Taming and Leveraging Directionality and Blockage in Millimeter Wave Communications

To cope with the challenge for high-rate data transmission, Millimeter Wave(mmWave) is one potential solution. The short wavelength unlatched the era of directional mobile communication. The semi-optical communication requires revolutionary thinking. To assist the research and evaluate various algorithms, we build a motion-sensitive mmWave testbed with two degrees of freedom for environmental sensing and general wireless communication.The first part of this thesis contains two approaches to maintain the connection in mmWave mobile communication. The first one seeks to solve the beam tracking problem using motion sensor within the mobile device. A tracking algorithm is given and integrated into the tracking protocol. Detailed experiments and numerical simulations compared several compensation schemes with optical benchmark and demonstrated the efficiency of overhead reduction. The second strategy attempts to mitigate intermittent connections during roaming is multi-connectivity. Taking advantage of properties of rateless erasure code, a fountain code type multi-connectivity mechanism is proposed to increase the link reliability with simplified backhaul mechanism. The simulation demonstrates the efficiency and robustness of our system design with a multi-link channel record.The second topic in this thesis explores various techniques in blockage mitigation. A fast hear-beat like channel with heavy blockage loss is identified in the mmWave Unmanned Aerial Vehicle (UAV) communication experiment due to the propeller blockage. These blockage patterns are detected through Holm\u27s procedure as a problem of multi-time series edge detection. To reduce the blockage effect, an adaptive modulation and coding scheme is designed. The simulation results show that it could greatly improve the throughput given appropriately predicted patterns. The last but not the least, the blockage of directional communication also appears as a blessing because the geometrical information and blockage event of ancillary signal paths can be utilized to predict the blockage timing for the current transmission path. A geometrical model and prediction algorithm are derived to resolve the blockage time and initiate active handovers. An experiment provides solid proof of multi-paths properties and the numeral simulation demonstrates the efficiency of the proposed algorithm

Evaluating the Use of sUAS-Derived Imagery for Monitoring Flood Protection Infrastructure

In the US there are approximately 33,000 miles of levees. This includes 14,500 miles of levee systems associated with US Army Corps of Engineers programs and approximately 15,000 miles from other state and federal agencies. More than 14 million people live behind levees and associated flood prevention infrastructure. Monitoring and risk assessment are an on-going process, especially during times of flood conditions. The city of New Orleans was heavily impacted by Hurricane Katrina in 2005 by storm surges and intense rainfall. The impact of the hurricane was substantial enough to cause levee failure and I-wall toppling where many of the levees were breached and waters flooded the city. Subsidence and increasing population are likely to make flooding events more frequent and costly. As new technologies emerge, monitoring and risk assessment can benefit to increase community resiliency. In this research, I investigate the use of the structure from motion photogrammetric method to monitor positional changes in invariant objects such as levees, specifically, I-walls. This method uses conventional digital images from multiple view locations and angles by either a moving aerial platform or terrestrial photography. Using parallel coded software and accompanying hardware, 3D point clouds, digital surface models and orthophotos can be created. By providing comparisons of similar processing workflows with a variety of imaging acquisition criteria using commercially available unmanned aerial systems (UAS), we created multiple image sets of a simulated I-wall at various flight elevations, look angles, and effective overlap. The comparisons can be used for sensor selection and mission planning to improve the quality of the final product

Augmented UAS navigation in GPS denied terrain environments using synthetic vision

GPS is a critical sensor for Unmanned Aircraft Systems (UASs) navigation due to its accu racy, global coverage, and small hardware footprint. However, GPS is subject to interruption or denial due to signal blockage or RF interference. In such a case, position, velocity and altitude (PVA) performance from other inertial and air data sensor is not sufficient for UAS platforms to continue their primary missions, especially for small UASs. Recently, image-based navigation has been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. This thesis develops a novel, automated UAS navigation augmentation scheme, which utilizes publicly available open source geo-referenced vector map data, in conjunction with real-time optical imagery from on-board monocular camera to augment UAS navigation in GPS denied terrain environments. The main idea is to analyze and use terrain drainage patterns for GPS-denied navigation of small UASs, such as ScanEagle, utilizing a down-looking fixed monocular imager. We leverage the analogy between terrain drainage patterns and human fingerprints, to match local drainage patterns to GPU (Graphics Processing Unit) rendered parallax occlusion maps of geo-registered radar returns (GRRR). The matching occurs in real-time. GRRR is assumed to be loaded on-board the aircraft pre-mission, so as not to require a scanning aperture radar during the mission. Once a successful match is made, using a known lens model a final PVA solution can be obtained from the extrinsic matrix of the camera [1]. Our approach allows extension of UAS missions to GPS denied terrain areas, with no assumption of human-made geographic objects. We study the influence of granularity of terrain drainage patterns on performance of our minutiae-based terrain matching approach. Based on experimental observations, we conclude that our approach delivers a satisfactory performance. We identify the conditions to achieve the desired performance for the input images based on UAS flight altitudes

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Applications of Finite Element Modeling for Mechanical and Mechatronic Systems

Modern engineering practice requires advanced numerical modeling because, among other things, it reduces the costs associated with prototyping or predicting the occurrence of potentially dangerous situations during operation in certain defined conditions. Thus far, different methods have been used to implement the real structure into the numerical version. The most popular uses have been variations of the finite element method (FEM). The aim of this Special Issue has been to familiarize the reader with the latest applications of the FEM for the modeling and analysis of diverse mechanical problems. Authors are encouraged to provide a concise description of the specific application or a potential application of the Special Issue

Securing NextG networks with physical-layer key generation: A survey

As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks