Bandit based Dynamic Spectrum Anti-jamming Strategy in Software Defined UAV Swarm Network

被引：0

作者：

Qiu, Qiming ^{[1
]}

Li, Haitao ^{[2
]}

Zhang, Hao ^{[2
]}

Luo, Jiawei ^{[2
]}

机构：

[1] China Natl Aeronaut Radio Elect Inst, Shanghai, Peoples R China

[2] Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

来源：

PROCEEDINGS OF 2020 IEEE 11TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2020) | 2020年

关键词：

software defined network; UAV swarm; collision avoidance; kl-UCB++; multi-armed bandit; GAME;

D O I：

10.1109/icsess49938.2020.9237733

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, we explore the problem of bandit learning based dynamic spectrum anti-jamming (DSAJ) strategy for enabling reliable information transmission in software defined UAV swarm (SD-UAS) network. We first present UAV swarm network architecture based on software-defined networking (SDN) and describe the multiuser multi-armed bandit (MAB) based anti-jamming channel selection model for SD-UAS network. Then, we propose a collision avoidance (CA) kl-UCB++ channel selection strategy based on the prior spectrum sensing channel information. Simulation results validate that the cumulative regret and the collisions on available channels obtained with the proposed spectrum channel selection strategy outperform the well-known UCB.kl-UCB++ learning algorithm, which can effectively improve the anti-jamming ability of SD-UAV swarm in complicated electromagnetic jamming environment.

引用

页码：184 / 187

页数：4

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