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Método para determinar información de tipo geométrico en dispositivos de redes en la banda de ondas milimétricas [METHOD FOR DETERMINING GEOMETRIC INFORMATION OF MMWAVE NETWORK DEVICES]
No full textPatent Application 27 March 2019.
Application number (OEPM): ES P201830297 (27.03.2018)
Filing Date: 27 March 2018.A method for determining geometric information of mmWave network devices comprising collecting measures, by at least one of the devices, of signal strength and SNR of a transmission received from another device of the mmWave network; estimating angle information of the received signals to generate a set of informed particles comprising initial values of state of each informed particle and input in a modified particle filter; the modified particle filter evolving the sets of informed particles and past particles to obtain a set of evolved particles which, in turn, is evolved to obtain a set of posterior particles delivered by the modified particle filter. Finally, the modified particle filter delivers as output final values of geometric information of the at least one device extracted from the delivered set of posterior particles.
US Patent Application. Application number: 16/365,953 (27.03.2019)IMDEA Networks, Madrid, Spainpu
Scaling Millimeter-Wave Networks to Dense Deployments and Dynamic Environments
Get PDFMillimeter wave (mmWave) communications have emerged as one of the most promising options to vastly increase wireless data rates due to the high bandwidth they offer. Given the high path loss at mmWave frequencies, such systems require directional antennas to achieve a good communication range. The communicating devices thus need to align the beam directions of their mmWave antennas. Due to the high penetration loss, the paths between the antennas also need to be free of blocking obstacles. This makes efficient and reliable operation of mmWave networks in dynamic environments very challenging. At the same time, the directionality reduces interference and allows to scale these networks to much higher access point and device densities. In this article, we discuss the above challenges and present techniques that allow mmWave networks to scale to high-density deployments, to adapt to dynamic and mobile environments, and to consistently achieve high data rates. This includes learning the environment to find different propagation paths, reacting timely to channel impairments such as blockage, and integrating mmWave networks with networks operating at lower-frequency for robustness. A key ingredient to enable these forms of adaptivity is the use of location information. Such mechanisms then turn a collection of very-high-speed but brittle mmWave links into an efficient, low-latency, and reliable network.pu
Experimental QoE evaluation of multicast video delivery over IEEE 802.11aa WLANs
Get PDFThe IEEE 802.11aa amendment standardised the Group Addressed Transmission Service (GATS), which extends 802.11 WLANs with a novel set of MAC mechanisms to support an effective and efficient multicast video service. The key challenge with GATS is the selection of the best scheme and its configuration for a given network scenario, as the standard does not provide any guidelines nor any assessment of the performance of each mechanism. Although some previous studies have addressed this challenge, their evaluation is either via analysis or simulations under non-realistic assumptions, or based on Quality of Service (QoS) metrics instead of video quality metrics, which are required for a proper video performance assessment. In this paper, we deploy a mid-size real-life testbed and develop a thoughtful methodology to perform an extensive Quality of Experience (QoE) evaluation of GATS under a variety of scenarios. We analyse the performance of the novel schemes under ideal conditions, as well as under controlled and non-controlled interference, assessing their ability to provide an adequate QoE and quantifying the resources left for other type of traffic. Ours is the first thorough QoE evaluation of GATS in a real-life scenario, providing key insights on their performance, and can be used to derive configuration guidelines for the schemes.pu
Higher than a kite: ADS-B communication analysis using a high-altitude balloon
Get PDFReceiving signals on the 1090 MHz frequency, one of the most important radio frequencies used in aviation, is typically done using ground-based receivers. However, an increasing number of airborne or even space-based receivers also aim to receive these signals for applications such as air traffic surveillance and collision avoidance. In this paper, we present our results from a high-altitude radio frequency measurement campaign with the goal to gain insights about the challenges and limitations of receiving 1090 MHz signals at high altitudes. We used a high-altitude balloon equipped with a software-defined radio to collect 1090 MHz signal data. In an extensive analysis of these data, we identify several challenges and provide a first impression of the radio environment at altitudes up to 33.5 km.TRUEpu
