Advanced wireless networks cognitive, cooperative opportunistic 4g technology 2nd edition

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ADVANCED WIRELESS
NETWORKS
Cognitive, Cooperative and
Opportunistic 4G Technology
Second Edition

Savo Glisic
Beatriz Lorenzo
University of Oulu, Finland

A John Wiley and Sons, Ltd., Publication

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ADVANCED WIRELESS
NETWORKS

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ADVANCED WIRELESS

NETWORKS
Cognitive, Cooperative and
Opportunistic 4G Technology
Second Edition

Savo Glisic
Beatriz Lorenzo
University of Oulu, Finland

A John Wiley and Sons, Ltd., Publication

www.allitebooks.com


This edition first published 2009
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Library of Congress Cataloging-in-Publication Data
Glisic, Savo G.
Advanced wireless networks : 4G technologies / Savo Glisic, Beatriz Lorenzo Veiga. – 2nd ed.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-470-74250-1 (cloth)
1. Wireless communication systems. I. Veiga, Beatriz Lorenzo. II. Title.
TK5103.2.G553 2009
621.384—dc22
2009001817
A catalogue record for this book is available from the British Library.
ISBN 978-0-470-74250-1 (H/B)
Typeset in 9/11 Times by Laserwords Private Limited, Chennai, India
Printed in Singapore by Markono Print Media Pte Ltd

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To our families

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Contents
Preface to the Second Edition

xix

1 Fundamentals
1.1
4G Networks and Composite Radio Environment
1.2
Protocol Boosters
1.2.1
One-element error detection booster for UDP
1.2.2
One-element ACK compression booster for TCP
1.2.3
One-element congestion control booster for TCP
1.2.4
One-element ARQ booster for TCP
1.2.5
A forward erasure correction booster for IP or TCP
1.2.6
Two-element jitter control booster for IP
1.2.7
Two-element selective ARQ booster for IP or TCP
1.3
Green Wireless Networks
References

1

1
7
9
9
9
9
10
10
11
11
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2 Opportunistic Communications
2.1
Multiuser Diversity
2.2
Proportional Fair Scheduling
2.3
Opportunistic Beamforming
2.4
Opportunistic Nulling in Cellular Systems
2.5
Network Cooperation and Opportunistic Communications
2.5.1
Performance example
2.6
Multiuser Diversity in Wireless Ad Hoc Networks
2.6.1
Multiple-output and multiple-input link diversity
2.6.2

Localized opportunistic transmission
2.6.3
Multiuser diversity-driven clustering
2.6.4
Opportunistic MAC with timeshare fairness
2.6.5
CDF-based K-ary opportunistic splitting algorithm
2.6.6
Throughput
2.6.7
Optimal opportunistic MAC

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viii

CONTENTS

2.7

2.8

2.6.8
Contention resolution between clusters
2.6.9
Performance examples
Mobility-Assisted Opportunistic Scheduling (MAOS)
2.7.1
Mobility models
2.7.2
Optimal MAOS algorithm
2.7.3
Suboptimum MAOS algorithm
2.7.4
Mobility estimation and prediction
2.7.5
Estimation of Lagrange multipliers
2.7.6
Performance examples
Opportunistic and Cooperative Cognitive Wireless Networks
2.8.1
The system model
2.8.2

The outage probability
2.8.3
Cellular traffic shaping
2.8.4
User mobility modeling
2.8.5
Absorbing Markov chain system model
2.8.6
Throughput analysis
2.8.7
Collision resolution
2.8.8
Opportunistic transmission with intercell interference awareness
2.8.9
Performance examples
References

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40
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48
49
51
51
52
52
53
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58

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68
70

3 Relaying and Mesh Networks
3.1
Relaying Strategies in Cooperative Cellular Networks
3.1.1
The system model
3.1.2
System optimization
3.1.3
Relay strategy selection optimization
3.1.4
Performance example
3.2
Mesh/Relay Networks
3.2.1
The system model
3.2.2
Exhaustive sleep
3.2.3
Practical applications
3.2.4
Performance example
3.3

