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Intentional Islanding of Power Systems Through Self-Embedding Learning 基于自嵌入学习的电力系统有意孤岛
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682069
Zhonglin Sun, Yannis Spyridis, Achilleas Sesis, G. Efstathopoulos, Elisavet Grigoriou, T. Lagkas, P. Sarigiannidis
{"title":"Intentional Islanding of Power Systems Through Self-Embedding Learning","authors":"Zhonglin Sun, Yannis Spyridis, Achilleas Sesis, G. Efstathopoulos, Elisavet Grigoriou, T. Lagkas, P. Sarigiannidis","doi":"10.1109/GCWkshps52748.2021.9682069","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682069","url":null,"abstract":"Intentional islanding is a procedure to divide the electrical grid into several parts to guarantee the stability of a system in the case of failure. This study provides an unsupervised deep neural network to deal with the issue of intentional islanding. We propose to use a self-learning neural network to improve the generalisation performance of the islanding task. In addition, we use a merging technology to assign isolated buses to their neighbour's label. Experiments are carried out on several grid cases to illustrate the effect of our solution.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"2016 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86130343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Detecting Attackers during Quantum Key Distribution in IoT Networks using Neural Networks 利用神经网络检测物联网量子密钥分发过程中的攻击者
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9681988
H. A. Al-Mohammed, A. Al-Ali, E. Yaacoub, K. Abualsaud, T. Khattab
{"title":"Detecting Attackers during Quantum Key Distribution in IoT Networks using Neural Networks","authors":"H. A. Al-Mohammed, A. Al-Ali, E. Yaacoub, K. Abualsaud, T. Khattab","doi":"10.1109/GCWkshps52748.2021.9681988","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9681988","url":null,"abstract":"Internet of Things (IoT) deployments face significant security challenges due to the limited energy and computational power of IoT devices. These challenges are more serious in the quantum communications era, where certain attackers might have quantum computing capabilities, which renders IoT devices more vulnerable. This paper addresses the problem of IoT security by investigating quantum key distribution (QKD) in beyond 5G networks. An architecture for implementing QKD in beyond 5G IoT networks is proposed, offloading the heavy computational tasks to IoT controllers, while considering the use case of sensors deployed in railroad networks. Neural Network (NN) techniques are proposed in order to detect the presence of an attacker during QKD without the need to disrupt the key distribution process. The results show that the proposed techniques can reach 99% accuracy.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"97 8","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91400551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Modeling a Sliding Window Decoder for Spatially Coupled LDPC Codes 空间耦合LDPC码的滑动窗解码器建模
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682064
Min Zhu, David G. M. Mitchell, M. Lentmaier, D. Costello
{"title":"Modeling a Sliding Window Decoder for Spatially Coupled LDPC Codes","authors":"Min Zhu, David G. M. Mitchell, M. Lentmaier, D. Costello","doi":"10.1109/GCWkshps52748.2021.9682064","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682064","url":null,"abstract":"Due to their capacity achieving performance with sliding window decoding (SWD), spatially coupled LDPC (SC-LDPC) codes are emerging as candidates for next generation channel coding applications. In this paper we present a general model of SWD of SC-LDPC codes and develop an analysis that allows us to estimate error probability performance under decoder error propagation conditions that can occur when low latency operation is desired. We also show how the model parameters can be estimated and indicate how the model can be used to predict the performance of code doping techniques used to mitigate the effects of decoder error propagation.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"12 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87185876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Secrecy Degradation for Inevitable Phase Noise in Artificial Noise Shielded FH Systems 人工噪声屏蔽跳频系统中不可避免相位噪声的保密性退化
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682033
Changqing Song, Lizhi Qin, Hongzhi Zhao, S. Shao, Youxi Tang
