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Conflict Resolution Strategy in Handover Management for 4G and 5G networks

computers, Materials & Continua 2022年第9期72卷 5215-5232页

作者： Abdulraqeb Alhammadi Wan Haslina Hassan Ayman A.El-Saleh Ibraheem Shayea Hafizal Mohamad Yousef Ibrahim Daradkeh Communication Systems and Networks Research Lab Malaysia-Japan International Institute of TechnologyUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia College of Engineering A’sharqiyah University(ASU)Ibra400Oman Department of Electronics and Communication Engineering Faculty of Electrical and Electronics EngineeringIstanbul Technical University(ITU)Istanbul34467Turke Faculty of Engineering and Built Environment Universiti Sains Islam MalaysiaBandar Baru Nilai71800Malaysia Department of Computer Engineering and Networks College of Engineering at Wadi AddawasirPrince Sattam Bin Abdulaziz UniversityAl Kharj11991KSA

Fifth-generation(5G)cellular networks offer high transmission rates in dense urban ***,a massive deployment of small cells will be required to provide wide-area coverage,which leads to an increase in the number of handovers(HOs).Mobility management is an important issue that requires considerable attention in heterogeneous networks,where 5G ultra-dense small cells coexist with current fourth-generation(4G)*** mobility robustness optimization(MRO)and load balancing optimization(LBO)functions have been introduced in the 3GPP standard to address HO problems,non-robust and nonoptimal algorithms for selecting appropriate HO control parameters(HCPs)still exist,and an optimal solution is subjected to compromise between LBO and MRO ***,HO decision algorithms become *** paper proposes a conflict resolution technique to address the contradiction between MRO and LBO *** proposed technique exploits received signal reference power(RSRP),cell load and user speed to adapt HO margin(HM)and time to trigger(TTT).Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during *** proposed technique is validated with other existing algorithms from the *** results demonstrate that the proposed technique outperforms existing algorithms overall performance *** proposed technique reduces the overall average HO ping-pong probability,HO failure rate and interruption time by more than 90%,46%and 58%,respectively,compared with the other schemes overall speed scenarios and simulation time.

关键词： Mobility management handover 5G heterogeneous networks

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Research on recognition algorithm for gesture page turning based on wireless sensing

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Intelligent and Converged networks 2023年第1期4卷 15-27页

作者： Lin Tang Sumin Wang Meng Zhou Yinfan Ding Chao Wang Shengbo Wang Zhen Sun Jie Wu Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai Institute for Advanced Communication and Data ScienceSchool of Communication and Information EngineeringShanghai UniversityShanghai 200444China School of Electronic Information Engineering Gannan University of Science and TechnologyGanzhou 341000China Affiliated High School of Peking University Beijing 100086China Peking University&National Engineering Laboratory for Big Data Analysis and Applications Beijing 100871China Department of Computer and Information Sciences Temple UniversityPhiladelphiaPA 19122-6096USA

When a human body moves within the coverage range of Wi-Fi signals,the reflected Wi-Fi signals by the various parts of the human body change the propagation path,so analysis of the channel state data can achieve the perception of the human *** extracting the Channel State Information(CSI)related to human motion from the Wi-Fi signals and analyzing it with the introduced machine learning classification algorithm,the human motion in the spatial environment can be *** the basis of this theory,this paper proposed an algorithm of human behavior recognition based on CSI wireless sensing to realize deviceless and over-the-air slide *** algorithm collects the environmental information containing upward or downward wave in a conference room scene,uses the local outlier factor detection algorithm to segment the actions,and then the time domain features are extracted to train Support Vector Machine(SVM)and eXtreme Gradient Boosting(XGBoost)classification *** experimental results show that the average accuracy of the XGBoost module sensing slide flipping can reach 94%,and the SVM module can reach 89%,so the module could be extended to the field of smart classroom and significantly improve speech efficiency.

关键词： Wi-Fi signal Channel State Information(CSI) wireless sensing human behavior recognition

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Adaptive Defense Mechanisms Against Zero-Day Attacks in Wireless Sensor networks

Adaptive Defense Mechanisms Against Zero-Day Attacks in Wire...

