caused by the low regularity and non-convexity,we creatively introduce several new artificial variables to transform the non-convex problem into a convex linear semidefinite programming.By introducing linear approximation vectors,this linear semidefinite programming can be approximated by a very simple linear relaxation problem.Moreover,we theoretically prove this approximation.Our proposed algorithm is used to optimize the photonic band gaps of two-dimensional Gallium Arsenide-based photonic crystals as an application.The results of numerical examples show the effectiveness of our proposed algorithm,while they also provide several optimized photonic crystal structures with a desired wide-band-gap.In addition,our proposed algorithm provides a technical way for solving a kind of PDE constrained fractional optimization problems with a generalized eigenvalue constraint.

关键词： PDE constrained optimization fractional programming linear approximation finite element method photonic band gap

A fractional programming Method for Interval-valued Intuitionistic Fuzzy Multi-attribute Decision Making

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A Fractional Programming Method for Interval-valued Intuitio...

Joint Beamforming Optimization for Reconfigurable Intelligent Surface-Enabled MISO-OFDM Systems

2010 Chinese Control and Decision Conference

作者： Zhoujing Wang~(1,2),Jianhui Xu~2 1.School of Computer Science and Engineering,Beihang University,Beijing 100083,China 2.Department of Automation,Xiamen University,Xiamen,Fujian,361005,China

＜正＞In decision making problems,the increasing complexity of the world and the fuzziness of human thinking make it difficult to express a decision maker’s preference information over alternatives and attributes with crisp data.As such,the interval-valued intuitionistic fuzzy sets（IVIFS） have become convenient and suitable to deal with the vagueness.This article investigates the multi-attribute decision making（MADM） problem under the IVIFS environment,where both the attribute weights and the assessments of alternatives with respect to attributes are given by the decision maker in terms of interval-valued intuitionistic fuzzy numbers.Several fractional programming models are derived from TOPSIS to determine the fuzzy relative closeness intervals of alternatives,and the corresponding decision-making method has also been developed.Feasibility and effectiveness of the proposed method are illustrated with an investment decision problem.

关键词： Multiattribute Decision Making（MADM） Interval-valued Intuitionistic Fuzzy Numbers（IVIFNs） fractional programming TOPSIS

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China Communications 2021年第3期18卷 63-79页

作者： Keming Feng Xiao Li Yu Han Yijian Chen National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China ZTE Corporation Shenzhen 518057China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518057China

In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.

关键词： reconfigurable intelligent surface(RIS) OFDM joint beamforming optimization fractional programming majorization-minimization manifold optimization

A Survey of Hidden Convex Optimization

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Journal of the Operations Research Society of China 2020年第1期8卷 1-28页

作者： Yong Xia Key Laboratory of Mathematics Informatics and Behavioral Semantics of the Ministry of EducationSchool of Mathematics and System SciencesBeihang UniversityBeijing 100191China

Motivated by the fact that not all nonconvex optimization problems are difficult to solve,we survey in this paper three widely used ways to reveal the hidden convex structure for different classes of nonconvex optimiz... 详细信息

关键词： Convex programming Quadratic programming Quadratic matrix programming fractional programming Lagrangian dual Semidefinite programming

The Ultimate Noise Limit for Hall Plates in Voltage, Current, and Hybrid Operating Modes

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Journal of Applied Mathematics and Physics 2020年第12期8卷 3019-3059页

作者： Udo Ausserlechner Department Sense and Control Infineon Technologies AG Villach Austria

If Hall plates are used as magnetic field sensors they are usually powered up by a current source connected to a pair of non-neighboring contacts. The output voltage is tapped at another pair of non-neighboring contacts. In this paper we study more general operating conditions of Hall plates with an arbitrary number of contacts. In such hybrid operating modes current sources are connected to a first set of contacts and voltage sources to a second set of contacts. Output voltages are tapped at the first set of contacts and output currents are measured at the second set of contacts. All these output signals are multiplied by coefficients and added up. The purpose of this work is to figure out which operating mode and which Hall plate achieve maximum signal at minimum thermal noise and power dissipation. To this end we develop a theory, which gives the ratio of signal over noise and power as a function of the resistance matrix of Hall plates, of the supply voltages and currents, and of the coefficients. Optimization is done analytically in closed form and numerically for specific examples. The results are: 1) all operating modes have identical noise performance if their parameters are optimized;2) for any Hall plate one can measure its resistance matrix and insert its values into our formulae to obtain the optimum supply currents and coefficients for optimum noise performance.

关键词： Canonical-Correlation Analysis fractional programming Hybrid N-Pole Matrix Multi-Port Hall Plates Noise Efficiency Rayleigh Quotient Signal to Noise Ratio

Global Optimization Model of Joint Aeronautical and Maritime Search

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Global Optimization Model of Joint Aeronautical and Maritime...