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Outage, Capacity, and Error Performance of Downlink RSMA-based systems: Analysis and Resource Optimization

IEEE Transactions on Communications 2025年

作者： Vu, Thai-Hoc Da Costa, Daniel Benevides Kim, Sunghwan Pham, Quoc-Viet University of Ulsan Department of Electrical Electronic and Computer Engineering Ulsan Korea Republic of Interdisciplinary Research Center for Communication Systems and Sensing Department of Electrical Engineering Dhahran31261 Saudi Arabia Kyonggi University School of Electronic Engineering Kyonggi Korea Republic of University of Dublin School of Computer Science and Statistics Trinity College Dublin Dublin 2 D02PN40 Ireland

This paper comprehensively investigates the performance of downlink multi-user rate-splitting multiple access (RSMA) networks under Nakagami-m fading channels. We first develop the mathematical outage probability (OP) and ergodic capacity (EC) frameworks, deriving exact expressions for both, along with asymptotic analysis in high signal-to-noise ratio (SNR) and low-rate regions, which serve as the foundation for deducing the approximate and maximal energy-reliability and energy-spectral formulas. To enhance system performance, we tackle the non-convex problems of jointly optimizing common and private power allocation (PA) coefficients to minimize the maximal OP performance. Moreover, we also delve into optimizing PA coefficients and rate-splitting factors concurrently to maximize the ergodic sum capacity (ESC). Addressing the influence of modulation schemes on user error rates, we introduce mathematical frameworks for symbol error rate (SER) considering four combined modulation schemes based on binary phase-shift keying (BPSK) and quadrature-phase shift keying (QPSK), the whole cases are quantified in terms of exact and asymptotic manners. Furthermore, we present a straightforward approach to optimize the PA coefficients to minimize the maximal SER performance. Finally, Monte-Carlo simulations are presented to validate our developed frameworks and optimization solutions. © 1972-2012 IEEE.

关键词： Signal to noise ratio

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A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization

arXiv

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arXiv 2023年

作者： He, Chuan Huang, Heng Lu, Zhaosong Department of Mathematics Linköping University Sweden Department of Computer Science University of Maryland United States Department of Industrial and Systems Engineering University of Minnesota United States

In this paper we consider finding an approximate second-order stationary point (SOSP) of general nonconvex conic optimization that minimizes a twice differentiable function subject to nonlinear equality constraints and also a convex conic constraint. In particular, we propose a Newton-conjugate gradient (Newton-CG) based barrier-augmented Lagrangian method for finding an approximate SOSP of this problem. Under some mild assumptions, we show that our method enjoys a total inner iteration complexity of Oe (ϵ−11/2) and an operation complexity of Oe (ϵ−11/2 min{n, ϵ−5/4}) for finding an (ϵ, √ϵ)-SOSP of general nonconvex conic optimization with high probability. Moreover, under a constraint qualification, these complexity bounds are improved to Oe (ϵ−7/2) and Oe (ϵ−7/2 min{n, ϵ−3/4}), respectively. To the best of our knowledge, this is the first study on the complexity of finding an approximate SOSP of general nonconvex conic optimization. Preliminary numerical results are presented to demonstrate superiority of the proposed method over first-order methods in terms of solution *** Codes 49M05, 49M15, 68Q25, 90C26, 90C30, 90C60 Copyright © 2023, The Authors. All rights reserved.

关键词： Lagrange multipliers

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Newton-CG methods for nonconvex unconstrained optimization with Hölder continuous Hessian

arXiv

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arXiv 2023年

In this paper we consider a nonconvex unconstrained optimization problem minimizing a twice differentiable objective function with Hölder continuous Hessian. Specifically, we first propose a Newton-conjugate gradient (Newton-CG) method for finding an approximate first- and second-order stationary point of this problem, assuming the associated the Hölder parameters are explicitly known. Then we develop a parameter-free Newton-CG method without requiring any prior knowledge of these parameters. To the best of our knowledge, this method is the first parameter-free second-order method achieving the best-known iteration and operation complexity for finding an approximate first- and second-order stationary point of this problem. Finally, we present preliminary numerical results to demonstrate the superior practical performance of our parameter-free Newton-CG method over a well-known regularized Newton method. © 2023, CC BY.

