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Massive Access in Secure NOMA Under Imperfect CSI: Security Guaranteed Sum-Rate Maximization With first-order algorithm

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2021年第4期39卷 998-1014页

作者： Li, Zongze Xia, Minghua Wen, Miaowen Wu, Yik-Chung Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai 519082 Peoples R China South China Univ Technol Sch Elect & Informat Engn Guangzhou 510640 Peoples R China

Non-orthogonal multiple access (NOMA) is a promising solution for secure transmission under massive access. However, in addition to the uncertain channel state information (CSI) of the eavesdroppers due to their passive nature, the CSI of the legitimate users may also be imperfect at the base station due to the limited feedback. Under both channel uncertainties, the optimal power allocation and transmission rate design for a secure NOMA scheme is currently not known due to the difficulty of handling the probabilistic constraints. This article fills this gap by proposing novel transformation of the probabilistic constraints and variable decoupling so that the security guaranteed sum-rate maximization problem can be solved by alternatively executing branch-and-bound method and difference of convex programming. To scale the solution to a truly massive access scenario, a first-order algorithm with very low complexity is further proposed. Simulation results show that the proposed first-order algorithm achieves identical performance to the conventional method but saves at least two orders of magnitude in computation time. Moreover, the resultant transmission scheme significantly improves the security guaranteed sum-rate compared to the orthogonal multiple access transmission and NOMA ignoring CSI uncertainty.

关键词： NOMA Interference Security Probabilistic logic Uncertainty Simulation Power system reliability first-order algorithm limited feedback massive access non-orthogonal multiple access outage probability physical layer security

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Energy-Efficient Precoding for Non-Orthogonal Multicast and Unicast Transmission via first-order algorithm

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第9期18卷 4590-4604页

作者： Li, Yang Xia, Minghua Wu, Yik-Chung Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Guangdong Peoples R China

As the demand for supporting hybrid multicast and unicast services is rapidly increasing, a non-orthogonal multiplexing transmission scheme called layered-division multiplexing (LDM) has been recognized as an effective way to provide high spectrum efficiency (SE). However, high SE is not necessarily equivalent to high energy efficiency (EE). In fact, it is still unclear how much benefit LDM would provide for hybrid multicast and unicast services under EE maximization, which belongs to the more challenging class of fractional programs. To fill this gap, we formulate the problem of energy-efficient preceding design for the LDM-based multi-user multi-input-multi-output downlink system, under both multicast and unicast multi-stream data rate constraints of each user. Although the problem is nonsmooth and nonconvex, we propose a first-order algorithm for finding both the initial point and the final solution. Since the proposed first-order algorithm involves only gradient information, it achieves very low complexity. The simulation results demonstrate that, compared with the orthogonal transmission schemes, the LDM transmission under the proposed preceding can provide a much higher EE. Moreover, the proposed first-order algorithm achieves the same EE as that of a second-order based approach, but requires much shorter computation time.

关键词： Energy-efficient preceding first-order algorithm layered-division multiplexing (LDM) multi-stream data rate constraints non-orthogonal multicast and unicast transmission

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Accelerated first-order Continuous-Time algorithm for Solving Convex-Concave Bilinear Saddle Point Problem 21st

Accelerated First-Order Continuous-Time Algorithm for Solvin...

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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Zeng, Xianlin Dou, Lihua Chen, Jie Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Key Lab Biomimet Robots Arid Syst Minist Educ Beijing Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Dept Control Sci & Engn Shanghai Peoples R China

first-order methods have simple structures and are of great importance to big data problems because first-order methods are easy to implement in a distributed or parallel way. However, in the worst cases, first-order methods often converge at a rate O(1/t), which is slow. This paper considers a class of convex-concave bilinear saddle point problems and proposes an accelerated first-order continuous-time algorithm. We design the accelerated algorithm by using both increasing and decreasing damping coefficients in the saddle point dynamics. If parameters of the proposed algorithm are proper, the algorithm owns O(1/t(2)) convergence without any strict or strong convexity requirement. Finally, we apply the algorithm to numerical examples to show the superior performance of the proposed algorithm over existing ones. Copyright (C) 2020 The Authors.

