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- Mobility sensing and V2X communication for emergency servicesPublication . Figueiredo, Andreia; Rito, Pedro; Luís, Miguel; Sargento, SusanaThe warning of traveling emergency response vehicles (ERVs) is performed through the help of both sound and lights when the ERV is approaching. This is not an ideal situation for, at least, two reasons: the information is received only when the ERV is very close to other vehicles; and the other vehicles cannot understand where exactly the ERV is, and which action is the best according to its location and direction. With the help of ehicular communications, this paper proposes a diferent approach for an ERV to be autonomously and preemptively detected. Based on the collected data through vehicle com munication and sensors, primarily through cooperative Awareness Messages (CAMs) and Radio Detection And Ranging (RADAR) data, a prediction of the ERV future location is performed in real-time, and warning messages are disseminated to vehicles just before the ERV arrival. Real-world evaluation tests, considering diferent warning dissemination scenarios, show that the warning messages lost during the process is signifcantly reduced from almost 80% down to 22%, especially when infrastructure-to-vehicle and vehicle-to-vehicle communications are used together. Moreover, 80% of the total warning messages are delivered in less than 100 ms
- Improving mmWave backhaul reliability: a machine-learning based approachPublication . Ferreira, Tânia; Figueiredo, Alexandre; Raposo, Duarte; Luís, Miguel; Rito, Pedro; Sargento, SusanaWiGig technologies, such as IEEE 802.11ad and later IEEE 802.11ay, provide multi-gigabit short-range communication at 60 GHz for bandwidth-intensive applications. However, this band suffers from high propagation losses that can only be compensated using highly directional antennas, making millimeter-wave (mmWave) links susceptible to blockage and errors. This high sensitivity to blockage leads to unstable and unreliable connections, since proprietary IEEE 802.11ad mechanisms, such as beamforming training, have high overhead, and can only be triggered when performance degradation is already detected, which compromises QoS and QoE even more.This article proposes a proactive machine learning framework that uses real-life data acquired in an outdoor setting to improve the reliability and resilience of a blockage-prone WiGig-based network. In particular, we propose a link quality classifier, which can differentiate between normal, long-term blockage and short-term operation with a test F1-score of 97%. Moreover, we introduce a novel deep learning forecasting model that can accurately capture the interactions between past multi-layer observations under different environments to produce accurate forecasts for 16 KPIs.
- On the performance of 5G for cloud- and edge-based emergency services in smart citiesPublication . Perna, Gonçalo; Rosmaninho, Rodrigo; Sampaio, Hugo; Rito, Pedro; Luís, Miguel; Sargento, SusanaThe deployment of emergency services in a city scenario, such as the ones for users’ safety in the roads, require the support of fast network technologies and efficient network architectures. Moreover, these services need to be available city-wide, so a flexible approach is needed to deploy high-speed technology to the overall city.This paper addresses the performance of 5G technology and its architecture to deploy emergency services with strict requirements, when compared to the use of fiber throughout the city. It considers the location of demanding services, in this specific case the people detection in the road through video cameras, both in the edge and the cloud, and with both fiber and real 5G connection between the edge and the cloud. We evaluate this architecture in a real scenario with real users and vehicles in the area. The obtained results show that 5G with an edge-based approach can provide similar services to fiber-based connections to the cloud.
- On the real experimentation and simulation models for millimeter-wavePublication . Figueiredo, Alexandre; Ferreira, Tânia; Raposo, Duarte; Luís, Miguel; Rito, Pedro; Sargento, SusanaThe emergence of millimeter-wave based technologies is pushing the deployment of the 5th generation of mobile communications (5G), on the potential to achieve multi-gigabit and low-latency wireless links. Part of this breakthrough was only possible with the introduction of small antenna arrays, capable to form highly directional and electronically steerable beams. This strategy allowed the overcoming of some drawbacks, but with a higher price: the re-design of the lower layers by introducing beamforming techniques. The impact of these changes is not well studied on the higher layers, in the most recent stacks (IEEE 802.11ad, 3GPP). Thus, the study of real deployments and the use of accurate network simulators play a key role, by enabling the test of complex large-scale scenarios. This article presents a key component missing in the simulation of mmWave networks, a blockage model. To the best of our knowledge, this is first blockage model that emulates the effects of obstacles in the mmWave links. Additionally, a codebook generation of a phased antenna array, with the Quasi-Deterministic (Q-D) channel model is also presented. All models are tested and compared with an outdoor mmWave network using the IEEE 802.11ad standard. The simulated and the real-life tests show similar results, with an average error for the worst case of 2.43% (index ranges) and 4.51% (distance), and to an average standard deviation of about 1.33 dBm and 2.26 dBm.