关键词： Newton-Raphson method

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Co-Design of Resource Limited Genetic Modules

Co-Design of Resource Limited Genetic Modules

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IEEE Conference on Decision and Control

作者： Carlos Eduardo Celeste Junior Ilaria Di Loreto Theodore Wu Grunberg Maria Domenica Di Benedetto Alessandro Borri Domitilla Del Vecchio Department of Mechanical Engineering Department of Electrical and Information Engineering Palazzo Camponeschi University of L'Aquila L'Aquila Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Institute for Systems Analysis and Computer Science “A. Ruberti” National Research Council of Italy Rome Italy

Modular composition of systems through defined input/output interfaces is a wide-spread engineering approach that allows to make the design of complicated systems tractable. Although this approach has percolated to the design of synthetic genetic circuits, it has proved challenging to obtain predictable design outcomes. In particular, context-dependence due to sharing a limited pool of cellular resources is a major factor that confounds modular composition of genetic modules. Here, we propose the use of a systems framework in which resource sharing among different subsystems is explicitly modeled through disturbance inputs and outputs. Within this system description, resource sharing results in undesired connectivity among subsystems, which is explicitly accounted for in design. Accordingly, we propose to use this system framework to co-design stable systems, with constant input, based on steady state specifications that each subsystem should satisfy. To this end, we provide sufficient conditions on the system parameters such that the output of each subsystem in the network remains in a small interval around a desired value, as well as an algorithmic procedure to compute the feasible region for these parameters. In general, this framework can be used to design subsystems to satisfy a specification, while explicitly accounting for context-dependence.

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Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

引用

computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed Mustufa Haider Abidi Abdulrahman Al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： Automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

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Forecasting of Photovoltaic Power with ARO based AI approach

Forecasting of Photovoltaic Power with ARO based AI approach

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Distributed Computing and Optimization Techniques (ICDCOT), International Conference on

作者： Mounika Nallur B M Nalini Zabiha Khan S Nayana Prasad N Achyutha G Manjula Masters in Computer Information Systems Murray State University USA Department of Computer Science and Engineering East West Institute of Technology Bengaluru India Department of Artificial Intelligence and Machine Learning Nitte Meenakshi Institute of Technology Bengaluru India Department of CSE BGS College of Engineering and Technology Bangalore India

Renewable power from sunlight can power the future smart grid with massive amounts of electricity. systems struggle with solar energy's unpredictability and intermittent nature. Unpredictability of solar electricity hinders smart grid optimization and planning. Photovoltaic (PV) power generation must be accurately estimated to reduce power interruptions. PV power must be accurately predicted to avoid grid disturbances from PV facilities. Thus, we describe a transfer learning and AlexNet-based CNN architecture for short-term power forecasting. Past power, solar radiation, wind speed, and temperature readings determine the input. AlexNet's hyper-parameters are optimized using the artificial rabbit method. By adding selective opposition to ARO, local solution tracking efficiency is improved. CNN input features are created from all input parameters as 2D feature maps. After analyzing real PV data from Limberg, Belgium, the math shows that PV systems work.

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Exploring the Frontiers of Firmware Fuzzing: μAFL’s Application on Cortex M4 and Unix Programs

Exploring the Frontiers of Firmware Fuzzing: μAFL’s Applic...

引用

International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Safayat Bin Hakim Muhammad Adil Jordi Mongay Batalla Constandinos X. Mavromoustakis Houbing Herbert Song Department of Information Systems University of Maryland Baltimore County Baltimore MD USA Computer Science and Engineering The State University of New York at Buffalo Buffalo NY USA Institute of Telecommunications Electronics and Information Technology Warsaw University of Technology Warsaw Poland Department of Computer Science School of Sciences and Engineering University of Nicosia Nicosia Cyprus

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

The aim of this study is to investigate into $\mu \mathrm{AFL}$, a non-intrusive, feedback-driven fuzzing framework, evaluated on Cortex M4 embedded systems and Unix platforms, focusing on the STM32F407VE Cortex M4 microcontroller. By leveraging the SEGGER J-Trace Pro for trace collection, it demonstrates $\mu$AFL’s utility beyond its traditional scope, showcasing its efficacy in both embedded and general-purpose computing environments. Our analysis, enriched by juxtaposing $\mu$AFL’s capabilities with traditional AFL, emphasizes the adaptability and effectiveness of fuzzing methodologies in firmware security enhancement. Furthermore, the study provides a deep understanding of fuzzing execution on different hardware, presenting an execution strategy for the STM32F407VE that highlights the framework’s potential in identifying vulnerabilities, evidenced by tests on specific firmware programs such as an LED blinking program integrated with semihosting breakpoints and ETM tracing. The use of uninitialized memory sections and strategically placed break-points offers significant insights into the firmware’s execution flow. The results of our comparative analysis clearly show that $\mu \mathrm{AFL}$ excels at uncovering vulnerabilities, reinforcing the need for evolving fuzzing methodologies to build stronger security systems for embedded devices. This contribution underscores the importance of refining fuzzing techniques to meet the intricate security demands of contemporary computing environments.

关键词： Wireless communication Macrocell networks Embedded systems Microcontrollers Refining Fuzzing Hardware

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Taming "data-hungry" reinforcement learning? stability in continuous state-action spaces 24

Taming "data-hungry" reinforcement learning? stability in co...

