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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Explore this insightful foundational resource for academics and industry professionals dealing with the move toward intelligent devices and networks Interference Mitigation in Device-to-Device Communications delivers a thorough discussion of device-to-device (D2D) and machine-to-machine (M2M) communications as solutions to the proliferation of ever more data hungry devices being attached to wireless networks. The book explores the use of D2D and M2M technologies as a key enabling component of 5G networks. It brings together a multidisciplinary team of contributors in fields like wireless communications, signal processing, and antenna design. The distinguished editors have compiled a collection of resources that practically and accessibly address issues in the development, integration, and enhancement of D2D systems to create an interference-free network. This book explores the complications posed by the restriction of device form-factors and the co-location of several electronic components in a small space, as well as the proximity of legacy systems operating in similar frequency bands. Readers will also benefit from the inclusion of: * A thorough introduction to device-to-device communication, including its history and development over the last decade, network architecture, standardization issues, and regulatory and licensing hurdles * An exploration of interference mitigation in device-to-device communication underlaying LTE-A networks * A rethinking of device-to-device interference mitigation, including discussions of the challenges posed by the proliferation of devices * An analysis of user pairing for energy efficient device-to-device content dissemination Perfect for researchers, academics, and industry professionals working on 5G networks, Interference Mitigation in Device-to-Device Communications will also earn a place in the libraries of undergraduate, graduate, and PhD students conducting research into wireless communications and applications, as well as policy makers and communications industry regulators.
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Veröffentlichungsjahr: 2022
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Table of Contents
Cover
Title Page
Copyright
Dedication
Preface
Acknowledgments
About the Editors
List of Contributors
1 Introduction to D2D Communications
1.1 D2D Communication
1.2 Evolution of D2D Communication
1.3 D2D Communication in Cellular Spectrum
1.4 Classification of D2D Communication
1.5 Challenges in D2D Implementation
1.6 Summary
References
2 Interference Mitigation in D2D Communication Underlaying LTE-A Network
2.1 Applicability of D2D Communication
2.2 Interference – The Compelling Issue in D2D
2.3 Types of D2D Communication
2.4 D2D Communication Underlaying Cellular Network – The Challenges
2.5 Interference in D2D
2.6 Summary
References
3 Rethinking D2D Interference: Beyond the Past
3.1 Interference Manipulation
3.2 Formulation of Interference Manipulation Problem
3.3 Matrix Rank Minimization: A Way to Manipulate Interference
3.4 Interference Manipulation: A Boolean Satisfiability Approach
3.5 Interference Manipulation: Index Coding Perspective
3.6 Summary
References
4 User Pairing Scheme for Efficient D2D Content Delivery in Cellular Networks
4.1 D2D Content Delivery
4.2 D2D Content Delivery Architecture
4.3 D2D Content Delivery Strategies
4.4 D2D Delivery Mode Selection
4.5 Performance Evaluation
4.6 Summary
References
5 Resource Allocation for NOMA-based D2D Systems Coexisting with Cellular Networks
5.1 NOMA-based D2D Systems
5.2 System Model and Performance Analysis
5.3 Joint Subchannel Assignment and Power Control for D2D Communication
5.4 Optimization of D2D Device Pairing
5.5 Results and Discussion
5.6 Summary
References
Note
6 Distributed Multi-Agent RL-Based Autonomous Spectrum Allocation in D2D-Enabled Multi-Tier HetNets
6.1 D2D Resource Allocation Methods
6.2 Reinforcement -Learning
6.3 System Model
6.4 Resource Allocation in Multi-tier D2D Communication
6.5 Performance Evaluation
6.6 Summary
References
7 Adaptive Interference Aware Device-to-Device-Enabled Unmanned Aerial Vehicle Communications
7.1 Key Elements in D2D Communication
7.2 Unmanned Aerial Vehicles in D2D
7.3 Summary
References
8 Emergency Device-to-Device Communication: Applicability, Case Studies and Interference Mitigation
8.1 Emergency D2D Communication
8.2 Approaches for Efficient Emergency D2D Communication
8.3 Emergency D2D Communication: Case Studies
8.4 Interference Mitigation in Emergency D2D Communication
8.5 Summary
References
9 Disaster Management Using D2D Communication With Power Transfer and Clustering Techniques
9.1 D2D Communication in Disaster Management
9.2 D2D Communication in Disaster Management: Key Considerations
9.3 D2D Disaster Management System Architecture
9.4 Power Transfer Using Relaying and Clustering in D2D Disaster Management
9.5 Results and Discussion
9.6 Summary
References
10 Road Ahead for D2D Communications
10.1 Future Prospects and Challenges
References
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Comparison between D2D technologies.
Table 1.2 Use cases for D2D in 3GPP release.
Chapter 2
Table 2.1 Comparative analysis of D2D communication.
Table 2.2 User communication modes in D2D enable cellular networks.
Table 2.3 Classification of interference scenarios for different resource-sh...
Table 2.4 Summary of literatures on interference mitigation techniques in D2...
Table 2.5 Comparative analysis of interference mitigation techniques in D2D ...
Table 2.6 Pros and cons of D2D interference mitigation techniques.
Chapter 3
Table 3.1 Interference manipulation.
