COOPERATION IN WIRELESS NETWORKS:

PRINCIPLES AND APPLICATIONS

Cooperation in Wireless Networks:

Principles and Applications

Edited by

FRANK H.P. FITZEK

Aalborg University, Denmark

and

Samsung Electronics Co. Ltd., Korea

MARCOS D. KATZ

Real Egoistic Behavior is to Cooperate!

A C.I.P. Catalogue record for this book is available from the Library of Congress.

ISBN-10 1-4020-4710-X (HB)

ISBN-13 978-1-4020-4710-7 (HB)

ISBN-10 1-4020-4711-8 (e-book)

ISBN-13 978-1-4020-4711-4 (e-book)

Published by Springer,

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All Rights Reserved

© 2006 Springer

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Printed in the Netherlands.

To Lilith and Samuel.

Contents

Dedication v

List of Figures xiii

List of Tables xxv

Contributing Authors xxvii

Foreword xliii

Foreword xlv

Acknowledgments xlvii

Preface xlix

Chapter 1

Cooperation in Nature and Wireless Communications 1Frank H. P. Fitzek and Marcos D. Katz

1. Basics of Cooperation 22. The Prisoner’s Dilemma 53. The Iterated Prisoner’s Dilemma 74. N–person Prisoner’s Dilemma 105. Stimulating Cooperative Behavior 126. Cooperation in Wireless Communication Systems 137. Cooperative Principles in Wireless Communications:

The Future 248. Conclusion 26References 26

Chapter 2

Cooperative Communications 29Arnab Chakrabarti, Ashutosh Sabharwal and Behnaam Aazhang

1. Introduction 302. A Brief History of Relaying 313. Preliminaries of Relaying 344. Relaying: Fundamental Limits 385. Practical Strategies for Relaying Information 516. Conclusion 61References 62

viii Contents

Chapter 3

Cooperation, Competition and Cognition in Wireless Networks 69Oh-Soon Shin, Natasha Devroye, Patrick Mitran, Hideki Ochiai, Saeed S.Ghassemzadeh, H. T. Kung and Vahid Tarokh

1. Introduction 712. Cooperative Diversity 743. Cooperative Beamforming 844. Cognitive Radio 885. Summary and Remarks 96References 97

Chapter 4

Cooperation Techniques in Cross-layer Design 101Shuguang Cui and Andrea J. Goldsmith

1. Introduction 1022. Cross-layer Design 1033. Node Cooperation in Wireless Networks 1074. Node Cooperation with Cross-layer Design 1085. Design Examples 110References 124

Chapter 5

Network Coding in Wireless Networks 127Desmond S. Lun, Tracey Ho, Niranjan Ratnakar, Muriel Medardand Ralf Koetter

1. Introduction 1282. Model 1323. Distributed Random Network Coding 1334. Cost Minimization 1425. Further Directions and Results 155References 158

Chapter 6

Cooperative Diversity 163J. Nicholas Laneman

1. Introduction 1632. Elements of Cooperative Diversity 1643. Cooperative Diversity in Existing Network Architectures 1734. Discussion and Future Directions 180References 183

Chapter 7

Cooperation in Ad-Hoc Networks 189Petri Mähönen, Marina Petrova and Janne Riihijärvi

1. Introduction 1902. Limits of Multihop 1953. Spectrum Cooperation 203

Contents ix

4. Topology Aware Ad Hoc Networks 2075. Hybrid Networks and 4G 2126. Discussion and Conclusions 214Acknowledgments 217References 217

Chapter 8

Multi-route and Multi-user Diversity 223Keivan Navaie and Halim Yanikomeroglu

1. Introduction 2232. Multi-route Diversity and Multi-user Diversity 2253. Cooperative Induced Multi-user Diversity Routing for

Multi-hop Infrastructure-based Networks with Mobile Relays 2324. Simulation Results 2385. Conclusion 239References 240

Chapter 9

Cognitive Radio Architecture 243Joseph Mitola III

1. Introduction 2442. Architecture 2533. CRA I: Functions, Components and Design Rules 2544. CRA II: The Cognition Cycle 2745. CRA III: The Inference Hierarchy 2796. CRA IV: Architecture Maps 2887. CRA V: Building the CRA on SDR Architectures 2958. Commercial CRA 3079. Future Direction 309References 310

Chapter 10

Stability and Security in Wireless Cooperative Networks 313Konrad Wrona and Petri Mahonen

1. Introduction 3142. Sustaining Cooperation 3153. Dynamics of Cooperative Communication Systems 3314. Conclusions and Discussion 357References 357

Chapter 11

Power Consumption and Spectrum Usage Paradigms in CooperativeWireless Networks

365

Frank H. P. Fitzek, Persefoni Kyritsi and Marcos D. Katz1. Motivation 3662. System under Investigation 3663. Time Division Multiple Access Cooperation 367

x Contents

4. Orthogonal Frequency Division Multiple Access Cooperation 3785. Conclusion 385References 386

Chapter 12

Cooperative Antenna Systems 387Patrick C. F. Eggers, Persefoni Kyritsi and Istvan Z. Kovacs

1. Introducing Antenna Cooperation 3882. Antenna Systems and Algorithms: Foundations

and Principles 3913. Channel Conditions, Measurements and Modeling: Practical

Channels 3984. Radio Systems: Performance Investigation 4055. General Conclusions on Practical Antenna Cooperation 416References 418

Chapter 13

Distributed Antennas: The Concept of Virtual Antenna Arrays 421Mischa Dohler and A. Hamid Aghvami

1. Introduction 4222. Background & State-of-the-Art 4233. Basic Application Principles 4294. Closed-Form Capacity Expressions 4325. Resource Allocation Protocols 4436. Case Studies & Observations 453References 459

Chapter 14

Cooperation in 4G Networks 463Marcos D. Katz and Frank H. P. Fitzek

1. Introduction 4632. Defining 4G 4653. Cooperation Opportunities in 4G 4764. Discussions and Conclusions 491References 493

Chapter 15

Cooperative Techniques in the IEEE 802 Wireless Standards:Opportunities and Challenges

497

Kathiravetpillai Sivanesan and David Mazzarese1. Introduction 4982. Mesh MAC Enhancement in IEEE 802.11s 4993. Mesh Mode Operation in IEEE 802.15 5014. Mesh Mode Operation in IEEE 802.16 5035. Mobile Multihop Relay PHY/MAC Enhancement for IEEE 802.16e 5036. Cognitive Radio/Spectrum Sharing Techniques in IEEE 802.22 5067. Conclusions 512References 513

Contents xi

Chapter 16

Cooperative Communication with Multiple Description Coding 515Morten Holm Larsen, Petar Popovski and Søren Vang Andersen

1. Introduction 5162. Multiple Description Coding (MDC) Basics 5193. Optimizing Multiple Description Coding for losses in the Cooperative

Context 5304. MDC with Conditional Compression (MDC–CC) 5345. Discussion 5396. Conclusion 542References 544

Chapter 17

Cooperative Header Compression 547Tatiana K. Madsen

1. Header Compression Principles 5482. Cooperative Header Compression 5503. Application Fields of the Cooperative Header Compression 5554. Tradeoff Between Compression Gain, Robustness

and Bandwidth Savings 5595. Conclusion 564References 565

Chapter 18

Energy Aware Task Allocation in Cooperative Wireless Networks 567Anders Brodlos Olsen and Peter Koch

1. Introduction 5682. Motivating Scenarios 5713. Energy Aware Computing in Cooperative Networks 5734. Modeling and Simulating Cooperative Energy Aware Computing 5805. Effects of System Parameters 5826. Summary 587References 589

Chapter 19

Cooperative Coding and Its Application to OFDM Systems 593Jerry C. H. Lin and Andrej Stefanov

1. Introduction 5932. System Model 5943. Performance Analysis of Coded Cooperative OFDM Systems 5954. Simulation Results 5995. Conclusions 604References 604

Chapter 20

Cooperative Methods for Spatial Channel Control 607Yasushi Takatori

1. Introduction 6072. Overview of SCC Methods 608

xii Contents

3. SCC with Multiple APs for High Density Hot Spots Scenario 6114. SCC with Multiple BSs for Multi-Cell Outdoor Systems 6195. Summary 627References 627

Glossary 631

Index 639

List of Figures

1.1 Cooperative Horizon. 5

1.2 Average payoff for seventy entities with five different strategiesfor 20000 iterations. 11

1.3 A practical classification of cooperation in wireless net works. 15

1.4 Relaying example with source node NB and relaying node NA

hoping to get paid off later. 18

1.5 Relaying example with source node NB and relaying node NA

having incentive to cooperate. 19

1.6 State of the art approach for wireless networks with autarkyterminals. 19

1.7 Cooperation among terminals exploiting the potential of com-bined data reception/transmission, battery, and processing unit. 21

1.8 Security example for cooperative wireless terminals. 24

2.1 Direct, two-hop and relay communications. 31

2.2 The relay channel with three nodes: the source S, the relay R, andthe destination D. These three nodes are conceptually dividedinto two subsets by two cuts of interest: C1 or the broadcast cutwhich separates S from {R, D}, and C2 or the multiple-accesscut, which separates {S, R} from D. The channel input at S isgiven by X , the input at R is W , and the outputs at R and D areV and Y respectively. 35

2.3 A network with multiple nodes divided in two sets S and SC

separated by a cut C. 40

2.4 Gaussian relay channel. 43

2.5 Regions where each protocol outperforms all others (P1 = P2 =−10dB, γ1 = 1). 46

2.6 Two states of the half-duplex relay channel. 48

2.7 Channel model for cooperation when source and relayexchange roles. 49

2.8 User cooperation using spreading codes. 51

xiv List of Figures

2.9 Factor graph for parity check matrix H and shorthand noations. 54

2.10 Factor graph for optimal decoding at the destination. 54

2.11 Factor graph of a pair of consecutive codes. 55

2.12 Factor graph for block-by-block successive decoding at the des-tination. 56

2.13 Performance of full-duplex relay coding scheme for the simpleprotocol. Performance of a single-user code using the same con-stituent parity check matrix is shown for comparison. Here sourceand relay are unit distance apart and the relay is on the line joiningthem at a distance d from the source. 56