Opportunistic Ad Hoc Relaying For Multicast
3.3.1
The system model
3.3.2
Proxy discovery and route interference
3.3.3
Near-optimal multicast and approximations
3.3.4
Performance examples
References

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73
73
75
79
84
85
86
88
94
95
97
98
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101
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4 Topology Control

4.1
Local Minimum Spanning Tree (LMST) Topology Control
4.1.1
Basics of MST topology control
4.1.2
Performance examples
4.2
Joint Topology Control, Resource Allocation and Routing
4.2.1
JTCR algorithm
4.3
Fault-Tolerant Topology
4.3.1
The system model
4.3.2
Fault-tolerant topology design
4.3.3
Þ-Approximation algorithms
4.3.4
Performance examples

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CONTENTS

4.4

ix

Topology Control in Directed Graphs
4.4.1
The system model
4.4.2
Minimum-weight-based algorithms
4.4.3
Augmentation-based algorithms
4.4.4
Performance examples
Adjustable Topology Control
4.5.1
The system model
4.5.2
The r -neighborhood graph
Self-Configuring Topologies
4.6.1
SCT performance
References

132

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148

5 Adaptive Medium Access Control
5.1
WLAN Enhanced Distributed Coordination Function
5.2
Adaptive MAC for WLAN with Adaptive Antennas
5.2.1
Description of the protocols
5.3
MAC for Wireless Sensor Networks
5.3.1
S-MAC protocol design
5.3.2
Periodic listen and sleep
5.3.3
Collision avoidance
5.3.4
Coordinated sleeping
5.3.5
Choosing and maintaining schedules

5.3.6
Maintaining synchronization
5.3.7
Adaptive listening
5.3.8
Overhearing avoidance and message passing
5.3.9
Overhearing avoidance
5.3.10 Message passing
5.4
MAC for Ad Hoc Networks
5.4.1
Carrier sense wireless networks
5.4.2
Interaction with upper layers
References

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157
160
160
166
167
168
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172

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179
180

6 Teletraffic Modeling and Analysis
6.1
Channel Holding Time in PCS Networks
References

183
183
191

7 Adaptive Network Layer
7.1
Graphs and Routing Protocols
7.1.1
Elementary concepts
7.1.2
Directed graph
7.1.3
Undirected graph
7.1.4
Degree of a vertex
7.1.5
Weighted graph
7.1.6

Walks and paths
7.1.7
Connected graphs
7.1.8
Trees
7.1.9
Spanning tree
7.1.10 MST computation
7.1.11 Shortest path spanning tree
7.2
Graph Theory

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4.5

4.6

x

CONTENTS

7.3
7.4

Routing with Topology Aggregation
Network and Aggregation Models
7.4.1
Line segment representation
7.4.2
QoS-aware topology aggregation
7.4.3
Mesh formation
7.4.4
Star formation
7.4.5
Line-segment routing algorithm
7.4.6
Performance measure
7.4.7
Performance example
References

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217

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228

8 Effective Capacity
8.1
Effective Traffic Source Parameters
8.1.1
Effective traffic source
8.1.2
Shaping probability
8.1.3
Shaping delay
8.1.4
Performance example
8.2
Effective Link Layer Capacity
8.2.1
Link-layer channel model
8.2.2
Effective capacity model of wireless channels
8.2.3
Physical layer vs link-layer channel model
8.2.4
Performance examples
References

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238
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9 Adaptive TCP Layer
9.1
Introduction
9.1.1
A large bandwidth-delay product
9.1.2
Buffer size
9.1.3
Round-trip time
9.1.4
Unfairness problem at the TCP layer
9.1.5
Noncongestion losses
9.1.6
End-to-end solutions
9.1.7

