Power Control Algorithm Based on a Cooperative Game in User-Centric Unmanned Aerial Vehicle Group

Yuexia Zhang,Pengfei Zhang,Fei Xiong

doi:10.1155/2021/7108198

Yuexia Zhang, Pengfei Zhang + Show 1 more

Open Access

https://doi.org/10.1155/2021/7108198

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Abstract

The quality of service (QoS) of a user in user-centric unmanned aerial vehicle group (UUAVG) is degraded by complex cochannel interference; hence, a cooperative game power control (CGPC) algorithm in UUAVG is proposed. The algorithm helps to establish a downlink power control model of the UUAVG, construct a product of the signal to interference noise ratio function of each user as a utility function of the cooperative game, and deduce the optimal power control scheme using the Lagrange function. This scheme reduces the interference of the service unmanned aerial vehicle (UAV) to edge users and improves the communication quality of all the users as well as the throughput of the entire system. Simulation results show that the average throughput of the CGPC algorithm improved by 10.32% compared with the traditional Stackelberg Game based Nonunified Pricing Power Control (SGNPPC) algorithm. This shows that the CGPC algorithm can effectively reduce the transmission power of the cooperative UAV and enhance the capacity of the entire system, ensuring communication quality.

Highlights

With the rapidly increasing number of wireless devices and growth of user traffic demand, improving the throughput of a communication system has gained considerable attention [1]
It can be observed from the figure that the initial transmitting power of cooperative unmanned aerial vehicles (CUAV) is 0.1 W
With the increase of iteration times, the transmitting power of CUAV decreases gradually and reaches a stable state after many games. e attenuation rate of CUAV1 is the fastest and that of CUAV4 is the slowest. is is due to the different distances between edge users (EU) and service user (SU). e distance between EU1 and SU is relatively close, and the downlink communication power of CUAV1 and EU1 has a greater impact on SU. e power attenuation of CUAV1 is relatively large. e distance between EU4 and SU is relatively long, and the influence of CUAV 4 and EU4 downlink communication power on SU is relatively small

Summary

Introduction

With the rapidly increasing number of wireless devices and growth of user traffic demand, improving the throughput of a communication system has gained considerable attention [1]. In [12], a noncooperative game distributed power control algorithm was introduced, which could effectively improve the system throughput and reduce cochannel interference; the proposed algorithm cannot achieve optimal system capacity. Considering the interference to user QoS and service UAV to edge users, a new cooperative game utility function is proposed, and the optimal power control scheme is solved using the Lagrange function. Owing to the scarcity of spectrum availability and to improve frequency utilisation, when deploying the UAVG, the downlink communication frequencies of the SUAV and SU are the same as those of the CUAVi and EUi. erefore, the interference between the SUAV and CUAV and those between the CUAVs are inevitable For each user, they are in the center of the network, and UAVs around the user are dynamically composed of UAVG.

CGPC Algorithm

Performance Evaluation

Conclusion