{"title":"Secrecy Degradation for Inevitable Phase Noise in Artificial Noise Shielded FH Systems","authors":"Changqing Song, Lizhi Qin, Hongzhi Zhao, S. Shao, Youxi Tang","doi":"10.1109/GCWkshps52748.2021.9682033","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682033","url":null,"abstract":"This paper adopts an artificial noise (AN) shielded frequency hopping (FH) architecture to counteract both wire-tapping and hostile attack, but the inevitable phase noise will degrade both the AN cancellation and secrecy performance. Considering this, first, the AN cancellation performance is analyzed by separating the received AN into the cancellable common phase component (CPC) and non-cancellable inter-carrier interference (ICI). On top of this, the system secrecy is analyzed via secrecy capacity, and the secrecy degradation for phase noise is extracted in terms of 3 dB coherence bandwidth of the adopted oscillators, transmitting power ratio of AN to expected signal (ES), propagation channel quality, and parameter estimation period. Numerical and simulation results show that phase noise will degrade both the AN cancellation and secrecy performance, and this degradation can be diminished by shortening the parameter estimation period, optimizing the power ratio of AN to ES, and improving the propagation channel quality.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"56 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87243501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Comprehensive RF Dataset Collection and Release: A Deep Learning-Based Device Fingerprinting Use Case 综合射频数据集收集和发布:基于深度学习的设备指纹用例
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682024
Abdurrahman Elmaghbub, B. Hamdaoui
{"title":"Comprehensive RF Dataset Collection and Release: A Deep Learning-Based Device Fingerprinting Use Case","authors":"Abdurrahman Elmaghbub, B. Hamdaoui","doi":"10.1109/GCWkshps52748.2021.9682024","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682024","url":null,"abstract":"Deep learning-based RF fingerprinting has recently been recognized as a potential solution tor enabling newly emerging wireless network applications, such as spectrum access policy enforcement, automated network device authentication, and unauthorized network access monitoring and control. Real, comprehensive RF datasets are now needed more than ever to enable the study, assessment, and validation of newly developed RF fingerprinting approaches. In this paper, we present nod release a large-scale RF fingerprinting dataset, collected from 25 different LoRa-enabled IoT transmitting devices using USRP B210 receivers. Our dataset consists of a large number of SigMF- compliant binary files representing the I/Q time-domain samples and their corresponding FFT-based files of LoRa transmissions. This dataset provides a comprehensive set of essential experimental scenarios, considering both indoor and outdoor environments and various network deployments and configurations, such as the distance between the transmitters and the receiver, the configuration of the considered LoRa modulation, the physical location of the conducted experiment, and the receiver hardware used for training and testing the neural network models.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"4 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90282644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Symbol-Level Precoding and Passive Beamforming Design for IRS-Aided Cognitive Radio Networks irs辅助认知无线网络的符号级预编码和无源波束形成设计
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9681951
Guangyang Zhang, Chao Shen, B. Ai, Z. Zhong
{"title":"Symbol-Level Precoding and Passive Beamforming Design for IRS-Aided Cognitive Radio Networks","authors":"Guangyang Zhang, Chao Shen, B. Ai, Z. Zhong","doi":"10.1109/GCWkshps52748.2021.9681951","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9681951","url":null,"abstract":"In this paper, we consider a joint beamforming design in a cognitive radio (CR) network aided with an intelligent reflecting surface (IRS) panel. The symbol-level precoding (SLP) is adopted at the base station to enhance the symbol error rate (SER) performance of the network. The joint beamforming design is formulated as a nonconvex optimization problem to achieve max-min fairness in the secondary network subject to the interference temperature constraints, the maximum power constraint, and the constant modulus constraints over the passive beamformer. To solve this problem with the coupling between variables, we propose an algorithm based on the alternating optimization (AO) technique, and then two subproblems can be obtained to optimize the transmit and passive beamformers alternately. Specifically, a penalized successive convex approximation (P-SCA) method is developed to optimize the passive beamformer. The simulation results demonstrate that the SLP technique can further enhance the system performance in terms of signal-to-interference-plus-noise ratio (SINR) compared with the conventional block-level precoding.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85661166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Performance Analysis of Wireless Practical Byzantine Fault Tolerance Networks Using IEEE 802.11 基于IEEE 802.11的无线实用拜占庭容错网络性能分析
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682068
Ziyi Zhou, Oluwakayode Onireti, Lei Zhang, Muhammad Ali Imran
