2021 IEEE International Conference on Communications Workshops (ICC Workshops)最新文献

Spectrum sharing between RLANs and terrestrial links in the 6 GHz band rlan和地面链路在6ghz频段的频谱共享

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473678

Nadia Yoza-Mitsuishi, P. Mathys

引用次数: 1

Node-Resource- and User-Demand-Aware Resource Allocation in NFV-enabled Elastic Optical Networks 支持nfv的弹性光网络中的节点资源感知和用户需求感知资源分配

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473602

Yihan Liu, Zhanqi Xu, F. Yang, Liwei Kuang

引用次数: 0

Joint User Grouping and Power Allocation for NOMA-Based UAV Relaying Networks 基于noma的无人机中继网络联合用户分组与功率分配

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473849

Bing Li, Rongqing Zhang, Liuqing Yang

引用次数: 3

Energy-Efficient Device-to-Device Privacy Content Transmission in Uplink Relay Networks 在上行中继网络中节能的设备到设备隐私内容传输

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473513

Qiang Li, Pinyi Ren, Dongyang Xu, Yuncong Xie

{"title":"Energy-Efficient Device-to-Device Privacy Content Transmission in Uplink Relay Networks","authors":"Qiang Li, Pinyi Ren, Dongyang Xu, Yuncong Xie","doi":"10.1109/ICCWorkshops50388.2021.9473513","DOIUrl":"https://doi.org/10.1109/ICCWorkshops50388.2021.9473513","url":null,"abstract":"The collaborative transmission of device-to-device (D2D) devices with the wireless networks enables the spectrum- efficient communication, which yet causes the interference of the wireless networks to D2D devices. It is fatal to the transmission of privacy content. To tackle the issue, we establish a collaborative D2D and uplink relay transmission model, in which D2D receiver eliminates the interference of the networks under the assist of the relay. Particularly, the relay and D2D receiver of the model can capture energy from the signals they received to relay the signals and facilitate the future D2D transmission, respectively. In order to guarantee the efficiency of D2D transmission, a novel energy- efficient D2D privacy content transmission protocol is proposed. In the protocol, a D2D transmission rate maximization problem is formulated subjected to several key rate and energy efficiency constraints. By solving the problem, the exact analytic solutions with respect to energy allocation parameters are acquired. Furthermore, the outage probabilities of the relay network and D2D transmission are characterized to verify the performance of the protocol. Finally, numerical results are provided to validate the analytical results of the protocol.","PeriodicalId":127186,"journal":{"name":"2021 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115824809","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

Generative Machine Learning for Resource-Aware 5G and IoT Systems 资源感知5G和物联网系统的生成机器学习

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473625

N. Piatkowski, J. Mueller-Roemer, P. Hasse, A. Bachorek, Tim Werner, Pascal Birnstill, A. Morgenstern, L. Stobbe

{"title":"Generative Machine Learning for Resource-Aware 5G and IoT Systems","authors":"N. Piatkowski, J. Mueller-Roemer, P. Hasse, A. Bachorek, Tim Werner, Pascal Birnstill, A. Morgenstern, L. Stobbe","doi":"10.1109/ICCWorkshops50388.2021.9473625","DOIUrl":"https://doi.org/10.1109/ICCWorkshops50388.2021.9473625","url":null,"abstract":"Extrapolations predict that the sheer number of Internet-of-Things (IoT) devices will exceed 40 billion in the next five years. Hand-crafting specialized energy models and monitoring sub-systems for each type of device is error prone, costly, and sometimes infeasible. In order to detect abnormal or faulty behavior as well as inefficient resource usage autonomously, it is of tremendous importance to endow upcoming IoT and 5G devices with sufficient intelligence to deduce an energy model from their own resource usage data. Such models can in-turn be applied to predict upcoming resource consumption and to detect system behavior that deviates from normal states. To this end, we investigate a special class of undirected probabilistic graphical model, the so-called integer Markov random fields (IntMRF). On the one hand, this model learns a full generative probability distribution over all possible states of the system—allowing us to predict system states and to measure the probability of observed states. On the other hand, IntMRFs are themselves designed to consume as less resources as possible—e.g., faithful modelling of systems with an exponentially large number of states, by using only 8-bit unsigned integer arithmetic and less than 16KB memory. We explain how IntMRFs can be applied to model the resource consumption and the system behavior of an IoT device and a 5G core network component, both under various workloads. Our results suggest, that the machine learning model can represent important characteristics of our two test systems and deliver reasonable predictions of the power consumption.","PeriodicalId":127186,"journal":{"name":"2021 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120836887","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

Effect of the Color Temperature of LED lighting on the sensing ability of Visible Light Communications LED照明色温对可见光通信传感能力的影响

