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A Framework for Interference Control in Software-Defined Mobile Radio
Networks
Conference Paper · January 2015
DOI: 10.1109/CCNC.2015.7158094
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Anteneh Atumo Gebremariam
Università degli Studi di Trento
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A Framework for Interference Control in Software-‐De6ined Mobile Radio Networks
Anteneh A. Gebremariam*; L. Gora1†; R. Riggio†; D. Siracusa†; T. Rasheed†; F. Granelli*
* ICT Doctoral School, University of Trento, Trento, Italy † CREATE-‐NET, Trento, Italy
CCNC2015 Workshops-‐VENITS January 9-‐12, 2015
Las Vegas, Nevada, USA
Outline
• IntroducHon • MoHvaHon
IntroducHon
• Problem Statement
• ObjecHve
Problem • System Model • SoluHon • Conclusions and Future work
SoluHons
2
Introduction • Computer networks play a very important role in our day to day life
• As the number of users increases so does the number of network devices
• Challenges: o ConfiguraHon and management becomes costly
o System updates are very demanding
o Lowers the pace of innovaHon 3
• Why? • The control logic (intelligence) is embedded to every device
• How it could be solved? • SoOware-‐Defined Networking (SDN)
• What is SDN? • Newly emerging network architecture paradigm • Promises innovaHon in terms of:
ü Network programmability ü High-‐level of abstracHon
Introduction (cont’d)
4
• How it is achieved? • SeparaHng the control-‐plane and data-‐plane with a well-‐defined programmable interface to provide: ü Centralized global view of the network ü Easy configurability and manageability ü Flexibility, Scalability and capability of reconfiguraHon of different network segments
5
Introduction (cont’d)
Motivation • Similarly, mobile data traffic is also booming due to:
6
Main Reasons for Mobile
Traffic Boom
Motivation (cont’d) • Device bandwidth consumpHon profile* o Growth in the number of devices
è growth in mobile data traffic
7
DensificaXon: -‐ SpaXal reuse -‐Interference -‐CAPEX/OPEX
-‐etc.
Increase in capacity demand
Mobile data traffic boom
Device Traffic
M2M 6 *
Wearable Devices 7 *
Smartphones 49 *
Tablets 127 *
Laptops 227 *
*Cisco and/or its affiliates, ”Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2013–2018”, White Paper, February 5, 2014
èTo account these issues, programmability of mobile networks is needed:
ü AllocaHng non-‐overlapping frequency bands
ü Monitoring interference ü CoordinaHng handovers ü ConfiguraHon and management
Problem Statement • Even though the problem of interference studied for decades at both PHY and MAC layers, so far none of them managed it saHsfactorily.
• ObjecXve: ü To come up with a framework for interference control (i.e., manage and avoid) to mobile networks by adopXng the SDN paradigm
8
System Model • How?
ü By exposing/abstracXng the lower layers of the protocol stack (i.e., PHY and MAC) in order to make system parameters available to the controller or applicaXons
ü Providing an efficient resource scheduling scheme to control interference
9
System Architecture Interference control framework
10
Solution Y =H ⋅X
ü The selecHon of H is done by the central controller based on the channel feedback informaXon of the UEs ü Y can be represented by a tuple of parameters, <time, frequency, space, transmit-power, modulation, coding, antenna-port, beam-pattern>, represenHng an abstracHon of the resources assigned to a data stream X
YX H
PORT
• IG represented by a pair (V, E) • IG construcHon:
I. Based on the history II. Micro-‐probing
Interference Graph (IG)
11
• Conflict Graph construcHon • What are weights assigned for each edge?
Ii,max = β−1Pi Xi − XR(i)
−η−σ 2
wik =
Pk Xk − XR(i)−η
Ii,max
èThe maximum allowed interference level at the receiver is:
èThe maximum allowable interference contribuHon of the kth interfering link on terminal XR(i):
Conflict Graph (CG)
èSm represents a set of communicaHon links that could be acXve at the same Xme, considering the following expression is saHsfied:
wik ≤1
lk
Sm
∑
Solution (cont’d)
Solution (cont’d)
12
• The opXmizer: ü Goal: to reduce the weights in a certain transmission link in the CG
• How? ü Efficient resource scheduling: Integer Linear Problem (ILP)
ObjecXve funcXon – minimizaHon of the weights (i.e., minimizing the aggregate interference)
minϕi,k ,r ,m
wik ⋅ϕi,k,r,m
m=1
M
∑r=1
R
∑k=1k≠i
L
∑i=1
L
∑
Constraints :
Pmin ≤ Pi ≤ Pmax
TPi,k,r,m ⋅ϕi,k,r,m ≥ TPi,kref
m=1
M
∑r=1
R
∑
è W =
w11 w1
2 ... w1L
w21 w2
2 ... w2L
. . . .wL1 wL
2 ... wLL
!
"
#####
$
%
&&&&&
Conclusions and Future work • ContribuXons:
ü SDN paradigm adopHon for to mobile networks in abstracHng low layer (PHY/MAC) wireless protocol stack
ü Interference Graph is proposed as an abstracXon in order to control interference
ü FormulaHon of an opXmizaXon tool for reducing the weights in the conflict graph
ü A set of mobile network system parameters are abstracted in order to improve the programmability of the network
• Future Work: ü ImplementaHon of sokware-‐defined framework for interference control using an open source SW/HW plamorm called OpenAirInterface (OAI) 13
Thank You!
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