Cellular and Wi-Fi technologies evolution: from complementarity to competition

This PhD thesis has the characteristic to span over a long time because while working on it, I was working as a research engineer at CTTC with highly demanding development duties. This has delayed the deposit more than I would have liked. On the other hand, this has given me the privilege of witnessing and studying how wireless technologies have been evolving over a decade from 4G to 5G and beyond. When I started my PhD thesis, IEEE and 3GPP were defining the two main wireless technologies at the time, Wi-Fi and LTE, for covering two substantially complementary market targets. Wi-Fi was designed to operate mostly indoor, in unlicensed spectrum, and was aimed to be a simple and cheap technology. Its primary technology for coexistence was based on the assumption that the spectrum on which it was operating was for free, and so it was designed with interference avoidance through the famous CSMA/CA protocol. On the other hand, 3GPP was designing technologies for licensed spectrum, a costly kind of spectrum. As a result, LTE was designed to take the best advantage of it while providing the best QoE in mainly outdoor scenarios. The PhD thesis starts in this context and evolves with these two technologies. In the first chapters, the thesis studies radio resource management solutions for standalone operation of Wi-Fi in unlicensed and LTE in licensed spectrum. We anticipated the now fundamental machine learning trend by working on machine learning-based radio resource management solutions to improve LTE and Wi-Fi operation in their respective spectrum. We pay particular attention to small cell deployments aimed at improving the spectrum efficiency in licensed spectrum, reproducing small range scenarios typical of Wi-Fi settings. IEEE and 3GPP followed evolving the technologies over the years: Wi-Fi has grown into a much more complex and sophisticated technology, incorporating the key features of cellular technologies, like HARQ, OFDMA, MU-MIMO, MAC scheduling and spatial reuse. On the other hand, since Release 13, cellular networks have also been designed for unlicensed spectrum. As a result, the two last chapters of this thesis focus on coexistence scenarios, in which LTE needs to be designed to coexist with Wi-Fi fairly, and NR, the radio access for 5G, with Wi-Fi in 5 GHz and WiGig in 60 GHz. Unlike LTE, which was adapted to operate in unlicensed spectrum, NR-U is natively designed with this feature, including its capability to operate in unlicensed in a complete standalone fashion, a fundamental new milestone for cellular. In this context, our focus of analysis changes. We consider that these two technological families are no longer targeting complementarity but are now competing, and we claim that this will be the trend for the years to come. To enable the research in these multi-RAT scenarios, another fundamental result of this PhD thesis, besides the scientific contributions, is the release of high fidelity models for LTE and NR and their coexistence with Wi-Fi and WiGig to the ns-3 open-source community. ns-3 is a popular open-source network simulator, with the characteristic to be multi-RAT and so naturally allows the evaluation of coexistence scenarios between different technologies. These models, for which I led the development, are by academic citations, the most used open-source simulation models for LTE and NR and havereceived fundings from industry (Ubiquisys, WFA, SpiderCloud, Interdigital, Facebook) and federal agencies (NIST, LLNL) over the years.Aquesta tesi doctoral té la característica d’allargar-se durant un llarg període de temps ja que mentre treballava en ella, treballava com a enginyera investigadora a CTTC amb tasques de desenvolupament molt exigents. Això ha endarrerit el dipositar-la més del que m’hagués agradat. D’altra banda, això m’ha donat el privilegi de ser testimoni i estudiar com han evolucionat les tecnologies sense fils durant més d’una dècada des del 4G fins al 5G i més enllà. Quan vaig començar la tesi doctoral, IEEE i 3GPP estaven definint les dues tecnologies sense fils principals en aquell moment, Wi-Fi i LTE, que cobreixen dos objectius de mercat substancialment complementaris. Wi-Fi va ser dissenyat per funcionar principalment en interiors, en espectre sense llicència, i pretenia ser una tecnologia senzilla i barata. La seva tecnologia primària per a la convivència es basava en el supòsit que l’espectre en el que estava operant era de franc, i, per tant, es va dissenyar simplement evitant interferències a través del famós protocol CSMA/CA. D’altra banda, 3GPP estava dissenyant tecnologies per a espectres amb llicència, un tipus d’espectre costós. Com a resultat, LTE està dissenyat per treure’n el màxim profit alhora que proporciona el millor QoE en escenaris principalment a l’aire lliure. La tesi doctoral comença amb aquest context i evoluciona amb aquestes dues tecnologies. En els primers capítols, estudiem solucions de gestió de recursos de radio per a operacions en espectre de Wi-Fi sense llicència i LTE amb llicència. Hem anticipat l’actual tendència fonamental d’aprenentatge automàtic treballant solucions de gestió de recursos de radio basades en l’aprenentatge automàtic per millorar l’LTE i Wi-Fi en el seu espectre respectiu. Prestem especial atenció als desplegaments de cèl·lules petites destinades a millorar la eficiència d’espectre llicenciat, reproduint escenaris de petit abast típics de la configuració Wi-Fi. IEEE i 3GPP van seguir evolucionant les tecnologies al llarg dels anys: El Wi-Fi s’ha convertit en una tecnologia molt més