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Portfolio selection with the effect of systematic risk diversification: formulation and accelerated gradient algorithm

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OPTIMIZATION METHODS & SOFTWARE 2019年第3期34卷 612-633页

作者： Li, Qian Bai, Yanqin Yan, Xin Zhang, Wei Shanghai Univ Dept Math Shanghai Peoples R China Shanghai Univ Int Business & Econ Sch Stat & Informat Shanghai Peoples R China

In this paper, we propose an optimal trade-off model for portfolio selection with the effect of systematic risk diversification, measured by the maximum marginal systematic risk of all the risk contributors. First, the classical portfolio selection model with constraints on allocation of systematic risk is shown to be equivalent to our trade-off model under certain conditions. Then, we transform the trade-off model into a special non-convex and non-smooth composite problem equivalently. Thus a modified accelerated gradient (AG) algorithm can be introduced to solve the composite problem. The efficiency of the algorithm for solving the composite problem is demonstrated by theoretical results on both the convergence rate and the iteration complexity bound. Finally, empirical analysis demonstrates that the proposed model is a preferred tool for active portfolio risk management when compared with the existing models. We also carry out a series of numerical experiments to compare the performance of the modified AG algorithm with the other three first-order algorithms.

关键词： mean-variance model systematic risk branch-and-bound non-convex programming accelerated gradient algorithm

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Joint Antenna Array Mode Selection and User Assignment for Full-Duplex MU-MISO Systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第6期18卷 2946-2963页

作者： Nguyen, Hieu V. Van-Dinh Nguyen Dobre, Octavia A. Wu, Yongpeng Shin, Oh-Soon Soongsil Univ Sch Elect Engn Seoul 06978 South Korea Soongsil Univ Dept ICMC Convergence Technol Seoul 06978 South Korea Mem Univ Fac Engn & Appl Sci St John NF A1X3C5 Canada Shanghai Jiao Tong Univ Dept Elect Engn Minhang 200240 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710126 Shaanxi Peoples R China

This paper considers a full-duplex (FD) multiuser multiple-input single-output system where a base station simultaneously serves both uplink (UL) and downlink (DL) users on the same time-frequency resource. The crucial barriers in implementing FD systems reside in the residual self-interference and co-channel interference. To accelerate the use of FD radio in future wireless networks, we aim at managing the network interference more effectively by jointly designing the selection of half-array antenna modes (in the transmit or receive mode) at the base station with time phases and user assignments. The first problem of interest is to maximize the overall sum rate subject to quality-of-service requirements, which is formulated as a highly non-concave utility function followed by non-convex constraints. To address the design problem, we propose an iterative low-complexity algorithm by developing new inner approximations, and its convergence to a stationary point is guaranteed. To provide more insights into the solution of the proposed design, a general max-min rate optimization is further considered to maximize the minimum per-user rate while satisfying a given ratio between UL and DL rates. Furthermore, a robust algorithm is devised to verify that the proposed scheme works well under channel uncertainty. The simulation results demonstrate that the proposed algorithms exhibit fast convergence and substantially outperform existing schemes.

关键词： Full-duplex radios multiuser transmission non-convex programming robust design self-interference spectral efficiency transmit beamforming user assignment

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Joint Power Control and User Association for NOMA-Based Full-Duplex Systems

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第11期67卷 8037-8055页

作者： Nguyen, Hieu, V Van-Dinh Nguyen Dobre, Octavia A. Nguyen, Diep N. Dutkiewicz, Eryk Shin, Oh-Soon Soongsil Univ Sch Elect Engn Seoul 06978 South Korea Soongsil Univ Dept ICMC Convergence Technol Seoul 06978 South Korea Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Mem Univ Fac Engn & Appl Sci St John NF A1C 5S7 Canada Univ Technol Sydney Fac Engn & Informat Technol Sydney NSW 2007 Australia

This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD) to improve both spectral efficiency (SE) and user fairness. In such a scenario, NOMA based on the successive interference cancellation technique is simultaneously applied to both uplink (UL) and downlink (DL) transmissions in an FD system. We consider the problem of jointly optimizing user association (UA) and power control to maximize the overall SE, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize UL users' decoding order and DL users' clustering, which results in a mixed-integer non-convex problem. For practically appealing applications, we first relax the binary variables and then propose two low-complexity designs. In the first design, the continuous relaxation problem is solved using the inner convex approximation framework. Next, we additionally introduce the penalty method to further accelerate the performance of the former design. For a benchmark, we develop an optimal solution based on brute-force search (BFS) over all possible cases of UAs. It is demonstrated in numerical results that the proposed algorithms outperform the conventional FD-based schemes and its half-duplex counterpart, as well as yield data rates close to those obtained by BFS-based algorithm.

