Future weather radar systems will need to provide rapid updates within a flexible multifunctional overall radar network. This naturally leads to the use of electronically scanned phased array antennas. However, the traditional multifaced planar antenna approaches suffer from having radiation patterns that are variant in both beam shape and polarization as a function of electronic scan angle; even with practically challenging angle-dependent polarization correction, this places limitations on how accurately weather can be measured. A cylindrical array with commutated beams, on the other hand, can theoretically provide patterns that are invariant with respect to azimuth scanning with very pure polarizations. This paper summarizes recent measurements of the cylindrical polarimetric phased array radar demonstrator, a system designed to explore the benefits and limitations of a cylindrical array approach to these future weather radar applications.

Wireless communication is increasingly being used to federate embedded devices in a variety of distributed systems application domains, ranging from wireless sensor networks to the emerging "Internet of Things (IoT)." Since such embedded devices are tightly coupled both with their environments and with each other through their wireless communication channels, both variations in their environments and the system's need to respond (sometimes rapidly) to those variations may produce (1) the need for such devices to communicate and (2) with it the potential for channel contention to arise, dynamically at run-time. Thus, how wireless channels among the embedded devices are allocated and managed in these systems may significantly influence both communication-specific quality-of-service (QoS) properties (such as message throughput) and broader QoS properties (such as timeliness of system responsiveness) that depend on them. A growing body of research has focused on managing different aspects of wireless communication, but has done so mainly in an ad hoc manner, with respect to individual aspects rather than multiple aspects and their potential interactions. Even less attention has been paid to formal methods for assessing how combinations of aspects may influence communication performance, and how to characterize, adapt to, and exploit their combined effects, which is essential to address the challenges noted above. To overcome these limitations of the current state of the art, this paper makes three main contributions to wireless communication for distributed embedded systems with QoS constraints. First, it shows how a basic but fundamental set of channel admission and modulation decisions can be combined within a single Markov decision process (MDP) model to optimize (in expectation) objectives such as message throughput, even with stochastic arrival and interference characteristics. Second, it identifies regular structure in the value-optimal policies generated off-line from these models, which forms the basis for efficient and accurate heuristics suitable for on-line use. Third, it shows how single-and multi-variable regression techniques can be used to characterize key parameters that govern such regular structure, which then are used to instantiate those heuristics.

The stochastic nature of wireless communication suggests a Markov Decision Process (MDP) as a formalism for identifying and evaluating spectrum control policies. However, in practice numerous factors influence the success or failure of a transmission, so that the applicability of particular MDP models to real spectrum management problems must itself be examined. This paper presents a series of model validation studies in which correspondence between an MDP model and a discrete-event simulation (DES) model is evaluated. We test several hypotheses that together provide a foundation and an exemplar for the idea of using MDPs to guide management of shared spectrum. We conclude that there is sufficient similarity between the performance predictions made by the MDP model and the DES model that MDPs can be used effectively to determine spectrum control policies.

Modern embedded systems are increasingly likely to be distributed across multiple devices and platforms that must interact with high precision across wireless networks. Traditional ways of managing the wireless radio spectrum suffer from two fundamental limitations, which our research addresses: (1) spectrum is divided a priori into static coarse-grained partitions, and (2) partitions are non-overlapping. To overcome these limitations, we propose an approach to spectrum allocation based on dynamic allocation of diverse portions of the overall spectrum and overlapping allocations to increase utilization. Our previous work has established the potential of a new generation of allocation strategies based on both memory-like and spectrum-specific features. Here, we describe new directions for that work based on Markov decision theory.

Modern embedded systems are increasingly likely to be distributed across multiple devices and platforms that must interact with high precision across wireless networks. Traditional ways of managing the wireless radio spectrum suffer from two fundamental limitations, which the research presented in this paper addresses: (1) spectrum is divided a priori into static coarse-grained partitions without reference to details of particular applications, and (2) partitions are non-overlapping, which although beneficial to reduce interference prevents a much greater utilization of the spectrum through carefully allowing overlap of spectrum allocations. To overcome these limitations, we propose an approach to spectrum allocation based on dynamic allocation of diverse portions of the overall spectrum and overlapping allocations to increase utilization. This paper makes three main contributions to the state of the art in spectrum management for embedded systems: (1) it examines how memory management techniques such as Knuth's buddy algorithm can be applied to spectrum management, in the face of transmission failures that may arise from the physical environment, (2) it extends that approach to consider transmission failures resulting from interference, when overlapping regions of spectrum are allocated to increase utilization, and (3) it presents results of simulation experiments we conducted to evaluate those approaches, which demonstrate their efficacy and suggest future extensions based on them.

Cross-polar measurements made with an agile-beam phased-array weather radar are compared with theory. The intensity of cross-polar fields places conditions on the accuracy of meteorological measurements. Results reported herein support the hypothesis that polarimetric phased-array radar for weather observations can be designed to allow the use of the polarimetric data acquisition mode being implemented by the National Weather Service on upgraded WSR-88Ds which use parabolic reflector antennas.

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No abstract available.