• 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

一种用于集成无线多媒体传感器和认知卫星网络的新型动态频谱共享方法。

A Novel Dynamic Spectrum-Sharing Method for Integrated Wireless Multimedia Sensors and Cognitive Satellite Networks.

机构信息

College of Communications Engineering, Army Engineering University of PLA, Nanjing 210007, China.

College of Telecommunications and Information Engineering, Nangjing University of Posts and Telecommunications, Nanjing 210003, China.

出版信息

Sensors (Basel). 2018 Nov 12;18(11):3904. doi: 10.3390/s18113904.

DOI:10.3390/s18113904
PMID:30424583
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6264101/
Abstract

With the growing demand, Wireless Multimedia Sensor Networks (WMSNs) play an increasingly important role, which enhances the capacity of typical Wireless Sensor Networks (WSNs). Additionally, integrating satellite systems into WMSNs brings about the beneficial synergy, especially in rural and sparsely populated areas. However, the available spectrum resource is scarce, which contradicts the high-speed content required for multimedia. Cognitive radio is a promising solution to address the conflict. In this context, we propose a novel spectrum-sharing method for the integrated wireless multimedia sensor and cognitive satellite network based on the dynamic frequency allocation. Specifically, the Low Earth Orbit (LEO) satellite system plays the role of the auxiliary to connect sensor nodes and the remote control host, and it shares the same frequency with the Geostationary Earth Orbit (GEO) system in the downlink. Because the altitudes of GEO and LEO satellites differ greatly, the beam size of GEO is much larger than that of LEO, which provides the opportunity for LEO beam to reuse the frequency that was allocated to the GEO beam. A keep-out region is defined to guarantee the spectral coexistence based on the interference analysis in the worst case. In addition, a dynamic frequency allocation algorithm is presented to deal with the dynamic configuration caused by the satellite motion. Numerical results demonstrate that the dynamic spectrum-sharing method can improve the throughput.

摘要

随着需求的增长,无线多媒体传感器网络(WMSNs)发挥着越来越重要的作用,增强了典型无线传感器网络(WSNs)的容量。此外,将卫星系统集成到 WMSNs 中带来了有益的协同作用,特别是在农村和人口稀少的地区。然而,可用的频谱资源稀缺,与多媒体所需的高速内容相矛盾。认知无线电是解决这一冲突的一种有前途的解决方案。在这种情况下,我们提出了一种基于动态频率分配的集成无线多媒体传感器和认知卫星网络的新型频谱共享方法。具体来说,低地球轨道(LEO)卫星系统充当辅助,连接传感器节点和远程控制主机,并在下行链路中与地球静止轨道(GEO)系统共享相同的频率。由于 GEO 和 LEO 卫星的高度差异很大,GEO 的波束尺寸比 LEO 的波束尺寸大得多,这为 LEO 波束提供了重用分配给 GEO 波束的频率的机会。基于最坏情况下的干扰分析,定义了一个禁止区域以确保频谱共存。此外,提出了一种动态频率分配算法来处理卫星运动引起的动态配置。数值结果表明,动态频谱共享方法可以提高吞吐量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/018b4ccaf572/sensors-18-03904-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/55d300cbe7db/sensors-18-03904-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/03092a8e649b/sensors-18-03904-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/3c7ef834c551/sensors-18-03904-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/3b2a917a6ede/sensors-18-03904-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/ba9bd6f318fd/sensors-18-03904-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/dade9bda8bdb/sensors-18-03904-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/a998196da02a/sensors-18-03904-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/ad59163900a6/sensors-18-03904-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/018b4ccaf572/sensors-18-03904-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/55d300cbe7db/sensors-18-03904-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/03092a8e649b/sensors-18-03904-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/3c7ef834c551/sensors-18-03904-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/3b2a917a6ede/sensors-18-03904-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/ba9bd6f318fd/sensors-18-03904-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/dade9bda8bdb/sensors-18-03904-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/a998196da02a/sensors-18-03904-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/ad59163900a6/sensors-18-03904-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bfe/6264101/018b4ccaf572/sensors-18-03904-g009.jpg

