Ubiquitous Cell-Free Massive MIMO Communications

Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users, and hence, increases the spectral and energy efficiency. It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and Networking on August 5, 201

Improved planning and resource management in next generation green mobile communication networks

In upcoming years, mobile communication networks will experience a disruptive reinventing process through the deployment of post 5th Generation (5G) mobile networks. Profound impacts are expected on network planning processes, maintenance and operations, on mobile services, subscribers with major changes in their data consumption and generation behaviours, as well as on devices itself, with a myriad of different equipment communicating over such networks. Post 5G will be characterized by a profound transformation of several aspects: processes, technology, economic, social, but also environmental aspects, with energy efficiency and carbon neutrality playing an important role. It will represent a network of networks: where different types of access networks will coexist, an increasing diversity of devices of different nature, massive cloud computing utilization and subscribers with unprecedented data-consuming behaviours. All at greater throughput and quality of service, as unseen in previous generations. The present research work uses 5G new radio (NR) latest release as baseline for developing the research activities, with future networks post 5G NR in focus. Two approaches were followed: i) method re-engineering, to propose new mechanisms and overcome existing or predictably existing limitations and ii) concept design and innovation, to propose and present innovative methods or mechanisms to enhance and improve the design, planning, operation, maintenance and optimization of 5G networks. Four main research areas were addressed, focusing on optimization and enhancement of 5G NR future networks, the usage of edge virtualized functions, subscriber’s behavior towards the generation of data and a carbon sequestering model aiming to achieve carbon neutrality. Several contributions have been made and demonstrated, either through models of methodologies that will, on each of the research areas, provide significant improvements and enhancements from the planning phase to the operational phase, always focusing on optimizing resource management. All the contributions are retro compatible with 5G NR and can also be applied to what starts being foreseen as future mobile networks. From the subscriber’s perspective and the ultimate goal of providing the best quality of experience possible, still considering the mobile network operator’s (MNO) perspective, the different proposed or developed approaches resulted in optimization methods for the numerous problems identified throughout the work. Overall, all of such contributed individually but aggregately as a whole to improve and enhance globally future mobile networks. Therefore, an answer to the main question was provided: how to further optimize a next-generation network - developed with optimization in mind - making it even more efficient while, simultaneously, becoming neutral concerning carbon emissions. The developed model for MNOs which aimed to achieve carbon neutrality through CO2 sequestration together with the subscriber’s behaviour model - topics still not deeply focused nowadays – are two of the main contributions of this thesis and of utmost importance for post-5G networks.Nos próximos anos espera-se que as redes de comunicações móveis se reinventem para lá da 5ª Geração (5G), com impactos profundos ao nível da forma como são planeadas, mantidas e operacionalizadas, ao nível do comportamento dos subscritores de serviços móveis, e através de uma miríade de dispositivos a comunicar através das mesmas. Estas redes serão profundamente transformadoras em termos tecnológicos, económicos, sociais, mas também ambientais, sendo a eficiência energética e a neutralidade carbónica aspetos que sofrem uma profunda melhoria. Paradoxalmente, numa rede em que coexistirão diferentes tipos de redes de acesso, mais dispositivos, utilização massiva de sistema de computação em nuvem, e subscritores com comportamentos de consumo de serviços inéditos nas gerações anteriores. O trabalho desenvolvido utiliza como base a release mais recente das redes 5G NR (New Radio), sendo o principal focus as redes pós-5G. Foi adotada uma abordagem de "reengenharia de métodos” (com o objetivo de propor mecanismos para resolver limitações existentes ou previsíveis) e de “inovação e design de conceitos”, em que são apresentadas técnicas e metodologias inovadoras, com o principal objetivo de contribuir para um desenho e operação otimizadas desta geração de redes celulares. Quatro grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: melhorias e otimização generalizada de redes pós-5G, a utilização de virtualização de funções de rede, a análise comportamental dos subscritores no respeitante à geração e consumo de tráfego e finalmente, um modelo de sequestro de carbono com o objetivo de compensar as emissões produzidas por esse tipo de redes que se prevê ser massiva, almejando atingir a neutralidade carbónica. Como resultado deste trabalho, foram feitas e demonstradas várias contribuições, através de modelos ou metodologias, representando em cada área de investigação melhorias e otimizações, que, todas contribuindo para o mesmo objetivo, tiveram em consideração a retro compatibilidade e aplicabilidade ao que se prevê que sejam as futuras redes pós 5G. Focando sempre na perspetiva do subscritor da melhor experiência possível, mas também no lado do operador de serviço móvel – que pretende otimizar as suas redes, reduzir custos e maximizar o nível de qualidade de serviço prestado - as diferentes abordagens que foram desenvolvidas ou propostas, tiveram como resultado a resolução ou otimização dos diferentes problemas identificados, contribuindo de forma agregada para a melhoria do sistema no seu todo, respondendo à questão principal de como otimizar ainda mais uma rede desenvolvida para ser extremamente eficiente, tornando-a, simultaneamente, neutra em termos de emissões de carbono. Das principais contribuições deste trabalho relevam-se precisamente o modelo de compensação das emissões de CO2, com vista à neutralidade carbónica e um modelo de análise comportamental dos subscritores, dois temas ainda pouco explorados e extremamente importantes em contexto de redes futuras pós-5G

