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International Black Sea Conference on communications and Networking (BlackSeaCom)

作者： Mohamed Abdel-Kader Mohammed Karmoose Mariam Aboelwafa Yasser Gadallah Hassan N. Kheirallah Department of Communications and Electronics Engineering Alexandria University Alexandria Egypt Department of Computer Communications and Autonomous Systems New Giza University Giza Egypt Department of Electronics and Communications Engineering The American University in Cairo New Cairo Egypt

ISBN: (数字)9798350351859

ISBN: (纸本)9798350351866

The integration of unmanned aerial vehicles (UAVs) and low earth orbit (LEO) satellites in communication networks is receiving increasing attention pursued in current research efforts. The UAVs, with links to LEO satellites, can be used as base stations to provide coverage in remote out-of-coverage areas. This paper proposes a machine learning (ML) based deployment of a single UAV that allocates uplink resources to cover mixed traffic demands. The UAV is positioned in the 3-D space and the resources are allocated to fulfill the requirements of all user equipment (UE) traffic profiles. These traffic profiles include the Ultra-reliable and low-latency communication (URLLC), the enhanced Mobile Broadband (eMBB) and the Age of Information (AoI) sensitive traffic. Our proposed technique aims at obtaining real-time results close to the optimal bound of the solution at lower complexity. Simulation results show that the proposed solution achieves close-to-optimal results and outperforms benchmark techniques from previous studies.

关键词： Space vehicles Satellites Q-learning Simulation Low earth orbit satellites Ultra reliable low latency communication Benchmark testing

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Wasserstein Graph Distance Based on L1-Approximated Tree Edit Distance between Weisfeiler-Lehman Subtrees

arXiv

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arXiv 2022年

作者： Fang, Zhongxi Huang, Jianming Su, Xun Kasai, Hiroyuki Department of Computer Science and Communications Engineering WASEDA University Japan Department of Communications and Computer Engineering WASEDA University Japan

The Weisfeiler-Lehman (WL) test is a widely used algorithm in graph machine learning, including graph kernels, graph metrics, and graph neural networks. However, it focuses only on the consistency of the graph, which means that it is unable to detect slight structural differences. Consequently, this limits its ability to capture structural information, which also limits the performance of existing models that rely on the WL test. This limitation is particularly severe for traditional metrics defined by the WL test, which cannot precisely capture slight structural differences. In this paper, we propose a novel graph metric called the Wasserstein WL Subtree (WWLS) distance to address this problem. Our approach leverages the WL subtree as structural information for node neighborhoods and defines node metrics using the L1-approximated tree edit distance (L1-TED) between WL subtrees of nodes. Subsequently, we combine the Wasserstein distance and the L1-TED to define the WWLS distance, which can capture slight structural differences that may be difficult to detect using conventional metrics. We demonstrate that the proposed WWLS distance outperforms baselines in both metric validation and graph classification experiments. Copyright © 2022, The Authors. All rights reserved.

关键词： Graph neural networks

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A low-cost buoyant force measurement device for monitoring sugar concentration in water solution

A low-cost buoyant force measurement device for monitoring s...

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Electrical, computer, communications and Mechatronics engineering (ICECCME), International Conference on

作者： Luka Kaučić Ivana Kovačević Ivan Aleksi Tomislav Keser Josip Zidar Snježana Rimac-Drlje Department of Computer Engineering and Automation Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Communications Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

Monitoring sugar concentration during fermentation is crucial for producing high-quality alcoholic beverages. Traditional methods for measuring sugar concentration can be costly and time-consuming, especially for small-scale producers. In this study, we developed a low-cost buoyant force measurement device for monitoring sugar concentration in water solutions. The device consists of a buoyant object fully submerged in the solution and connected to a load-cell sensor. As the sugar concentration in the liquid increases, the buoyant force on the object increases, and the load-cell measures this force. Proposed device is calibrated using solutions of known sugar concentrations and its high accuracy and precision is presented. The device is tested in controlled environment to ensure accurate tracking changes in sugar concentration over time. Proposed device can be a valuable tool for small-scale producers looking to optimize their fermentation processes while minimizing costs.

