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arXiv 2021年

作者： Zhang, Miao Cumanan, Kanapathippillai Thiyagalingam, Jeyarajan Tang, Yanqun Wang, Wei Ding, Zhiguo Dobre, Octavia A. School of Information Science and Engineering Chongqing Jiaotong University Chongqing China Department of Electronic Engineering University of York YorkYO10 5DD United Kingdom Scientific Computing Department of Rutherford Appleton Laboratory Science and Technology Facilities Council Harwell Campus Ditcot United Kingdom School of Electronics and Communication Engineering Sun Yat-Sen University Shenzhen510006 China School of Information Science and Technology Nantong University Nantong China Nantong Research Institute for Advanced Communication Technologies Nantong China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China School of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom Department of Electrical and Computer Engineering Memorial University St. John’sNLA1B 3X5 Canada

This paper investigates a machine learning-based power allocation design for secure transmission in a cognitive radio (CR) network. In particular, a neural network (NN)based approach is proposed to maximize the secrecy rate of the secondary receiver under the constraints of total transmit power of secondary transmitter, and the interference leakage to the primary receiver, within which three different regularization schemes are developed. The key advantage of the proposed algorithm over conventional approaches is the capability to solve the power allocation problem with both perfect and imperfect channel state information. In a conventional setting, two completely different optimization frameworks have to be designed, namely the robust and non-robust designs. Furthermore, conventional algorithms are often based on iterative techniques, and hence, they require a considerable number of iterations, rendering them less suitable in future wireless networks where there are very stringent delay constraints. To meet the unprecedented requirements of future ultra-reliable low-latency networks, we propose an NN-based approach that can determine the power allocation in a CR network with significantly reduced computational time and complexity. As this trained NN only requires a small number of linear operations to yield the required power allocations, the approach can also be extended to different delay sensitive applications and services in future wireless networks. When evaluate the proposed method versus conventional approaches, using a suitable test set, the proposed approach can achieve more than 94% of the secrecy rate performance with less than 1% computation time and more than 93% satisfaction of interference leakage constraints. These results are obtained with significant reduction in computational time, which we believe that it is suitable for future real-time wireless applications. © 2021, CC0.

关键词： Cognitive radio

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Enhancing effectivity of automated irrigation system using fuzzy logic

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AIP Conference Proceedings 2021年第1期2336卷

作者： S. Krishna Bhat Sukanya S. Kumar Keerthana Krishnakumar Sherin Shaju Pankaj Kumar G. 1Department of Computer Science and Engineering Federal Institute of Science And Technology (FISAT) Angamaly Kerala-683 577 India 2Department of Electrical and Electronics Engineering Mets School of Engineering Mala Kerala-680 732 India

Irrigation in agricultural lands is critical and time-consuming and its automation possess huge challenges. A smart irri- gation system needs real-time values of moisture, humidity, temperature etc. Capturing the real-time values of moisture, humidity, temperature etc. requires the deployment of multiple sensors at multiple locations. The occurrence of localized phenomena can affect the proper functioning of the irrigation system. Determining the parameters and deciding how much irrigation is to be done, is a daunting task. Moreover, these values can be altered or falsely measured due to highly localized situations or interference, like the proximity of a generator when it switches on can alter the temperature measured by the nearest sensor, or that of a water container or bucket placed near the sensor can alter humidity values. All these factors can affect the judgement of how irrigation is done by the automation system and hence affect the crops, as these readings would cause either over-irrigation or dehydration of certain areas of the crop, and can result in damaged or reduced productivity. Our approach consists of deploying a large number of sensors throughout a large agricultural land and aggregating the data. The localized errors can be weeded out through proper analysis of sensor data. We used a fuzzy logic-based system to make decisions on irrigation. Certain instances may require human intervention to resolve, such as intentional tampering of sensors or destruction of sensors due to pests or natural phenomenon. The system detects and alerts the farmer or worker to check in at that particular site.

