Resource Optimization in Heterogeneous Cloud Radio Access Networks.

Saved in:
Bibliographic Details
Title: Resource Optimization in Heterogeneous Cloud Radio Access Networks.
Authors: Dai, Haibo, Huang, Yongming, Wang, Jiaheng, Yang, Luxi
Source: IEEE Communications Letters; Mar2018, Vol. 22 Issue 3, p494-497, 4p
Abstract: This letter tackles the problem of sum-rate maximization via joint user association and power allocation in heterogeneous cloud radio access networks, while guaranteeing the quality-of-service requirements of all users. A generalized Stackelberg game is applied to this problem with the coupled strategy set of power allocation, and a centralized-distributed method is designed to achieve the optimal solution. Specifically, the user association problem is efficiently solved in a centralized manner and a distributed power allocation algorithm is proposed by using variational inequality theory. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Communications Letters is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Description
Abstract:This letter tackles the problem of sum-rate maximization via joint user association and power allocation in heterogeneous cloud radio access networks, while guaranteeing the quality-of-service requirements of all users. A generalized Stackelberg game is applied to this problem with the coupled strategy set of power allocation, and a centralized-distributed method is designed to achieve the optimal solution. Specifically, the user association problem is efficiently solved in a centralized manner and a distributed power allocation algorithm is proposed by using variational inequality theory. [ABSTRACT FROM PUBLISHER]
ISSN:10897798
DOI:10.1109/LCOMM.2017.2787676