集成认知共生计算和环境反向散射通信网络

IF 7.4 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-08-06 DOI:10.1109/TCCN.2024.3439628
Chao Ren;Yanglin Hu;Lei Sun;Haojin Li;Chen Sun;Haijun Zhang;Arumugam Nallanathan;Victor C. M. Leung
{"title":"集成认知共生计算和环境反向散射通信网络","authors":"Chao Ren;Yanglin Hu;Lei Sun;Haojin Li;Chen Sun;Haijun Zhang;Arumugam Nallanathan;Victor C. M. Leung","doi":"10.1109/TCCN.2024.3439628","DOIUrl":null,"url":null,"abstract":"Ambient backscatter communication (AmBC) possesses signal reception and energy-harvesting capabilities, allowing providing wireless cognition through simple energy detection. In typical applications like industrial Internet of Things (IoT), cognitive AmBC (CAmBC) networks are required to offer passive communication, edge computing, and cognition capabilities. However, passive communication relies on the environment and has limited computing power, creating interdependencies among spectrum sensing, networking, and computational cognition. Moreover, the heterogeneous evaluation metrics for communication and computation make unified planning and management challenging. Therefore, this paper proposes the integrated cognitive symbiotic computing-AmBC (CSC-AmBC) based on symbiotic communication and cognitive radio. CSC-AmBC integrates AmBC communication and computational cognition capabilities in a task-oriented manner, sharing proximity and AmBC computing and communication (ACC) resources among primary and secondary tasks. Meta-Link with Tokens and two cognitive ACC reuse models is used to facilitate integration and enhance task execution efficiency, which introduces Places to accommodate the heterogeneous and variable ACC resources. Additionally, the task execution gain metric is introduced to evaluate the multi-task ACC resource utilization. Numerical results validate the cognition networking and the advantage of the proposed task execution gain of CSC-AmBC.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":null,"pages":null},"PeriodicalIF":7.4000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated Cognitive Symbiotic Computing and Ambient Backscatter Communication Network\",\"authors\":\"Chao Ren;Yanglin Hu;Lei Sun;Haojin Li;Chen Sun;Haijun Zhang;Arumugam Nallanathan;Victor C. M. Leung\",\"doi\":\"10.1109/TCCN.2024.3439628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ambient backscatter communication (AmBC) possesses signal reception and energy-harvesting capabilities, allowing providing wireless cognition through simple energy detection. In typical applications like industrial Internet of Things (IoT), cognitive AmBC (CAmBC) networks are required to offer passive communication, edge computing, and cognition capabilities. However, passive communication relies on the environment and has limited computing power, creating interdependencies among spectrum sensing, networking, and computational cognition. Moreover, the heterogeneous evaluation metrics for communication and computation make unified planning and management challenging. Therefore, this paper proposes the integrated cognitive symbiotic computing-AmBC (CSC-AmBC) based on symbiotic communication and cognitive radio. CSC-AmBC integrates AmBC communication and computational cognition capabilities in a task-oriented manner, sharing proximity and AmBC computing and communication (ACC) resources among primary and secondary tasks. Meta-Link with Tokens and two cognitive ACC reuse models is used to facilitate integration and enhance task execution efficiency, which introduces Places to accommodate the heterogeneous and variable ACC resources. Additionally, the task execution gain metric is introduced to evaluate the multi-task ACC resource utilization. Numerical results validate the cognition networking and the advantage of the proposed task execution gain of CSC-AmBC.\",\"PeriodicalId\":13069,\"journal\":{\"name\":\"IEEE Transactions on Cognitive Communications and Networking\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Cognitive Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10623808/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cognitive Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10623808/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

环境反向散射通信(AmBC)具有信号接收和能量收集功能,可通过简单的能量检测提供无线认知。在工业物联网(IoT)等典型应用中,认知 AmBC(CAmBC)网络需要提供被动通信、边缘计算和认知功能。然而,无源通信依赖于环境,计算能力有限,这就造成了频谱传感、网络和计算认知之间的相互依存关系。此外,由于通信和计算的评价指标不尽相同,统一规划和管理具有挑战性。因此,本文提出了基于共生通信和认知无线电的集成认知共生计算-AmBC(CSC-AmBC)。CSC-AmBC 以任务为导向的方式整合了 AmBC 通信和计算认知能力,在主要任务和次要任务之间共享近距离和 AmBC 计算与通信(ACC)资源。元链接(Meta-Link)与令牌和两种认知 ACC 重用模型被用来促进整合和提高任务执行效率,其中引入了适应异构和可变 ACC 资源的 Places。此外,还引入了任务执行增益指标来评估多任务 ACC 资源利用率。数值结果验证了 CSC-AmBC 的认知网络和拟议任务执行增益的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Integrated Cognitive Symbiotic Computing and Ambient Backscatter Communication Network
Ambient backscatter communication (AmBC) possesses signal reception and energy-harvesting capabilities, allowing providing wireless cognition through simple energy detection. In typical applications like industrial Internet of Things (IoT), cognitive AmBC (CAmBC) networks are required to offer passive communication, edge computing, and cognition capabilities. However, passive communication relies on the environment and has limited computing power, creating interdependencies among spectrum sensing, networking, and computational cognition. Moreover, the heterogeneous evaluation metrics for communication and computation make unified planning and management challenging. Therefore, this paper proposes the integrated cognitive symbiotic computing-AmBC (CSC-AmBC) based on symbiotic communication and cognitive radio. CSC-AmBC integrates AmBC communication and computational cognition capabilities in a task-oriented manner, sharing proximity and AmBC computing and communication (ACC) resources among primary and secondary tasks. Meta-Link with Tokens and two cognitive ACC reuse models is used to facilitate integration and enhance task execution efficiency, which introduces Places to accommodate the heterogeneous and variable ACC resources. Additionally, the task execution gain metric is introduced to evaluate the multi-task ACC resource utilization. Numerical results validate the cognition networking and the advantage of the proposed task execution gain of CSC-AmBC.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
期刊最新文献
A Self-Supervised-Based Approach of Specific Emitter Identification for the Automatic Identification System SAMS-GNN: Self-Adaptive Multi-Scale Graph Neural Network for Multi-Band Spectrum Prediction A Lightweight Learning Framework for Packet Loss Concealment and Speech Enhancement Semantic Information Extraction and Multi-Agent Communication Optimization Based on Generative Pre-Trained Transformer U-shaped Error Correction Code Transformers
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1