Electrical stimulation of the peripheral nervous system is a promising therapeutic option for several conditions; however, its effects on tissue and the safety of the stimulation remain poorly understood. In order to devise stimulation protocols that enhance therapeutic efficacy without the risk of causing tissue damage, we constructed computational models of peripheral nerve and stimulation cuffs based on extremely high-resolution cross-sectional images of the nerves using the most recent advances in computing power and machine learning techniques. We developed nerve models using nonstimulated (healthy) and over-stimulated (damaged) rat sciatic nerves to explore how nerve damage affects the induced current density distribution. Using our in-house computational, quasi-static, platform, and the Admittance Method (AM), we estimated the induced current distribution within the nerves and compared it for healthy and damaged nerves. We also estimated the extent of localized cell damage in both healthy and damaged nerve samples. When the nerve is damaged, as demonstrated principally by the decreased nerve fiber packing, the current penetrates deeper into the over-stimulated nerve than in the healthy sample. As safety limits for electrical stimulation of peripheral nerves still refer to the Shannon criterion to distinguish between safe and unsafe stimulation, the capability this work demonstrated is an important step toward the development of safety criteria that are specific to peripheral nerve and make use of the latest advances in computational bioelectromagnetics and machine learning, such as Python-based AM and CNN-based nerve image segmentation.

The impact of antenna mutual coupling on signal correlation in multi-antenna receivers has been studied in great detail. By contrast, there has been little work on how mutual coupling affects noise. In this paper we present a noise model for a diversity receiver that includes noise generated by the antennas, front-end amplifiers, and other receiver components. This model shows that noise in a compact diversity receiver may be spatially correlated. Expressions relating noise correlation to properties of the antennas and amplifiers are derived and its impact on the outage probability of an optimal diversity combiner is studied. Examples illustrating the relationship between mutual coupling and noise correlation demonstrate how different noise sources may impact performance in profoundly different ways.

The effect of antenna mutual coupling on fading correlation in compact MIMO arrays has received considerable attention. By contrast, relatively little attention has been paid to the noise. In this paper we present a circuit model for a noisy MIMO receiver front-end that includes arbitrary coupling and noise correlation. The noise figure for two-port networks is extended to multiport networks, from which theorems for optimal front-end design are derived. Numerical results are presented which provide insight into receiver noise behavior in the presence of coupled antennas.

We consider the impact of transmitter correlation, mutual coupling and matching networks on the design and performance of MIMO MRC systems with limited feedback. We present codebook design techniques for three measures of transmitted power and we investigate the impact of antenna matching on the performance of these codebooks. Numerical results suggest that, regardless of the power measure and matching networks, the benefits of MIMO MRC with limited feedback can be achieved with antennas spaced as close as 0.2 - 0.3 wavelengths apart.

In this paper, we provide a theoretical, simulation and experimental characterization of the performance of linear arrays of tri-polarized dipole antennas in multiple input multiple output (MIMO) systems in terms of degrees of freedom and channel capacity. Specifically, we formulate three distinct approaches, theoretical and experimental, that lead to the conclusion that linear arrays of tri-polarized dipole antennas employed at the transmit and receive end of a MIMO system can achieve a three-fold increase in channel capacity with respect to analogous arrays of linearly polarized antennas.

Previous studies of receive diversity have carefully modeled the impact of spatial correlation and antenna coupling on the signal component at the receiver. By contrast, relatively little attention has been paid to noise. In this paper we introduce a receive diversity model that articulates the dominant physical noise sources and relates their spatial correlation to the properties of the antennas, front-end amplifiers and matching networks. We then derive an optimal receiver as well as a formula for the resulting outage probability in terms of these noise sources. Numerical results are presented which suggest that different noise sources can impact performance in profoundly different ways.

We consider the impact of transmitter correlation and mutual coupling on MIMO MRC systems. We present optimal transmission strategies for three input power metrics as well as formulas for the resulting outage probabilities. Numerical results suggest that, regardless of the power metric, most of the performance benefits of MIMO MRC can be obtained with transmit antennas spaced as close as 0.2 - 0.3 wavelengths.

A dielectric composite is developed with permittivity ranging from 8 to 75 with selectable conductive and dielectric losses. The composite comprises gelatin, high fructose corn syrup (HFCS), NaCl, and water, and can be used to model soils, loams, and sands in the 200-MHz to 20-GHz range. A single-term Cole-Cole dispersion equation is developed with frequency-independent parameters being functions of component concentrations. Fits are provided for various soil samples and surrogate concentrations.

Most wireless communication systems currently employ single- or dual-polarized antennas which measure one or two components of the received electromagnetic (EM) signal. In this paper, we investigate the performance gains achievable by using "vector antennas" that can detect or excite up to six independent degrees of freedom.

The antenna of a cellular telephone in close proximity to the human head for a variety of time periods raises questions. This research uses the finite-difference time-domain (FDTD) method to calculate the power deposition from a cellular telephone on a high-resolution model of a human head as measured by the specific absorption rates (SAR) in W/kg. Visualization has been used to verify the modeling for simulation, assisted in analyzing the data and understanding the physical aspects controlling the power absorption.