Resource Allocation and MIMOfor 4G and Beyond

Francisco Rodrigo Porto CavalcantiEditor

Resource Allocationand MIMO for 4Gand Beyond

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EditorFrancisco Rodrigo Porto CavalcantiFederal University of CearáFortaleza, CearáBrazil

ISBN 978-1-4614-8056-3 ISBN 978-1-4614-8057-0 (eBook)DOI 10.1007/978-1-4614-8057-0Springer New York Heidelberg Dordrecht London

Library of Congress Control Number: 2013951132

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To Renesa, Eduarda and Marcele

Foreword

Access to Internet and Internet-based services are today fundamental componentsof society with large impact on business and life. Exploiting the opportunities andbenefits of the Internet is no longer a luxury restricted to a few as a rapidlyincreasing part of the world’s population is getting connected. The large impact ithas had on many peoples’ private and professional lives has also changed how werelate to the Internet. To many, Internet and Internet access is seen as a necessity, acommodity, in many aspects not different from how we see upon electricity orwater. Enabled by advances in cellular network and handsets technologies duringthe last decade, the way to access Internet has changed. From something you did infront of a computer it has been integrated with the daily life on the move; it hasgone mobile.

The foundation for the present massive uptake in mobile Internet usage isresearch conducted in industry and academia during the 1990s and the first decadeof 2000. These activities resulted in definition and subsequent evolution of anumber of radio interface standards fulfilling the ITU IMT-2000 requirements,often referred to as the 3G standards. A major milestone in the 3G evolution,fundamental for mobile Internet access, was reached by the introduction of HSPAas an extension to the WCDMA standard. By this extension, the circuit switchedparadigm of WCDMA was changed in favor of packet switching, allowing con-siderably improved spectrum efficiency and support for IP-based traffic. Driven byexpected needs of future services but also advancements in technologies for mobilesystems, the evolution of technologies beyond 3G started around 2000 and is stillongoing. Research in industry and academia again led to the definition and evo-lution of a new family of standards, the 4G standards, this time targeting fulfill-ment of the ITU IMT-Advanced specifications.

The existing 4G standards, with LTE as the dominating example, targetsessentially three improvement areas as compared to 3G: data rates, latency, andcapacity. With data rates an order of magnitude larger than 3G, latency in therange of 10 ms, and spectral efficiency of up to 30 bps/Hz, LTE and its evolutionLTE-Advanced targets to provide true mobile broadband experience to the endusers similar to what is possible with wired access. This is a clearly challengingtask that, despite the fact that standardization is ongoing in parallel, still offersmany interesting and important research problems to be addressed.

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The Wireless Telecommunications Research Group (GTEL) at the FederalUniversity of Ceará was founded in June 2000 by Prof. Francisco Rodrigo PortoCavalcanti and his colleagues with the mission to develop wireless communicationtechnology and impact the development of the Brazilian telecom sector. Withsupport from Ericsson Research, Prof. Francisco Rodrigo Porto Cavalcanti hassince the start built up an independent research organization with an impressingspan in competence and abilities, covering and mastering the entire range ofwireless link and system research aspects, from signal processing algorithms andradio link design to cellular systems design and system analysis.

In this book, the second from the group, Prof. Francisco Rodrigo Porto Cavalcantiand his colleagues share their insights and views on a number of highly relevantresearch topics related to 4G and 4G technology developments. Results from recentresearch activities within the group are presented. In particular, findings and resultsrelating to research on radio resource management (RRM), relaying, scheduling, andDevice-to-Device (D2D) communication are presented. Contributions and findingsrelated to coordinated multipoint transmission (CoMP), MIMO precoding, andinterference alignment (IA) are also comprehensively covered.

The content of this book aims at design and optimization of current andemerging cellular systems. Researchers and engineers active or interested in thefield will find the content useful and are encouraged to share the insights andresults.

Sweden, July 2013 Dr. Göran Klang

viii Foreword

Preface

Introduction

Mobile and wireless communication systems are a prominent communicationstechnology of the twenty-first century with profound economic and social impactsin practically all parts of the world. The current state of wireless communicationsystems allows for a much wider scope of applications than what it used to beoriginally, that is, to be a mobile extension of the public switched telephonenetwork. The convergence of mobile systems and the Internet has become a realityas new radio access technologies emerged with improved coverage, capacity, andlatency. While the need and desire to develop and establish a truly mobile Internetdates back to the mid-1990s, it is only recently that mobile broadband has taken offto become a prominent part of the whole mobile communications business.

This book is about some of the latest developments in wireless access tech-nology, and underlying breakthroughs, that are part of or can be applied to Fourthgeneration mobile communication systems onwards, in order to keep up with theincreasing demand for mobile data.

The specific focus of the book is on the two lower layers of the ISO/OSI layeredmodel, that is, the physical and data link layers, in particular the media accesscontrol sublayer of the latter. A common thread throughout the book is cross-layeroptimization between these layers. These two layers are of specific importance inwireless systems, as opposed to many of its wired counterparts. This is funda-mentally due to spectrum shortage, limited signal coverage, the broadcast nature ofinterference, and time variability of the wireless channel response. As a conse-quence, much of the improvements in coverage, capacity, and latency of modernwireless systems are due to new approaches for tackling old problems in highcapacity radio communications in these two lower layers.

Intended Audience and Usage

This book is intended for researchers in the field of wireless communications,more specifically to those involved with the design and optimization of current andemerging wireless access technologies for mobile communications. Graduate

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students working on subjects such as radio resource allocation (RRA) and man-agement (RRM), interference management, Orthogonal Frequency DivisionMultiple Access (OFDMA) and Multiple-Input-Multiple-Output (MIMO) systems,as applied to fourth generation systems and beyond, will benefit from the state-of-the-art concepts, methods, examples, and case studies presented. Every chapter, inaddition to having a clear ambition to address the state of the art of the corre-sponding subject, discusses basic concepts in the introductory sections and givesreferences for the interested reader to deepen his/her understanding. All chapterscan be used independently as a complement to a graduate-level ‘‘Advanced’’Wireless Communications course, where each separate chapter can be used asbasis to a supervised study or a seminar.

The book should also be of interest to the practitioner or to engineers involvedin standardization efforts. The attention to technical details from standards is givenin several chapters when performance results and case studies are presented asresulting from the application of selected techniques. The idea in many instances isto demonstrate how advanced concepts can be adapted to be applicable in morerealistic scenarios.

Finally, almost every chapter of the book sheds light, direct or indirectly, on thesubject of performance evaluation of wireless systems by means of analyticalapproaches and of system and link-level simulations. As the complexity of wire-less systems grows, efficient and correct methods for modeling and analyzingperformance of these systems is becoming a fundamental discipline on its own.

Organization of the Book

This book brings a total of 11 chapters and, for the sake of clarity of presentation,these chapters are organized into two parts. The parts are named ‘‘ResourceAllocation’’ and ‘‘MIMO’’ after the book’s title and as the focus is on two layeredmodel mentioned above. Such type of division is becoming increasingly artificialas cross-layer optimizations are commonplace and multiple antennas at networknodes can be seen as ‘‘resources’’ to be managed. Therefore, some of the chapterscould well be placed in both parts.

Part I: Resource Allocation

Radio Resource Allocation (RRA) has its roots in frequency reuse planning of Firstgeneration cellular systems. Its fundamental goal is to increase spectrum efficiency.

More efficient utilization of the radio spectrum plays such an important rolebecause spectrum is simultaneously a very scarce and widely shared resource.

In the evolution towards 3G systems, RRA became a discipline on its own,encompassing a variety of techniques such as power control, frequency hopping,

x Preface

dynamic channel allocation, and being integrated into more advanced multi-antenna concepts, such as beamforming and MIMO solutions.

The explosion of mobile broadband and the demand for high data-rate packetswitched services has required a new set of RRA techniques able to handlecapacity challenging scenarios. These new RRA approaches started off by bor-rowing concepts from wired data networks, such as packet scheduling and con-gestion control, but that were reformulated and adapted to the wirelessenvironment.

