DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version

Improving next-generation wireless network performance and reliability with deep learning

A rudimentary question whether machine learning in general, or deep learning in particular, could add to the well-established field of wireless communications, which has been evolving for close to a century, is often raised. While the use of deep learning based methods is likely to help build intelligent wireless solutions, this use becomes particularly challenging for the lower layers in the wireless communication stack. The introduction of the fifth generation of wireless communications (5G) has triggered the demand for “network intelligence” to support its promises for very high data rates and extremely low latency. Consequently, 5G wireless operators are faced with the challenges of network complexity, diversification of services, and personalized user experience. Industry standards have created enablers (such as the network data analytics function), but these enablers focus on post-mortem analysis at higher stack layers and have a periodicity in the time scale of seconds (or larger). The goal of this dissertation is to show a solution for these challenges and how a data-driven approach using deep learning could add to the field of wireless communications. In particular, I propose intelligent predictive and prescriptive abilities to boost reliability and eliminate performance bottlenecks in 5G cellular networks and beyond, show contributions that justify the value of deep learning in wireless communications across several different layers, and offer in-depth analysis and comparisons with baselines and industry standards. First, to improve multi-antenna network reliability against wireless impairments with power control and interference coordination for both packetized voice and beamformed data bearers, I propose the use of a joint beamforming, power control, and interference coordination algorithm based on deep reinforcement learning. This algorithm uses a string of bits and logic operations to enable simultaneous actions to be performed by the reinforcement learning agent. Consequently, a joint reward function is also proposed. I compare the performance of my proposed algorithm with the brute force approach and show that similar performance is achievable but with faster run-time as the number of transmit antennas increases. Second, in enhancing the performance of coordinated multipoint, I propose the use of deep learning binary classification to learn a surrogate function to trigger a second transmission stream instead of depending on the popular signal to interference plus noise measurement quantity. This surrogate function improves the users' sum-rate through focusing on pre-logarithmic terms in the sum-rate formula, which have larger impact on this rate. Third, performance of band switching can be improved without the need for a full channel estimation. My proposal of using deep learning to classify the quality of two frequency bands prior to granting the band switching leads to a significant improvement in users' throughput. This is due to the elimination of the industry standard measurement gap requirement—a period of silence where no data is sent to the users so they could measure the frequency bands before switching. In this dissertation, a group of algorithms for wireless network performance and reliability for downlink are proposed. My results show that the introduction of user coordinates enhance the accuracy of the predictions made with deep learning. Also, the choice of signal to interference plus noise ratio as the optimization objective may not always be the best choice to improve user throughput rates. Further, exploiting the spatial correlation of channels in different frequency bands can improve certain network procedures without the need for perfect knowledge of the per-band channel state information. Hence, an understanding of these results help develop novel solutions to enhancing these wireless networks at a much smaller time scale compared to the industry standards todayElectrical and Computer Engineerin

Video Caching, Analytics and Delivery at the Wireless Edge: A Survey and Future Directions

Future wireless networks will provide high bandwidth, low-latency, and ultra-reliable Internet connectivity to meet the requirements of different applications, ranging from mobile broadband to the Internet of Things. To this aim, mobile edge caching, computing, and communication (edge-C3) have emerged to bring network resources (i.e., bandwidth, storage, and computing) closer to end users. Edge-C3 allows improving the network resource utilization as well as the quality of experience (QoE) of end users. Recently, several video-oriented mobile applications (e.g., live content sharing, gaming, and augmented reality) have leveraged edge-C3 in diverse scenarios involving video streaming in both the downlink and the uplink. Hence, a large number of recent works have studied the implications of video analysis and streaming through edge-C3. This article presents an in-depth survey on video edge-C3 challenges and state-of-the-art solutions in next-generation wireless and mobile networks. Specifically, it includes: a tutorial on video streaming in mobile networks (e.g., video encoding and adaptive bitrate streaming); an overview of mobile network architectures, enabling technologies, and applications for video edge-C3; video edge computing and analytics in uplink scenarios (e.g., architectures, analytics, and applications); and video edge caching, computing and communication methods in downlink scenarios (e.g., collaborative, popularity-based, and context-aware). A new taxonomy for video edge-C3 is proposed and the major contributions of recent studies are first highlighted and then systematically compared. Finally, several open problems and key challenges for future research are outlined

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&

Design of a Recommender System for Participatory Media Built on a Tetherless Communication Infrastructure

We address the challenge of providing low-cost, universal access of useful information to people in different parts of the globe. We achieve this by following two strategies. First, we focus on the delivery of information through computerized devices and prototype new methods for making that delivery possible in a secure, low-cost, and universal manner. Second, we focus on the use of participatory media, such as blogs, in the context of news related content, and develop methods to recommend useful information that will be of interest to users. To achieve the first goal, we have designed a low-cost wireless system for Internet access in rural areas, and a smartphone-based system for the opportunistic use of WiFi connectivity to reduce the cost of data transfer on multi-NIC mobile devices. Included is a methodology for secure communication using identity based cryptography. For the second goal of identifying useful information, we make use of sociological theories regarding social networks in mass-media to develop a model of how participatory media can offer users effective news-related information. We then use this model to design a recommender system for participatory media content that pushes useful information to people in a personalized fashion. Our algorithms provide an order of magnitude better performance in terms of recommendation accuracy than other state-of-the-art recommender systems. Our work provides some fundamental insights into the design of low-cost communication systems and the provision of useful messages to users in participatory media through a multi-disciplinary approach. The result is a framework that efficiently and effectively delivers information to people in remote corners of the world

