Cooperative Communications for Improved Wireless Network Transmission:Framework for Virtual Antenna Array Applications

Murat UysalUniversity of Waterloo, Canada

Hershey • New YorkInformatIon scIence reference

Preface ..............................................................................................................................................xviii

Acknowledgment .............................................................................................................................xxiii

Section 1Information Theoretical Results on Cooperative Communications

Chapter 1Information Theoretical Limits on Cooperative Communications ......................................................... 1 Melda Yuksel, TOBB University of Economics and Technology, Turkey Elza Erkip, Polytechnic Institute of New York University, USA

Chapter 2 Overview of Amplify-and-Forward Relaying ....................................................................................... 29 Ioannis Krikidis, University of Edinburgh, UK John S. Thompson, University of Edinburgh, UK

Chapter 3Power Allocation for Cooperative Communications ............................................................................ 62 Onur Kaya, Işık University, Turkey Sennur Ulukus, University of Maryland, USA

Chapter 4Capacity Limits of Base Station Cooperation in Cellular Networks .................................................. 102 Symeon Chatzinotas, University of Surrey, UK Muhammad Ali Imran, University of Surrey, UK Reza Hoshyar, University of Surrey, UK

Table of Contents

Section 2Practical Coding Schemes for Cooperative Communications

Chapter 5Source and Channel Coding Techniques for Cooperative Communications ...................................... 135 John M. Shea, University of Florida, USA Tan F. Wong, University of Florida, USA Chan Wong Wong, University of Florida, USA Byonghyok Choi, University of Florida, USA

Chapter 6Network Coding for Multi-Hop Wireless Networks ........................................................................... 187 Meng Yu, Lehigh University, USA Jing (Tiffany) Li, Lehigh University, USA Haidong Wang, Thales Communications Inc., USA

Section 3Distributed Transmit and Receive Diversity Techniques for Cooperative Communications

Chapter 7Cross-Layer Cooperative Beamforming for Wireless Networks ........................................................ 207 Lun Dong, Drexel University, USA Athina P. Petropulu, Drexel University, USA H. Vincent Poor, Princeton University, USA

Chapter 8Distributed Space-Time Block Coding for Amplify-and-Forward Cooperative Networks ................ 238 Zhihang Yi, Queen’s University, Canada Il-Min Kim, Queen’s University, Canada

Chapter 9Relay Selection in Cooperative Networks .......................................................................................... 260 Elzbieta Beres, University of Toronto, Canada Raviraj Adve, University of Toronto, Canada

Chapter 10Energy Efficient Communication with Random Node Cooperation .................................................. 280 Zhong Zhou, University of Connecticut, USA Jun-Hong Cui, University of Connecticut, USA Shengli Zhou, University of Connecticut, USA Shuguang Cui, Texas A&M University, USA

Chapter 11Diversity Combining for Cooperative Communications .................................................................... 301 Diomidis S. Michalopoulos, Aristotle University of Thessaloniki, Greece George K. Karagiannidis, Aristotle University of Thessaloniki, Greece

Chapter 12Single and Double-Differential Coding in Cooperative Communications ......................................... 321 Manav R. Bhatnagar, University of Oslo, Norway Are Hjørungnes, University of Oslo, Norway

Chapter 13Space-Time Coding For Non-Coherent Cooperative Communications ............................................. 352 J. Harshan, Indian Institute of Science, India G. Susinder Rajan, Indian Institute of Science, India B. Sundar Rajan, Indian Institute of Science, India

Section 4Broadband Cooperative Communications

Chapter 14Resource Allocation for a Cooperative Broadband MIMO-OFDM System ...................................... 382 Ibrahim Y. Abualhaol, Broadcom Corporation, USA Mustafa M. Matalgah, University of Mississippi, USA

Chapter 15Single-Carrier Frequency Domain Equalization for Broadband Cooperative Communications ........ 399 Tae-Won Yune, POSTECH, Republic of Korea Dae-Young Seol, POSTECH, Republic of Korea Dongsik Kim, POSTECH, Republic of Korea Gi-Hong Im, POSTECH, Republic of Korea

Section 5Mathematical Tools for the Analysis and Design of Cooperative Networks

Chapter 16Applications of Majorization Theory in Space-Time Cooperative Communications ........................ 429 Aydin Sezgin, Stanford University, USA Eduard A. Jorswieck, TU Dresden, Germany

