2020 IEEE International Conference on Communications Workshops (ICC Workshops)最新文献

On the Performance of Single Side-Band OFDM for Band-Limited Visible Light Communication 限带可见光通信中单边带OFDM的性能研究

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145204

Hossein Kazemi, H. Haas

{"title":"On the Performance of Single Side-Band OFDM for Band-Limited Visible Light Communication","authors":"Hossein Kazemi, H. Haas","doi":"10.1109/ICCWorkshops49005.2020.9145204","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145204","url":null,"abstract":"The use of a multicarrier modulation scheme based on orthogonal frequency division multiplexing (OFDM) is a very promising approach to enable high-speed transmissions for band-limited visible light communication (VLC) systems. The existing variants of optical OFDM have been designed mostly to establish a compromise between spectral and power efficiencies, with the premise that the signal is purely transmitted in the baseband, thereby it needs to be real-valued. A common way to synthesize a real waveform with the digital implementation of OFDM is to use Hermitian symmetry. An alternative, but not fully explored, solution without imposing Hermitian symmetry is to upconvert the complex baseband OFDM signal within the limited bandwidth of VLC systems using an appropriate carrier frequency. In this paper, the bandpass transmission of OFDM signals based on optical single side-band OFDM (SSB-OFDM) is considered. The detailed mechanism for the generation and detection of an SSB-OFDM signal with discrete-time processing is presented. To address the bandwidth constraint, spectrum shaping of the SSB-OFDM signal is discussed. Furthermore, performance analyses of spectral efficiency (SE) and bit error ratio (BER) are carried out and the results are verified using Monte-Carlo simulations. Novel insights are provided, highlighting the signal-to-noise ratio (SNR) gain of SSB-OFDM over a baseline direct current-biased optical OFDM (DCO-OFDM) system.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"12389 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115605371","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

Physically Secure Sub-THz Wireless Links 物理安全的次太赫兹无线链路

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145177

K. Sengupta, Xuyang Lu, S. Venkatesh, Bingjun Tang

{"title":"Physically Secure Sub-THz Wireless Links","authors":"K. Sengupta, Xuyang Lu, S. Venkatesh, Bingjun Tang","doi":"10.1109/ICCWorkshops49005.2020.9145177","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145177","url":null,"abstract":"Ensuring security is emerging as one of the grand challenges towards realization of a large-scale and high-speed wireless network fabric for 5G and beyond. In particular, enabling security at the network layer and application layers becomes computationally very challenging in multi-Gbps sub-THz and THz wireless links operating under strict energy constraints and latency requirements. To address this, there has been renewed interest in physical layer security techniques that attempt to exploit the physics of propagation in the channel to incorporate security features. Phased arrays, that are expected to be the foundational building blocks behind such sub-THz links, attempt to address such physical layer security by creating directive links and minimizing leakage power to undesired directions. However, the spectrum and constellation transmitted by such arrays at these off-axis angles are fully preserved allowing eavesdroppers with sensitive enough receivers to compromise the communication channel. In this paper, we demonstrate incorporation of physical layer security in sub-THz wireless links through spatio-temporal array architectures. Unlike phased arrays, these architectures enforce spectral aliasing, loss of information and constellation scrambling at undesired directions to mitigate eavesdropper attacks. We present the fundamental operation principle of such architectures and discuss various modulation techniques and their intended security features. We also demonstrate them experimentally with fully integrated sub-THz arrays in custom designed silicon ICs and packaged antennas operating at 76 GHz. The presented architectures can enable future large-scale deployment of multi-Gbps wireless networks with physically secure links operating at sub-THz frequencies for future 5G and beyond.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123111603","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: 7

NEAT-TCP: Generation of TCP Congestion Control through Neuroevolution of Augmenting Topologies 通过增强拓扑的神经进化生成TCP拥塞控制

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145446

Kay Luis Wallaschek, Robin Klose, Lars Almon, M. Hollick

引用次数: 3

RAMNe: Realtime Animal Monitoring over Network with Age of Information RAMNe:信息时代下的网络动物实时监测

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145235

Yu Nakayama, Yoshiaki Inoue, Marie Katsurai

{"title":"RAMNe: Realtime Animal Monitoring over Network with Age of Information","authors":"Yu Nakayama, Yoshiaki Inoue, Marie Katsurai","doi":"10.1109/ICCWorkshops49005.2020.9145235","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145235","url":null,"abstract":"The ever-improving Internet of things (IoT) and computer vision technologies have enabled automated monitoring of animals, which is essential for understanding animal behavior and conservation of ecosystem. The tradeoff between survey cost and sampling variability is a significant issue in designing a camera survey considering the risk of losing informative images; the monitoring accuracy tends to decrease in accordance with data reduction. However, there has been no designing method for time-lapse realtime monitoring over networks to guarantee monitoring accuracy. To address this problem, this paper proposes a Realtime Animal Monitoring over Network (RAMNe). The goal of RAMNe is to efficiently detect target animals in realtime using network cameras. We propose a determination method for the monitoring interval to guarantee the target value of monitoring accuracy based on a formal theoretical analysis using the Age of Information (AoI). The proposed scheme can minimize the amount of transferred data to enable efficient and stable monitoring even in resource-limited environments. The performance of RAMNe was evaluated with ns-3 simulations to confirm the relationship between monitoring accuracy and interval.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126027387","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

Simultaneous Lightwave Information and Power Transfer via Scattering and Line-of-Sight Links 同时光波信息和能量传输通过散射和视距链接

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145408

Haotian Qiao, Chen Gong, Weijie Liu, Zhengyuan Xu

引用次数: 1

Joint Transmit Power and Trajectory Optimization for Two-Way Multi-Hop UAV Relaying Networks 双向多跳无人机中继网络联合发射功率与轨迹优化