The Coverage, Capacity and Coexistence of Mixed High Altitude Platform and Terrestrial Segments

This thesis explores the coverage, capacity and coexistence of High Altitude Platform (HAP) and terrestrial segments in the same service area. Given the limited spectrum available, mechanisms to manage the co-channel interference to enable effective coexistence between the two infrastructures are examined. Interference arising from the HAP, caused by the relatively high transmit power and the antenna beam profile, has the potential to significantly affect the existing terrestrial system on the ground if the HAP beams are deployed without a proper strategy. Beam-pointing strategies exploiting phased array antennas on the HAPs are shown to be an effective way to place the beams, with each of them forming service cells onto the ground in the service area, especially dense user areas. Using a newly developed RF clustering technique to better point the cells over an area of a dense group of users, it is shown that near maximum coverage of 96% of the population over the service area can be provided while maintaining the coexistence with the existing terrestrial system. To improve the user experience at the cell edge, while at the same time improving the overall capacity of the system, Joint Transmission – Coordinated Multipoint (JT-CoMP) is adapted for a HAP architecture. It is shown how the HAP can potentially enable the tight scheduling needed to perform JT-CoMP due to the centralisation of all virtual E-UTRAN Node Bs (eNodeBs) on the HAP. A trade-off between CINR gain and loss of capacity when adapting JT-CoMP into the HAP system is identified, and strategies to minimise the trade-off are considered. It is shown that 57% of the users benefit from the JT-CoMP. In order to enable coordination between the HAP and terrestrial segments, a joint architecture based on a Cloud – Radio Access Network (C-RAN) system is introduced. Apart from adapting a C-RAN based system to centrally connect the two segments together, the network functional split which varies the degree of the centralised processing is also considered to deal with the limitations of HAP fronthaul link requirements. Based on the fronthaul link requirements acquired from the different splitting options, the ground relay station diversity to connect the HAP to centralised and distributed units (CUs and DUs) is also considered

Joint User‑Centric Clustering and Multi‑cell Radio Resource Management in Coordinated Multipoint Joint Transmission