关键词： Accelerated method first-order algorithm continuous-time algorithm saddle-point problem

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Activity Detection for Massive Connectivity Under Frequency Offsets via first-order algorithms

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第3期18卷 1988-2002页

作者： Li, Yang Xia, Minghua Wu, Yik-Chung Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Guangdong Peoples R China

Activity detection in machine-type communication (MTC) has been recognized as an effective way to support massive connectivity of the Internet-of-Things (IoT) devices. However, due to the sporadic traffic pattern of the MTC, only a small portion of the massive potential devices are active, making the activity detection a challenging large-scale sparsity-constrained problem. On the other hand, since the low-cost IoT devices are commonly equipped with cheap crystal oscillators, the resulting frequency offsets would intensify the multi-user interference during the activity detection and invalidate existing detection methods that are designed under ideal frequency synchronization. To fill this gap, this paper proposes two methods for activity detection under unknown frequency offsets: a Lasso-based method and a sparsity-constrained method. Both the methods are first-order algorithms, making them suitable for large-scale IoT systems. Furthermore, the sparsity-constrained method can be executed in parallel and is proved to converge to a set of critical points. The simulation results show that both the proposed methods achieve much better detection performance than a two-stage approach that separately performs frequency synchronization and activity detection. Moreover, the proposed sparsity-constrained method is shown to perform better than two competing algorithms exploiting hierarchical sparsity.

关键词： first-order algorithm frequency offset Internet-of-Things (IoT) machine-type communication (MTC) massive connectivity nonsmooth optimization

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Secure Multicast Energy-Efficiency Maximization With Massive RISs and Uncertain CSI: first-order algorithms and Convergence Analysis

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第9期21卷 6818-6833页

作者： Li, Zongze Wang, Shuai Wen, Miaowen Wu, Yik-Chung Peng Cheng Lab Shenzhen 518038 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol SIAT Shenzhen 518055 Peoples R China South China Univ Technol Sch Elect & Informat Engn Guangzhou 510640 Peoples R China Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

Reconfigurable intelligent surface (RIS) has the potential to significantly enhance the network secure transmission performance by reconfiguring the wireless propagation environment. However, due to the passive nature of eavesdroppers and the cascaded channel brought by the RIS, the eavesdroppers' channel state information is imperfect at the base station. Under channel uncertainty, the optimal phase-shift, power allocation, and transmission rate design for massive antennas and reflecting elements secure transmission are challenging to solve due to the outage probabilistic constraint with coupled variables. To fill this gap, this paper formulates a problem of energy-efficient secure transmission design with the probabilistic outage constraint. By leveraging the exponential distribution property of the received signal power, the stochastic resource allocation is equivalently transformed into a deterministic one, and the secure energy efficiency maximization problem can be iteratively solved via low complexity first-order algorithms under the alternating maximization (AM) framework. However, due to the nonsmooth problem, the convergence of the objective function value and nature of the converged solution under AM iteration are uncertain. Therefore, the convergence properties with respect to the objective function value and sequence of solutions are further established. Simulation results corroborate the convergence results of the first-order algorithms and show that the proposed algorithm achieves identical performance to the conventional method but saves at least two orders of magnitude in computation time. Moreover, the resultant RIS aided secure transmission significantly improves the energy efficiency compared to baseline schemes of random phase-shift, fixed phase-shift, and RIS ignoring CSI uncertainty.

关键词： Probabilistic logic Wireless communication Convergence Linear programming Receivers Optimization Resource management Alternating maximization energy efficiency first-order algorithm outage probability physical layer security reconfigurable intelligent surface

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Caching at Base Stations With Multi-Cluster Multicast Wireless Backhaul via Accelerated first-order algorithms

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2020年第5期19卷 2920-2933页

作者： Li, Yang Xia, Minghua Wu, Yik-Chung Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai 519082 Peoples R China

Cloud radio access network (C-RAN) has been recognized as a promising architecture for next-generation wireless systems to support the rapidly increasing demand for higher data rate. However, the performance of C-RAN is limited by the backhaul capacities, especially for the wireless deployment. While C-RAN with fixed BS caching has been demonstrated to reduce backhaul consumption, it is more challenging to further optimize the cache allocation at BSs with multi-cluster multicast backhaul, where the inter-cluster interference induces additional non-convexity to the cache optimization problem. Despite the challenges, we propose an accelerated first-order algorithm, which achieves much higher content downloading sum-rate than a second-order algorithm running for the same amount of time. Simulation results demonstrate that, by simultaneously delivering the required contents to different multicast clusters, the proposed algorithm achieves significantly higher downloading sum-rate than those of time-division single-cluster transmission schemes. Moreover, it is found that the proposed algorithm allocates larger cache sizes to the farther BSs within the nearer clusters, which provides insight to the superiority of the proposed cache allocation.

关键词： Caching cloud radio access network (C-RAN) first-order algorithm large-scale nonsmooth nonconvex optimization multi-cluster multicast beamforming (MCMB) wireless backhaul

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Performance of first-order algorithms for TV Penalized Weighted Least-Squares Denoising Problem

Performance of First-Order Algorithms for TV Penalized Weigh...

