2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)最新文献_第8页

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

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

MINE-based Geometric Constellation Shaping in AWGN Channel 基于地雷的AWGN通道几何星座整形

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233820

Qian Wang, Xiuli Ji, L. Qian, Zilong Liu, Xinwei Du, P. Kam

{"title":"MINE-based Geometric Constellation Shaping in AWGN Channel","authors":"Qian Wang, Xiuli Ji, L. Qian, Zilong Liu, Xinwei Du, P. Kam","doi":"10.1109/ICCCWorkshops57813.2023.10233820","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233820","url":null,"abstract":"The use of high-order constellation modulations is imperative to improve the spectral efficiency, for both radio frequency/laser-based satellite systems and optical wireless communications. The geometric shaping (GS) optimization as one typical constellation shaping method drives the improvement of communication capacity and system performance. This paper presents a novel mutual information neural estimation (MINE)based GS method to optimize the high-order constellations in pure additive white Gaussian noise (AWGN) channel, which uses the deep neural network (DNN) to estimate the mutual information (MI) value and maximize the MI to approach the AWGN capacity asymptotically. The proposed system trains both the encoder and MINE networks by back propagation, and does not need to train a decoder for optimization and thus can avoid the loss caused by the decoder. Simulation results show that the MINE-based shaping design outperforms the unshaped M-ary quadrature amplitude modulation (QAM) in terms of MI values. Note that the capacity gain increases slightly as the order M increases. Furthermore, the proposed scheme is promising for constellation design in various channel models, such as the phase noise and the fading channels, once the channel model used in MINE is matched, which can be a future research topic.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"126 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":"123810295","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

Constellation Optimization Assisted OTFS with Index Modulation 星座优化辅助OTFS索引调制

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233740

Chenglin Zhong, Qinghe Du, Lei Lu, Shijiao Zhang

引用次数: 0

An Unequal Error Protection-based Coded Transmission for Federated Learning 基于不等错误保护的联邦学习编码传输

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233736

Qingya Lu, Rongchi Xu, Chang Liu, Shuangyang Li, B. Bai

引用次数: 0

A Cloud-Edge Collaborative Framework for Cross-environment Human Action Recognition based on Wi-Fi 基于Wi-Fi的跨环境人体动作识别的云边缘协作框架

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233265

Sai Zhang, Ting Jiang, Xue Ding, Yi Zhong, Haoge Jia

{"title":"A Cloud-Edge Collaborative Framework for Cross-environment Human Action Recognition based on Wi-Fi","authors":"Sai Zhang, Ting Jiang, Xue Ding, Yi Zhong, Haoge Jia","doi":"10.1109/ICCCWorkshops57813.2023.10233265","DOIUrl":"https://doi.org/10.1109/ICCCWorkshops57813.2023.10233265","url":null,"abstract":"Device-free human action recognition (HAR) based on Wi-Fi signals is an essential support in the field of the Internet of Things and shows bright application prospects. With the rapid development of deep learning (DL), HAR based on DL models has become mainstream and achieved good performance. However, most of these methods are still far from the practical application, the main challenges include poor cross-environment recognition performance and the high requirements for sensing devices of DL models. Based on this, we propose a cloud-edge collaborative HAR framework (Co-WiSensing), which explores the possibility of cross-environment HAR with low resource consumption. Considering the characteristic of the massive resources of cloud servers and the resource constraints of edge devices, a high-performance multi-branch cloud HAR model is delicately designed and the personalized model compression and offloading strategies are proposed to construct lightweight edge HAR models for different environments, this allows the edge users to realize perception under resource-limitation conditions. Extensive experiments are conducted to validate the effectiveness of the proposed framework. Experimental results show that our framework can provide better HAR accuracy across all environments while using less computation and storage cost than the state-of-the-art lightweight models.","PeriodicalId":201450,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","volume":"30 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":"123367359","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 Position Prediction-Assisted Two-Way Time Synchronization Algorithm for Highly Mobile Networks 高度移动网络中位置预测辅助的双向时间同步算法

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233790

Jiachi Zhang, Xueyun Wang, L. Liu, Kai Wang, Ju Zhang

引用次数: 0

Application of traffic scheduling mechanism based on time sensitive network in Intelligent Manufacturing Network* 基于时间敏感网络的交通调度机制在智能制造网络中的应用*

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233755

Yun Bai, Xia Jing, Junsheng Mu, Wanbin Qi

引用次数: 0

UAV-Assisted Multi-User Secure Communication Based on Hybrid DF and AF Protocol 基于DF和AF混合协议的无人机辅助多用户安全通信

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233786

Kaige Jian, Yisheng Zhao, Li Liang, Hongyi You, Xinyu Zhang

引用次数: 0

Research on 6G intelligent network architecture and key technologies for intelligent generation and autonomy 6G智能网络架构及智能生成与自主关键技术研究

2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops) Pub Date : 2023-08-10 DOI: 10.1109/ICCCWorkshops57813.2023.10233837

Wanfei Sun, Xiaoyan Duan, Min Shu, Liping Wu, Ming Ai

引用次数: 0