Resource Allocation for Next Generation Radio Access Networks

126 Pages·2016·11.2 MB·English

by  Vahid Samadi Bokharaie

Resource Allocation for
Next Generation Radio Access Networks
In Partial fulfilment of the requirements for the degree of
PhD
by:
Bahar Partov Poor
Supervisor:
Professor Douglas J. Leith
Hamilton Institute
Maynooth University
February, 2016

Contents
Contents i
List of Figures xiii
List of Tables xv
1 Introduction 1
1.1 Next Generation Radio Access Networks . . . . . . . . . . . . 1
1.1.1 Network Densification . . . . . . . . . . . . . . . . . . 2
1.1.2 Self Organisation . . . . . . . . . . . . . . . . . . . . . 4
1.2 Introductory Remarks . . . . . . . . . . . . . . . . . . . . . . 5
1.2.1 Multiple Access Strategies . . . . . . . . . . . . . . . . 5
1.2.2 Fairness and Utility Functions . . . . . . . . . . . . . . 7
1.2.3 Optimisation Tools . . . . . . . . . . . . . . . . . . . . 8
1.3 Outline of the Thesis . . . . . . . . . . . . . . . . . . . . . . . 8
1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 Antenna Tilt Angle Adaptation in LTE Networks 12
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3.1 Network Architecture . . . . . . . . . . . . . . . . . . . 13
2.3.2 Antenna Gain and Path Loss . . . . . . . . . . . . . . 14
2.3.3 User Throughput . . . . . . . . . . . . . . . . . . . . . 15
2.4 High SINR Regime . . . . . . . . . . . . . . . . . . . . . . . . 16
2.4.1 Utility Fair Optimisation of Tilt Angle . . . . . . . . . 17
2.4.2 Convexity Properties . . . . . . . . . . . . . . . . . . . 17
2.4.3 Convex Optimisation . . . . . . . . . . . . . . . . . . . 19
2.4.4 Difficulty of Using Conventional Dual Algorithms . . . 19
2.4.5 Distributed Algorithm for Finding Optimal Solution . . 19
2.4.6 Message Passing and Implementation . . . . . . . . . . 20
2.4.7 Example . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.5 Any SINR: Proportional Fair Rate Allocation . . . . . . . . . 24
2.5.1 Convexity Properties . . . . . . . . . . . . . . . . . . . 25
2.5.2 Convex Optimisation . . . . . . . . . . . . . . . . . . . 25
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2.5.3 Distributed Algorithm . . . . . . . . . . . . . . . . . . 26
2.5.4 Example . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . 27
2.7 LTE SIMO Links and MMSE Post-Processing . . . . . . . . . 29
2.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3 User Association in LTE/802.11 Networks 34
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.1.1 Motivating Example . . . . . . . . . . . . . . . . . . . 35
3.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.3 Network model . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.3.1 Network topology . . . . . . . . . . . . . . . . . . . . . 37
3.3.2 LTE throughput . . . . . . . . . . . . . . . . . . . . . 37
3.3.3 802.11 WLAN scheduling . . . . . . . . . . . . . . . . . 38
3.3.4 802.11 MAC slots . . . . . . . . . . . . . . . . . . . . . 40
3.3.5 802.11 throughput . . . . . . . . . . . . . . . . . . . . 40
3.3.6 Non-convexity of Network Rate Region . . . . . . . . . 44
3.4 Proportional Fair Rate Allocation . . . . . . . . . . . . . . . . 45
3.4.1 Utility Fair Optimisation . . . . . . . . . . . . . . . . . 45
3.4.2 Approximate Optimisation Via Maximal Convex Subsets 45
3.4.3 Adaptation of Maximal Convex Subsets . . . . . . . . 49
3.5 Motivating Example Revisited . . . . . . . . . . . . . . . . . . 52
3.5.1 Network Setup . . . . . . . . . . . . . . . . . . . . . . 52
3.5.2 Rate Allocations . . . . . . . . . . . . . . . . . . . . . 52
3.5.3 Convergence . . . . . . . . . . . . . . . . . . . . . . . . 53
3.6 Example Scenarios . . . . . . . . . . . . . . . . . . . . . . . . 53
3.6.1 802.11 Offload . . . . . . . . . . . . . . . . . . . . . . . 53
3.6.2 802.11 Multihoming . . . . . . . . . . . . . . . . . . . . 58
3.6.3 LTE Multihoming . . . . . . . . . . . . . . . . . . . . . 59
3.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4 Dynamic Power Adaptation in LTE/3G Small Cell Networks 62
