2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)最新文献_第7页

Graph Convolutional Integration based Distributed Multi-View Learning in Urban Air Mobility 基于图卷积集成的城市空中交通分布式多视图学习

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233715

Kai Xiong, Rui Wang, S. Leng, Quanxin Zhao, Meie Peng

{"title":"Graph Convolutional Integration based Distributed Multi-View Learning in Urban Air Mobility","authors":"Kai Xiong, Rui Wang, S. Leng, Quanxin Zhao, Meie Peng","doi":"10.1109/ICCCWorkshops57813.2023.10233715","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233715","url":null,"abstract":"Urban Air Mobility (UAM) expands vehicles from the ground to the near-ground space, envisioned as a revolution for transportation systems. Comprehensive scene perception is the foundation for Autonomous Air Vehicles (AAV). However, AAV encounters a primary perception challenge: three-dimensional piloting makes the visual perception of AAVs easily obstructed by skyscrapers in urban. High perception learning requirements conflict with the view-limited visual information. To overcome the challenge, multi-view learning has been proposed to collect multi-view data to train the onboard deep learning model. But traditional multi-view learning is deployed on a single device operating centrally, which is difficult to deploy in dynamic environments. Accordingly, this paper proposes Graph Convolutional Network (GCN) based Distributed Multi-View learning (GCNDMV), taking account of GCN relation extractability to facilitate single-view representation learning integration. The proposed distributed multi-view learning framework allows distinct single-view representation learning integration. Moreover, due to the diversity gain of different single-view learning, various single-view representation learning of the GCN-DMV outperforms a homogeneous single-view representation learning of GCN-DMV in terms of recognition accuracy. Simulation experiments are conducted over a realistic multi-view dataset to verify the efficiency of the distributed multi-view learning framework.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123623923","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

Semantic Information Extraction for Text Data with Probability Graph 基于概率图的文本数据语义信息提取

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233741

Zhouxiang Zhao, Zhaohui Yang, Ye Hu, Licheng Lin, Zhaoyang Zhang

引用次数: 0

Transfer Learning-Based Physical Layer Authentication for Wireless Networks Handover 基于迁移学习的无线网络切换物理层认证

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233819

Shiji Wang, Shida Xia, Sha Liu, Yan Zhang, Chang Cao

引用次数: 0

Reduced Complexity SCL Decoding of U-UV Codes Through List Pruning 通过列表修剪降低U-UV码的SCL译码复杂度

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233707

Wenhao Chen, Li Chen, Huazi Zhang

引用次数: 0

Decentralized Federated Learning With Asynchronous Parameter Sharing 异步参数共享的分散联邦学习

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233712

Haihui Xie, M. Xia, Peiran Wu, Shuai Wang, Kaibin Huang

{"title":"Decentralized Federated Learning With Asynchronous Parameter Sharing","authors":"Haihui Xie, M. Xia, Peiran Wu, Shuai Wang, Kaibin Huang","doi":"10.1109/ICCCWorkshops57813.2023.10233712","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233712","url":null,"abstract":"Federated learning (FL) enables wireless terminals to collaboratively learn a shared parameter model while keeping all the training data on devices per se. Whatever parameter sharing is applied, the learning model shall adapt to distinct network architectures because an improper learning model will deteriorate learning performance and, even worse, lead to model divergence, especially for the asynchronous transmission in resource-limited distributed networks. To address this issue, this paper proposes a decentralized learning model and develops an asynchronous parameter-sharing algorithm for resource-limited distributed Internet of Things (IoT) networks. It can improve learning efficiency and realize efficient communication. By jointly accounting for the convergence bound of federated learning and the transmission delay of wireless communications, we develop a node scheduling and bandwidth allocation algorithm to improve the learning performance. Extensive simulation results corroborate the effectiveness of the distributed algorithm in terms of fast learning model convergence and low transmission delay.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130409420","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

OTFS Transmission Assisted USV Environment Awareness in Satellites-denied Scenario 在卫星拒绝的情况下，OTFS传输辅助USV环境感知