Bandwidth asymmetry
9.2
TCP Operation and Performance
9.2.1
The TCP transmitter
9.2.2
Retransmission timeout
9.2.3
Window adaptation
9.2.4
Packet loss recovery
9.2.5
TCP-OldTahoe (timeout recovery)
9.2.6
TCP-Tahoe (fast retransmit)
9.2.7
TCP-Reno fast retransmit, fast (but conservative) recovery
9.2.8
TCP-NewReno (fast retransmit, fast recovery)
9.2.9
Spurious retransmissions
9.2.10 Modeling of TCP operation
9.3
TCP for Mobile Cellular Networks
9.3.1
Improving TCP in mobile environments
9.3.2
Mobile TCP design
9.3.3
The SH-TCP client

9.3.4
The M-TCP protocol
9.3.5
Performance examples

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CONTENTS

9.4

9.5

Random Early Detection Gateways for Congestion Avoidance
9.4.1
The RED algorithm
9.4.2
Performance example
TCP for Mobile Ad Hoc Networks
9.5.1
Effect of route recomputations
9.5.2
Effect of network partitions
9.5.3
Effect of multipath routing
9.5.4
ATCP sublayer
9.5.5
ATCP protocol design
9.5.6
Performance examples
References

10 Network Optimization Theory

10.1 Introduction
10.2 Layering as Optimization Decomposition
10.2.1 TCP congestion control
10.2.2 TCP Reno/RED
10.2.3 TCP Vegas/Drop Tail
10.2.4 Optimization of the MAC protocol
10.2.5 Utility optimal MAC protocol/social optimum
10.3 Crosslayer Optimization
10.3.1 Congestion control and routing
10.3.2 Congestion control and physical resource allocation
10.3.3 Congestion and contention control
10.3.4 Congestion control, routing and scheduling
10.4 Optimization Problem Decomposition Methods
10.4.1 Decoupling coupled constraints
10.4.2 Dual decomposition of the basic NUM
10.4.3 Coupling constraints
10.4.4 Decoupling coupled objectives
10.4.5 Alternative decompositions
10.4.6 Application example of decomposition techniques to distributed
crosslayer optimization
10.5 Optimization of Distributed Rate Allocation for Inelastic Utility Flows
10.5.1 Nonconcave utility flows
10.5.2 Capacity provisioning for convergence of the basic algorithm
10.6 Nonconvex Optimization Problem in Network with QoS Provisioning
10.6.1 The system model
10.6.2 Solving the nonconvex optimization problem for joint
congestion–contention control
10.7 Optimization of Layered Multicast by Using Integer and Dynamic Programming
10.7.1 The system model
10.7.2 Lagrangian relaxation for integer programs

10.7.3 Group profit maximization by dynamic programming
10.8 QoS Optimization in Time-Varying Channels
10.8.1 The system model
10.8.2 Dynamic control algorithm
10.9 Network Optimization by Geometric Programming
10.9.1 Power control by geometric programming: high SNR
10.9.2 Power control by geometric programming: low SNR
10.10 QoS Scheduling by Geometric Programming

xi

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CONTENTS

10.10.1 Optimization of OFDM system by GP
10.10.2 Maximum weight matching scheduling by GP
10.10.3 Opportunistic scheduling by GP
10.10.4 Rescue scheduling by GP
References

344
344
345
345
346

11 Mobility Management
11.1 Introduction
11.1.1 Mobility management in cellular networks
11.1.2 Location registration and call delivery in 4G
11.2 Cellular Systems with Prioritized Handoff
11.2.1 Channel assignment priority schemes
11.2.2 Channel reservation – CR handoffs
11.2.3 Channel reservation with queueing – CRQ handoffs
11.2.4 Performance examples
11.3 Cell Residing Time Distribution
11.4 Mobility Prediction in Pico- and MicroCellular Networks
11.4.1 PST-QoS guarantees framework
11.4.2 Most likely cluster model