2.14 LDPC code structure for ρ = 1. 57

2.15 LDPC code structure for ρ = 0. 58

2.16 Rate vs. Eb/N0. Theoretical limits and LDPC performance basedon thresholds. 60

2.17 BER vs. Eb/N0 for relay LDPC coding scheme (ρ = 1). 61

3.1 Inter-cluster behaviors of wireless networks. (a) Competitive be-havior. All messages are independent. (b) Cognitive behavior. Thethick solid arrow indicates that the second cluster has knowledgeof the messages of the first cluster, but not vice versa. (c) Cooper-ative behavior. The thick solid two-way arrow indicates that eachcluster knows the messages to be sent by the other cluster. 71

3.2 The cooperative communications problem for two transmit coop-erators and one receiver. 75

3.3 Outage probability of two transmit collaborators and onereceiver for various geometric gain factors G. (a) R = 0.5. (b)R = 2. 80

3.4 The three cooperators problem with one receiver. (a) Nodes r0,r1, and d are listening. (b) Node r0 has stopped listening andstarted cooperating. It transmits to nodes d and r1. (c) Node r1

has stopped listening and started cooperating. 81

3.5 Block diagram of the CO-OFDM transmitter and receiver (dottedblocks are used only in the cooperation phase). 82

3.6 The overall FER performance of the CO-OFDM system. 83

3.7 Definitions of notation for cooperative beamforming. 84

3.8 CCDF of beampattern with R = 2 and φ = π/4. 87

3.9 Dirty paper coding channel with input X, auxiliary random vari-able U, interference S known non-causally to the transmitter, ad-ditive noise Z and output Y. 88

3.10 The additive interference channel with inputs X1, X2, outputsY1, Y2, additive noise Z1, Z2 and interference coefficientsa12, a21. 89

List of Figures xv

3.11 The additive interference genie-aided cognitive radio channel withinputs X1, X2, outputs Y1, Y2, additive noise Z1, Z2 and interfer-ence coefficients a12, a21. S1’s input X1 is given to S2 (indicatedby the arrow), but not the other way around. 90

3.12 The modified cognitive radio channel with auxiliary random vari-ables M1, M2, N1, N2, inputs X1, X2, additive noise Z1, Z2, out-puts Y1, Y2 and interference coefficients a12, a21. 91

3.13 The modified Gaussian genie-aided cognitive radio channel withinterference coefficients a12, a21. 93

3.14 Achievable region of [Han and Kobayashi, 1981] (innermost poly-hedron), Theorem 3.5 (the next to smallest), and Corollary 3.6 (thesecond to largest), and the intersection of the capacity region ofthe 2 × 2 MIMO broadcast channel with the outer bound on R2

of an interference-free Gaussian channel of capacity 1/2 log(1 +P2/Q2) (the largest region). (a) Q1 = Q2 = 1, a12 = a21 =0.55, P1 = P2 = 6. (b) Q1 = Q2 = 1, a12 = a21 = 0.55,P1 = 6, P2 = 1.5. 94

3.15 A wireless network consisting of cognitive and possibly non-cognitive devices. Black nodes are senders (Si), striped nodesare receivers (Ri), and white nodes are neither (i.e., single nodeclusters). A directed edge is placed between each desired sender-receiver pair at each point /period in time. The graph has beenpartitioned into subsets of generalized MIMO channels. 95

4.1 Simplified layered structure. 105

4.2 Cross-layer Interaction. 107

4.3 Data collection in a sensor network. 111

4.4 Minimizing total energy consumption,R1 = 60pps,R2 = 80pps,R3 = 20 pps. 112

4.5 A clustered network. 114

4.6 A double-string network. 114

4.7 Cooperative transmission. 115

4.8 Equivalent SISO system. 116

4.9 Transmission Energy only. 117

4.10 Circuit energy included. 118

4.11 Sensor network with a fusion center. 119

4.12 Amplify and Forward. 120

4.13 (a) Power savings of optimal power allocation vs. uniform power;(b) Number of active sensors versus distance deviation. 122

5.1 Canonical example of network coding in wireline networks givenby [Ahlswede et al. 2000]. We denote by b1 + b2 the binary sumof bits b1 and b2. 129

xvi List of Figures

5.2 Figure 5.1 redrawn for wireless links. 129

5.3 A simple five-node wireless network employing network coding. 130

5.4 Figure 5.3 redrawn in its hypergraph representation. 134

5.5 Illustration of linear coding at a node. 134

5.6 A network consisting of two links in tandem. 139

5.7 Fluid flow system corresponding to two-link tandem network. 141

5.8 Cost optimization of a wireless network with multicast. Eachhyperarc is marked withziJ at the start and with the pair (x(6)

iJj , x(7)iJj)

at the ends. 143

6.1 Illustration of cooperative wireless transmission with (a) paral-lel relays and (b) serial relays. Colors indicate transmissions thatoccur in different time slots or frequency bands. Solid arrowsindicate transmissions that are utilized in traditional multihoptransmission. Cooperative communications utilizes transmissionscorresponding to both solid and dashed arrows by having theappropriate receivers perform some form of combining of theirrespective incoming signals. 165

6.2 Example outage performance of non-cooperative and cooperativetransmission computed via Monte Carlo simulations. The modelhas: path-loss with exponent α = 3, independent Rayleigh fading,network geometry with relays located at the midpoint between thesource and destination, spectral efficiency R = 1/2, and uniformpower allocation. 174

6.3 Matching algorithm performance in terms of average outage prob-ability vs. received SNR (normalized for direct transmission). 177

6.4 Matching algorithm results for an example network: (a) minimalmatching, (b) greedy matching. Terminals are indicated by circles,and matched terminals are connected with lines. 179

6.5 Clustering with (a) direct transmission and (b) cooperative diver-sity transmission. 180

6.6 Illustration of multi-stage cooperative transmission. Downstreamreceivers can combine signals from all upstream transmitters.Only one complicated “link” is presented to the network layer. 181

7.1 TCP/UDP multihop throughput measurements and simulations. 199

7.2 TCP throughput measured with 802.11a, 802.11b and 802.11g. 200

7.3 Comparison of a single BT link and a heterogeneous 3-hop con-nection consisting of BT, 802.11g and 802.11b. 201

7.4 The architecture of the unified link-layer API. 202

List of Figures xvii

7.5 An example of a four-node wireless network, with the interferencegraph together with the values assigned by the colouring algorithmon the left, and illustration of the resulting “cell structure” on theright. 206

7.6 A geometric graph modeling an Ad Hoc network with uniformlydistributed nodes in flat and curved terrain. 210

7.7 Using directional antennae in Ad Hoc networks for interferenceminimization and topology control. 211

7.8 Geometric graphs corresponding to stationary node location dis-tributions for random walk, random waypoint, and nomadic groupmobility models. Differences, especially in terms of clustering, areclearly visible. 212

8.1 Multi-route diversity in infrastructure-based multi-hop networks. 226

8.2 Multi-user diversity in an infrastructure-based network with mul-tiple users. 230

8.3 CIMDR for 2-hop transmission. 233

8.4 CIMDR two-phase protocol and packet structure. 234

8.5 CIMDR signaling: Normal transmission. 235

8.6 CIMDR signaling: Lost packet. 236

8.7 Normalized average achieved net throughput versus the numberof users. 239

8.8 Packet-drop-ratio (PDR) of CIMDR and single-hop multi-userdiversity scheduling for τmax = 2 and 10 seconds. 240

9.1 The CR Systems Engineer Augments SDR with ComputationalIntelligence. 255

9.2 Minimal AACR Node Architecture . 257

9.3 Discovering and Maintaining Services. 268

9.4 Simplified Cognition Cycle. 275

9.5 Natural Language Encapsulation in the Observation Hierarchy. 283

9.6 The Inference Hierarchy Supports Lateral Knowledge Sources. 285

9.7 Radio Skills Respond to Observations. 286

9.8 External Radio Knowledge Includes Concrete and AbstractKnowledge. 287

9.9 Architecture Based on The Cognition Cycle. 289

9.10 Cognitive Behavior Model Consists of Domains and TopologicalMaps. 292

9.11 SWR Principle Applied to Cellular Base Station. 296

9.12 Software Radio Principle - “ADC and DAC At the Antenna” MayNot Apply. 296

xviii List of Figures

9.13 SDR Design Space Shows How Designs Approach the IdealSWR. 297

9.14 SDR Forum (MMITS) Information Transfer Thread Architecture. 299

9.15 JTRS SCA Version 1.0; c© SDR Forum, Reprinted withPermission. 299

9.16 SDR Forum UML Model of Radio Services c SDR Forum, Usedwith Permission. 300

9.17 SDR Forum UML Management and Computational Architec-tures; c© SDR Forum, Used with Permission. 301

9.18 Functions-Transforms Model of a Wireless Nod. 302

9.19 Fixed Spectrum Allocations versus Pooling with CognitiveRadio. 305

10.1 Microeconomic models and relationship between identificationand incentives in cooperative systems. 316

10.2 The payoff matrix of Prisoner’s Dilemma game. 336

10.3 The payoff matrix of conditional cooperation game. 338

10.4 The normal form of simultaneous monitoring and reporting game. 339

10.5 The payoff matrix of cooperation monitoring game. 340

10.6 Necessary and sufficient asymptotic stability constraints for e2. 345

10.7 Necessary asymptotic stability constraints on p, m, and c for e3

and e4. 345

10.8 Necessary asymptotic stability constraints on p, h, and l for e3. 346

10.9 Necessary asymptotic stability constraints on p, m, and c for e5

and e6. 347

10.10 Necessary asymptotic stability constraints on p, h, and l for e5. 348

10.11 Additional stability constraints on p, m, and c for e6. 348

10.12 Bilateral IPD game used in simulation. 350

11.1 Example of cooperative groups with one central access point. 367

11.2 Scenario 1: Non cooperative reception of the J sub–streams. 368

11.3 Scenario 2: Cooperative reception of the J sub–streams. 369

11.4 Scenario 3: Cooperative reception of the J sub–streams. 370

11.5 Normalized energy versus number of cooperating terminals forall three scenarios with two WLAN cards. 374

11.6 Detailed power consumption versus number of cooperating ter-minals for Scenarios 2. 374

11.7 Example of an star configuration for the cooperating group withone terminal sending with 54 Mbit/s and others with 36 Mbit/s. 375