complexa i sofisticada, incorporant les característiques clau de les tecnologies cel·lulars, com ara HARQ i la reutilització espacial. D’altra banda, des de la versió 13, també s’han dissenyat xarxes cel·lulars per a espectre sense llicència. Com a resultat, els dos darrers capítols d’aquesta tesi es centren en aquests escenaris de convivència, on s’ha de dissenyar LTE per conviure amb la Wi-Fi de manera justa, i NR, l’accés a la radio per a 5G amb Wi-Fi a 5 GHz i WiGig a 60 GHz. A diferència de LTE, que es va adaptar per funcionar en espectre sense llicència, NR-U està dissenyat de forma nativa amb aquesta característica, inclosa la seva capacitat per operar sense llicència de forma autònoma completa, una nova fita fonamental per al mòbil. En aquest context, el nostre focus d’anàlisi canvia. Considerem que aquestes dues famílies de tecnologia ja no estan orientades cap a la complementarietat, sinó que ara competeixen, i afirmem que aquesta serà el tendència per als propers anys. Per permetre la investigació en aquests escenaris multi-RAT, un altre resultat fonamental d’aquesta tesi doctoral, a més de les aportacions científiques, és l’alliberament de models d’alta fidelitat per a LTE i NR i la seva coexistència amb Wi-Fi a la comunitat de codi obert ns-3. ns-3 és un popular simulador de xarxa de codi obert, amb la característica de ser multi-RAT i, per tant, permet l’avaluació de manera natural d’escenaris de convivència entre diferents tecnologies. Aquests models, pels quals he liderat el desenvolupament, són per cites acadèmiques, els models de simulació de codi obert més utilitzats per a LTE i NR i que han rebut finançament de la indústria (Ubiquisys, WFA, SpiderCloud, Interdigital, Facebook) i agències federals (NIST, LLNL) al llarg dels anys.Esta tesis doctoral tiene la característica de extenderse durante mucho tiempo porque mientras trabajaba en ella, trabajaba como ingeniera de investigación en CTTC con tareas de desarrollo muy exigentes. Esto ha retrasado el depósito más de lo que me hubiera gustado. Por otro lado, gracias a ello, he tenido el privilegio de presenciar y estudiar como las tecnologías inalámbricas han evolucionado durante una década, de 4G a 5G y más allá. Cuando comencé mi tesis doctoral, IEEE y 3GPP estaban definiendo las dos principales tecnologías inalámbricas en ese momento, Wi-Fi y LTE, cumpliendo dos objetivos de mercado sustancialmente complementarios. Wi-Fi fue diseñado para funcionar principalmente en interiores, en un espectro sin licencia, y estaba destinado a ser una tecnología simple y barata. Su tecnología primaria para la convivencia se basaba en el supuesto en que el espectro en el que estaba operando era gratis, y así fue diseñado simplemente evitando interferencias a través del famoso protocolo CSMA/CA. Por otro lado, 3GPP estaba diseñando tecnologías para espectro con licencia, un tipo de espectro costoso. Como resultado, LTE está diseñado para aprovechar el espectro al máximo proporcionando al mismo tiempo el mejor QoE en escenarios principalmente al aire libre. La tesis doctoral parte de este contexto y evoluciona con estas dos tecnologías. En los primeros capítulos, estudiamos las soluciones de gestión de recursos de radio para operación en espectro Wi-Fi sin licencia y LTE con licencia. Anticipamos la tendencia ahora fundamental de aprendizaje automático trabajando en soluciones de gestión de recursos de radio para mejorar LTE y funcionamiento deWi-Fi en su respectivo espectro. Prestamos especial atención a las implementaciones de células pequeñas destinadas a mejorar la eficiencia de espectro licenciado, reproduciendo los típicos escenarios de rango pequeño de la configuración Wi-Fi. IEEE y 3GPP siguieron evolucionando las tecnologías a lo largo de los años: Wi-Fi se ha convertido en una tecnología mucho más compleja y sofisticada, incorporando las características clave de las tecnologías celulares, como HARQ, OFDMA, MU-MIMO, MAC scheduling y la reutilización espacial. Por otro lado, desde la Release 13, también se han diseñado redes celulares para espectro sin licencia. Como resultado, los dos últimos capítulos de esta tesis se centran en estos escenarios de convivencia, donde LTE debe diseñarse para coexistir con Wi-Fi de manera justa, y NR, el acceso por radio para 5G con Wi-Fi en 5 GHz y WiGig en 60 GHz. A diferencia de LTE, que se adaptó para operar en espectro sin licencia, NR-U está diseñado de forma nativa con esta función, incluyendo su capacidad para operar sin licencia de forma completamente independiente, un nuevo hito fundamental para los celulares. En este contexto, cambia nuestro enfoque de análisis. Consideramos que estas dos familias tecnológicas ya no tienen como objetivo la complementariedad, sino que ahora están compitiendo, y afirmamos que esta será la tendencia para los próximos años. Para permitir la investigación en estos escenarios de múltiples RAT, otro resultado fundamental de esta tesis doctoral, además de los aportes científicos, es el lanzamiento de modelos de alta fidelidad para LTE y NR y su coexistencia con Wi-Fi y WiGig a la comunidad de código abierto de ns-3. ns-3 es un simulador popular de red de código abierto, con la característica de ser multi-RAT y así, naturalmente, permite la evaluación de escenarios de convivencia entre diferentes tecnologías. Estos modelos, para los cuales lideré el desarrollo, son por citas académicas, los modelos de simulación de código abierto más utilizados para LTE y NR y han recibido fondos de la industria (Ubiquisys, WFA, SpiderCloud, Interdigital, Facebook) y agencias federales (NIST, LLNL) a lo largo de los años.Postprint (published version

