DATA-DRIVEN ALLOCATION OF NETWORK RESOURCES IN UDNs

Silvestre Lomba Malta, supervised by Manuel Fernandez Veiga

Department of Telematics Engineering

Due to UDN characteristics, energy management and energy

consumptions are serious challenges to network operators.

Generally speaking, the UDN is an extension of the

Heterogeneous Network (HetNet), where a large number of small

cells are deployed to offload network traffic from over-crowded

macro cells, such that the overall network capacity can be

improved [1].

Studies have concluded that Base Stations consume about 60%-

80% of energy use in cellular networks [1] [2] [3].

The key patterns of a UDN are the user end (UE) and the UE

mobility [4].

Could users mobility prediction schemes help in the optimization

of power-saving algorithms implemented in coordinated or

uncoordinated cellular network BSC’s/eNB’s

Motivation of the work

Thesis Objectives

• Study prediction schemes of user’s mobility.

• Search new tecniques for sampling, compressing and

summarizing network mobility

information in real-time.

• Evaluate the performance

improvements of knowing mobility

and traffic patterns in UDNs as far as

energy-efficiency is concerned.

• Develop deterministic mean-field approximations for predicting

the performance in large UDNs.

• Literature review.

• Learn and play examples in Network Simulator 3

• Learn how to implement LTE scenarios in NS3

• Get sampled mobility patterns and use them on statisticals learning

tools.

• Make a survey of existing models for energy saving region on BS.

• Make a survey of existing simulation models for spatial configuration

in UDN.

• Apply and combine models for EE with simulation models of UDN

spatial configuration.

Research Plan

2017/2018 planning

References

[1]Wei Yu, et al , Ultra-Dense Networks: Survey of State of the Art and Future Directions, (2016)

[2] A. Fehske, et al, The global footprint of mobile communications: The ecological and economic perspective, IEEE Communications magazine v. 49, 55-62, (2011)

[3]Sérgio Herrería-Alonso, et al, Optimal Dynamic Sleeping Control Policy for Single Base Stations in Green Cellular Networks

[4]Wei Yu, et al, Towards energy efficiency in ultra dense networks, Performance Computing and Communications Conference (IPCCC), 2016 IEEE 35th International

Time Task

October 2017 Finish how to implement LTE network scenarios in

NS3

February 2018 Have mobility data collection analized on statisticals

learning tools.

June 2018 Finish the survey of existing models for energy saving

region on Base Stations

Virtual Poster

About the Autor, Silvestre Malta is PhD student at UVigo, Assistant lecturer at

ESTG - Polytechnic Institute of Viana do Castelo. Master in Technology and Infor-

mation Systems and degree in Computer Network Engineering. He has professio-

nal experience in the administration of linux systems, as well as implementation

and maintenance of IP/MPLS networks in several ISPs.