2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)最新文献_第2页

UAV-Based Intelligent Reflecting Surface Transmission: Weighted Sum Rate Maximization of Wireless Network 基于无人机的智能反射面传输:无线网络加权和速率最大化

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012856

Wen-Jing Wang, Ziyang Du, Sha Li, Guangyue Lu, Long Chen, Nan Qi

引用次数: 0

Cybertwin-Driven Multi-Intelligent Reflecting Surfaces aided Vehicular Edge Computing Leveraged by Deep Reinforcement Learning 基于深度强化学习的cybertwin驱动的多智能反射面辅助车辆边缘计算

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012694

Xuhui Zhang, Huijun Xing, Weilin Zang, Zhenzhen Jin, Yanyan Shen

{"title":"Cybertwin-Driven Multi-Intelligent Reflecting Surfaces aided Vehicular Edge Computing Leveraged by Deep Reinforcement Learning","authors":"Xuhui Zhang, Huijun Xing, Weilin Zang, Zhenzhen Jin, Yanyan Shen","doi":"10.1109/VTC2022-Fall57202.2022.10012694","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012694","url":null,"abstract":"Recently, the cybertwin-driven intelligent internet of vehicles has received widespread consideration in modern smart cities which makes it possible to run high dimensional, low-latency tolerating, and computational-intensive tasks on the vehicles. Thanks to the development in mobile edge computing, the so-called vehicular edge computing allows mobile vehicles to offload their tasks to the road-side unit or hybrid access point due to the limited computation capability. In this paper, we consider a cybertwin-driven internet of vehicle system that provides computing services for mobile vehicles in local area network or wide area network aided with multi-intelligent reflecting surfaces. Based on this system model, we investigate an optimization problem to jointly maximize the sum of data rate in wide area network, and the sum of energy utilities of vehicles. However, in the proposed system model, it is complicated to design the optimal phase, scheduling and offloading decision policy. To solve this issue, we propose a block coordinate descent and deep reinforcement learning based intelligent IoV computing policy. Numerical results have verified that the proposed algorithm can achieve better IoV computing performance compared with four relative benchmark algorithms.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126936871","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

Study on Optical Fiber Communication in Vehicle 车载光纤通信技术研究

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10013017

Toshihito Tatsuoka, Zhenni Pan, S. Shimamoto

引用次数: 0

Outdoor Localization of Intelligent Reflecting Surfaces using Radio Maps 基于无线电地图的智能反射面户外定位

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012902

S. K. Vankayala, Purnima Lala Mehta, Seungil Yoon, K. Sharma, N. Prashant, Sai Krishna Santosh Gollapudi

{"title":"Outdoor Localization of Intelligent Reflecting Surfaces using Radio Maps","authors":"S. K. Vankayala, Purnima Lala Mehta, Seungil Yoon, K. Sharma, N. Prashant, Sai Krishna Santosh Gollapudi","doi":"10.1109/VTC2022-Fall57202.2022.10012902","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012902","url":null,"abstract":"Determining the best locations for Intelligent Reflecting Surface (IRS) is crucial in attaining an intelligent and controllable wireless environment, where increased probability of Line-of-Sight (LoS) links results in achieving higher performance gains. This paper investigates the potential in improving the performance of IRS-assisted wireless communication systems for Non-Line-of-Sight (NLoS) users. We particularly evaluate the coverage performance of placing multiple IRSs within an area map that consists of pre-installed Base Stations (BSs). We propose a fast and novel Angle-Direction Localization algorithm to determine optimal IRS locations such that a virtual LoS (VLoS) path to the NLoS users can be established. Through our proposed algorithm, we show an increase in the LoS connections to the NLoS users in the area map using optimally localized IRSs. Lastly, we show minimized end-to-end path loss levels at the NLoS user locations on the placement of IRSs using radio maps. Our results showcase that optimally localized IRSs, play an important role in extending the coverage of an existing network.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123533814","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

Design of Robust LoS-MIMO Transmission in HAPS Feeder Link HAPS馈线链路中LoS-MIMO的鲁棒传输设计

