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An Enhanced Aquila-Based Resource Allocation for Efficient Indoor IoT Visible Light Communication

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An Enhanced Aquila-Based Resource Allocation for Efficient I...

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Selma Yahia Yassine Meraihi Sylia Mekhmoukh Taleb Seyedali Mirjalili Amar Ramdane-Cherif Tu Dac Ho Hossien B. Eldeeb Sami Muhaidat LIST Laboratory University of M’Hamed Bougara Boumerdes Boumerdes Algeria Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Brisbane Australia LISV Laboratory University of Versailles St-Quentin-en-Yvelines Velizy France Department of Electrical Engineering Faculty of Engineering Science and Technology UiT Arctic University of Norway Electrical Engineering Computer Science Center of Cyber-Physical Systems Khalifa University UAE

Visible light communication (VLC) is a rapidly growing wireless communication technology for the Internet of Things (IoT) that offers high data rates and low latency, making it ideal for massive connectivity. Efficient resource allocation is essential in VLC networks to minimize inter-symbol and cochannel interferences, which can greatly improve network performance and user satisfaction. This paper focuses on an indoor IoT-based VLC system that utilizes photodetectors (PDs) on users’ cell phones as receivers, with the goal of maximizing system performances and reducing power consumption by selectively activating some PDs while deactivating others. However, this objective presents a challenge due to the inherent non-convex nature of the multi-objective optimization problem, which cannot be solved by analytical means. To address this, we propose an enhanced Aquila optimization (EAO) scheme that improves upon the Aquila Optimizer (AO) by incorporating a fitness distance balance (FDB) function. We evaluate our proposed EAO in various scenarios under different settings, considering both capacity and fairness metrics. Through simulations, we demonstrate the effectiveness of our approach and its superiority over classical algorithms such as Aquila Optimizer (AO), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) in finding the optimal solution. Our results confirm that the proposed EAO algorithm can efficiently optimize the system capacity and ensure fairness among all users, providing a promising solution for indoor VLC systems.

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Performance Analysis of MIMO-HARQ Assisted V2V Communications With Keyhole Effect

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arXiv 2022年

作者： Zhang, Huan Liao, Zhengtao Shi, Zheng Yang, Guanghua Dou, Qingping Ma, Shaodan The State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China

Vehicle-to-vehicle (V2V) communications under dense urban environments usually experience severe keyhole fading effect especially for multi-input multi-output (MIMO) channels, which degrades the capacity and outage performance due to the rank deficiency. To avoid these, the integration of MIMO and hybrid automatic repeat request (HARQ) is proposed to assist V2V communications in this paper. By using the methods of integral transforms, the outage probabilities are derived in closed-form for different HARQ-assisted schemes, including Type I-HARQ, HARQ with chase combining (HARQ-CC), and HARQ with incremental redundancy (HARQ-IR). With the results, meaningful insights are gained by conducting the asymptotic outage analysis. Specifically, it is revealed that full time diversity order can be achieved, while full spatial diversity order is unreachable as compared to MIMO-HARQ systems without keyhole effect. Moreover, we prove that the asymptotic outage probability is a monotonically increasing and convex function of the transmission rate. More importantly, although HARQ-IR performs better than HARQ-CC owing to its higher coding complexity, this advantage becomes negligible in the large-scale array regime. Finally, the numerical results are verified by Monte-Carlo simulations along with some in-depth discussions. © 2022, CC BY.

关键词： Functions

Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node

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arXiv 2024年

作者： Latif, Imran Newkirk, Alex C. Carbone, Matthew R. Munir, Arslan Lin, Yuewei Koomey, Jonathan Yu, Xi Dong, Zhihua Computing and Data Sciences Directorate Brookhaven National Laboratory UptonNY United States Building Technology and Urban Systems Lawrence Berkeley National Laboratory BerkeleyCA United States Department of Electrical Engineering and Computer Science Florida Atlantic University Boca RatonFL United States Koomey Analytics San FranciscoCA United States

The expansion of artificial intelligence (AI) applications has driven substantial investment in computational infrastructure, especially by cloud computing providers. Quantifying the energy footprint of this infrastructure requires models parameterized by the power demand of AI hardware during training. We empirically measured the instantaneous power draw of an 8-GPU NVIDIA H100 HGX node during the training of open-source image classifier (ResNet) and large-language models (Llama2-13b). The maximum observed power draw was approximately 8.4 kW, 18% lower than the manufacturer-rated 10.2 kW, even with GPUs near full utilization. Holding model architecture constant, increasing batch size from 512 to 4096 images for ResNet reduced total training energy consumption by a factor of 4. These findings can inform capacity planning for data center operators and energy use estimates by researchers. Future work will investigate the impact of cooling technology and carbon-aware scheduling on AI workload energy consumption. © 2024, CC BY.