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Dual-Band Slot Array Antenna for W-Band Application Based on Gap Waveguide

Dual-Band Slot Array Antenna for W-Band Application Based on...

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European Conference on Antennas and Propagation, EuCAP

作者： Mu Fang A Uz Zaman J. Yang D. Santiago I. Arregui Miguel A. G. Laso Ahmed A. Kishk Department of Electrical Engineering Chalmers University of Technology Sweden Department of Electrical and Communications Engineering Public University of Navarre Spain Department of Electrical and Computer Engineering Concordia University Canada

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

A co-aperture dual-band linearly polarized slot array utilizing ridge gap waveguide (RGW) technology has been developed to operate within the 74 – 78 GHz and 102 – 106 GHz frequency ranges. The subarray features two sets of longitudinal slots positioned on the broad wall of the single waveguide channel, allowing for dual-band radiation through a planar aperture. Furthermore, two bandpass filters (BPFs) are placed on either side of the subarray, enabling independent feeding and filtering characteristics for the dual bands. A subarray column of several slot elements has been designed and simulated to demonstrate the dual-band concept. The subarray can produce high-gain beams when expanded into a planar array configuration.

关键词： Band-pass filters Wireless communication Slot antennas Filtering Dual band Gap waveguide Planar arrays Aperture antennas Planar waveguides Linear antenna arrays

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Enhanced MIMO-DCT-OFDM System Using Cosine Domain Equalizer

arXiv

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arXiv 2023年

作者： Ramadan, Khaled Department of Communications and Computer Engineering The Higher Institute of Engineering at Al-Shorouk City Cairo Egypt

Discrete Cosine Transform (DCT) can be used instead of conventional Discrete Fourier Transform (DFT) for the Orthogonal Frequency Division Multiplexing (OFDM) construction, which offers many advantages. In this paper, the Multiple-Input-Multiple-Output (MIMO) DCT-OFDM is enhanced using a proposed Cosine Domain Equalizer (CDE) instead of a Frequency Domain Equalizer (FDE). The results are evaluated through the Rayleigh fading channel with Co-Carrier Frequency Offset (Co-CFO) of different MIMO configurations. The average bit error probability and the simulated time of the proposed scheme and the conventional one is compared, which indicates the importance of the proposed scheme. Also, a closed formula for the number of arithmetic operations of the proposed equalizer is developed. The proposed equalizer gives a simulation time reduction of about 81.21%, 83.74% compared to that of the conventional LZF-FDE, and LMMSE-FDE, respectively for the case of 4×4 configuration. © 2023, CC BY.

关键词： Equalizers

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Path Planning Solution for Intelligent Robots Using Ex*RRT Algorithm in Disaster Relief 5

Path Planning Solution for Intelligent Robots Using Ex*RRT A...

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5th IEEE International Conference on Recent Trends in computer Science and Technology, ICRTCST 2024

作者： Hariprasath, V.Y. Mukesh, S. Aruna, T.N. Gayana, R. Akshya, J. Choudhry, Mani Deepak Sundarrajan, M. SRM Institute of Science and Technology Department of Computational Intelligence Chennai India KGiSL Institute of Technology Department of Computer Science and Engineering Coimbatore India K. Ramakrishnan College of Engineering Department of Information Technology Tiruchirappalli India KGiSL Institute of Technology Department of Information Technology Coimbatore India SRM Institute of Science and Technology Department of Networking and Communications Chennai India

