Bandwidth Allocation and Service Differentiation in D2D Wireless Networks

International audienceInspired by a new feature in 5G NR called bandwidth part (BWP), this paper presents a bandwidth allocation (BA) model that allows one to adapt the bandwidth allocated to users depending on their data rate needs. Specifically, in adaptive BA, a wide bandwidth is divided into chunks of smaller bandwidths and the number of bandwidth chunks allocated to a user depends on its needs or type. Although BWP in 5G NR mandates allocation of a set of contiguous bandwidth chunks, our BA model also allows other assumptions on chunk allocation such as the allocation of any set of bandwidth chunks, as in, e.g., LTE resource allocation, where chunks are selected uniformly at random. The BA model studied here is probabilistic in that the user locations are assumed to form a realization of a Poisson point process and each user decides independently to be of a certain type with some probability. This model allows one to quantify spectrum sharing and service differentiation in this context, namely to predict what performance a user gets depending on its type as well as the overall performance. This is based on exact representations of key performance metrics for each user type, namely its success probability, the meta distribution of its signal-to-interference ratio, and its Shannon throughput. We show that, surprisingly, the higher traffic variability stemming from adaptive BA is beneficial: when comparing two networks using adaptive BA and having the same mean signal and the same mean interference powers, the network with higher traffic variability performs better for all these performance metrics. With respect to Shannon throughput, we observe that our BA model is roughly egalitarian per Hertz and leads to a linear service differentiation in aggregated throughput value

Trajectory optimization of autonomous vehicles considering radio access network constraints

The aim of this project is to combine the research work done so far on vehicle navigation and mobile data networks for vehicle-to-network applications. With this, autonomous vehicles would be able to choose a route from predefined starting and destination points, that assure to them the minimum data rate requirements across the route for the target level of autonomy in the driving. For this we propose two algorithms. The first one is an autonomous car-oriented algorithm that aims at maximizing the number of Autonomous Vehicles that can travel at the same time. The second one is an operator-oriented algorithm that allows the network to maintain as much as possible communication resources at the Base Stations that would be ready to use for other mobile services. A comparison between both algorithms is also presented in order to determine which algorithm would be a better fit for each use case of autonomous driving.El objetivo de este proyecto es combinar la investigación hecha hasta ahora en navegación de vehículos y la investigación en redes de datos móviles para aplicaciones vehicle-to-network. Con esto, los vehículos autónomos podrían escoger una ruta, a partir de un origen y un destino predefinidos, que les asegurase la mínima tasa de datos requerida para el nivel de autonomía de la conducción requerido. Para esto proponemos dos algoritmos. El primero es un algoritmo orientado al coche autónomo que pretende maximizar el número de coches autónomos que pueden viajar al mismo tiempo. El segundo es un algoritmo orientado al operador que permite a la red mantener en la medida de lo posible recursos de comunicaciones en las estaciones base que pueden ser usados por otros servicios móviles. Una comparación entre los dos algoritmos es presentada para determinar que algoritmo resulta mejor en cada caso específico de conducción autónoma.L'objectiu d'aquest projecte és combinar la recerca feta fins ara en navegació en vehicles i les xarxes de dades mòbils per a aplicacions vehicle-to-network. Amb això, els vehicles autònoms series capaços d'escollir una ruta a partir d'uns punts d'inici i fi predefinits que els assegurés la mínima velocitat de dades a través de tota la ruta per un nivell d'autonomia vehicular específic. Per això proposem dos algoritmes. El primer és un algoritme orientat al cotxe autònom que pretén maximitzar el número de vehicles autònoms que poden circular al mateix temps. El segon és un algoritme orientat a l'operador que permet a la xarxa mantenir, en la mesura del possible, recursos de comunicacions a les estacions base que podrien ser utilitzats per altres serveis mòbils. Una comparació entre els dos algoritmes també es presenta per tal de determinar quin algoritme és millor car a cada cas específic de conducció autònoma