Appendix: Distance Calculation in an Intermediate Cell
References

351
351
353
355
374
377
377
378
382
383
388
390
391
398
403

12 Cognitive Radio Resource Management
12.1 Channel Assignment Schemes
12.1.1 Different channel allocation schemes
12.1.2 Fixed channel allocation
12.1.3 Channel borrowing schemes
12.1.4 Simple channel borrowing schemes
12.1.5 Hybrid channel borrowing schemes
12.1.6 Dynamic channel allocation
12.1.7 Centralized DCA schemes
12.1.8 Cell-based distributed DCA schemes
12.1.9 Signal strength measurement-based distributed DCA schemes

12.1.10 One-dimensional cellular systems
12.1.11 Reuse partitioning (RUP)
12.2 Dynamic Channel Allocation with SDMA
12.2.1 Single-cell environment
12.2.2 Resource allocation
12.2.3 Performance examples
12.3 Packet-Switched SDMA/TDMA Networks
12.3.1 The system model
12.3.2 Multibeam SDMA/TDMA capacity and slot allocation
12.3.3 SDMA/TDMA slot allocation algorithms
12.3.4 SDMA/TDMA performance examples
12.4 SDMA/OFDM Networks with Adaptive Data Rate
12.4.1 The system model
12.4.2 Resource allocation algorithm
12.4.3 Impact of OFDM/SDMA system specifications on resource allocations
12.4.4 Performance examples
12.5 Intercell Interference Cancellation – SP Separability

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CONTENTS

12.6

12.7

12.8

12.9

12.5.1 Channel and cellular system model
12.5.2 Turbo space–time multiuser detection for intracell communications

12.5.3 Multiuser detection in the presence of intercell interference
12.5.4 Performance examples
Intercell Interference Avoidance in SDMA Systems
12.6.1 The BOW scheme
12.6.2 Generating beam-off sequences
12.6.3 Constrained QRA-IA
Multilayer RRM
12.7.1 The SRA protocol
12.7.2 The ESRA protocol
Resource Allocation with Power Preassignment (RAPpA)
12.8.1 Resource assignment protocol
12.8.2 Analytical modeling of RAPpA
Cognitive and Cooperative Dynamic Radio Resource Allocation
12.9.1 Signal-to-interference ratio
12.9.2 System performance
12.9.3 Multicell operation
12.9.4 Performance examples
Appendix 12A: Power Control, CD Protocol, in the Presence of Fading
Appendix 12B: Average Intercell Throughput
References

13 Ad Hoc Networks
13.1 Routing Protocols
13.1.1 Routing protocols
13.1.2 Reactive protocols
13.2 Hybrid routing protocol
13.2.1 Loop-back termination
13.2.2 Early termination
13.2.3 Selective broadcasting (SBC)
13.3 Scalable Routing Strategies

13.3.1 Hierarchical routing protocols
13.3.2 Performance examples
13.3.3 FSR (fisheye routing) protocol
13.4 Multipath Routing
13.5 Clustering Protocols
13.5.1 Introduction
13.5.2 Clustering algorithm
13.5.3 Clustering with prediction
13.6 Cashing Schemes for Routing
13.6.1 Cache management
13.7 Distributed QoS Routing
13.7.1 Wireless links reliability
13.7.2 Routing
13.7.3 Routing information
13.7.4 Token-based routing
13.7.5 Delay-constrained routing
13.7.6 Tokens
13.7.7 Forwarding the received tokens
13.7.8 Bandwidth-constrained routing

xiii

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470
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491
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xiv

