Current propogation models are no longer sufficient for wireless network planning. They are neither accurate (empirical) nor fast enough (deterministic) to be applicable in the applications of Automated Cell Planning. This thesis focuses on the development of a new method, namely Intelligent Ray Launching Algorithm (IRLA), which is based on a fast, accurate and robust algorithm that is especially suitable for wireless network planning. The infrastructure of IRLA is thoroughly analysed in this thesis and the results are presented. Foster's design methodology has been used to parallelise the new model. Various scenarios for outdoor, indoor, indoor-to-outdoor and outdoor-to-indoor settings have been employed to test the effectiveness and efficiency of IRLA. The field strengths (path loss) and multipath information were calculated, which were used to demonstrate the application of IRLA. The accuracy of IRLA is guaranteed via the use of a meta-based heuristics calibration procedure. In order to achieve a simulation within a realistic time scale, acceleration techniques such as avoid double marking, multi-threading and the use of Parallel Object-Oriented Programming C++ have been employed. Since multipath for a large number of receiver locations can be easily obtained via IRLA, the study of delay spread has been presented. The success of the integration with a wireless network planning platform exemplifies that IRLA is suitable for wireless network planning and optimisation, which is beneficial to relevant academics and industries. Testing demonstrated that depending on various scenarios, IRLA obtains industrially-recognised accuracy ranging from 5 to 8 dB Root-Mean-Square-Error. This model is highly-efficient because its required runtime for most simulations is from a few seconds to a few minutes.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:536692 |
| Date | January 2010 |
| Creators | Lai, Zhihua |
| Publisher | University of Bedfordshire |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10547/134379 |
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