• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

莱斯衰落信道上非正交多址接入增强型自主飞行器辅助车联网的性能分析

Performance Analysis of Non-Orthogonal Multiple Access-Enhanced Autonomous Aerial Vehicle-Assisted Internet of Vehicles over Rician Fading Channels.

作者信息

Zhang Zheming, He Yixin, Lei Yifan, Cai Zehui, Huang Fanghui, Zhao Xingchen, Wang Dawei, Li Lujuan

机构信息

College of Information Science and Engineering, Jiaxing University, Jiaxing 314001, China.

Sino-European Joint Lab for Health Information Processing and Applications, Jiaxing University, Jiaxing 314001, China.

出版信息

Entropy (Basel). 2025 Aug 27;27(9):907. doi: 10.3390/e27090907.

DOI:10.3390/e27090907
PMID:41008032
Abstract

The increasing number of intelligent connected vehicles (ICVs) is leading to a growing scarcity of spectrum resources for the Internet of Vehicles (IoV), which has created an urgent need for the use of full-duplex non-orthogonal multiple access (FD-NOMA) techniques in vehicle-to-everything (V2X) communications. Meanwhile, for the flexibility of autonomous aerial vehicles (AAVs), V2X communications assisted by AAVs are regarded as a potential solution to achieve reliable communication between ICVs. However, if the integration of FD-NOMA and AAVs can satisfy the requirements of V2X communications, then quickly and accurately analyzing the total achievable rate becomes a challenge. Motivated by the above, an accurate analytical expression for the total achievable rate over Rician fading channels is proposed to evaluate the transmission performance of NOMA-enhanced AAV-assisted IoV with imperfect channel state information (CSI). Then, we derive an approximate expression with the truncated error, based on which the closed-form expression for the approximate error is theoretically provided. Finally, the simulation results demonstrate the accuracy of the obtained approximate results, where the maximum approximate error does not exceed 0.5%. Moreover, the use of the FD-NOMA technique in AAV-assisted IoV can significantly improve the total achievable rate compared to existing work. Furthermore, the influence of key network parameters (e.g., the speed and Rician factor) on achievable rate is thoroughly discussed.

摘要

智能网联汽车(ICV)数量的不断增加,导致车联网(IoV)的频谱资源日益稀缺,这使得在车与万物(V2X)通信中迫切需要使用全双工非正交多址接入(FD-NOMA)技术。同时,考虑到自主飞行器(AAV)的灵活性,由AAV辅助的V2X通信被视为实现ICV之间可靠通信的一种潜在解决方案。然而,如果FD-NOMA与AAV的集成能够满足V2X通信的要求,那么快速准确地分析总可达速率就成为一项挑战。受上述因素的启发,本文提出了一种在莱斯衰落信道上总可达速率的精确解析表达式,用于评估信道状态信息(CSI)不完善时非正交多址接入增强型AAV辅助车联网的传输性能。然后,我们推导了一个带有截断误差的近似表达式,并在此基础上从理论上给出了近似误差的闭式表达式。最后,仿真结果验证了所获近似结果的准确性,其中最大近似误差不超过0.5%。此外,与现有工作相比,在AAV辅助车联网中使用FD-NOMA技术可显著提高总可达速率。此外,还深入讨论了关键网络参数(如速度和莱斯因子)对可达速率的影响。

相似文献

1
Performance Analysis of Non-Orthogonal Multiple Access-Enhanced Autonomous Aerial Vehicle-Assisted Internet of Vehicles over Rician Fading Channels.莱斯衰落信道上非正交多址接入增强型自主飞行器辅助车联网的性能分析
Entropy (Basel). 2025 Aug 27;27(9):907. doi: 10.3390/e27090907.
2
Vesicoureteral Reflux膀胱输尿管反流
3
Prescription of Controlled Substances: Benefits and Risks管制药品的处方:益处与风险
4
Shoulder Arthrogram肩关节造影
5
Mid Forehead Brow Lift额中眉提升术
6
Edge computing for Vehicle to Everything: a short review.车对一切的边缘计算:一个简短的回顾。
F1000Res. 2023 Nov 10;10:1104. doi: 10.12688/f1000research.73269.4. eCollection 2021.
7
Anterior Approach Total Ankle Arthroplasty with Patient-Specific Cut Guides.使用患者特异性截骨导向器的前路全踝关节置换术。
JBJS Essent Surg Tech. 2025 Aug 15;15(3). doi: 10.2106/JBJS.ST.23.00027. eCollection 2025 Jul-Sep.
8
Integrated neural network framework for multi-object detection and recognition using UAV imagery.用于使用无人机图像进行多目标检测与识别的集成神经网络框架。
Front Neurorobot. 2025 Jul 30;19:1643011. doi: 10.3389/fnbot.2025.1643011. eCollection 2025.
9
Optimizing IoV cloud trust with adaptive blockchain and reinforcement learning.
Sci Rep. 2025 Sep 25;15(1):32850. doi: 10.1038/s41598-025-00951-1.
10
Data prioritization aware resource allocation in internet of vehicles using multi-agent deep reinforcement learning.基于多智能体深度强化学习的车联网中数据优先级感知资源分配
Neural Netw. 2025 Oct;190:107671. doi: 10.1016/j.neunet.2025.107671. Epub 2025 Jun 6.

本文引用的文献

1
Deep Reinforcement Learning-Based Resource Allocation for UAV-GAP Downlink Cooperative NOMA in IIoT Systems.基于深度强化学习的工业物联网系统中无人机辅助分组接入下行链路协作非正交多址接入资源分配
Entropy (Basel). 2025 Jul 29;27(8):811. doi: 10.3390/e27080811.
2
Research on Computation Offloading and Resource Allocation Strategy Based on MADDPG for Integrated Space-Air-Marine Network.基于多智能体深度确定性策略梯度算法的空天海一体化网络计算卸载与资源分配策略研究
Entropy (Basel). 2025 Jul 28;27(8):803. doi: 10.3390/e27080803.
3
Error-Constrained Entropy-Minimizing Strategies for Multi-UAV Deception Against Networked Radars.
用于多无人机对网络化雷达欺骗的误差约束熵最小化策略
Entropy (Basel). 2025 Jun 18;27(6):653. doi: 10.3390/e27060653.
4
A Survey on Semantic Communications in Internet of Vehicles.车联网中的语义通信研究
Entropy (Basel). 2025 Apr 20;27(4):445. doi: 10.3390/e27040445.