Chapter 17Data Gathering in Correlated Wireless Sensor Networks with Cooperative Transmission ................ 471 Laxminarayana S. Pillutla, The University of British Columbia, Canada Vikram Krishnamurthy, The University of British Columbia, Canada

Chapter 18Cooperative Broadcast in Large-Scale Wireless Networks ................................................................ 497 Birsen Sirkeci-Mergen, San Jose State University, USA Anna Scaglione, University of California at Davis, USA Michael Gastpar, University of California at Berkeley, USA

Section 6An Industrial Perspective on Cooperative Communications

Chapter 19Cooperative Communication System Architectures for Cellular Networks ....................................... 522 Mischa Dohler, CTTC, Spain Djamal-Eddine Meddour, Orange Labs, France Sidi-Mohammed Senouci, Orange Labs, France Hassnaa Moustafa, Orange Labs, France

Compilation of References ............................................................................................................... 548

About the Contributors .................................................................................................................... 584

Index ................................................................................................................................................... 598

Preface ..............................................................................................................................................xviii

Acknowledgment .............................................................................................................................xxiii

Section 1Information Theoretical Results on Cooperative Communications

Chapter 1Information Theoretical Limits on Cooperative Communications ......................................................... 1 Melda Yuksel, TOBB University of Economics and Technology, Turkey Elza Erkip, Polytechnic Institute of New York University, USA

This chapter provides an overview of the information theoretic foundations of cooperative communica-tions. Earlier information theoretic achievements, as well as the more recent developments, are discussed. The analysis accounts for full/half-duplex nodes and for multiple relays. Various channel models such as discrete memory less, additive white Gaussian noise (AWGN) ,and fading channels are considered. Co-operative communication protocols are investigated using capacity, diversity, and diversity-multiplexing tradeoff (DMT) as performance metrics. Overall, this chapter provides a comprehensive view on the foundations of and the state-of-the-art reached in the theory of cooperative communications.

Chapter 2 Overview of Amplify-and-Forward Relaying ....................................................................................... 29 Ioannis Krikidis, University of Edinburgh, UK John S. Thompson, University of Edinburgh, UK

Amplify-and-Forward (AF) is a simple cooperative strategy for ad-hoc networks with critical power constraints. It involves an amplification of the received signal in the analogue domain at the relays without further signal processing. This chapter gives an overview of the basic AF protocols in the literature and discusses recent research contributions in this area. Based on some well-defined AF-based cooperative configurations, it focuses on the behaviour of AF in block-fading channels, in power allocation problems, in relay selection and in cross-layer coordination. Mathematical models and outage probability simula-tions are used in order to show the enhancements of the presented AF techniques.

Detailed Table of Contents

Chapter 3Power Allocation for Cooperative Communications ............................................................................ 62 Onur Kaya, Işık University, Turkey Sennur Ulukus, University of Maryland, USA

In this chapter, we review the optimal power allocation policies for fading channels, in single user and multiple access scenarios. We present some background on cooperative communications, starting with the relay channel, and moving onto mutually cooperative systems. Then, we consider power control and user cooperation jointly, and for a fading Gaussian multiple access channel (MAC) with user cooperation, we present a channel adaptive encoding policy which relies on block Markov superposition coding. We obtain the power allocation policies that maximize the average rates achievable by this policy, subject to average power constraints. The optimal policies result in a coding scheme that is simpler than the one for a general multiple access channel with generalized feedback. This simpler coding scheme also leads to the possibility of formulating an otherwise non-concave optimization problem as a concave one. Using the perfect channel state information (CSI) available at the transmitters to adapt the pow-ers, we demonstrate gains over the achievable rates for existing cooperative systems. We consider both backwards and window decoding, and show that, window decoding, which incurs less decoding delay, achieves the same sum rate as backwards decoding, when the powers are optimized.

Chapter 4Capacity Limits of Base Station Cooperation in Cellular Networks .................................................. 102 Symeon Chatzinotas, University of Surrey, UK Muhammad Ali Imran, University of Surrey, UK Reza Hoshyar, University of Surrey, UK

In the information-theoretic literature, it has been widely shown that multicell processing is able to provide high capacity gains in the context of cellular systems. What is more, it has been proved that the per-cell sum-rate capacity of multicell processing systems grows linearly with the number of base station (BS) receive antennas. However, the majority of results in this area has been produced assuming that the fading coefficients of the MIMO subchannels are completely uncorrelated. In this direction, this chapter investigates the ergodic per-cell sum-rate capacity of the Gaussian MIMO Cellular Channel under cor-related fading and BS cooperation (multicell processing). More specifically, the current channel model considers Rayleigh fading, uniformly distributed user terminals (UTs) over a planar cellular system and power-law path loss. Furthermore, both BSs and UTs are equipped with correlated multiple antennas, which are modelled according to the Kronecker product correlation model. The per-cell sum-rate capac-ity is evaluated while varying the cell density of the system, as well as the level of receive and transmit correlation. In this context, it is shown that the capacity performance is compromised by correlation at the BS-side, whereas correlation at the UT-side has a negligible effect on the system’s capacity.

