Fast integral equation techniques for propagation problems

In this paper, the Method of Moments (MoM) solution is achieved for scattering problems by using the stationary Spectrally Accelerated Forward-Backward method (FBSA) and the non-stationary Spectrally Accelerated BiConjugate Gradient Stabilized (SA-BiCGSTAB) method, with a storage requirement and a computational cost of O(N) per iteration where N is the number of surface unknowns in the discretized integral equation. The SA-BiCGSTAB method is applied over rough terrain profiles as well as re-entrant surfaces which can not be handled by any conventional stationary iterative technique

On the capacity of printed planar rectangular patch antenna arrays in the MIMO channel: Analysis and measurements

Printed arrays of rectangular patch antennas are analyzed in terms of their MIMO performance using a full-wave channel model. These antennas are designed and manufactured in various array configurations, and their MIMO performance is measured in an indoor environment. Good agreement is achieved between the measurements and simulations performed using the full-wave channel model. Effects on the MIMO capacity of the mutual coupling and the electrical properties of the printed patches, such as the relative permittivity and thickness of the dielectric material, are explored. © 2006 IEEE

Optimization of linear wire antenna arrays to increase MIMO capacity using swarm intelligence

Free standing linear arrays (FSLA) are analyzed and optimized to increase MIMO capacity. A MIMO channel model based on electric fields is used. The effects of mutual interactions among the array elements are included into the channel matrix using method of moments (MoM) based full-wave solvers. A tool to design an antenna array of superior MIMO capacity for any specified volume is developed. Particle swarm optimization is used as the main engine for the optimization tasks of the tool. Uniform linear arrays, uniform circular arrays and non-uniform arrays are analyzed and compared in terms of their channel capacity

Particle swarm optimization for SAGE maximization step in channel parameter estimation

This paper presents an application of particle swarm optimization (PSO) in space alternating generalized expectation maximization (SAGE) algorithm. SAGE algorithm is a powerful tool for estimating channel parameters like delay, angles (azimuth and elevation) of arrival and departure, Doppler frequency and polarization. To demonstrate the improvement in processing time by utilizing PSO in SAGE algorithm, the channel parameters are estimated from a synthetic data and the computational expense of SAGE algorithm with PSO is discussed. (4 pages)

Particle swarm optimization of dipole arrays for superior MIMO capacity

The particle swarm optimization (PSO) technique is employed to design MIMO arrays for superior capacity. A channel model based on the method of moments solution of the electric field integral equation is utilized with PSO for arrays of dipole elements. Freestanding and printed dipole arrays are analyzed and optimized. Their adaptive performance in the MIMO channel is compared. Numerical results in the form of mean capacity, including comparisons with genetic algorithm results and measurements, are given. © 2008 Wiley Periodicals, Inc

Investigation of planar and conformal printed arrays for MIMO performance analysis

MIMO channel capacity of printed arrays with dipole elements is analyzed. A MIMO channel model based on electric fields is used. The effects of mutual interactions among the array elements through space and surface waves are included into the channel matrix using a full-wave hybrid Method of Moments (MoM)/Green's function technique in the spatial domain. MIMO capacity of printed arrays is then compared with that of free standing thin wire dipole arrays. Results show better performance of printed arrays

A model with electric fields for the inclusion of mutual coupling effects in the MIMO channel

[No abstract available

On the Number of Clusters in Channel Model

Typically, scatterers in an environment are not distributed uniformly but rather observed to occur in clusters. Identification of clusters is an issue under discussion. To this end, we study the effect of number of clusters on channel model through computer simulations. We focus on a geometric stochastic directional channel model based on COST259. Fixing a scatterer scenario, we calculate root mean square delay and angular spreads when scatterers are grouped into varying numbers of clusters and study how sensitive these parameters are to the number of clusters used in this channel model. © 2006 IEEE