{"title":"基于超前业务质量通知的V2N上行通信自适应传输暂停","authors":"Ryoichi Hasegawa, E. Okamoto","doi":"10.3390/vehicles5010012","DOIUrl":null,"url":null,"abstract":"There are levels of automation in autonomous driving, and each level requires different performances of wireless communication, such as quality, delay time, and throughput. Therefore, the vehicle is required to adaptively control the level of automation when the performance of the wireless communication changes. In particular, it is essential to have a sufficient in-advance time for changing the level of automation. To ensure this time, an in-advance quality of service notification (IQN) has been considered in the fifth-generation mobile communications system (5G) standardization groups, in which predictive information about the quality of service is provided to vehicles from base stations. However, any specific utilizations of IQN for quality enhancement of wireless transmission were not considered. Therefore, in this study, we assume IQN as a prediction of throughput value and propose an improvement scheme for the uplink vehicle-to-network communication by distributing the traffic load and reducing the congestion of base stations. The effectiveness of the proposed scheme is evaluated via the summation of transmitted bits and counts when the target base stations connected by the target vehicles are fully loaded. The numerical results show that the proposed scheme realizes the reduction of network congestion without degrading the throughput performances of the vehicles.","PeriodicalId":73282,"journal":{"name":"IEEE Intelligent Vehicles Symposium. IEEE Intelligent Vehicles Symposium","volume":"47 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Transmission Suspension of V2N Uplink Communication Based on In-Advanced Quality of Service Notification\",\"authors\":\"Ryoichi Hasegawa, E. Okamoto\",\"doi\":\"10.3390/vehicles5010012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are levels of automation in autonomous driving, and each level requires different performances of wireless communication, such as quality, delay time, and throughput. Therefore, the vehicle is required to adaptively control the level of automation when the performance of the wireless communication changes. In particular, it is essential to have a sufficient in-advance time for changing the level of automation. To ensure this time, an in-advance quality of service notification (IQN) has been considered in the fifth-generation mobile communications system (5G) standardization groups, in which predictive information about the quality of service is provided to vehicles from base stations. However, any specific utilizations of IQN for quality enhancement of wireless transmission were not considered. Therefore, in this study, we assume IQN as a prediction of throughput value and propose an improvement scheme for the uplink vehicle-to-network communication by distributing the traffic load and reducing the congestion of base stations. The effectiveness of the proposed scheme is evaluated via the summation of transmitted bits and counts when the target base stations connected by the target vehicles are fully loaded. The numerical results show that the proposed scheme realizes the reduction of network congestion without degrading the throughput performances of the vehicles.\",\"PeriodicalId\":73282,\"journal\":{\"name\":\"IEEE Intelligent Vehicles Symposium. IEEE Intelligent Vehicles Symposium\",\"volume\":\"47 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Intelligent Vehicles Symposium. IEEE Intelligent Vehicles Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/vehicles5010012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Intelligent Vehicles Symposium. IEEE Intelligent Vehicles Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/vehicles5010012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Transmission Suspension of V2N Uplink Communication Based on In-Advanced Quality of Service Notification
There are levels of automation in autonomous driving, and each level requires different performances of wireless communication, such as quality, delay time, and throughput. Therefore, the vehicle is required to adaptively control the level of automation when the performance of the wireless communication changes. In particular, it is essential to have a sufficient in-advance time for changing the level of automation. To ensure this time, an in-advance quality of service notification (IQN) has been considered in the fifth-generation mobile communications system (5G) standardization groups, in which predictive information about the quality of service is provided to vehicles from base stations. However, any specific utilizations of IQN for quality enhancement of wireless transmission were not considered. Therefore, in this study, we assume IQN as a prediction of throughput value and propose an improvement scheme for the uplink vehicle-to-network communication by distributing the traffic load and reducing the congestion of base stations. The effectiveness of the proposed scheme is evaluated via the summation of transmitted bits and counts when the target base stations connected by the target vehicles are fully loaded. The numerical results show that the proposed scheme realizes the reduction of network congestion without degrading the throughput performances of the vehicles.