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2024 International Conference on Distributed Systems, computer networks and Cybersecurity, ICDSCNC 2024

作者： Chaturvedi, Abhay Kukreti, Sanjeev Durga Bhavani, A. Nizampatnam, Venkata Naga Ravi Kiran Kaur, Davinder Natrayan, L. Gla University Department of Electronics & Communication Engineering Chaumuhan India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Bms Institute of Technology and Management Department of Computer Science and Engineering Bengaluru India Expert Network Security Engineer Acxiom Llc Department of Computer Networks AustinTX United States Symbiosis Law School Department of Law Pune India Saveetha School of Engineering Simats Department of Mechanical Engineering Kuthambakkam India

ISBN: (纸本)9798350375442

Important fields including healthcare, environmental monitoring, and military operations are seeing a rise in the use of wireless sensor networks (WSNs). But they are susceptible to complex cyber dangers, especially zero-day assaults, due to their dispersed nature and lack of resources. In order to protect WSNs against zero-day attacks, this research introduces an Adaptive Defense Mechanism (ADM). A dynamic response system that can adjust to changing attack patterns in real-time is integrated with machine learning-based anomaly detection in the proposed ADM. A hybrid model integrating Support Vector Machines (SVM) and Long Short-Term Memory (LSTM) networks is used by the anomaly detection module. It achieves a detection accuracy of 94.7% on simulated zero-day assault scenarios. In comparison to static defensive systems, the ADM's adaptive response mechanism, which is based on reinforcement learning, dynamically modifies the network's security regulations, resulting in a 23.5% reduction in false positives. Results from testing the proposed ADM in a simulated WSN setting show that it can greatly improve the network's ability to withstand zero-day assaults. With assaults present, the total network throughput increased by 15% and the average detection time dropped to 0.35 seconds. Based on these findings, the ADM provides a strong and effective defensive technique, guaranteeing the safety and dependability of WSNs in mission-critical applications. © 2024 IEEE.

关键词： Zero-day attack

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Large Scale Model Enabled Semantic communications Based on Robust Knowledge Distillation

Large Scale Model Enabled Semantic Communications Based on R...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Ding, Kuiyuan Liu, Fangfang Yang, Yang Chen, Mingzhe Guo, Caili Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering The Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9798350351255

Large scale artificial intelligence (AI) models possess excellent capabilities in semantic representation and understanding, making them particularly well-suited for semantic encoding and decoding. However, the substantial scale of these AI models imposes unacceptable computational resources and communication delays. To address this issue, we propose a semantic communication scheme based on robust knowledge distillation (RKD-SC) for large scale model enabled semantic communications. In the considered system, a transmitter extracts the features of the source image for robust transmission and accurate image classification at the receiver. To effectively utilize the superior capability of large scale model while make the cost affordable, we first transfer knowledge from a large scale model to a smaller scale model to serve as the semantic encoder. Then, to enhance the robustness of the system against channel noise, we propose a channel-aware autoencoder (CAA) based on the Transformer architecture. Experimental results show that the encoder of proposed RKD-SC system can achieve over 93.3% of the performance of a large scale model while compressing 96.67% number of parameters. Code: https://***/echojayne/RKD-SC. © 2024 IEEE.

关键词： Channel coding

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⁠Marine Ecosystem Monitoring Based on Remote Sensing Using Underwater Image Analysis for Biodiversity Conservation Model

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Remote Sensing in Earth Systems Sciences 2024年第4期7卷 309-318页

作者： Rao, Chandana Narasimha Rao, A. Venkateswara Shanmugasundar, G. Hamid, Junainah Abd Haldorai, Anandakumar Naidu, G. Rama Sapthami, I. Department of Chemistry Koneru Lakshmaiah Education Foundation Green Fields Vaddeswaram Andhra Pradesh Guntur 522302 India Department of Mechanical Engineering Sri Sairam Institute of Technology Chennai 600044 India Management and Science University Selangor Shah Alam Malaysia Center for Future Networks and Digital Twin Department of Computer Science and Engineering Sri Eshwar College of Engineering Tamil Nadu Coimbatore 641202 India Department of Electronics & amp Communication Engineering Aditya University Surampalem India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

The growing focus on underwater observation and use of marine resources in recent years has led to an active research area in underwater image processing and analysis. Because of its importance in marine engineering as well as aquatic robotics, underwater picture enhancement serves as a preprocessing step to increase performance of high-level vision tasks like underwater object detection as well as recognition. While a number of studies demonstrate that underwater image enhancement methods (synthetic underwater environment image) increase the detectors’ F-measure, no research has examined the connection between these two jobs. This research proposed novel technique in remote sensing–based underwater image analysis in ecosystem monitoring in biodiversity conservation model using machine learning techniques. Here, the underwater-based remote sensing image based on marine ecosystem has been collected and analysed for noise removal with normalisation. The processed image feature extracted and classified using Gaussian spatial gradient neural network (GSGNN) and multilayer pyramid Bayes network (MPBN). The output images show coral surface texture. The experimental analysis has been carried out for various underwater dataset in terms of kappa coefficient, classification accuracy, random precision, F-measure, and normalised square error. Proposed technique kappa coefficient is 94%, classification accuracy is 98%, random precision is 95%, F-measure is 93%, and Normalised square error is 63%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Biodiversity conservation model Ecosystem monitoring Machine learning Remote sensing Underwater image analysis

