基于宽频认知层叠网的海上跨域协同组网通信技术

李忠孝; 罗荣; 王刚; 张卫强

doi:10.11993/j.issn.2096-3920.2024-0036

基于宽频认知层叠网的海上跨域协同组网通信技术

doi: 10.11993/j.issn.2096-3920.2024-0036

1.
天津七一二通信广播股份有限公司, 天津, 300462
2.
中国人民解放军91054部队, 北京, 102442

详细信息

作者简介:
李忠孝(1977-), 男, 硕士, 工程师, 主要研究方向为数据链通信、认知无线电、无线数字孪生、空天地一体化信息网络等

中图分类号: TP393.08, TN915.04
计量
- 文章访问数: 4
- HTML全文浏览量: 1
- PDF下载量: 2
- 被引次数: 0
出版历程
- 收稿日期: 2024-02-29
- 修回日期: 2024-04-03
- 录用日期: 2024-04-07
- 网络出版日期: 2024-04-10

Broadband Cognitive Stacked Networks for the Cross Domain Decentralized Networking Communications at Sea

1.
Tianjin 712 Communication & Broadcasting Co., Ltd, Tianjin, 300462, China
2.
Unit 91054th, the Liberation Army of China, Beijing, 102442, China

摘要

摘要: 随着海上多平台远洋部署和强敌对抗形势日益严峻, 依托于短波、超短波、微波等单频段海上无线通信技术已不能满足海上跨域协同作战对多链融合组网、动态资源分配和体系化抗干扰的通信保障需求。文中提出一种基于宽频认知层叠网的新型多链融合网络通信架构, 采用综合射频一体化前端进行宽频带射频资源管理, 通过统一带宽、统一时隙、统一时空形成数据链融合元模型, 在此基础上采用软件通信体系后端进行多链融合和层叠组网, 通过宽带频谱感知、认知频谱接入和任务驱动自适应组网等技术实现对空海潜等海上多域通信环境的动态适应和强敌对抗环境的认知决策, 可提升海上通信网络扩展、跨域传输和抗干扰通信能力。文中对宽频认知层叠网的关键技术进行了深入研究, 给出了宽频认知层叠网的可行技术途径, 可为本领域的体系架构设计和技术研究提供参考借鉴。
- 海上分布式作战 /
- 软件通信体系架构 /
- 任务驱动自适应组网 /
- 宽频层叠网 /
- 认知频谱接入
Abstract: With the increasingly severe situation of enemy confrontation at sea, multi-platform deployment in deep ocean is needed. Maritime Wireless Communication relying on single band including HF、V/UHF and Microwave frequency can no longer meet the communication support needs of multiple datalink networking, flexible resource allocation, and systematic anti-interference for distributed maritime operations. This paper proposes a new network communication architecture based on broadband cognitive layered network to meet the requirements of multiple datalink networking communication technology in distributed maritime operations. The integrated RF front-end is used for broadband RF resource management, and the data link fusion meta model is formed by unifying bandwidth, time slot, and time and space. On this basis, a software communication system backend is adopted for multi chain fusion and layered networking. Through technologies such as broadband spectrum sensing, cognitive spectrum access, and task driven adaptive networking, dynamic adaptation to multi domain communication environments such as air, sea, and submarine is achieved, as well as cognitive decision-making in strong enemy adversarial environments. This can enhance the expansion, cross domain transmission, and anti-interference communication capabilities of maritime communication networks. This paper conducts in-depth research on the key technologies of broadband cognitive stacked networks, which can provide reference for the architecture design and technical research in the maritime communication field.
- Distributed maritime operations /
- Software communication architecture /
- Task driven networking /
- Broadband stacked networks /
- Cognitive spectrum access