More recently, with the emergence of 4G, noticeably in the form of 3GPP’sLong Term Evolution (LTE) standards, a highly configurable radio access tech-nology based on OFDMA has been made available. This has, again, widened thescope of RRA. By means of advanced optimization approaches, RRA is nowpossible with fine granularity, increasing the efficiency-potential of spectrum usageto unprecedented levels. This is mainly due to a clever exploitation of the mul-tidimensional (spatial, frequency, time, and multiuser) diversity by RRA algo-rithms. To mention one example of such, MIMO techniques, once restricted to thesingle-user case, are now considered an inherent part of RRA at a network level.

Advances in computing power and energy efficiency at mobile devices are alsoan important enabler for the actual implementation of sophisticated RRA algo-rithms. Nevertheless, computational complexity is still an issue that should beconsidered when evaluating the applicability of RRA proposed solutions. Anotheraspect that deserves attention is the demand for channel state information andcontrol signaling at multiple network nodes (e.g., mobile devices and base sta-tions). Since the dimensionality of RRA problems has grown in OFDMA-basedsystems such as LTE, one must verify if the algorithm’s demand for such infor-mation are realistic in order not to overburden the system’s backhaul. These andother practical issues are treated in most of the chapters in this book when RRAapproaches are presented.

Chapter 1 revisits many of the issues concerning RRM with a focus on theupcoming systems embodying the Coordinated Multipoint (CoMP) technology.CoMP-based systems have attracted special attention due to their potential benefitsin terms of spectral efficiency and coverage. As a part of 3GPP Long TermEvolution—Advanced, CoMP technology promises substantial improvement ofthe users’ experience at the expense of requiring a reliable and efficient connectionamong the evolved Node Bs (eNBs). Provided that multiple users and eNBs arecoordinated using a suitable technique, the concerns about interference can begreatly alleviated and, consequently, also the restrictions on sharing radioresources. In this chapter, the authors explore the grouping of users and eNBs intwo different occasions. First they address coordinated strategies of grouping andscheduling users in order to improve the system performance; afterwards, clus-tering of eNBs is described as an attractive approach to deal with the processingand signaling overheads brought by CoMP. The chapter presents an analysis ofdifferent algorithms, as well as case studies illustrating some key concepts throughcomputer simulations.

Preface xi

Chapter 2 starts by recognizing that cellular networks have experienced a strongdevelopment in the past decades and now face an important challenge that is asteep increase of mobile traffic expected for the next years. In this context, cellularoperators have as objective to increase the number of satisfied users in the systemand consequently their revenues, whereas users or subscribers aim at having ful-filled their expected Quality of Service (QoS). In order to increase the number ofsatisfied users in the system the authors identify the RRA as a key functionality.RRA is responsible for managing and distributing the available scarce resources ofthe radio interface to the active connections. In this chapter the authors presentRRA strategies to increase the number of satisfied users in cellular networks basedon two approaches: heuristic and utility-based strategies. While the heuristicdesign provides simple and quick solutions to the RRA problems, the utility-basedapproach is a flexible and general tool for RRA design.

Authors in Chap. 3 recognize that the increasing demand for rich multimediaservices and the scarcity of electromagnetic spectrum has motivated the researchof technologies able to increase the capacity of wireless systems without requiringadditional spectrum. In this context, Device-to-Device (D2D) communicationrepresents a promising technology. By enabling direct and low-power communi-cation among devices, D2D communication leads to an increased and intelligentspatial reuse of radio resources allowing offloading the network of data transport.As a result, the overall system’s capacity and specially the spectral efficiency isincreased; and the proximity between devices allows data transfer with low delaysand high rates without requiring extra power from devices’ batteries. Other ben-efits of D2D communication especially while underlying a cellular networkencompasses the reuse gain and hop gain, which are further detailed in thischapter. However, in order to realize the potential gains of D2D communicationsas a secondary network of the cellular (primary) one, some key issues must becontrolled. First, at each transmission request for a D2D-capable device, it isnecessary to determine the neighbors, i.e., other D2D-capable devices that are inthe vicinity of the latter and therefore may establish a D2D communication. Then,once neighbors are discovered and the target device is in the neighbors’ poll, theactual link (channel) conditions must be evaluated. If beneficial, RRA techniquesare employed so that the co-channel interference caused in cellular devices ismitigated. Such techniques may be summarized as: band selection, grouping,mode selection, and power control. In this chapter, the authors focus attention onthe RRA for D2D communications underlying an LTE-like network, and the mainRRA techniques to mitigate the co-channel interference so generated. Namely, it isshown the basis for grouping, mode selection, and power control techniques, andpresented results that highlight their benefits.

Authors in Chap. 4 propose that wireless mobile network optimization is acomplex task that consists in achieving different design objectives such as spectralefficiency, energy efficiency, fairness, and QoS. Then, RRA is responsible formanaging the available resources in the radio access interface and, therefore, is animportant tool for optimizing networks and achieving the designed objectivesmentioned previously. However, in general all these network design objectives

xii Preface

cannot be achieved at the same time by RRA strategies. In fact, different RRAstrategies can be designed to maximize one objective in detriment of the other aswell as to balance the objectives. In this chapter the authors deal with importanttrade-offs between contradicting objectives in modern wireless mobile networks:capacity versus fairness and capacity versus QoS. The authors then present RRAstrategies that can achieve static and adaptive performances when the previouslymentioned trade-offs are considered. In order to design these RRA strategies, theauthors consider heuristics and utility-based solutions.

Chapter 5 is focused on designing efficient, low-complexity cooperativediversity schemes from different perspectives and it is divided into four parts. Inthe first part, assuming a general multi-source, multi-relay cooperative system, anew efficient scheme for the combined use of cooperative diversity and multiuserdiversity is proposed. The proposed scheme significantly reduces the amount ofnecessary channel estimation while achieving comparable outage performance tothat using the joint selection scheme. In the second part, two spectrally efficientschemes for the diversity exploitation of downlink cooperative cellular networksare proposed. By scheduling the user with the best direct link to access thechannel, an incremental decode-and-forward relaying scheme is first presented. Tofurther enhance the transmission robustness against fading, an improved scheme isalso proposed, which substantially utilizes opportunistic scheduling mechanismwhen the direct transmission fails. In the third part, new and efficient link selectionschemes for selection relaying systems with transmit beamforming are proposed.Two distributed link selection schemes are presented that invoke a distributeddecision mechanism and rely on the success/fail signaling feedback between ter-minals. In the fourth part, a novel distributed transmit antenna selection for dual-hop amplify-and-forward relaying systems is proposed. A multi-antenna sourcetransmits information to a single-antenna destination by using a single-antennahalf-duplex relay. By invoking local channel information exploitation/decisionmechanism along with decision feedback between terminals, a distributed antennaselection scheme is formulated. Compared with the optimal/suboptimal antennaselection, the proposed scheme can maintain a low and constant delay/feedbackoverhead irrespective of the number of transmit antennas.

In Chap. 6 authors address distributed parameter coordination methods forwireless communication systems. The authors present two distributed algorithmsfor the problem of precoder selection. The first and simplest method is the greedysolution in which each communication node in the network acts selfishly. Thesecond method and the focus of this chapter is based on a message-passingalgorithm, namely minsum algorithm, in factor graphs. Three kinds of precodingcodebooks are considered: transmit antenna selection, fixed-beam selection, andLTE precoder selection. Evaluations on the potential of such an approach in awireless communication network are provided and its performance and conver-gence properties are compared with those of a baseline selfish/greedy approach.Simulation results are presented and discussed, which show that the graph-basedtechnique generally obtains gain in sum rate over the greedy approach at the costof a larger message size. For instance, the percentage gain in sum rate over the

Preface xiii

greedy is about 33 % within 5 iterations in a 7-cell network considering single-layer LTE precoders. Besides, the graph-based method usually reaches the globaloptima in an efficient manner. Methods of improving the rate of convergence ofgraph-based distributed coordination technique and reducing its associated mes-sage size are therefore important topics for wireless communication networks.

