Jackson W. Massey

Implementation of a real-time wireless interference alignment network

Interference alignment (IA) is a cooperative transmission technique for the interference channel. This paper describes two testbeds that implement real-time Multiple-input multiple-output (MIMO) IA for a network with three 2-antenna user pairs using software defined radio techniques: a PC-based testbed for rapid prototyping of potential IA protocols and an embedded testbed for evaluating IA under real-world computational constraints. The IA implementations rely on a wired backbone to share global channel state information (CSI) and a shared clock for frequency and timing synchronization. The testbeds are used to demonstrate the viability of IA, and to compare its robustness with several alternative transmission strategies, such as 2 × 2 MIMO TDMA, in terms of sum-rates. Results show that we are able to successfully achieve over-the-air IA in our three-user 2×2 MIMO testbed. The paper highlights key challenges with the practical realization of IA that are encountered while developing the testbed and identifies areas for future research.

AustinMan and AustinWoman: High-fidelity, anatomical voxel models developed from the VHP color images

The current versions (v2.3) of AustinMan and AustinWoman anatomical voxel models are presented with the methodology used to generate them from the Visible Human Projects color cross-sectional anatomical images. Both models are freely available online and documented in detail to increase their reproducibility. Visualizations of the models are shown to highlight their complexity.

Error measures for comparing bioelectromagnetic simulators

Various error norms that can be used to quantify the accuracy of large-scale, high-fidelity bioelectromagnetic simulations are presented. The merits of the norms are highlighted and they are used to compare large-scale benchmark simulations for voxel-based and CAD models of multi-layered spherical head and leg phantoms.

Benchmarking to close the credibility gap: A computational BioEM benchmark suite

The dearth of verification, validation, and performance benchmarks is identified as a roadblock to further progress in computational electromagnetics. The necessary ingredients for a useful benchmark suite are an application-specific list of problems, reference solutions, performance (error and computational cost) measures, and online databases publicizing comparisons. Computational cost comparisons are particularly difficult, rare, and important. As a case study, a benchmark suite for comparing existing and future computational bioelectromagnetics methods is developed.

FDTD vs. AIM for bioelectromagnetic analysis

The effectiveness of a time-domain differential-equation and a frequency-domain integral-equation solver are contrasted for bioelectromagnetic analysis. The two fundamentally different methods are compared empirically in terms of their accuracy and efficiency for benchmark problems.

A multiregion integral-equation method for antennas implanted in anatomical human models

To aid the design of power- and spectrum-efficient implanted antennas, efficient computational methods that can account for the presence of nearby inhomogeneous and dispersive human tissues are needed. While layered planar or spherical tissue models are often used to represent the antenna environment, the increasing fidelity and availability of anatomical human models can enable site-specific modeling, more accurate analysis, and better designs. Simulating radiation from antennas near/on/in anatomical human models, however, gives rise to large-scale problems as the latest high-fidelity models are composed of over 100 million voxels (J. W. Massey et al., 34th Annu. Conf. Bioelectromagn. Soc., June 2012). Such large problems can be solved by coupling the surface and volume electric-field integral equations and using a preconditioned, parallel FFT-accelerated iterative solver (F. Wei and A. E. Yilmaz, USNC/URSI Rad. Sci. Meet., July 2013). Unlike traditional finite-difference time-domain based methods, this approach (i) does not require the antenna model to conform to a regular grid to avoid staircasing errors and (ii) accurately models complex antennas by using irregular meshes. Moreover, as is the case for integral-equation methods in general, it requires meshing neither free space (to propagate fields) nor an extended computational domain (to truncate the problem with local boundary conditions that approximate the radiation condition); therefore, for antennas outside the body, this approach does not require the region between the antenna and the body to be meshed. For antennas implanted in voxel-based anatomical human models (by removing tissue voxels at the antenna site from the human model and inserting the antenna mesh), however, the method becomes impractical because it requires the transition region between the antenna and human tissues to be meshed such that the mesh conforms to both the irregular (triangular/tetrahedral) antenna mesh and the voxel tissue mesh.