Chapter 4
Table 4.1 Mode selection algorithm for content delivery.
Table 4.2 Simulation parameter settings.
Chapter 5
Table 5.1 Simulated network parameters.
Chapter 6
Table 6.1 Notations.
Table 6.2 Basic working of autonomous spectrum allocation scheme.
Table 6.3 Network model and simulation parameters.
Chapter 7
Table 7.1 Summary of some D2D-funded projects.
Chapter 8
Table 8.1 Studies utilizing D2D communications in disaster management.
Table 8.2 Parameters of RSU unit and ITU signal.
Table 8.3 Parameters for intergroup V2V communication.
Chapter 9
Table 9.1 Simluation parameters.
Chapter 10
Table 10.1 RF and VLC technologies in comparison.
List of Illustrations
Chapter 1
Figure 1.1 Device-to-device communication modes.
Figure 1.2 D2D communication overview.
Figure 1.3 In-band D2D communication.
Figure 1.4 Out-band D2D communication.
Figure 1.5 Challenges in D2D implementation.
Chapter 2
Figure 2.1 D2D communication architecture [7]. (a) D2D communication as an u...
Figure 2.2 Illustration of D2D-enabled cellular network concepts and use cas...
Figure 2.3 Classification of D2D communication [7].
Figure 2.4 A single cell comprising of multiple cellular links, and D2D link...
Figure 2.5 Schematic frequency band occupancy of D2D communication in cellul...
Figure 2.6 Network-assisted D2D control message exchange and link establishm...
Figure 2.7 Device-controlled discovery and session setup procedures [7].
Figure 2.8 Schematic representation of D2D-enhanced LTE architecture [7].
Figure 2.9 Interference scenario of D2D and cellular links under uplink reso...
Figure 2.10 Interference scenario of D2D and cellular links under downlink r...
Figure 2.11 D2D power control model [7].
Figure 2.12 Schematic representation of beamforming with eNB and D2D users e...
Figure 2.13 Interference scenario in multi-cell network [7].
Figure 2.14 Overview of interference mitigation techniques in D2D communicat...
Chapter 3
Figure 3.1 A multi-source multi-receiver wireless interference network.
Figure 3.2 Index coding's instance corresponding to Interference Manipulatio...
Figure 3.3 (a) Dependency graph for the instance of the Index Coding problem...
Figure 3.4 An efficient solution for Interference Manipulation.
Figure 3.5 Algorithm
IM
.
Chapter 4
Figure 4.1 Successfully receiving probability
against the D2D link distanc...
Figure 4.2 The number of UEs successfully receiving their required files
a...
Figure 4.3 The number of UEs successfully receiving their required files
a...
Figure 4.4 The transmission power
against radius of TSZ
under different ...
Figure 4.5 The transmission efficiency coefficient
with different radii of...
Figure 4.6 The transmission efficiency coefficient
with different TSZ radi...
Figure 4.7 The transmission efficiency coefficient
with different TSZ radi...
Figure 4.8 Caching and delivery coefficient
with different files number
....
Figure 4.9 The expectation of MP
under D2D mode against D2D transmitter de...
Figure 4.10 The expectation of MP
under cellular mode against BS density
Figure 4.11 D2D energy-efficient coefficient
under different cases. Case I...
Chapter 5
Figure 5.1 The proposed system model [42].
Figure 5.2 Total transmit power of D2D devices various number of pairs in ea...
Figure 5.3 Number of accessed D2D pairs versus number of cellular users [42]...
Figure 5.4 Total transmit power of D2D devices versus number of cellular use...
Figure 5.5 Total transmit power of D2D devices versus various number of D2D ...
Figure 5.6 The accessed probability of NOMA-D2D system versus the number of ...
Chapter 6
Figure 6.1 Infrastructure of heterogeneous network.
Figure 6.2 Machine learning in 5G.
Figure 6.3 Illustration of network model.
Figure 6.4 Jane's fairness index for ASA scheme.
Figure 6.5 Aggregate throughput of D2D users against number of D2D users in ...
Figure 6.6 Spectral efficiency comparison of different schemes.
Figure 6.7 Comparison of CDF of average throughput of D2D user in network.
Figure 6.8 Mean SINR of conventional cellular users in network against numbe...
Figure 6.9 Outage ratio of conventional cellular users against number of D2D...
Figure 6.10 CCDF of coverage of network with 50 D2D users-ASA scheme.
Figure 6.11 CCDF of coverage of network with 50 D2D users-DRC scheme.
Figure 6.12 CCDF of coverage of network with 50 D2D users-joint RALA scheme....
Figure 6.13 Computation time comparison of different schemes for resource al...
Figure 6.14 Effect of increase in base stations density on aggregate through...
Figure 6.15 Effect of network tier on aggregate throughput of D2D users in t...
Chapter 7
Figure 7.1 D2D modes of operation.
Figure 7.2 Mission critical and D2D service enhancements with 3GPP releases....
Figure 7.3 Architecture of the heterogeneous network scenario with multihop ...
Figure 7.4 Packet error rate for UAV-UE link.
Figure 7.5 Throughput for UAV-UE link.
Figure 7.6 BPSK BER constellation diagram.