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6th International Conference on Image and Signal Processing (ICISP)

作者： Sawatzky, Alex Univ Munster Inst Computat & Appl Math D-48149 Munster Germany

ISBN: (纸本)9783319079981;9783319079974

Denoising of images perturbed by non-standard noise models (e. g., Poisson or Gamma noise) can be often realized by a sequence of penalized weighted least-squares minimization problems. In the recent past, a variety of first-order algorithms have been proposed for convex problems but their efficiency is usually tested with the classical least-squares data fidelity term. Thus, in this manuscript, first-order state-of-the-art computational schemes are applied on a total variation penalized weighted least-squares denoising problem and their performance is evaluated on numerical examples simulating a Poisson noise perturbation.

关键词： Image denoising weighted least-squares total variation first-order algorithm primal-dual algorithm alternating direction method of multipliers Chambolle-Pock

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Accelerated first-order Continuous-Time algorithm for Solving Convex-Concave Bilinear Saddle Point Problem

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IFAC-PapersOnLine 2020年第2期53卷 7362-7367页

作者： Xianlin Zeng Lihua Dou Jie Chen Key Laboratory of Biomimetic Robots and Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Department of Control Science and Engineering Tongji University the Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China

first-order methods have simple structures and are of great importance to big data problems because first-order methods are easy to implement in a distributed or parallel way. However, in the worst cases, first-order methods often converge at a rate O(1/t), which is slow. This paper considers a class of convex-concave bilinear saddle point problems and proposes an accelerated first-order continuous-time algorithm. We design the accelerated algorithm by using both increasing and decreasing damping coefficients in the saddle point dynamics. If parameters of the proposed algorithm are proper, the algorithm owns O(1/ t 2 ) convergence without any strict or strong convexity requirement. Finally, we apply the algorithm to numerical examples to show the superior performance of the proposed algorithm over existing ones.

关键词： Accelerated method first-order algorithm continuous-time algorithm saddle-point problem

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Energy-Efficient Non-Orthogonal Multicast and Unicast Transmission of Cell-Free Massive MIMO Systems With SWIPT

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2021年第4期39卷 949-968页

作者： Tan, Fangqing Wu, Peiran Wu, Yik-Chung Xia, Minghua Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou 510006 Peoples R China Guilin Univ Elect Technol Key Lab Cognit Radio & Informat Proc Guilin 541004 Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai 519082 Peoples R China Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

This work investigates the energy-efficient resource allocation for layered-division multiplexing (LDM) based non-orthogonal multicast and unicast transmission in cell-free massive multiple-input multiple-output (MIMO) systems, where each user equipment (UE) performs wireless information and power transfer simultaneously. To begin with, the achievable data rates for multicast and unicast services are derived in closed form, as well as the received radio frequency (RF) power at each UE. Based on the analytical results, a nonsmooth and nonconvex optimization problem for energy efficiency (EE) maximization is formulated, which is however a challenging fractional programming problem with complex constraints. To suit the massive access setting, a first-order algorithm is developed to find both initial feasible point and the nearly optimal solution. Moreover, an accelerated algorithm is designed to improve the convergence speed. Numerical results demonstrate that the proposed first-order algorithms can achieve almost the same EE as that of second-order approaches yet with much lower computational complexity, which provides insight into the superiority of the proposed algorithms for massive access in cell-free massive MIMO systems.

关键词： Unicast MIMO communication Array signal processing Wireless networks Antennas NOMA Multiplexing Cell-free massive multiple-input multiple-output energy efficiency first-order algorithm layered-division multiplexing non-orthogonal multicast and unicast transmission

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Globally and superlinearly convergent algorithm for minimizing a normal merit function

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SIAM JOURNAL ON CONTROL AND OPTIMIZATION 1998年第3期36卷 1005-1019页

作者： Polak, E Qi, LQ Univ Calif Berkeley Dept Elect Engn Berkeley CA 94720 USA Univ New S Wales Sch Math Sydney NSW 2052 Australia

In this paper we present two new concepts related to the solution of systems of nonsmooth equations (NE) and variational inequalities (VI). The first concept is that of a normal merit function, which summarizes the simple basic properties shared by various known merit functions. In general, normal merit functions are locally Lipschitz, but not differentiable. The second concept is that of a Newtonian operator, whose values generalize the concept of the Hessian for normal merit functions. These two concepts are then used to generalize the nonsmooth Newton method for solving the equation del f(x) = 0, where f is a normal merit function with f is an element of C-1, to the case where f is only locally Lipschitz and the set-valued inclusion 0 is an element of partial derivative f(x) needs to be solved. Combining the resulting generalized Newton method with certain first-order methods, we obtain a globally and superlinearly convergent algorithm for minimizing normal merit functions.

关键词： normal merit function generalized Newton method first-order algorithm global convergence superlinear convergence

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