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Proceedings of the 38th International Conference on Neural Information Processing systems

作者： Yaqi Duan Martin J. Wainwright Department of Technology Operations and Statistics Stern School of Business New York University New York NY Laboratory for Information and Decision Systems Statistics and Data Science Center and Department of Electrical Engineering and Computer Science and Department of Mathematics Massachusetts Institute of Technology Cambridge MA

ISBN: (纸本)9798331314385

We introduce a novel framework for analyzing reinforcement learning (RL) in continuous state-action spaces, and use it to prove fast rates of convergence in both off-line and on-line settings. Our analysis highlights two key stability properties, relating to how changes in value functions and/or policies affect the Bellman operator and occupation measures. We argue that these properties are satisfied in many continuous state-action Markov decision processes. Our analysis also offers fresh perspectives on the roles of pessimism and optimism in off-line and on-line RL.

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FedAccess: Federated Learning-Based Built Surface Recognition for Wheelchair Routing

FedAccess: Federated Learning-Based Built Surface Recognitio...

引用

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Rochishnu Banerjee Ethan Han Longze Li Haoxiang Yu Md Osman Gani Vaskar Raychoudhury Roger O. Smith Department of Computer Science & Software Engineering Miami University Oxford OH USA Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA Department of Information Systems University of Maryland Baltimore County Baltimore MD USA Department of Rehabilitation Sciences & Technology University of Wisconsin Milwaukee WI USA

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Wheelchair and mobility aid users often face challenges in navigating the built environment due to uneven sidewalks, temporary barriers, steep inclines, and narrow lanes. To assist these users, accessible routing systems have been introduced that generate wheelchair-accessible paths to facilitate navigation in unfamiliar environments. In general, accessible routing systems rely on surface and path characteristics like surface type, incline, width, etc., and crowd-sourced information about barriers to provide the optimal route. Emerging routing systems even provide personalized routing to users that are catered to the user's specific needs and requirements. However, these types of systems collect crowd-sourced personal/identifiable information which introduces privacy and data heterogeneity concerns that are not addressed by them or elsewhere in the concerned domain. To address these two issues specifically, we propose the novel FedAccess system for accessible routing that utilizes the federated learning paradigm for surface recognition using vibration data. The surface-induced vibrations are captured through smartphone-embedded motion sensors (accelerometers and gyroscopes) from 23 manual wheelchair users during their regular navigation. We have covered 10 distinct surfaces from the USA. As a result, the distribution of the data is naturally non-IID. Empirical evaluation shows that the FedAccess system can protect user data and identity while dealing with non-IID data and still recognize heterogeneous surfaces with higher accuracy than the state-of-the-art.

关键词： Vibrations Navigation Federated learning Wheelchairs Face recognition Manuals Routing

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Assessing the Effects of Blackhole Attacks on MANET Reliability and Security

Assessing the Effects of Blackhole Attacks on MANET Reliabil...

引用

Decision Aid sciences and Application (DASA), International Conference on

作者： Amjed Abbas Ahmed Saif Aamer Fadhil Ali Hamza Najim Khattab M. Ali Alheeti Nurhizam Safie Mohd Satar Aisha Hassan Abdallah Hashim Faculty of Information Science and Technology Center for Cyber Security Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Imam AlKadhum College (IKC) Baghdad Iraq Department of Computer Technical Engineering Imam Al-Kadhum College (IKC) Baghdad Iraq Computer Networking Systems Department College of Computer and Information Technology University of Anbar Anbar Iraq Faculty of Information Science and Technology Center for Cyber Security Universiti Kebangsaan Malaysia (UKM) Bangi Malaysia Department of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Selangor Malaysia

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

Mobile Ad Hoc Networks (MANETs) are characterized by some important attributes, including infrastructure, mobile, and dynamic nature, which makes them have vast applications in different areas of computer networks. The black hole attack falls among the strongly criticized security threats within the framework of the MANETs. This deceptive behavior captures data packets from a source destined for the malicious node and then declines them when they are received. This paper comprehensively reviews prior studies done to analyze and mitigate black hole attacks in MANETs. Besides this, we will conduct a comparative analysis of the research above projects. The present paper extends prior work by actually performing the black hole assault simulations in a MANETs environment. This is done with the aid of the NS2 simulator and the Ad Hoc On-Demands Distance Vector (AODV) routing protocol. In this study, the black hole attack is analyzed and the consequences of the attack are assessed in terms of the system performance and security. We analyze crucial parameters like end-to-end latency, PDR, packet drop, and throughput to evaluate the consequences of this assault. From our results derived from the analysis of our simulations, we aim to present substantial points to do with the impacts of blackhole attacks on MANETs. In this way, our goal is to participate in the perpetually evolving efforts aimed at enhancing the security and reliability of such dynamic networks.

关键词： computer network reliability Collaboration Throughput Ad hoc networks Vectors Security Reliability Mobile computing AODV Mobile ad hoc networks

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