Research Article
A Resource Allocation Algorithm Based on Game Theory in UDN
@INPROCEEDINGS{10.1007/978-3-319-73564-1_45, author={Changjun Chen and Jianxin Dai and Chonghu Cheng and Zhiliang Huang}, title={A Resource Allocation Algorithm Based on Game Theory in UDN}, proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part I}, proceedings_a={MLICOM}, year={2018}, month={2}, keywords={UDN Femtocells Clustering Stackelberg game}, doi={10.1007/978-3-319-73564-1_45} }- Changjun Chen
Jianxin Dai
Chonghu Cheng
Zhiliang Huang
Year: 2018
A Resource Allocation Algorithm Based on Game Theory in UDN
MLICOM
Springer
DOI: 10.1007/978-3-319-73564-1_45
Abstract
In ultra-dense networks (UDNs), large-scale deployment of femtocells base stations is an important technique for improving the network throughput and quality of service (QoS). However, traditional resource allocation algorithms are concerned with the improvement of the overall performance of the network. In this paper, a new resource allocation algorithm based on game theory is proposed to manage the resource allocation in UDNs. The quality of service (QoS) and energy consumption of each femtocell are considered. Firstly, a modified clustering algorithm is performed. Then we transform this resource allocation problem to a Stackelberg game. In sub-channel resource allocation, we aim to maximize the throughput of the whole system by cluster heads (CHs). The power allocation takes account of the balance between QoS requirement and transmit power consumption. Simulation results show that this method has some advantages in improving the overall system throughput, while obtaining a performance improvement compared with other algorithms.