Section 2Practical Coding Schemes for Cooperative Communications

Chapter 5Source and Channel Coding Techniques for Cooperative Communications ...................................... 135 John M. Shea, University of Florida, USA Tan F. Wong, University of Florida, USA Chan Wong Wong, University of Florida, USA Byonghyok Choi, University of Florida, USA

This chapter provides a survey of practical cooperative coding schemes currently available in the literature, with focus on those schemes that achieve performance close to capacity or the best known achievable rates. To provide an insight into the construction of practical coding schemes for various cooperative communication scenarios, we first summarize the main design principles and tools that are used. We then present a survey of cooperative communication scenarios, and the progress on practical coding schemes for each of these scenarios is discussed in detail. Throughout the chapter, we demonstrate how the common design principles and tools are exploited to construct the existing practical coding schemes. We hope that the integrated view presented in this chapter can lead to further advances in this area.

Chapter 6Network Coding for Multi-Hop Wireless Networks ........................................................................... 187 Meng Yu, Lehigh University, USA Jing (Tiffany) Li, Lehigh University, USA Haidong Wang, Thales Communications Inc., USA

We consider practical network coding, a useful generalization of routing, in multi-hop multicast wire-less networks. The model of interest comprises a set of nodes transmitting data wirelessly to a set of destinations across an arbitrary, unreliable, and possibly time-varying network. This model is general and subsumes peer-to-peer, ad-hoc, sensory and mobile networks. It is first shown that, in the single-hop case, the idea of adaptively matching code-on-graph with network-on-graph, first developed in the adaptive-network-coded-cooperation (ANCC) protocol, provides a significant improvement over the conventional strategies. To generalize the idea to the multi-hop context, we propose to transform an arbitrarily connected network to a possibly time-varying “trellis network,” such that routing design for the network becomes equivalent to path discovery in the trellis. Then, exploiting the distributed, real-time graph-matching technique in each stage of the trellis, a general network coding framework is developed. Depending on whether or not the intermediate relays choose to decode network codes, three practical network coding categories, progress network coding, concatenated network coding and hybrid network coding, are investigated. Analysis shows that the proposed framework can be as dissemination-efficient as those with random codes, but only more practical.

Section 3Distributed Transmit and Receive Diversity Techniques for Cooperative Communications

Chapter 7Cross-Layer Cooperative Beamforming for Wireless Networks ........................................................ 207 Lun Dong, Drexel University, USA Athina P. Petropulu, Drexel University, USA H. Vincent Poor, Princeton University, USA

Cooperative beamforming (CB) is a signal transmission technique that enables long-range communica-tions in an energy efficient manner. CB relies on cooperation from a set of distributed network nodes, each carrying a single transmit antenna and acting as elements of a virtual antenna array. By appropriately weighting their transmissions, the cooperating nodes form one or more beams to cooperatively transmit one or more message signals to the desired destinations. In this chapter, a cross-layer framework is pre-sented that brings the CB ideas closer to implementation in a wireless network setting. The process of sharing among the network nodes the information to be beamed is studied and evaluated in terms of its effect on the spectral efficiency of the overall system. Optimal or suboptimal beamforming weights are designed, and queuing analysis is provided to study delay characteristics of source messages.

Chapter 8Distributed Space-Time Block Coding for Amplify-and-Forward Cooperative Networks ................ 238 Zhihang Yi, Queen’s University, Canada Il-Min Kim, Queen’s University, Canada

This chapter focuses on distributed space-time codes (DSTCs) in cooperative networks. DSTCs can sub-stantially improve the bandwidth efficiency of the cooperative network without requiring any feedback overheads from the destination to the relays. The first part of this chapter is dedicated to reviewing the existing works on DSTCs. In the second part of this chapter, distributed orthogonal space-time block codes (DOSTBCs) are presented in detail. It is shown that the DOSTBCs can achieve the single-symbol maximum likelihood decodability and full diversity order in an amplify-and-forward cooperative network. Then some special DOSTBCs, which generate uncorrelated noises at the destination, are introduced. Those codes are referred to as the row-monomial DOSTBCs. An upper bound of the data-rate of the row-monomial DOSTBC is derived and the codes achieving the upper bound are presented as well.

