Research Article
Downlink Power Allocation Strategy in Multi-antenna Ultra-dense Networks Based on Non-cooperative Game
@INPROCEEDINGS{10.1007/978-3-030-93398-2_62, author={Donglai Zhao and Gang Wang and Haoyang Liu and Shaobo Jia}, title={Downlink Power Allocation Strategy in Multi-antenna Ultra-dense Networks Based on Non-cooperative Game}, proceedings={Wireless and Satellite Systems. 12th EAI International Conference, WiSATS 2021, Virtual Event, China, July 31 -- August 2, 2021, Proceedings}, proceedings_a={WISATS}, year={2022}, month={1}, keywords={Power allocation Ultra-dense network Non-cooperative game Spectral efficiency (SE) Quality-of-service (QoS)}, doi={10.1007/978-3-030-93398-2_62} }- Donglai Zhao
Gang Wang
Haoyang Liu
Shaobo Jia
Year: 2022
Downlink Power Allocation Strategy in Multi-antenna Ultra-dense Networks Based on Non-cooperative Game
WISATS
Springer
DOI: 10.1007/978-3-030-93398-2_62
Abstract
This paper investigates the downlink power allocation strategy for a multi-antenna spectrum sharing ultra-dense small cell network in order to suppress the inter-cell interference and improve the system spectral efficiency (SE). The non-cooperative game is adopted to transform the system SE maximization problem into several convex subproblems which maximize the utility function of each user. By designing a dynamic pricing, each Nash equilibrium (NE) of the game is a stationary point of the original optimization problem. In addition, an interference power constraint is applied to guarantee the quality-of-service (QoS) of the key user. Under the game theory framework, an iterative dynamic pricing power allocation (DPPA) algorithm is designed, which is proved to be convergent to the NE of the game model. Furthermore, in order to reduce the signaling overhead and improve the resource utilization, an approximate dynamic pricing power allocation (ADPPA) algorithm is also proposed. Simulation results show that the proposed DPPA algorithm achieves a better performance than benchmark methods and the proposed ADPPA algorithm effectively reduces the signaling overhead with a little performance loss.