HTML全文

图 1 航母编队远海作战概念图

Figure 1. Aircraft Carrier Formation for Deep-Sea Operations

下载: 全尺寸图片幻灯片

图 2 数据链元模型

Figure 2. Datalink Meta Model

下载: 全尺寸图片幻灯片

图 3 宽频认知层叠网

Figure 3. Broadband Cognitive Overlay Networks

下载: 全尺寸图片幻灯片

图 4 任务驱动自适应组网

Figure 4. Task Driven Adaptive Networking

下载: 全尺寸图片幻灯片

图 5 多链融合组网能力框架

Figure 5. Multiple Datalink Fusion Capability Framework

下载: 全尺寸图片幻灯片

图 6 软件通信体系架构

Figure 6. Software Communication Architecture

下载: 全尺寸图片幻灯片

图 7 TC-OFDM信号产生框图

Figure 7. TC-OFDM Signal Generation

下载: 全尺寸图片幻灯片

图 8 TSPMA多址接入

Figure 8. Timing Statistical Priority Multiple Access

下载: 全尺寸图片幻灯片

图 9 认知频谱接入

Figure 9. Cognitive Spectrum Access

下载: 全尺寸图片幻灯片

图 10 任务驱动网络过程

Figure 10. Task Driven Networking Process

下载: 全尺寸图片幻灯片

图 11 体系能力清单

Figure 11. System Capability List

下载: 全尺寸图片幻灯片

图 12 作战单元消息转换

Figure 12. Combat Unit Message Transformation

下载: 全尺寸图片幻灯片

图 13 系统通信能力描述

Figure 13. System Communication Capability Description

下载: 全尺寸图片幻灯片

表 1 典型海上跨域协同组网通信能力需求

军种	平台类型	网络数量	作战距离	是否需要编队协同	通信距离	区域拒止抗干扰能力	交互业务	时延	通信手段
空军	预警机	2~6	以基地为中心5 000 km	否	5 000 km	强抗干扰	话音、数据、图片、视频	秒级、毫秒级	卫通、短波、超短波
空军	战斗机	100~200	以基地为中心1 500 km	是	3 000 km	强抗干扰	话音、数据、图片、视频	秒级、毫秒级	短波、超短波
海军	航母	1~2	以任务为中心, 全海域	否	全海域	强抗干扰	话音、数据、图片、视频	秒级、毫秒级	卫通、短波、超短波
	舰载机	24~48	以航母为中心500 km	是	500 km	强抗干扰	话音、数据、图片、视频	秒级、毫秒级	短波、超短波
	直升机	12~24		是	500 km	强抗干扰	话音、数据、图片、视频	秒级、毫秒级	短波、超短波
	舰艇	7~14		是	100 km	强抗干扰	话音、数据、图片、视频	秒级、毫秒级	卫通、短波、超短波
	潜艇	1~6	以任务为中心, 全海域	否	全海域	强抗干扰	话音、数据、图片	秒级、毫秒级	水声、短波
火箭军	导弹	1~16	2 500 km	是	2 500 km	强抗干扰	数据、图片	秒级、毫秒级	弹载链
总容量		300~400

下载: 导出CSV

参考文献(25)