Chapter 9Relay Selection in Cooperative Networks .......................................................................................... 260 Elzbieta Beres, University of Toronto, Canada Raviraj Adve, University of Toronto, Canada

Cooperative diversity has the potential of implementing spatial diversity and mitigating the adverse ef-fects of channel fading without requiring multiple antennas at transmitters and receivers. Traditionally, cooperative diversity is implemented using maximal ratio combining (MRC), where all available nodes

relay signals between the source and destination. It has recently been proposed, however, that for each source-destination transmission, only a single best node should be selected to act as a relay. The result-ing scheme, referred to as selection cooperation or opportunistic relaying, outperforms MRC schemes and can be implemented in a distributed fashion with limited feedback. This result is not unexpected, as selection requires some (though very limited) information regarding instantaneous channel conditions, while MRC does not. When implemented in a distributed network, however, MRC does require feedback for the synchronization of nodes, rendering a comparison of the two schemes worthwhile and fair. In this chapter, we provide a detailed overview of selection. We begin with a single source-destination pair, and discuss its implementation and performance under various constraints and scenarios. We then discuss a less-common scenario, a multi-source network where nodes act both as sources and as relays.

Chapter 10Energy Efficient Communication with Random Node Cooperation .................................................. 280 Zhong Zhou, University of Connecticut, USA Jun-Hong Cui, University of Connecticut, USA Shengli Zhou, University of Connecticut, USA Shuguang Cui, Texas A&M University, USA

In this chapter, we focus on the energy efficient cooperative communication with random node cooperation for wireless networks. By “random,” we mean that the cooperative nodes for each communication event are randomly selected based on the network and channel conditions. Different from the conventional deterministic cooperative communication where cooperative nodes are determined prior to the com-munication, here the number of cooperative nodes and the cooperation pattern may be random, which is more practical given the random nature of the channels among the source nodes, relay nodes, and destination nodes. In addition, it is more robust to the dynamic wireless network environment. Starting with a thorough literature survey, we then discuss the challenges for random cooperative communica-tion systems. Afterwards, two examples are presented to illustrate the design methodologies. In the first example, we analyze a simple scheme for clustered wireless networks, where cooperative communication is deployed in the long-haul inter-cluster transmissions to improve the energy efficiency. We quantify the energy performance and emphasize its difference from the conventional deterministic ones. In the second example, we consider the cross-layer design between the physical layer and the medium access control (MAC) layer for the one-hop random single-relay networks. We unify the power control and the relay selection at the physical layer into the MAC signalling in a distributed fashion. This example clearly shows the strength of cross-layer design for energy-efficient cooperative systems with random node collaboration. Finally, we conclude with discussions over possible future research directions.

Chapter 11Diversity Combining for Cooperative Communications .................................................................... 301 Diomidis S. Michalopoulos, Aristotle University of Thessaloniki, Greece George K. Karagiannidis, Aristotle University of Thessaloniki, Greece

A major advantage of cooperative communications is the potential for forming distributed antenna ar-rays, that is, arrays whose elements are not co-located but carried by independent relaying terminals.

This allows for a study and design of cooperative communications under a novel perspective, where the inherent end-to-end paths between the source and destination terminal constitute the multiple branches of a virtual, distributed diversity receiver. As a result, the well-known combining methods used in conventional diversity receivers can be implemented in a distributed fashion, resulting in novel relay-ing protocols and generally in new ways for exploiting the resources available in cooperative relaying setups. This chapter provides an overview of this distributed diversity concept, as well as a performance analysis of the corresponding distributed diversity schemes, with particular emphasis on the analysis of distributed switch-and-stay combining. Further insights regarding the potential of implementing the distributed diversity concept in practical applications are obtained.

