Monte Carlo algorithm for the evaluation of the distance estimation variance in RSS-based visible light positioning

In this work, the Monte Carlo algorithm to determine the variance on the distance estimation in Received Signal Strength-based visible light positioning is considered. The method is build on the maximization of the signal-to-noise-ratio by means of matched filtering, and leads to a number of characteristics that are typically only obtained after intensive analytical elaborations. It is shown that the results match those obtained by calculating the Cramer-Rao lower bound when only the noise is considered as non-deterministic. It is demonstrated that the method is also applicable when multiple physical parameters exhibit a probability distribution, leading to an assessment of the distance estimation accuracy in more realistic settings

Experimental evaluation of the precision of received signal strength based visible light positioning

In this work, the experimental evaluation of the distance estimation variance is executed for received signal strength based visible light positioning. It is shown that based on the signal to noise ratio at the matched filter output, an accurate determination of the precision is achieved. In order to suppress dc ambient light which contains no information regarding the distance between the LED and the receiver, matched filtering with the dc-balanced part of the transmitted signal is required. As a consequence, the theoretical lower bound for the precision can not be achieved

Multi-RAT IoT -- What's to Gain? An Energy-Monitoring Platform

Multiple LPWANs have been rolled out to support the variety of IoT applications that are crucial to the ongoing digital transformation. These networks vary largely in terms of quality-of-service, throughput and energy-efficiency. To cover all LPWAN use-cases most optimally, multiple networks can be combined into a multiple radio access technology (multi-RAT) solution. In particular environmental monitoring in both smart city and remote landscapes. We present and share such a multi-RAT platform. To derive an accurate profile of the multi-RAT opportunities in various scenarios, in the-field network parameter are monitored. The platform collects per-packet energy-consumption, packet delivery ratio (PDR) and other parameters of LoRaWAN, NB-IoT and Sigfox. Our preliminary measurements demonstrate the validity of using a multi-RAT solution. For example, we illustrate the potential energy savings when adopting multi-RAT in various scenarios

Low-Power Synchronization for Multi-IMU WSNs

Wireless time synchronization is one of the most important services in a Wireless Sensor Network (WSN). Inertial Measurement Units (IMUs) are often used in these WSNs in healthcare-related treatments. We present a low-power, wirelessly synchronized multi-IMU platform. The proposed approach synchronously captures packets from different IMUs and transmits the data over Bluetooth Low Energy (BLE) to a central Data Capturing Unit (DCU). The contribution of this work is, rather than focussing on the highest possible accuracy, to provide a low-power accurate enough solution for use in a multi-IMU WSN. We examine key factors affecting synchronization accuracy and elaborate on the implementation challenges. An accuracy of sub 1 us can be achieved with the approach using 74.8 J/h of energy, while a power-optimized implementation is presented with an accuracy of 200 us and an energy consumption of only 198 mJ/h. This approach suits the required accuracy and low-power requirements for a multi-IMU system

High Precision Hybrid RF and Ultrasonic Chirp-based Ranging for Low-Power IoT Nodes

Hybrid acoustic-RF systems offer excellent ranging accuracy, yet they typically come at a power consumption that is too high to meet the energy constraints of mobile IoT nodes. We combine pulse compression and synchronized wake-ups to achieve a ranging solution that limits the active time of the nodes to 1 ms. Hence, an ultra low-power consumption of 9.015 {\mu}W for a single measurement is achieved. Measurements based on a proof-of-concept hardware platform show median distance error values below 10 cm. Both simulations and measurements demonstrate that the accuracy is reduced at low signal-to-noise ratios and when reflections occur. We introduce three methods that enhance the distance measurements at a low extra processing power cost. Hence, we validate in realistic environments that the centimeter accuracy can be obtained within the energy budget of mobile devices and IoT nodes. The proposed hybrid signal ranging system can be extended to perform accurate, low-power indoor positioning.Comment: 19 pages, 18 figures, 5 table

Indoor Multipath Assisted Angle of Arrival Localization.

Indoor radio frequency positioning systems enable a broad range of location aware applications. However, the localization accuracy is often impaired by Non-Line-Of-Sight (NLOS) connections and indoor multipath effects. An interesting evolution in widely deployed communication systems is the transition to multi-antenna devices with beamforming capabilities. These properties form an opportunity for localization methods based on Angle of Arrival (AoA) estimation. This work investigates how multipath propagation can be exploited to enhance the accuracy of AoA localization systems. The presented multipath assisted method resembles a fingerprinting approach, matching an AoA measurement vector to a set of reference vectors. However, reference data is not generated by labor intensive site surveying. Instead, a ray tracer is used, relying on a-priori known floor plan information. The resulting algorithm requires only one fixed receiving antenna array to determine the position of a mobile transmitter in a room. The approach is experimentally evaluated in LOS and NLOS conditions, providing insights in the accuracy and robustness. The measurements are performed in various indoor environments with different hardware configurations. This leads to the conclusion that the proposed system yields a considerable accuracy improvement over common narrowband AoA positioning methods, as well as a reduction of setup efforts in comparison to conventional fingerprinting systems