[1]	齐嘉兴, 杨继坤. 美军作战概念发展及其逻辑[J]. 战术导弹技术, 2022(1): 97-105. Qi Jiaxing, Yang Jikun. The development and logic of US military operation concepts[J]. Tactical Missile Technology, 2022(1): 97-105.
[2]	赵新路, 韩志强, 李兵, 等. 美军分布式作战体系及实战化运用发展分析[J]. 中国电子科学研究院学报, 2022, 17(2): 149-154. doi: 10.3969/j.issn.1673-5692.2022.02.008 Zhao Xinlu, Han Zhiqiang, Li Bing, et al. Analysis of the u. s. Military’s distributed combat system and actual combat application development[J]. Journal of CAEIT, 2022, 17(2): 149-154. doi: 10.3969/j.issn.1673-5692.2022.02.008
[3]	初军田, 张武, 丁超, 等. 跨域无人系统协同作战需求分析[J]. 指挥信息系统与技术, 2022, 13(6): 1-8. Chu Juntian, Zhang Wu, Ding Chao, et al. Requirement analysis on cross-domain unmanned system cooperative operation[J]. Command Information System and Technology, 2022, 13(6): 1-8.
[4]	全杰, 贺庆. 跨域融合机理与运用研究[J]. 中国电子科学研究院学报, 2021, 16(12): 1205-1214. doi: 10.3969/j.issn.1673-5692.2021.12.005 Quan Jie, He Qing. Research on mechanism and application of cross-domain synergy[J]. Journal of CAEIT, 2021, 16(12): 1205-1214. doi: 10.3969/j.issn.1673-5692.2021.12.005
[5]	Trendler, D., & Jonsson, C. The joint all-domain command and control (JADC2)–Enabler for future multi-domain operations[J]. Journal of Strategic Studies, 2020, 43(2): 265-291.
[6]	Munro, J. Distributed maritime operations and network-centric warfare[J]. International Journal of Maritime Security, 2019, 30(2): 213-227.
[7]	Broyan, J. L., Jr., & Gumata, R. T. Distributed kill chains: Enabling the fight through multi-domain operations[J]. Joint Forces Quarterly, 2018, 81(1): 42-49.
[8]	Hoffman, D. T., & Reimers, H. The evolution of the distributed kill chain: Adapting to the multi-domain battle space[J]. Military Technology, 2021, 45(4): 34-43.
[9]	Brown, C. M., & Kime, E. M. Naval integrated fire control-air defense: A comprehensive approach to maritime air defense[J]. Journal of Military Operations, 2018, 6(1): 1-16.
[10]	Brown, C. M., & Johnson, J. A. Advanced naval weapons systems and targeting: The impact of technology on maritime operations[J]. International Journal of Naval History, 2019, 27(2): 145-162.
[11]	付彩越. 美国海军新概念武器现状和发展[J]. 舰船科学技术, 2017(2): 151-154. doi: 10.3404/j.issn.1672-7619.2017.02.030 Fu Caiyue. US Navy new concept weapon status and development trend[J]. Ship Science and Technology, 2017(2): 151-154. doi: 10.3404/j.issn.1672-7619.2017.02.030
[12]	易亮, 陆杨. 美国海军分布式杀伤概念的装备技术支撑[J]. 海军工程大学学报, 2018, 15(2): 36-40. Yi Liang, Lu Yang. United States navy equipment technology for “Distributed Lethality” concept[J]. Journal of Naval University of Engineering, 2018, 15(2): 36-40.
[13]	Mané, E. P., & Agostini, D. Mosaic Warfare: The next generation of cyber operations[J]. Journal of Cybersecurity, 2018, 4(2): 131-140.
[14]	张杰勇, 钟赟, 孙鹏, 马晋哲. 有人/无人机协同作战指挥控制系统技术[J]. 指挥与控制学报, 2021, 7(2): 203-214. doi: 10.3969/j.issn.2096-0204.2021.02.0203 Zhang Jieyong, Zhong Yun, Sun Peng, et al. Command and control system and technology for manned-unmanned aerial vehicle cooperative operation[J]. Journal of Command and Control, 2021, 7(2): 203-214. doi: 10.3969/j.issn.2096-0204.2021.02.0203
[15]	吴立尧, 韩维, 张勇, 等. 有人/无人机编队指挥控制系统结构设计[J]. 系统工程与电子技术, 2020, 42(8): 1826-1834. Wu Liyao, Han Wei, Zhang Yong, et al. Structure design of command and control system for manned-unmanned aerial vehicles formation[J]. System Engineering and Electronics, 2020, 42(8): 1826-1834.
[16]	易侃, 钟元芾, 等. 联合全域指挥与控制机理模型及应用分析[J]. 指挥与控制学报, 2022, 8(1): 1-13. Yi Kan, Zhong Yuanfu, et al. Mechanism model and application analysis of joint all-domain command and control[J]. Journal of Command and Control, 2022, 8(1): 1-13.
[17]	陈志新, 徐劢, 高鑫, 等. 美军联合全域指挥控制研究与启示[C]//中国指挥与控制学会. 第九届中国指挥控制大会论文集. 中国电子科技集团公司第二十八研究所联合作战指挥系统技术及应用重点实验室;南京, 2021: 144-149. .
[18]	张维明, 黄松平, 黄金才等. 多域作战及其指挥控制问题探析[J]. 指挥信息系统与技术, 2020, 11(1): 1-6. Zhang Weiming, Huang Songping, Huang Jincai, et al. Analysis on multi-domain operation and its command and control problems[J]. Command Information System and Technology, 2020, 11(1): 1-6.
[19]	HITCHENS T. Army’s Project Convergence tested space links for TITAN targeting system [EB/OL]. [2022-11-19]. https://breakingdefense.com/2022/11/armys-project-convergence-tested-space-links-for-titan-targeting-system/.
[20]	赵小璞, 谭志强. 基于软件通信体系架构的短波波形设计与实现[J]. 电子技术, 2022, 51(10): 22-23. Zhao Xiaopu, Tan Zhiqiang. Design and implementation of HF communication system based on software communications architecture[J]. Electronics, 2022, 51(10): 22-23.
[21]	王兆祺, 徐然, 公佳龙, 等. 通信导航一体化波形关键技术及研究进展[J]. 无线电通信技术, 2023, 49(5): 853-864. doi: 10.3969/j.issn.1003-3114.2023.05.010 Wang Zhaoqi, Xu Ran, Gong Jialong, et al. Key technologies and research progress of integrated communication and navigation waveform design[J]. Radio Communications Technology, 2023, 49(5): 853-864. doi: 10.3969/j.issn.1003-3114.2023.05.010
[22]	杨志明, 李金喜, 张亦居. 基于跨层信道感知的 SPMA 协议自适应阈值算法[J]. 航空电子技术, 2023, 54(2): 39-44. Yang Zhiming, Li Jinxi, Zhang Yiju. Adaptive threshold algorithm based on the cross-layer channel awareness for SPMA protocol[J]. Avionics Technology, 2023, 54(2): 39-44.
[23]	侯征军, 姚智, 杨涛, 等. 基于深度强化学习的能量采集认知无线电动态频谱接入[J]. 无线电通信技术, 2023, 49(2): 239-247. Hou Zhengjun, Yao Zhi, Yang Tao, et al. Dynamic Spectrum Access For Cognitive Radio With Energy Harvesting Based On Deep Reinforcement Learning[J]. Radio Communications Technology, 2023, 49(2): 239-247.
[24]	Verma K, Bharti M R. Energy-efficient resource allocation in cognitive radio networks[C]// Proc of International Conference on Frontiers of Intelligent Computing: Theory and Applications. Singapore: Springer, 2022: 137-150.
[25]	林娣娜. 面向任务驱动的无人机自组网智能路由算法 [D]. 成都: 电子科技大学, 2023.