CONTENTS

13.7.9 Forwarding the received tickets
13.7.10 Performance example
References

562
564
567

14 Sensor Networks
14.1 Introduction
14.2 Sensor Networks Parameters
14.2.1 Pre-deployment and deployment phase

14.2.2 Post-deployment phase
14.2.3 Re-deployment of additional nodes phase
14.3 Sensor networks architecture
14.3.1 Physical layer
14.3.2 Data link layer
14.3.3 Network layer
14.3.4 Transport layer
14.3.5 Application layer
14.4 Mobile Sensor Networks Deployment
14.5 Directed Diffusion
14.5.1 Data propagation
14.5.2 Reinforcement
14.6 Aggregation in Wireless Sensor Networks
14.7 Boundary Estimation
14.7.1 Number of RDPs in P
14.7.2 Kraft inequality
14.7.3 Upper bounds on achievable accuracy
14.7.4 System optimization
14.8 Optimal Transmission Radius in Sensor Networks
14.8.1 Back-off phenomenon
14.9 Data Funneling
14.10 Equivalent Transport Control Protocol in Sensor Networks
References

573
573
575
576
576
577

577
578
578
581
585
586
587
590
591
593
593
596
598
598
599
600
602
606
607
610
613

15 Security
15.1 Authentication
15.1.1 Attacks on simple cryptographic authentication
15.1.2 Canonical authentication protocol
15.2 Security Architecture
15.3 Key Management
15.3.1 Encipherment
15.3.2 Modification detection codes

15.3.3 Replay detection codes
15.3.4 Proof of knowledge of a key
15.3.5 Point-to-point key distribution
15.4 Security management in GSM networks
15.5 Security management in UMTS
15.6 Security architecture for UMTS/WLAN Interworking
15.7 Security in Ad Hoc Networks
15.7.1 Self-organized key management
15.8 Security in Sensor Networks
References

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623
625
629
631
635
637
637
637
637
638
639
643
645
647
651
652
654

CONTENTS

xv

16 Active Networks
16.1 Introduction
16.2 Programable Networks Reference Models
16.2.1 IETF ForCES
16.2.2 Active networks reference architecture
16.3 Evolution to 4G Wireless Networks
16.4 Programmable 4G Mobile Network Architecture
16.5 Cognitive Packet Networks
16.5.1 Adaptation by cognitive packets
16.5.2 The random neural networks-based algorithms
16.6 Game Theory Models in Cognitive Radio Networks
16.6.1 Cognitive radio networks as a game
16.7 Biologically Inspired Networks
16.7.1 Bio-analogies
16.7.2 Bionet architecture
References

659
659
661
662
662
665
667
670

672
673
675
678
682
682
684
686

17 Network Deployment
17.1 Cellular Systems with Overlapping Coverage
17.2 Imbedded Microcell in CDMA Macrocell Network
17.2.1 Macrocell and microcell link budget
17.2.2 Performance example
17.3 Multitier Wireless Cellular Networks
17.3.1 The network model
17.3.2 Performance example
17.4 Local Multipoint Distribution Service
17.4.1 Interference estimations
17.4.2 Alternating polarization
17.5 Self-Organization in 4G Networks
17.5.1 Motivation
17.5.2 Networks self-organizing technologies
References

693
693
698
699
702

703
704
708
709
711
711
713
713
715
717

18 Network Management
18.1 The Simple Network Management Protocol
18.2 Distributed Network Management
18.3 Mobile Agent-Based Network Management
18.3.1 Mobile agent platform
18.3.2 Mobile agents in multioperator networks
18.3.3 Integration of routing algorithm and mobile agents
18.4 Ad Hoc Network Management
18.4.1 Heterogeneous environments
18.4.2 Time varying topology
18.4.3 Energy constraints
18.4.4 Network partitioning
18.4.5 Variation of signal quality
18.4.6 Eavesdropping
18.4.7 Ad hoc network management protocol functions
18.4.8 ANMP architecture
References

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CONTENTS

19 Network Information Theory
19.1 Effective Capacity of Advanced Cellular Networks
19.1.1 4G cellular network system model
19.1.2 The received signal
19.1.3 Multipath channel: near–far effect and power control
19.1.4 Multipath channel: pointer tracking error, rake receiver and interference
canceling
19.1.5 Interference canceler modeling: nonlinear multiuser detectors

