Jeff Frolik

A case for considering hyper-Rayleigh fading channels

This work is motivated by the problem of characterizing small-scale radio propagation environments for wireless sensor networks. If sensors are statically deployed near the ground or within structures, temporal fading may not exist but the channel may nevertheless experience severe frequency-selective behavior. The work presents real-world, frequency-selective fading data measured for in-vehicle wireless sensor applications. This fading data often exhibit statistics more severe than predicted by the Rayleigh fading model; a scenario referred herein as to as being hyper-Rayleigh. A two-ray, small-scale model is proposed as a new worst-case for this application space.

Effects of natural propagation environments on wireless sensor network coverage area

This work presents new near-ground propagation models at 915 MHz based on field measurement data for three naturally occurring environments (open fields, woods and wooded hills). The models are incorporated into a network simulation for randomly distributed transmitting sensors. The effects of the various. environments on coverage area are explored for various power transmission levels. This work has implications on quantifying the spatial-temporal resolution of single and multiple hop wireless sensor networks as a function of both transmission power constraints and the environment in which the network is deployed.

Quality of service analysis and control for wireless sensor networks

This paper investigates wireless sensor network spatial resolution as a measurement of quality of service (QoS). We seek to control the network in such a way that sensors participate equally in the network while conserving energy and maintaining the desired spatial resolution. This work provides an analytic solution of a sensor network QoS control strategy demonstrated recently through simulation. General conclusions about the selection of parameters to control network performance, specifically the mean and variance of the QoS are presented. We show that there is a tradeoff between the static and dynamic QoS performance, as well as energy usage and conclude by presenting the several potential applications that are enabled by ability to control both the mean and variance of network QoS.

On appropriate models for characterizing hyper-rayleigh fading

Recent work presented empirical data for which the small-scale fading statistics were more severe than Rayleigh; a phenomena deemed hyper-Rayleigh fading. This paper considers whether commonly utilized small-scale propagation models can be appropriately adapted to represent this class of fading. The work argues that the most meaningful model for the hyper- Rayleigh regime is based on a physical wave model (as opposed to stochastic); in particular, the TWDP model, where Deltaap1, holds the greatest promise. The crux of the argument is that the stochastic models significantly over-predict the amount of constructive interference in comparison to what is physically realizable.

Non-Line-of-Sight Identification and Mitigation Using Received Signal Strength

Indoor wireless systems often operate under non-line-of-sight (NLOS) conditions that can cause ranging errors for location-based applications. As such, these applications could benefit greatly from NLOS identification and mitigation techniques. These techniques have been primarily investigated for ultra-wide band (UWB) systems, but little attention has been paid to WiFi systems, which are far more prevalent in practice. In this study, we address the NLOS identification and mitigation problems using multiple received signal strength (RSS) measurements from WiFi signals. Key to our approach is exploiting several statistical features of the RSS time series, which are shown to be particularly effective. We develop and compare two algorithms based on machine learning and a third based on hypothesis testing to separate LOS/NLOS measurements. Extensive experiments in various indoor environments show that our techniques can distinguish between LOS/NLOS conditions with an accuracy of around 95%. Furthermore, the presented techniques improve distance estimation accuracy by 60% as compared to state-of-the-art NLOS mitigation techniques. Finally, improvements in distance estimation accuracy of 50% are achieved even without environment-specific training data, demonstrating the practicality of our approach to real world implementations.

Worse-than-Rayleigh fading: Experimental results and theoretical models

This article is motivated by the recent recognition that channel fading for new wireless applications is not always well described by traditional models used for mobile communication systems. In particular, fading data collected for vehicleto- vehicle and wireless sensor network applications has motivated new models for conditions in which channel fading statistics can be worse than Rayleigh. We review the use of statistical channel models, describe our example applications, and provide both measured and modeling results for these severe fading conditions.

Packetized Plug-In Electric Vehicle Charge Management

Plug-in electric vehicle (PEV) charging could cause significant strain on residential distribution systems, unless technologies and incentives are created to mitigate charging during times of peak residential consumption. This paper describes and evaluates a decentralized and “packetized” approach to PEV charge management, in which PEV charging is requested and approved for time-limited periods. This method, which is adapted from approaches for bandwidth sharing in communication networks, simultaneously ensures that constraints in the distribution network are satisfied, that communication bandwidth requirements are relatively small, and that each vehicle has fair access to the available power capacity. This paper compares the performance of the packetized approach to an optimization method and a first-come, first-served (FCFS) charging scheme in a test case with a constrained 500 kVA distribution feeder and time-of-use residential electricity pricing. The results show substantial advantages for the packetized approach. The algorithm provides all vehicles with equal access to constrained resources and attains near optimal travel cost performance, with low complexity and communication requirements. The proposed method does not require that vehicles report or record driving patterns, and thus provides benefits over optimization approaches by preserving privacy and reducing computation and bandwidth requirements.

Electric vehicle charging: Transformer impacts and smart, decentralized solutions

This paper compares distribution transformer aging impacts resulting from plug-in electric vehicles charging under AC Level 1 versus AC Level 2 charging conditions. Additionally, we propose an algorithm for PEV smart charging and evaluate its effectiveness on transformer aging. We use a Monte Carlo simulation of a 25kVA distribution transformer, with ambient temperature data from Burlington, VT and Phoenix, AZ, to calculate transformer aging under both uncoordinated and smart charging conditions. The results indicate more substantial aging as a result of AC Level 2 charging compared to AC Level 1. Smart charging can significantly mitigate these effects. We also present a more decentralized approach to smart charging and compare two distributed automaton-based charge management strategies, which both prevent the transformer from becoming overloaded. These methods give vehicle owners the ability to select among charging priorities in an environment in which the vehicles manage their charging autonomously.

A Compact Reverberation Chamber for Hyper-Rayleigh Channel Emulation

Recent propagation measurements conducted for emerging applications such as vehicle-to-vehicle communications and wireless sensor systems have illustrated that present worst-case channel models are not sufficient to characterize the small-scale propagation effects seen. New theoretical models have thus been proposed but existing emulation environments do not create sufficiently severe channel conditions. In this work we present the design of a compact, reconfigurable channel emulator (CRCE) specifically designed to create Ricean, Rayleigh and hyper-Rayleigh fading environments in a repeatable manner. The bench-top sized chamber leverages concepts seen in reverberation chambers but in addition to a mechanical stirrer varies the multipath environment through the use of multiple antennas. Emulated channels illustrating space-, time- and frequency-selective behaviors are presented.

An Implementation of Decentralized Consensus Building in Sensor Networks

In cognitive sensor networks, achieving consensus among the sensor nodes without requiring centralized control is an important attribute that can enable quick and reliable network decisions. Decentralized consensus building can be achieved through iterative information exchange among sensor nodes. While much of the literature has concentrated on developing theory, minimizing the number of iterations is necessary in practice to reduce energy consumption. In this work, we present an approach aimed at solving this practical problem. Specifically, the contributions of this work are fourfold. First, existing theoretical, continuous-time results are reformulated so that they can be implemented in physical, discrete-time hardware. Second, we show that the number of iterations needed to achieve consensus can be minimized a priori for a given network topology. Third, we illustrate our results through numerical analysis and network simulation. Finally, we present results from a hardware implementation.