Challenges in Designing Future High Speed Wireless Networks
No full texthttps://www.humboldt-foundation.de/web/dates-humboldt-colloquia.htmlTRUEpu
ASUNA: A Topology Dataset for Underwater Network Emulation
Get PDFWe report the details of ASUNA, a freely shared dataset for underwater network emulation (ASUNA). ASUNA tackles the time-consuming and costly logistics of multiple underwater networking sea trials by providing a benchmark database of time-varying network topologies recorded across multiple sea experiments, thus facilitating experiment replay and network emulation. The ASUNA database currently includes 20 diverse, time-varying topology structures, multimodal communication technologies, and different link quality measurements. With the aim of becoming a standard benchmark, ASUNA is open to extensions as new data becomes available from the underwater communications community. We provide the details of ASUNA structure, the list of recorded topologies, as well as examples of how to use the database as part of an emulation system to test the performance of two scheduling protocols. We freely share the database and the emulation code both through a web server and via the Code Ocean repository.pu
Do You Get What You Pay For? Comparing the Privacy Behaviors of Free vs. Paid Apps
Get PDFIt is commonly assumed that the availability of “free” mobile apps comes at the cost of consumer privacy, and that paying for apps could offer consumers protection from
behavioral advertising and long-term tracking. This work empirically evaluates the validity of this assumption by investigating the degree to which “free” apps and their paid premium versions differ in their bundled code, their declared permissions, and their
data collection behaviors and privacy practices.
We compare pairs of free and paid apps using a combination of static and dynamic analysis. We also examine the differences in the privacy policies within pairs. We rely on static analysis to determine the requested permissions and third-party SDKs in each app; we use dynamic analysis to detect sensitive data collected by remote services at the network traffic level; and we compare text versions of privacy policies to identify differences in
the disclosure of data collection behaviors. In total, we analyzed 1,505 pairs of free Android apps and their paid counterparts, with free apps randomly drawn from the Google Play Store’s category-level top charts.
Our results show that over our corpus of free and paid pairs, there is no clear evidence that paying for an app will guarantee protection from extensive data collection. Specifically, 48% of the paid versions reused all of the same third-party libraries as their free versions, while 56% of the paid versions inherited all of the free versions’ Android permissions to access sensitive device resources (when considering free apps that include at least one third-party library and request at least one Android permission).
Additionally, our dynamic analysis reveals that 38% of the paid apps exhibit all of the same data collection and transmission behaviors as their free counterparts. Our exploration of privacy policies reveals that only 45% of the pairs provide a privacy
policy of some sort, and less than 1% of the pairs overall have policies that differ between free and paid versions.TRUEpu
Mobile Small Cells for Adaptive RAN Densification: Preliminary Throughput Results
Get PDFIn this paper, we study the capacity (i.e., the maximum achievable throughput) of radio access networks that exploit mobile small cell base stations carried by vehicles for adaptive densification in urban areas. While traditional approaches for radio access network densification with fixed small cell base stations are proving ineffective and extremely costly,
mobile small cell base stations carried by vehicles can provide adaptive densification while achieving higher efficiency and lower cost. As a matter of fact, the existence of correlations between the number of mobile network subscribers and the number of vehicles in a given area allows for the spontaneous creation of temporary dense small cell deployments where and when needed. Ultimately, this approach to Radio Access Network densification increases efficiency, hence reducing costs for the operator. In this context, we first present an approach for the computation of the maximum throughput that can be obtained in an area served by traditional fixed base stations and mobile small cell base stations. We then provide initial estimates for the throughput improvements with respect to traditional deployments that rely on fixed base stations only. Evaluations in the realistic case study of the main railway station area in Milan, Italy, reveal that the use of mobile base stations achieves throughout gains up to 120%
over legacy fixed access infrastructures, while granting higher fairness among subscribers.TRUEpu
