Indoor wireless communications and applications

Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter

An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters

A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values

High performance computing of explicit schemes for electrofusion jointing process based on message-passing paradigm

The research focused on heterogeneous cluster workstations comprising of a number of CPUs in single and shared architecture platform. The problem statements under consideration involved one dimensional parabolic equations. The thermal process of electrofusion jointing was also discussed. Numerical schemes of explicit type such as AGE, Brian, and Charlies Methods were employed. The parallelization of these methods were based on the domain decomposition technique. Some parallel performance measurement for these methods were also addressed. Temperature profile of the one dimensional radial model of the electrofusion process were also given

Characterizing the Cluster Lens Population

We present a detailed investigation into which properties of CDM halos make them effective strong gravitational lenses. Strong lensing cross sections of 878 clusters from an N-body simulation are measured by ray tracing through 13,594 unique projections. We measure concentrations, axis ratios, orientations, and the amount of substructure of each cluster, and compare the lensing weighted distribution of each quantity to that of the cluster population as a whole. The concentrations of lensing clusters are on average 34% larger than the typical cluster in the Universe. Despite this bias, the anomalously high concentrations (c >14) recently measured by several groups, appear to be inconsistent with the concentration distribution in our simulations, which predict < 2% of lensing clusters should have concentrations this high. No correlation is found between lensing cross section and the amount of substructure. We introduce several types of simplified dark matter halos, and use them to isolate which properties of CDM clusters make them effective lenses. Projections of halo substructure onto small radii and the large scale mass distribution of clusters do not significantly influence cross sections. The abundance of giant arcs is primarily determined by the mass distribution within an average overdensity of ~ 10,000. A multiple lens plane ray tracing algorithm is used to show that projections of large scale structure increase the giant arc abundance by a modest amount <7%. We revisit the question of whether there is an excess of giant arcs behind high redshift clusters in the RCS survey and find that the number of high redshift (z > 0.6) lenses is in good agreement with LCDM, although our simulations predict more low redshift (z < 0.6) lenses than were observed. (abridged)Comment: 19 pages, 15 figures. Submitted to Ap