2023 IEEE/CIC International Conference on Communications in China (ICCC)最新文献_第4页

STAR-RIS Enhanced Covert Communication with Delay Constraint 基于延迟约束的STAR-RIS增强隐蔽通信

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233489

Beixi Cheng, Jinsong Hu, Youjia Chen, Feng Shu, Zhizhang David Chen

引用次数: 0

Probe Selection Method based on Switch Matrix for 5G Massive MIMO Base Station OTA Testing 基于交换矩阵的5G海量MIMO基站OTA测试探针选择方法

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233457

Jie Zhao, Nan Ma, Baoling Liu

引用次数: 0

An Approach for Attack Scenario Construction Based on Dynamic Attack Path Graph 基于动态攻击路径图的攻击场景构建方法

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233417

Siying He, Mi Wen, Xiumin Li, Zhou Su

{"title":"An Approach for Attack Scenario Construction Based on Dynamic Attack Path Graph","authors":"Siying He, Mi Wen, Xiumin Li, Zhou Su","doi":"10.1109/ICCC57788.2023.10233417","DOIUrl":"https://doi.org/10.1109/ICCC57788.2023.10233417","url":null,"abstract":"With the complexity and variability of cyber attacks increasing, current approaches for constructing attack scenarios often overlook the continuity of attack behaviors. These approaches lead to challenges in dynamically reconstructing the complete attack path. Additionally, many false alerts significantly reduce the accuracy of restoring an attack scenario. Against these issues, this paper proposes an approach for attack scenario construction based on a dynamic attack path graph. First, this paper proposes an alert truth rate calculating approach which utilizes mutual information. And the paper constructs the attack path graph by considering multiple dimensions, including calculated alert features and alert truth rate. In addition, an attack chain generation algorithm is proposed to restore the dynamic and complete attack scenario. Secondly, in order to cope with the changing network, the paper introduces a dynamic probabilistic update algorithm that periodically adjusts the attack path as time progresses. Finally, Experimental results show that the proposed approach can recover all attack processes in the dataset, with an algorithmic complexity of O (M × N).","PeriodicalId":191968,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"24 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":"116994138","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

Distributed Computation Offloading Based on Deep Reinforcement Learning and Blockchain in Internet of Vehicles 基于深度强化学习和区块链的车联网分布式计算卸载

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233288

Guobin Zhang, Zehao Luo, Tingting Yang

{"title":"Distributed Computation Offloading Based on Deep Reinforcement Learning and Blockchain in Internet of Vehicles","authors":"Guobin Zhang, Zehao Luo, Tingting Yang","doi":"10.1109/ICCC57788.2023.10233288","DOIUrl":"https://doi.org/10.1109/ICCC57788.2023.10233288","url":null,"abstract":"With the rapid development of Internet of Vehicles (IoV), the traditional centralized cloud computing cannot efficiently satisfy the computation requirements of vehicles. The deployment of mobile edge server (MEC) on road side unit (RSU) can shorten the distance between vehicles and computing servers so as to reduce the service delay. In order to provide wide coverage and more computation resources, we introduce high altitude platform system (HAPS) as a central node for computation controlling in the IoV system. To improve data security and user privacy, blockchain technology is applied to verify and determine the offloading strategy between RSUs. Aiming at minimizing the sum of the transmission and computation time, an optimization problem is formulated under the power and offloading constraints. The deep reinforcement learning (DRL) with the soft actor-critic (SAC) algorithm is utilized to solve the problem. Simulation results demonstrate the time reduction by the application of HAPS and significant superiority of the proposed scheme compared to the existing approaches.","PeriodicalId":191968,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"16 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":"117239749","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 Training-time Friendly Network for Real-time Drone Detection 一种训练时间友好的无人机实时检测网络

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233680

Miao Li, Shengjian Mao, Hanzhuo Wang, Zhiguo Shi, Chengwei Zhou

{"title":"A Training-time Friendly Network for Real-time Drone Detection","authors":"Miao Li, Shengjian Mao, Hanzhuo Wang, Zhiguo Shi, Chengwei Zhou","doi":"10.1109/ICCC57788.2023.10233680","DOIUrl":"https://doi.org/10.1109/ICCC57788.2023.10233680","url":null,"abstract":"The rapid development of the unmanned aerial vehicle (UAV) market poses potential threats to public safety and personal privacy, and vision sensors are widely deployed to detect intruding drones due to the intuitiveness and accessibility of videos. However, the pixel area of long-distance intrusion drones is small and the morphological features are weak, which makes identification and positioning difficult. At present, a lot of work has focused on improving the detection accuracy of drones, but there is very little to improve the detection speed of drones and shorten the network training time. Therefore, we propose a drone detector with high accuracy, short training time, and fast inference speed. In this work, we choose Centernet from the consideration of a light-head, single-stage, and anchor-free design that enables fast inference. In addition, we improve the original framework of Centernet through the separation strategy of identification features and positioning features. Furthermore, encoding more training samples from annotated boxes has a similar effect to increasing the batch size, which helps to increase the learning rate and speed up the training process. To this end, we introduce a new method of Gaussian elliptic coding and propose a new loss function for it. Considering the complexity of background during flight and the small size of the drone compared to the background, a background filter is used to reduce the influence of the complex background. In this paper, the proposed model is trained and tested on the Drone-vs-Bird dataset, and its mAP reaches 83.7%, and its FPS reaches 29.6.","PeriodicalId":191968,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"44 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":"125840045","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 New Variational Bayesian-based Radiation Source Positioning Method with Multistage Parameter Modification 基于变分贝叶斯的多阶段参数修正辐射源定位新方法

