Optimal Deployment of Air Vehicle as Communication Relay for Multiple Ground Vehicles

Heterogeneous teams of both air and ground mobile vehicles can combine the advantages of mobility, sensing capability, and operation time when performing complex tasks. However, when ground vehicles operate in cluttered environments with randomized obstacles, they may experience line of sight (LoS) obstructions and loss of communication due to those obstacles. To mitigate this issue, an airborne relay can be positioned in the vicinity of the ground vehicles to aid communication by establishing two-hop communication links between the vehicles. This thesis develops an analytical framework to calculate the probability of spanning a two-hop communication between a pair of ground vehicles deployed in a task space with obstacles at random locations and with random heights (i.e., a Poisson Forest) using an airborne relay at any location near the ground vehicles. It allows to provide the main result, the optimization of the airborne relay\u27s location in scenarios involving multiple ground vehicles. By considering the locations and heights of the ground vehicles and the airborne relay, the distance-dependent critical height describing the required height of an obstacle to block the LoS is established. To account for the dependence on distance, the blocking is modeled as an inhomogeneous Poisson point process, and the LoS probability is its void probability. When pairwise communication links are considered, the throughput (metric depending on the LoS probability and channel capacity) is used to determine when to deploy the airborne relay, and, when the airborne relay is deployed, its optimal 3-D location. When multiple ground vehicles are considered, the throughput of the links and the layout of the communication network formed by the vehicles are used to compute the optimal positioning of the airborne relay, thus enhancing the overall throughput and connectivity of the network. The results are illustrated considering two obstacle height distributions: uniform and truncated Gaussian

Next-Generation Self-Organizing Networks through a Machine Learning Approach

Fecha de lectura de Tesis Doctoral: 17 Diciembre 2018.Para reducir los costes de gestión de las redes celulares, que, con el tiempo, aumentaban en complejidad, surgió el concepto de las redes autoorganizadas, o self-organizing networks (SON). Es decir, la automatización de las tareas de gestión de una red celular para disminuir los costes de infraestructura (CAPEX) y de operación (OPEX). Las tareas de las SON se dividen en tres categorías: autoconfiguración, autooptimización y autocuración. El objetivo de esta tesis es la mejora de las funciones SON a través del desarrollo y uso de herramientas de aprendizaje automático (machine learning, ML) para la gestión de la red. Por un lado, se aborda la autocuración a través de la propuesta de una novedosa herramienta para una diagnosis automática (RCA), consistente en la combinación de múltiples sistemas RCA independientes para el desarrollo de un sistema compuesto de RCA mejorado. A su vez, para aumentar la precisión de las herramientas de RCA mientras se reducen tanto el CAPEX como el OPEX, en esta tesis se proponen y evalúan herramientas de ML de reducción de dimensionalidad en combinación con herramientas de RCA. Por otro lado, en esta tesis se estudian las funcionalidades multienlace dentro de la autooptimización y se proponen técnicas para su gestión automática. En el campo de las comunicaciones mejoradas de banda ancha, se propone una herramienta para la gestión de portadoras radio, que permite la implementación de políticas del operador, mientras que, en el campo de las comunicaciones vehiculares de baja latencia, se propone un mecanismo multicamino para la redirección del tráfico a través de múltiples interfaces radio. Muchos de los métodos propuestos en esta tesis se han evaluado usando datos provenientes de redes celulares reales, lo que ha permitido demostrar su validez en entornos realistas, así como su capacidad para ser desplegados en redes móviles actuales y futuras

Multi-channel access solutions for 5G new radio

Abstract Multi-channel access is a family of multi-service radio resource management solutions that enable a user equipment to aggregate radio resources from multiple sources. The objective is multi-fold: throughput enhancement through access to a larger bandwidth tailored for enhanced mobile broadband, reliability improvement by increasing the diversity order and/or coordinated transmission/reception tailored for ultra-reliable low latency communication service classes, as well as flexibility and load balancing improvement by decoupling the downlink and the uplink access points, for both service classes. This paper presents several multi-channel access solutions for 5G New Radio multi-service scenarios. In particular, throughput enhancement and latency reduction concepts like multi-connectivity, carrier aggregation, downlink-uplink decoupled access and coordinated multi-point connectivity are discussed. Moreover, novel design solutions exploiting these concepts are proposed. Numerical evaluation of the introduced solutions indicates significant performance gains over state-of-the-art schemes; for example, our proposed component carrier selection mechanism leads to a median throughput gain of up to 100% by means of an implicit load balance. Therefore, the proposed multi-channel access solutions have the potential to be key multi-service enablers for 5G New Radio