{"title":"Performance Analysis of Wireless Practical Byzantine Fault Tolerance Networks Using IEEE 802.11","authors":"Ziyi Zhou, Oluwakayode Onireti, Lei Zhang, Muhammad Ali Imran","doi":"10.1109/GCWkshps52748.2021.9682068","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682068","url":null,"abstract":"Blockchain has achieved great success in cryptocurrency for its peculiarities for security and privacy, which are also important in the wireless network. Therefore, there are growing interests in applying blockchain to the wireless network. Wireless Practical Byzantine Fault Tolerance (PBFT) is considered the most applicable consensus mechanism. However, the existing researches and applications are mostly under wired scenarios. In this paper, we investigated the performance of the wireless PBFT network using IEEE 802.11 under unsaturated situations. The performance is evaluated through three metrics: success probability, delay and throughput. Results suggest that there exists a minimum transmission success probability to achieve the end-to-end performance required for the PBFT consensus protocol.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"115 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88693925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Network Intelligence with Quantum Computing in 6G and B6G: Design Principles and Future Directions 6G和B6G中量子计算的网络智能:设计原则和未来方向
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682045
Francesco Vista, V. Musa, G. Piro, L. Grieco, G. Boggia
{"title":"Network Intelligence with Quantum Computing in 6G and B6G: Design Principles and Future Directions","authors":"Francesco Vista, V. Musa, G. Piro, L. Grieco, G. Boggia","doi":"10.1109/GCWkshps52748.2021.9682045","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682045","url":null,"abstract":"Network intelligence in 6G systems and beyond may require computing power and computation time hard to reach in current deployments. While the employment of quantum computers for supporting Quantum Machine Learning emerged as a viable solution to overcome this issue, their integration within a network architecture still represents an uncovered research topic. To bridge this gap, this paper illustrates the design principles of centralized and distributed architectures, where quantum computers are deployed in the remote cloud or geographically distributed at the edge, respectively. The advantages and disadvantages of the resulting network architectures are investigated to point out open issues and future research directions.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"1465 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86501571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Degree-aware In-network Aggregation for Federated Learning with Fog Computing 基于雾计算的联邦学习的度感知网络内聚合
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682059
Wan-Ting Ho, S. Fang, Tingfeng Liu, Jian-Jhih Kuo
{"title":"Degree-aware In-network Aggregation for Federated Learning with Fog Computing","authors":"Wan-Ting Ho, S. Fang, Tingfeng Liu, Jian-Jhih Kuo","doi":"10.1109/GCWkshps52748.2021.9682059","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682059","url":null,"abstract":"Data privacy preservation has drawn much attention in emerging machine learning applications, and thus collaborative training is getting much higher such as Federated Learning (FL). However, FL requires a central server to aggregate local models trained by different users. Thus, the central server may become a crucial network bottleneck and limit scalability. To remedy this issue, a novel Fog Computing (FC)-based FL is presented to locally train the model and cooperate to accomplish in-network aggregation to prevent overwhelm the central server. Then, the paper formulates a new optimization problem termed DAT to minimize the total communication cost and maximum latency jointly. We first prove the hardness and propose two efficient algorithms, ADAT-C and ADAT, for the special and general cases, respectively. Simulation and experiment results manifest that our algorithms at least outperform 30% of communication cost compared with other heuristics without sacrificing the convergence rate.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"8 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89696142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Chernoff Bound and Saddlepoint Approximation for Outage Probability in IRS-Assisted Wireless Systems irs辅助无线系统中断概率的Chernoff界和Saddlepoint逼近
2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9681955
Tianxiong Wang, Gaojie Chen, J. Coon, Mihai-Alin Badiu
{"title":"Chernoff Bound and Saddlepoint Approximation for Outage Probability in IRS-Assisted Wireless Systems","authors":"Tianxiong Wang, Gaojie Chen, J. Coon, Mihai-Alin Badiu","doi":"10.1109/GCWkshps52748.2021.9681955","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9681955","url":null,"abstract":"We analyze the outage probability of an intelligent reflecting surface (IRS)-assisted communication network. An upper bound on the outage probability is formulated based on the Chernoff inequality. Furthermore, through an exact asymptotic (a large number of reflecting elements) analysis based on a saddlepoint approximation, we derive closed-form expressions of the outage probability for systems with and without a direct link and obtain the corresponding diversity orders. Simulation results corroborate our theoretical analysis and show the inaccuracies inherent in using the central limit theorem (CLT) to analyze system performance. Our analysis is accurate even for a small number of IRS elements in the high signal-to-noise ratio (SNR) regime.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"82 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87356844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
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