Multi-Polarized Channel Characterization

Machine-to-machine (M2M) communication is becoming an important aspect of warehouse management, remote control, robotics, traffic control, supply chain management, fleet management and telemedicine. M2M is expected to become a significant portion of the Industrial Internet and, more broadly, the Internet of Things (IoT). The environments in which M2M systems are expected to operate may be challenging in terms of radio wave propagation due to their cluttered, multipath nature, which can cause deep signal fades and signal depolarization. Polarization diversity in two dimensions is a well-known technique to mitigate such fades. But in the presence of reflectors and retarders where multipath components arrive from any direction, we find the detrimental effects to be three-dimensional and thus consider herein mitigation approaches that are also 3D. The objectives of this dissertation are three. First, to provide a theoretical framework for depolarization in three dimensions. Second, to prepare a tripolar antenna design that meets cost, power consumption, and simplicity requirements of M2M applications and that can mitigate the expected channel effects. Finally, to develop new channel models in three dimensional space for wireless systems. Accordingly, this dissertation presents a complete description of 3D electromagnetic fields, in terms of their polarization characteristics and confirms the advantage of employing tripolar antennas in multipath conditions. Furthermore, the experimental results illustrate that highly variable depolarization occurs across all three spatial dimensions and is dependent on small changes in frequency and space. Motivated by these empirical results, we worked with a collaborating institution to develop a three-dimensional tripolar antenna that can be integrated with a commercially available wireless sensor. This dissertation presents the testing results that show that this design significantly improves channels over traditional 2D approaches. The implications of tripolar antenna integration on M2M systems include reduction in energy use, longer wireless communication link distances, and/or greater link reliability. Similar results are shown for a planar antenna design that enables four different polarization configurations. Finally, the work presents a novel three-dimensional geometry-based stochastic channel model that builds the channel as a sum of shell-like sub-regions, where each sub-region consists of groups of multipath components. The model is validated with empirical data to show the approach may be used for system analyses in indoor environments

Three Branch Diversity Systems for Multi-Hop IoT Networks

Internet of Things (IoT) is an emerging technological paradigm connecting numerous smart objects for advanced applications ranging from home automation to industrial control to healthcare. The rapid development of wireless technologies and miniature embedded devices has enabled IoT systems for such applications, which have been deployed in a variety of environments. One of the factors limiting the performance of IoT devices is the multipath fading caused by reflectors and attenuators present in the environment where these devices are deployed. Leveraging polarization diversity is a well-known technique to mitigate the deep signal fades and depolarization effects caused by multipath. However, neither experimental validation of the performance of polarization diversity antenna with more than two branches nor the potency of existing antenna selection techniques on such antennas in practical scenarios has received much attention. The objectives of this dissertation are threefold. First, to demonstrate the efficacy of a tripolar antenna, which is specifically designed for IoT devices, in harsh environments through simulations and experimental data. Second, to develop antenna selection strategies to utilize polarized signals received at the antenna, considering the restrictions imposed due to resource limitations of the IoT devices. Finally, to conduct comparative analyses on the existing standard diversity techniques and proposed approaches, in conjunction with experimental data. Accordingly, this dissertation presents the testing results of tripolar antenna integrated with Arduino based IoT devices deployed in environments likely to be experienced by IoT devices in real life applications. Both simulation and experimental results from single point-to-point wireless links demonstrate the advantage of utilizing tripolar antennas in harsh propagation conditions over single branch antenna. Motivated by these empirical results, we deploy a small-scale IoT network with tripolar antenna based nodes to analyze the impact of tripolar antenna on neighbor nodes performance as well as to investigate end-to-end network performance. This work illustrates that the selection of antenna branches, while considering network architecture and the level of congestion on the repeater nodes, minimizes excessive antenna switching and energy consumption. Similar results are shown for IoT networks with predetermined and dynamic routing protocols, where the proposed techniques yielded lower energy consumption than the conventional diversity schemes. Furthermore, a probabilistic, low complexity antenna selection approach based on Hidden Markov model is proposed and implemented on wireless sensor nodes aiming to reduce energy consumption and improve diversity gain. Finally, we develop a dual-hop based technique where a node selects the antenna element for optimal performance based on its immediate network neighbors antenna configuration status during selection. The performance of the proposed technique, which is verified through simulation and measured data, illustrates the importance of considering network-wide evaluations of antenna selection techniques