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Intuitionistic fuzzy clustering and natural exponential inertia weight with Artificial Bee Colony based scheduling approach for mobile grid

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AIP Conference Proceedings 2021年第1期2387卷

作者： Kavitha Bharathi Shanmugam Dhavamani Mohanasundaram 1Department of Computer Technology –UG Kongu Engineering College Perundurai Erode Tamilnadu India - 638 060 2Department of Mathematics Kongu Engineering College Perundurai Erode Tamilnadu India - 638 060

Research in mobile grid computing is inspired by the broad benefits of intensive scientific and enterprise applications by the scientific community in grid and mobile computing. The primary aim of grid computing is to combine the power of wide-ranging resources that are very diverse in nature and provide users with essential services to users in the future. Resources are complex and varying in a mobile grid system and the availability is limited for a period of time. With resource mobility in mind, classification is the most challenging and primitive challenge in the mobile grid environment. The previous paradigm outlined the Quantum based approach on Gravitational search Algorithm (QBGSA) for scheduling the task (job) on a mobile computing grid. In any case, it has problem with computational difficulty and execution time. To solve this problem, the proposed system designed an Intuitionistic Fuzzy C-Means (IFCM) clustering and Natural Exponential Inertia Weight with Artificial Bee Colony (NEIWABC) based scheduling approaches. In this proposed research work, grid server has all the information about mobile grid networks. Once it receiving the task request from user, it verifies the available resource providers. The nodes are clustered by using Intuitionistic Fuzzy C-Means (IFCM) clustering algorithm and Cluster Head (CH) selection is done using mobile capacity such as storage capacity, computational power. Then the task request is promoting to the selected CH in the cluster. Then the CH schedules the jobs to the appropriate mobiles to respond user. The task scheduling is performed by using Natural Exponential Inertia Weight with Artificial Bee Colony (NEIWABC) algorithm. The results of this experiment depicts that the proposed system attains good efficiency on comparison with previous system.

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On the effective capacity of an underwater acoustic channel under impersonation attack

arXiv

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arXiv 2020年

作者： Aman, Waqas Haider, Zeeshan Waqas H. Shah, S. Mahboob Ur Rahman, M. Dobre, Octavia A. Electrical engineering department Information Technology University Lahore54000 Pakistan Computer Laboratory University of Cambridge CambridgeCB3 0FD United Kingdom Department of Electrical and Computer engineering Memorial University St. John'sNLA1B 3X5 Canada

This paper investigates the impact of authentication on effective capacity (EC) of an underwater acoustic (UWA) channel. Specifically, the UWA channel is under impersonation attack by a malicious node (Eve) present in the close vicinity of the legitimate node pair (Alice and Bob);Eve tries to inject its malicious data into the system by making Bob believe that she is indeed Alice. To thwart the impersonation attack by Eve, Bob utilizes the distance of the transmit node as the feature/fingerprint to carry out feature-based authentication at the physical layer. Due to authentication at Bob, due to lack of channel knowledge at the transmit node (Alice or Eve), and due to the threshold-based decoding error model, the relevant dynamics of the considered system could be modelled by a Markov chain (MC). Thus, we compute the state-transition probabilities of the MC, and the moment generating function for the service process corresponding to each state. This enables us to derive a closed-form expression of the EC in terms of authentication parameters. Furthermore, we compute the optimal transmission rate (at Alice) through gradient-descent (GD) technique and artificial neural network (ANN) method. Simulation results show that the EC decreases under severe authentication constraints (i.e., more false alarms and more transmissions by Eve). Simulation results also reveal that the (optimal transmission rate) performance of the ANN technique is quite close to that of the GD method. Copyright © 2020, The Authors. All rights reserved.

关键词： Quality of service

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Connection Density Maximization of Narrowband IoT Systems with NOMA

Connection Density Maximization of Narrowband IoT Systems wi...

