Optimal Power Control in Ultra-Dense Small Cell Networks: A Game-Theoretic Approach

In this paper, we study the power control problem for interference management in the ultra-dense small cell networks, which is formulated to maximize the sum-rate of all the small cells while keeping tolerable interference to the macrocell users. We investigate the problem by proposing a novel game...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on wireless communications 2017-07, Vol.16 (7), p.4139-4150
Main Authors: Zheng, Jianchao, Wu, Yuan, Zhang, Ning, Zhou, Haibo, Cai, Yueming, Shen, Xuemin
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Complexity
Computer simulation
Control algorithms
Control systems
Control theory
Design optimization
distributed algorithm
Electric power distribution
Game theory
Games
Interference
Interference management
Iterative methods
local information
Macrocell networks
Maximization
Optimization
Power control
Transmission rate (communications)
ultra-dense small cell networks
Wireless communication
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we study the power control problem for interference management in the ultra-dense small cell networks, which is formulated to maximize the sum-rate of all the small cells while keeping tolerable interference to the macrocell users. We investigate the problem by proposing a novel game with dynamic pricing. Theoretically, we prove that the Nash equilibrium (NE) of the formulated game coincides with the stationary point of the original sum-rate maximization problem, which could be locally or globally optimal. Furthermore, we propose a distributed iterative power control algorithm to converge to the NE of the game with guaranteed convergence. To reduce the information exchange and computational complexity, we propose an approximation model for the original optimization problem by constructing the interfering domains, and accordingly design a local information-based iterative algorithm for updating each small cell's power strategy. Theoretic analysis shows that the local information-based power control algorithm can converge to the NE of the game, which corresponds to the stationary point of the original sum-rate maximization problem. Finally, simulation results demonstrate that the proposed approach yields a significant transmission rate gain, compared with the existing benchmark algorithms.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2016.2646346