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145414

Bing Li, Shengjie Zhao, Rongqing Zhang, Hao Zhang, Hanli Wang, Liuqing Yang

引用次数: 11

Channel Estimation for Intelligent Reflecting Surface Enabled Terahertz MIMO Systems 基于智能反射面的太赫兹MIMO系统信道估计

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145343

Xinying Ma, Zhi Chen, Yaojia Chi, Wenjie Chen, Linsong Du, Zhuoxun Li

{"title":"Channel Estimation for Intelligent Reflecting Surface Enabled Terahertz MIMO Systems","authors":"Xinying Ma, Zhi Chen, Yaojia Chi, Wenjie Chen, Linsong Du, Zhuoxun Li","doi":"10.1109/ICCWorkshops49005.2020.9145343","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145343","url":null,"abstract":"With the development of sixth generation (6G) wireless systems, terahertz (THz) communication has been envisioned as an emerging technology pillar to provide large bandwidth and support diverse application scenarios. However, due to the severe path attenuation and poor diffraction of THz waves, THz communication links are easily interrupted by the obstacles when it is applied to indoor scenarios. To tackle this challenge, an intelligent reflecting surface (IRS), which is able to control the propagation direction of THz waves by adjusting the discrete phase shifts of IRS elements, is considered as an available alternate to mitigate blockage vulnerability and enhance the coverage capability. To begin with, the hardware characteristics of graphene-enabled IRS is investigated and the IRS-assisted THz multiple-input multiple-output (MIMO) system model is developed. Then, a low complexity compressed sensing (CS) based channel estimation scheme, namely iterative atom pruning based subspace pursuit (IAP-SP), is proposed for channel state information (CSI) acquisition. Concretely, the IAP-SP scheme reduces the computational burden by eliminating the redundant columns of sensing matrix during the iterative process. Simulation results demonstrate that, in contrast with conventional subspace pursuit (C-SP) scheme, the developed IAP-SP maintains basically consistent channel recovery performance while realizes extra 99.51% complexity reduction.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125393857","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: 13

Indoor Communications with OAM Array 基于OAM阵列的室内通信

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145397

Rui Chen, Hanyu Du, Jiandong Li

引用次数: 1

A Two-Fold Group Lasso Based Lightweight Deep Neural Network for Automatic Modulation Classification 基于双组套索的轻量级深度神经网络自动调制分类

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145050

Xiaofeng Liu, Qing Wang, Haozhi Wang

{"title":"A Two-Fold Group Lasso Based Lightweight Deep Neural Network for Automatic Modulation Classification","authors":"Xiaofeng Liu, Qing Wang, Haozhi Wang","doi":"10.1109/ICCWorkshops49005.2020.9145050","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145050","url":null,"abstract":"Automatic modulation classification (AMC) is a hot topic in modern wireless communication, which is a classification problem essentially. The deep learning methods have been applied to AMC gradually, for its excellent performance in classification, regression and decision-making tasks. However, the deep learning methods always come with complex network structure, vast training parameters and extra long training time, which seriously affected its application and promotion on power-limited and resource-constrained devices. In this paper, we propose a lightweight end-to-end AMC model named lightweight deep neural network (LDNN) via a novel group-level sparsity inducing norm, which can help network pruning itself automatically to obtain a highly compact network. In order to solve the problem of recognition confusing types, such as QAM16 and QAM 64 are always been confused in AMC task, a improved two-step training lightweight deep neural network (TLDNN) is well designed to improve the recognition accuracy. Experimental results shows the accuracy improvement of the proposed lightweight compact networks via two-fold group lasso regularization and two-step training schemes.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122294643","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

KaRuNa: A Blockchain-Based Sentiment Analysis Framework for Fraud Cryptocurrency Schemes KaRuNa:基于区块链的欺诈加密货币方案情感分析框架

2020 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2020-06-01 DOI: 10.1109/ICCWorkshops49005.2020.9145151

Patel Nikunjkumar Sureshbhai, Pronaya Bhattacharya, S. Tanwar

{"title":"KaRuNa: A Blockchain-Based Sentiment Analysis Framework for Fraud Cryptocurrency Schemes","authors":"Patel Nikunjkumar Sureshbhai, Pronaya Bhattacharya, S. Tanwar","doi":"10.1109/ICCWorkshops49005.2020.9145151","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145151","url":null,"abstract":"The current open cryptocurrency markets pose varied challenges on a prospective investor (PI), such as pseudoanonymity of cryptocurrency transactions, selection criteria for investments in crowdfunding schemes (CF), modus-operandi for these schemes, non-transparency of money generation and distribution among peers, and untraceable scams. PIs are susceptible to monetary losses in the open market due to the aforementioned issues. The fraudsters could be both internal (operator of the scheme) and external (financial institutions (FI), such as banks, money-lenders, and insurance companies). The centrality of trust among stakeholders like PI, CF, and FI is a prime concern. Motivated from these facts, this paper proposes a decentralized framework, KaRuNa, A Blockchain-based Sentiment analysis framework for Fraud Cryptocurrency schemes. KaRuNa operates on public blockchain three phases of trust modeling among stakeholders. In the first phase, transactions are performed on the blockchain that offers trust, auditability, and transparency among stakeholders. In the second phase, sentiment analysis (SA) of cryptocurrencies is proposed based on a novel algorithm of hash addresses to generate classification scores (CS). Parameters like social trends, rise/fall in cryptocurrency price, measured standard deviation, peak and low are selected to fed to proposed novel Long-short term memory (LSTM) classifier to generate recommendations based on CS. An accuracy of 98.99% is achieved using LSTM over generated CS to evaluate risks in the investment. Results demonstrate that KaRuNa achieves more scalability compared to conventional approaches.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114157273","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: 14