19.1.6 Approximations
19.1.7 Outage probability
19.2 Capacity of Ad Hoc Networks
19.2.1 Arbitrary networks
19.2.2 Random networks
19.2.3 Arbitrary networks: an upper bound on transport capacity
19.2.4 Arbitrary networks: lower bound on transport capacity
19.2.5 Random networks: lower bound on throughput capacity
19.3 Information Theory and Network Architectures
19.3.1 Network architecture
19.3.2 Definition of feasible rate vectors
19.3.3 The transport capacity
19.3.4 Upper bounds under high attenuation
19.3.5 Multihop and feasible lower bounds under high attenuation
19.3.6 The low-attenuation regime
19.3.7 The Gaussian multiple-relay channel
19.4 Cooperative Transmission in Wireless Multihop Ad Hoc Networks
19.4.1 Transmission strategy and error propagation
19.4.2 OLA flooding algorithm
19.4.3 Simulation environment
19.5 Network Coding
19.5.1 Max-flow min-cut theorem (mfmcT)
19.5.2 Achieving the max-flow bound through a generic LCM
19.5.3 The transmission scheme associated with an LCM
19.5.4 Memoryless communication network
19.5.5 Network with memory
19.5.6 Construction of a generic LCM on an acyclic network
19.5.7 Time-invariant LCM and heuristic construction
19.6 Capacity of Wireless Networks Using MIMO Technology
19.6.1 Capacity metrics

19.7 Capacity of Sensor Networks with Many-to-One Transmissions
19.7.1 Network architecture
19.7.2 Capacity results
References

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20 Energy-efficient Wireless Networks
20.1 Energy Cost Function
20.2 Minimum Energy Routing
20.3 Maximizing Network Lifetime
20.4 Energy-efficient MAC in Sensor Networks
20.4.1 Staggered wakeup schedule
References

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CONTENTS

xvii

21 Quality-of-Service Management
21.1 Blind QoS Assessment System
21.1.1 System modeling
21.2 QoS Provisioning in WLAN
21.2.1 Contention-based multipolling
21.2.2 Polling efficiency
21.3 Dynamic Scheduling on RLC/MAC Layer
21.3.1 DSMC functional blocks
21.3.2 Calculating the high service rate
21.3.3 Heading-block delay
21.3.4 Interference model
21.3.5 Normal delay of a newly arrived block
21.3.6 High service rate of a session
21.4 QoS in OFDMA-Based Broadband Wireless Access Systems
21.4.1 Iterative solution
21.4.2 Resource allocation to maximize capacity
21.5 Predictive Flow Control and QoS
21.5.1 Predictive flow control model
References

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841
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842
842
846
848
849
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854

Index

859

www.allitebooks.com



Preface to the Second Edition
Although the first edition of the book was not published long ago, a constant progress in research
in the field of wireless networks has resulted in a significant accumulation of new results that urge
the extension and modification of its content. The major additions in the book are the following

new chapters: Chapter 1: Fundamentals, Chapter 2: Opportunistic Communications, Chapter 3:
Relaying and Mesh Networks, Chapter 4: Topology Control, Chapter 10: Network Optimization
and Chapter 12: Cognitive Radio Resource Management.

OPPORTUNISTIC COMMUNICATIONS
Multiuser diversity is a form of diversity inherent in a wireless network, provided by independent
time-varying channels across the different users. The diversity benefit is exploited by tracking the
channel fluctuations of the users and scheduling transmissions to users when their instantaneous
channel quality is near the peak. The diversity gain increases with the dynamic range of the
fluctuations and is thus limited in environments with little scattering and/or slow fading.
In such environments, the multiple transmit antennas can be used to induce large and fast channel
fluctuations so that multiuser diversity can still be exploited. The scheme can be interpreted as
opportunistic beamforming and true beamforming gains can be achieved when there are sufficient
users, even though very limited channel feedback is needed. Furthermore, in a cellular system,
the scheme plays an additional role of opportunistic nulling of the interference created on users
of adjacent cells. This chapter discusses the design implications of implementing this scheme in a
wireless system.

