Diffraction at TOTEM

The TOTEM experiment at the LHC measures the total proton-proton cross section with the luminosity-independent method and the elastic proton-proton cross-section over a wide |t|-range. It also performs a comprehensive study of diffraction, spanning from cross-section measurements of individual diffractive processes to the analysis of their event topologies. Hard diffraction will be studied in collaboration with CMS taking advantage of the large common rapidity coverage for charged and neutral particle detection and the large variety of trigger possibilities even at large luminosities. TOTEM will take data under all LHC beam conditions including standard high luminosity runs to maximize its physics reach. This contribution describes the main features of the TOTEM physics programme including measurements to be made in the early LHC runs. In addition, a novel scheme to extend the diffractive proton acceptance for high luminosity runs by installing proton detectors at IP3 is described.Comment: 10 pages, 9 figures, contribution to the proceedings of the HERA and the LHC workshop 2007-0

The TOTEM Experiment at the CERN Large Hadron Collider

The TOTEM Experiment will measure the total pp cross-section with the luminosity independent method and study elastic and diffractive scattering at the LHC. To achieve optimum forward coverage for charged particles emitted by the pp collisions in the interaction point IP5, two tracking telescopes, T1 and T2, will be installed on each side in the pseudorapidity region 3,1 <h< 6,5, and Roman Pot stations will be placed at distances of 147m and 220m from IP5. Being an independent experiment but technically integrated into CMS, TOTEM will first operate in standalone mode to pursue its own physics programme and at a later stage together with CMS for a common physics programme. This article gives a description of the TOTEM apparatus and its performance

Multi-RAT LPWAN in Smart Cities: Trial of LoRaWAN and NB-IoT Integration

The landscape of the contemporary IoT radio access technologies (RATs) is excessively diverse, especially when it comes to such a complex environment as Smart City. On the one hand, this diversity offers operators sufficient flexibility to select the most appropriate RAT for their target application. On the other hand, it becomes a severe limiting factor leading to high level of uncertainty for the IoT device vendors, who need to decide, which technology to support in their hardware. In this paper, we consider the provisioning of the low-power wide area network (LPWAN) devices supporting multiple RATs. First, we briefly discuss the parameters of several potential radio technologies as well as analyze the pros and cons of combining them in a single device. Next, we prototype a real-life device capable of communicating via two perspective LPWAN technologies, namely, LoRaWAN and NB-IoT, and report on the initial results of its performance evaluation. These confirm the feasibility of instrumenting dual-mode devices as well as reveal several important aspects related to the development of multi-radio IoT equipment and its performance. In our view, due to their higher flexibility, reliability, and dependability, the devices such as the one developed can be beneficial for various Smart City applications, with smart energy grids and road traffic control being only two of many examples. © 2018 IEEE

Multi-RAT LPWAN in Smart Cities: Trial of LoRaWAN and NB-IoT Integration

The landscape of the contemporary IoT radio access technologies (RATs) is excessively diverse, especially when it comes to such a complex environment as Smart City. On the one hand, this diversity offers operators sufficient flexibility to select the most appropriate RAT for their target application. On the other hand, it becomes a severe limiting factor leading to high level of uncertainty for the IoT device vendors, who need to decide, which technology to support in their hardware. In this paper, we consider the provisioning of the low-power wide area network (LPWAN) devices supporting multiple RATs. First, we briefly discuss the parameters of several potential radio technologies as well as analyze the pros and cons of combining them in a single device. Next, we prototype a real-life device capable of communicating via two perspective LPWAN technologies, namely, LoRaWAN and NB-IoT, and report on the initial results of its performance evaluation. These confirm the feasibility of instrumenting dual-mode devices as well as reveal several important aspects related to the development of multi-radio IoT equipment and its performance. In our view, due to their higher flexibility, reliability, and dependability, the devices such as the one developed can be beneficial for various Smart City applications, with smart energy grids and road traffic control being only two of many examples. © 2018 IEEE

Automated estimation of link quality for Lora: A remote sensing approach

Many research and industrial communities are betting on LoRa to provide reliable, long-range communication for the Internet of Things. This new radio technology, however, provides widely heterogeneous coverage; a LoRa link may span hundreds of meters or tens of kilometers, depending on the surrounding environment. This high variability is not captured by popular channel models for LoRa, and on-site measurementsÐa common alternativeÐare impractical due to the large geographical areas involved. We propose a novel, automated approach to estimate the coverage of LoRa gateways prior to deployment and without on-site measurements. We achieve this goal by combining free, readily-available multispectral images from remote sensing with the right channel model. Our processing toolchain automatically classifies the type of environment (e.g., buildings, trees, or open fields) traversed by a link, with high accuracy (&gt;90%) and spatial resolution (10×10m2). We use this information to explain the attenuation observed in experiments. As signal attenuation is not well captured by popular channel models, we focus on the Okumura-Hata empirical model, hitherto largely unexplored for LoRa, and show that i) it yields estimates very close to our observations, and ii) we can use our toolchain to automatically select and configure its parameters. A validation on 8,000+ samples from a real dataset shows that our automated approach predicts the expected signal power within a ∼10dBm error, against the 20ś40dBm of popular channel models.Embedded and Networked System

Automated estimation of link quality for Lora: A remote sensing approach

Many research and industrial communities are betting on LoRa to provide reliable, long-range communication for the Internet of Things. This new radio technology, however, provides widely heterogeneous coverage; a LoRa link may span hundreds of meters or tens of kilometers, depending on the surrounding environment. This high variability is not captured by popular channel models for LoRa, and on-site measurementsÐa common alternativeÐare impractical due to the large geographical areas involved. We propose a novel, automated approach to estimate the coverage of LoRa gateways prior to deployment and without on-site measurements. We achieve this goal by combining free, readily-available multispectral images from remote sensing with the right channel model. Our processing toolchain automatically classifies the type of environment (e.g., buildings, trees, or open fields) traversed by a link, with high accuracy (&gt;90%) and spatial resolution (10×10m2). We use this information to explain the attenuation observed in experiments. As signal attenuation is not well captured by popular channel models, we focus on the Okumura-Hata empirical model, hitherto largely unexplored for LoRa, and show that i) it yields estimates very close to our observations, and ii) we can use our toolchain to automatically select and configure its parameters. A validation on 8,000+ samples from a real dataset shows that our automated approach predicts the expected signal power within a ∼10dBm error, against the 20ś40dBm of popular channel models.</p