Study of Anti-jamming Decision for Multi-channel Routing in Finite Buffer

XU Jiang; REN Guochun; XU Yifan; XU Yuhua; GONG Yuping; ZHENG Xueqiang; CUI Li; HAN Hao

doi:10.12382/bgxb.2025.0409

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Study of Anti-jamming Decision for Multi-channel Routing in Finite Buffer

更新时间：2026-04-24

- Study of Anti-jamming Decision for Multi-channel Routing in Finite Buffer
- Acta Armamentarii Vol. 47, Issue 3, Pages: 250409(2026)
- 作者机构：
  
  陆军工程大学通信工程学院，江苏南京 210000
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2025.0409
  CLC： TN918.91
- Received：27 May 2025，
  
  Online First：25 December 2025，
  
  Published：2026-03
- 稿件说明：
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XU Jiang, REN Guochun, XU Yifan, et al. Study of Anti-jamming Decision for Multi-channel Routing in Finite Buffer[J]. Acta Armamentarii, 2026, 47(3): 250409.
DOI：

XU Jiang, REN Guochun, XU Yifan, et al. Study of Anti-jamming Decision for Multi-channel Routing in Finite Buffer[J]. Acta Armamentarii, 2026, 47(3): 250409. DOI： 10.12382/bgxb.2025.0409.

摘要

由于节点缓冲区有限且无线信道开放易受干扰，关键节点在承担多路数据转发任务时易发生缓冲区溢出和链路中断，加剧网络拥堵。以多源并发下无线自组织网络的多信道路由抗干扰问题为研究对象，提出一种面向有限缓冲区的多信道路由抗干扰决策方法，旨在解决动态干扰和高负载环境下的路由规划、信道选择以及拥塞控制的协同优化问题。将路由规划与信道决策问题建模为部分可观测随机博弈模型，提出基于分层深度Q学习的多信道路由抗干扰决策算法：上层网络基于邻居缓冲区状态与目的地址优化路由路径以避免拥塞，下层网络结合路由决策与频谱感知结果动态规避干扰信道，通过融合跳数代价、拥塞惩罚与干扰规避的奖励函数设计，实现路由与抗干扰信道接入的协同优化。仿真结果表明，相较于对比算法，新算法在数据包传输成功率方面提升15%，有效增强了无线自组织网络在干扰环境下的可靠性和抗干扰能力。

Abstract

This paper investigates the anti-jamming problem of multi-channel routing in wireless ad hoc networks . Due to finite node buffers and open wireless channels that are susceptible to jamming

the critical nodes are prone to buffer overflow and link interruption when undertaking the multi-path data forwarding tasks

thereby exacerbating network congestion. To this end

a finite buffer-oriented multi-channel routing anti-jamming decision-making method is proposed to achieve the co-optimization of route planning

channel selection and congestion control in dynamic jamming and high load environments. The route planning and channel decision-making problems are modeled as a partially observable stochastic game model. A multi-channel routing anti-jamming decision-making algorithm based on hierarchical deep Q-learning is proposed:the upper layer network optimizes the routing paths based on the neighbor buffer states and destination addresses to avoid congestion

the lower layer network combines the routing decision-making with the spectrum sensing results to dynamically avoid jamming channels. The cooperative optimization of routing and anti-jamming channel access is realized by designing a reward function that combines hop cost

congestion penalty and jamming avoidance. Simulated results show that the proposed algorithm improves the success rate of packet transmission by 15%

which effectively enhances the reliability and anti-jamming capability of wireless ad hoc network in the jamming environment

compared with other related algorithms.

关键词

Keywords

references

CUI Y J, TIAN H, CHEN C J, et al. New geographical routing protocol for three-dimensional flying ad-hoc network based on new effective transmission range[J]. IEEE Transactions on Vehicular Technology,2023,72(12):16135-16147.

FAN B, SU Z X, CHEN Y Y, et al. Ubiquitous control over heterogeneous vehicles:a digital twin empowered edge AI approach[J]. IEEE Wireless Communications,2023,30(1):166-173.

李军,陈士超.无人机蜂群关键技术发展综述[J].兵工学报, 2023,44(9):2533-2545.

LI J,CHEN S C. A review on the development of key technology of UAV swarm[J]. Acta Armamentarii,2023,44(9):2533-2545. (in Chinese)

FLOYD S,FALL K. Promoting the use of end-to-end congestion control in the Internet[J]. IEEE/ACM Transactions on Networking,1999,7(4):458-472.