Part II: MIMO Systems

The significant improvements at the physical layer have been instrumental for theincrease of the wireless link capacity over the last decade. OFDM itself, already apopular modulation mechanism in fixed digital subscriber lines, has been com-bined with the use of multiple antennas at both ends of wireless links, in so-calledMultiple-Input-Multiple-Output (MIMO) schemes. MIMO has changed the waywireless engineers face the fundamental capacity limits of the wireless channel byexploiting fading variability in favor of it. This fact also illustrates the majorchallenge—how can a wireless system be designed that allows for a practicalimplementation in the presence of such potentially fast fading propagation chan-nels between and among the multitude of employed antennas? The main aspects totake into consideration is how to make such a system design both observable andcontrollable—the former, important in order to generate the appropriate amount ofradio network measurements and the associated signaling and the latter, is sig-nificant in the sense of keeping the interference levels under control on a systemlevel.

MIMO has been originally proposed as a single-user point-to-point techniquefor increasing spectral efficiency by means of a clever exploitation of multipathscattering. However, a related and somewhat parallel approach known as SDMA(Spatial Division Multiple Access) already pointed out the possibility of using thespace domain for organizing multiple users sharing a given spectrum. The evo-lution of MIMO toward multi-user settings can be seen, in retrospect, relativelystraightforward. Enablers for this widened MIMO scope include better charac-terization of the spatial domain of wireless channels and the increased computa-tional processing capabilities of both base stations and mobile terminals.

Following the same path but maybe not so obvious is the evolution of MIMO tothe network level, where virtual antenna arrays can be formed by the cooperationof multiple single or multi-antenna nodes (base stations, terminals, and relays).Another recent technique that originated in such a multi-user multi-antenna con-text is the Interference Alignment (IA) approach, in which different transmitter-receiver pairs cooperate in order to align the interference within the same subspaceat each receiver. Although IA is not restricted to the spatial domain, it has foundapplication in different MIMO scenarios, such as the MIMO interference channelpresent in multi-antenna wireless cellular networks.

This evolution of MIMO has renewed the interest on problems such as transmitand receive algorithms for signal coding, multiplexing, and parameter estimation

xiv Preface

and corresponding computational complexities; spectrum reuse versus interferencecontrol; and backhaul capacity for inter-exchange of channel state information,among others.

Chapters in the second part present MIMO research from several standpoints,from optimizing the placement of antennas within small terminals to transceiverarchitectures to several precoding approaches.

Chapter 7 is focused in propagation and antenna aspects of MIMO systems.While the understanding and modeling of MIMO propagation channels have alreadyreached a rather mature level, there are still many aspects to understand when itcomes to including antenna design and more realistic modeling aspects in MIMOapplications. This is in particular the case on the user equipment side, mainly due tothe fundamental restrictions originating from the size of handheld or portable suchdevices. This is the focus of this chapter where authors devise an automated opti-mization method based on a genetic algorithm for the optimal placement of antennaswithin a limited volume and considering such aspects as the spatial directionalchannel models and antenna coupling. The objective is to maximize ergodiccapacity while considering antenna polarization and pattern diversities. Antennaselection aspects are also considered during the optimization process.

In Chap. 8 authors present tensor-based approaches for MIMO-OFDM systemscombining space-frequency and time domain processing allowing iterative jointblind channel estimation and symbol decoding. First, they consider the case ofmulti-layered space-frequency codes (MLSFC) with an extended linear precodingtechnique (LCP). Then, a space-time-frequency signaling technique that combinesspace-frequency modulation with a time-varying linear precoding is developed.They show that both systems satisfy PARAllel FACtor (PARAFAC)-based mod-els, which allow a blind joint channel and symbol estimation using iterative orclosed-form receiver algorithms. For this system, they propose two closed-formsemi-blind receivers that exploit differently the multilinear structure of thereceived signal, which is formulated as a nested PARAFAC model. For the firstsystem, alternating least squares (ALS) and least squares Khatri-Rao factorizationbased (LS-KRF) receivers are proposed and compared. For the later system, andaiming at reducing pilot overhead, they develop a simplified closed-formPARAFAC (S-CFP) receiver coupled with a pairing algorithm that yields anunambiguous estimation of the transmitted symbols without the need of a pilotframe. Simulation results are shown to evaluate the performance of the proposedtransceivers in terms of bit-error-rate and channel estimation accuracy.

Chapter 9 is focused again on the CoMP technique which is expected toincrease cell-average and cell-edge throughputs in 4G and beyond wireless sys-tems. Joint processing (JP) is a branch of CoMP systems which can enhance thesystems’ performance, mainly by employing precoding algorithms based onchannel state information at the transmitter (CSIT). Many research efforts focus onreducing feedback and optimizing precoding with partial CSIT. In this chapter, theprecoder design for multi-user (MU) MIMO CoMP systems is discussed. First,some initial concepts are presented, such as the MIMO channel and some classicalprecoding techniques found in literature. Following, the availability of partial

Preface xv

channel knowledge at the transmitter is studied in order to design the precoder.Since the wireless channel is random and time-varying, it is difficult and oftenexpensive to obtain perfect CSIT. Thus, considering partial CSIT is valuable forpractical applications. In this context, two algorithms maximizing the first- andsecond-order approximations of the ergodic sum rate of an MU-MIMO CoMPsystem are presented. These algorithms consider, as partial CSIT, the channelmean and the spatial correlation among the antennas and show the potential ofusing statistical measurements of the channel for precoder design, instead of usingfull CSIT. The proposed algorithms are computationally simple, highly reducefeedback overheads, and have fast convergence. Simulation results show that theproposed algorithms are near-optimal compared to the iterative water-filling(optimal full CSIT) case and present only moderate and negligible sum rate lossesfor low and high SNR values, respectively.

In Chap. 10 authors describe several aspects of the interference alignment (IA)technique with a focus on the spatial domain. The basic idea of IA consists inprecoding the transmitted signals such that they are aligned at the receiver wherethey constitute interference, while at the same time disjointed from the desiredsignal. This alignment limits the generated interference to a subspace at eachreceiver which in turn leaves the remaining dimensions free from any interference.The number of dimensions free from interference corresponds to the number ofDegrees of Freedom (DoF), or the multiplexing gain of the system. Most of theliterature on IA considers an idealized scenario with perfect Channel StateInformation (CSI) available at the transmitter. The authors describe some well-known IA algorithms from the literature, also with simulation results for thisidealized scenario. After that they provide some insights into the impact ofimperfections, where CSI error and transmit antenna correlation are included intothe channel model. Furthermore, it is analyzed extensions to IA to also obtaindiversity gains, in which IA is jointly employed with antenna selection and userselection. In both cases subspace-related metrics are used for the selection: thechordal distance and the Fubini-Study distance. After that IA is analyzed with asystem level view, where it is also provided some insights into complexity issues.Finally, some conclusions and research directions are provided.

In Chap. 11 authors observe that increasing capacity shortfall and coverage issuesare aggravated by inefficient fixed spectrum management policies and obsoletenetwork structures. Then, the development of new technologies and spectrummanagement policies is seen as a necessary step to take, in order to cope with theseissues. A significant research effort has been made since the beginning of the cen-tury, to investigate the advantages brought by the introduction of flexible manage-ment paradigms and new hierarchical approaches to network planning. The resultingtiered network layout may improve the capacity of current networks in several ways.In this chapter, the authors focus on the challenging problem arising when the twotiers share the transmit band, to capitalize on the available spectrum and avoidingpossible inefficiencies. In this case, the coexistence of the two tiers is not feasible,if suitable interference management techniques are not designed to mitigate/cancelthe mutual interference generated by the active transmitters in the network.

xvi Preface

The authors show that by intelligently designing the transmit waveform by means ofa special precoder, the two-tier coexistence problem is solved for several differentnetwork configurations. Such configurations range from single to multi-user, thelatter being also possible for centralized and distributed cases.

