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dies in Science and Technology Dissertations No Radio Network Planning and Resource Optimization: Ma...

Description

Link¨oping Studies in Science and Technology Dissertations No.

Radio Network Planning and Resource Optimization: Mathematical Models and Algorithms for UMTS,

WLANs,

and Ad Hoc Networks Iana Siomina

Department of Science and Technology Link¨ oping University,

SE-601 74 Norrk¨ oping,

Sweden Norrk¨ oping 2007

Link¨oping Studies in Science and Technology,

Dissertations No.

WLANs,

Iana Siomina Image on front cover was designed by Iana Siomina.

ISBN 978-91-85831-44-9 ISSN 0345-7524 http://urn.kb.se/resolve

?urn=urn:nbn:se:liu:diva-9158 c'Copyright 2007,

Iana Siomina,

unless otherwise noted Printed by LiU-Tryck,

Link¨ oping,

Sweden,

Abstract The tremendous popularity of wireless technologies during the last decade has created a considerable expansion of wireless networks both in size and use.

This fact,

together with a great variety of mobile devices and numerous different services that are becoming increasingly resource-demanding,

have attracted the attention of many researchers into the area of radio resource planning and optimization.

Due to network complexity,

these tasks require intelligent,

automated approaches that are able to deal with many factors in order to enable design of high capacity networks with a high service quality at the lowest possible cost.

This is a perfect application of optimization theory.

In this thesis,

mathematical optimization is considered as the main approach to designing and improving the performance of wireless networks such as Universal Mobile Telecommunications System (UMTS),

Wireless Local Area Networks (WLANs) and ad hoc networks.

Due to different underlying access technologies,

design parameters and system limitations vary by network type.

Therefore,

the goals of the presented work are to identify a relevant optimization problem for each type of network,

to model the problem and to apply the optimization approach in order to facilitate wireless network planning and improve radio resource utilization.

The optimization problems addressed in this thesis,

in the context of UMTS networks,

focus on minimizing the total amount of pilot power which,

from the modeling point of view,

is not just an amount of power consumed by a certain type of control signal,

but also an indicator of the interference level in the network and means of controlling cell coverage.

The presented models and algorithms enable flexible coverage planning and optimization of pilot power and radio base station antenna configuration in large networks.

For WLANs,

in the first part of the study,

the access point placement and the channel assignment problems are considered jointly to maximize net user throughput and minimize coand adjacent channel interference and contention.

The second part of the study addresses the contention issue and involves,

optimization of access point transmit power.

Due to the dynamic and infrastructureless nature of ad hoc networks,

static resource planning is less suitable for this type of network.

Two algorithmic frameworks which enable dynamic topology control for power-efficient broadcasting in stationary and mobile networks are presented.

In both frameworks,

the performance of the presented algorithms is studied by simulations.

Keywords: planning,

UMTS,

WLAN,

Popul¨ arvetenskaplig Sammanfattning Tr˚ adl¨ osa n¨atverk har under det senaste ˚ artiondet blivit enormt popul¨ ara.

I kombination med att det finns m¨angder av mobila enheter och resurskr¨ avande tj¨ anster har den snabba utbyggnaden av nya n¨ atverk medf¨ort ¨okad forskningsverksamhet inom planering och optimering av radioresurser.

Tr˚ adl¨ osa n¨atverk ¨ar v¨aldigt komplexa och f¨ or att utforma dessa s˚ a att de har h¨ og kapacitet och p˚ alitlighet till en l˚ ag kostnad kr¨ avs intelligenta tillv¨ agag˚ angss¨att som tar h¨ansyn till flertalet faktorer

detta utg¨ or en perfekt till¨ ampning f¨ or optimeringsteori.

I den h¨ar avhandlingen anv¨ ands huvudsakligen optimering f¨ or att designa och f¨ orb¨ attra tr˚ adl¨ osa n¨atverk som Universal Mobile Telecommunications System (UMTS),

Wireless Local Area Networks (WLANs) och ad hoc-n¨atverk.

Dessa nyttjar olika ˚ atkomsttekniker,

varf¨ or aspekter som optimeringsfokus,

designparametrar och systembegr¨ansningar varierar mellan n¨ atverken.

Syftet med avhandlingen a¨r att identifiera och presentera relevanta optimeringsproblem f¨ or olika tr˚ adl¨ osa n¨atverkstyper,

modellera problemen och d¨ arefter till¨ampa optimering f¨or att underl¨ atta planering samt effektivisera nyttjandet av radioresurser.

Optimeringsproblemen som ber¨or UMTS-n¨atverk handlar om att minimera den effekt som ˚ atg˚ ar f¨or uts¨andning av en speciell signalsekvens som bland annat anv¨ ands f¨or att skatta egenskaperna hos en kommunikationskanal.