ISBN: (纸本)9798350351378

Unmanned Ground Robots (UGVs) are increasingly becoming vital tools in disaster relief operations, offering a means to navigate through hazardous environments where human intervention may be risky or impossible. These intelligent robots are designed to perform a variety of tasks, such as searching for survivors, delivering supplies, and assessing damage. However, the effectiveness of UGVs in such critical missions largely depends on their ability to navigate complex and unpredictable terrains, a challenge that necessitates advanced path-planning strategies. The paper introduces a novel approach to path planning for UGVs in disaster relief scenarios. This approach combines the strengths of advanced rapidly Rapidly-exploring Random Trees (RRT) algorithms with the capabilities of YOLOv4, a state-of-the-art technique for object detection, specifically tailored here for human detection. RRT algorithms are known for their efficiency in exploring complex spaces, making them ideal for navigating through the unpredictable terrains typical of disaster zones. Meanwhile, YOLOv4 enhances the UGVs' ability to detect and respond to human presence, a critical requirement in rescue operations. The UGVs equipped with this novel path-planning strategy were able to navigate safely and efficiently, adapting to the dynamic nature of the environment. More importantly, the accuracy in detecting human presence was significantly improved, a crucial factor in ensuring that aid and rescue efforts are directed where they are most needed. By enhancing the path planning capabilities of UGVs with advanced algorithms and human detection technology, this approach holds the potential to revolutionize disaster response operations, making them more efficient and impactful, ultimately leading to faster and more effective aid delivery to those in dire need. © 2024 IEEE.

关键词： Motion planning

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Intelligent Target Cell Selection Algorithm for Low Latency 5G Networks 2nd

Intelligent Target Cell Selection Algorithm for Low Latency ...

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2nd EAI International Conference on Computational Intelligence and communications, CICom 2021

作者： Nyangaresi, Vincent Omollo Al Sibahee, Mustafa A. Abduljabbar, Zaid Ameen Alhassani, Abdulhadi Abduljaleel, Iman Qays Abood, Enas Wahab Faculty of Biological & Physical Sciences Tom Mboya University College Homabay Kenya College of Big Data and Internet Shenzhen Technology University Shenzhen China Computer Technology Engineering Department Iraq University College Basrah Iraq Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah Iraq Huazhong University of Science and Technology Shenzhen Institute Shenzhen China Communications Engineering Department Iraq University College Basrah Iraq Department of Computer Science College of Computer Science and Information Technology University of Basrah Basrah Iraq Department of Mathematics College of Science University of Basrah Basrah Iraq

ISBN: (纸本)9783031195228

Security and efficiency during the handover process are critical challenges in 5G heterogeneous networks owing to its strict low latency and security requirements. The 5G networks support many services and communication paradigms. Examples of these applications include as Internet of Things (IoT), vehicular ad hoc networks (VANETs), device-to-device communication (D2D), among others. As such, security lapses in the core network can easily escalate to the supported communication devices and networks and vice versa. Unfortunately, legacy cellular networks deploy the received signal strength indicator (RSSI) as the only parameter during the handover process. This results in increased handover latencies, packet losses, and high handover failure probability. Consequently, other protocols have been introduced that deploy additional handover parameters such as data rates, service costs, battery power, bandwidth, and energy consumption. However, these schemes only deal with efficiency of the handoff process but rarely consider security and privacy issues. Conversely, security and privacy protocols rarely address efficiency aspects of the handover process. In this paper, an algorithm that leverages on artificial neural networks coupled with fuzzy logic for target cell selection is presented. Based on the obtained results, there is a 56.1% reduction in handover latency and a 38.8% reduction in packet losses when the proposed scheme is deployed. In terms of security, it upholds both backward and forward key secrecy. In addition, desynchronization and replay and attacks are effectively thwarted in the proposed algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： 5G mobile communication systems

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GNSS Interference Classification Using Federated Reservoir Computing 24

GNSS Interference Classification Using Federated Reservoir C...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Ye, Ziqiang Gao, Yulan Liu, Xinyue Xiao, Yue Xiao, Ming Zammit, Saviour University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Kth Royal Institute of Technology Division of Information Science and Engineering Stockholm100 44 Sweden Southwest Jiaotong University SWJTU-Leeds Joint School Chengdu611756 China University of Malta Department of Communications and Computer Engineering MsidaMSD 2080 Malta

