DocumentCode :
3611619
Title :
QoS-aware cell association in 5G heterogeneous networks with massive MIMO
Author :
Ping Wang ; Wei Song ; Niyato, Dusit ; Yong Xiao
Volume :
29
Issue :
6
fYear :
2015
Firstpage :
76
Lastpage :
82
Abstract :
5G cellular networks aim to improve the connection speed to ensure ultra-low latency (e.g., to support real-time video streaming service) through heterogeneous environments. HetNets composed of different types of cells (e.g., macrocells and small cells) are the major direction of 5G network design. In this article, we first introduce the key features and highlight resource management issues in 5G HetNets. We then focus on the cell association problem of multiple classes of users in HetNets. Users in different classes have different data rate requirements and will choose to associate with the cell(s) (e.g., a macrocell or small cells) that yield(s) the highest data rate. Therefore, the cells also have to allocate resources in terms of antennas to different classes of users to maximize their total revenue. We introduce cell association and antenna allocation algorithms based on the evolutionary game theory. The algorithms can achieve equilibrium solutions, ensuring that the users and the cells cannot gain higher data rate and total revenue, respectively, by changing their cell association and antenna allocation.
Keywords :
5G mobile communication; MIMO communication; channel allocation; evolutionary computation; game theory; mobile antennas; mobility management (mobile radio); quality of service; 5G heterogeneous cellular network; HetNets; QoS-aware cell association; antenna allocation algorithms; data rate requirements; evolutionary game theory; massive MIMO; resource allocation; resource management; revenue maximisation; 5G mobile communication; Base stations; Computer architecture; MIMO; Macrocell networks; Microprocessors; Quality of service; Resource management;
fLanguage :
English
Journal_Title :
Network, IEEE
Publisher :
ieee
ISSN :
0890-8044
Type :
jour
DOI :
10.1109/MNET.2015.7340428
Filename :
7340428
Link To Document :
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