2021 IEEE Globecom Workshops (GC Wkshps)最新文献_第6页

Network AI Management & Orchestration: A Federated Multi-task Learning Case 网络人工智能管理与编排:一个联邦多任务学习案例

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9681969

Rongpeng Li, Wenliang Liang, Chenghui Peng, Xueli An, Zhifeng Zhao, Honggang Zhang

引用次数: 2

Energy Efficiency Framework for Time-limited Contention in the IEEE 802.11ah Standard IEEE 802.11ah标准中限时竞争的能源效率框架

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9681998

Hamid Taramit, L. Orozco-Barbosa, A. Haqiq

引用次数: 2

SISO Decoding of U-UV Codes U-UV码的SISO解码

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682136

Changyu Wu, Li Chen

引用次数: 0

SeqNet: Data-Driven PAPR Reduction via Sequence Classification SeqNet:基于序列分类的数据驱动PAPR降低

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682102

Hyeondeok Jang, Seowoo Jang, Yosub Park, Jungsoo Jung, Juho Lee, Sunghyun Choi

{"title":"SeqNet: Data-Driven PAPR Reduction via Sequence Classification","authors":"Hyeondeok Jang, Seowoo Jang, Yosub Park, Jungsoo Jung, Juho Lee, Sunghyun Choi","doi":"10.1109/GCWkshps52748.2021.9682102","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682102","url":null,"abstract":"To fully exploit Terahertz spectrum for the upcoming 6G communications, peak-to-average power ratio (PAPR) reduction plays an important role to enhance power efficiency and extend communication coverage. In this paper, we address the PAPR reduction with a data-driven approach and propose a PAPR reduction neural network, SeqNet, with the aid of a deep learning technique. Inspired by the well-known selected mapping (SLM) scheme, SeqNet finds a phase sequence leading to low PAPR when multiplied to a given modulated symbol block. SeqNet classifies a modulated symbol block into one of phase sequences, which are designed not to affect BER (Bit Error Rate) performance. We also propose, Split-SeqNet which splits the symbol block into multiple segments and finds a phase sequence for each. We perform comparative study with various data-driven PAPR reduction approaches and simulation result shows that SeqNet achieves better PAPR performance than conventional auto-encoder-based scheme, tone-reservation based, DFT-s-OFDM, and OFDM by about 0.2 dB, 0.4 dB, 1.6 dB, and 3.4 dB, respectively, which can be converted into 4.3%, 8.7%, 40.1% and 104.4% improvement of the communication coverage.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"19 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":"78673482","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

Deep Learning Approaches for Mobile Trajectory Prediction 移动轨迹预测的深度学习方法

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682164

Yannis Filippas, A. Margaris, K. Tsagkaris

{"title":"Deep Learning Approaches for Mobile Trajectory Prediction","authors":"Yannis Filippas, A. Margaris, K. Tsagkaris","doi":"10.1109/GCWkshps52748.2021.9682164","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682164","url":null,"abstract":"Mobility analytics is a very critical research topic related closely with the wide field of human behavior analysis. Mobility trajectory prediction refers to the model-based projection of an individual’s location in the foreseeable future, within the boundaries of a predefined area. This information is proved to be an important input for information systems in multiple ICT-related scientific fields. Various algorithms have been proposed so far for solving this problem, however, traditional predictive approaches are shown to underperform in accuracy and reliability. This leaves room for more sophisticated, deep-learning modeling formulations. Framed within this statement, the focus in this paper is placed on contemporary deep learning approaches for trajectory prediction and more specifically, sequential machine learning models such as the Social GAN, Trajectory Transformer, and the proposed scheme, which is based on a customized GRU neural network extended with the attention mechanism. The three approaches are theoretically described and most importantly, they are implemented, validated, and evaluated on top of a realistic experimental platform and based on both simulated mobility data and open-source mobility datasets. The evaluation process of the models takes into consideration ml regression error metrics, qualitative 2D projection but also system aspects such as training complexity in the form of hyperparameter order. The results indicate that our proposed scheme outweighs SotA deep learning approaches by 29% in terms of Mean Displacement Error and by a factor of thousands in computation complexity, making it a realistic candidate for latency-sensitive applications, placed at edge computing nodes with limited processing capabilities.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"265 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":"76726321","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

Stochastic Modelling of LoS Aggregate Interference in Uplink of Aerial Base Station-assisted Network 空中基站辅助网络上行链路LoS聚合干扰的随机建模

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682095

Francesco Linsalata, M. Magarini, U. Spagnolini

{"title":"Stochastic Modelling of LoS Aggregate Interference in Uplink of Aerial Base Station-assisted Network","authors":"Francesco Linsalata, M. Magarini, U. Spagnolini","doi":"10.1109/GCWkshps52748.2021.9682095","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682095","url":null,"abstract":"The progress in unmanned aerial vehicles technology nowadays is boosting the development of Aerial Base Station (ABS) systems to provide on-demand Line of Sight (LoS) uplink connectivity. The limited capacity of wireless networks in a crowed area could result in temporary connectivity congestion. To face with this problem, the deployment of ABS to support the offloading of the demand could represent a solution in the next future. In fact, the ground-to-air channels experience limited scattering and the probability of having only LoS link above a certain altitude is higher than ground-to-ground communications. LoS prevalence provides a stable and reliable link for a target ground user, but interference impairs the communication itself, thus affecting the connectivity. Starting from the above considerations, the aim of this paper is to investigate a stochastic framework to model the impact of the uplink LoS aggregated users interference to derive the outage probability. The interfering nodes, i.e. user equipments accessing the same network cell, are scattered on the ground according to a Poisson point process in the two dimensional area. First, we show analytically how essential physical parameters involved in the ground-to-air communication affect the quality of service. Then, the mathematical derivation is validated by means of numerical simulations.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"71 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":"77560409","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