Figure 7.7 PER with varying SINR at UE for different environments.
Figure 7.8 PER with varying altitude of interfering UAV for different enviro...
Chapter 8
Figure 8.1 D2D communication scenario.
Figure 8.2 Features of D2D communication.
Figure 8.3 System scenario for D2D.
Figure 8.4 Energy efficiency of the multi-hop D2D transmissions.
Figure 8.5 Analog interference mitigation scheme for adjacent channel proble...
Figure 8.6 Average SINR versus distance between two groups of vehicles for t...
Chapter 9
Figure 9.1 Energy harvesting concept in disaster situation [18].
Figure 9.2 Outage probability as a function of energy efficiency for differe...
Figure 9.3 Outage probability as a function of
for different values of
[...
Figure 9.4 Outage probability as a function of
for different values of
[...
Figure 9.5 Combined system model framework for disaster recovery communicati...
Figure 9.6 Energy loss during transfer of energy [18].
Figure 9.7 Comparison of total energy consumption of UEs devices in non-clus...
Figure 9.8 Average number of clusters [18].
Figure 9.9 Gain of D2D clustering versus non-clustering box plot of energy g...
Figure 9.10 Power of single subcarrier [18].
Figure 9.11 CDF for 100 UEs devices [18].
Figure 9.12 The power drained from the battery of relay to transmit the data...
Chapter 10
Figure 10.1 Closed access 5G and D2D communication.
Figure 10.2 Separated information and energy receiver.
Figure 10.3 Integrated information and energy receiver.
Figure 10.4 (a) Co-tier interference (b) cross-tier interference.
Figure 10.5 (a) Centralized resource allocation (b) distributed resource all...
Guide
Cover Page
Title Page
Copyright
Dedication
Preface
Acknowledgments
About the Editors
List of Contributors
Table of Contents
Begin Reading
Index
End User License Agreement
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Interference Mitigation in Device-to-Device Communications
Edited by
Masood Ur RehmanJames Watt School of Engineering, University of Glasgow, UK
Ghazanfar Ali SafdarSchool of Computer Science and Technology, University of Bedfordshire, UK
Mohammad Asad Rehman ChaudhrySoptimizer, Toronto, Canada
This edition first published 2022
© 2022 John Wiley & Sons Ltd
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Library of Congress Cataloging-in-Publication Data
Names: Ur Rehman, Masood, editor. | Safdar, Ghazanfar Ali, editor. | Chaudhry, Mohammad Asad Rehman, editor.
Title: Interference mitigation in device-to-device communications / edited by Masood Ur Rehman, Ghazanfar Ali Safdar, Mohammad Asad Rehman Chaudhry.
Description: Hoboken, NJ : Wiley, 2022. | Includes index.
Identifiers: LCCN 2021046319 (print) | LCCN 2021046320 (ebook) | ISBN 9781119788799 (cloth) | ISBN 9781119788805 (adobe pdf) | ISBN 9781119788812 (epub)
Subjects: LCSH: Wireless communication systems. | Electromagnetic interference.
Classification: LCC TK5103.2 .I5179 2022 (print) | LCC TK5103.2 (ebook) | DDC 621.384--dc23
LC record available at https://lccn.loc.gov/2021046319
LC ebook record available at https://lccn.loc.gov/2021046320
Cover Design: Wiley
Cover Image: © metamorworks/Shutterstock
Dedicated to ALLAH, the Lord and the Sustainer of all the realms. Asad lowers his wings of humility to Mum and Abbu.Mohammad Asad Rehman ChaudhryMasood Ur RehmanGhazanfar Ali Safdar
To my biggest inspiration, my parents, Khalil Ur Rehman and Ilfaz Begum my support system, siblings; Habib, Waheed, Tahera and wife; Faiza and apple of my eyes, my son, Musaab.Masood Ur Rehman
To my late parents, Safdar Hussain and Sadiq Sultana and my two little angels, Taha and Taqi and my wife, Misbah.Ghazanfar Ali Safdar
Preface
Emergence of data-extensive applications such as online gaming and video sharing has resulted in exponential increase in the mobile data traffic. Advances in Internet-of-Things (IoT) and 5G require fusion of multiple sensors and wireless devices operating in real time. Supporting such high data rate demands within the framework of existing wireless access networks is a challenging task. Addressing this ever-increasing demand of data hungry devices in an efficient and effective manner has driven the wireless industry to investigate new paradigms. Device-to-device (D2D) communication is a promising solution to this complex problem and hence a key-enabling technology for 5G. The D2D is envisioned to operate either in out-band mode representing usage of a dedicated spectrum or in-band mode demonstrating operation within the same spectrum of the existing cellular spectrum.
The D2D communication provides the closely located users with an opportunity to communicate directly without traversing traffic through the base station while offering exciting advantages of improved throughput, increased spectrum reuse, and enhanced energy gain. The attractive features and simple infrastructure of D2D communication are making it experience a tremendous growth, having an expectation of the global number of D2D connections specifically to reach 14.7 billion devices by 2023. Applications of D2D communication cover a wide variety of fields ranging from communication to infotainment, healthcare to surveillance, and public safety to manufacturing.