关键词： Full-duplex radios non-convex programming non-orthogonal multiple access self-interference spectral efficiency successive interference cancellation user clustering

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Privacy Preservation via Beamforming for NOMA

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第7期18卷 3599-3612页

作者： Cao, Yang Zhao, Nan Chen, Yunfei Jin, Minglu Fan, Lisheng Ding, Zhiguo Yu, F. Richard Dalian Univ Technol Sch Informat & Commun Engn Dalian 116024 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Shaanxi Peoples R China Univ Warwick Sch Engn Coventry CV4 7AL W Midlands England Guangzhou Univ Sch Comp Sci & Educ Software Guangzhou 510006 Guangdong Peoples R China Univ Manchester Sch Elect & Elect Engn Manchester M13 9PL Lancs England Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada

non-orthogonal multiple access (NOMA) has been proposed as a promising multiple access approach for 5G mobile systems because of its superior spectrum efficiency. However, the privacy between the NOMA users may be compromised due to the transmission of a superposition of all users' signals to successive interference cancellation (SIC) receivers. In this paper, we propose two schemes based on beamforming optimization for NOMA that can enhance the security of a specific private user while guaranteeing the other users' quality of service (QoS). Specifically, in the first scheme, when the transmit antennas are inadequate, we intend to maximize the secrecy rate of the private user, under the constraint that the other users' QoS is satisfied. In the second scheme, the private user's signal is zero-forced at the other users when redundant antennas are available. In this case, the transmission rate of the private user is also maximized while satisfying the QoS of the other users. Due to the non-convexity of optimization in these two schemes, we first convert them into convex forms, and then, an iterative algorithm based on the Concave-convex Procedure is proposed to obtain their solutions. The extensive simulation results are presented to evaluate the effectiveness of the proposed schemes.

关键词： non-orthogonal multiple access physical layer security beamforming optimization privacy protection non-convex programming zero-forcing

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Sequential convex programming for nonlinear optimal control problems in UAV path planning

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AEROSPACE SCIENCE AND TECHNOLOGY 2018年第May期76卷 280-290页

作者： Zhang, Zhe Li, Jianxun Wang, Jun Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Dept Automat 800 Dong Chuan Rd Shanghai Peoples R China Luoyang Elect Equipment Test Ctr China Luoyang Peoples R China

Usually, an UAV (Unmanned Aerial Vehicle) path planning problem can be modeled as a nonlinear optimal control problem with non-convex constraints in practical applications. However, it is quite difficult to obtain stable solutions quickly for this kind of non-convex optimization with certain convergence and optimality. In this paper, an algorithm is proposed to solve the problem through approximating the non-convex parts by a series of sequential convex programming problems. Under mild conditions, the sequence generated by the proposed algorithm is globally convergent to a KKT (Karush-Kuhn-Tucker) point of the original nonlinear problem, which is verified by a rigorous theoretical proof. Compared with other methods, the convergence and effectiveness of the proposed algorithm is demonstrated by trajectory planning applications. (C) 2018 Elsevier Masson SAS. All rights reserved.

关键词： UAV path planning Sequential convex programming nonlinear optimal control Globally convergent algorithm non-convex programming

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A Novel Spectral-Efficient Resource Allocation Approach for NOMA-Based Full-Duplex Systems

A Novel Spectral-Efficient Resource Allocation Approach for ...

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IEEE Global Communications Conference (IEEE GLOBECOM)

作者： Nguyen, Hieu V. Nguyen, Van-Dinh Dobre, Octavia A. Nguyen, Diep N. Dutkiewicz, Eryk Shin, Oh-Soon Soongsil Univ Sch Elect Engn Seoul South Korea Soongsil Univ Dept ICMC Convergence Technol Seoul South Korea Mem Univ Fac Engn & Appl Sci St John NF Canada Univ Technol Sydney Fac Engn & Informat Technol Sydney NSW 2007 Australia

ISBN: (纸本)9781728109626

This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD), where the NOMA successive interference cancellation technique is applied simultaneously to both uplink (UL) and downlink (DL) transmissions in the same time-frequency resource block. Specifically, we jointly optimize the user association (UA) and power control to maximize the overall sum rate, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize the UL users' decoding order and the DL users' clustering, which results in a mixed-integer non-convex problem. For solving this problem, we first relax the binary variables to be continuous, and then propose a low-complexity design based on the combination of the inner convex approximation framework and the penalty method. Numerical results show that the proposed algorithm significantly outperforms the conventional FD-based schemes, FD-NOMA and its half-duplex counterpart with random UA.