Chapter 12Single and Double-Differential Coding in Cooperative Communications ......................................... 321 Manav R. Bhatnagar, University of Oslo, Norway Are Hjørungnes, University of Oslo, Norway

In this chapter, we discuss single and double-differential coding for two-user cooperative communica-tion system. The single-differential coding is important for the cooperative systems as the data at the destination/relaying node can be decoded without knowing the channel gains. The double-differential modulation is useful as it avoids the need of estimating the channel and carrier offsets for the decod-ing of the data. We explain single-differential coding for a cooperative system with one relay utilizing orthogonal transmissions with respect to the source. Next, we explain two single-differential relaying strategies; active user strategy (AUS) and passive users relaying strategy (PURS), which could be used by the base-station to transmit data of two users over downlink channels in the two-user cooperative communication network with decode-and-forward protocol. The AUS and PURS follow an improved time schedule in order to increase the data rate. A probability of error based approach is also discussed, which can be used to reduce the erroneous relaying of data by the regenerative relay. In addition, we also discuss how to implement double-differential (DD) modulation for decode-and-forward and amplify-and-forward based cooperative communication system with single source-destination pair and a single relay. The DD based systems work very well in the presence of random carrier offsets without any channel and carrier offset knowledge at the receivers, where the single differential cooperative scheme breaks down. It is further shown that optimized power distributions can be used to improve the performance of the DD system.

Chapter 13Space-Time Coding For Non-Coherent Cooperative Communications ............................................. 352 J. Harshan, Indian Institute of Science, India G. Susinder Rajan, Indian Institute of Science, India B. Sundar Rajan, Indian Institute of Science, India

Cooperative communication in a wireless network can be based on the relay channel model where a set of users act as relays to assist a source terminal in transmitting information to a destination terminal. Recently, the idea of space-time coding (STC) has been applied to wireless networks wherein the relay

nodes cooperate to process the received signal from the source and forward them to the destination such that the signal received at the destination appears like a space-time block code (STBC). Such STBCs (referred as distributed space time block codes [DSTBCs]) when appropriately designed are known to offer spatial diversity. It is known that separate classes of DSTBCs can be designed based on the destina-tion‘s knowledge of various fading channels in the network. DSTBCs designed for the scenario when the destination has either the knowledge of only a proper subset of the channels or no knowledge of any of the channels are called non-coherent DSTBCs. This chapter addresses the problems and results associated with the design, code construction, and performance analysis (in terms of pairwise error probability [PEP]) of various non-coherent DSTBCs.

Section 4Broadband Cooperative Communications

Chapter 14Resource Allocation for a Cooperative Broadband MIMO-OFDM System ...................................... 382 Ibrahim Y. Abualhaol, Broadcom Corporation, USA Mustafa M. Matalgah, University of Mississippi, USA

In this chapter, a cooperative broadband relay-based resource allocation technique is proposed for adap-tive bit and power loading multiple-input-multiple-output/orthogonal frequency division multiplexing (MIMO-OFDM) system. In this technique, sub-channels allocation, M-QAM modulation order, and power distribution among different sub-channels in the relay-based MIMO-OFDM system are jointly optimized according to the channel state information (CSI) of the relay and the direct link. The transmit-ted stream of bits is divided into two parts according to a suggested cooperative protocol that is based on sub-channel-division. In this protocol, the first part is sent directly from the source to the destination, and the second part is relayed to the destination through an indirect link. Such a cooperative relay-based system enables us to exploit the inherent system diversities in frequency, space and time to maximize the system power efficiency. The BER performance using this cooperative sub-channel-division proto-col with adaptive sub-channel assignment and adaptive bit/power loading are presented and compared with a non-cooperative ones. The use of cooperation in a broadband relay-based MIMO-OFDM system showed high performance improvement in terms of BER.

Chapter 15Single-Carrier Frequency Domain Equalization for Broadband Cooperative Communications ........ 399 Tae-Won Yune, POSTECH, Republic of Korea Dae-Young Seol, POSTECH, Republic of Korea Dongsik Kim, POSTECH, Republic of Korea Gi-Hong Im, POSTECH, Republic of Korea

Cooperative diversity is an effective technique to combat the fading phenomena in wireless communica-tions without additional complexity of multiple antennas. Multiple terminals in the network form a virtual antenna array in a distributed fashion. Even though each of them is equipped with only one antenna,

spatial diversity gain can be achieved through cooperation. In this chapter, we discuss relay-assisted single carrier transmissions extending conventional transmit diversity schemes. We focus on distributed space-frequency block coded single carrier transmission, in order to operate over fast fading channels. A pilot design technique is also discussed for channel estimation of this single carrier cooperative system, which shows better channel tracking performance than conventional block-type channel estimations. In addition, spectral efficient cooperative diversity protocols are presented, where the users access a relay simultaneously or transmit superposed data blocks. Interference from the other user is effectively removed by using an iterative detection technique.

