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Automatic transmit power control for power efficient communications in UAS
- Publication Year :
- 2020
-
Abstract
- Nowadays, unmanned aerial vehicles (UAV) have become one of the most popular tools that can be used in commercial, scientific, agricultural and military applications. As drones become faster, smaller and cheaper, with the ability to add payloads, the usage of the drone can be versatile. In most of the cases, unmanned aerials systems (UAS) are equipped with a wireless communication system to establish a link with the ground control station to transfer the control commands, video stream, and payload data. However, with the limited onboard calculation resources in the UAS, and the growing size and volume of the payload data, computational complex signal processing such as deep learning cannot be easily done on the drone. Hence, in many drone applications, the UAS is just a tool for capturing and storing data, and then the data is post-processed off-line in a more powerful computing device. The other solution is to stream payload data to the ground control station (GCS) and let the powerful computer on the ground station to handle these data in real-time. With the development of communication techniques such as orthogonal frequency-division multiplexing (OFDM) and multiple-input multiple-output (MIMO) transmissions, it is possible to increase the spectral efficiency over large bandwidths and consequently achieve high transmission rates. However, the drone and the communication system are usually being designed separately, which means that regardless of the situation of the drone, the communication system is working independently to provide the data link. Consequently, by taking into account the position of the drone, the communication system has some room to optimize the link budget efficiency. In this master thesis, a power-efficient wireless communication downlink for UAS has been designed. It is achieved by developing an automatic transmit power control system and a custom OFDM communication system. The work has been divided into three parts: research of the drone co
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1190527185
- Document Type :
- Electronic Resource