11.8 Cooperative group with some clustered and one exposedterminal. 377

List of Figures xix

11.9 Spectrum partitioning: The base station sends out four data streams(D1, D2, D3, D4) on the downlink frequencies on the left. Eachone is received by a different terminal, which in turn transmits thedata stream to its neighbors over the short–range frequencies onthe right, and receives the others on the rest of the short–rangefrequencies. 379

11.10 Examples where α equals 0,0.5, and 0.75. 385

12.1 Median rate improvement with relaying. 396

12.2 Cumulative distribution functions of the achievable rates for var-ious relative channel gains. 397

12.3 Median achievable rate for various power allocations, relativechannel gains and coding losses. 399

12.4 Sketch of indoor short range cooperative operation measurementscenario. 401

12.5 Shadow fading for all 4x4 trunks of the short range cooperativeoperation measurements. 402

12.6 Short term signal envelope distributions of the short range coop-erative operation measurements. 402

12.7 Total capacity of 4x4 MIMO with no power control. 405

12.8 Total capacity of 4x4 MIMO with MA power control. 406

12.9 Total capacity of 4x4 MIMO with instant power control (40dBrange). 406

12.10 Median achievable rate improvement with relaying (normalizedmeasured data such that E[g1] = E[g2]). 408

12.11 Rate cumulative distribution functions for two relative channelgains (normalized measured data such that E[g1] = E[g2]). 409

12.12 Median achievable rate improvement with relaying (normalizedmeasured data such that E[g1] = E[g2] + 3dB). 410

12.13 Rate cumulative distribution functions for two relative channelgains (normalized measured data such that E[g1] = E[g2]+3dB). 411

12.14 Median achievable rate improvement with relaying (normalizedmeasured data such that E[g1] = E[g2] − 3dB). 412

12.15 Rate cumulative distribution functions for two relative channelgains (normalized measured data such that E[g1] = E[g2]−3dB). 413

12.16 Median achievable rates in TETRA DMO scenarios versus rela-tive channel gains (normalized measured data such that E[g1] =E[g2]). 414

xx List of Figures

12.17 Rate cumulative distribution functions in TETRA DMO scenariosfor two relative channel gains (normalized measured data such thatE[g1] = E[g2]). 415

12.18 Median achievable rate improvement with relaying in UWB sys-tems (normalized measured data such that E[g1] = E[g2]): a)narrowband; b) wideband. 417

12.19 Rate cumulative distribution functions in UWB mobile-to-mobilescenarios for two relative channel gains (normalized measureddata such that E[g1] = E[g2]): a-b) narrowband; c-d) wideband. 418

13.1 Virtual Antenna Arrays in a cellular deployment. 423

13.2 Distributed and cooperative MIMO multi-stage communicationsystem. 428

13.3 Distributed sensor network, where a source sensor communicateswith a target sensor via a number of sensor tiers, each of which isformed of distributed relaying sensors. 433

13.4 Multiple-Input-Multiple-Output Transceiver Model. 434

13.5 Distributed STBC communication scenario with one transmitterand two cooperating receivers, all of which possess two antennaelements. 440

13.6 Capacity versus SNR for the scheme of Figure 13.5; γ1 + γ2 ≡ 8,γ1 : γ2 = 2 : 1. 441

13.7 Distributed-MIMO multi-stage communication system. 443

13.8 Established MIMO channels from the vth to the (v + 1)st VAArelaying tier. 448

13.9 Flowchart specifying the algorithmic method for determining thefractional bandwidth and power. 452

13.10 End-to-end throughput for optimum, near-optimum and sub-optimum resource allocation protocols for various two and threestage relaying networks. 455

14.1 Approaching 4G through convergence of cellular, nomadic(WLAN) and metropolitan (WMAN). 471

14.2 Network layers coverage. 473

14.3 Power consumption of past, present and future mobile communi-cation generations. 479

14.4 Power consumption breakdown of wireless terminals, Figure cour-tesy of Nokia. 481

14.5 Key practical challenges in 4G. 484

14.6 Can cooperation help us to reduce terminal complexity in 4G?. 486

14.7 Recent views on the role of heterogeneous networks in 4G: Gettingmobile and nomadic networks to cooperate. 488

List of Figures xxi

14.8 Network cooperation: Bringing together mobile and nomadic net-works. 489

14.9 Domains for cooperation in 4G mobile and wireless networks. 492

15.1 The IEEE 802.11s mesh operation from IEEE P802.11-04/0730d3[802wirelessworld, 2006]. 501

15.2 Operating scenario for two overlapping WRAN cells coexistingwith a television broadcasting station. 510

16.1 Source encoder (at the information source node) and source de-coder (at the destination node). 517

16.2 A simple cooperative network with two terminals and a Base Sta-tion (BS). The gray cloud denotes the cooperative link. 518

16.3 Scenario for cooperative reception of broadcast information withbase station and two terminals. 519

16.4 An example of a Z2 lattice (left) and an A2 lattice (right). Thedots are lattice points λ, the lines bounds the voronoi regions andarrows are the basis vectors. 521

16.5 An example of an A2 lattice and a similar sublattice (dashed) withN = 13. 525

16.6 In the top an example of a Z1 lattice and a clean sublattice whereN = 3. In the bottom a sublattice where N = 2 and not clean. 525

16.7 Block diagram of a two channel lattice vector quantizer. 526

16.8 A MDLVQ example with N1 = 5 and N2 = 9, where the Voronoiregions are shown on the left and the centroids on the right. Onthe left, the solid line is the lattice Λ, dashed line is the sublatticeΛ1, wide line is the sublattice Λ2. On the right, the solid line isthe Voronoi region Vs(0). 528

16.9 A communication network that provides two paths from S toD. X and Y are intermediate nodes along the paths. The feed-back from D is not available timely at S, but can be availableat X or Y . 535

16.10 An interpretation of a MDLVQ. 536

16.11 Access to multimedia content that is stored by MD encoding inthree content servers S1, S2 and S3. The user gets a full descrip-tion from the closest server (d2 from S2), while it retrieves thecompressed descriptions cd1, cd3 from the other two servers. 541

16.12 Broadcast scenario with cooperative destinations (MS1 andMS2)when the link from the source (base station BS) is unidirectionalsuch that feedback to the source is not available. 542

16.13 Meshed cooperation with three nodes, where each node is a sourceand a destination of information. lij denotes unidirectional linkbetween nodes i and j. 543

xxii List of Figures

17.1 The concept of context in header compression. 548

17.2 Delta coding approach. 549

17.3 The concept of context in header compression. 552

17.4 AICs construction for three cooperative channels. 552

17.5 Context healing in COHC by using AICs. 553

17.6 Possible Application Fields of the Cooperative Header Compres-sion Mechanism in next generation cellular networks. 556

17.7 Application of COHC in WLAN. 557

17.8 Presence of multiple channels in a multi-hop network. 558

17.9 Cooperation among terminals by AICs exchange through a short-range link. 558

17.10 Network overhead (RTP/UDP/IPv6) for the foreman video se-quence and the quantization parameter 41. 559

17.11 Expected bandwidth savings for the framed delta coding and co-operative compression (with three cooperative channels) with dif-ferent frame length N and different BER. Payload X is 40 bytes. 562

17.12 Expected bandwidth savings for COHC with different BER. L =3; X = 40 bytes. 563

17.13 Expected bandwidth savings for COHC with different number ofcooperative channels. BER = 10−3; X = 40 bytes. 564

18.1 The principle cooperation scenario between terminals within acellular network. A user receives input over a centralized link,which initiates workload on the terminal and by using a shortrange wireless links the workload is offloaded to other cooperativeusers. 569

18.2 Multiple description coding example of task distribution amongterminals for cooperative execution using centralized links to re-ceive the task and short range links to forward the decode result. 574

18.3 A non- and cooperative scenario of energy aware task allocation.Energy and workload levels are illustrated for both scenarios. 574

18.4 Analogy of cooperative terminals into a parallel/distributed sys-tem containing a number of computational elements connected bya given network architecture. 576

18.5 A task-set of two tasks with a periodic arrival. A traditional sched-ule indicating that slack time is introduced by the tasks-set, imply-ing idle time for the processing unit. A DVS schedule stretchesthe execution time of the task by speed scaling, utilizing avail-able time. In the bubble: a single task defined by its parameters,showing that task is utilized by scaling the speed. 578

List of Figures xxiii

18.6 Workload distribution, showing overheads introduced by the com-munication and also the potential decreasing scaling potential onthe remote terminal. 579

18.7 The utilization squared energy model, compared to measurementson an Analog Devices Blackfin 535 EZ-Kit Lite evaluation board.Normalized for speed and energy. 581

18.8 Energy consumption as a function of PU’s, both illustrated for theUS and the AD energy models. Showing the effect of hardwarequantization. 583

18.9 Effect of task distribution, where at the two left hand side plotsare task distribution ratios on two terminals. The right hand sideis task distribution ratios on three terminals. Shown at differentnetwork activity time levels. 584

18.10 Network power and active time shown as a function of terminalsand using the US energy model. Power shown in values {2, 1,0.75, 0.5} seen in sequence from top left to bottom right. Tasktime load in values {0.5, 0.4, 0.3, 0.25, 0.2, 0.15, 0.1, 0.05} seenfrom top to bottom in each plot. 586

18.11 Network power and activity time parameters shown as a func-tion of terminals and using the AD energy model. With similarparameter set-up as Figure 18.10. 586

18.12 Task-set utilization effect on similar task network load time asshowed in Figure 18.10 and showed for network power 0.75. 587

19.1 Time-division channel allocations: (a) orthogonal direct transmis-sion and (b) orthogonal cooperative diversity transmission. 595

