Abstract
In future scenarios of heterogeneous and dense networks, randomly-deployed small star networks (SSNs) become a key paradigm, whose system performance is restricted to inter-SSN interference and requires an efficient resource allocation scheme for interference coordination. Traditional resource allocation schemes do not specifically focus on this paradigm and are usually too time consuming in dense networks. In this article, a very efficient graph-based scheme is proposed, which applies the maximal independent set (MIS) concept in graph theory to help divide SSNs into almost interference-free groups. We first construct an interference graph for the system based on a derived distance threshold indicating for any pair of SSNs whether there is intolerable inter-SSN interference or not. Then, SSNs are divided into MISs, and the same resource can be repetitively used by all the SSNs in each MIS. Empirical parameters and equations are set in the scheme to guarantee high performance. Finally, extensive scenarios both dense and nondense are randomly generated and simulated to demonstrate the performance of our scheme, indicating that it outperforms the classical max K-cut-based scheme in terms of system capacity, utility and especially time cost. Its achieved system capacity, utility and fairness can be close to the near-optimal strategy obtained by a time-consuming simulated annealing search.
Highlights
Heterogeneity and high density have been important trends for the research and development of wireless communication and networking in recent years toward 5G mobile communication systems supporting future promising applications, such as artificial intelligence, smart cities and telemedicine.This leads to the mission of deploying more small access points (APs), such as WiFi hotspots and femtocells, as well as clustering of sensors into small groups for the Internet of Things (IoT) [1,2].many studies involve scenarios with randomly-deployed small networks, each obeying a star topology
The utilities might be different in the orders of magnitude, so we draw the curves for α = 0, 0.4, 0.8, 1 in the four sub-figures in Figure 9 to clearly show the gap between the two schemes
For each sub-figure, we can see that the utilities gradually decrease along with the increment of system density, because the increment of the density brings about more interference
Summary
Heterogeneity and high density have been important trends for the research and development of wireless communication and networking in recent years toward 5G mobile communication systems supporting future promising applications, such as artificial intelligence, smart cities and telemedicine.This leads to the mission of deploying more small access points (APs), such as WiFi hotspots and femtocells, as well as clustering of sensors into small groups for the Internet of Things (IoT) [1,2].many studies involve scenarios with randomly-deployed small networks, each obeying a star topology. Heterogeneity and high density have been important trends for the research and development of wireless communication and networking in recent years toward 5G mobile communication systems supporting future promising applications, such as artificial intelligence, smart cities and telemedicine. This leads to the mission of deploying more small access points (APs), such as WiFi hotspots and femtocells, as well as clustering of sensors into small groups for the Internet of Things (IoT) [1,2]. This example can be extended to body sensor network (BSN)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