De framtagna modellerna och algoritmerna m¨ ojligg¨ or optimering av uts¨ and effektniv˚ a f¨or dessa signaler,

flexibel planering av t¨ ackningsomr˚ aden samt reglering av basstationers antennkonfiguration i st¨ orre n¨atverk.

Arbetet g¨allande WLAN handlar dels om hur man l¨ ampligen placerar ut accesspunkter vars uppgift a¨r att sammankoppla n¨ arliggande enheter till ett n¨ atverk.

Detta innefattar a¨ven hur dessa accesspunkter b¨or tilldelas olika kanaler i syfte att maximera data¨ overf¨ oring samt minimera olika st¨orningsfaktorer.

Dessutom presenteras en studie som bland annat fokuserar a optimering av uts¨ andningseffekt hos utlokaliserade accesspunkter.

p˚ Statisk resursplanering a¨r ol¨ampligt f¨or ad hoc-n¨atverk,

som karakt¨ ariseras av f¨or¨ anderlighet och avsaknad av fast infrastruktur.

I avhandlingen presenteras tv˚ a algoritmer f¨or dynamisk topologikontroll som kan nyttjas f¨ or att uppn˚ a energieffektiv uts¨andning i s˚ av¨ al station¨ara som mobila n¨atverk.

Algoritmerna a¨r utv¨arderade genom simuleringar.

Acknowledgments

I wish to express my deepest and sincere gratitude to my supervisor Di Yuan,

Associate Professor and the head of Mobile Telecommunications group at the Department of Science and Technology (ITN),

for his excellent guidance throughout the four years I spent at Link¨ oping University and continuously challenging me to generate new ideas.

It has been a great pleasure for me to work with such an excellent researcher and extraordinary person,

from whom I tried to learn as much as I could.

I also wish to thank Professor Peter V¨ arbrand,

my supervisor and the head of our department,

for offering me this PhD position and his support and encouragement throughout these four years,

as well as for always being open to new ideas and ready to help.

I am very grateful for the financial support I received enabling my research during the four years provided by Center for Industrial Information Technology (CENIIT),

Link¨ oping Institute of Technology,

under project “Optimal Design och Effektive Planering av Telekommunikationssystem”.

I also appreciate the financial support I received during the last two years from Swedish Research Council (Vetenskapsr˚ adet) within two projects: “Mathematical Optimization in the Design of UMTS Networks” and “Energy-efficient Broadcasting in Mobile Ad Hoc Networks: Distributed Algorithms and Performance Simulation”.

I also wish to thank my current manager at Ericsson Research,

Johan Lundsj¨ o,

and the Spirit project for financially supporting my travel to two recent conferences: the 5th IEEE Intl.

Symposium on Modeling and Optimization in Mobile,

Ad Hoc,

and Wireless Networks (WiOpt 2007) and the 8th IEEE Intl.

Symposium on a World of Wireless,

Mobile and Multimedia Networks (WoWMoM 2007).

My research work on UMTS networks definitely benefitted from technical discussions with Dr.

Fredrik Gunnarsson and his colleagues at Ericsson Research in Link¨ oping,

who are also acknowledged for providing a test data set.

Also,

I am very grateful to Dr.

Fredrik Gunnarsson,

who was the opponent at my Licentiate seminar in March 2005,

for his valuable comments and suggestions on the Licentiate thesis.

My special thanks go to the group of the EU project Momentum IST-2000-28088 for making publicly available the data sets for several European cities,

which definitely made the results of my work on UMTS network planning and optimization more valuable from the application point of view.

I am very thankful to COST (European Cooperation in the field of Scientific and Technical Research) Action TIST 293 “Graphs and Algorithms in Communication Networks” for a financial support of my Short-Term Scientific Mission,

and the optimization group at Zuse Institute of Berlin,

Andreas Eisenbl¨ atter and Hans-Florian Geerdes,

for hosting the STSM which resulted in a joint paper that won the Best Paper Award in Helsinki at the WoWMoM 2007 Symposium.

Also,

I wish to thank Hans-Florian for providing his visualization software I used for generating nice figures in Chapter 7.

Jaouhar Jemai from Braunschweig Technical University is also acknowledged for generating radio propagation data for a WLAN.

I am grateful to Dr.

Peter Brostr¨ om,

Sandro Bosio,

Anders Peterson for

vi their detailed comments and practical suggestions that were very helpful in improving the presentation quality of this thesis.

I would also like to thank my colleagues at ITN for a friendly and inspiring atmosphere in the department.

Finally,

I would like to express my thanks to my family for their love and continued care,

and to my friends for their belief in me and being near.

