Paper Info
Title
Stochastic Geometry Based Hierarchical Power Allocation for the Uplink Ultra-Dense Networks
Abstract
Ultra-Dense Networks (UDNs) is widely considered as a key technology of fifth generation (5G) networks, where access points (APs) are densely deployed to meet the high capacity requirements in various environments. However, the large scale of UDNs inevitably increases the computational complexity and signaling overhead for resource allocation processes. In this paper, employing discrete power levels, we propose a stochastic geometry based hierarchical power allocation scheme to maximize the user sum rate in uplink UDNs. Using stochastic geometry theory, we first group all users in terms of their transmit powers, and then derive two key metrics including statistical information-based signal to interference and noise ratio (SSINR) and the lower bound of statistical information-based user rate (SR). Furthermore, an alternative genetic algorithm (AGA) is utilized to obtain the power allocation scheme. Simulation results show that the proposed power allocation algorithm is not only able to improve the user sum rate, but also can significantly reduce the signaling overhead and computation complexity.
Year
DOI
Venue
2018
10.1109/ICCAIS.2018.8570550
2018 International Conference on Control, Automation and Information Sciences (ICCAIS)
Keywords
Field
DocType
Power allocation,ultra-dense network,stochastic geometry
Stochastic geometry,Mathematical optimization,Upper and lower bounds,Control theory,Resource allocation,Ultra dense,Interference (wave propagation),Engineering,Genetic algorithm,Computational complexity theory,Telecommunications link
Conference
ISSN
ISBN
Citations 
2475-790X
978-1-5386-6021-8
0
PageRank 
References 
Authors
0.34
10
5
Name
Order
Citations
PageRank
Mengting Liu11006.26
yinglei teng29119.76
Ning An339836.33
Mei Song426544.50
Linkun Wang500.34