Reliable Decision-Making with Imprecise Models

The rapid growth in the deployment of autonomous systems across various sectors has generated considerable interest in how these systems can operate reliably in large, stochastic, and unstructured environments. Despite recent advances in artificial intelligence and machine learning, it is challenging to assure that autonomous systems will operate reliably in the open world. One of the causes of unreliable behavior is the impreciseness of the model used for decision-making. Due to the practical challenges in data collection and precise model specification, autonomous systems often operate based on models that do not represent all the details in the environment. Even if the system has access to a comprehensive decision-making model that accounts for all the details in the environment and all possible scenarios the agent may encounter, it may be intractable to solve this complex model optimally. Consequently, this complex, high fidelity model may be simplified to accelerate planning, introducing imprecision. Reasoning with such imprecise models affects the reliability of autonomous systems. A system\u27s actions may sometimes produce unexpected, undesirable consequences, which are often identified after deployment. How can we design autonomous systems that can operate reliably in the presence of uncertainty and model imprecision? This dissertation presents solutions to address three classes of model imprecision in a Markov decision process, along with an analysis of the conditions under which bounded-performance can be guaranteed. First, an adaptive outcome selection approach is introduced to devise risk-aware reduced models of the environment that efficiently balance the trade-off between model simplicity and fidelity, to accelerate planning in resource-constrained settings. Second, a framework that extends stochastic shortest path framework to problems with imperfect information about the goal state during planning is introduced, along with two solution approaches to solve this problem. Finally, two complementary solution approaches are presented to minimize the negative side effects of agent actions. The techniques presented in this dissertation enable an autonomous system to detect and mitigate undesirable behavior, without redesigning the model entirely

A Cyber-War Between Bots: Human-Like Attackers are More Challenging for Defenders than Deterministic Attackers

Adversary emulation is commonly used to test cyber defense performance against known threats to organizations. However, designing attack strategies is an expensive and unreliable manual process, based on subjective evaluation of the state of a network. In this paper, we propose the design of adversarial human-like cognitive models that are dynamic, adaptable, and have the ability to learn from experience. A cognitive model is built according to the theoretical principles of Instance-Based Learning Theory (IBLT) of experiential choice in dynamic tasks. In a simulation experiment, we compared the predictions of an IBL attacker with a carefully designed efficient but deterministic attacker attempting to access an operational server in a network. The results suggest that an IBL cognitive model that emulates human behavior can be a more challenging adversary for defenders than the carefully crafted optimal attack strategies. These insights can be used to inform future adversary emulation efforts and cyber defender training