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作者： Mostafa, Ahmed Elhamy Zhou, Yong Wong, Vincent W.S. Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada School of Information Science and Technology ShanghaiTech University Shanghai201210 China

Narrowband Internet of Things (NB-IoT) provides energy-efficient communications with extended coverage for the low data rate IoT devices. In this paper, we propose a power-domain non-orthogonal multiple access (NOMA) scheme for the NB-IoT systems to enhance the connection density by allowing multiple IoT devices to simultaneously access one subcarrier. We consider both single-tone and multi-tone transmission modes of the NB-IoT systems, where each device can access a single subcarrier or a bond of contiguous subcarriers, respectively. We formulate joint subcarrier and power allocation problems for both transmission modes to maximize the connection density while taking the quality of service requirements and the transmit power constraints of IoT devices into account. We solve the single-tone nonconvex mixed integer programming problem by transforming it into a mixed integer linear programming problem to obtain the optimal solution. The multi-tone problem is solved by using the difference of convex programming approach to obtain a close-to-optimal solution. We also propose low-complexity heuristic algorithms to solve both problems in a suboptimal manner. The simulations results show that our proposed scheme increases the connection density of NB-IoT systems by 87% in the single-tone mode and by 24% in the multi-tone mode compared to orthogonal multiple access. © 2002-2012 IEEE.

关键词： Internet of things

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Error analysis of the numerical method for correcting the propagation of EM waves in the troposphere

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Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2020年第3期19卷 407-414页

作者： Liu, Yuanzhi Tang, Tao Liu, Guo Olaimat, M. Science and Technology on Electronic Information Control Laboratory Southwest China Research Institute of Electronic Equipment Chengdu610036 China College of Electronic Engineering Chengdu University of Information Technology Chengdu610025 China Department of Electrical and Computer Engineering University of Waterloo WaterlooN2L 3G1 Canada School of Electrical Engineering and Computer Science University of Ottawa OttawaK1N 6N5 Canada Key laboratory of Atmospheric Sounding China Meteorological Administration Chengdu610225 China

Electromagnetic (EM) waves do not travel in straight lines in the troposphere due to refraction. This leads to errors in many engineering applications. In order to correct these errors, a numerical solution based on the difference method has been proposed, which can reveal the degree of EM wave bending owing to atmospheric refraction, moreover, it can predict the actual path of the EM wave propagating in the troposphere. The error of the numerical method is studied here, which reveals the source of the error. Based on this, two improvement methods are proposed. The computational accuracy of the numerical methods is verified by comparison with the analytical solution. The proposed method ensures the computational efficiency and accuracy of the problem of refraction of EM waves in the troposphere. © 2020 SBMO/SBMag

关键词： Error analysis

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Distributed Antenna Selection and Beamforming for ELAA based Downlink ISAC Systems

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IEEE Transactions on Vehicular technology 2025年

作者： Gao, Qian Zhong, Ruikang Mu, Xidong Peng, Mugen Shin, Hyundong Liu, Yuanwei Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom School of Electronics Electrical Engineering and Computer Science BelfastBT3 9DT United Kingdom Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Kyung Hee University Dept. of Electronics and Information Convergence Eng. Yongin-si17104 Korea Republic of The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of

An extremely large-scale antenna array (ELAA) based integrated sensing and communication (ISAC) system is investigated. Focusing on a practical user-roaming environment, the ISAC beamforming design and antenna selection for ELAA are studied. In particular, two antenna selection schemes, namely, movable subarray selection (MSS) and adjustable antenna selection (ASS), are proposed to provide low complexity and flexible beamforming design. For each proposed scheme, a long-term sum rate maximization problem is formulated via jointly optimizing the antenna selection and beamforming, subject to the constraints of transmitting power and beampattern gain for target sensing. To address this problem, a dimension reduction assisted multi-agent proximal policy optimization (DR-MAPPO) algorithm, which can be used for different antenna selection schemes, is developed. An OrderConv layer is designed, which reduces the input dimension by removing the channel state information (CSI) of unselected antennas while keeping the order information of selected ones. Moreover, multiple agents are employed to execute antenna selection and beamforming in a distributed manner according to current channel state information and previous antenna selection, which can reduce the complexity by decomposing the problem. Numerical results demonstrate that MSS outperforms the fixed subarray selection by providing more degrees of freedom and ASS further surpasses MSS through adopting changeable subarray shape. Moreover, the proposed DR-MAPPO algorithm improves the computational efficiency and achieves preferable data rates compared to original MAPPO algorithm. © 1967-2012 IEEE.