关键词： Full-duplex radios non-convex programming non-orthogonal multiple access self-interference spectral efficiency successive interference cancellation user clustering

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A JPEG Decompression Technique based on Compressed Sensing

A JPEG Decompression Technique based on Compressed Sensing

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International Workshop on Advanced Image Technology (IWAIT)

作者： Tsutake, Chihiro Yamada, Ryoya Yoshida, Toshiyuki Univ Fukui Dept Informat Sci Fukui 9108507 Japan

ISBN: (数字)9781510627741

ISBN: (纸本)9781510627741

Total-variation-minimization-based JPEG decompression is recognized as a promising technique for providing artifact-free images. Such a technique is typically accomplished in solving an optimization problem based on iterative methods. However, conventional decompression techniques sometimes exhibit over-smoothed regions in decompressed images by increasing iteration count. As a result, users are confused since an optimal iteration number is unknown for an arbitrarily given JPEG bitstream. To overcome the difficulty, we propose a new iterative JPEG decompression technique that combines a total variation minimization strategy with the so-called compressed sensing. In contrast to existing approaches, our technique always provides optimal decompression results, despite increasing iteration count. The experimental results indicate that the proposed technique is advantageous over conventional ones.

关键词： JPEG decompression total variation minimization compressed sensing non-convex programming proximity operator primal-dual splitting method

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Pricing and revenue maximization over a multicommodity transportation network: the nonlinear demand case

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2018年第3期71卷 641-671页

作者： Kuiteing, Aime Kamgaing Marcotte, Patrice Savard, Gilles Ecole Polytech Montreal Dept Math & Ind Engn Montreal PQ Canada Univ Montreal Dept Comp Sci & Operat Res Montreal PQ Canada

This paper is concerned with the design of efficient exact and heuristic algorithms for addressing a bilevel network pricing problem where demand is a nonlinear function of travel cost. The exact method is based on the piecewise linear approximation of the demand function, yielding mixed integer programming formulations, while heuristic procedures are developed within a bilevel trust region framework.

关键词： Pricing Bilevel programming Elastic demand Networks non-convex programming Mixed integer programming

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Globally convergent homotopy algorithm for solving the KKT systems to the principal-agent bilevel programming

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OPTIMIZATION METHODS & SOFTWARE 2017年第1期32卷 69-85页

作者： Zhu, Zhichuan Yu, Bo Northeast Normal Univ Sch Math & Stat Changchun 130024 Jilin Peoples R China Jilin Univ Finance & Econ Fac Stat Changchun 130117 Jilin Peoples R China Dalian Univ Technol Sch Math Sci Dalian 116024 Liaoning Peoples R China

In this paper, a constraint set swelling homotopy (CSSH) algorithm for solving the single-level non-convex programming problem with designing piecewise linear contractual function which is equivalent to the principal-agent model with integral operator is proposed, and the existence and global convergence is proven under some mild conditions. As a comparison, a piecewise constant contract is also designed for solving the single-level non-convex programming problem with the corresponding discrete distributions. And some numerical tests are done by the proposed homotopy algorithm as well as by using fmincon in Matlab, LOQO and MINOS. The numerical results show that the CSSH algorithm is robust, feasible and effective.

关键词： principal-agent model homotopy algorithm bilevel programming non-convex programming

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Energy-Efficient Beamforming for Massive MIMO with Inter-Cell Interference and Inaccurate CSI

Energy-Efficient Beamforming for Massive MIMO with Inter-Cel...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Zhang, Shuai Liu, Lu Cheng, Yu Cao, Xianghui Cai, Lin IIT Dept Elect & Comp Engn Chicago IL 60616 USA Southeast Univ Sch Automat Nanjing 210018 Jiangsu Peoples R China

ISBN: (纸本)9781538636527

Massive MIMO is one of the important technologies for the 5G cellular communications. It boasts to greatly increase the spectrum efficiency through aggressive spatial multiplexing, consuming a much lower antenna power. However, fully exploiting the capability of Massive MIMO requires accurate channel state information (CSI) at base stations (BSs). Obtaining accurate CSI is quite challenging in a heterogeneous networking context or a fast-changing urban environment;the limited supply of pilot signal versus increased number of users also contributes to the errors in channel state estimation. Another challenge in massive MIMO is that most of the existing precoding algorithms for interference mitigation consider only intra-cell interference, but overlook the impact of inter-cell interference. In this paper we propose a beamforming scheme accounting for both issues - CSI error and inter-cell interference, with the objective of maximizing system energy efficiency. This problem has many coupling non-convex constraints and is intractable to solve directly. We investigate the use of a sequential convex approximation (SCA) algorithm. It solves a series of approximated convex sub-problems, and provably arrives at a stationary solution to the original problem. Compared with the commonly used but oversimplified semi-definite relaxation, numerical results demonstrate that SCA algorithm can guarantee solution feasibility with robust performance, at the cost of moderately increased computation complexity.

关键词： Massive MIMO 5G beamforming power allocation non-convex programming approximation algorithm

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