Variable link performance due to weather effects in a long-range, low-power LoRa sensor network

When aiming for the wider deployment of low-power sensor networks, the use of sub-GHz frequency bands shows a lot of promise in terms of robustness and minimal power consumption. Yet, when deploying such sensor networks over larger areas, the link quality can be impacted by a host of factors. Therefore, this contribution demonstrates the performance of several links in a real-world, research-oriented sensor network deployed in a (sub)urban environment. Several link characteristics are presented and analysed, exposing frequent signal deterioration and, more rarely, signal strength enhancement along certain long-distance wireless links. A connection is made between received power levels and seasonal weather changes and events. The irregular link performance presented in this paper is found to be genuinely disruptive when pushing sensor-networks to their limits in terms of range and power use. This work aims to give an indication of the severity of these effects in order to enable the design of truly reliable sensor networks

Modeling and Performance Evaluation of Bicycle-to-X Communication Networks

The growing connectivity of vehicles and Vulnerable Road Users, i.e., pedestrians and cyclists, allows to explore solutions based on wireless communication to support safety, efficiency and infotainment applications.However, there are few communication technologies that enjoy similar penetration ratios on cars, bicycles and pedestrians.WiFi is one of such technologies, as can be found in smart phones and in on-board hotspots.This thesis aims to characterize experimentally the wireless link performance and develop a model to estimate the received signal strength (RSS) between WiFi devices installed on bicycles and cars equipped with built-in WiFi APs.The RSS estimation model extends existing empirical models (e.g., the Log-Distance Path Loss model) by including the shadowing of the bicycle-and-cyclist system and of a vehicle.We first characterize the radiation pattern of antennas installed in several mounting points of a bicycle, in order to reduce the set of mounting points to be explored in future measurements.We then measured the radiation pattern of the bicycle and cyclist system, and the radiation pattern of a car with built-in and dedicated WiFi access points.Finally, we evaluate the performance of the model by comparing RSS estimates and measurements collected in selected interaction scenarios between bicycles and car: (i) bicycle overtaking a parked car, (ii) perpendicular crossing with LOS, and (iii) without LOS. We observed that 50% of the RSS estimates our model underestimates by less than are within 10 dBs of measured values about 50% of the RSSI values for the scenarios in LOS, and overestimates the RSSI values by more than 5 DBs about 75% of the RSSI values for the scenario containing obstructions

Authentication in Millimeter-Wave Body-Centric Networks Through Wireless Channel Characterization

Advent of 5G technologies has ensued in massive growth of body-centric communications (BCCs), especially at millimeter-wave (mm-wave) frequencies. As a result, the portable/handheld terminals are becoming more and more “intelligent” but not without the cost of being less secure. Improved authentication measures need to be explored, as effective identity authentication is the first level of security in these devices. This paper presents a novel keyless authentication method exploiting wireless channel characteristics. Human palm has distinct transmission coefficient (S21) for each of the users and is used for in vivo fingerprint identification in this paper. A detailed channel modeling using data acquisition from real environment and empirical approach is adopted to evaluate the usability of this method. The results show that this method can provide a secure operation for the mm-wave 5G BCCs

RF-EMF exposure induced by mobile phones operating in LTE small cells in two different urban cities

With the huge growth in data traffic, the densification of the macro cell (MC) layer with low-powered small cell (SC) base stations (resulting in a heterogeneous network) will improve network performances in terms of radio coverage and capacity. However, this may influence the human exposure to radiofrequency electromagnetic fields (RF-EMFs). Through measurement campaigns in two different urban cities (in France and the Netherlands), the authors characterized the RF-EMF exposure induced by LTE (Long-Term Evolution) MC and SC networks, while considering radio emissions from both base stations (downlink or DL) and user equipment (uplink or UL). For an internet data usage and with respect to an MC connection, results showed that an SC connection may increase the DL exposure while decreasing the UL exposure (with a factor of 5 to 17), mainly due to the lower mobile phone emitted power and depending on whether the throughput is limited or not. Furthermore, the city with a dense network is characterized by low UL exposure and high DL exposure

Distance-based sensor node localization by using ultrasound, RSSI and ultra-wideband - A comparision between the techniques

Wireless sensor networks (WSNs) have become one of the most important topics in wireless communication during the last decade. In a wireless sensor system, sensors are spread over a region to build a sensor network and the sensors in a region co-operate to each other to sense, process, filter and routing. Sensor Positioning is a fundamental and crucial issue for sensor network operation and management. WSNs have so many applications in different areas such as health-care, monitoring and control, rescuing and military; they all depend on nodes being able to accurately determine their locations. This master’s thesis is focused on distance-based sensor node localization techniques; Received signal strength indicator, ultrasound and ultra-wideband. Characteristics and factors which affect these distance estimation techniques are analyzed theoretically and through simulation the quality of these techniques are compared in different scenarios. MDS, a centralized algorithm is used for solving the coordinates. It is a set of data analysis techniques that display the structure of distance-like data as a geometrical picture. Centralized and distributed implementations of MDS are also discussed. All simulations and computations in this thesis are done in Matlab. Virtual WSN is simulated on Sensorviz. Sensorviz is a simulation and visualization tool written by Andreas Savvides.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format