Title
Resource Allocation for Ultra-Dense Networks: A Survey, Some Research Issues and Challenges
Abstract
Driven by the explosive data traffic and new quality of service (QoS) requirement of mobile users, the communication industry has been experiencing a new evolution by means of network infrastructure densification. With the increase of the density as well as the variety of access points (APs), the network benefits from proximal transmissions and increased spatial reuse of system resources, thus introducing a new paradigm named ultra-dense networks (UDNs). Since the limited available resources are shared by ubiquitous APs in UDNs, the demand for efficient resource allocation schemes becomes even more compelling. However, the large scale of UDNs impedes the exploration of effective resource allocation approaches particularly on the computational complexity and significance overhead or feedback. In this paper, we provide a survey-style introduction to resource allocation approaches in UDNs. Specifically, we first present some common scenarios of UDNs with the relevant special issues. Second, we provide a taxonomy to classify the resource allocation methods in the existing literatures. Then, to alleviate the main difficulties of UDNs, some prevailing and feasible solutions are elaborated. Next, we present some emerging technologies thriving UDNs with special RA features discussed. Additionally, the challenges and open research directions are outlined in this field.
Year
DOI
Venue
2019
10.1109/comst.2018.2867268
IEEE Communications Surveys and Tutorials
Keywords
Field
DocType
Resource management,Wireless communication,Computer architecture,Microprocessors,Quality of service,Device-to-device communication
Resource management,Open research,Wireless,Reuse,Computer science,Quality of service,Risk analysis (engineering),Emerging technologies,Resource allocation,Distributed computing,Computational complexity theory
Journal
Volume
Issue
Citations 
21
3
12
PageRank 
References 
Authors
0.51
0
6
Name
Order
Citations
PageRank
yinglei teng19119.76
Mengting Liu21006.26
Fei Yu35116335.58
Victor C. M. Leung49717759.02
Mei Song526544.50
Yong Zhang6438103.95