关键词： Beamforming

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Preparing a commercial quantum key distribution system for certification against implementation loopholes

arXiv

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arXiv 2023年

作者： Makarov, Vadim Abrikosov, Alexey Chaiwongkhot, Poompong Fedorov, Aleksey K. Huang, Anqi Kiktenko, Evgeny Petrov, Mikhail Ponosova, Anastasiya Ruzhitskaya, Daria Tayduganov, Andrey Trefilov, Daniil Zaitsev, Konstantin Russian Quantum Center Skolkovo Moscow121205 Russia Vigo Quantum Communication Center University of Vigo VigoE-36310 Spain NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow119049 Russia Department of Physics Faculty of Science Mahidol University Bangkok10400 Thailand Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Bangkok10110 Thailand QRate Skolkovo Moscow143026 Russia Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Steklov Mathematical Institute Russian Academy of Sciences Moscow119991 Russia atlanTTic Research Center University of Vigo VigoE-36310 Spain School of Telecommunication Engineering Department of Signal Theory and Communications University of Vigo VigoE-36310 Spain National Research University Higher School of Economics Moscow101000 Russia

A commercial quantum key distribution (QKD) system needs to be formally certified to enable its wide deployment. The certification should include the system’s robustness against known implementation loopholes and attacks that exploit them. Here we ready a fiber-optic QKD system for this procedure. The system has a prepare-and-measure scheme with decoy-state BB84 protocol, polarisation encoding, qubit source rate of 312.5 MHz, and is manufactured by QRate. We detail its hardware and post-processing. We analyse the hardware for known implementation loopholes, search for possible new loopholes, and discuss countermeasures. We then amend the system design to address the highest-risk loopholes identified. We also work out technical requirements on the certification lab and outline its possible structure. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum cryptography

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The implementation of an intelligent algorithm hybrid biometric identification for the exemplary hardware platforms 13th

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13th International Conference on Dependability and Complex Systems, DepCoS-RELCOMEX 2018

作者： Gomolka, Zbigniew Twarog, Boguslaw Zeslawska, Ewa Department of Computer Engineering Faculty of Mathematics and Natural Sciences University of Rzeszow ul. Pigonia 1 Rzeszow35-959 Poland Department of Applied Information Faculty of Applied Informatics University of Information Technology and Management in Rzeszow ul. Sucharskiego 2 Rzeszow35-225 Poland

ISBN: (纸本)9783319914459

The area of security of biometric access control systems is a rapidly growing field of scientific studies, diversely applicable in banking, electronic payment, etc. The paper presents the implementation of an intelligent algorithm hybrid biometric identification with the use of VistaFA2, IriTech and Futronic scanners. The system uses the biometric reading of human iris, face and fingerprints. An intelligent module determines a similarity measure of a processed hybrid feature vector to the consecutive records in the access database. This approach helps to increase the reliability of identification systems and reduces the risk of counterfeits and intrusion into restricted access resources. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Hybrid systems

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Head shape variations based on a three-shell forward electroencephalographic spherical model

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AIP Conference Proceedings 2022年第1期2425卷

作者： A. Papargiri V. Kalantonis P. Vafeas M. Doschoris F. Kariotou G. Fragoyiannis 1Department of Electrical and Computer Engineering University of Patras 26504 Patras Greece 2Department of Chemical Engineering University of Patras 26504 Patras Greece 3Institute of Genetics and Biometry Leibniz Institute for Farm Animal Biology 18196 Dummerstorf Germany 4School of Science and Technology Hellenic Open University 26222 Patras Greece

The current research is focused on the study of the effect of head shape geometrical deformations to the solution of the forward electroencephalographic (EEG) problem and its sensitivity response. A novel and accurate analytical scheme has been developed by performing a perturbation analysis in the linear regime, where a homogenous three-shell spherical model, equipped with all the necessary mathematical tools, is introduced. The efficacy of the method is demonstrated by incorporating the numerical implementation of the obtained formulae in which both cases, with or without surface deviations, are presented and benchmarked. The suggested procedure provides us with a criterion, which recognizes whether surface perturbations will influence EEG recordings.

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