Security Performance Analysis of a Health System using Hybrid NOMA-OMA based IoT System 基于混合NOMA-OMA物联网系统的卫生系统安全性能分析

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682100

H. Chamkhia, A. Erbad, A. Al-Ali, Amr Mohamed, A. Refaey, M. Guizani

{"title":"Security Performance Analysis of a Health System using Hybrid NOMA-OMA based IoT System","authors":"H. Chamkhia, A. Erbad, A. Al-Ali, Amr Mohamed, A. Refaey, M. Guizani","doi":"10.1109/GCWkshps52748.2021.9682100","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682100","url":null,"abstract":"Internet of Things (IoT) systems have been playing a significant role in improving the quality of various applications and services. With the expansion increase of loT devices and users, different Multiple Access (MA) techniques have been proposed to overcome the spectrum scarcity and the high latency. However, in MA-based loT systems, communication is not only threatened by external eavesdroppers but also by untrusted internal users. Therefore, proposing secured MA-based loT systems is of high importance. This paper proposes a hybrid Non Orthogonal Multiple Access (NOMA) I Orthogonal Multiple Access (OMA)-based loT system to improve the data transmission security. The proposed scheme exploits the advantages of the two different MA techniques as well as the Physical Layer Security (PLS). We first describe the system model and then we detail the proposed scheme and the relevant performance analysis. Finally, our simulation results verify the accuracy of the derived expressions and evaluate the advantage of the proposed scheme, when compared to the pure NOMA and pure OMA-based loT systems.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"16 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":"74023980","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

A Robust Protocol for Smart eHealthcare based on Elliptic Curve Cryptography and Fuzzy logic in IoT 基于椭圆曲线加密和物联网模糊逻辑的智能电子医疗鲁棒协议

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682030

Abderrazak Abdaoui, A. Erbad, A. Al-Ali, Amr Mohamed, M. Guizani

{"title":"A Robust Protocol for Smart eHealthcare based on Elliptic Curve Cryptography and Fuzzy logic in IoT","authors":"Abderrazak Abdaoui, A. Erbad, A. Al-Ali, Amr Mohamed, M. Guizani","doi":"10.1109/GCWkshps52748.2021.9682030","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9682030","url":null,"abstract":"Emerging technologies change the qualities of modern healthcare by employing smart systems for patient monitoring. To well use the data surrounding the patient, tiny sensing devices and smart gateways are involved. These sensing systems have been used to collect and analyze the real-time data remotely in Internet of Medical Thinks (IoM). Since the patient sensed information is so sensitive, the security and privacy of medical data are becoming challenging problem in IoM. It is then important to ensure the security, privacy and integrity of the transmitted data by designing a secure and a lightweight authentication protocol for the IoM. In this paper, in order to improve the authentication and communications in health care applications, we present a novel secure and anonymous authentication scheme. We will use elliptic curve cryptography (ECC) with random numbers generated by fuzzy logic. We simulate IoM scheme using network simulator 3 (NS3) and we employ optimized link state routing protocol (OLSR) algorithm and ECC at each node of the network. We apply some attack algorithms such as Pollard’s ρ and Baby-step Giant-step to evaluate the vulnerability of the proposed scheme.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"65 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":"75038959","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

Particle Swarm Optimized Federated Learning For Securing IoT Devices 粒子群优化联邦学习保护物联网设备

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9681946

P. Kishore, S. Barisal, D. Mohapatra

{"title":"Particle Swarm Optimized Federated Learning For Securing IoT Devices","authors":"P. Kishore, S. Barisal, D. Mohapatra","doi":"10.1109/GCWkshps52748.2021.9681946","DOIUrl":"https://doi.org/10.1109/GCWkshps52748.2021.9681946","url":null,"abstract":"Federated learning (FL) focuses on interpreting optimization, privacy, and communication but pays little consideration to enhance training and results on the edge devices. The major challenge on these Internet of Things (IoT) devices is efficient training and inference. Another considerable challenge is securing IoT devices for a long time. This paper resolves it by selecting appropriate parameters for building a local machine learning or deep learning (ML/DL) model. Appropriate parameters will make the model's training less computationally expensive and secure the edge or IoT device. So, we propose a particle swarm optimization (PSO) method to optimize the hyper-parameter environments for the bounded DL model in an FL environment. First, we select the 2-gram represented Application Programming Interface (API) calls of the malicious and benign instances for the dataset's feature. Then, API calls of the sample are represented using 2-gram, and their frequency fills the dataset's rows. Later, we represent the sample's feature in a grayscale image and apply the LeNet-5 model. Our experiment indicates that PSO efficiently tunes the hyperparameters of LeNet-5 compared to the grid search method. The near-optimal parameters for FL do not affect the model's accuracy.","PeriodicalId":6802,"journal":{"name":"2021 IEEE Globecom Workshops (GC Wkshps)","volume":"60 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":"75119705","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

Ergodic Capacity Analysis of Large Intelligent Surface Assisted MIMO Systems 大型智能表面辅助MIMO系统的遍历容量分析

2021 IEEE Globecom Workshops (GC Wkshps) Pub Date : 2021-12-01 DOI: 10.1109/GCWkshps52748.2021.9682121

Marjan Abbasi Mosleh, F. Héliot, R. Tafazolli

引用次数: 2