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.3 System Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.3.1 RF Fingerprints . . . . . . . . . . . . . . . . . . . . . . 65
4.3.2 Classification . . . . . . . . . . . . . . . . . . . . . . . 66
4.4 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . 70
4.4.1 Cross Validation and Misclassification Error . . . . . . 70
4.4.2 Evaluation Using Synthetic Data Records . . . . . . . 74
4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5 Semi-Static Power Adaptation in LTE Small Cell Networks 80
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
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5.3 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
5.3.1 User Association . . . . . . . . . . . . . . . . . . . . . 82
5.3.2 User Throughput . . . . . . . . . . . . . . . . . . . . . 82
5.3.3 Base Station Energy Model . . . . . . . . . . . . . . . 83
5.3.4 Time Snapshots . . . . . . . . . . . . . . . . . . . . . . 83
5.3.5 User Report Data . . . . . . . . . . . . . . . . . . . . . 83
5.4 Balancing Energy Minimisation and User QoS . . . . . . . . . 84
5.4.1 Optimisation Problem . . . . . . . . . . . . . . . . . . 84
5.4.2 Non-Convexity of Optimisation . . . . . . . . . . . . . 84
5.4.3 Predictive Solution of Optimisation . . . . . . . . . . . 85
5.4.4 Simulated Annealing . . . . . . . . . . . . . . . . . . . 85
5.5 Performance Evaluation: Berlin City Centre . . . . . . . . . . 86
5.5.1 User traffic load and locations . . . . . . . . . . . . . . 87
5.5.2 Scenario A . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.5.3 Scenario B . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.5.4 Impact of Hotspot Location . . . . . . . . . . . . . . . 88
5.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
6 Concluding Remarks 93
6.1 Overview and Discussions . . . . . . . . . . . . . . . . . . . . 93
6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Bibliography 96
A Primal-Dual Updates: Convergence 103
A.1 Gradient Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 103
A.2 Fixed Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
A.3 Convergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
B LTE/802.11 User Association: Convergence 107
B.1 Proof of Theorem 3.4.1 . . . . . . . . . . . . . . . . . . . . . . 107
B.2 Proof of Theorem 3.4.2 . . . . . . . . . . . . . . . . . . . . . . 108
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Declaration
I hereby certify that this material, which I now submit for assessment on the
programme of study leading to the award of Doctor of Philosophy from the
Hamilton Institute is entirely my own work and has not been taken from the
work of others save and to the extent that such work has been cited and
acknowledged within the text of my work.
Signed:
Date: 1st Feb, 2016.
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Acknowledgement
I feel truly fortunate to be given the opportunity to pursue a research path
in stimulating environments of the Hamilton Institute, and Bell Laboratories
and alongside a number of very bright people. There are many people that I
would like to thank for their feedback and support in the past three years.
First and foremost, I’m forever grateful for the insight, and generous guidance
of my supervisor Prof. Douglas Leith, whose endless patience is beyond de-
scription. I’m most thankful for his help to making my time working on the
material of this thesis, a thoroughly constructive experience.
I also like to thank Dr. Holger Claussen and Dr. Rouzbeh Razavi of Bell Labs,
for providing me the opportunity to have a taste of research in industry and
for the helpful discussions. Thanks are also due to Dr. David Lopez-Perez,
Dr. Lester Ho, Dr. Vijay Venkateswaran, and Dr. Afra Mashhadi of Bell Labs
for their friendship and the technical conversations that we had in the past
few years. I have also benefited from discussions with Dr. David Malone, Dr.