19.2 Single user performance vs. two user cooperation, for differentinter-user channel qualities. 600

19.3 Single user performance versus two user cooperation, for twousers with different channel qualities. 601

19.4 Cooperative coding example, the inter-user channel has two taps,Lin = 2. 602

19.5 Cooperative coding example, (γin ≈ γ), the inter-user channelhas either one or two taps, Lin = 1 or Lin = 2. 603

20.1 Block diagram of a spatial channel control technique. 608

20.2 Configuration of digital reception beamforming. 609

20.3 Configuration of digital transmit beamforming. 610

20.4 MIMO channel capacity in i.i.d. fading environments. 612

20.5 MIMO channel capacity in LOS environment. 612

20.6 System configuration for a MAP-SCC. 613

20.7 Influence of SNR on the channel capacity of MAP–MIMO in thedirect path environment. 617

xxiv List of Figures

20.8 Channel capacity of MAP–MIMO in the direct path environment. 618

20.9 Cumulative probability of the achievable total throughput. 619

20.10 System configuration. 619

20.11 Asymmetrical environments in the uplink and the downlink. 620

20.12 Convergence performance of the MBS system. 624

20.13 An example of locations and powers of interference signals. 625

20.14 Influence of the distance between BSs. 626

List of Tables

1.1 The Prisoner’s Dilemma. 6

1.2 Axelrod’s Tournament Settings for the Prisoner’s Dilemma. 8

1.3 The Prisoner’s Dilemma Example for Wireless Communication. 22

5.1 Average energy of random multicast connections of unit rate forvarious approaches in random wireless networks of varying size.Nodes were placed randomly within a 10×10 square with a radiusof connectivity of 3. The energy required to transmit at unit rateto a distance d was taken to be d2. Source and sink nodes wereselected according to an uniform distribution over all possibleselections. 131

8.1 Simulation Parameters. 238

9.1 AACR N-Squared Diagram Characterizes AACR Node InternalInterfaces. 260

9.2 Radio Knowledge in the Node Architecture. 267

9.3 Features of AACR to be Organized via Architecture. 272

9.4 Standard Inference Hierarchy. 280

10.1 Comparison of the signed content formats. The performanceanalysis has been divided into two separate parts: message size andoverhead caused by the additional data and processing time forcreation, transmission and verification of signed content. Theratings range from [−−] (not satisfactory) to [++] (verysatisfactory). 329

10.2 Comparison of certificate validation mechanisms. 330

10.3 Parameters used in the game definition. 341

10.4 Necessary asymptotic stability constraints on p. 349

11.1 Parameters for the Analysis. 373

11.2 Cooperation Matrix for the Clustered and Exposed Terminal. 378

12.1 Statistics of short term signal power correlations from the shortrange cooperative operation measurements.The mean traces of theactual channels are shown in Figure 12.5. 400

xxvi List of Tables

14.1 Key characteristics of future 4G systems. 476

15.1 The IEEE 802 standardization activities that address cooperativetechniques across the different Working Groups. 498

15.2 Table The topology and operating scenarios considered in IEEE802.16 MMR-SG. 504

16.1 Second moment for the most popolar lattice, ([Conway and Sloane,1999]). 522

16.2 Label function α: The lattice points λ for a given λ1 (rows) andλ2 (column). 529

16.3 Label function β: The relative lattice points λ∗ for a given λ∗1

(column) and λ∗2 (rows). 537

16.4 Label function β: The offset lattice points λ+2 for a given λ∗

1 (col-umn) and λ∗

2 (rows). On the empty places the offset lattice pointis zero. 537

17.1 Compression gain for framed delta coding (FDC) and cooperativescheme (COHC). 560

18.1 Normalized speed values and energy consumptions for AD model,showing quantization due to hardware limitations. 583

Contributing Authors

Frank H.P. Fitzek Frank H. P. Fitzek is an Associate Professor in the Depart-ment of Communication Technology, University of Aalborg, Denmark headingthe Future Vision group. He received his diploma (Dipl.-Ing.) degree in elec-trical engineering from the University of Technology - Rheinisch-WestfälischeTechnische Hochschule (RWTH) - Aachen, Germany, in 1997 and his Ph.D.(Dr.-Ing.) in Electrical Engineering from the Technical University Berlin, Ger-many in 2002 for quality of service support in wireless CDMA networks. Asa visiting student at the Arizona State University he conducted research in thefield of video services over wireless networks. He co-founded the start-up com-pany acticom GmbH in Berlin in 1999. In 2002 he was Adjunct Professor atthe University of Ferrara, Italy giving lectures on wireless communications andconducting research on multi-hop networks. In 2005 he won the YRP award forthe work on MIMO MDC and in 2005 he received the Young Elite ResearcherAward of Denmark. His current research interests are in the areas of 4G wire-less communication networks, cross layer protocol design and cooperativenetworking.

Marcos D. Katz received the B.S. degree in Electrical Engineering fromUniversidad Nacional de Tucumán, Argentina in 1987, and the M.S. and Ph.D.degrees in Electrical Engineering from University of Oulu, Finland, in 1995 and2002, respectively. He worked as a Research Engineer at Nokia Telecommuni-cations from 1987 to 1995, designing analog circuits for high-speed PDH/SDHline interfaces. From 1995 to 2001 he was a Senior Research Engineer at NokiaNetworks, Finland, where he developed multiple antenna techniques for severalTDMA and CDMA research projects. In 2001-2002 he was a Research Scientistat the Centre for Wireless Communications, University of Oulu, Finland, wherehe concentrated on synchronization problems of CDMA networks. Since 2003Dr. Katz has been working as a Principal Engineer at Samsung Electronics,Advanced Research Lab., Telecommunications R&D Center, Suwon, Korea.His current research interests include synchronization, multi-antenna, and co-operative techniques, as well as optical wireless communications for future 4G

xxviii Contributing Authors

wireless communication systems. From the beginning of 2006 he is servingas the vice-chair of Working Group 5 (short-range communications) for theWireless World Research Forum (WWRF).

Anders Brødløs Olsen received his M.Sc.E.E. degree in signal processing withspecialization in Applied Signal Processing and Implementation from AalborgUniversity, Denmark, in 2002. From August 2002 he worked at the Center forIndlejrede Software Systemer (CISS), Aalborg University as research engineer,and from March 2004 he started towards the pursue of a Ph.D. degree at the de-partment for Communication Technology at Aalborg University, His researchinterests are overall energy conservation, within implementation issues fordynamic resource optimization for mobile wireless systems, with main focuson Dynamic Voltage Scaling (DVS) methods.

Andrea J. Goldsmith is an associate professor of Electrical Engineering atStanford University, USA, and was previously an assistant professor of Electri-cal Engineering at Caltech, USA. She has also held industry positions at MaximTechnologies and AT&T Bell Laboratories. Her research includes work on thecapacity of wireless channels and networks, wireless communication and infor-mation theory, adaptive resource allocation in wireless networks, multiantennawireless systems, energy-constrained wireless communications, wireless com-munications for distributed control, and cross-layer design for cellular systems,ad-hoc wireless networks, and sensor networks. She received the B.S., M.S.,and Ph.D. degrees in Electrical Engineering from U.C. Berkeley. Dr. Goldsmithis a Fellow of the IEEE and of Stanford, and currently holds Stanford’s BredtFaculty Development Scholar Chair. She has received several awards for herresearch, including the National Academy of Engineering Gilbreth Lectureship,the Alfred P. Sloan Fellowship, the Stanford Terman Fellowship, the NationalScience Foundation CAREER Development Award, and the Office of NavalResearch Young Investigator Award. She currently serves as editor for theJournal on Foundations and Trends in Communications and Information The-ory and in Networks, and was previously an editor for the IEEE Transactionson Communications and for the IEEE Wireless Communications Magazine.Dr. Goldsmith is active in the IEEE Information Theory and CommunicationsSocieties and is an elected member of the Board of Governor for both societies.She also serves as Vice President of the Communication Theory TechnicalCommittee of the Communications Society.

Andrej Stefanov received the B.S. degree in electrical engineering from Cyriland Methodius University, Skopje, Macedonia, in 1996. He received the M.S.and Ph.D. degrees in electrical engineering from Arizona State University,Tempe, AZ, in 1998 and 2001, respectively. During the summer 2000, he was

Contributing Authors xxix

with the Advanced Development Group, Hughes Network Systems, German-town, MD. He joined the Electrical and Computer Engineering Department ofthe Polytechnic University, Brooklyn, NY, as an assistant professor in October2001. His current research interests are in communication theory, wireless andmobile communications, wireless networks, channel coding and joint source-channel coding.

David Mazzarese received the Diplome d’Ingenieur in Electrical Engineeringfrom ENSEA (Ecole Nationale Superieure de l’Electronique et de ses Applica-tions), France, in 1998. In 1999, he joined TRLabs and the University of Alberta,Edmonton, Canada, in the Wireless Group directed by Dr. Witold Krzymien. Hereceived the Ph.D. in Computer and Electrical Engineering from the Universityof Alberta in 2005 for the thesis entitled “High Throughput Downlink Wire-less Packet Data Access with Multiple Antennas and Multi-User Diversity”.Currently, David Mazzarese is a research engineer with Samsung Electronicsin Suwon, South Korea, in the Global Standards and Research Lab, Telecom-munications Network R&D Centre. He is currently participating in the IEEE802.22 Working Group on Wireless Regional Area Networks. His research in-terests include multiuser MIMO systems, cooperative techniques and cognitiveradios.

Desmond S. Lun received the B.Sc. and B.E. (Hons.) degrees from the Univer-sity of Melbourne, Melbourne, Australia, in 2001, and the S.M. degree in 2002 inelectrical engineering and computer science from the Massachusetts Institute ofTechnology (MIT), Cambridge, where he is currently working toward the Ph.D.degree in the Department of Electrical Engineering and Computer Science. Hisresearch interests include network coding and wireless communications.

H. T. Kung received his Ph.D. degree from Carnegie Mellon in 1974 and B.S.degree from National Tsing Hua University in Taiwan in 1968. He is currentlyWilliam H. Gates Professor of Computer Science and Electrical Engineeringat Harvard University. Since 1999, he has co-chaired a joint Ph.D. programwith the Harvard Business School on information, technology and manage-ment. Prior to joining Harvard, he served on the faculty of Carnegie MellonUniversity from 1974 to 1992. Dr. Kung has pursued a variety of interests overhis career, including complexity theory, database theory, systolic arrays, VLSIdesign, parallel computing, computer networks, and network security. He lednumerous research projects on the design, implementation and experiment ofnovel computers and networks. In addition to his academic activities, he main-tains a strong link with industry by serving as a consultant and board member

xxx Contributing Authors

to numerous companies. Dr. Kung is a member of National Academy of Engi-neering in US and Academia Sinica in Taiwan.