Integration of the D2D communication with legacy systems brings new technical challenges. Interference to the primary users is one of the major challenges that needs to be managed and mitigated effectively in order to have an optimal system performance. The current developments and expected future growth of the D2D communication necessitate a comprehensive reference dealing with this fundamental and paramount issue.
A dedicated book that addresses these important issues is rarely available. This book is, therefore, a laborious effort to put together the basis of interference and principles for advanced management techniques in D2D communication. It brings together multidisciplinary contributors in the field of wireless communication, system modeling, and signal processing to take up on the challenges and devise solutions related to the development, integration, and enhancement of D2D systems to solicit an interference-free operation.
The state of the art as well as advanced topics on interference mitigation in standard as well as emergency scenarios are discussed. Interference management through power control, resource allocation, spectrum splitting, MIMO antennas, interference manipulation, user pairing, content delivery, subchannel assignment, reinforcement learning, mode selection, and clustering is considered. Moreover, a comprehensive account of system modeling, design challenges, and performance analysis are presented. Particular focus is put on the promising new dimension of D2D-based disaster management and use of Unmanned Aerial Vehicles for infrastructure-less communications. The book is concluded by highlighting potential future application areas and avenues of research and development for D2D communication. Treatment of variety of topics makes this book a valued reference for the communication system designers, researchers, lecturers, and students.
Masood Ur RehmanGhazanfar Ali SafdarMohammad Asad Rehman Chaudhry
Acknowledgments
Editing a book is more strenuous than we thought and more rewarding than we could have imagined. This journey took two years for us to enjoy this sense of contentment. We would like to thank the commissioning editor Sandra Grayson, managing editor Juliet Booker, editorial assistant Becky Cowan, and publishers who showed great patience and extended a supporting hand throughout the journey of compiling this book. None of this would have been possible without their help.
We would also like to thank Mr. Khuram Ashfaq and Mr. Abduljabbar for their help in reviewing Chapters 1 and 10, respectively.
And finally, our sincere gratitude goes to all the contributors whose participation resulted in an excellent reference on this interesting topic.
About the Editors
Masood Ur Rehman received the BSc degree in Electronics and Telecommunication Engineering from University of Engineering and Technology, Lahore, Pakistan, in 2004, and the MSc and PhD degrees in Electronic Engineering from Queen Mary University of London, London, UK, in 2006 and 2010, respectively. He worked at Queen Mary University of London as a Postdoctoral Research Assistant till 2012 before joining the Centre for Wireless Research at University of Bedfordshire as a Lecturer. He served briefly at the University of Essex and then moved to the James Watt School of Engineering at University of Glasgow in the capacity of an Assistant Professor in 2019. His research interests include compact antenna design, radiowave propagation and channel characterization, satellite navigation system antennas in cluttered environment, electromagnetic wave interaction with human body, body-centric wireless networks and sensors, remote healthcare technology, mmWave and nano communications for body-centric networks, and D2D/H2H communication. He has worked on a number of projects supported by industrial partners and research councils. He has contributed to a patent and authored/co-authored 4 books, 8 book chapters, and more than 120 technical articles in leading journals and peer-reviewed conferences.
He is a Fellow of the Higher Education Academy (UK), a Senior Member of the IEEE, a Member of the IET, and a part of the technical program committees and organizing committees of several international conferences, workshops, and special sessions. He is acting as an Associate Editor of the IEEE Access, IET Electronics Letters & Microwave and Optical Technology Letters and lead guest editor of numerous special issues of renowned journals. He also serves as a reviewer for book publishers, IEEE conferences, and leading journals.
Ghazanfar Ali Safdar received his BSc Hons in Electrical Engineering from University of Engineering and Technology, Pakistan, and MEngg in Computer Science and Telecommunications from ENSIMAG, INPG, France. He was awarded a PhD from Queen's University Belfast, UK, in 2005, for his work in the area of power-saving MAC protocols for the IEEE 802.11 family of wireless LANs. Moreover, he has worked as a Research Fellow at Queen's University Belfast on a project related to Wireless Networks security. Currently, he is working as a Senior Lecturer in Computer Networking at the University of Bedfordshire, UK. His research interests mainly include cognitive radio networks, energy-saving MAC protocols, security protocols for wireless networks, LTE networks, interference mitigation, device-to-device communications, network modeling, and performance analysis. He has authored/co-authored 4 books, 13 books chapters, and around 100 plus research articles in leading journals and peer-reviewed conferences.
He is an Associate Fellow of Higher Education academy (UK) and a Session Chair and part of technical program committees of several international conferences. He has also worked as R&D Engineer with Carrier Telephone Industries (SIEMENS), Pakistan, and Schlumberger, France. He is currently serving as the Editor-in-Chief of EAI Endorsed Transactions on Energy Web and Information Technology, and an Area Editor for Springer Wireless Networks. He regularly serves as a reviewer for several esteemed journals, book proposals, and conferences.