Oliver Mason, Prof. Ken Duffy, Dr. Buket Benek Gursoy, Dr. Andreas Gar-
cia Saavedra, Dr. Cristina Cano and Dr. Mohammad Karzand of Hamilton
Institute, as well as many other fellow students. Also thanks go to Rosemary
Hunt and Kate Moriarty for their help with the various administrative issues
that needed to be dealt with, during the course of my research at the Institute.
On a more personal level, I’m forever indebted to my parents, to my dearest friend,
Bijan and to my good humoured brother, for not only tolerating me but also being
a constant supporting force over the years.
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Abstract
Driven by data hungry applications, the architecture of mobile networks is
moving towards that of densely deployed cells where each cell may use a dif-
ferent access technology as well as a different frequency band. Next generation
networks(NGNs)areessentiallyidentifiedbytheirdramaticallyincreaseddata
rates and their sustainable deployment. Motivated by these requirements, in
this thesis we focus on (i) capacity maximisation, (ii) energy efficient configu-
ration of different classes of radio access networks (RANs). To fairly allocate
the available resources, we consider proportional fair rate allocations. We
first consider capacity maximisation in co-channel 4G (LTE) networks, then
we proceed to capacity maximisation in mixed LTE (including licensed LTE
small cells) and 802.11 (WiFi) networks. And finally we study energy effi-
cient capacity maximisation of dense 3G/4G co-channel small cell networks.
In each chapter we provide a network model and a scalable resource allocation
approach which may be implemented in a centralised or distributed manner
depending on the objective and network constraints.
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Notations and Abbreviations
Notations:
Symbol Meaning
R The set of real numbers
Rn The set of all n-tuples of real numbers
N The set of natural numbers
E[.] The expected value of a random variable
I The indicator matrix
[.]+ The projection on the positive orthant
1 The indicator function
(x)
B The set of base stations
B The set of macro base stations
m
B The set of small cell base stations
sc
I The set of available LTE sub-channels
A The set of access points
A The set of access points in the geographic area of user u
u
U The set of users
U The set of users which can connect to AP a
a
U The set of users which can connect to AP a at time slot t
a,t
U The set of users in the geographic area of base station b
b
M The set of MAC slots of access point a that are fully contained
a,t
within time slot t
¯
M The set of MAC slots which are only partially contained
a,t
in time slot t
Ei The set of user-BS pairs for which transmissions
on sub-channel i interfere
Λ The set of Lagrangian multipliers
B A compact set in Rn
C A compact set of the feasible solutions
to a constrained optimisation problem
µ(Γ∩Σ) The volume of the intersection of two sets Γ and Σ
T The training data set of RF fingerprint vectors
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Symbol Meaning
N The set of neighbouring cells associated with
i
the RF fingerprint vector X
i
S The set of snapshots
S A zero mean Gaussian Random Variable
A A random variable denoting the access point which user u selects
u,t
at time slot t
N A random variable denoting the number of users associated
a,t
with access point a at time slot t
X A random variable indicating transmissions for the 802.11 user u
i,u
at MAC slot i
Y A random variable indicating successful transmission for 802.11
i,u
user u at MAC slot i
Z A random variable indicating absence of transmissions at
i
MAC slot i of the 802.11 channel
U(.) The utility function
L(.,Λ) The Lagrangian function
P(.) The penalty function associated a constrained optimisation problem
r The throughput of user u
u
r¯ The maximum achievable throughput
r The minimum acceptable throughput
γ The average signal to interference plus noise ratio for user u
u
γi The signal to interference plus noise ratio for user u on sub-channel i
u
γi The signal to noise ratio for base station b- user u pair on sub-channel i
b,u
ζi The fraction of time sub-channel i of BS b is used by user u
b,u
ω Total available bandwidth
ωi Bandwidth of sub-channel i
p The transmit power of base station b
b
σ2 The noise power at the receiver
n
p transmit power of user u
u
pp transmit power of pilot channels for base station b
b
pd transmit power of data channels for base station b
b
θ The tilt angle of base station b
b
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