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473610

A. Dowhuszko, M. C. Ilter, P. Pinho, R. Wichman, Jyri Hämäläinen

{"title":"Effect of the Color Temperature of LED lighting on the sensing ability of Visible Light Communications","authors":"A. Dowhuszko, M. C. Ilter, P. Pinho, R. Wichman, Jyri Hämäläinen","doi":"10.1109/ICCWorkshops50388.2021.9473610","DOIUrl":"https://doi.org/10.1109/ICCWorkshops50388.2021.9473610","url":null,"abstract":"This paper studies the effect that the color temperature of an LED lamp has on the ability of a Visible Light Communication (VLC) system to detect different events, which could be the presence, position, and/or color of an object in the sensing area. The proposed VLC-based monitoring system takes advantage of the Channel State Information (CSI) that the VLC receiver estimates regularly for OFDM equalization, and makes use of K-means++ clustering to estimate the number of events that can be identified in the collected CSI data. The color temperature of the LED lighting is varied by changing the fraction of the total radiant flux emitted by Cool-White and Red-Orange LEDs, respectively, enabling to obtain a complete palette of white light that ranges from warm reddish (2600 K) to cool blueish (6200 K). The experimental evaluation is carried out with the aid of a software-defined VLC demonstrator, and shows that the sensing performance when using the reflected VLC signal to estimate the position of the object does not vary notably with the color temperature of the LED lamp. In contrast, the use of white light with high Color Rendering Index provides better results when the objective is to identify the color signature that different objects create when placed in the sensing area.","PeriodicalId":127186,"journal":{"name":"2021 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"462 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125828503","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

Dynamic Scheduling and Routing for TSN based In-vehicle Networks 基于TSN的车载网络动态调度与路由

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473810

Ammad Ali Syed, S. Ayaz, T. Leinmüller, Madhu Chandra

{"title":"Dynamic Scheduling and Routing for TSN based In-vehicle Networks","authors":"Ammad Ali Syed, S. Ayaz, T. Leinmüller, Madhu Chandra","doi":"10.1109/ICCWorkshops50388.2021.9473810","DOIUrl":"https://doi.org/10.1109/ICCWorkshops50388.2021.9473810","url":null,"abstract":"The future autonomous vehicle is not only processing the copious amount of indispensable data generated by its onboard sensors but also utilizing the data from other vehicles, roadside unit (RSU) etc. Managing the mixed-criticality data requires intelligent time-sensitive scheduling and routing within the in-vehicle network (IVN) infrastructure. Use-cases related to self-adaptivity (including vehicular communication), partial networking and embedded virtualization require to change the configuration of the IVN at runtime. State-of-the-art IEEE Time-Sensitive Networking (TSN) standards possess a grave challenge in handling runtime reconfigurations. Above mentioned use-cases foster the development of scalable and efficient dynamic scheduling and routing algorithms for TSN based IVN. In this paper, four meticulously designed heuristics are analyzed for dynamic scheduling and routing on-the-fly in TSN based IVN. One of the algorithms, Bottleneck heuristic outperforms others in term of schedulability and response time. It schedules around 16 − 22% more flows as compared to other developed heuristics depending on the network load.","PeriodicalId":127186,"journal":{"name":"2021 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115218039","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: 20

Modulation Classification of Active Attack Signals for Internet of Things Using GP-CNN Network 基于GP-CNN网络的物联网主动攻击信号调制分类

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473800

Kejia Ji, Shuo Chang, Sai Huang, Hao Chen, Shao Jia, Hua Lu

引用次数: 3

Enabling QoS for Collaborative Robotics Applications with Wireless TSN 利用无线TSN实现协作机器人应用的QoS

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473897

Susruth Sudhakaran, Vincent Mageshkumar, Amit S. Baxi, D. Cavalcanti

引用次数: 12

Deep Learning Based Integrated Information and Energy Relaying in RF Powered Communication 基于深度学习的射频供电通信集成信息与能量中继

2021 IEEE International Conference on Communications Workshops (ICC Workshops) Pub Date : 2021-06-01 DOI: 10.1109/ICCWorkshops50388.2021.9473767

G. Prasad, Deepak Mishra

{"title":"Deep Learning Based Integrated Information and Energy Relaying in RF Powered Communication","authors":"G. Prasad, Deepak Mishra","doi":"10.1109/ICCWorkshops50388.2021.9473767","DOIUrl":"https://doi.org/10.1109/ICCWorkshops50388.2021.9473767","url":null,"abstract":"Energy transfer (ET) in RF powered harvesting as well as information transfer (IT) in end-to-end communication is obstructed by range of transmission in the network under consideration. This can be resolved by employing a cooperative relay in both ET and IT operations. However, involving the composite operations in a practically unknown environment require a learning based algorithms to obtain an optimal policy for efficient energy management and data communication together. To confront it, here, we propose a deep learning algorithm based on deep deterministic policy gradient (DDPG), providing continuous course of actions under optimal online policy for integrated information and energy relaying (i2ER) network. In the designed nonconvex problem, the long-term average net bit rate of the end-to-end communication is maximized in four phases of operations under the given constraints on the harvested energy at relay and source nodes. Via extensive simulations, various insights are obtained on the performance of the proposed algorithm in different used modulation for transmission and learning rate while and after learning. Lastly, the achieved bit rate in the i2ER network is compared with the performance of a greedy benchmark scheme and get an improvement upto 62%.","PeriodicalId":127186,"journal":{"name":"2021 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114509907","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