Halim Yanikomeroglu was born in Giresun, Turkey, in 1968. He receiveda B.Sc. degree in Electrical and Electronics Engineering from the MiddleEast Technical University, Ankara, Turkey, in 1990, and a M.A.Sc. degree inElectrical Engineering (now ECE) and a Ph.D. degree in Electrical and Com-puter Engineering from the University of Toronto, Canada, in 1992 and 1998,respectively. He was with the Research and Development Group of MarconiKominikasyon A.S., Ankara, Turkey, from January 1993 to July 1994. Since1998 Dr. Yanikomeroglu has been with the Department of Systems and Com-puter Engineering at Carleton University, Ottawa, where he is now an AssociateProfessor with tenure. His research interests include almost all aspects of wire-less communications with a special emphasis on cellular multihop networks,radio resource management, and CDMA multi-antenna systems. At CarletonUniversity, he teaches graduate courses on digital, mobile, and wireless commu-nications. Dr. Yanikomeroglu has been involved in the steering committees andtechnical program committees of numerous international conferences in wire-less communications; he has also given several tutorials in such conferences.He was the Technical Program Co-Chair of the IEEE Wireless Communica-tions and Networking Conference 2004 (WCNC’04). He is an editor for IEEETransactions on Wireless Communications, and a guest editor for Wiley Journalon Wireless Communications & Mobile Computing; he was an editor for IEEECommunications Surveys & Tutorials for 2002-2003. Currently he is servingas the Chair of the IEEE Communication Society’s Technical Committee onPersonal Communications (2005-06), and he is also a member of the Society’sTechnical Activities Council (2005-06). Dr. Yanikomeroglu is a member of theAdvisory Committee for Broadband Communications and Wireless Systems(BCWS) Centre at Carleton University; he is also a registered ProfessionalEngineer in the province of Ontario, Canada.

Hamid Aghvami is presently the Director of the Centre for Telecommunica-tions Research at King’s. He has published over 300 technical papers and giveninvited talks all over the world on various aspects of Personal and Mobile RadioCommunications as well as giving courses on the subject world wide. He wasVisiting Professor at NTT Radio Communication Systems Laboratories in 1990and Senior Research Fellow at BT Laboratories in 1998-1999. He is currentlyExecutive Advisor to Wireless Facilities Inc., USA and Managing Directorof Wireless Multimedia Communications LTD. He leads an active researchteam working on numerous mobile and personal communications projects forthird and fourth generation systems, these projects are supported both by the

Contributing Authors xxxi

government and industry. He is a distinguished lecturer and a member of theBoard of Governors of the IEEE Communications Society. He has been member,Chairman, Vice-Chairman of the technical programme and organising commit-tees of a large number of international conferences. He is also founder of PIMRC& ICT. He is a fellow of the Royal Academy of Engineering, and fellow memberof the IEEE and IEE.

Hideki Ochiai received the B.E. degree in communication engineering fromOsaka University, Osaka, Japan, in 1996, and the M.E. and Ph.D. degrees ininformation and communication engineering from The University of Tokyo,Tokyo, Japan, in 1998 and 2001, respectively. From 2001 to 2003, he waswith the Department of Information and Communication Engineering, TheUniversity of Electro-Communications, Tokyo, Japan. Since April 2003, hehas been with the Department of Electrical and Computer Engineering, Yoko-hama National University, Yokohama, Japan, where he is currently an AssociateProfessor. From 2003 to 2004, he was a Visiting Scientist at the Division ofEngineering and Applied Sciences, Harvard University, Cambridge, MA, USA.Dr. Ochiai was a recipient of a Student Paper Award from the Telecommunica-tions Advancement Foundation in 1999 and the Ericsson Young Scientist Awardin 2000.

Istvan Z. Kovacs received his B.Sc. from ‘Politehnica’ Technical Univer-sity of Timisoara, Romania in 1989, his M.Sc.E.E. from The Franco-PolishSchool of New Information and Communication Technologies/ Ecole NationaleSupérieure des Télécommunications de Bretagne, Poland/France in 1996, andhis Ph.D.E.E. in Wireless Communications from Aalborg University, Denmarkin 2002. From 2002 to August 2005 he held the position of assistant researchprofessor with the Center For TeleInFrastruktur, Department of Communica-tion Technology of Aalborg University, in the Antennas and Propagation divi-sion. His research interests have been in the field of radio channel propagationmeasurements and modeling, with major focus on short-range ultra-widebandradio channel and ultra-wideband antenna investigations. He has been activelyinvolved in the European IST PACWOMAN and IST MAGNET projects andparticipated in several industrial projects with partners such as TeleDanmark,Motorola, IOSpan, and ArrayComm. He has made a number of paper contri-butions and has contributed to two book chapters on UWB propagation topics.Currently Istvan Z. Kovacs holds a position as a Wireless Networks Specialistin Network Systems Research/Nokia Networks, Aalborg, Denmark conductingresearch in the area of 3G/3.9G wireless networks.

xxxii Contributing Authors

J. Nicholas Laneman received B.S. degrees (summa cum laude) in ElectricalEngineering and in Computer Science from Washington University, St. Louis,MO, in 1995. At the Massachusetts Institute of Technology (MIT), Cambridge,MA, he earned the S.M. and Ph.D. degrees in Electrical Engineering in 1997and 2002, respectively. Since 2002, Dr. Laneman has been on the faculty ofthe Department of Electrical Engineering, University of Notre Dame, wherehis current research interest lie in wireless communications and networking,information theory, and detection & estimation theory. From 1995 to 2002,he was affiliated with the Department of Electrical Engineering and ComputerScience and the Research Laboratory of Electronics, MIT, where he held aNational Science Foundation Graduate Research Fellowship and served as botha Research and Teaching Assistant. During 1998 and 1999 he was also withLucent Technologies, Bell Laboratories, Murray Hill, NJ, both as a Member ofthe Technical Staff and as a Consultant, where he developed robust source andchannel coding methods for digital audio broadcasting. His industrial interac-tions have led to five U.S. patents. Dr. Laneman received the MIT EECS HaroldL. Hazen Teaching Award in 2001 and the ORAU Ralph E. Powe Junior FacultyEnhancement Award in 2003. He is a member of IEEE, ASEE, and Sigma Xi.

Janne Riihijarvi currently works as a senior project manager (the GOLLUMproject) and research assistant at the RWTH Aachen University in the Wire-less Networks Research Group (MobNets). Before joining Aachen Universityhe worked in various networking research projects at the University of Oulu,where he received his M.Sc. degree from in 2002, and at VTT Electronics. Hiscurrent research includes studying networking aspects of small mobile elec-tronic devices and theoretical aspects of large-scale networks.

Jerry C. H. Lin received the B.S. degree in electrical engineering and an-other B.S. degree (First Class Honors) with double major in pure and appliedmathematics from University of Calgary, Calgary, Alberta, Canada in 2002 and2003, respectively. He received the M.S. degree in electrical engineering fromPolytechnic University, Brooklyn, New York, in 2005.

Joseph Mitola III is a consulting scientist with The MITRE Corporation. Hepublished the first paper on software radios back in 1992. Dr. Mitola not onlycoined the widely used terms “software radio” and its evolutionary develop-ment, “cognitive radio”, but he created the fundamental associated technicalframework to make these enabling technologies one of the pillars of future wire-less communications. He was elected first chair of the global Software-DefinedRadio Forum in 1996, and continues to foster dual use military-civilian radio

Contributing Authors xxxiii

technology. His current research interests center on enhancing the computa-tional intelligence of software radios enabling future cognitive radios. Prior tojoining The MITRE Corporation in 1993, he was chief scientist of electronicsystems, E-Systems Melpar Division (now Raytheon Falls Church), where hewas responsible for research and technology development for communicationsand electronic warfare systems. He holds a Bachelor of Science in electricalengineering from Northeastern University (Highest Honors), a Master’s in engi-neering degree from the Johns Hopkins University, and a licentiate and doctoratein engineering from the Royal Institute of Technology (KTH). Stockholm, Swe-den (June 2000). Ever since its introduction almost 15 years ago Dr. Mitola hasbeen a prolific contributor, educator and writer on software radios, and morerecently on cognitive radios. He is the author of the books “Software RadioArchitecture”, Wiley, 2000, and “Cognitive Radio Architecture”, Wiley, 2006and co-editor of Software Radio Technologies: Selected Readings, Wiley-IEEEpress, 2001. In addition Dr. Mitola has served as guest editor of several IEEECommunication Magazines, and he has written numerous technical papers onhis subject.

Kathiravetpillai Sivanesan received the B.Sc. in Electrical and Electronic En-gineering from University of Peradeniya, Sri Lanka in 1996. He received hisM.Phil. in Telecommunications from University of Hong Kong in 2000. Then,he joined Icore wireless communication laboratory at University of Alberta,Canada and obtained his Ph.D. in 2005 under the supervision of Prof. N.C.Beaulieu. Currently, he is with Samsung Electronics as a research engineer atSuwon, South-Korea. His research interest lies in the general areas of commu-nication theory and statistical signal processing, more particularly cooperativetechniques, multiple antenna systems and interference cancellation.

Keivan Navaie received his B.Sc. degree from Sharif University of Technology,Tehran, Iran, his M.Sc. degree from the University of Tehran, Tehran, Iran, andhis Ph.D degree from Tarbiat Modarres University, Tehran, Iran, all in ElectricalEngineering in 1995, 1997 and 2004 respectively. From August 2002 to March2004, he was with Bell University Laboratories, University of Toronto. FromMarch to November 2004, he was with the School of Mathematics and Statistics,Carleton University, Ottawa, Canada, as a Postdoctoral Research Fellow. He iscurrently with the Broadband Communication and Wireless System Centre,System and Computer Engineering Department, Carleton University, Ottawa,Canada. His research interests are mainly in the radio resource managementissues of cellular and multi-hop wireless networks and traffic modelling.Dr. Navaie is a member of the IEEE.

xxxiv Contributing Authors

Konrad Wrona is currently a Principal Investigator in Security & Trust at SAPResearch Lab in Sophia Antipolis, France. He was born in Warsaw, Poland. Hewas awarded MSc in Telecommunications from Warsaw University of Tech-nology, Poland in 1997 and PhD in Electrical Engineering from RWTH AachenUniversity, Germany in 2005. He has over 8 years of work experience in indus-trial (Ericsson Research and SAP Research) and academic (Media Lab Europeand RWTH Aachen) research and development environment. He is author andco-author of over 20 publications and several patents. His research interestsinclude security in communication networks and distributed systems, securewireless applications, and electronic commerce.

