Use this URL to cite or link to this record in EThOS:
Title: Wireless channel modelling for specknet
Author: Darbari, Faisal
ISNI:       0000 0004 2674 5852
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Access from Institution:
A wireless sensor network (WSN) consists of spatially distributed autonomous devices using sensors to cooperatively monitor physical or environmental conditions, such as pressure, temperature, sound, vibration or motion at different locations. The development of wireless sensor networks was originally motivated by military applications such as battlefield surveillance. However, wireless sensor retworks are now used in many commercial applications, including environment and habitat monitoring, healthcare applications, home automation, and traffic control. The physical size of these devices is shrinking due to advances in semiconductor technology. The main challenge is to produce low cost and miniature sensor nodes. Energy is the scarcest resource for these nodes as it determines the WSN lifetime. Since these nodes will be deployed close together to form a dense wireless network the received signaI to noise ratio at any instant of time not only depends on physical channel (i. e. path loss and fading) but also on various design parameters like CSMA/CA inhibition threshold, polarization, deployment strategy and node density. This thesis characterises the propagation channel for miniature wireless nodes. A characterization of the short range (<10cm), narrowband, wireless channel, appropriate to a dense network of wireless transceivers operating in the 2.4 GHz ISM band, is presented. Transmission loss measurements have been made in the laboratory at 2.45 GHz and a fading model derived. Aggregate interference due to neighboring carrier-sense-multiple-access (CSMA) nodes has been calculated. The resulting dependence of signl-to-interference ratio (SIR) on node density is presented to allow density dimensioning. Cumulative distributions of SIR have been used to establish performance statistics for example modulation and detection schemes. A simulation model has been developed to characterise the physical link experienced by these networks.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral