Unmanned aerial vehicle-to-wearables (UAV2W) indoor radio propagation channel measurements and modeling

In this paper, off-body ultra-wide band (UWB) channel characterization and modeling are presented between an unmanned aerial vehicle (UAV) and a human subject. The wearable antenna was patched at nine different body locations on a human subject during the experiment campaign. The prime objective of this work was to study and evaluate the distance and frequency dependent path loss factors for different bandwidths corresponding to various carrier frequencies, and also look into the time dispersion properties of such unmanned aerial vehicle-to-wearables (UAV2W) system. The environment under consideration was an indoor warehouse with highly conductive metallic walls and roof. Best fit statistical analysis using Akaike Information Criteria revealed that the Log-normal distribution is the best fit distribution to model the UWB fading statistics. The study in this paper will set up a road map for future UAV2W studies to develop enhanced retail and remote health-care monitoring/diagnostic systems

Statistical analysis and channel modeling in next generation wireless communication systems

In this thesis, statistical analysis and channel modeling in next generation wireless communication systems is presented in detail. The primary focus of this thesis is on the statistical modeling of interference temperature (IT) in cognitive radio systems, and empirical study of wireless channel characterization of unmanned aerial vehicle (UAV)-assisted communications at ultra-wideband (UWB) and at millimeter wave (mmWave) frequencies.Firstly, in the cognitive radio system, a novel idea to statistically model the dynamic interference threshold (IT) from user traffic demand is presented in detail. It is shown that the cognitive radio system with dynamic IT will have high capacity performance with less outage probability over a system that does not utilize dynamic IT. The detailed theoretical analysis with expressions for mean capacity and outage probability in general operation region, and in high power region are derived and subsequently, validated with the simulations results. In addition, the effect of secondary user interference on primary user is also examined in this part.In the second part, wireless channel characterisation for unmanned aerial vehicle-to-wearables (UAV2W) at UWB frequency is analysed, and studied empirically in an indoor warehouse environment. The frequency and distance dependent path gain analysis at different bandwidths for a corresponding carrier frequency with time dispersion characteristics is presented in detail. Furthermore, from statistical modeling, it was shown that the Log-normal distribution is the best fit distribution model to characterize fading in these UAV2W systems.Finally, a novel emulation method for UAV motion by a robotic arm is presented to study the mmWave channel characteristics (Doppler spreading and path loss) at 28 GHz. In addition to that, empirical study is carried out to analyze the propeller modulation effect caused by the propellers in UAVs with an actual UAV setup. These important statistical analysis, and channel modeling discussed in this thesis are very critical in designing, analysing, and in implementation of fifth generation (5G) and beyond 5G (B5G) communication for the future. This thesis is a stepping stone in that direction

Characterizing the UAV-to-Machine UWB Radio Channel in Smart Factories

In this work, the results of Ultra-Wideband air-to-ground measurements carried out in a real-world factory environment are presented and discussed. With intelligent industrial deployments in mind, we envision a scenario where the Unmanned Aerial Vehicle can be used as a supplementary tool for factory operation, optimization and control. Measurements address narrow band and wide band characterization of the wireless radio channel, and can be used for link budget calculation, interference studies and time dispersion assessment in real factories, without the usual limitation for both radio terminals to be close to ground. The measurements are performed at different locations and different heights over the 3.1-5.3 GHz band. Some fundamental propagation parameters values are determined vs. distance, height and propagation conditions. The measurements are complemented with, and compared to, conventional ground-to-ground measurements with the same setup. The conducted measurement campaign gives an insight for realizing wireless applications in smart connected factories, including UAV-assisted applications

Body-UAV Near-Ground LoRa Links through a Mediterranean Forest

LoRa low-power wide-area network protocol has recently gained attention for deploying ad-hoc search and rescue (SaR) systems. They could be empowered by exploiting body-UAV links that enable communications between a body-worn radio and a UAV-mounted one. However, to employ UAVs effectively, knowledge of the signal's propagation in the environment is required. Otherwise, communications and localization could be hindered. The radio range, the packet delivery ratio (PDR), and the large- and small-scale fading of body-UAV LoRa links at 868 MHz when the radio wearer is in a Mediterranean forest are here characterized for the first time with a near-ground UAV having a maximum flying height of 30 m. A log-distance model accounting for the body shadowing and the wearer's movements is derived. Over the full LoRa radio range of about 600 m, the new model predicts the path loss (PL) better than the state-of-the-art ones, with a reduction of the median error even by 10 dB. The observed small-scale fading is severe and follows a Nakagami-m distribution. Extensions of the model for similar scenarios can be drawn through appropriate corrective factors