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Intelligent Robotic Sonographer: Mutual Information-based Disentangled Reward Learning from Few Demonstrations

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arXiv 2023年

作者： Jiang, Zhongliang Bi, Yuan Zhou, Mingchuan Hu, Ying Burke, Michael Navab, Nassir The Chair for Computer Aided Medical Procedures and Augmented Reality Technical University of Munich Germany Shenzhen Institute of Advanced Technology Chinese Academy of Science China The Department of Electrical and Computer Systems Engineering Monash University Australia The Laboratory for Computer Aided Medical Procedures Johns Hopkins University BaltimoreMD21218 United States

Ultrasound (US) imaging is widely used for biometric measurement and diagnosis of internal organs due to the advantages of being real-time and radiation-free. However, due to inter-operator variations, resulting images highly depend on the experience of sonographers. This work proposes an intelligent robotic sonographer to autonomously "explore"target anatomies and navigate a US probe to a relevant 2D plane by learning from the expert. The underlying high-level physiological knowledge from experts is inferred by a neural reward function, using a ranked pairwise image comparisons approach in a self-supervised fashion. This process can be referred to as understanding the "language of sonography". Considering the generalization capability to overcome inter-patient variations, mutual information is estimated by a network to explicitly disentangle the task-related and domain features in latent space. The robotic localization is carried out in coarse-to-fine mode based on the predicted reward associated with B-mode images. To validate the effectiveness of the proposed reward inference network, representative experiments were performed on vascular phantoms ("line"target), two types of ex-vivo animal organs (chicken heart and lamb kidney) phantoms ("point"target) and in-vivo human carotids, respectively. To further validate the performance of the autonomous acquisition framework, physical robotic acquisitions were performed on three phantoms (vascular, chicken heart, and lamb kidney). The results demonstrated that the proposed advanced framework can robustly work on a variety of seen and unseen phantoms as well as in-vivo human carotid data. Code: https://***/yuan-12138/MI-GPSR. Copyright © 2023, The Authors. All rights reserved.

关键词： Phantoms

Enhanced Redundant Scheme Based on Weighted Cluster-Head Selection for Critical 6G Infrastructures

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Enhanced Redundant Scheme Based on Weighted Cluster-Head Sel...

IEEE Globecom Workshops

作者： Grace Khayat Constandinos X Mavromoustakis Andreas Pitsillides Jordi Mongay Batalla Evangelos K. Markakis Andreas Andreou Department of Computer Science Mobile Systems Laboratory (MoSys Lab) University of Nicosia Nicosia Cyprus Department of Computer Science University of Cyprus Cyprus Department of Electrical & Electronic Engineering Science University of Johannesburg Warsaw University of Technology Warsaw Poland Department of Electrical and Computer Engineering Hellenic Mediteranean University Estavromenos Heraklion Greece Department of Computer Science Research Foundation University of Nicosia and University of Nicosia Nicosia Cyprus

ISBN: (纸本)9781665459761

Flying Ad hoc Network (FANET) consists of a group of unmanned aerial vehicles (UAVs) that fulfill a certain mission in various applications. The UAV targets uploading data to the 6G networks through communication to other UAVs or to the base station. UAVs collaborate for a purpose to achieve a certain mission in a faster and more reliable way compared to a single UAV. In critical cases such as flooding or earthquakes, one or more UAVs can be non-functional thus emerging a disconnected network. One of the most reliable routing schemes is clustering which splits the network into clusters. Every cluster incorporates a cluster-head and cluster-members. The selection of the cluster-head possesses a high influence on the routing scheme’s performance as it is responsible for all intra-cluster communication. A new clustered weighted scheme with a redundant cluster-head is proposed to ensure end-to-end communication in critical 6G infrastructures. The parameters of the weighted formula used for cluster establishment and primary cluster-head selection are the distance, the performance index, the speed, and the energy. A secondary cluster-head that automatically replaces the primary cluster-head whenever it is non-functional is selected based on the link reliability. The promising results obtained from MATLAB simulation are discussed in section IV.

关键词： 6G mobile communication Base stations Conferences Earthquakes Routing Autonomous aerial vehicles Ad hoc networks

A provable-secure and practical two-party distributed signing protocol for SM2 signature algorithm

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Frontiers of computer Science 2020年第3期14卷 203-215页

作者： Yudi ZHANG Debiao HE Mingwu ZHANG Kim-Kwang Raymond CHOO Key Laboratory of Aerospace Information Security and Trusted Computing of Ministry of Education School of Cyber Science and EngineeringWuhan UniversityWuhan 430072China School of Computer Sciences Hubei University of TechnologyWuhan 430068China Department of Information Systems and Cyber Security and Department of Electrical and Computer Engineering University of Texas at San AntonioSan AntonioTX 78249USA

Mobile devices are widely used for data access,communications and ***,storing a private key for signature and other cryptographic usage on a single mobile device can be challenging,due to its computational ***,a number of(t,n)threshold secret sharing schemes designed to minimize private key from leakage have been proposed in the ***,existing schemes generally suffer from key reconstruction *** this paper,we propose an efficient and secure two-party distributed signing protocol for the SM2 signature *** latter has been mandated by the Chinese government for all electronic commerce *** proposed protocol separates the private key to storage on two devices and can generate a valid signature without the need to reconstruct the entire private *** prove that our protocol is secure under nonstandard ***,we implement our protocol using MIRACL Cryptographic SDK to demonstrate that the protocol can be deployed in practice to prevent key disclosure.

