Interference Mitigation Methods for Unmanned Aerial Vehicles Served by Cellular Networks

A main challenge in providing connectivity to the low altitude unmanned aerial vehicles (UAVs) through existing cellular network arises due to the increased interference in the network. The increased altitude and favourable propagation condition cause UAVs to generate more interference to the neighbouring cells, and at the same time experience more interference from the downlink transmissions of the neighbouring base stations. The uplink interference problem may result in terrestrial UEs having degraded performance, whereas the downlink interference problem may make it challenging for a UAV to maintain connection with the network. In this paper, we propose several uplink and downlink interference mitigation techniques to address these issues. The results indicate that the proposed solutions can reduce the uplink throughput degradation of terrestrial UEs and ensure UAVs to remain in LTE coverage under the worst case scenarios when all the base stations transmit at full power.Comment: Submitted to IEEE 5G Word Forum 201

Rogue Drone Detection: A Machine Learning Approach

The emerging, practical and observed issue of how to detect rogue drones that carry terrestrial user equipment (UEs) on mobile networks is addressed in this paper. This issue has drawn much attention since the rogue drones may generate excessive interference to mobile networks and may not be allowed by regulations in some regions. In this paper, we propose a novel machine learning approach to identify the rogue drones in mobile networks based on radio measurements. We apply two classification machine learning models, Logistic Regression, and Decision Tree, using features from radio measurements to identify the rogue drones. We find that for high altitudes the proposed machine learning solutions can yield high rogue drone detection rate while not mis-classifying regular ground based UEs as rogue drone UEs. The detection accuracy however degrades at low altitudes.Comment: Submitted to Globecom 201

Simulação ao nível de sistema de comunicações por drone

A rede de acesso rádio de quinta geração, 5G NR, permite o acesso a uma vasta diversidade de novos serviços sobre a rede móvel, através da sua capacidade de fornecer aos clientes maiores ritmos binários, fiabilidade, eficiência espetral e uma latência reduzida. Os Unmanned Aerial Vehicles (UAVs), têm recebido grande atenção devido à sua mobilidade, capacidade de transporte, velocidade e adaptabilidade, o que poderá permitir o surgimento de novas ofertas no mercado. Uma das principais dificuldades impostas para a sua introdução são os requisitos necessários para o controlo do veículo, uma vez que deve ser garantida a segurança da missão, especialmente em missões para além da linha de vista. A reutilização das infraestruturas de rede móvel poderá ser uma solução, através da sua elevada capacidade de cobertura e pelo surgimento das redes de nova geração, que poderão finalmente dar resposta às exigências impostas no controlo de UAVs, especialmente em termos de fiabilidade e ritmos binários. Foi desenvolvido um simulador de nível de sistema que pretende analisar a performance de uma rede de acesso rádio 5G NR, em termos de throughput e de cobertura, quando esta, para além de servir os UEs terrestres convencionais, tem de servir os novos UEs aéreos, possibilitando o estudo do impacto da incorporação de UAVs nas redes móveis convencionais, nos cenários Rural Macro with Aerial Vehicle (RMa-AV), Urban Macro with Aerial Vehicle (UMa-AV) e Urban Micro with Aerial Vehicle (UMi-AV), utilizando-se a técnica de transmissão Massive Multi-Input Multi-Output (mMIMO) e uma técnica de clustering de TRPs.The fifth generation of the new radio access network, 5G NR, allows access to a vast diversity of new services through the mobile network, through their capacity to provide clients with higher data rates, reliability, spectral efficiency, and reduced latency. Unmanned Aerial Vehicles (UAVs) have been receiving large attention due to their mobility, capacity of transport, speed, and adaptability, which may allow the emergence of new offers to the market. One of the main difficulties imposed for their launch is the necessary requirements on the control of the vehicle, since it must be guaranteed the security of the mission, especially during beyond-line-of-sight missions. The reuse of the mobile network infrastructures may be one solution, through its high coverage capacity and the emergence of new mobile network generations, this could finally meet the demands imposed on the control of an UAV, especially in terms of reliability and data rate. It was developed a system-level simulator that intends to analyze the performance of a 5G NR radio access network, in terms of throughput and coverage, which, in addition to serving the conventional terrestrials users, it will also serve the new aerial users, enabling the study of the impact of the incorporation of UAVs into the conventional mobile networks, in the scenarios Rural Macro with Aerial Vehicle (RMa-AV), Urban Macro with Aerial Vehicle (UMa-AV) and Urban Micro with Aerial Vehicle (UMi-AV), using the transmission technique Massive Multi-Input Multi-Output (mMIMO) and a TRPs clustering technique