CR-based UAV communication network secondary link throughput optimization method
An optimization method and communication network technology, applied in the field of UAV communication processing, can solve the problems of low spectrum efficiency, scarce spectrum resources, spectrum efficiency, and scarce spectrum resources of UAV communication networks, etc.
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2020-10-16
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Abstract
Description
technical field
[0001] The invention belongs to the technical field of unmanned aerial vehicle communication processing, and in particular relates to a CR-based method for optimizing the throughput of a secondary link of a UAV communication network. Background technique
[0002] Currently, drones typically use unlicensed frequency bands (e.g., IEEE S-band, IEEE L-band, Industrial Scientific and Medical (ISM) bands) and use static spectrum allocation policies. In recent years, with the rapid development of 5G network, D2D (Device-to-Device) communication and Internet of Things (IoT), the demand for spectrum has increased dramatically. Due to these factors, the operating frequency band for drones will become overcrowded, and drones will face spectrum shortage. Cognitive radio (CR) solves the waste problem of spectrum occupation by opportunistically accessing licensed frequency bands, and uses advanced communication methods to improve spectrum utilization efficiency. As a new...
Examples
Embodiment
[0077] The present invention proposes a CR-based UAV communication network secondary link throughput optimization method. The basic idea is to use cognitive radio technology to solve the current situation of scarcity of spectrum resources and low spectrum efficiency in the UAV communication network. By constructing an A2G channel Under the cognitive UAV network model, the system perception parameters are jointly optimized, and the system spectrum efficiency is improved under the premise of ensuring the QoS of the PU.
[0078] Establish a cognitive UAV communication network model under the A2G channel, such as image 3 As shown, the cognitive UAV network is composed of base station (BS) and UAV, and the distance between PU and BS is R P , the UAV flies in a circular orbit centered on BS with a uniform flight speed v, and the orbit radius is R S , the flying height is H. With BS as the center, the UAV makes periodic circular motions. One flight cycle contains one frame of flig...