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233780

Ganlin Hao, Yu Wang, Minghao Yin, Chuanhui Ju, Yue Yu

{"title":"OTFS Transmission Assisted USV Environment Awareness in Satellites-denied Scenario","authors":"Ganlin Hao, Yu Wang, Minghao Yin, Chuanhui Ju, Yue Yu","doi":"10.1109/ICCCWorkshops57813.2023.10233780","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233780","url":null,"abstract":"In the upcoming area of 6G, integrating sensing and communication in complex environments, such as satellites-denied sea surface, evolving into a key point for unmanned surface vehicle(USV) environment awareness. However, accurately perceived heading velocity and position of high speed USV in maritime scenario remains a challenge due to the limited availability of information and hardware cost. To address this issue, the newly released Orthogonal Time Frequency and Space (OTFS) modulation, which extracts Doppler shifts in the spatial domain and time delays, has been proposed to lift relative velocity and position accuracy. In this paper, we introduce a solution that leverages the OTFS waveform to continuously receive communication signals and identify delay-Doppler domain indices simultaneously. Specifically, we design a factor graph to realize belief propagation(BP), which has the potential to retrieve enough information to complete perception. Simulation results show that the proposed method yields significant improvements in velocity and position accuracy compared to the classic methods.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133118918","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

Integration of ToB Service and ToC Service for 5G-Advanced Networks 面向5g先进网络的ToB业务和ToC业务融合

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233842

Shuangyue Liu, J. Yin, Xuexin Li, Wenyi Li, Peirong Xie

{"title":"Integration of ToB Service and ToC Service for 5G-Advanced Networks","authors":"Shuangyue Liu, J. Yin, Xuexin Li, Wenyi Li, Peirong Xie","doi":"10.1109/ICCCWorkshops57813.2023.10233842","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233842","url":null,"abstract":"The fifth-generation (5G) network enables vertical industries and facilitates the digital and intelligent transformation of industries. However, 5G to business (ToB) and 5G to customer (ToC) cannot be accessed simultaneously by universal terminals, which poses inconvenience to customers in the education, government, cultural tourism. In this paper, a dual-domain fast network (DDFN) with network-side routed selected solution (NRSS) is proposed at the 5G core architecture and process level, which integrates ToB and ToC services for 5G-advanced networks. The DDFN customers can access the local public network and nearby private network simultaneously and imperceptibly with universal terminals at anytime and anywhere. NRSS is a routing scheme of DDFN, which directs various services onto distinct protocol data unit (PDU) sessions. Private network PDU sessions are automatically created when triggered by a particular policy. Compared to universal or standard solutions, NRSS without the upgrade of terminals exhibits superior capabilities in interprovincial roaming and compatibility with various access modes. In summary, NRSS-based DDFN enables service-based diversion without upgrading terminals and wireless infrastructure, which is a potential solution for applications in 5G-advanced industries.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128556726","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

Rate-Compatible Shortened PAC Codes 速率兼容的缩短PAC代码

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233795

Xinyi Gu, M. Rowshan, Jinhong Yuan

引用次数: 1

Heterogeneous Wireless Resources On-demand Access Distributed Decision Based on Spectrum Sensing 基于频谱感知的异构无线资源按需接入分布式决策

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233809

Shuying Zhang, Kunze Yang, Zuyao Ni, Ming Su

{"title":"Heterogeneous Wireless Resources On-demand Access Distributed Decision Based on Spectrum Sensing","authors":"Shuying Zhang, Kunze Yang, Zuyao Ni, Ming Su","doi":"10.1109/ICCCWorkshops57813.2023.10233809","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233809","url":null,"abstract":"In this paper, we investigate the problem of multi-user on-demand access to heterogeneous wireless resources based on spectrum sensing (SS) considering the impact of traffic buffering scenarios, the variation of channel occupancy, and channel quality levels. Because both variations can be modeled as Markov chains, a two-layer Markov chain modeling approach and a two-layer Multi-Agent deep reinforcement learning (MARL) training model are used to achieve a reasonable matching of users’ load degrees with the heterogeneous wireless resource blocks. Specifically, the local information of spectrum sensing is used as the input state of the outer layer Agent, while the user’s current traffic queue information and the action decisions collected by the local accumulation window, and the corresponding acknowledge (ACK) feedback are used as the input state of the inner layer. A network-wide utility function associated with the user traffic changes is used to centrally train the two layers of user Agents offline. According to the simulation results, the proposed algorithm significantly simplifies the online computation and online interaction process because the complex training process has been completed offline.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130864433","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

An Intelligent Detector for Carrier Index Differential Chaos Shift Keying System 载波指数差分混沌移位键控系统的智能检测器

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233810

Dongyang Peng, Yi Fang, Huan Ma, Pingping Chen, Meiyuan Miao

引用次数: 0