Coordinated multipoint joint transmission (JT-CoMP) is a promising solution to address inter-cell interference in dense future wireless networks due its strength in converting interfering signals into useful signals, thereby enhancing capacity especially at the cell edge. However, allowing all user equipments (UEs) to operate using the JT-CoMP mode reduces the availability of radio resources. This paper develops an efficient algorithm that can identify which UEs will benefit from operating in a JT-CoMP mode and how to efficiently allocate radio resources from multiple base stations. Joint user-centric JT-CoMP clustering and multi-cell resource management is used in two steps where user-centric clusters are constructed as a first step and according to the clustering results obtained, resources are assigned. This paper also provides a new user-centric clustering approach that allows a user to utilize the JT-CoMP technique only if JT-CoMP boosts its rate above a certain threshold level. A multi-cell resource allocation scheme that can address the resource mismatching problem between cooperative BSs that happens due to load imbalance is proposed. Simulation results show that the proposed user-centric clustering algorithm outperforms the traditional power level difference scheme in terms of the system’s overall throughput as well as the throughput of cell-edge users. Also, results show that the performance of JT-CoMP is mainly affected by the user-centric approach and the amount of physical radio resources assigned to CoMP UEs

NOVEL USER-CENTRIC ARCHITECTURES FOR FUTURE GENERATION CELLULAR NETWORKS: DESIGN, ANALYSIS AND PERFORMANCE OPTIMIZATION

Ambitious targets for aggregate throughput, energy efficiency (EE) and ubiquitous user experience are propelling the advent of ultra-dense networks. Inter-cell interference and high energy consumption in an ultra-dense network are the prime hindering factors in pursuit of these goals. To address this challenge, we investigate the idea of transforming network design from being base station-centric to user-centric. To this end, we develop mathematical framework and analyze multiple variants of the user-centric networks, with the help of advanced scientific tools such as stochastic geometry, game theory, optimization theory and deep neural networks. We first present a user-centric radio access network (RAN) design and then propose novel base station association mechanisms by forming virtual dedicated cells around users scheduled for downlink. The design question that arises is what should the ideal size of the dedicated regions around scheduled users be? To answer this question, we follow a stochastic geometry based approach to quantify the area spectral efficiency (ASE) and energy efficiency (EE) of a user-centric Cloud RAN architecture. Observing that the two efficiency metrics have conflicting optimal user-centric cell sizes, we propose a game theoretic self-organizing network (GT-SON) framework that can orchestrate the network between ASE and EE focused operational modes in real-time in response to changes in network conditions and the operator's revenue model, to achieve a Pareto optimal solution. The designed model is shown to outperform base-station centric design in terms of both ASE and EE in dense deployment scenarios. Taking this user-centric approach as a baseline, we improve the ASE and EE performance by introducing flexibility in the dimensions of the user-centric regions as a function of data requirement for each device. So instead of optimizing the network-wide ASE or EE, each user device competes for a user-centric region based on its data requirements. This competition is modeled via an evolutionary game and a Vickrey-Clarke-Groves auction. The data requirement based flexibility in the user-centric RAN architecture not only improves the ASE and EE, but also reduces the scheduling wait time per user. Offloading dense user hotspots to low range mmWave cells promises to meet the enhance mobile broadband requirement of 5G and beyond. To investigate how the three key enablers; i.e. user-centric virtual cell design, ultra-dense deployments and mmWave communication; are integrated in a multi-tier Stienen geometry based user-centric architecture. Taking into account the characteristics of mmWave propagation channel such as blockage and fading, we develop a statistical framework for deriving the coverage probability of an arbitrary user equipment scheduled within the proposed architecture. A key advantage observed through this architecture is significant reduction in the scheduling latency as compared to the baseline user-centric model. Furthermore, the interplay between certain system design parameters was found to orchestrate the ASE-EE tradeoff within the proposed network design. We extend this work by framing a stochastic optimization problem over the design parameters for a Pareto optimal ASE-EE tradeoff with random placements of mobile users, macro base stations and mmWave cells within the network. To solve this optimization problem, we follow a deep learning approach to estimate optimal design parameters in real-time complexity. Our results show that if the deep learning model is trained with sufficient data and tuned appropriately, it yields near-optimal performance while eliminating the issue of long processing times needed for system-wide optimization. The contributions of this dissertation have the potential to cause a paradigm shift from the reactive cell-centric network design to an agile user-centric design that enables real-time optimization capabilities, ubiquitous user experience, higher system capacity and improved network-wide energy efficiency