相似文献

1
A Novel Dynamic Spectrum-Sharing Method for Integrated Wireless Multimedia Sensors and Cognitive Satellite Networks.一种用于集成无线多媒体传感器和认知卫星网络的新型动态频谱共享方法。
Sensors (Basel). 2018 Nov 12;18(11):3904. doi: 10.3390/s18113904.
2
Sensing-Based Dynamic Spectrum Sharing in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.基于感知的集成无线传感器和认知卫星地面网络中的动态频谱共享。
Sensors (Basel). 2019 Dec 1;19(23):5290. doi: 10.3390/s19235290.
3
An Efficient Multi-Dimensional Resource Allocation Mechanism for Beam-Hopping in LEO Satellite Network.一种用于低地球轨道卫星网络中的跳波束的高效多维资源分配机制。
Sensors (Basel). 2022 Nov 29;22(23):9304. doi: 10.3390/s22239304.
4
Fractional Frequency Reuse Scheme for Device to Device Communication Underlaying Cellular on Wireless Multimedia Sensor Networks.无线多媒体传感器网络中蜂窝网络下设备到设备通信的分数频率复用方案。
Sensors (Basel). 2018 Aug 13;18(8):2661. doi: 10.3390/s18082661.
5
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.集成无线传感器与认知卫星地面网络中的节能最优功率分配
Sensors (Basel). 2017 Sep 4;17(9):2025. doi: 10.3390/s17092025.
6
Performance Analysis of Integrated Wireless Sensor and Multibeam Satellite Networks Under Terrestrial Interference.陆地干扰下集成无线传感器与多波束卫星网络的性能分析
Sensors (Basel). 2016 Oct 14;16(10):1711. doi: 10.3390/s16101711.
7
Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications.认知型低地球轨道卫星系统的资源分配:促进物联网通信。
Sensors (Basel). 2023 Apr 11;23(8):3875. doi: 10.3390/s23083875.
8
The CODYSUN Approach: A Novel Distributed Paradigm for Dynamic Spectrum Sharing in Satellite Communications.CODYSUN方法:一种用于卫星通信中动态频谱共享的新型分布式范式。
Sensors (Basel). 2021 Dec 2;21(23):8052. doi: 10.3390/s21238052.
9
Efficient Wideband Spectrum Sensing with Maximal Spectral Efficiency for LEO Mobile Satellite Systems.用于低地球轨道移动卫星系统的具有最大频谱效率的高效宽带频谱感知
Sensors (Basel). 2017 Jan 21;17(1):193. doi: 10.3390/s17010193.
10
Topology Abstraction-Based Routing Scheme for Secret-Key Provisioning in Hybrid GEO/LEO Quantum Satellite Networks.混合GEO/LEO量子卫星网络中基于拓扑抽象的密钥供应路由方案
Entropy (Basel). 2023 Jul 12;25(7):1047. doi: 10.3390/e25071047.

引用本文的文献

1
Cognitive Radio Strategy Combined with MODCOD Technique to Mitigate Interference on Low-Orbit Satellite Downlinks.结合MODCOD技术的认知无线电策略以减轻对低轨道卫星下行链路的干扰
Sensors (Basel). 2023 Aug 17;23(16):7234. doi: 10.3390/s23167234.
2
Resource Allocation for Cognitive LEO Satellite Systems: Facilitating IoT Communications.认知型低地球轨道卫星系统的资源分配:促进物联网通信。
Sensors (Basel). 2023 Apr 11;23(8):3875. doi: 10.3390/s23083875.

本文引用的文献

1
Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.集成无线传感器与认知卫星地面网络中的节能最优功率分配
Sensors (Basel). 2017 Sep 4;17(9):2025. doi: 10.3390/s17092025.
2
Performance Analysis of Integrated Wireless Sensor and Multibeam Satellite Networks Under Terrestrial Interference.陆地干扰下集成无线传感器与多波束卫星网络的性能分析
Sensors (Basel). 2016 Oct 14;16(10):1711. doi: 10.3390/s16101711.
3
Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.
应急场景下集成远程无线传感器与卫星网络的容量模型及约束分析
Sensors (Basel). 2015 Nov 17;15(11):29036-55. doi: 10.3390/s151129036.
4
Diversity Performance Analysis on Multiple HAP Networks.多跳接入点(HAP)网络的多样性性能分析
Sensors (Basel). 2015 Jun 30;15(7):15398-418. doi: 10.3390/s150715398.