Performance of management solutions and cooperation approaches for vehicular delay-tolerant networks

A wide range of daily-life applications supported by vehicular networks attracted the interest, not only from the research community, but also from governments and the automotive industry. For example, they can be used to enable services that assist drivers on the roads (e.g., road safety, traffic monitoring), to spread commercial and entertainment contents (e.g., publicity), or to enable communications on remote or rural regions where it is not possible to have a common network infrastructure. Nonetheless, the unique properties of vehicular networks raise several challenges that greatly impact the deployment of these networks. Most of the challenges faced by vehicular networks arise from the highly dynamic network topology, which leads to short and sporadic contact opportunities, disruption, variable node density, and intermittent connectivity. This situation makes data dissemination an interesting research topic within the vehicular networking area, which is addressed by this study. The work described along this thesis is motivated by the need to propose new solutions to deal with data dissemination problems in vehicular networking focusing on vehicular delay-tolerant networks (VDTNs). To guarantee the success of data dissemination in vehicular networks scenarios it is important to ensure that network nodes cooperate with each other. However, it is not possible to ensure a fully cooperative scenario. This situation makes vehicular networks suitable to the presence of selfish and misbehavior nodes, which may result in a significant decrease of the overall network performance. Thus, cooperative nodes may suffer from the overwhelming load of services from other nodes, which comprises their performance. Trying to solve some of these problems, this thesis presents several proposals and studies on the impact of cooperation, monitoring, and management strategies on the network performance of the VDTN architecture. The main goal of these proposals is to enhance the network performance. In particular, cooperation and management approaches are exploited to improve and optimize the use of network resources. It is demonstrated the performance gains attainable in a VDTN through both types of approaches, not only in terms of bundle delivery probability, but also in terms of wasted resources. The results and achievements observed on this research work are intended to contribute to the advance of the state-of-the-art on methods and strategies for overcome the challenges that arise from the unique characteristics and conceptual design of vehicular networks.O vasto número de aplicações e cenários suportados pelas redes veiculares faz com que estas atraiam o interesse não só da comunidade científica, mas também dos governos e da indústria automóvel. A título de exemplo, estas podem ser usadas para a implementação de serviços e aplicações que podem ajudar os condutores dos veículos a tomar decisões nas estradas, para a disseminação de conteúdos publicitários, ou ainda, para permitir que existam comunicações em zonas rurais ou remotas onde não é possível ter uma infraestrutura de rede convencional. Contudo, as propriedades únicas das redes veiculares fazem com que seja necessário ultrapassar um conjunto de desafios que têm grande impacto na sua aplicabilidade. A maioria dos desafios que as redes veiculares enfrentam advêm da grande mobilidade dos veículos e da topologia de rede que está em constante mutação. Esta situação faz com que este tipo de rede seja suscetível de disrupção, que as oportunidades de contacto sejam escassas e de curta duração, e que a ligação seja intermitente. Fruto destas adversidades, a disseminação dos dados torna-se um tópico de investigação bastante promissor na área das redes veiculares e por esta mesma razão é abordada neste trabalho de investigação. O trabalho descrito nesta tese é motivado pela necessidade de propor novas abordagens para lidar com os problemas inerentes à disseminação dos dados em ambientes veiculares. Para garantir o sucesso da disseminação dos dados em ambientes veiculares é importante que este tipo de redes garanta a cooperação entre os nós da rede. Contudo, neste tipo de ambientes não é possível garantir um cenário totalmente cooperativo. Este cenário faz com que as redes veiculares sejam suscetíveis à presença de nós não cooperativos que comprometem seriamente o desempenho global da rede. Por outro lado, os nós cooperativos podem ver o seu desempenho comprometido por causa da sobrecarga de serviços que poderão suportar. Para tentar resolver alguns destes problemas, esta tese apresenta várias propostas e estudos sobre o impacto de estratégias de cooperação, monitorização e gestão de rede no desempenho das redes veiculares com ligações intermitentes (Vehicular Delay-Tolerant Networks - VDTNs). O objetivo das propostas apresentadas nesta tese é melhorar o desempenho global da rede. Em particular, as estratégias de cooperação e gestão de rede são exploradas para melhorar e optimizar o uso dos recursos da rede. Ficou demonstrado que o uso deste tipo de estratégias e metodologias contribui para um aumento significativo do desempenho da rede, não só em termos de agregados de pacotes (“bundles”) entregues, mas também na diminuição do volume de recursos desperdiçados. Os resultados observados neste trabalho procuram contribuir para o avanço do estado da arte em métodos e estratégias que visam ultrapassar alguns dos desafios que advêm das propriedades e desenho conceptual das redes veiculares