Research on Narrowband Interference Suppression Technology of UAV Network Based on Spread Spectrum Communication

Tan, Xiaopeng; Su, Shaojing; Sun, Xiang

doi:10.1109/icaiis49377.2020.9194891

Cited by 9 publications

(4 citation statements)

References 7 publications

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“…Ref. [105] investigated a narrowband interference suppression technique based on fast Fourier transform, providing a solution that can adapt to changing interference environments and effectively suppress narrowband interference in UAV networks. Ref.…”

Section: New Technologies Of Strong Electromagnetic Protection For Th...mentioning

confidence: 99%

Strong Electromagnetic Interference and Protection in UAVs

Zhang,

Zhou,

Zhang

et al. 2024

Electronics

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With the proliferation of unmanned aerial vehicles (UAVs) and the escalating electromagnetic environment in space, there has been growing attention and research focus on the strong electromagnetic effects and electromagnetic protection design of UAVs. This paper aims to introduce the potential strong electromagnetic interference that UAVs may encounter during flight. It specifically concentrates on three crucial subsystems: the datalink system, the flight control and navigation system, and the power system. The goal is to provide an overview of the current state of research on the strong electromagnetic effects of UAVs, along with a discussion of commonly employed research methods. Additionally, this paper introduces various means of strong electromagnetic protection that can be utilized for UAVs. Finally, it concludes with a summary of the research status and development trends concerning the effects of strong electromagnetic interference and the corresponding protection measures for UAVs.

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Section: New Technologies Of Strong Electromagnetic Protection For Th...mentioning

confidence: 99%

Strong Electromagnetic Interference and Protection in UAVs

Zhang,

Zhou,

Zhang

et al. 2024

Electronics

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“…. , M ´1u for agent n. The action a n P A n denotes the steps that agent n moves clockwise 3 in current time slot relative to the channel m 1 n P tCH 1 , CH 2 , . .…”

Section: A Marl Problem Modelmentioning

confidence: 99%

“…C LUSTERED unmanned aerial vehicle (UAV) communication networks technology, which is one of the key supporting technologies of clustered UAV system, have received extensive attention and in-depth research recently [1] [2]. Due to the particularities of clustered UAV applications, they generally form a self-organizing network which is in a complex electromagnetic interference environment [3]. The solution of allocating fixed spectrum resources for clustered UAV communication networks will lead to poor system robustness consequently.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Reinforcement Learning Based Cooperative Content Caching for Mobile Edge Networks

et al. 2019

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Designing clustered unmanned aerial vehicle (UAV) communication networks based on cognitive radio (CR) and reinforcement learning can significantly improve the intelligence level of clustered UAV communication networks and the robustness of the system in a time-varying environment. Among them, designing smarter systems for spectrum sensing and access is a key research issue in CR. Therefore, we focus on the dynamic cooperative spectrum sensing and channel access in clustered cognitive UAV (CUAV) communication networks. Due to the lack of prior statistical information on the primary user (PU) channel occupancy state, we propose to use multiagent reinforcement learning (MARL) to model CUAV spectrum competition and cooperative decision-making problem in this dynamic scenario, and a return function based on the weighted compound of sensing-transmission cost and utility is introduced to characterize the real-time rewards of multi-agent game. On this basis, a time slot multi-round revisit exhaustive search algorithm based on virtual controller (VC-EXH), a Q-learning algorithm based on independent learner (IL-Q) and a deep Q-learning algorithm based on independent learner (IL-DQN) are respectively proposed. Further, the information exchange overhead, execution complexity and convergence of the three algorithms are briefly analyzed. Through the numerical simulation analysis, all three algorithms can converge quickly, significantly improve system performance and increase the utilization of idle spectrum resources.

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“…Such communications are not only immune to the noise as they usually operate at a negative signal-to-noise ratio, but they also do not interfere with other communication services due to their extremely low power. Moreover, techniques mainly used for higher frequency ranges such as spread spectrum [9] or ultra-wide band technologies [10] could be implemented on a fully software defined radio platform [11], [12], [13], and can further reduce the risk of interference with other HF communication systems or between components of the same communication system.…”

Section: Introductionmentioning

confidence: 99%

A Full Calibration Approach on a Drone-Borne Platform for HF Antenna Measurements in Smart Grid Energy Facilities

Pastorcici,

Constantin,

Heiman

et al. 2024

Preprint

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Emerging data processing techniques brought back into attention the HF range communication as an interesting alternative to third-party solutions for IoT applications, such as data transmission in distributed energy production facilities. The physical size of HF antennas, often comparable to the surrounding objects, require in-situ radiation measurements. Drone-borne measuring systems are already known as a flexible solution, but mostly restricted to higher frequency ranges. In this work, we propose to use an electrically small, folded dipole as a probe for drone-borne measurements on HF antennas. We also propose a calibration approach for the effects related to the near-field zone, and to the drone body proximity. The impact of ground reflection is also investigated. We show that despite its low, realized gain figure such a probe can provide stable results for near-field measurements, even at low input power levels.

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Research on Narrowband Interference Suppression Technology of UAV Network Based on Spread Spectrum Communication

Cited by 9 publications

References 7 publications

Strong Electromagnetic Interference and Protection in UAVs

Strong Electromagnetic Interference and Protection in UAVs

Multi-Agent Reinforcement Learning Based Cooperative Content Caching for Mobile Edge Networks

A Full Calibration Approach on a Drone-Borne Platform for HF Antenna Measurements in Smart Grid Energy Facilities

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