Norrk¨oping,

September 2007 Iana Siomina

Contents Abbreviations

Optimization or Both

Bibliography

Network Planning and Resource Optimization for UMTS

Contents 3.5

Mathematical Programming Formulations .

A Solution Approach Based on Lagrangian Relaxation .

A Solution Approach Based on Column Generation .

Numerical Studies .

Discussion and Conclusions .

II Coverage Planning and Radio Resource Optimization for Wireless LANs 107 6 Introduction to Wireless LANs 109 6.1 Technical Background .

Contents 6.4 6.5

Performance Issues in IEEE 802.11 WLANs .

Network Planning and RRM Challenges in IEEE 802.11 WLANs 6.5.1 Channel Assignment .

Related Work .

III Managing Dynamic Power-efficient Broadcast Topologies in Ad Hoc Networks 173 9 Introduction to Ad Hoc Networks 9.1 The Concept of Ad Hoc Networking and Its 9.2 Research Challenges in Ad Hoc Networking 9.3 Broadcast Techniques in Ad Hoc Networks 9.4 Related Work .

Application .

Contents 9.4.2

Designing a Power-controlled Broadcast Topology .

Networks .

Bibliography

A UMTS Test Networks

B The Problem of Minimizing the Number of Cells with Blocked Users

C WLAN Test Networks and Parameter Setting

List of Tables 2.1 2.2

Similarities and differences between P-CPICH and S-CPICH .

Typical power allocation for the downlink common channels .

38 40

3.7 3.8

Ad hoc solutions for full coverage .

Optimal solutions obtained using CPLEX .

Solutions obtained by the Lagrangian heuristic .

Solutions obtained by the column generation approach .

Optimal and near-optimal solutions for a set of power levels obtained by discretization on linear scale .

Optimal and near-optimal solutions for a set of power levels obtained from discretization on logarithmic scale .

Ad hoc solutions with smooth handover .

Lagrangian heuristic solutions with smooth handover .

Solutions for various coverage degrees,

Net1 .

Solutions for various coverage degrees,

Net6 .

Solutions for various coverage degrees,

Net7 .

84 84 84

5.1 5.2

Radio base station antenna characteristics .

Test network characteristics .

Optimal solutions to W1-NAP for different serving thresholds .

Performance of network designs for three non-overlapping channels Performance of network designs for three overlapping channels .

Test scenarios .

Evaluation of reference configurations .

Optimal integer and LP solutions obtained by contention-aware optimization Channel assignment .

Channel coverage,

Lower bounds obtained by Approach 1,

Approach 2,

Lower and upper bounds obtained by decomposing the problem .

The key points of the algorithm cycle .

Parameters of the algorithm with probabilistic pruning Average backbone size .

Full connectivity duration .

Connectivity probing .

Connectivity information database update .

List of Tables 11.6 Possible state transitions for a PrGW node .

List of Figures 2.1 2.2 2.3 2.4 2.5 2.6 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10 4.1 4.2 4.3 4.4

UMTS network architecture.

Network planning and optimization.

Examples of horizontal and vertical antenna diagrams.

3D interpolation of antenna diagrams and the tilting effect on radio propagation.

The effect of changing design parameters on the received CPICH signal strength.

CPICH frame structure.

30 34 36

Modeling CPICH coverage.

The handover operation and cell overlap.

Set Aj of adjacent bins for bin j.

Total CPICH power in solutions obtained by different approaches.

CPICH signal strength characteristics in the uniform,

and optimized pilot power solutions for Net1,

Net6,

CPICH RSCP difference between the serving cell and the second,

Best-server CPICH power in two solutions for Net6,

Coverage statistics in the ad hoc and optimized CPICH power solutions for Net6.

Cell size statistics in the ad hoc and optimized CPICH power solutions for Net6.

CPICH power range discretization on linear and logarithmic scales (Net2-Net7).

Pareto’s principle (80/20 rule).

Cumulative distribution of cell CPICH power levels in the optimized solutions for Net6 for various traffic coverage degrees.

CPICH power consumption versus traffic coverage degree.

Optimized power solution for Net6,

36 36 37

83 83 83

Best-server path loss prediction maps.

antenna mechanical and electrical tilts,

IEEE 802.11 architectures.

Hidden and exposed terminal problems.

Three non-overlapping channels specified Centralized WLAN architecture.

7.1 7.2

Coverage overlap area of two APs.

IEEE 802.11b/g standards.

List of Figures 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.1 8.2 8.3 8.4 8.5 8.6

Candidate APs locations and path-loss predictions for location 22.

W1-WCO with 3 non-overlapping channels).144 Joint optimization (W1-NTWCO with 3 non-overlapping channels),

149 l'.