A method of UAV trajectory design and power allocation based on radio map

Abstract

The invention discloses a UAV track design and power allocation method based on a radio map, which is characterized in that the communication link of the UAV is maximized by designing the UAV trajectory and transmission power according to the channel model obtained based on the radio map At the same time, the interference to the existing ground link is controlled to be less than a certain threshold; the reinforcement learning algorithm is used to design the trajectory and transmission power of the UAV. Jointly design UAV trajectory and power allocation based on fixed line-of-sight channel or statistical probabilistic line-of-sight channel in existing UAV communication to maximize the throughput of UAV communication system and control the interference introduced by UAV Compared with the methods, the method of the present invention can conform to the channel characteristics of the actual environment, and further improve the throughput of the unmanned aerial vehicle communication system under the requirement of interference limitation.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a UAV trajectory design and a power distribution method based on a radio map in UAV communication to realize UAV communication system throughput maximization and interference control. Background technique [0002] Nowadays, drones have been widely used in many fields, such as cargo delivery, aerial photography, agricultural surveying, etc. In order to integrate drones into existing cellular networks, in the 3 rd In the Generation Partnership Project (3GPP) agreement, a new technology applied to UAV communication is pointed out, in which UAVs are used as air users to complete the tasks they need to perform, and are controlled by the ground cellular network to Ensure the safe flight of drones. Under this new technology, in order to ensure the coexistence of UAV users and ground users, there will be a severe challenge, that is, air-to-ground (A2G) inter...

AI Technical Summary

Problems solved by technology

However, the above assumptions based on LoS channels and probabilistic LoS channels still have certain defects in practical applications

On the one hand, the assumption that the A2G channel obeys a specific LoS channel corresponds to the UAV performing tasks in the suburbs and other open areas and the flying height is high enough, but the high flying height will bring a certain degree of loss to the system performance; On the one hand, the assumption that the A2G channel obeys the statistical probability LoS channel corresponds to the UAV performing tasks in an environment with uniform distribution of obstacles, but in actual scenarios, obstacles in urban environments are difficult to obey a uniform distribution

Therefore, in general, although the design results based on the LoS channel or probabilistic LoS channel assumptions can provide good theoretical guidance for practical applications, due to the mismatch of the used model, the results based on the above assumptions are not good in the actual environment. suffer a certain loss

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