高曌,王亚琼,曾骏杰,等.天基自组织网络分布式抗毁路由算法设计与研究[J].兵工学报,2022,43(增刊2):126-132.

GAO Z, WANG Y Q, ZENG J J, et al. Design and research on distributed destruction-resistant routing algorithm for space-based self-organized networks[J]. Acta Armamentarii,2022,43(S2):126-132. (in Chinese)

RYU J, KIM S. Reputation-based opportunistic routing protocol using Q-learning for MANET attacked by malicious nodes[J]. IEEE Access,2023,11:47701-47711.

WANG X M,WANG J L,XU Y H,et al. Dynamic spectrum anti-jamming communications:challenges and opportunities[J]. IEEE Communications Magazine,2020,58(2):79-85.

邓鑫源.卫星网络拥塞控制技术研究[D].北京：北京邮电大学,2024.

DENG X Y. Research on congestion control technology for satellite networks[D]. Beijing: Beijing University of Posts and Telecommunications,2024. (in Chinese)

QUY V K, BAN N T, ANH D V, et al. An adaptive gateway selection mechanism for MANET-IoT applications in 5G networks[J]. IEEE Sensors Journal,2023,23(19):23704-23712.

吕文红,屈衍玺,徐锋,等.车载自组织网络中AODV协议研究进展[J].山东科技大学学报(自然科学版),2021,40(3):105-115.

LÜ W H,QU Y X,XU F, et al. Research progress of AODV protocol in vehicular ad hoc networks[J]. Journal of Shandong University of Science and Technology (Natural Science),2021, 40(3):105-115. (in Chinese)

ADIL M,USMAN M,JAN M A,et al. An improved congestion-controlled routing protocol for IoT applications in extreme environments[J]. IEEE Internet of Things Journal,2024,11(3):3757-3767.

ZENATI D,MAIMON T,COHEN K. RRO:a regularized routing optimization algorithm for enhanced throughput and low latency with efficient complexity[J]. IEEE Journal on Selected Areas in Communications,2025,43(2):437-447.

LE L B,MODIANO E,SHROFF N B. Optimal control of wireless networks with finite buffers[J]. IEEE/ACM Transactions on Networking,2012,20(4):1316-1329.

曹子建,孙泽龙,闫国闯,等.基于强化学习的无人机集群对抗策略推演仿真[J].兵工学报,2023,44(增刊S2):126-134.

CAO Z J, SUN Z L, YAN G C, et al. Reinforcement learning based simulation of UAV cluster confrontation strategy[J]. Acta Armamentarii,2023,44(S2):126-134. (in Chinese)

HAN C, NIU Y T, PANG T Y, et al. Intelligent anti-jamming communication based on the modified Q-learning[J]. Procedia Computer Science,2018,131:1023-1031.

HAN C, HUO L Y, TONG X H, et al. Spatial anti-jamming scheme for internet of satellites based on the deep reinforcement learning and Stackelberg game[J]. IEEE Transactions on Vehicular Technology,2020,69(5):5331-5342.

OKINE A A, ADAM N, NAEEM F, et al. Multi-agent deep reinforcement learning for packet routing in tactical mobile sensor networks[J]. IEEE Transactions on Network and Service Management,2024,21(2):2155-2169.

LI Y Y,XU Y H,XU Y T,et al. Dynamic spectrum anti-jamming in broadband communications:a hierarchical deep reinforcement learning approach[J]. IEEE Wireless Communications Letters, 2020,9(10):1616-1619.

LAN X L,CHEN Q C,CAI L,et al. Buffer-aided adaptive wireless powered communication network with finite energy storage and data buffer[J]. IEEE Transactions on Wireless Communications, 2019,18(12):5764-5779.

罗俊仁,张万鹏,苏炯铭,等.多智能体博弈学习研究进展[J].系统工程与电子技术,2024,46(5):1628-1655.

LUO J R, ZHANG W P, SU J M, et al. Research progress on multi-agent game learning[J]. Systems Engineering and Electronics,2024,46(5):1628-1655. (in Chinese)

HAN H,XU Y H,LI W,et al. Robust spectrum access scheme against diverse jamming policies:a prioritized fictitious rival-play-based approach[J]. IEEE Internet of Things Journal, 2025, 12(1):1-17.

HE K M, SUN J. Convolutional neural networks at constrained time cost[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Boston, MA, US: IEEE, 2015:5353-5360.

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