Systems with Massive Number of Antennas: Distributed Approaches

As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.The radio access network (RAN) has already gone through an evolution on the path towards 5G. One of the main changes was a large increment of the number of antennas in the base-station. Some of them may even reach 100 elements, in what is commonly referred as Massive MIMO. New proposals for 6G RAN point in the direction of continuing this path of increasing the number of antennas, and locate them throughout a certain area of service. Different technologies have been proposed in this direction, such as: cell-free Massive MIMO, distributed MIMO, and large intelligent surface (LIS). In this thesis we focus on LIS, whose conducted theoretical studies promise the fulfillment of the aforementioned requirements.While the theoretical capabilities of LIS have been conveniently analyzed, little has been done in terms of implementing this type of systems. When the number of antennas grow to hundreds or thousands, there are numerous challenges that need to be solved for a successful implementation. The most critical challenges are the interconnection data-rate and the computational complexity.In the present thesis we introduce the implementation challenges, and show that centralized processing architectures are no longer adequate for this type of systems. We also present different distributed processing architectures and show the benefits of this type of schemes. This work aims at giving a system-design guideline that helps the system designer to make the right decisions when designing these type of systems. For that, we provide algorithms, performance analysis and comparisons, including first order evaluation of the interconnection data-rate, processing latency, memory and energy consumption. These numbers are based on models and available data in the literature. Exact values depend on the selected technology, and will be accurately determined after building and testing these type of systems.The thesis concentrates mostly on the topic of communication, with additional exploration of other areas, such as localization. In case of localization, we benefit from the high spatial resolution of a very-large array that provides very rich channel state information (CSI). A CSI-based fingerprinting via neural network technique is selected for this case with promising results. As the communication and localization services are based on the acquisition of CSI, we foresee a common system architecture capable of supporting both cases. Further work in this direction is recommended, with the possibility of including other applications such as sensing.The obtained results indicate that the implementation of these very-large array systems is feasible, but the challenges are numerous. The proposed solutions provide encouraging results that need to be verified with hardware implementations and real measurements

Evolution Toward 5G Mobile Networks - A Survey on Enabling Technologies

In this paper, an extensive review has been carried out on the trends of existing as well as proposed potential enabling technologies that are expected to shape the fifth generation (5G) mobile wireless networks. Based on the classification of the trends, we develop a 5G network architectural evolution framework that comprises three evolutionary directions, namely, (1) radio access network node and performance enabler, (2) network control programming platform, and (3) backhaul network platform and synchronization. In (1), we discuss node classification including low power nodes in emerging machine-type communications, and network capacity enablers, e.g., millimeter wave communications and massive multiple-input multiple-output. In (2), both logically distributed cell/device-centric platforms, and logically centralized conventional/wireless software defined networking control programming approaches are discussed. In (3), backhaul networks and network synchronization are discussed. A comparative analysis for each direction as well as future evolutionary directions and challenges toward 5G networks are discussed. This survey will be helpful for further research exploitations and network operators for a smooth evolution of their existing networks toward 5G networks

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed

Utilization of cloud RAN architecture with eCPRI fronthaul in 5G network

With increased reliability, massive network capacity, and extremely reduced latency, 5G expands the mobile ecosystem into new realms. 5G impacts every industry and innovation, making transportation and conveyance safer, remote healthcare, accuracy agriculture, digitized logistics, and much more. In this age, 5G calls for new levels of flexibility and broadness in architecting, scaling, and deploying telecommunication networks, which need a further step ahead in technology and enter Cloud Technology. Cloud technology provides fascinating possibilities to complement the existing tried and tested technologies in the Radio Access Network (RAN) domain. Cloud RAN (CRAN) refers to relying on RAN functions over an inclusive platform instead of a purpose-built hardware platform. It represents a progression in wireless communication technology, leveraging the Common public radio interface (CPRI) standard, Dense Wavelength Division Multiplexing (DWDM) innovation, and millimeter wave (mmWave) propagation for extended-range signals. A CRAN network comprises of three fundamental elements. The initial element is the Distant Wireless Unit (DRU) or Remote Radio Component (RRH), utilized within a network to link wireless devices to entry points; these units are equipped with transceivers for transmitting and receiving signals. Next, a Baseband Unit (BBU) centre or hub serves as a centralized site functioning as a data processing hub. Separate BBU modules can be assembled independently or interconnected to distribute resources, adapting to the network's changing dynamics and needs. Communication among these modules boasts remarkably high bandwidth and exceptionally low latency. The BBU can be further segmented into DU (Distributed Unit) and CU (Centralized Unit). The third crucial component is a fronthaul or conveyance network – the connecting layer between a baseband unit (BBU) and a set of RRUs, utilizing optical fibres, cellular links, or mmWave communication. The goal of this thesis is to find a way to utilize the 5G RAN Architecture as efficiently as possible and for this purpose, Enhanced Common Public Radio Interface (eCPRI) or enhanced CPRI fronthaul is adopted instead of CPRI as it is a manner of splitting up the functions performed by baseband unit and putting some of that in the RRU so it can reduce the burden on the fibre. Enhanced CPRI makes it possible to send some data packets to a virtual Distributed Unit (vDU) and others to a virtual Centralized Unit (vCU) which results in reduced data traffic on fibre. The first part of this research paper focuses on considering and learning about the 5G Cloud RAN architecture's main components, some cloud RAN history, and important components included in the 5G Cloud RAN. In the second part, research goes in depth about the fronthaul gateway technology that is eCPRI structure, its functional split, its difference from CPRI in structure and functionality, and how it is enhanced and developed. Considering CRAN specifications, it will also include some eCPRI protocol delay management and timing studies. Finally, Test cases are developed that can authenticate the low latency and high throughput of data with eCPRI fronthaul in 5G Cloud RAN as compared to CPRI fronthaul. The inspiration behind this is to recreate the model with substantial changes that work with an ideal behaviour of a subsystem, with this a tool or an environment can be obtained that maximizes the efficiency of 5G CRAN. It will also permit network architects and designers to experiment with new features, which can reduce costs, save time, improve latency. It can also provide a tool to verification engineers that will help them to generate optimal replies of the system necessary for evaluating the practical realization of that system

Study, Measurements and Characterisation of a 5G system using a Mobile Network Operator Testbed

The goals for 5G are aggressive. It promises to deliver enhanced end-user experience by offering new applications and services through gigabit speeds, and significantly improved performance and reliability. The enhanced mobile broadband (eMBB) 5G use case, for instance, targets peak data rates as high as 20 Gbps in the downlink (DL) and 10 Gbps in the uplink (UL). While there are different ways to improve data rates, spectrum is at the core of enabling higher mobile broadband data rates. 5G New Radio (NR) specifies new frequency bands below 6 GHz and also extends into mmWave frequencies where more contiguous bandwidth is available for sending lots of data. However, at mmWave frequencies, signals are more susceptible to impairments. Hence, extra consideration is needed to determine test approaches that provide the precision required to accurately evaluate 5G components and devices. Therefore, the aim of the thesis is to provide a deep dive into 5G technology, explore its testing and validation, and thereafter present the OTE (Hellenic Telecommunications Organisation) 5G testbed, including measurement results obtained and its characterisation based on key performance indicators (KPIs)

The edge cloud: A holistic view of communication, computation and caching

The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth generation (5G) communication networks. This ambitious goal requires a paradigm shift towards a vision that looks at communication, computation and caching (3C) resources as three components of a single holistic system. The further step is to bring these 3C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing: Principles and Applications", P. Djuric and C. Richard Eds., Academic Press, Elsevier, 201