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This Springerbreif introduces a threshold-based channel sparsification approach, and then, the sparsity is exploited for scalable channel training. Last but not least, this brief introduces two scalable cooperative signal detection algorithms in C-RANs. The authors wish to spur new research activities in the following important question: how to leverage the revolutionary architecture of C-RAN to attain unprecedented system capacity at an affordable cost and complexity. Cloud radio access network (C-RAN) is a novel mobile network architecture that has a lot of significance in future wireless networks like 5G. the high density of remote radio heads in C-RANs leads to severe scalability issues in terms of computational and implementation complexities. This Springerbrief undertakes a comprehensive study on scalable signal processing for C-RANs, where ‘scalable’ means that the computational and implementation complexities do not grow rapidly with the network size. This Springerbrief will be target researchers and professionals working in the Cloud Radio Access Network (C-Ran) field, as well as advanced-level students studying electrical engineering.
This unique text will enable readers to understand the fundamental theory, current techniques, and potential applications of Cloud Radio Access Networks (C-RANs). Leading experts from academia and industry provide a guide to all of the key elements of C-RANs, including system architecture, performance analysis, technologies in both physical and medium access control layers, self-organizing and green networking, standards development, and standardization perspectives. Recent developments in the field are covered, as well as open research challenges and possible future directions. The first book to focus exclusively on Cloud Radio Access Networks, this is essential reading for engineers in academia and industry working on future wireless networks.
This unique text helps make sense of big data using signal processing techniques, in applications including machine learning, networking, and energy systems.
This book examines signal processing techniques for cognitive radios. The book is divided into three parts: Part I, is an introduction to cognitive radios and presents a history of the cognitive radio (CR), and introduce their architecture, functionalities, ideal aspects, hardware platforms, and state-of-the-art developments. Dr. Jayaweera also introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Part II of the book, Theoretical Foundations, guides the reader from classical to modern theories on statistical signal processing and inference. The author addresses detection and estimation theory, power spectrum estimation, classification, adaptive algorithms (machine learning), and inference and decision processes. Applications to the signal processing, inference and learning problems encountered in cognitive radios are interspersed throughout with concrete and accessible examples. Part III of the book, Signal Processing in Radios, identifies the key signal processing, inference, and learning tasks to be performed by wideband autonomous cognitive radios. The author provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios.
Software defined radio (SDR) is a hot topic in the telecommunications field, with regard to wireless technology. It is one of the most important topics of research in the area of mobile and personal communications. SDR is viewed as the enabler of global roaming and a platform for the introduction of new technologies and services into existing live networks. It therefore gives networks a greater flexibility into mobile communications. It bridges the inter-disciplinary gap in the field as SDR covers two areas of development, namely software development and digital signal processing and the internet. It extends well beyond the simple re-configuration of air interface parameters to cover the whole system from the network to service creation and application development. Reconfigurability entails the pervasive use of software reconfiguration, empowering upgrades or patching of any element of the network and of the services and applications running on it. It cuts across the types of bearer radio systems (Paging to cellular, wireless local area network to microwave, terrestrial to satellite, personal communications to broadcasting) enable the integration of many of today's disparate systems in the same hardware platform. Also it cuts across generation (second to third to fourth). This volume complements the already published volumes 1 and 2 of the Wiley Series in Software Radio. The book discusses the requirements for reconfigurability and then introduces network architectures and functions for reconfigurable terminals. Finally it deals with reconfiguration in the network. The book also provides a comprehensive view on reconfigurability in three very active research projects as CAST, MOBIVAS and TRUST/SCOUT. Key features include: Presents new research in wireless communications Summarises the results of an extensive research program on software defined radios in Europe Provides a comprehensive view on reconfigurability in three very active research projects as CAST (Configurable radio with Advanced Sodftware Technology), MOBIVAS (Downloadable MOBIle Value Added Services through Software Radio and Switching Integrated Platforms), TRUST (Transparently Re-configurable Ubiquitous Terminal) and SCOUT (Smart User-Centric Communciation Environment).
Cloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes.
This book presents a synthesis of the research carried out in the Laboratory of Signal Processing and Communications (LaPSyC), CONICET, Universidad Nacional del Sur, Argentina, since 2003. It presents models and techniques widely used by the signal processing community, focusing on low-complexity methodologies that are scalable to different applications. It also highlights measures of the performance and impact of each compensation technique. The book is divided into three parts: 1) basic models 2) compensation techniques and 3) applications in advanced technologies. The first part addresses basic architectures of transceivers, their component blocks and modulation techniques. It also describes the performance to be taken into account, regardless of the distortions that need to be compensated. In the second part, several schemes of compensation and/or reduction of imperfections are explored, including linearization of power amplifiers, compensation of the characteristics of analog-to- digital converters and CFO compensation for OFDM modulation. The third and last part demonstrates the use of some of these techniques in modern wireless-communication systems, such as full-duplex transmission, massive MIMO schemes and Internet of Things applications.
This book, written by leading experts from academia and industry, offers a condensed overview on hot topics among the Cognitive Radios and Networks scientific and industrial communities (including those considered within the framework of the European COST Action IC0902) and presents exciting visions for the future. Examples of the subjects considered include the design of new filter bank-based air interfaces for spectrum sharing, medium access control design protocols, the design of cloud-based radio access networks, an evolutionary vision for the development and deployment of cognitive TCP/IP, and regulations relevant to the development of a spectrum sharing market. The concluding chapter comprises a practical, hands-on tutorial for those interested in developing their own research test beds. By focusing on the most recent advances and future avenues, this book will assist researchers in understanding the current issues and solutions in Cognitive Radios and Networks designs.
Finally, we propose a globally distributed synchronization algorithm for wireless sensor networks. In the proposed scheme, there is a master node that controls the network synchronization and the other sensors periodically broadcast synchronization pulses; they also monitor different frequency channels in an effort to overcome the effect of channel fading.