ISBN: (纸本)9798350363760

The expanding use of Unmanned Aerial Vehicles (UAVs) in vital areas like traffic management, surveillance, and environmental monitoring highlights the need for robust communication and navigation systems. Particularly vulnerable are Global Navigation Satellite Systems (GNSS), which face a spectrum of interference and jamming threats that can significantly undermine their performance. While traditional deep learning approaches are adept at mitigating these issues, they often fall short for UAV applications due to significant computational demands and the complexities of managing large, centralized datasets. In response, this paper introduces Federated Reservoir Computing (FedRC) as a potent and efficient solution tailored to enhance interference classification in GNSS systems used by UAVs. Our experimental results demonstrate that FedRC not only achieves faster convergence but also sustains lower loss levels than traditional models, highlighting its exceptional adaptability and operational efficiency. © 2024 IEEE.

关键词： Federated learning

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Quantum Computing in Wireless communications and Networking: A Tutorial-cum-Survey

arXiv

引用

arXiv 2024年

作者： Zhao, Wei Weng, Tangjie Ruan, Yue Liu, Zhi Wu, Xuangou Zheng, Xiao Kato, Nei School of Computer Science and Technology Anhui University of Technology China The University of Electro-Communications Department of Computer and Network Engineering Japan Tohoku University Sendai Japan

Owing to its outstanding parallel computing capabilities, quantum computing (QC) has been a subject of continuous attention. With the gradual maturation of QC platforms, it has increasingly played a significant role in various fields such as transportation, pharmaceuticals, and industrial manufacturing, achieving unprecedented milestones. In modern society, wireless communication stands as an indispensable infrastructure, with its essence lying in optimization. Although artificial intelligence (AI) algorithms such as reinforcement learning (RL) and mathematical optimization have greatly enhanced the performance of wireless communication, the rapid attainment of optimal solutions for wireless communication problems remains an unresolved challenge. QC, however, presents a new alternative. This paper aims to elucidate the fundamentals of QC and explore its applications in wireless communications and networking. First, we provide a tutorial on QC, covering its basics, characteristics, and popular QC algorithms. Next, we introduce the applications of QC in communications and networking, followed by its applications in miscellaneous areas such as security and privacy, localization and tracking, and video streaming. Finally, we discuss remaining open issues before concluding. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

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RM-Net: An Encrypted Traffic Classification Method Based on Deep Learning for Low Labeled Rate Scenarios

RM-Net: An Encrypted Traffic Classification Method Based on ...

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2023 China Automation Congress, CAC 2023

作者： Yang, Xu Zhang, Kaisa Chuai, Gang Chen, Zibin Chen, Xiangyu Xiong, Zihao Xu, Yichao Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Ministry of Education Beijing100876 China University of Massachusetts Department of Electrical and Computer Engineering AmherstMA01003 United States

ISBN: (纸本)9798350303759

The development of Internet has led to increasingly serious network security issues. Although encryption technology applied to network communication do users the favour of protecting data privacy to a certain extent, the existence of encrypted traffic also provides a cover for malicious attacks in the network. Accurate identification of encrypted traffic is crucial for maintaining network security. However, improving classification performance for low labeled rate scenarios remains a challenge in current research. Therefore, we propose an encryption traffic classification method based on Deep Learning, named RM-Net. This method combines ResNet, MobileNet and LSTM models and fully leverages their advantages to extract data features from both spatial and temporal dimensions, while continuously learning complex relationships between features. To verify the effectiveness of proposed model, we conduct multiple experiments using real network encrypted traffic data under a 5 % labeled rate scenario, and compare them with ResNet and LSTM. The experimental results show that our method performs well in accuracy, precision, recall and Fl-score metrics, achieving an accuracy rate of 97.72 % with only 5 % labeled data. © 2023 IEEE.

关键词： Network security

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