Overview on Agent-Based Social Modelling and the Use of Formal Languages

The use of agent-based modelling and simulation techniques in the social sciences has flourished in the recent decades. The main reason is that the object of study in these disciplines, human society present or past, is difficult to analyse through classical analytical techniques. Population dynamics and structures are inherently complex. Thus, other methodological techniques need to be found to more adequately study this field. In this context, agent-based modelling is encouraging the introduction of computer simulations to examine behavioural patterns in complex systems. Simulation provides a tool to artificially examine societies where a big number of actors with decision capacity coexist and interact. However, formal modelling in these areas has not traditionally been used compared to other fields of science, in particular in their use of formal languages during the modelling process. In this chapter, the authors aim to revise the most relevant aspects on modelling in social sciences and to discuss the use formal languages by social scientists

Innate heuristics and fast learning support escape route selection in mice

When faced with imminent danger, animals must rapidly take defensive actions to reach safety. Mice can react to threatening stimuli in ∼250 milliseconds and, in simple environments, use spatial memory to quickly escape to shelter. Natural habitats, however, often offer multiple routes to safety that animals must identify and choose from. This is challenging because although rodents can learn to navigate complex mazes, learning the value of different routes through trial and error during escape could be deadly. Here, we investigated how mice learn to choose between different escape routes. Using environments with paths to shelter of varying length and geometry, we find that mice prefer options that minimize path distance and angle relative to the shelter. This strategy is already present during the first threat encounter and after only ∼10 minutes of exploration in a novel environment, indicating that route selection does not require experience of escaping. Instead, an innate heuristic assigns survival value to each path after rapidly learning the spatial environment. This route selection process is flexible and allows quick adaptation to arenas with dynamic geometries. Computational modeling shows that model-based reinforcement learning agents replicate the observed behavior in environments where the shelter location is rewarding during exploration. These results show that mice combine fast spatial learning with innate heuristics to choose escape routes with the highest survival value. The results further suggest that integrating prior knowledge acquired through evolution with knowledge learned from experience supports adaptation to changing environments and minimizes the need for trial and error when the errors are costly

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Smart Sustainable Mobility: Analytics and Algorithms for Next-Generation Mobility Systems

To this date, mobility ecosystems around the world operate on an uncoordinated, inefficient and unsustainable basis. Yet, many technology-enabled solutions that have the potential to remedy these societal negatives are already at our disposal or just around the corner. Innovations in vehicle technology, IoT devices, mobile connectivity and AI-powered information systems are expected to bring about a mobility system that is connected, autonomous, shared and electric (CASE). In order to fully leverage the sustainability opportunities afforded by CASE, system-level coordination and management approaches are needed. This Thesis sets out an agenda for Information Systems research to shape the future of CASE mobility through data, analytics and algorithms (Chapter 1). Drawing on causal inference, (spatial) machine learning, mathematical programming and reinforcement learning, three concrete contributions toward this agenda are developed. Chapter 2 demonstrates the potential of pervasive and inexpensive sensor technology for policy analysis. Connected sensing devices have significantly reduced the cost and complexity of acquiring high-resolution, high-frequency data in the physical world. This affords researchers the opportunity to track temporal and spatial patterns of offline phenomena. Drawing on a case from the bikesharing sector, we demonstrate how geo-tagged IoT data streams can be used for tracing out highly localized causal effects of large-scale mobility policy interventions while offering actionable insights for policy makers and practitioners. Chapter 3 sets out a solution approach to a novel decision problem faced by operators of shared mobility fleets: allocating vehicle inventory optimally across a network when competition is present. The proposed three-stage model combines real-time data analytics, machine learning and mixed integer non-linear programming into an integrated framework. It provides operational decision support for fleet managers in contested shared mobility markets by generating optimal vehicle re-positioning schedules in real time. Chapter 4 proposes a method for leveraging data-driven digital twin (DT) frameworks for large multi-stage stochastic design problems. Such problem classes are notoriously difficult to solve with traditional stochastic optimization. Drawing on the case of Electric Vehicle Charging Hubs (EVCHs), we show how high-fidelity, data-driven DT simulation environments fused with reinforcement learning (DT-RL) can achieve (close-to) arbitrary scalability and high modeling flexibility. In benchmark experiments we demonstrate that DT-RL-derived designs result in superior cost and service-level performance under real-world operating conditions