RELAYING AND MESH NETWORKS
In a wireless network with many source–destination pairs, cooperative transmission by relay nodes
has the potential to improve the overall network performance. In a distributed multihop mesh/relay
network (e.g. wireless ad hoc/sensor network, cellular multihop network), each node acts as a relay
node to forward data packets from other nodes. These nodes are often energy-limited and also have
limited buffer space. Therefore, efficient power-saving mechanisms (e.g. sleeping mechanisms) are


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PREFACE TO THE SECOND EDITION

required so that the lifetime of these nodes can be extended while at the same time the quality
of service (QoS) requirements (e.g. packet delay and packet loss rate) for the relayed packets
can be satisfied. In Chapter 3, a queuing analytical framework is presented to study the tradeoffs
between the energy saving and the QoS at a relay node as well as relaying strategies in cooperative
cellular networks. In addition integrated cellular and ad hoc multicast, which increases multicast
throughput through opportunistic use of ad hoc relays, is also discussed.

NETWORK TOPOLOGY CONTROL
Energy efficiency and network capacity are perhaps two of the most important issues in wireless
ad hoc networks and sensor networks. Topology control algorithms have been proposed to maintain
network connectivity while reducing energy consumption and improving network capacity.
The key idea to topology control is that, instead of transmitting with maximal power, nodes
in a wireless multihop network collaboratively determine their transmission power and define the
network topology by forming the proper neighbour relation under certain criteria. The topology
control affects network spatial reuse and contention for the medium.
A number of topology control algorithms have been proposed to create a power-efficient network
topology in wireless multihop networks with limited mobility. In Chapter 4, we summarize existing
work in this field. Some of the algorithms require explicit propagation channel models, while
others incur significant message exchanges. Their ability to maintain the topology in the case
of mobility is also rather limited. The chapter will discuss the tradeoffs between these opposing
requirements.

NETWORK OPTIMIZATION
Network protocols in layered architectures have traditionally been obtained on an ad hoc basis, and
many of the recent crosslayer designs are also conducted through piecemeal approaches. Network
protocol stacks may instead be systematically analyzed and designed as distributed solutions to
some global optimization problems. Chapter 10 presents a survey of the recent efforts toward a
systematic understanding of layering as optimization decomposition, where the overall communication network is modelled by a generalized network utility maximization problem, where each layer
corresponds to a decomposed subproblem and the interfaces among layers are quantified as functions of the optimization variables coordinating the subproblems. There can be many alternative
decompositions, leading to a choice of different layering architectures. This chapter will survey the

current status of horizontal decomposition into distributed computation and vertical decomposition
into functional modules such as congestion control, routing, scheduling, random access, power
control and channel coding. Key results are summarized and open issues discussed. Through case
studies, it is illustrated how layering as optimization decomposition provides a common language
to modularization, a unifying, top-down approach to design protocol stacks and a mathematical
theory of network architectures.

COGNITIVE RADIO RESOURCE MANAGEMENT
Network optimization, including radio resource management, discussed in Chapter 10, provides
algorithms that optimize system performance defined by a given utility function. In Chapter 12, we
present suboptimum solutions for resource management that include high level of cognition and
cooperation to mitigate intercell interference. An important segment of this topic dealing with the


PREFACE TO THE SECOND EDITION

xxi

flexible spectra sharing is covered in another of our books on Advanced Wireless Communications
focusing more on the physical layer, published by John Wiley & Sons, Ltd in 2007.
In addition to the new chapters, which represent about 40 % of the book, other chapters have
been also updated with latest results.
Savo Glisic
Beatriz Lorenzo