Self-organised multi-objective network clustering for coordinated communications in future wireless networks

The fifth generation (5G) cellular system is being developed with a vision of 1000 times more capacity than the fourth generation (4G) systems to cope with ever increasing mobile data traffic. Interference mitigation plays an important role in improving the much needed overall capacity especially in highly interference-limited dense deployment scenarios envisioned for 5G. Coordinated multi-point (CoMP) is identified as a promising interference mitigation technique where multiple base stations (BS) can cooperate for joint transmission/reception by exchanging user/control data and perform joint signal processing to mitigate inter-cell interference and even exploit it as a useful signal. CoMP is already a key feature of long term evolution-advanced (LTE-A) and envisioned as an essential function for 5G. However, CoMP cannot be realized for the whole network due to its computational complexity, synchronization requirement between coordinating BSs and high backhaul capacity requirement. BSs need to be clustered into smaller groups and CoMP can be activated within these smaller clusters. This PhD thesis aims to investigate optimum dynamic CoMP clustering solutions in 5G and beyond wireless networks with massive small cell (SC) deployment. Truly self-organised CoMP clustering algorithms are investigated, aiming to improve much needed spectral efficiency and other network objectives especially load balancing in future wireless networks. Low complexity, scalable, stable and efficient CoMP clustering algorithms are designed to jointly optimize spectral efficiency, load balancing and limited backhaul availability. Firstly, we provide a self organizing, load aware, user-centric CoMP clustering algorithm in a control and data plane separation architecture (CDSA) proposed for 5G to maximize spectral efficiency and improve load balancing. We introduce a novel re-clustering algorithm for user equipment (UE) served by highly loaded cells and show that unsatisfied UEs due to high load can be significantly reduced with minimal impact on spectral efficiency. Clustering with load balancing algorithm exploits the capacity gain from increase in cluster size and also the traffic shift from highly loaded cells to lightly loaded neighbours. Secondly, we develop a novel, low complexity, stable, network-centric clustering model to jointly optimize load balancing and spectral efficiency objectives and tackle the complexity and scalability issues of user-centric clustering. We show that our clustering model provide high spectral efficiency in low-load scenario and better load distribution in high-load scenario resulting in lower number of unsatisfied users while keeping spectral efficiency at comparably high levels. Unsatisfied UEs due to high load are reduced by $68.5\%$ with our algorithm when compared to greedy clustering model. In this context, the unique contribution of this work that it is the first attempt to fill the gap in literature for multi-objective, network-centric CoMP clustering, jointly optimizing load balancing and spectral efficiency. Thirdly, we design a novel multi-objective CoMP clustering algorithm to include backhaul-load awareness and tackle one of the biggest challenges for the realization of CoMP in future networks i.e. the demand for high backhaul bandwidth and very low latency. We fill the gap in literature as the first attempt to design a clustering algorithm to jointly optimize backhaul/radio access load and spectral efficiency and analyze the trade-off between them. We employ 2 novel coalitional game theoretic clustering methods, 1-a novel merge/split/transfer coalitional game theoretic clustering algorithm to form backhaul and load aware BS clusters where spectral efficiency is still kept at high level, 2-a novel user transfer game model to move users between clusters to improve load balancing further. Stability and complexity analysis is provided and simulation results are presented to show the performance of the proposed method under different backhaul availability scenarios. We show that average system throughout is increased by 49.9% with our backhaul-load aware model in high load scenario when compared to a greedy model. Finally, we provide an operator's perspective on deployment of CoMP. Firstly, we present the main motivation and benefits of CoMP from an operator's viewpoint. Next, we present operational requirements for CoMP implementation and discuss practical considerations and challenges of such deployment. Possible solutions for these experienced challenges are reviewed. We then present initial results from a UL CoMP trial and discuss changes in key network performance indicators (KPI) during the trial. Additionally, we propose further improvements to the trialed CoMP scheme for better potential gains and give our perspective on how CoMP will fit into the future wireless networks