Final Words

I hope this book can be useful for students and practitioners working in theevolution of wireless communication systems toward a truly ubiquitous andaffordable mobile broadband service.

Fortaleza, Brazil, July 2013 Francisco Rodrigo Porto Cavalcanti

Preface xvii

Acknowledgments

Most of the contents of this book are a collection of research resulting from acollaboration between the Wireless Telecommunications Research Group (GTEL)at the Federal University of Ceará (UFC), Brazil; the Ericsson Innovation Center,in Brazil; and Ericsson Research, in Sweden.

I am in deep gratitude to the whole GTEL team—students, researchers, pro-fessors, administrative, and support personnel: this book is a tangible outcome ofyour everyday dedication and professionalism at the laboratory. A particular thankyou is passed to the professors and project leaders at GTEL who have shared withme many decisions and helped overcome technical and managerial challenges overthe years: Professors André L. F. de Almeida, Charles C. Cavalcante, João C. Mota,Tarcisio F. Maciel, Walter C. Freitas Jr. and Yuri C. B. Silva. Senior researchers atGTEL are thanked for their focus on project objectives and dedication to work onthese projects: M.Sc. Darlan C. Moreira, Dr. Elvis M. G. Stancanelli, Dr. EmanuelB. Rodrigues, M.Sc. Igor M. Guerreiro, Dr. Lígia M. C. Sousa, Dr. FranciscoR. M. Lima and M.Sc. Rodrigo L. Batista. On the administrative side, Mrs. AnaL. Carvalho personalizes the effort to make the bureaucracy and working envi-ronment as smooth as possible so that we can concentrate on the technical matters.

I am also particularly thankful to Eduardo Oliva, Maria Marquezini, andAndrea Barros from Ericsson in Brazil, who have managed the strategic, formal,and legal aspects of the research projects over the years with GTEL, as well as tothe management at Ericsson in Brazil for entrusting our Group with over 13 yearsof continuous partnership and financial support.

All chapter authors are thanked for having accepted my invitation and forhaving worked hard to provide sound technical material in time to compose thisbook. A particular expression of gratitude is sent to authors from abroad and fromcollaborating institutions of GTEL.

At Ericsson Research in Sweden a sincere thanks for the support, trust, andcollaboration from Göran Klang, Sven-Olof Jonsson, Mikael Hook, Ian Fargh,Gabor Fodor, Dennis Hui, Robert Baldemair, Mats Nordberg, Arne Simonsson,Erik Wang, Fredrick Lindqvist, Sara Sandberg, Yngve Selén, Stefän Wänstedt,Jiann-Ching Guey, Icaro da Silva, Jonas Medbo, and Henrik Asplund.

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Last, but by no means least, thank you my family—Renesa, Eduarda, andMarcele—for your understanding and support now and ever.

Francisco Rodrigo Porto Cavalcanti

xx Acknowledgments

Contents

Part I Resource Allocation

1 Radio Resource Management for CoordinatedMultipoint Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3Elvis M. G. Stancanelli, Rodrigo L. Batista, Tarcisio F. Macieland Yuri C. B. Silva

2 Resource Allocation for Improved User Satisfactionwith Applications to LTE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Francisco R. M. Lima, Emanuel B. Rodrigues, Tarcisio F. Macieland Mats Nordberg

3 Radio Resource Management for Device-to-DeviceCommunications in Long Term Evolution Networks . . . . . . . . . . 105Carlos F. M. Silva, José Mairton B. Silva Jr. and Tarcisio F. Maciel

4 Capacity, Fairness, and QoS Trade-Offs in Wireless Networkswith Applications to LTE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157Emanuel B. Rodrigues, Francisco R. M. Lima, Ferran Casadevalland Francisco Rodrigo Porto Cavalcanti

5 The Design of Efficient, Low-Complexity CooperativeDiversity Schemes from Different Perspectives. . . . . . . . . . . . . . . 213Daniel B. da Costa, Haiyang Ding, Jianhua Ge and Wenjing Yang

6 Distributed Optimization Techniques in WirelessCommunication Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271Igor M. Guerreiro, Charles C. Cavalcante and Dennis Hui

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Part II MIMO

7 A Genetic Algorithm for the Optimization of MIMOAntenna Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313Manuel O. Binelo, André L. F. de Almeidaand Francisco Rodrigo Porto Cavalcanti

8 Multiantenna Multicarrier Transceiver Architectures . . . . . . . . . 359Walter C. Freitas, André L. F. de Almeida,João Paulo C. L. da Costa, Kefei Liu and Hing Cheung

9 Precoder Design for Coordinated Multipoint Systems . . . . . . . . . 397Lígia M. C. Sousa, Tarcisio F. Maciel and Charles C. Cavalcante

10 Interference Alignment, Concepts and Algorithmsfor Wireless Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439Darlan C. Moreira, Paulo G. Normando, Carlos I. R. Bandeira,Walter C. Freitas and Yuri C. B. Silva

11 Null-Space Precoder for Dense 4G and Beyond Networks . . . . . . 475Leonardo S. Cardoso, Marco Maso and Mérouane Debbah

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523

xxii Contents

Contributors

Carlos I. R. Bandeira received the Bachelor’s degree and the Master of Sciencedegree in Teleinformatics Engineering from the Federal University of Ceará(UFC), Brazil, in 2009 and 2012, respectively. Nowadays, he is a Ph.D. student atthe Teleinformatics Engineering Department and a Member of the Research Groupin Wireless Telecommunications (GTEL). His research interests include Inter-ference Alignment, Resource Scheduling and Link Adaptation.

Rodrigo L. Batista received the B.Sc. degree in Computer Engineering fromFederal University of Espírito Santo, Brazil, in 2008, and the M.Sc. degree inTeleinformatics Engineering from the Federal University of Ceará, Brazil, in 2011.Since 2009, he is working as a Research Engineer with the Wireless Telecom-munications Research Group (GTEL), Brazil, in projects within technical coop-eration with the Ericsson Research. In 2012, he was a visiting researcher atEricsson Research, Sweden, where he investigated the application of dynamicclustering techniques into CoMP (Coordinated Multipoint) systems. He hasexpertise on wireless networks simulation and related topics such as connectionadmission control and radio resource allocation for cooperative communications.Currently, his main interests focus the radio resource allocation for Device-to-Device communications.

Manuel O. Binelo received the B.Sc. degree in Computing Science from theUniversity of Cruz Alta, (UNICRUZ), Cruz Alta, Brazil, in 2004 and the M.Sc.degree in Mathematical Modeling from the Regional University of Northwest ofRio Grande do Sul State (UNIJUI), Ijuí, Brazil, in 2007. In 2013 he received thePh.D. degree in Teleinformatics Engineering from the Federal University of Ceará,Fortaleza, Brazil. He is currently a Professor at the Mathematic Modeling Grad-uation Program at UNIJUI.

Leonardo S. Cardoso received his B.Sc. in Electrical Engineering and M.Sc. inTelecommunications Engineering from Federal University of Ceará, Fortaleza,Brazil, in 2003 and 2006, respectively. He received his Ph.D. degree in 2011 fromSupélec, France. From 2001 to 2006, he worked in several projects for EricssonResearch at the Wireless Telecom Research Group (GTEL), Brazil. In 2006, hejoined the Eurécom Institute, France, working in projects on heterogeneous net-works and real-time MIMO channel performance assessment, contributing to the

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EMOS MIMO platform. He is currently a postdoc at Inria/INSA at Lyon, France,working on a testbed for physical layer centric large-scale cognitive radio net-works. His current research interests include interference cancellation, dynamicspectrum access, heterogeneous networks, and femto/small-cells.