Marina Petrova is currently working as a senior project manager and researchassistant at the RWTH Aachen University in the Wireless Networks ResearchGroup. She has a degree in electronics and telecommunication engineeringfrom the University St. Cyril and Methodius, Skopje, Macedonia. She was alsoa project manager for Aachen University in the European 6HOP project forheterogeneous multihop wireless networks. Her main research interest are inthe areas of ad hoc wireless networks, cognitive communication systems, andservice discovery.

Mischa Dohler obtained his MSc degree in Telecommunications from King’sCollege London in 1999, and his Diploma in Electrical Engineering from Dres-den University of Technology, Germany, in 2000. He has been lecturer at theCentre for Telecommunications Research, King’s College London, until June2005. He is now in the R&D department of France Telecom working on em-bedded and future communication systems. Prior to Telecommunications, hestudied Physics in Moscow. He has won various competitions in Mathemat-ics and Physics, and participated in the 3rd round of the International PhysicsOlympics for Germany. He has published numerous research papers and holdsseveral patents. He is a member of the IEEE, has been the Student Representativeof the IEEE UKRI Section and a member of the Student Activity Committee ofIEEE Region 8. He has also been the London Technology Network Business Fel-low for King’s College London. He has given five international short-courses,two on UMTS at WPMC02 & ATAMS02 and three on distributed cooperativesystems at VTC Spring 2004, COST273 & VTC Spring 2006.

Morten Holm Larsen was born in Denmark, on the 1’st of September 1978. Hereceived the M.Sc. degree in electrical engineering from Aalborg University,Aalborg, Denmark, in 2004. He is currently an PhD student at Aalborg Uni-versity in the Department of Communication Technology. His main research

Contributing Authors xxxv

interests are Multiple Description, data compression and digital communicationtheory.

Muriel Medard is a Harold E. and Esther Edgerton Associate Professor in theElectrical Engineering and Computer Science at MIT and the Associate Directorof the Laboratory for Information and Decision Systems. She was previously anAssistant Professor in the Electrical and Computer Engineering Department anda member of the Coordinated Science Laboratory at the University of IllinoisUrbana-Champaign. From 1995 to 1998, she was a Staff Member at MIT Lin-coln Laboratory in the Optical Communications and the Advanced NetworkingGroups. Professor Medard received B.S. degrees in EECS and in Mathematicsin 1989, a B.S. degree in Humanities in 1990, a M.S. degree in EE 1991, anda Sc.D. degree in EE in 1995, all from the Massachusetts Institute of Tech-nology (MIT), Cambridge. She serves as an Associate Editor for the OpticalCommunications and Networking Series of the IEEE Journal on Selected Areasin Communications, as an Associate Editor in Communications for the IEEETransactions on Information Theory and as a Guest Editor for the Joint spe-cial issue of the IEEE Transactions on Information Theory and the IEEE/ACMTransactions on Networking on Networking and Information Theory . She hasserved as a Guest Editor for the IEEE Journal of Lightwave Technology andas an Associate Editor for the OSA Journal of Optical Networking. ProfessorMedard’s research interests are in the areas of network coding and reliable com-munications, particularly for optical and wireless networks. She was awardedthe IEEE Leon K. Kirchmayer Prize Paper Award 2002 for her paper, “TheEffect Upon Channel Capacity in Wireless Communications of Perfect and Im-perfect Knowledge of the Channel,” IEEE Transactions on Information Theory,volume 46, issue 3, May 2000, pages 935–946. She was co-awarded the BestPaper Award for G. Weichenberg, V. Chan, M. Medard, “Reliable Architecturesfor Networks Under Stress,” Fourth International Workshop on the Design ofReliable Communication Networks (DRCN 2003), October 2003, Banff, Al-berta, Canada. She received a NSF Career Award in 2001 and was co-winner2004 Harold E. Edgerton Faculty Achievement Award, established in 1982 tohonor junior faculty members “for distinction in research, teaching and serviceto the MIT community.”

Natasha Devroye received her Bachelor’s degree in electrical engineering in2001 from McGill University, Montreal, PQ, Canada. She received her Mas-ter’s degree in 2003, and is currently working towards her Ph.D. degree bothin the Division of Engineering and Applied Sciences at Harvard University,Cambridge, MA, USA.

xxxvi Contributing Authors

Niranjan Ratnakar received the B.Tech. degree in electrical engineering fromthe Indian Institute of Technology, Madras in 2001 and the M.S. degree inelectrical and computer engineering from the University of Illinois at Urbana-Champaign in 2003. He is currently working toward the Ph.D. degree at theUniversity of Illinois at Urbana-Champaign. His research interests include net-work coding, multiterminal information theory, wireless communications, andalgebraic coding.

Oh-Soon Shin received the B.S., M.S., and Ph.D. degrees in electricalengineering from Seoul National University, Seoul, Korea, in 1998, 2000, and2004, respectively. Since March 2004, he has been with the Division of Engi-neering and Applied Sciences at Harvard University, Cambridge, MA, USA, asa postdoctoral research fellow. His research interests include wireless commu-nications, communication theory, and signal processing for communications.Dr. Shin received the Best Paper Award from CDMA International Conference2000.

Patrick Claus Friedrich Eggers has since 1992 been project leader of thepropagation group of CPK. He is now the research coordinator of the Antennasand Propagation division, Department of Communication Technology (KOM),Aalborg University (AAU). He is on the technical research council of the Centerfor TeleInFrastruktur (CTIF) at AAU, and has been project and work packagemanager in several European research projects (TSUNAMI, CELLO etc) andin industrial projects with partners such as Nokia, Ericsson, Motorola, IOSpan,ArrayComm, Avendo Wireless, Samsung etc., as representative of CTIF, KOM(and previously the center for PersonKommunikation-CPK). He is author ofover 40 papers, as well as section author and chapter editor in different COSTfinal reports (COST207, 231, 259) and books. He is initiator and coordinatorof an internationally targeted M.Sc.E.E. program in Mobile Communicationstaught in English at Aalborg University, as well as designer and coordinator ofthe newly starting programme in Software Defined Radio.

Patrick Mitran received the Bachelor’s and Master’s degrees in electricalengineering, in 2001 and 2002, respectively, from McGill University, Montreal,PQ, Canada. He is currently working toward the Ph.D. degree in the Division ofEngineering and Applied Sciences, Harvard University, Cambridge, MA, USA.His research interests include iterative decoding theory, joint source-channelcoding, detection and estimation theory as well as information theory.

Contributing Authors xxxvii

Persefoni Kyritsi received the B.S. degree in electrical engineering from theNational Technical University of Athens, Athens, Greece, in 1996, the M.S. andthe Ph.D. degrees in Electrical Engineering from Stanford University, Stanford,CA, in 1998 and 2002 respectively. She has worked in several aspects of wirelesscommunications for Lucent Technologies Bell Labs, in wireline communica-tions for Deutsche Telekom, Frankfurt- Germany, and in circuit design for IntelCorporation and the Nokia Research Center, Helsinki- Finland. She currentlyholds the position of Assistant Professor at the Department of Communica-tion Technology in Aalborg University, Aalborg, Denmark. Her research inter-ests include radio channel measurements, channel modeling, multiple antennasystems, radio propagation and information theory for multiple input-multipleoutput systems. Dr. Kyritsi is a member of Sigma Xi.

Petar Popovski received the Dipl.-Ing. in electrical engineering and M.Sc. incommunication engineering from the Faculty of Electrical Engineering, Sts.Cyril and Methodius University, Skopje, Macedonia, in 1997 and 2000, res-pectively. He received a Ph.D. degree from Aalborg University, Denmark, in2004. From 1998 to 2001 he was a teaching and research assistant at the Insti-tute of Telecommunications, Faculty of Electrical Engineering in Skopje. Heis currently Assistant Research Professor at the Department of Communica-tion Technology at the Aalborg University. His research interests are related towireless ad hoc networks, wireless sensor networks, random access protocols,joint optimization of source coding and network protocols, and error-controlcoding.

Peter Koch received his MSc and PhD degrees in Electronics Engineering fromAalborg University in 1989 and 1996, respectively. Since 1997 he has been em-ployed as an associate professor at Aalborg University, Institute for ElectronicSystems. In 2004 he was one of the funders of Center for TeleInFrastruktur,Aalborg University, and currently he is acting as co-director for this center.His research interests are methodologies for software design for heterogeneousmultiprocessor platforms, in particular with energy reduction as the driving costparameter.

Petri Mahonen is a full professor and Ericsson chair of wireless networks atthe RWTH Aachen University. Previously he studied and worked in the UnitedStates, the United Kingdom, and Finland. Before accepting his chair at RWTHAachen in 2002, he was working as a professor and research director of net-working at the Center for Wireless Communications, Oulu, Finland. He hasbeen principal investigator in several international research projects, includingseveral large European Union research projects for wireless communications.

xxxviii Contributing Authors

He has published over 100 journal and conference articles, and is author of over20 patents or patent applications. He has been also active on different standard-ization fora, and is consulting several multinational companies on wireless and4G research strategies. His current research with his students focuses on wire-less Internet, low-power communications including sensors, broadband wirelessaccess, applied mathematical methods for telecommunications, and cognitivenetworks and radios.

Ralf Koetter received the Diploma degree in electrical engineering from theTechnical University Darmstadt, Darmstadt, Germany, in 1990 and the Ph.D.degree from the Department of Electrical Engineering, Linkoping University,Sweden. From 1996 to 1997, he was a Visiting Scientist at the IBM AlmadenResearch Laboratory, San Jose, CA. He was a Visiting Assistant Professorat the University of Illinois at Urbana-Champaign, and a Visiting Scientist atCNRS, Sophia Antipolis, France, from 1997 to 1998. He joined the faculty ofthe University of Illinois at Urbana-Champaign in 1999, where he is currentlyan Associate Professor with the Coordinated Science Laboratory. His researchinterests include coding and information theory and their application to commu-nication systems. Dr. Koetter received an IBM Invention Achievement Awardin 1997, a National Science Foundation CAREER Award in 2000, and an IBMPartnership Award in 2001. He served as Associate Editor for coding theoryand techniques for the IEEE Transactions on Communications from 1999 to2001. In 2000, he started a term as Associate Editor for coding theory of theIEEE Transactions on Information Theory. He received the 2004 paper awardof the Information Theory Society of the IEEE and is a member of the Boardof Governors of this society.

