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

Experimental analysis of dense multipath components in an industrial environment

This work presents an analysis of dense multipath components (DMC) in an industrial workshop. Radio channel sounding was performed with a vector network analyzer and virtual antenna arrays. The specular and dense multipath components were estimated with the RiMAX algorithm. The DMC covariance structure of the RiMAX data model was validated. Two DMC parameters were studied: the distribution of radio channel power between specular and dense multipath, and the DMC reverberation time. The DMC power accounted for 23% to 70% of the total channel power. A significant difference between DMC powers in line-of-sight and nonline-of-sight was observed, which can be largely attributed to the power of the line-of-sight multipath component. In agreement with room electromagnetics theory, the DMC reverberation time was found to be nearly constant. Overall, DMC in the industrial workshop is more important than in office environments: it occupies a fraction of the total channel power that is 4% to 13% larger. The industrial environment absorbs on average 29% of the electromagnetic energy compared to 45%-51% for office environments in literature: this results in a larger reverberation time in the former environment. These findings are explained by the highly cluttered and metallic nature of the workshop

People-Sensing Spatial Characteristics of RF Sensor Networks

An "RF sensor" network can monitor RSS values on links in the network and perform device-free localization, i.e., locating a person or object moving in the area in which the network is deployed. This paper provides a statistical model for the RSS variance as a function of the person's position w.r.t. the transmitter (TX) and receiver (RX). We show that the ensemble mean of the RSS variance has an approximately linear relationship with the expected total affected power (ETAP). We then use analysis to derive approximate expressions for the ETAP as a function of the person's position, for both scattering and reflection. Counterintuitively, we show that reflection, not scattering, causes the RSS variance contours to be shaped like Cassini ovals. Experimental tests reported here and in past literature are shown to validate the analysis