Ferran Casadevall received his Engineer of Telecommunication and Dr. Eng.degrees from UPC, Spain, in 1977 and 1983 respectively. In 1978 he joined UPC,where he was an Associate Professor from 1983 to 1991. He is currently a fullprofessor in the Signal Theory and Communications Department. After graduationhe was concerned with equalization techniques for digital fiber optic systems. Hehas also been working in the field of digital communications with particularemphasis on digital radio and its performance under multipath propagation con-ditions. In the last 15 years, he has mainly been concerned with the performanceanalysis and development of digital mobile radio systems. In particular hisresearch interest include cellular and personal communication system, multipathtransceiver design (including software radio techniques), mobility and radioresources management, and end-to-end QoS issues. During the last 10 years he hasparticipated in more than 30 research-projects funded by both public and privateorganizations. In particular, he actively participated in 10 research projects fundedby the European Commission, being Project Manager of three of them: ARROWS,EVEREST, and AROMA (see http://www.gcr.tsc.upc.edu for details). He haspublished around 100 technical papers in both international conferences andmagazines, most of them IEEE publications. He has also been a Technical Pro-gram Committee Member of different international IEEE supported conferences aswell as a reviewer of several IEEE magazines. From October 1992 to January 1996he was responsible for the Information Technology Area in the National Agencyfor Evaluation and Forecasting (Spanish National Research Council).

Charles C. Cavalcante received the B.Sc and M.Sc in Electrical Engineeringfrom the Federal University of Ceará (UFC), Brazil, in 1999 and 2001, respec-tively, and the Ph.D. degree from the University of Campinas (UNICAMP), Brazil,in 2004. He has held a grant for Scientific and Technological Development from2004 to 2007 and since March 2009 he has a grant of Scientific Research Pro-ductivity both from the Brazilian Research Council (CNPq). From March 2007 toNovember 2008 he was a visiting Professor at Teleinformatics EngineeringDepartment of UFC and since November 2008 he is an Adjunct Professor at thesame department and university holding the Statistical Signal Processing chair. Hehas been working on signal processing strategies for communications where he hasseveral papers published in journal and conferences, has authored two internationalpatents, and has worked on several funded research projects on the signal pro-cessing and wireless communications areas. He is also a co-author of the bookUnsupervised Signal Processing: Channel Equalization and Source Separation,published by CRC Press. He is a researcher of the Wireless TelecommunicationsResearch Group (GTEL) where he leads research on signal processing and wire-less communications. Dr. Cavalcante is a Senior Member of the IEEE and member

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of the Brazilian Telecommunications Society (SBrT). His main research interestsare in signal processing for communications, blind source separation, wirelesscommunications, information geometry, and statistical signal processing.

Francisco Rodrigo Porto Cavalcanti received the B.Sc. and M.Sc. degrees inElectrical Engineering from Federal University of Ceará, Fortaleza, Brazil, in 1994and 1996, respectively, and the D.Sc. degree in Electrical Engineering from theState University of Campinas, São Paulo, Brazil, in 1999. Upon graduation, hejoined the Federal University of Ceará, where he is currently an Associate Pro-fessor and holds the Wireless Communications Chair with the Department ofTeleinformatics Engineering. In 2000, he founded and since then has directed theWireless Telecom Research Group (GTEL), which is a research laboratory basedon Fortaleza, which focuses on the advancement of wireless telecommunicationstechnologies. At GTEL, he has managed, for over a decade, a program of researchprojects in wireless communications sponsored by the Ericsson Innovation Centerin Brazil and Ericsson Research in Sweden. Professor Cavalcanti has produced avaried body of work including one book, conference and journal papers, inter-national patents, and computer software dealing with subjects such as radioresource allocation, cross-layer algorithms, service quality provisioning, trans-ceiver architectures, MIMO communications, signal processing, and projectmanagement. In 2009, Prof. Cavalcanti edited Optimizing Wireless Communica-tion Systems, published by Springer, dealing with foundations and advances inwireless technologies from 2G to 4G. Professor Cavalcanti is a distinguishedresearcher of the Brazilian Scientific and Technological Development Council forhis technology development and innovation record. He also holds a Leadershipand Management professional certificate from the Massachusetts Institute ofTechnology, Cambridge.

Hing Cheung was born in Hong Kong. He received the B.Eng. degree from theCity University of Hong Kong and the Ph.D. degree from The Chinese Universityof Hong Kong, both in Electronic Engineering, in 1990 and 1995, respectively.From 1990 to 1991, he was an Electronic Engineer with the Research andDevelopment Division, Everex Systems Engineering Ltd., Hong Kong. During1995–1996, he worked as a Postdoctoral Fellow with The Chinese University ofHong Kong. From 1996 to 1999, he was a Research Assistant Professor with theDepartment of Electronic Engineering, City University of Hong Kong, where he iscurrently an Associate Professor. His research interests include statistical signalprocessing, fast and adaptive algorithms, signal detection, parameter estimation,and source localization. Dr. So has been on the editorial boards of the IEEETransactions on Signal Processing, Signal Processing, Digital Signal Processing,and ISRN Applied Mathematics, as well as a member of the Signal ProcessingTheory and Methods Technical Committee of the IEEE Signal Processing Society.

João Paulo C. L. Costa was born in Fortaleza, Brazil, on May 22, 1981. Hereceived the Diploma degree in Electronic Engineering in 2003 from the MilitaryInstitute of Engineering (IME) in Rio de Janeiro, Brazil, his M.Sc. degree in

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Telecommunications in 2006 from University of Brasília (UnB) in Brazil, and hisDoktor-Ingenieur Ph.D. degree with Magna cum Laude in Electrical Engineeringand information technology in 2010 at Ilmenau University of Technology (TUIlmenau) in Germany. Currently, he is a Professor at the Department of ElectricalEngineering, University of Brasília (UnB), and he cooperates with the Laboratoryof Technologies for Decision Making (LATITUDE) supported by DELL com-puters of Brazil, with the Laboratory of Automation and Robotics (LARA), andwith the Microwave and Wireless Systems Laboratory (MWSL). He coordinatesthe Laboratory of Array Signal Processing (LASP) at UnB. His research interestsare in the areas of multi-dimensional array signal processing, model order selec-tion, principal component analysis, MIMO communications systems, multilinearalgebra, and parameter estimation schemes.

Daniel B. da Costa was born in Fortaleza, Ceará, Brazil, in 1981. He received theB.Sc. degree in Telecommunications from the Military Institute of Engineering,Rio de Janeiro, Brazil, in 2003 and the M.Sc. and Ph.D. degrees in Telecommu-nications from the University of Campinas, Campinas, Brazil, in 2006 and 2008,respectively. From 2008 to 2009, he was a Postdoctoral Research Fellow withINRS-EMT, University of Quebec, Montreal, QC, Canada. Since 2010, he hasbeen with the Federal University of Ceará, Brazil, where he is currently anAssistant Professor. He has authored or co-authored more than 50 papers in IEEE/IET journals and more than 40 papers in international conferences. His researchinterests lie in the area of wireless communications and include channel modelingand characterization, relaying/multihop/mesh networks, cooperative systems,cognitive radio networks, tensor modeling, physical layer security, and analysis/design of Multiple-Input-Multiple-Output systems. He is currently an AssociateEditor of the IEEE Communications Letters, the IEEE Transactions on VehicularTechnology, the EURASIP Journal on Wireless Communications and Networking,and the KSII Transactions on Internet and Information Systems. He is currentlyserving as the Lead Guest Editor for EURASIP Journal on Wireless Communi-cations and Networking in the Special Issue on ‘‘Cooperative Cognitive Net-works,’’ and as a Guest Editor for IET Communications in the Special Issue on‘‘Secure Communications with Physical Layer Security.’’ He has also served asAssociate Technical Editor for the IEEE Communications Magazine. He is also aProductivity Research Fellow of the CNPq, where he is currently coordinating aproject with partnership of researchers from Brazil and China. He is also therecipient of three conference paper awards: one at the 2009 IEEE InternationalSymposium on Computers and Communications, one at the 13th InternationalSymposium on Wireless Personal Multimedia Communications in 2010, andanother at the XXIX Brazilian Telecommunications Symposium in 2011.