Saeed S. Ghassemzadeh received his Ph.D. degree in electrical engineeringfrom the City University of New York in 1994. From 1989-1992, he was a con-sultant to SCS Mobilecom, a wireless technology development company, wherehe conducted research in the areas of propagation and CDMA systems. In 1992,SCS Mobilecom merged with IMM (International Mobile Machines) to formInterDigital Communications corp (http://www.interdigital.com). From1992-1995, while pursuing his Ph.D., he worked as a principal research engi-neer at InterDigital, where he conducted research in the areas of fixed/mobilewireless channels and was involved in system design, development, integra-tion, and testing of B-CDMA technology. During the same time, he was also anadjunct lecturer at City College of New York. In 1995, he joined AT&T Wire-less communication center of excellence at AT&T Bell-Labs (http://www.lucent.com) as a member of technical staff involved in design and develop-ment of the fixed wireless base station development team. He also conducted

Contributing Authors xxxix

research in all areas of CDMA access technologies, propagation channel mea-surement and modeling, satellite communications, wireless local area networksand coding in wireless systems. Currently, he is a senior technical specialistin Communication Technology Research department at AT&T Labs-Research(http://www.research.att.com), Florham Park, NJ. His current researchinterest includes ultra-wideband technologies, wireless channel measurementand modeling, wireless LANs and Cognitive Radio communication. Dr. Ghas-semzadeh is a senior member of IEEE, IEEE communication society and IEEEVehicular technology society.

Shuguang Cui is an assistant professor of Electrical and Computer Engineer-ing at the University of Arizona, USA. He received the B.Eng. degree in RadioEngineering with the highest distinction from Beijing University of Posts andTelecommunications, Beijing, China, in 1997, the M.Eng. degree in ElectricalEngineering from McMaster University, Hamilton, Canada, in 2000, and thePh.D. in Electrical Engineering from Stanford University, California, USA, in2005. From 1997 to 1998 he worked at Hewlett-Packard, Beijing, P. R. China,as a system engineer. In the summer of 2003, he worked at National Semicon-ductor, Santa Clara, CA, as a wireless system researcher. His current researchinterests include cross-layer optimization for energy-constrained wireless net-works, hardware and system synergies for high-performance wireless radios,and general communication theories. He is the winner of the NSERC graduatefellowship from the National Science and Engineering Research Council ofCanada and the Canadian Wireless Telecommunications Association (CWTA)graduate scholarship.

Søren Vang Andersen received his M.Sc and Ph.D degrees in electricalengineering from Aalborg University, Aalborg, Denmark, in 1995 and 1999,respectively. Between 1999 and 2002 he was with the Department of Speech,Music and Hearing at the Royal Institute of Technology, Stockholm, Sweden,and Global IP Sound AB, Stockholm, Sweden. Since 2002 he is an associateprofessor with the digital communications (DICOM) group at Aalborg Uni-versity. Søren Vang Andersen’s research interests are within multimedia signalprocessing: coding, transmission, and enhancement.

Tatiana Kozlova Madsen received the M.Sc and Ph.D degrees in Mathemat-ics from Moscow Lomonosov State University, Moscow, Russia, in 1997 and2000, respectively. From 2001 she joined the Department of CommunicationTechnology, Aalborg University where she is currently an Assistant Profes-sor. She undertakes research and teaching within wireless communication andnetworking areas. Her current research interests are in the areas of wireless

xl Contributing Authors

networking and mathematical modelling of communication systems and proto-cols. She is particular interested in influence of wireless channel and wirelessaccess technologies on the behavior of the upper layer protocols and protocolsoptimization for wireless links. Dr. Madsen is an Associate Editor of SpringerJournal of Wireless Personal Communications responsible for the networkingarea.

Tracey Ho received S.B. and M.Eng. degrees in electrical engineering (1999)and a Ph.D. in electrical engineering and computer science (2004) from theMassachusetts Institute of Technology. She has done postdoctoral work at theUniversity of Illinois at Urbana-Champaign and Lucent’s Bell Labs. She iscurrently an Assistant Professor at the California Institute of Technology and anassociate editor for the IEEE Communications Letters. Her research interests areat the intersection of information theory, networking, wireless communicationsand machine learning.

Vahid Tarokh received the Ph.D. degree in electrical engineering from theUniversity of Waterloo, Waterloo, ON, Canada, in 1995. He then worked atAT&T Labs-Research, Florham Park, NJ, and AT&T wireless services untilAugust 2000 as a Member, Principal Member of Technical Staff, and finally theHead of the Department of Wireless Communications and Signal Processing.In September 2000, he joined the Department of Electrical Engineering andComputer Science, Massachusetts Institute of Technology (MIT), Cambridge,MA, as an Associate Professor, where he worked until June 2002. Since June2002, he is with Harvard University, Cambridge, MA, where he is a Professorof Applied Mathematics and a Senior Fellow in Electrical Engineering. Dr.Tarokh has received a number of awards, including the 1987 Gold Tablet ofThe Iranian Math Society, the 1995 Governor General of Canada’s AcademicGold Medal, the 1999 IEEE Information Theory Society Prize Paper Award,and the 2001 Alan T. Waterman Award. In 2002, he was selected as one of thetop 100 young inventors of the year by the Technology Review Magazine. Hehas received honorary degrees from Harvard University and The University ofWindsor.

Yasushi Takatori was born in Tokyo, Japan, 1971. He received his B.E. degreein electrical and communication engineering and his M.E. degree in systeminformation engineering from Tohoku University, Sendai, Japan in 1993 and1995, respectively. He received his Ph.D. degree in wireless communicationengineering from Aalborg University, Denmark in 2005. In 1995, he joined theNTT Wireless Systems Laboratories, Nippon Telegraph and Telephone Cor-poration (NTT), in Japan. He is now working on NTT Network Innovation

Contributing Authors xli

Laboratories. He was a visiting researcher at the Center for TeleInFrastruc-ture (CTIF), Aalborg University, Aalborg, Denmark from 2004 to 2005. Hereceived the Young Engineers Award from the IEICE of Japan in 2000, theExcellent Paper Award of WPMC in 2004 and YRP Award in 2005. His currentresearch interest is smart antennas, MIMO systems and spatial signal processingtechniques. He is an associate editor of Springer Journal of Wireless PersonalCommunications. He is a member of the IEEE and the IEICE.

Foreword

by Professor Robert Axelrod

Cooperation has been the subject of intensive study in the social and biologicalsciences, as well as in mathematics and artificial intelligence. The fundamentalfinding is that even egoists can sustain cooperation provided the structure oftheir environment allows for repeated interactions (Axelrod 1984).

Some truly remarkable illustrations of this principle have recently appearedin the realm of information systems. One example is the success of open source(Axelrod and Cohen, 1999; Weber 2005) in which thousands of people coop-erate to build a system, such as Linux. Another example is the success of eBaywhich is based on a feedback system that allows strangers to trust each otherbased upon the validity of the reputations for cooperating with others in thepast. Still another example is Wikipedia, an encyclopedia to which anyone cancontribute, and which by means of peer cooperation attains remarkable cover-age and quality.

Wireless networks provide yet another realm in which cooperation amonglarge numbers of egoists can be attained, provided that the right institutionalstructure can designed and implemented. Wireless communications is a rapidlyemerging area of technology. Its success will depend in large measure onwhether self-interested individuals can be provided a structure in which they areproper incentives to act in a cooperative mode. The editors and contributors toCooperation in Wireless Networks demonstrate that our understanding of howcooperation works in a variety of other realms can illuminate what it will takefor wireless technology to realize its full potential.

Axelrod, Robert, The Evolution of Cooperation (NY: Basic Books, 1984).

Axelrod, Robert and Michael D. Cohen, Harnessing Complexity (NY:Free Press, 1999).

xliv Foreword

Cohen, Adam. The Perfect Store: Inside Ebay, (NY: Little, Brown; 2002).

Weber, Steven, The Success of Open Source (Cambridge: MA: HarvardUniversity Press, 2005).

Robert Axelrod, November, 2005Gerald Ford School of Public PolicyUniversity of MichiganAnn Arbor, MI 48109axe@umich.edu

Foreword

by Professor John G. Proakis

It is with pleasure that I write this Forward to the book on cooperation in wire-less communications. This is indeed a unique book that treats an emerging topicin wireless communications. As the reader will observe in reading this book,cooperative techniques can be employed across different layers of a communi-cation system and across different communication networks. Such techniquesare based on the premise that through cooperation, all participants engaged incooperative communication will achieve some benefit.

The editors in their introductory chapter categorize cooperation as either Im-plicit, or Explicit Macro, or Explicit Micro (Functional) Cooperation. Examplesof implicit cooperation are communication protocols such as TCP and ALOHA.In such protocols, participants share a common resource based on fair sharingof that resource but without experiencing any other tangible gain and withoutthe establishment of any particular framework for cooperation.

In contrast, explicit macro cooperation is characterized by a specified frame-work and established by design. Cooperative entities that fall in this category arewireless terminals and routers, which may cooperate, for example, by employingrelaying techniques that extend the range of communication for users beyondtheir immediate coverage area. Such cooperation potentially provides mutualbenefits to all users.

Explicit micro or functional cooperation is also characterized by a specificframework that is established by design. However, the cooperation involvesfunctional parts or components of various entities, such as antennas in wirelessterminals, processing units in mobile computing devices, and batteries in mobiledevices. Explicit micro cooperation provides the potential for building lowcomplexity wireless terminals with low battery consumption.

xlvi Foreword

In the chapters contained in the book, the reader will find in-depth treat-ments of various aspects of cooperation in wireless communications. Amongtopics covered are fundamental limits, enabling technologies and implemen-tation issues for cooperative communications; cooperative coding techniquesfor wireless networks; security in wireless cooperative networks; relaying andmultihop techniques; energy aware allocation techniques in cooperative wire-less networks; and perspectives on cooperative techniques in 4th generationnetworks.

