The deployment of small-size, low-cost and efficient internet-of-things (IoT) sensors has been growing rapidly to serve several applications like health monitoring, autonomous cars, spectrum sensing, environ- ment monitoring, etc. As a result, there is a persistent need for efficient signal processing tools to efficiently make use of sensory data. As well as, the demands on low-energy and ultra high data rate telecommunica- tion are obviously increasing, which considerably has led to increase the pressure on the existing backhaul links. Thus, adequate spectral and energy efficient communication technologies and network paradigms are required for current and future communications. Therefore, in this thesis, two emerging technologies in the areas of signal processing and wireless communications are explored, namely; sensing services and intelligent reflecting surfaces (IRSs) as a prominent technology for wireless backhauling. Several aspects of wireless sensor networks (WSNs) and IoT are explored including target localization using radio frequency identification (RFID) network, decision fusion of multiple sensors, and integrated sensing and communication system (ISAC). Decision fusion rules and localization methods using a net- work of sensors and RFID tags are proposed, investigated and analyzed. The obtained results show the effectiveness of these proposed fusion rules and location estimators. Moreover, for ISAC system, a uni- fied performance evaluation is introduced based on Kullback-Leibler divergence theorem, or so called the relative information theorem, where results clearly confirm that the relative information can efficiently characterize ISAC systems holistically. Furthermore, the performance of IRS based communications is evaluated and their use in multi-hop wireless backhauling is explored. Multi-hop terrestrial backhauling is introduced first, where a small base-station communicating with a macro base-station through a number of small base-stations. The line-of-sight path between the small base-stations is dropped and communication takes place through IRS panels which provide virtual line-of-sight and thus the link is modeled using Rician channel. The bit error rate and outage probability are derived for the introduced system model and random number of hops is also considered. As well as, a multi-layer unmanned aerial vehicles (UAV) network is considered, in which an IRS panel is attached to a high altitude platform and provide line-of-sight paths to low altitude UAVs. Imperfect channel estimation and phase compensation at IRS are considered, and the bit error rate, outage probability and ergodic capacity are derived. Simulation and theoretical results are provided for the introduced system models and the performance limits are presented and investigated. Obtained results depicts a perfect match between the analysis and simulation when the number of reflectors is considerable, we well as the performance improvement gained by deploying IRS is shown.
|Date of Award
|1 Aug 2023
- The University of Manchester
|Emad Alsusa (Supervisor) & Ka Chun So (Supervisor)