André L. F. de Almeida received the B.Sc. and M.Sc. degrees in ElectricalEngineering from the Federal University of Ceará, Brazil, in 2001 and 2003,respectively, and the double Ph.D. degree in Sciences and TeleinformaticsEngineering from the University of Nice, Sophia Antipolis, France, and the Federal

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University of Ceará, Fortaleza, Brazil, in 2007. He is currently an AssistantProfessor with the Department of Teleinformatics Engineering of the FederalUniversity of Ceará. During fall 2002, he was a visiting researcher at EricssonResearch Labs, Stockholm, Sweden. From 2007 to 2008, he held a one-yearresearch position at the I3S Laboratory, CNRS, France. In 2008, he was awarded aCAPES/COFECUB research fellowship with the I3S Laboratory, CNRS, France. In2010, he was appointed a productivity research fellow from CNPq (the BrazilianNational Council for Scientific and Technological Development). In the spring2012, he was a visiting Professor at the University of Nice Sophia-Antipolis,France. Dr. Almeida is affiliated to the IEEE Signal Processing for Communicationsand Networking (SPCOM) Technical Committee. He serves as an Associate Editorof the IEEE Transactions on Signal Processing, Circuits Systems and Signal Pro-cessing, and KSII Transactions on Internet and Information Systems. He is a SeniorMember of the IEEE and an ad hoc consultant for Brazilian public funding agen-cies. His research interests lie in the broad area of signal processing for commu-nications, and include blind/semi-blind identification and equalization, arrayprocessing, tensor decompositions and multilinear algebra applied to MIMOcommunications and cooperative networks.

Mérouane Debbah entered the Ecole Normale Supérieure de Cachan (France) in1996 where he received his M.Sc. and Ph.D. degrees respectively. He worked forMotorola Labs (Saclay, France) from 1999–2002 and the Vienna Research Centerfor Telecommunications (Vienna, Austria) until 2003. He then joined the MobileCommunications Department of the Institut Eurecom (Sophia Antipolis, France)as an Assistant Professor until 2007. He is now a Full Professor at Supélec(Gif-sur-Yvette, France), holder of the Alcatel-Lucent Chair on Flexible Radio anda recipient of the ERC starting grant MORE (Advanced Mathematical Tools forComplex Network Engineering). His research interests are in information theory,signal processing, and wireless communications. He is a senior area editor forIEEE Transactions on Signal Processing. Mérouane Debbah is the recipient of the‘‘Mario Boella’’ award in 2005, the 2007 General Symposium IEEE GLOBECOMbest paper award, the Wi-Opt 2009 best paper award, the 2010 Newcom?? bestpaper award as well as the Valuetools 2007, Valuetools 2008, Valuetools 2012 andCrownCom2009 best student paper awards. He is a WWRF fellow. In 2011, hereceived the IEEE Glavieux Prize Award.

Haiyang Ding was born in Hebei, China, in 1980. He received his B.A. inCommunications Engineering from Xi’an Communications Institute, Xi’an, Chinain June 2003, and the M.Sc. degree (with honors) in Electrical Engineering fromBeijing University of Technology, China, in July 2006. Since the September of2008, he has been working toward his Ph.D. degree with the department of tele-communications engineering, Xi’an Communications Institute, under the super-vision of Prof. Jianhua Ge. His research interest lies in the area of channelmodeling, cooperative communications, and cognitive radio. In 2013, he receivedthe prestigious IEEE Communications Letters Exemplary Reviewer Certificate

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(less than 3 % of all the reviewers received this prestigious award). In 2012, hereceived the RIM Wireless Research Scholarship at Xidian University and thefirst-class paper award at the 2012 military degree and graduate training seminar.During the past three years, he has published more than 20 papers in peer-reviewedjournals and major conferences, which includes IEEE Trans. Wireless Commun.,IEEE Trans. Veh. Technol., IEEE Commun. Lett., IET Electron. Lett., SCIENTIASINICA Informationis, IEEE WCNC, etc. At present, he presides over one openresearch fund of the State Key Lab. of ISN. On November 28th of 2012, he wasinvited to make a keynote speech at the 2012 graduate annual seminar at XidianUniversity.

Walter C. Freitas Jr. received his Ph.D. degree in Teleinformatic Engineeringfrom Federal University of Ceará (UFC), Brazil in 2006 and his B.S. and M.S.degrees in Electrical Engineering from the same university. During his studies, hewas supported by the Brazilian agency FUNCAP and Ericsson. During 2005Walter Freitas Jr. was a senior research of Nokia Technology Institute, now he isProfessor at Federal University of Ceará-Brazil and researcher of Wireless Tele-com Research Group (GTEL). His main area of interest concerns features devel-opment to improve the performance of the wireless communication systems,application of link adaptation techniques, OFDMA resource allocation, MIMOsystems and space-time coding and Interference Avoidance Tools.

Jianhua Ge was born in Jiangsu Province, China, in 1961. He is currently aProfessor and Deputy Director of State Key Laboratory of Integrated ServicesNetworks (ISN) at the Department of Communication Engineering in XidianUniversity. He has worked at the DTV standardization as a DTV technical expert.His research interests include digital video broadcasting system, MIMO andmobile communication techniques.

Igor M. Guerreiro received the B.S. and the M.S. degrees in TeleinformaticsEngineering from the Federal University of Ceará (UFC), Brazil, in 2007 and2010, respectively. He is currently pursuing the Ph.D. degree in TeleinformaticsEngineering at UFC, Brazil. Since 2007 he has been a Research Engineer atWireless Telecommunications Research Group (GTEL), Brazil, working inresearch projects within a technical cooperation with Ericsson Research, Sweden.In 2008, he was a guest researcher at Advanced Research Institute (ARI) ofVirginia Tech, Arlington, Virginia, USA. In 2010, he was a guest researcher atEricsson Research in Luleå, Sweden, and in 2011, in San José, California, USA.Some topics of his research interests include techniques for Multiple-Input-Mul-tiple-Output (MIMO) transceiver design, strategies for distributed optimization forwireless communication, modeling and simulation of cellular communication, anddynamic spectrum access methodologies.

Dennis Hui received his Ph.D. degree from the University of Michigan at AnnArbor in 1998. Since then, he has joined the advanced development and researchgroup at Ericsson, currently located in San Jose, California. He worked on a

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number of different wireless communication systems in the past, including Blue-tooth, GSM/EDGE, and LTE. He is currently working on a future ‘‘5G’’ cellularsystem. His current research interests include distributed signal processing,interference coordination, radio resource management, and signal compression.

Francisco R. M. Lima received the B.Sc. degree with honors in ElectricalEngineering in 2005, and M.Sc. and Ph.D. degrees in TelecommunicationsEngineering from the Federal University of Ceará, Fortaleza, Brazil, in 2008 and2012, respectively. In 2008, he has been in an internship at Ericsson Research inLuleå, Sweden, where he studied scheduling algorithms for LTE system. Since2010, he has been a Professor of Computer Engineering Department of FederalUniversity of Ceará, Sobral, Brazil. Mr. Lima is also a researcher at the WirelessTelecom Research Group (GTEL), Fortaleza, Brazil where he works in projects incooperation with Ericsson Research and is author of many technical reports,conference papers, journal articles, and patents. His research interests includeRadio Resource Allocation algorithms for QoS guarantees in scenarios withmultiple services, resources, antennas, and users.

Kefei Liu is currently a Ph.D. candidate in the Department of ElectronicEngineering, City University of Hong Kong, Hong Kong. He received the B.Sc.degree in Applied Mathematics from Wuhan University in 2006 and M.Sc. degreein Mathematics from Beihang University in January 2009, both in China. FromFebruary 2012 to August 2012, he studied as a visiting Ph.D. student at theDepartment of Electrical Engineering, University of Brasilia, Brazil. His researchinterests are statistical and array signal processing, with primary focus on sourceenumeration, prewhitening, and parameter estimation.