Mohammad Asad Rehman Chaudhry received a PhD in Electrical and Computer Engineering from Texas A&M University, and an MBA from University of Toronto-Rotman School of Management. He is a thought-leader, strategist, innovator, and entrepreneur. He has been leading multidisciplinary global projects in Digital Disruption and its adaptation for Socio-Economic transformation. He has delivered several keynotes at international events. He has advised senior executives from Fortune 500 companies on Digital Strategy and Future-Tech. He leads IEEE standards related to Software Defined and Virtualized Ecosystems. He is also a co-founder of two companies. He has previously held positions with IBM Research, Hamilton Institute, University of Toronto, DARPA System F6, and the University of Calgary. He has served in various executive and board positions. He is a recipient of the Fulbright Fellowship and the Presidential Scholarship.
List of Contributors
Sohail AhmedDepartment of Avionics EngineeringAir UniversityIslamadadPakistan
Kamran AliComputer Science DepartmentMiddlesex UniversityLondonUnited Kingdom
Rafay I. AnsariDepartment of Computer and Information SciencesNorthumbria UniversityNewcastleUnited Kingdom
Zakia AsadSoptimizerCanada
Muhammad AwaisComputer Science DepartmentEdge Hill UniversityOrmskirkUnited Kingdom
Mohammad Asad Rehman ChaudhrySoptimizerCanada
Imran HaiderAcme Center for Research in Wireless Communications (ARWiC)Capital University of Science and TechnologyIslamabadPakistan
Muhammad A. ImranJames Watt School of EngineeringUniversity of GlasgowGlasgowUnited Kingdom
Byungtae JangElectronics and Telecommunications Research InstituteDaejeonSouth Korea
Tahera KalsoomSchool of Computing, Engineering and Physical SciencesUniversity of West of ScotlandPaisleyUnited Kingdom
Nauman JavedSchool of Electrical Engineering & Computer ScienceNational University of Sciences and TechnologyIslamabadPakistan
Rida KhanThomas Johann Seebeck Department of ElectronicsTallinn University of TechnologyTallinnEstonia
Aboubaker LasebaeComputer Science DepartmentMiddlesex UniversityLondonUnited Kingdom
Hassan MalikDepartment of Computer ScienceEdge Hill UniversityOrmskirkUnited Kingdom
Muhammad Y. M. MirzaLahore Business SchoolUniversity of LahoreLahorePakistan
Mujahid MuhammadBirmingham City UniversityBirminghamUnited Kingdom
Bushrah NaeemDepartment of Computer ScienceBalochistan University of Information TechnologyEngineering, and Management Sciences (BUITEMS)QuettaPakistan
Huan NguyenComputer Science DepartmentMiddlesex UniversityLondonUnited Kingdom
Tien H. NguyenSchool of Electronics and TelecommunicationsHanoi University of Science and Technology (HUST)HanoiVietnam
Van D. NguyenHanoi University of Science and TechnologyHanoiVietnam
Xuan T. NguyenSchool of Electronics and TelecommunicationsHanoi University of Science and TechnologyHanoiVietnam
Vishnu V. ParanthamanRDS Global Ltd.DerbyUnited Kingdom
Haris PervaizSchool of Computing and CommunicationsLancaster UniversityBailriggUnited Kingdom
Farrukh PervezSchool of Electrical Engineering & Computer ScienceNational University of Sciences and TechnologyIslamadadPakistan
Asad A. PirzadaSchool of Electrical Engineering & Computer ScienceNational University of Sciences and TechnologyIslamadadPakistan
Mohsin RazaComputer Science DepartmentEdge Hill UniversityOrmskirkUnited Kingdom
Ghazanfar Ali SafdarSchool of Computer Science and TechnologyUniversity of BedfordshireLutonUnited Kingdom
Purav ShahComputer Science DepartmentMiddlesex UniversityLondonUnited Kingdom
Navuday SharmaTest Software DevelopmentEricsson Eesti ASTallinnEstonia
Muhammad N. SialDepartment of InformaticsKing's College LondonLondonUnited Kingdom
Anum TanveerComputer Science DepartmentMiddlesex UniversityLondonUnited Kingdom
Masood Ur RehmanJames Watt School of EngineeringUniversity of GlasgowGlasgowUnited Kingdom
Yanli XuCollege of Information EngineeringShanghai Maritime UniversityShanghaiChina
Daeseung YooElectronics and Telecommunications Research InstituteDaejeonSouth Korea
Taehyun YoonElectronics and Telecommunications Research InstituteDaejeonSouth Korea
Kamran ZiaSchool of Electrical Engineering & Computer ScienceNational University of Sciences and TechnologyIslamabadPakistan
1Introduction to D2D Communications
Ghazanfar Ali Safdar1, Masood Ur Rehman2, and Mohammad Asad Rehman Chaudhry3
1 School of Computer Science and Technology, University of Bedfordshire, Luton, United Kingdom
2 James Watt School of Engineering, University of Glasgow, Glasgow, United Kingdom
3 Soptimizer, Canada
A perceptible upsurge has been discerned in wireless data traffic in recent years due to the occurrence of numerous new applications, thereby imposing an abrupt requirement for a large capacity network. Among them, multimedia applications such as high definition (HD) video streaming, HD video conferencing, and online gaming are most common [1]. Another factor impacting wireless data traffic is the primer of smart wearable technology such as watches, air pods and wrist band. In the near future, these devices would increase tenfold or even more, and their presence ensures more and more usage of smart wireless devices. For majority of the users, the wireless cellular network is the main access system for the internet due to its universal availability. According to Cisco white paper [2], there will be 12.3 billion mobile-connected devices by 2022 and mobile will represent 20 percent of total IP traffic, and global mobile data traffic will increase sevenfold between 2017 and 2022, reaching 77.5 exabytes per month by 2022. This pretense new contest to those working in the field of cellular communication and operators is deploying more and more wireless links between terminals with radio networking to meet the required demand.