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233596

Xuezhao Cai, Zhipeng Lin, Yuqing Peng, Qiuming Zhu, Jie Wang, Xiaoxiang He, Qihui Wu, Kun Liu

引用次数: 0

Impact of Device Specifications on VLC Path Loss and System Performance: An Empirical Study 器件规格对VLC路径损耗和系统性能影响的实证研究

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233660

Shuo Liu, Pan Tang, Yu Tong, Yue Yin, Linchao Li, Anrui Niu, Liang Xia, Jianhua Zhang

{"title":"Impact of Device Specifications on VLC Path Loss and System Performance: An Empirical Study","authors":"Shuo Liu, Pan Tang, Yu Tong, Yue Yin, Linchao Li, Anrui Niu, Liang Xia, Jianhua Zhang","doi":"10.1109/ICCC57788.2023.10233660","DOIUrl":"https://doi.org/10.1109/ICCC57788.2023.10233660","url":null,"abstract":"Visible light communication (VLC) is a promising technology for sixth-generation (6G) networks due to its unlicensed bands and high transmission rates. In recent years, several studies have explored the physical propagation characteristics of VLC channels. Nevertheless, the existing models are limited by reliance on customized optical devices. In addition, only sporadic studies have investigated the influence of device specifications, yet neglecting the joint effects of the transmitter and receiver specifications. In this paper, we experimentally measure the optical channel taking into account the specifications of light-emitting diode (LED) and photo-diode (PD). Measurement results show that the path loss exponent (PLE) is 2.47 and 1.78 when the angle of departure (AOD) is larger and smaller than the half-power angle (HPA), respectively. Moreover, changing the PD size from 9.7 mm to 2 mm results in a 15.05 dB difference in path loss (PL). We further derive a PL model that can capture the joint effects of LED and PD specifications based on empirical data. The root mean square error (RMSE) of the measured and simulated data is 2.52, thereby demonstrating the accuracy and practicality of the proposed model. Based on the model, we particularly investigate the impact of the device specifications on the bit error rate (BER) performance. Results indicate that the specifications of the device need to be carefully considered for developing VLC systems. Overall, the proposed model accurately characterizes PL under different device specifications and provides a feasible and universal device selection paradigm for the design and optimization of VLC systems.","PeriodicalId":191968,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"15 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":"129743056","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

Anti-Eavesdropping and Anti-Jamming Waveform Design with Coding Split Index Modulation 编码分折射率调制的防窃听抗干扰波形设计

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233372

Ying Chen, Chao Wang, Jiangbo Si, Tongyang Xu

引用次数: 0

WVGR: Gesture Recognition based on WiFi-Video Fusion WVGR:基于wifi -视频融合的手势识别

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233557

Zixin Dai, Shuangjiao Zhai, Pinle Qin, Rui Chai, Pengcheng Zhao

{"title":"WVGR: Gesture Recognition based on WiFi-Video Fusion","authors":"Zixin Dai, Shuangjiao Zhai, Pinle Qin, Rui Chai, Pengcheng Zhao","doi":"10.1109/ICCC57788.2023.10233557","DOIUrl":"https://doi.org/10.1109/ICCC57788.2023.10233557","url":null,"abstract":"Gesture recognition is widely used in emerging industries, such as smart homes, smart medical care, and human-computer interaction. Despite its promising applications, gesture recognition based on a single-modal, such as WiFi or Video, has significant limitations. WiFi-based gesture recognition suffers from the susceptibility of its signals to multipath interference, affecting the sensing data quality, while Video signals are light and shadow sensitive and cannot penetrate obstacles, which limits its practicality in gesture recognition, particularly in cross-target recognition settings. To overcome these limitations, this paper proposes a WiFi-Video based gesture recognition method WVGR. WVGR utilizes both contrastive and iterative learning to combine the useful features of WiFi and Video, thereby increasing the accuracy of cross-target gesture recognition. Specifically, WVGR develops a two-stage learning framework. The first stage involves the fusion of WiFi and Video data utilizing a contrastive learning-based method, while the second stage integrates few labeled data to improve the efficiency of the fusion process. We recruited 10 volunteers to participate in the experiment, including two modalities of WiFi and Video, 6 gestures, and each gesture was repeated 30 times. Experimental results demonstrate that WVGR improves the recognition performance of cross-target gesture recognition. In particular, WVGR achieved an accuracy improvement of 18.8% over WiFi-based recognition and 4.4% over Video-based recognition.","PeriodicalId":191968,"journal":{"name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","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":"128454056","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

Enhancing User Experience in High-Resolution Collaborative Virtual Reality on Commodity Mobile Devices 在商用移动设备上增强高分辨率协同虚拟现实的用户体验

2023 IEEE/CIC International Conference on Communications in China (ICCC) Pub Date : 2023-08-10 DOI: 10.1109/ICCC57788.2023.10233336

Hongyuan Liang, Yuqi Li, Senyang Zhu, Liang Huang, Kaikai Chi

引用次数: 0