Method for estimating downlink channel in unmanned aerial vehicle communication

Abstract

The invention discloses a method for estimating a downlink channel in unmanned aerial vehicle communication, which comprises the following steps of: inserting a pilot signal, and obtaining a channel frequency response of a communication pilot position of an unmanned aerial vehicle according to pilot signals at a receiving end and a transmitting end in the unmanned aerial vehicle communication; according to the pilot signal and the channel frequency response of the pilot position, enabling a long-short-term memory network to learn unmanned aerial vehicle channel time related characteristics; and estimating complete channel state information by using the learned long-short-term memory network according to the pilot signal and the channel frequency response of the pilot position. The long-short-term memory network is applied to the field of unmanned aerial vehicle channel estimation, and good mean square error performance can be obtained in channel estimation, so that the precision of unmanned aerial vehicle channel estimation is improved.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a downlink channel estimation method in unmanned aerial vehicle communication. Background technique [0002] UAVs are widely used because of their flexible maneuverability and wide range of movement, and have attracted the attention of modern communication technology. In the new generation of mobile communication technology, UAVs will also become an important research object. Under the communication quality puts forward new requirements. [0003] The communication quality of wireless communication largely depends on the accuracy of channel estimation. Channel estimation is the process of estimating the model parameters of an assumed channel model from the received data. To improve the accuracy of channel estimation, an estimation algorithm that minimizes the estimation error is needed. In order to accurately restore the transmitted signal at the transmitting end ...

AI Technical Summary

Problems solved by technology

[0005] The present invention aims at the problem of insufficient channel estimation accuracy in UAV random high-mobility scenarios in the prior art, and provides a downlink channel estimation method in UAV communication. Using the long-short-term memory network in deep learning, the channel estimation method can Good mean square error performance is obtained in

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