1.1 D2D Communication
Existing device-to-device (D2D) technologies such as Bluetooth and Wi-Fi direct are available for thorough communication between two devices in close contiguity. They can associate different types of devices since the level of compatibility between modern devices is very high. The pairing procedure is considerably easy and both technologies simplify the entire pairing process by making enabled devices readily discoverable to one another [3]. Devices can communicate over a reliable communication channel with a moderate date rate and latency. Since the communication range is limited in these technologies, mobile device benefits from low power consumption that improves the battery life of the devices. In addition, it allows different devices to connect and communicate with each other without the need of an additional infrastructure.
Despite all the above benefits, both technologies have some limitations like single hop communication, limited range, latency, and moderate data. Both technologies are operated in the unlicensed band; hence, interference is eminent due to the number of devices already operated in that band [4]. Also, on an unlicensed band, the maximum transmit power constraint confines communication to a limited range. Both technologies have asynchronous nature, and the device receiver is supposed to continuously monitor the channel. The reason for this channel monitoring (idle listening) is not to miss the discovery signal from other devices, but this can drain the device battery significantly. Finally, to establish a reliable communication, the users are responsible for the discovery and initiation mechanism, and there is no centralized control. All of the above factors are the main obstacles in the integration of both technologies with next generation of mobile networks and they fail to act as a D2D on large scale. Another most common technology operated in the unlicensed band is Wi-Fi that has already assisted cellular networks in offloading local traffic and easing congestion. But its implementation requires a setup of access points connected to the internet and performance degrades as the number of user increases.
The diversity of radio accessing in mobile users provides lots of flexibility for D2D communication in terms of link establishment, resource allocation, energy efficiency, as well as applications and services. D2D communication enables researchers to merge together the achievements of long-term development in previously two disjoint networking techniques, i.e. ad-hoc networking and centralized networking. D2D users can form clusters or multihop routes, operates autonomously or under partial or full control of the operator. On the other hand, with the assistance of the operator, it is possible to achieve network-wide performance optimization after properly allocating frequency bands to D2D pairs and managing the interference there. D2D communication in cellular band is a very flexible communication technique with unique advantages over existing D2D techniques. D2D in cellular band can significantly enhance the cellular communication in terms of system capacity, coverage, throughput, latency, and user experience [1]. D2D communication can offload traffic from the serving base station by quickly exchanging a large amount of data among mobile devices in short range and alleviate congestion in the cellular core network.
In addition to that, D2D can also support local area services such as content distribution, local advertisement, and location aware services very effectively through unicast, groupcast, and broadcast transmission. A D2D in-coverage user can also act as a relay and extend the existing coverage of a serving base station and benefits the device that is on the edge of the cell boundary to experience better coverage [1]. The serving base station has the overall view of the entire cell, and it can facilitate D2D communication in different aspect, for example, finding the neighboring devices, reducing the transmitting power, and providing a suitable environment for communication. D2D implementation in cellular network does not require additional infrastructure and hence suppresses the high implementation costs. Undoubtedly, the reduction in transmission delay and offloading traffic from the existing base station to eases congestion in the cellular core network are the driving factors toward its addition in next generation of mobile networks [4].
In recent research, there are various attractive benefits of D2D in terms of spectral efficiency, energy efficiency, through put, and signal-to-interference and noise ratio (SINR). However, it is still unknown that if these gains could be fully utilized in the practice. In D2D communication, in spite of having many advantages, there are still many open challenges for the successful implementation of this technology. In particular, D2D communication will require efficient device discovery mechanisms (among devices in close proximity), intelligent mode selection (D2D or cellular mode) algorithms, complex resource management techniques (to avoid interference), and robust security protocols. Interference management is one of the compelling areas in D2D communication, and researchers have proposed different schemes, protocols, and methods to reduce interface. It is quite beneficial from a capacity and spectral efficiency point of view that D2D users reuse the same cellular resource for D2D communication. But it generates interference and requires different techniques to ensure that the quality of service (QoS) of a cellular link is not degraded because of D2D communication.
1.2 Evolution of D2D Communication
The wireless revolution in telecommunication begun in 1990s with the introduction of cellular network and has been driven by advances in radio frequency (RF) and microwave engineering [11]. In the past, infrared (IR) wireless technology was used for point-to-point links that use devices that are inexpensive, compact, lightweight, and consume low power. The limitations of IR technology were short distance, mobility of devices during transmission, and line-of-sight (LOS) requirement between transmitter and receiver. Unlike IR, the RF technology was effectively used for a long-distance communication that can penetrate through obstacles and does not require a LOS. RF technology operates in the range of 3 kHz–300 GHz and used for communication and broadcasting. The radio spectrum is divided into different segments and assigned to different technology industries, for example, very high frequency (VHF) band that ranges from 30 to 300 MHz is assigned to FM radio and TV broadcast, while ultra-high frequency (UHF) is dedicated to cellular, wireless local area network (WLAN), and Bluetooth, etc.