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Delay-Differentiated Routing in Meshed Backbone networks 21

Delay-Differentiated Routing in Meshed Backbone Networks

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21. ITG-Fachtagung Photonische Netze - 21st ITG Conference on Photonic networks

作者： Enderle, Tobias Witt, Arthur Christou, Filippos Institute of Communication Networks and Computer Engineering University of Stuttgart Stuttgart Germany

ISBN: (纸本)9783800754243

Today's network applications require strict quality of service (QoS) guarantees, e. g., in terms of availability or delay. Due to shortest path routing in backbone networks, the point-to-point delay is usually very low. However, this is not only true for the services with strict delay requirements but also for all others. Since there is no customer-perceivable delay difference, it is difficult for the network operator to justify differences in pricing between low-delay and other services. We propose a routing and network reconfiguration approach for packet-optical networks that enforces delay differentiation by routing on non-shortest paths. We present an integer linear program formulation and study the effects of our approach by simulation in two backbone topologies. We show that a considerable number of services can be routed with delay differentiation if the use of additional spectral resources is allowed. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach

关键词： Integer programming

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ILP-based Resource Optimization Realized by Quantum Annealing for Optical Wide-area communication networks – A Framework for Solving Combinatorial Problems of a Real-world Application by Quantum Annealing

arXiv

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arXiv 2024年

作者： Witt, Arthur Kim, Jangho Körber, Christopher Luu, Thomas Institute of Communication Networks and Computer Engineering University of Stuttgart Stuttgart Germany JARA HPC Forschungszentrum Jülich Jülich Germany Fraunhofer Research Institution for Energy Infrastructures and Geothermal Systems IEG Fraunhofer IEG Bochum Germany

Resource allocation of wide-area internet networks is inherently a combinatorial optimization problem that if solved quickly, could provide near real-time adaptive control of internet-protocol traffic ensuring increased network efficacy and robustness, while minimizing energy requirements coming from power-hungry transceivers. In recent works we demonstrated how such a problem could be cast as a quadratic unconstrained binary optimization (QUBO) problem that can be embedded onto the D-Wave Advantage™ quantum annealer system, demonstrating proof of principle. Our initial studies left open the possibility for improvement of D-Wave solutions via judicious choices of system run parameters. Here we report on our investigations for optimizing these system parameters, and how we incorporate machine learning (ML) techniques to further improve on the quality of solutions. In particular, we use the Hamming distance to investigate correlations between various system-run parameters and solution vectors. We then apply a decision tree neural network (NN) to learn these correlations, with the goal of using the neural network to provide further guesses to solution vectors. We successfully implement this NN in a simple integer linear programming (ILP) example, demonstrating how the NN can fully map out the solution space that was not captured by D-Wave. We find, however, for the 3-node network problem the NN is not able to enhance the quality of space of solutions. © 2024, CC BY.

关键词： Machine learning

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Integrated Sensing,Computing and communications Technologies in IoV and V2X

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China communications 2023年第3期20卷 I0002-I0004页

作者： Shanzhi Chen FRichard Yu Weisong Shi Changle Li China Information and Communication Technology Group Co. Ltd.(CICT) State Key Laboratory of Wireless Mobile Communications SMIC IEEE VTS Mobile World newsletter IEEE Canadian Academy of Engineering(CAE) Engineering Institute of Canada(EIC) IET Department of Computer and Information Sciences at the University of Delaware(UD) State Key Laboratory of Integrated Services Networks of Xidian University

With the development of new generation of information and communication technology,the Internet of Vehicles(IoV)/Vehicle-to-Everything(V2X),which realizes the connection between vehicle and X(i.e.,vehicles,pedestrians,infrastructures,clouds,etc.),is playing an increasingly important role in improving traffic operation efficiency and driving safety as well as enhancing the intelligence level of social traffic services.

关键词： driving traffic operation

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Wavelength-division-multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-division-multiplexed Transmission and Dispersion ...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Liu, Yuanbin Zhang, Hongyi Liu, Jiacheng Lu, Liangjun Du, Jiangbing Li, Yu He, Zuyuan Chen, Jianping Zhou, Linjie Poon, Andrew W. State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

We demonstrate wavelength-division-multiplexed data transmission and dispersion compensation of 25 Gb/s × 9 on-off-keying signals over a 20-km singlemode fiber using an integrated single-soliton microcomb and a cascaded microring resonator-based reconfigurable dispersion compensator. © Optica Publishing Group 2024

关键词： Dispersion compensation

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Wavelength-division-multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-division-multiplexed Transmission and Dispersion ...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Optical fibers

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