Air-ground non-orthogonal multiple access uplink transmission method based on intelligent reflecting surface

Abstract

The invention discloses an air-ground non-orthogonal multiple access uplink transmission method based on an intelligent reflecting surface, and belongs to the field of wireless communication. The method comprises the following steps: firstly, establishing an air-ground communication scene comprising a ground user, an unmanned aerial vehicle, an IRS and a base station, respectively modeling effective links from the ground user and the unmanned aerial vehicle to the base station in a current time slot, and calculating a signal-to-noise ratio of a received signal; then, the transmission rate, received by the base station, of the unmanned aerial vehicle and the ground user is calculated; taking the maximization of the total uplink transmission rate as an optimization target, and establishing a joint optimization problem about the flight path of the unmanned aerial vehicle, the IRS phase deviation, the transmitting power of the unmanned aerial vehicle user and the transmitting power of the ground user; and the problem is modeled as a Markov decision process. And finally, training the model by adopting a distributed robust reinforcement learning algorithm based on an Actor-Critic framework, outputting parameters, applying the parameters to a central control Actor network of an air-ground communication scene, and realizing real-time joint optimization of IRS-assisted air-ground communication. According to the invention, the robustness of the system in a dynamic complex environment is ensured.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, aims at the application requirement of optimal allocation of air-ground communication spectrum resources, and specifically relates to an air-ground non-orthogonal multiple access uplink transmission method based on an intelligent reflecting surface. Background technique [0002] In the past few years, the use of Unmanned Aerial Vehicles (UAVs) as aerial platforms for communication networks to improve the capacity and coverage of existing wireless networks has attracted extensive attention from academia and industry. One way to achieve high-quality air-ground communication at this stage is to use terrestrial cellular networks, which introduces the concept of operation of cellular-connected UAV communication. Cellular connected UAV communication can significantly improve the performance of existing air-ground communication systems under the condition of limited spectrum resources in ...

AI Technical Summary

Problems solved by technology

[0006] (1) The introduction of the NOMA protocol has brought about a more complex interference environment and a decoding order design based on channel conditions, which has led to a high degree of coupling between the requirements of UAV track, IRS phase offset and uplink power control. In this situation, it is difficult to obtain the optimal decision-making scheme efficiently and quickly, so as to improve the performance of the receiving end of the ground base station (Ground Base Station, GBS) in the uplink

[0007] (2) Since the reflection coefficient of the IRS will affect both the UAV and the Ground User (GU), the optimal beamforming of the reflected signal is not only aligned with the direct signal, but also due to the existence of co-channel interference, The configuration of the reflection unit of the IRS has become more complicated

[0009] In addition, since environmental uncertainty is difficult to accurately model, how to improve the robustness of the decision-making process in the face of dynamic uncertainty is another important challenge

Images