Current D2D technologies such as Bluetooth and Wi-Fi direct operate in unlicensed industrial, scientific, and medical (ISM) band; therefore, the interference with other devices operated in similar band is uncontrollable. Both suffers from limitations such as single hop communication, interference, limited range, latency, moderate data rate, and no centralized control. The burden of device discovery and communication initiation is also upon the user to establish a successful and reliable communication. The biggest obstacle is the inherit architecture of both technologies that does not allow a centralized controller to control and manage the D2D communication. Future cellular nodes would have the global view of the entire cell, and they can effectively manage the available resources for a successful D2D communication. The diversity of cellular communication provides lots of flexibility for D2D communication in terms of link establishment, resource allocation, energy efficiency, as well as applications and services. The communication on a licensed cellular band can be better in terms of interference avoidance under a controlled environment.
Table 1.1 Comparison between D2D technologies.
Technology/ parameters
Device-to-device in LTE-A
Bluetooth
Wi-Fi direct
Standardization
3GPP LTE-A (release 12)
Bluetooth SIG 5.0
IEEE 802.11, WECA
Frequency band
Licensed band for LTE-A
2.4 GHz
2.4 and 5 GHz
Max transmission distance
Up to 500 m
Up to 200 m
Up to 200 m
Max transmit power
24 dBm
4 dBm
15 dBm
Data throughput
1 Gbps
1.4 Mbps
250 Mbps
Frequency sharing
In-band UL or DL frequency spectrum
Frequency hoping spread spectrum
(
FHSS
)
Orthogonal frequency division multiplexing
(
OFDM
)
Modulation technique
SC-
frequency division multiple access
(
FDMA
) (UL),
orthogonal frequency division multiple access
(
OFDMA
) (DL)
GFSK
DSSS
Latency
D2D mode – Ultra-low Cellular mode – 9 ms
200 ms
150 ms
Power consumption
Low in D2D mode High in cellular mode
Low
High
Interference
Controlled interference environment that leads to less interference
Yes
Yes
Quality of service
Provide hard QoS guarantees
Bluetooth
medium access control
(
MAC
) scheduling
Wi-Fi multimedia extensions
(
WME
)
Security
Better security guarantee
Service-level security Device-level security
Strong
Wi-Fi protected access
(
WPA
)
Control
Centrally control by the base station (either fully or partially)
No centralized control
No centralized control
Discovery procedure
Discovery via broadcast
Use
SDP
(
service discovery protocol
) to locate services that are available nearby
Two steps asynchronous message-based discovery
Hardware requirement
ProSe application sever incorporated in
evolved packet core
(
EPC
) ProSe application installed on user device
Bluetooth adaptor on all the devices connecting with each other
Wireless adaptors on all the devices
Implementation complexity
High – ProSe application on User device ProSe application server incorporated in EPC
Low – Small low-cost microchip embedded in Bluetooth enabled device
Low – It is relatively simple and requires configuration of hardware and software.
Applications
Offload traffic, multimedia content sharing, local advertising and PS applications
Data sharing between peripheral connection
Content sharing, group gaming and device connection
Primary devices
Cellular device only
Mobile phones, mouse, keyboards, office, and industrial automation devices
Cellular devices, portable media players, printers, cameras, and scanners
D2D communication can be utilized during the absence of an active mobile network, and it allows the device to establish an alternate wireless link with the surrounding in-coverage devices. This can increase the overall coverage area and D2D user acting as a relay extends communication over a greater range. Other applications of D2D are content distribution, local advertisement, and location-aware services [5]. D2D can also be implemented in machine-to-machine communication where one machine can talk with another machine in close proximity. D2D can also be implemented in vehicle-to-vehicle communication and other autonomous driving applications. A comprehensive comparison between Bluetooth, Wi-Fi direct, and D2D in cellular band is shown in Table 1.1
1.3 D2D Communication in Cellular Spectrum
D2D communication has always been present in the unlicensed spectrum but it was not investigated in the licensed spectrum in the first three cellular generations. The idea of D2D in licensed spectrum was introduced in the fourth generation and third generation partnership project (3GPP) announced D2D functionality in release 12 in 2012. In order to embed D2D functionality in long term evolution-advanced (LTE-A) network, they proposed a proximity services (ProSe) function to exchange data and voice among nearby devices. Initially, the discovery procedure was limited to in-coverage scenario where a user device autonomously selects the resource from a preconfigured pool. In addition, D2D communication was also proposed for public safety (PS includes police, firefighter, and ambulances) services in an area with no active network coverage [6,7]. Later in release 13 in 2014, a further enhancement in D2D was proposed that include one-to-one communication between devices and discovery procedure was extended to out-of-coverage scenario. ProSe function was also proposed to use as a user equipment (UE)-to-network relay by means of a layer 3 based relaying and UE acts as a relay between a remote UE and a base station.
Table 1.2 Use cases for D2D in 3GPP release.