关键词： SM2 signature two-party signing wireless environment provable security threshold secret sharing

Outage Performance and Optimal Design of MIMO-NOMA Enhanced Small Cell Networks with Imperfect Channel-State Information

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China Communications 2021年第10期18卷 107-128页

作者： Zheng Shi Hong Wang Yaru Fu Guanghua Yang Shaodan Ma Xinrong Ye School of Intelligent Systems Science and Engineering Jinan UniversityZhuhai 519070China State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Communication and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China School of Science and Technology Hong Kong Metropolitan UniversityHong Kong SARChina School of Physics and Electronic Information Anhui Normal UniversityWuhu 241002China

This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state information(CSI).The estimation error and the spatial randomness of base stations(BSs)are characterized by using Kronecker model and Poisson point process(PPP),*** outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies,including random grouping and distance-based *** is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime,while the outage performance deteriorates if the intensity is sufficiently ***,as the channel uncertainty lessens,the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell ***,highly correlated estimation error ameliorates the outage performance under a low quality of CSI,otherwise it behaves ***,the goodput is maximized by choosing appropriate precoding matrix,receiver filters and transmission *** the end,the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.

关键词： imperfect channel-state information(CSI) multiple-input multiple-output(MIMO) non-orthogonal multiple access(NOMA) small cell networks(SCNs)

Real-Time Adaptive Safety-Critical Control with Gaussian Processes in High-Order Uncertain Models

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Real-Time Adaptive Safety-Critical Control with Gaussian Pro...

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yu Zhang Long Wen Xiangtong Yao Zhenshan Bing Linghuan Kong Wei He Alois Knoll Department of Informatics Technical University of Munich Germany Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents an adaptive online learning framework for systems with uncertain parameters to ensure safety-critical control in non-stationary environments. Our approach consists of two phases. The initial phase is centered on a novel sparse Gaussian process (GP) framework. We first integrate a forgetting factor to refine a variational sparse GP algorithm, thus enhancing its adaptability. Subsequently, the hyperparameters of the Gaussian model are trained with a specially compound kernel, and the Gaussian model’s online inferential capability and computational efficiency are strengthened by updating a solitary inducing point derived from newly samples, in conjunction with the learned hyperparameters. In the second phase, we propose a safety filter based on high order control barrier functions (HOCBFs), synergized with the previously trained learning model. By leveraging the compound kernel from the first phase, we effectively address the inherent limitations of GPs in handling high-dimensional problems for real-time applications. The derived controller ensures a rigorous lower bound on the probability of satisfying the safety specification. Finally, the efficacy of our proposed algorithm is demonstrated through real-time obstacle avoidance experiments executed using both simulation platform and a real-world 7-DOF robot.

关键词： Adaptation models Adaptive systems Uncertainty Computational modeling Gaussian processes Real-time systems Safety

Path Loss Modeling for NLoS Ultraviolet Channels Incorporating Scattering and Reflection Effects

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arXiv 2024年

作者： Wu, Tianfeng Yang, Fang Li, Fei Yuan, Renzhi Cao, Tian Cheng, Ling Song, Jian Cheng, Julian Han, Zhu Department of Electronic Engineering BNRist Tsinghua University Beijing100084 China Hanjiang National Laboratory Wuhan430060 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China School of Telecommunications Engineering Xidian University Xi’an710071 China School of Electrical and Information Engineering University of the Witwatersrand Johannesburg2000 South Africa Shenzhen International Graduate School Tsinghua University Shenzhen518055 China School of Engineering The University of British Columbia KelownaBCV1V 1V7 Canada Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States

This paper tackles limitations in existing non-line-of-sight (NLoS) ultraviolet (UV) channel models, where conventional approaches assume obstacle-free propagation or uniform radiation intensity. In this paper, we develop a path loss model incorporating scattering and reflection, and then propose an obstacle-boundary approximation method to achieve computational tractability. Our framework systematically incorporates spatial obstacle properties, including dimensions, coordinates, contours, and orientation angles, while employing the Lambertian radiation pattern for source modeling. Additionally, the proposed path loss model is validated by comparing it with the Monte-Carlo photon-tracing model and analytical integral model via numerical results, which indicate that when obstacle reflection is prominent, an approximation treatment of obstacle boundaries has a negligible influence on the path loss estimation of NLoS UV communication channels. Copyright © 2024, The Authors. All rights reserved.

关键词： Monte Carlo methods