Tarcisio F. Maciel received the B.Sc. and M.Sc. degrees in Electrical Engineeringfrom the Federal University of Ceará (UFC), Fortaleza, Brazil, in 2002 and 2004,respectively, and the Dr.-Ing. degree in electrical engineering from the TechnischeUniversität Darmstadt (TUD), Darmstadt, Germany, in 2008. From 2001 to 2004,he was a Researcher with the Wireless Telecom Research Group (GTEL) of theUFC. From 2005 to 2008, he was a Research Assistant with the CommunicationsEngineering Laboratory of the TUD. In 2009, he was a Professor of the computerengineering course with UFC. Since 2008, he has been a Senior Researcherwith GTEL and a member of the Post-Graduation Program in TeleinformaticsEnginnering (PPGETI) of the UFC. Since 2010, he has been a Professor with theCenter of Technology, UFC. His research interests include radio resource man-agement, numerical optimization, and multiuser/multiantenna communications.

Marco Maso received the bachelor’s degree in 2005 and the M.Sc. degree inTelecommunications Engineering in 2008, both from University of Padova, Italy.He received his Ph.D. degree in 2013 from University of Padova and Supélec. Heworked on projects dealing with practical implementations of OFDM packetsynchronization in 2005/06, and DVB-T2 system simulation in 2008/09. He iscurrently involved in the HENIAC project, studying new techniques for high speed

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coherent optical communications. His research interests include heterogeneousnetworks, wireless communications, cognitive radio, and embedded devices.

Darlan C. Moreira received the Bachelor’s degree in Electrical Engineering andthe Master of Science degree in Teleinformatics Engineering from the FederalUniversity of Ceará (UFC), Brazil, in 2005 and 2007, respectively. He is aMember of the Wireless Telecommunications Research Group (GTEL), Fortaleza,Brazil, and since 2004, he has been working in projects within the technicalcooperation between GTEL and Ericsson Research. In 2007 he was a visitingresearcher at Ericsson Research, Stockholm, Sweden, working on channel qualitymeasurement and reporting for 3GPP’s Long-Term-Evolution (LTE) wirelesssystem. His research interests include MIMO-OFDM systems, channel estimation,and interference alignment.

Mats Nordberg is a Manager at Ericsson Research, Luleå, Sweden, working onthe subject of Optimization of IP over Wireless, at the Wireless Access NetworksDepartment.

Paulo G. Normando received his B.S. degree in 2011 and he is currently con-cluding his master’s degree, both in Teleinformatics Engineering and at theFederal University of Ceará (UFC). From 2007 to 2010 he worked on signalprocessing and pattern recognition. Since 2011, he has been working at theWireless Telecom Research Group (GTEL/UFC), with a focus on the InterferenceAlignment topic. His research interests include interference mitigation techniquesin wireless networks, cooperative communications, and MIMO.

Emanuel B. Rodrigues received the B.Sc. and M.Sc. degrees in ElectricalEngineering from the Federal University of Ceará (UFC), Fortaleza, Brazil, in2001 and 2004, respectively. He also received the Ph.D. Degree with honors insignal theory and communications from the Universitat Politècnica de Catalunya(UPC), Barcelona, Spain, in 2011. He has been working in the Wireless TelecomResearch Group (GTEL) since 2001 and has actively participated in several pro-jects in a technical and scientific cooperation between GTEL and EricssonResearch. Within this cooperation, he has been in an internship at EricssonResearch at Linköping, Sweden, in 2004, where he studied admission controlalgorithms for HSDPA systems. During the last 12 years, he has published severalconference papers, journal/magazine articles and book chapters, and has been areviewer of important international conferences and IEEE journals and magazines.His main research interests are radio resource management and QoS control formacrocell and femtocell networks.

Carlos F. M. Silva received a five-year degree diploma and M.Sc degree inElectronics and Telecommunications Engineering from University of Aveiro(UA), Aveiro, Portugal, in 2005 and 2010, respectively. Since February 2011 he isworking toward his Ph.D. degree in Teleinformatics Engineering, first in the sameuniversity and since June 2012 in the Federal University of Ceará (UFC), Fort-aleza, Brazil. Since February 2006, Carlos Silva has participated as a researcher in

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several European projects, such as WINNER, FUTON, and more recently inCOGEU, where he was involved with cognitive radio systems for efficient use andsharing of TVWS in European context. Currently, Carlos Silva is a researcher atWireless Telecommunications Research Group (GTEL), Fortaleza, Brazil, wherehe works in cooperation projects with Ericsson Research. At present, his mainresearch interests include spectrum usage optimization, scarcity and management,namely related with TVWS sharing and Device-to-Device (D2D) communications.

José Mairton B. Silva Jr. received the B.Sc. degree with honors in Teleinfor-matics Engineering from the Federal University of Ceará (UFC), Fortaleza, Brazil,in 2012. During his studies, he was supported by the Brazilian agency CNPq.Currently he is pursuing his M.Sc. degree in Teleinformatics Engineering from thesame university. Since 2012 he has been with the Wireless TelecommunicationsResearch Group (GTEL) where he is a researcher working on Device-to-Device(D2D) communications, power control, mode selection, resource allocation andcooperative communications. His research interests include radio resource man-agement, numerical optimization, and D2D communications.

Yuri C. B. Silva received the B.Sc. and M.Sc. degrees from the Federal Universityof Ceará, Fortaleza, Brazil, in 2002 and 2004, respectively, and the Ph.D. degreefrom the Technische Universität Darmstadt, Germany, in 2008, all in ElectricalEngineering. In 1999 he attended the Technische Universität Berlin, Germany, aspart of a one-year sandwich graduation program. From 2001 to 2004 he was withthe Wireless Telecom Research Group (GTEL), Fortaleza, Brazil, working for thetechnical cooperation between GTEL and Ericsson Research. In 2003 he was avisiting researcher at Ericsson Research, Stockholm, Sweden, where he developedadvanced radio resource management solutions for the GSM/EDGE standard. From2005 to 2008 he was with the Communications Engineering Lab of the TechnischeUniversität Darmstadt and since 2010 he is a Professor at the Federal University ofCeará. His main research interests are in the areas of wireless communicationssystems, multi-antenna processing, interference alignment, multicast services, andcooperative communications.

Lígia M. C. Sousa received the B.Sc. degree in Electrical Engineering from theFederal University of Ceará (UFC), Fortaleza, Brazil, in 2004; the M.Sc. degree inElectrical Engineering from the State University of Campinas (UNICAMP),Campinas, Brazil, in 2006. During this period she participated in the scientificinitiation programs PIBIC-UFC and CAPES, respectively. In 2011, she receivedthe Ph.D. degree in Teleinformatics Engineering from the Federal University ofCeará (UFC), Brazil. In 2010, she took a position as Adjunct Professor at theComputer Engineering Course of the UFC in Sobral, Brazil. She has been workingon signal processing strategies for communications where she has some paperspublished in conferences and has authored one international patent. Since 2007 sheis part of the Wireless Telecommunication Research Group (GTEL) as SeniorResearch Engineer in Fortaleza, Brazil. Her research interests include multi-user

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and multi-antenna communications, signal processing for interference mitigation,and limited-feedback techniques.

Elvis M. G. Stancanelli received the B.S. and the M.S. degrees in ElectricalEngineering from, respectively, the State University of Londrina, Brazil, in 2002,and the Polytechnic School of the University of São Paulo, Brazil, in 2004, and thePh.D. degree in Teleinformatics Engineering from the Federal University of Ceará,Brazil, in 2012. Since 2004 he is working as a Research Engineer with theWireless Telecommunications Research Group (GTEL), Brazil, in projects withinthe technical cooperation with the Ericsson Research. In 2009 he was a visitingresearcher at Ericsson Research, Sweden, where he investigated advanced solu-tions for link-to-system interface. His main research interests include techniquesfor radio resource management, strategies for cooperative communication andinterference alignment, modeling and simulation of cellular communication net-works, and applied machine learning.