Release 12
Release 13
Release 14
Release 15
Release 16 and beyond
PS
PS enhancement
V2V
Platooning
Maritime communication system
ProSe
ProSe enhancement
V2I
Extended sensors
Side link enhancements include V2X
UE-to-network relay
V2N
Advanced driving
Critical communications
V2P
Remote driving
Commercial use between smartphone directly
Since release 14, the implementation of D2D application is focused on V2X (that includes Vehicular to Vehicular, Vehicular to Infrastructure, Vehicular to Network, and Vehicular to Pedestrian) and aims to guarantee a safety application for comfort driving with high degree of quality and reliability (Table 1.2). In release 15, the D2D communication is extended to platooning (group of vehicles that operates like a train with virtual string attached between vehicles), extended sensors (that perform functions like exchanging live videos among nearby vehicles, road site units, pedestrian devices, and V2X application services), advance driving (enables semi or full automated driving), and remote driving.
In release 16, the focus is on the two iterations of the LTE-V2X, 3GPP system is adding advanced features primarily in the area of low latency use cases. It introduces a concept of “Side-link enhancements” for the D2D communication between devices, this is primarily used for the automotive use case as well as for critical communications. There is also a push toward using side-link for commercial use between smartphone directly. The 3GPP system in release 16 also focus on the development of a maritime communication system known as LTE-Maritime. The overall coverage area will be up to 100 km, and there will be seamless communication between the existing 3GPP system and the maritime radio communication system. It will also support voice communication and data communication between different vessels at sea [8,9]. This intervehicular communication can occur using D2D communication technology.
V2X communication capabilities are undergoing rapid development to enhance the experience of comfort and safe self-driving. 5G cellular communication system is evolving to provide support to V2X because of its higher data rate, low latency, reliability, global deployment, and broader coverage. 3GPP has specified V2X services in LTE-A network in release 14 and 15 and introduced a concept of enhanced V2X in release 16. Vehicles not only can communicate with each other through multiple wireless hops but also through V2I links. The V2I link can improve the communication stability and reduce the reaction time of the drivers. In order to ensure timely vehicular safety communications, higher data rate is required to achieve fast data exchanges that can significantly improve the interworking of V2V and V2I. V2X can also help in the detection of traffic congestion because of real time information, and it does not require any additional infrastructure or roadside equipment. However, V2X implementation is not as simple as it looks it can encounter different real time traffic scenarios that are caused by varying driving speeds, traffic patterns, and driving environment and poses greater challenges (Figure 1.1).
D2D communication in cellular spectrum enables direct communication between devices that are in close proximity, and it is an exciting and innovative feature for next generation of cellular networks (Figure 1.1). It can increase spectral and energy efficiency, provides high data rate, low latency, controlled interference, as well as offloads traffic from the base station and alleviate congestion [6,10] (Figure 1.2). It also provides higher control because of centralized management and allows D2D communication in a disciplined environment. D2D functionality was not implemented in the first four generations of mobile communication as this was only considered as a tool to reduce the cost of local services.
Moreover, D2D can play a critical role in areas where infrastructure is damaged by natural disasters, i.e. earthquake or hurricane. An urgent communication network can easily be set up in a very short time scale that can benefit PS services. Previously in emergency situation, ad hoc networks were created with the help of local devices that communicate with each other. Despite several benefits of ad hoc networks, it lacks connectivity to the existing communication network [4]. D2D users in emergency situations can act as relay and supports communication over a greater range hence increasing the overall coverage area of cellular network. D2D technology can also be very instrumental in disaster hit areas for issuing alerts and updates using local content distribution feature.
Figure 1.1 Device-to-device communication modes.
Figure 1.2 D2D communication overview.
1.4 Classification of D2D Communication
In terms of spectrum usage, D2D is primarily classified into two categories, in-band and out-band [6]. In in-band, D2D user shares the licensed spectrum band with the cellular user and managed by the serving base station. In-band D2D, can be an underlay (re-use model) where eNodeB shares radio resource between D2D and cellular user or overlay (fixed resource) where eNB allocates a fixed resource for D2D. In out-band, D2D user uses the unlicensed ISM frequency band for D2D and can either be controlled by eNB (network controlled) or by the D2D user them self (autonomous) [6,10]. The main advantage of out-band D2D is that it eliminates the interference problem linked to cellular user when using licensed band.
In-band D2D Communication
In in-band D2D communication, D2D user shares the cellular licensed spectrum used in either uplink (UL) or downlink (DL) communication [12]. This approach increases the spectral efficiency of the existing cellular network and is further divided into underlay (non-orthogonal) and overlay (orthogonal) modes (Figure 1.3).
Out-band D2D Communication
In out-band, D2D communication uses unlicensed ISM band where cellular communication does not occur (Figure 1.4). The biggest advantage is the elimination of interference between D2D and cellular users, although we still face interference from other devices that are operating in that band, for example, Bluetooth and Wi-Fi direct users. Out-band D2D is further categorized into controlled and autonomous mode, in controlled mode, the radio interface for D2D is controlled by the cellular network, while in autonomous mode, the D2D user control the link for D2D. In this scheme, resource allocation is much simpler as eNodeB is not considering exiting cellular RB, time, and location. Moreover, additional infrastructure enables a user to maintain both cellular and D2D connection at the same time, but this results in poor power consumption and leads to uncontrollable
