Beyond Massive MIMO : Trade-offs and Opportunities with Large Multi-Antenna Systems

After the commercial emergence of 5G, the research community is already putting its focus on proposing innovative solutions to enable the upcoming 6G. One important lesson put forth by 5G research was that scaling up the conventional multiple-input-multiple-output (MIMO) technology by increasing the number of antennas could be extremely beneficial for effectively multiplexing data streams in the spatial domain. This idea was embodied in massive MIMO, which constitutes one of the major technical advancements included in 5G. Consequently, 6G research efforts have been largely directed towards studying ways to further scale up wireless systems, as can be seen in some of the proposed 6G enabling technologies like large intelligent surface (LIS), cell-free massive MIMO, or even reconfigurable intelligent surface (RIS). This thesis studies the possibilities offered by some of these technologies, as well as the trade-offs that may naturally arise when scaling up such wireless systems.An important part of this thesis deals with decentralized solutions for base station (BS) technologies including a large number of antennas. Already in the initial massive MIMO prototypes, the increased number of BS antennas led to scalability issues due to the high interconnection bandwidths required to send the received signals---as well as the channel state information (CSI)---to a central processing unit (CPU) in charge of the data processing. These issues can only be exacerbated if we consider novel system proposals like LIS, where the number of BS antennas may be increased by an order of magnitude with respect to massive MIMO, or cell-free massive MIMO, where the BS antennas may be located far from each other. We provide a number of decentralized schemes to process the received data while restricting the information that has to be shared with a CPU. We also provide a framework to study architectures with an arbitrary level of decentralization, showing that there exists a direct trade-off between the interconnection bandwidth to a CPU and the complexity of the decentralized processing required for fixed user rates.Another part of this thesis studies RIS-based solutions to enhance the multiplexing performance of wireless communication systems. RIS constitutes one of the most attractive 6G enabling technologies since it provides a cost- and energy-efficient solution to improve the wireless propagation links by generating favorable reflections. We extend the concept of RIS by considering reconfigurable surfaces (RSs) with different processing capabilities, and we show how these surfaces may be employed for achieving perfect spatial multiplexing at reduced processing complexity in general multi-antenna communication settings. We also show that these surfaces can exploit the available degrees of freedom---e.g., due to excess of BS antennas---to embed their own data into the enhanced channel

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

6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap

The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to have a proper insight into the vision and requirements of 6G. Second, we provide a panoramic view of the enabling technologies proposed to facilitate 6G and introduce emerging 6G applications such as multi-sensory–extended reality, digital replica, and more. Next, the technology-driven challenges, social, psychological, health and commercialization issues posed to actualizing 6G, and the probable solutions to tackle these challenges are discussed extensively. Additionally, we present new use cases of the 6G technology in agriculture, education, media and entertainment, logistics and transportation, and tourism. Furthermore, we discuss the multi-faceted communication capabilities of 6G that will contribute significantly to global sustainability and how 6G will bring about a dramatic change in the business arena. Finally, we highlight the research trends, open research issues, and key take-away lessons for future research exploration in 6G wireless communicatio

Distributed Filter Design and Power Allocation for Small-CellMIMO Networks

The deluge of wireless data traffic catalyzed by the growing number of data-intensive deviceshas motivated the deployment of small-cell in fifth-generation (5G) networks. A primary challengefor deploying dense small-cell networks comes from the lack of practical techniques that efficientlyhandle the increased network interference at a low cost. This has aroused considerable interest inthe distributed precoder/combiner coordination techniques that leverage the channel reciprocity,while relying on the local channel state information (CSI) available at each communication end. Inthis thesis, a distributed approach is proposed to the problem of signal-to-interference-plus-noise-ratio (SINR)-guaranteed power minimization (SGPM) for multicell multiuser (MCMU) multiple-input multiple-output (MIMO) systems. Unlike prior SGPM approaches, the proposed techniqueis based on solving necessary and sufficient optimality conditions, which are derived by decom-posing the original problem into forward and backward (FB) subproblems, while ensuring thestrong duality of each subproblem. The proposed distributed SGPM algorithm makes use of FBadaptation and Jacobi recursion for iterative filter design and power allocation, respectively. Asufficient condition for the feasibility of the proposed distributed algorithm is analyzed, based onthe application of the matrix inverse-positive theory. Unlike the existing fully distributed FB filterupdate algorithms, the proposed approach guarantees target SINR performance as well as its convergence to a stationary point. Simulation results illustrate the enhanced power efficiency with theperformance guarantees of the proposed method compared to the existing distributed techniques

Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios

Radiocommunication networks are one of the main support tools of agencies that carry out actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these communications technologies from narrowband to broadband and integrated to information technologies to have an effective action before society. Understanding that this problem includes, besides the technical aspects, issues related to the social context to which these systems are inserted, this study aims to construct scenarios, using several sources of information, that helps the managers of the PPDR agencies in the technological decisionmaking process of the Digital Transformation of Mission-Critical Communication considering Smart City scenarios, guided by the methods and approaches of Technological Assessment (TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários, utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de Avaliação Tecnológica (TA)