Wenjing Yang received the M.S. degree and Ph.D. degree in Computer Scienceand Ttechnology from Xi’an Jiaotong University, in 2005 and 2011, respectively.She attends the Chinese 863 Project ‘‘Research in heterogeneous mobile ad hocnetworks.’’ Her main research interests lie in the areas of wireless communicationand mobile ad hoc networks.

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Acronyms

2G Second Generation3G Third Generation4G Fourth Generation3GPP Third Generation partnership projectADSL Asymmetric digital subscriber lineAF Amplify-and-forwardALS Alternating least squaresAMC Adaptive modulation and codingAM Altruistic minimizationAPA Adaptive power allocationASL Active set limitAS Antenna selectionATEF Adaptive throughput-based efficiency-fairness trade-offATES Adaptive throughput-based efficiency-satisfaction trade-offAWGN Additive white Gaussian noiseBB Branch and boundBD Block diagonalizationBER Bit error rateBF Best fitBLER Block error rateBPSK Binary phase-shift keyingBS Base stationCAP CapacityCAPEX Capital expenditureCbAA Clustering-based assignment algorithmCDF Cumulative distribution functionCDMA Code division multiple accessCFI Cell fairness indexCFP Closed-form PARAFACCFT Cell fairness targetCIC Cognitive interference channelCoMP Coordinated multi-pointCONFAC Constrained factorCPU Central processing unit

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CP Cyclic prefixCQI Channel quality indicatorCR Cognitive radioCRM Constrained rate maximizationCS Coordinated schedulingCSI Channel state informationCSIT Channel state information at the transmitterD2D Device-to-DeviceDAS Distributed antenna selectionDF Decode-and-forwardDFT Discrete fourier transformDL DownlinkDMT Diversity-multiplexing tradeoffDOA Direction of arrivalDOD Direction of departureDOF Degrees of freedomDPC Dirty-paper codingDRA Dynamic resource assignmentDSA Dynamic spectrum accessDSM Delay-based satisfaction maximizationDT Direct transmissioneNB Evolved node BEPA Equal power allocationFDD Frequency division duplexFER Frame erasure rateFFT Fast fourier transformFJP Full joint processingFSRM Fairness-based sum rate maximizationFTP File transfer protocolGA Genetic algorithmGRASS Game-theoretic antenna subset selectionGSM Global system for mobile communicationsH-S/MIMO Hybrid selection/MIMOHDR High data rateHOL Head of lineHOSVD Higher order SVDi.i.d. Independent and identically distributedIA Interference alignmentIBI Inter-block interferenceIC Interference channelICI Inter-cell interferenceICIC Inter-cell interference coordinationIDF Incremental DFIEEE Institute of electrical and electronics engineersIID Independent and identically distributed

xxxiv Acronyms

IIDF Improved incremental DFILP Integer linear problemIML Iterative maximum likelihoodIMT International mobile telecommunicationsIRBD Iterative regularized block diagonalizationISI Inter symbol interferenceJP Joint processingKKT Karush-Kuhn-TuckerLCP Linear precoding techniqueLDPC Low-density parity checkLHS Left-hand sideLOS Line-of-sightLS Least squaresLS-KRF Least squares Khatri-Rao factorizationLTE Long-term evolutionLTE-A Long-term evolution-advancedMAC Media access controlMaxGain Maximum gainMaxRate Maximum rateMBS Macro-cell base stationMCS Modulation and coding schemeMF Matched filterMIMO Multiple-input-multiple-outputMIMO-IC MIMO interference channelMinGain Minimum gainMinRate Minimum rateMISO Multiple-input-single-outputMLSFC Multilayered space-frequency codesMLWDF Modified largest weighted delay firstMMF Max-min fairnessMMR Max-min rateMMSE Minimum mean-square errorMMSV Maximum minimum singular valueMOM Method of momentsMRC Maximum ratio combiningMRT Maximum ratio transmissionMS Mobile station (in all chapters, except Chap. 1)MS Multiple-Stream (in Chap. 1)MSE Mean squared errorMU-MIMO Multiuser MIMOMUD Multiuser diversityMUE Macro-cell user equipmentMU Multi-userNE Nash equilibriumNLOS Non-line-of-sight

Acronyms xxxv

NMSE Normalized mean square errorNP Non-deterministic polynomial-timeNRT Non-real timeOFDM Orthogonal frequency-division multiplexingOFDMA Orthogonal frequency-division multiple accessORBF Opportunistic random beamformingP-LS-KRF Parallelized LS-KRFP2P Peer-to-peerPAPR Peak to average power ratioPARAFAC PARAllel FACtorPCS Personal communications servicesPDF Probability density functionPDP Power delay profilePF Proportional fairPIFA Planar inverted F antennasPJP Partial joint processingPMI Precoding matrix indexPRB Physical resource blockPS Packet schedulingPSD Positive semidefinitePSK Phase-shift keyingQAM Quadrature amplitude modulationQoS Quality of serviceQPSK Quadrature phase-shift keyingr.m.s. Root mean squareRAS Receive antenna selectionRAT Radio access technologyRB Resource blockRF Radio frequencyRHS Right-hand sideRIBF Regularized inverse beamformingRM Rate maximizationRND RandomRR Round robinRRA Radio resource allocationRRM Radio resource managementRS Random scheduling (in Chap. 6)RS Relay station (in Chap. 5)RSAM Relay selection acknowledge messageRSRC Root square reconstruction changeRSS Received signal strengthRT Real timeRV Random variableRVQ Random vector quantizationRX Receiver

xxxvi Acronyms

S-CFP Simplified closed-form PARAFACSBS Small-cell base stationSCM Spatial channel modelSDM Space-division multiplexingSDMA Space-division multiple accessSER Symbol error rateSES Simple exponential smoothingSFC Space-frequency codeSIMO Single-input multiple-outputSINR Signal-to-interference-plus-noise ratioSISO Single-input-single-outputSM Selfish maximization (in Chap. 11)SM Spatial Multiplexing (in Chaps. 6, 8 and 9)SMD Simultaneous matrix diagonalizationsSMMSE Successive minimum mean square errorSNR Signal-to-noise ratioSON Self organizing networkSORA-NRT Satisfaction-oriented resource allocation for non-real time servicesSORA-RT Satisfaction-oriented resource allocation for real time servicesSP Successive projectionSRA Sequential removal algorithmSRM Sum rate maximizationSRM-P Sum rate maximization with proportional rate constraintsSS Simultaneous scheduling (in Chap. 6)SS Single-stream (in Chap. 1)SSAM Source acknowledge messageSSRM Source selection request messageSTC Space-time codingSU Single-userSU-MIMO Single-user MIMOSUE Small-cell user equipmentSVD Singular value decompositionT-RAS Antenna selection at transmitter and receiver sideTAS Transmit antenna selectionTCP Transmission control protocolTDD Time divison duplexTDMA Time division multiple accessTETRA Terrestrial trunked radio accessTP Transmission pointTPD True polarization diversityTSM Throughput-based satisfaction maximizationTTI Transmission time intervalTU Typical urbanTV-LCP Time-varying LCPTX Transmitter

Acronyms xxxvii

UCA Uniform circular arrayUE User equipmentUEPS Urgency and efficiency-based packet schedulingUFI User fairness indexUL UplinkULA Uniform linear arrayUSR User selection requirementVFDM Vandermonde-subspace frequency division multiplexingVoIP Voice over IPVQ Vector quantizationWF Water-fillingWIFI Wireless fidelityWLAN Wireless local area networkWWW World Wide WebZF Zero-forcingZFBF Zero-forcing beamformingZMCSCG Zero mean circularly symmetric complex gaussian

xxxviii Acronyms