Design and implementation of aerial communication using directional antennas: learning control in unknown communication environments

Li, Songwei; He, Chenyuan; Liu, Mushuang; Wan, Yan; Gu, Yixin; Xie, Junfei; Fu, Shengli; Lu, Kejie

doi:10.1049/iet-cta.2018.6252

Cited by 38 publications

(14 citation statements)

References 23 publications

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“…For the mitigation of downlink interference from cochannel base stations to UAVs, directional antenna and MIMO beamforming can be similarly applied. Recently, various techniques have been explored in measurement campaigns to mitigate the interference induced by cellular-connected UAV, e.g., power control [84], directional antenna [75,85], multi-antennas [39,76,84,86], and joint cooperative multi-point transmission [81,84], etc.…”

Section: Interference Mitigationmentioning

confidence: 99%

“…The performance of cellular-connected UAVs can be greatly improved by aligning the antenna main lobe with the direction of the associated base station, which can be achieved either mechanically or electrically (multi-antennas beamforming). A mechanically automatic alignment system of directional antennas was developed in [85], where the communication quality indicator and RSSI were used for the objective function of antenna alignment. This antenna alignment system can be directly applied in interference mitigation for cellular-connected UAVs.…”

Section: Interference Mitigationmentioning

confidence: 99%

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A survey of prototype and experiment for UAV communications

Song

Zeng

et al. 2021

Sci. China Inf. Sci.

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Unmanned aerial vehicle (UAV) communications have attracted significant attention from both academia and industry. To facilitate the large-scale usage of UAVs for various applications in practice, we provide a comprehensive survey on the prototype and experiment for UAV communications. To this end, we first provide an overview on the general architecture of the prototype and experiment for UAV communications, and then present experimental verification for air-to-ground channel models and UAV energy consumption models. Next, we discuss measurement experiments on two promising paradigms of UAV communications, namely cellular-connected UAVs and UAV-enabled aerial communication platforms. For the former, we focus on the feasibility study and address the interference mitigation issue. For UAV-enabled aerial communication platforms, we present three scenarios, namely UAV-enabled aerial base stations, UAVenabled aerial relays and UAV-enabled aerial data collection/dissemination. Finally, we point out some promising future directions for prototype and experimental measurements of UAV communications.

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Section: Interference Mitigationmentioning

confidence: 99%

Section: Interference Mitigationmentioning

confidence: 99%

A survey of prototype and experiment for UAV communications

Song

Zeng

et al. 2021

Sci. China Inf. Sci.

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“…With Jetson TX2 chosen as the computing unit, we then develop a prototype of the airborne computing platform [44, 45] that also incorporates a quadcopter unit for lifting and mobility, a communication unit for UAS‐to‐UAS (U2U), UAS‐to‐ground (U2G) and ground‐to‐UAS (G2U) communications, and a control unit for addressing communications, networking, UAS navigation and application needs (see Fig. 2).…”

Section: Hardware Design For the Airborne Computing Platformmentioning

confidence: 99%

Computing in the air: An open airborne computing platform

Wang

Xie

et al. 2020

IET Communications

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“…MATLAB simulations and real experiments are carried out on a scenario with 2 UAVs. The same authors study the same problem in [11], but, in this paper, the authors use a reinforcement learning approach to learn the communication channel model. The proposed solution is validated with 2 UAVs and with a focus on the reached angles and the learned antenna radiation pattern.…”

Section: Related Workmentioning

confidence: 99%

Leveraging Antenna Orientation to Optimize Network Performance of Fleets of UAVs

Grünblatt

Lassous

Simonin

2020

Proceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

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In this paper, we investigate the problem of optimizing the network performance of a fleet of unmanned aerial vehicles (UAVs) in static positions. More precisely, we allow each UAV to change its orientation in order to improve the quality of communication with its neighbours. This form of controlled mobility takes advantage of the effective radiation pattern of each UAV. We build a decentralized scheme based on the hill climbing optimization approach without a priori knowledge of the antennas radiation patterns. Then, we propose a simulation framework, based on ns-3, allowing to evaluate the gain in network performance. We provide results in several deployment scenarios involving different rate adaptation algorithms and network sizes. 1

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Design and implementation of aerial communication using directional antennas: learning control in unknown communication environments

Cited by 38 publications

References 23 publications

A survey of prototype and experiment for UAV communications

A survey of prototype and experiment for UAV communications

Computing in the air: An open airborne computing platform

Leveraging Antenna Orientation to Optimize Network Performance of Fleets of UAVs

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