Section 5Mathematical Tools for the Analysis and Design of Cooperative Networks

Chapter 16Applications of Majorization Theory in Space-Time Cooperative Communications ........................ 429 Aydin Sezgin, Stanford University, USA Eduard A. Jorswieck, TU Dresden, Germany

This chapter discusses important aspects in cooperative communications such as power allocation and node distributions using majorization theory, spanning both theoretical foundations and practical is-sues. Majorization theory provides a large amount of tools and techniques which can be used in order to accelerate the pace of developments in this fascinating research area of cooperative communications. The aim of the chapter is to build good intuition and insight into this important field of cooperative communications and how majorization theory can be used in order to solve quite complex problems in a very efficient and elegant way. Although we focus on some specific applications, the tools can be also applied to other setups and processing techniques.

Chapter 17Data Gathering in Correlated Wireless Sensor Networks with Cooperative Transmission ................ 471 Laxminarayana S. Pillutla, The University of British Columbia, Canada Vikram Krishnamurthy, The University of British Columbia, Canada

This chapter considers the problem of data gathering in correlated wireless sensor networks with dis-tributed source coding (DSC), and virtual multiple input and multiple output (MIMO) based coopera-tive transmission. Using the concepts of super and sub modularity on a lattice, we analytically quantify as how the optimal constellation size, and optimal number of cooperating nodes, vary with respect to the correlation coefficient. In particular, we show that the optimal constellation size is an increasing function of the correlation coefficient. For the virtual MIMO transmission case, the optimal number of cooperating nodes is a decreasing function of the correlation coefficient. We also prove that in a virtual MIMO based transmission scheme, the optimal constellation size adopted by each cooperating node is a decreasing function of number of cooperating nodes. Also, it is shown that the optimal number of cooperating nodes is a decreasing function of the constellation size adopted by each cooperating node.

We also study numerically that for short distance ranges, SISO transmission achieves better energy-mutual information (MI) tradeoff. However, for medium and large distance ranges, the virtual MIMO transmission achieves better energy-MI tradeoff.

Chapter 18Cooperative Broadcast in Large-Scale Wireless Networks ................................................................ 497 Birsen Sirkeci-Mergen, San Jose State University, USA Anna Scaglione, University of California at Davis, USA Michael Gastpar, University of California at Berkeley, USA

This chapter studies the cooperative broadcasting in wireless networks. We especially focus on multistage cooperative broadcasting in which the message from a source node is relayed by multiple groups of cooperating nodes. Interestingly, group transmissions become beneficial in the case of broadcasting as opposed to the case in traditional networks where receptions from different transmitters are considered as collision and disregarded. Different aspects of multistage cooperative broadcasting are analyzed in the chapter: (i) coverage behavior; (ii) power efficiency; (ii) error propagation; (iv) maximum communication rate. Whenever possible, performance is compared with multi-hop broadcasting where transmissions are relayed by a single node at each hop. We consider a large-scale network with many nodes distributed randomly in a given area. In order to analyze such networks, an important methodology, the continuum limit, is introduced. In the continuum limit, random networks are approximated by their dense limits under sum relay power constraint. This method allows us to obtain analytical results for the analysis of cooperative multistage broadcasting.

Section 6An Industrial Perspective on Cooperative Communications

Chapter 19Cooperative Communication System Architectures for Cellular Networks ....................................... 522 Mischa Dohler, CTTC, Spain Djamal-Eddine Meddour, Orange Labs, France Sidi-Mohammed Senouci, Orange Labs, France Hassnaa Moustafa, Orange Labs, France

An ever-growing demand for higher data-rates has facilitated the growth of wireless networks in the past decades. These networks, however, are known to exhibit capacity and coverage problems, hence jeopardizing the promised quality of service towards the end-user. To overcome these problems, prohibi-tive investment costs in terms of base station or access point rollouts would be required if traditional non-scalable cell-splitting and micro-cell capacity dimension procedures were applied. The prime aim of current R&D initiatives is hence to develop innovative network solutions that decrease the cost per bit/s/Hz over the wireless link. To this end, cooperative networks have emerged as an efficient and promising

solution. We discuss in this chapter some key research and deployment issues, with emphasis on coopera-tive architectures, networking and security solutions. We expose some motivations to use such networks, as well as latest state-of-the-art developments, open research challenges and business models.

Compilation of References ............................................................................................................... 548

About the Contributors .................................................................................................................... 584

Index ................................................................................................................................................... 598