I am confident that this book will stimulate and challenge both the academicand industrial communities in the field of telecommunications, as researchersand groups of engineers investigate, design and implement future wireless com-munication networks.

John G. Proakis, December, 2005Northeastern University516 Dana Research BuildingDepartment of Electrical and Computer EngineeringBoston, MA 02115proakis@ece.neu.edu

Acknowledgments

The hardest arithmetic to master is that which enables us to count ourblessings.

Eric Hoffer

The present book is the result of the coordinated efforts of many people, andit would have not been possible without the key contributions of our invitedauthors. We are deeply indebted and immensely proud to have each and everyone of them contributing in this book. We thank you all for sharing with us yourtechnical expertise, and for the professionalism and endless enthusiasm showedduring the writing period.

We would like to thank Prof. Ramjee Prasad from Aalborg University, Den-mark and Sr.V.P. Dr. Young Kyun Kim, from Samsung Electronics, Korea.Their support and open minded attitude towards new technical horizons wereinstrumental to carry out this project. We also thank Prof. Torben Larsen fromAalborg University for his valuable comments and support.

We are greatly beholden to Prof. Robert Axelrod from University of Michi-gan, USA, and Prof. John Proakis from Northeastern University, USA for theirencouragement as well as for their kindness in writing, in their respective fields,both Forewords.

We wish sincerely to thank Dr. Tim Brown and Mr. Robert Sheahan fromAalborg University for their invaluable help in proof reading several chaptersof the book.

We are particularly thankful to Mark de Jongh and Cindy Zitter, from Springerfor their encouragement, patience and flexibility during the whole editionprocess. We also thank Rajeshwari Thiagarajan and Werner Hermens for theirkind help during the final edition.

xlviii Acknowledgments

We would also like to thank all our colleagues in Aalborg University andSamsung Electronics for their encouragement and interest. Henrik Benner, OleBenner, Finn Hybjerg Hansen, Per Mejdal Rasmussen, Bo Nygaard Bai, SvendErik Volsgaard and Torben H. Knudsen, from the KOM Computer WorkShopdeserve our sincere thanks and appreciation for keeping this project web siteup and running day and night, and for always providing us with technical assis-tance and handy solutions. We thank Simone Zecchetto for his nice illustration.We are grateful to our secretaries, Hanne Gade and Kirsten Jensen in Aalborgand So-youn Park in Korea, for their helpful and continuous assistance.

Finally, but most importantly, we Editors would like to thank our betterhalves, Sterica and Paula, and our children, Lilith and Samuel, for their unfail-ing support and for being so understanding while we worked on this book.

Preface

None is so great that he needs no help, and none is so small that he cannotgive it.

King Solomon

It is important for him who wants to discover not to confine himself to onechapter of science, but to keep in touch with various others.

Jacques Hadamard

The idea of a book on cooperation in wireless networks was conceivedand essentially implemented through cooperation. While working on a jointacademia-industry research project on future wireless communication systems,we realized that a great deal of techniques having the potential to tackle many ofthe identified technical challenges exploited cooperative principles. Cooperationhas been and continues to be a subject of intense research in many disciplines,notably natural, social and economic sciences. More recently, cooperation hasstarted to receive attention in other sciences, particularly in engineering. In thelast years, we have witnessed an increasing interest in exploring cooperativetechniques in the domain of wireless communications. There are several rea-sons explaining such an interest. In the first instance, wireless communicationsystems are increasingly becoming more complex, with local processing influ-enced or even governed by other entities or global conditions. More and moresystem parts, protocols and algorithms are designed to support elaborated in-teractions between entities or functions. Sometimes it is even convenient to seeconventional procedures in a wireless system from the cooperation perspective:the simplest communication between two terminals in the ubiquitous cellulararchitecture can be described by a cooperative model. Also, the steady emer-gence of distributed access architectures, independent of centralized decisions,is paving the way towards cooperative interactions between nodes. Moreover,opportunities for interaction also arise as new and planned wireless systemsoffer more fine-grain resource availability than ever, in particular in the time,

l Preface

frequency and spatial domains. Furthermore, cooperation in wireless communi-cations is emerging as a key technology as we are consistently finding technicalevidence that cooperating does pay off.

Cooperation can be understood as a joint action for mutual benefit. In wire-less networks that definition is still valid but since there is a broad diversity inpossible interacting entities, cooperation needs to be approached more widely.Cooperating entities do not necessarily need to be of the same type and thebenefits obtained may vary from entity to entity. Cooperative techniques canbe applied within and across the OSI layers and they can take place even be-tween heterogeneous networks. Cooperative mechanisms can be embedded inthe system and cooperation may then happen as a part of the normal interactionsneeded to move information across the network, without the knowledge or spe-cific consent of the involved users. However, in some cases users themselvescould be in a key position to allow cooperation by sharing their resources, i.e.,terminals, with each other. In such a case, clear incentives are needed.

Cooperation has different connotations and meanings in wireless communi-cations. On the communicational perspective, cooperation embraces a numberof techniques taking advantage of the synergetic interaction of more than oneentity as well as the collaborative use of resources, all aiming to enhance perfor-mance. Entities in this context can be defined at many levels, including signals,functions, algorithms, processing elements, building blocks and complete units,to name a few. Examples of this type of cooperation abound and it is the maincooperative approach dealt with in this book. From a purely operational point ofview, cooperation implies the interaction and negotiating procedures betweenentities needed to establish and maintain interoperation. A typical example inthis case would be the setups and procedural actions required to ensure end-to-end operation in an inter-network setup, in particular in environments withheterogeneous networks. In a setup that includes a number of nodes (i.e., wire-less terminals, base stations, etc.) the social or collective aspect of cooperationis also of key importance. Cooperation here can be understood as the processof establishing and maintaining a network of collaborating nodes aiming to amutual benefit. The process of node engagement has a key role as the nodeneeds to decide on its participation on this ad hoc network. Unlike the previousapproaches, where typically cooperation is inherently embedded in the systemand hence invisible to the user, in this arrangement each user is in a key positionas he or she ultimately decides whether to cooperate or not. These decisions,on an individual or collective scale, are important and both have impact on net-work performance. Appealing incentives should be offered in order to inducethe users to cooperate.

Preface li

We were initially motivated to compile this book mostly by numerous tech-nical challenges, however, work in other fields had a profound influence in theway we approached cooperation. The simple but thoughtful quote ‘Real egoisticbehavior is to cooperate!’ by Kurt Edwin always inspired us with its unvarnishedtruth. We acknowledge the work by Robert Axelrod, which markedly influencedour views. In his work, among others, he identified a number of fundamentalanswers and behavioral rules from the question ‘How can cooperation emergein a world of egoists without central authority?’ The reader might be intriguedto know how this question is related to our wireless world. A paradigm shift istaking place in wireless and mobile communications, where two network accessconcepts (and their associated network architectures) are usually considered.In general, the centralized wireless access has been the dominant approach,typically exemplified by cellular communications. However, distributed (i.e.,decentralized) access concepts are rapidly gaining ground, making communi-cation links between terminals possible, and eventually giving to the user thepower to decide whether his or her terminal can be part of a cooperative net-work. Indeed, in a cooperation-enabled wireless world, people will ultimatelydecide to switch their terminals to a cooperative mode or not. In a long-termperspective, where virtually everything will be connected and a truly wirelessknowledge society will emerge, one may wonder how the patterns of cooperationwill evolve in such a hyper-connected world, and what will be their technical,social and economic impact? With this book we hope not only to give technicalinsights on how cooperative techniques can improve performance in wirelesscommunication systems, but also we would like to motivate further explorationin a fertile multidisciplinary research ground.

What are the benefits of cooperation in the wireless world? As the chaptersof the book will discuss, cooperative techniques can be used to enhance manyfundamental performance figures of a wireless communication system, beingperhaps data throughput, quality of service, network coverage as well as spectraland power efficiency being the most relevant ones. In our view, every involvedparty will benefit from cooperation, namely manufacturers, operators, serviceproviders and ultimately and most importantly, users. While cooperation is theleitmotiv of this book, such collaborative interactions are explored from twodifferent angles. The first part of the book considers the underlying principles ofcooperative techniques in wireless communication systems, covering a numberof fundamental theoretical concepts. Applications of cooperation are discussedin the final part of the book, where practical examples at different layers arepresented. Some chapters deal with both principles and applications.

lii Preface

Cooperation, widely exploited by nature, has been present probably fromrather early origins of our time. Complex cooperative interactions take place atmany levels, in organisms, within or between groups, or in large communities,to name a few. We people take advantage of cooperation on a daily basis,on small and big scales, thoughtfully and unconsciously. We are starting toapply and even mimic cooperative principles in engineering, and we have alot to learn from around us. Other sciences have already extensively studiedcooperation, developing models and analysis tools. Some of these ideas arenow started to be investigated also in the context of wireless communications.We expect that the upcoming wireless and mobile communication systems willmake well use of cooperative techniques, though not necessarily on a large scalein their introductory phase. If we look into a more distant future, cooperativetechniques have the potential to be widely used in communications, eventuallybecoming one of the underlying principles to support communications. Ouropening quotation, some three thousand years old, contains enough insight andwisdom as to be applied today, not only to people as originally intended, butalso to future wireless communication systems.

Even though cooperation in wireless communications has not yet reachedits full maturity, its realm is already broad, spreading and growing in depthincessantly. However we felt that the information on cooperative techniques iswidely scattered over different, often not well connected, research areas. Thisbook is an attempt to put into one volume a comprehensive and technically richview of the wireless communications scene from a cooperation point of view.Considering the already vast and diverse existing research output, we thoughtthat the most reasonable way to proceed is to invite leading researchers in thefield to share their expertise in this book. Thus, this book owes its existence tothe cooperative efforts of many people from all over the globe.

The editors welcome any suggestions, comments or constructive criticismon this book. Such a feedback would be used to improve forthcoming editions.Editors can be contacted at editors@cowinet.com and additional material canbe found at http://cowinet.kom.aau.dk.

Frank H.P Fitzek, Aalborg, DenmarkMarcos D. Katz, Suwon, Korea

December, 2005