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012950

Motoshi Tawada, Y. Ohta, A. Nagate

引用次数: 1

Adaptive and Efficient Key Extraction for Fast and Slow Fading Channels in V2V Communications V2V通信中快慢衰落信道的自适应高效密钥提取

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012884

M. Shawky, Muhammad Usman, M. Imran, Q. Abbasi, Shuja Ansari, Ahmad Taha

{"title":"Adaptive and Efficient Key Extraction for Fast and Slow Fading Channels in V2V Communications","authors":"M. Shawky, Muhammad Usman, M. Imran, Q. Abbasi, Shuja Ansari, Ahmad Taha","doi":"10.1109/VTC2022-Fall57202.2022.10012884","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012884","url":null,"abstract":"Securing data exchange between intercommunicating terminals, e.g., vehicle-to-everything, constitutes a technological challenge that needs to be addressed. Security solutions must be computationally efficient and flexible enough to be implemented in any wireless propagation environment. Recently, physical layer security has gained popularity, which exploits the randomness of wireless channel responses for extracting high entropy secret cryptographic keys. The current state-of-the-art relies on the independently varying channel sources of randomness, e.g., received signal strength (RSS) and phase. However, the limited capability of RSS-based extraction techniques has motivated researchers to investigate alternative approaches. Although phase-based approaches have emerged in many studies, optimising the extraction performance by adapting the algorithm to the non-reciprocal components of static and dynamic channels remains a challenge. In this paper, we propose an adaptive multilevel quantisation approach that adjusts the size of the quantisation region to the channel responses’ non-reciprocity parameters, thus optimising the trade-off between the bit generation rate (BGR) and the bit mismatch rate (BMR). The probability of error has been theoretically formulated. Accordingly, the order of the quantisation process is adapted for acceptable mismatching probability. Moreover, simulation analysis is conducted to prove the ability of the proposed approach to provide flexible adaptation of the quantisation order at different signal-to-noise ratios (SNRs), achieving fast secret bit generation rates 1. 1$sim$2.85bits/packet at SNRs of 10$sim$25 dB for acceptable BMR $leq 0.1$.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116333196","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

Approximate Noise-Whitening in MIMO Detection via Banded-Inverse Extension 基于带逆扩展的MIMO检测中的近似噪声白化

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012712

Sha Hu, Hao Wang

引用次数: 0

Secrecy Performance of RIS-Aided Wireless Systems in the Presence of Mobile Interferers and Eavesdropper Mobility 存在移动干扰和窃听者移动时ris辅助无线系统的保密性能

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012999

Aman Sikri, Aashish Mathur

引用次数: 0

Real-Time Emotion Recognition Using Deep Learning Algorithms 使用深度学习算法的实时情绪识别

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012772

Abderrahmane El Mettiti, M. Oumsis, A. Chehri, Rachid Saadane

引用次数: 0

Underwater Optical Communication Module: An Extension to the ns-3 Network Simulator 水下光通信模块:ns-3网络模拟器的扩展

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012885

Rabia Qadar, Waleed Bin Qaim, Bo Tan, J. Nurmi

{"title":"Underwater Optical Communication Module: An Extension to the ns-3 Network Simulator","authors":"Rabia Qadar, Waleed Bin Qaim, Bo Tan, J. Nurmi","doi":"10.1109/VTC2022-Fall57202.2022.10012885","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012885","url":null,"abstract":"In the last decade, the field of wireless optical communication has gathered immense interest due to its adoption in growing bandwidth-hungry underwater applications. The expensive and non-standardized on-field research measurements call for a reliable simulation tool that allows researchers to realistically design and assess the performance of Underwater Optical Communication (UOC) systems before conducting actual underwater experiments. In this paper, we present a UOC module as an extension to the network simulator ns-3. The module can study the impact of different water conditions on underwater optical networks from the physical layer to the network layer. The proposed UOC module realizes physical layer models of the UOC channels where the added noise and interference effects are modeled as Additive White Gaussian Noise (AWGN). Results show the capability of our module to facilitate large underwater optical network design and optimization. Since ns-3 is an open-source software, the module has the flexibility and reusability to be further developed by the worldwide research community.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125678674","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