Homogenization of three-dimensional metamaterial objects and validation by a fast surface-integral equation solver.

A homogenization model is applied to describe the wave interaction with finite three-dimensional metamaterial objects composed of periodic arrays of magnetodielectric spheres and is validated with full-wave numerical simulations. The homogenization is based on a dipolar model of the inclusions, which is shown to hold even in the case of densely packed arrays once weak forms of spatial dispersion and the full dynamic array coupling are taken into account. The numerical simulations are based on a fast surface-integral equation solver that enables the analysis of scattering from complex piecewise homogeneous objects. We validate the homogenization model by considering electrically large disk- and cube-shaped arrays and quantify the accuracy of the transition from an array of spheres to a homogeneous object as a function of the array size. Simulation results show that the fields scattered from large arrays with up to one thousand spheres and equivalent homogeneous objects agree well, not only far away from the arrays but also near them.

Mixed basis functions for fast analysis of antennas near voxel-based human models

To support the continuing proliferation of wireless devices that operate near/on/in the human body in the UHF band (0.3-3 GHz), antenna properties (input impedance, radiation patterns, etc.) must be characterized in the presence of human models. In recent years, a significant number of different anatomically accurate high-fidelity human models have been developed for these problems (Massey et al., 34th Annu. Conf. Bioelectromagnetics Society, 2012). With a few exceptions, almost all human models developed to date are based on voxels because the underlying data sets are 2-D medical images, e.g., CT, MRI, and cross-sectional images, and because it is extremely challenging to smooth these models while maintaining their accuracy. Given the difficulty of the problem, it should be expected that voxel-based models will continue to dominate the available human models in the future. As a result, computational methods that are based on regular meshes, such as the finite-difference time-domain (FDTD) and conjugate gradient FFT (CG-FFT) methods, have clear advantages for analyzing scattering from human models; in fact, these methods remain the two most popular approaches in bioelectromagnetics. When antennas must be modeled, however, the classical FDTD and CG-FFT methods constrain the antenna to conform to a regular mesh to avoid significant staircasing errors. Recently, a massively parallel and preconditioned version of the adaptive integral method (AIM) has been used to analyze antennas near human models (F. Wei and A. E. Yılmaz, Int. Conf. on Electromag. in Advanced Applicat., 869-872, 2012). The AIM approach allows irregular meshes to be used when discretizing integral equations because it introduces an auxiliary regular grid to accelerate the method of moments solution. Thus, arbitrarily shaped, located, and oriented antennas can be modeled accurately by using triangular surface and tetrahedral volume meshes when AIM is used. Discretizing voxel-based human models with tetrahedral volume meshes, however, is inefficient. It requires splitting each voxel into five or more tetrahedra and assigning the voxels material properties to these tetrahedra; this increases the number of elements/unknowns without adding any information on material properties and boundary locations. In this article, the AIM procedure is modified to use mixed basis functions; specifically, voxel-based volume basis functions (rooftops) are used in the human model and triangle-based surface and tetrahedron-based volume basis functions are used in the antenna region. While a single auxiliary grid is used to enclose both the human and antennas models, the remaining AIM parameters (number of auxiliary grid points and the near-zone correction size assigned to the basis functions) are optimized separately for the different types of basis functions. The mixed basis functions are observed to reduce the iterative solution time by a factor of ~5-10.

Austin benchmark suite for computational bioelectromagnetics: AIM performance data

The adaptive integral method (AIM) is used to solve the basic, moderate, and hard classes of problems in the Austin Benchmark Suite for Computational Bioelectromagnetics. Performance data, including computational costs and errors, are shown for both fast and efficient simulations run on a supercomputer cluster.

A Schur-complement method for integral-equation analysis of antennas near anatomical human models

The Schur complement method is applied to a multiregion integral equation formulation for analyzing antennas near anatomical human models to improve the conditioning of the system. The multiregion problem is split into a primary (external) domain and a secondary (internal) domain. The antenna unknowns are transferred as an effective load to the equivalent surface unknowns via the Schur complement. The proposed methods implementation and costs are detailed.