An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker

Md. Sumon, Sarker (2011) An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker. Masters thesis, University of Malaya.

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    The potential implementation of Wireless Radio Networks and Personal Communication Systems (PCS) inside buildings requires a thorough understanding of signal propagation within buildings. Empirical approaches in this regards offer computational simplicity with low accuracy, while the deterministic models based on the numerical calculation of electromagnetic field provide higher accuracy as well as very high computational intensity which should not be expected now-a-days. So, the ray-tracing technique, which accelerates the computation while achieving the reasonable accuracy, is an appropriate selection for wireless signal prediction. Ray tracing is of vast use in the field of computational electromagnetic, such as the well known shooting and bouncing ray (SBR) algorithm. While designing the wireless networks, it is also crucial to obtain the optimum coverage for indoor environment by using minimum number of transmitting antennas. The purpose of this study is to propose a model that efficiently predicts the trajectory of the radio signal and at the same time can provide optimum wireless coverage. In this regards, this study explores two algorithms. The first algorithm is an efficient and faster ray-tracing technique based on binary angle division for radio signal prediction in indoor environment. And the second algorithm is the optimization technique for indoor wireless coverage. It minimizes the number of transmitters in the corresponding indoor area using a novel integrated approach of the proposed ray-tracing and genetic algorithm (GA). The study mainly focuses on the single floor of a typical building while describing the proposed model. Genetic algorithm is combined with the Breath First Search (BFS) algorithm incorporated with Branch-And-Bound terminology while exploring the search space tree to achieve the optimum coverage solution. BFS is used to generate the search space tree and Branch-And- Bound terminology is to avoid the unnecessary generation of the sub-tree using proposed bounding functions. Some termination criteria have also been presented to make sure the successful termination of the proposed coverage algorithm. The simulation results generated from the proposed ray-tracing technique are compared with the conventional raytracing and the ray launching techniques to prove the superiority of the proposed algorithm in terms of both computational efficiency and accuracy. And it is also found that the proposed ray tracing system achieves better performance in terms of higher computational efficiency of about 22.17% and superior average accuracy of 94% in case of signal prediction compared to other existing techniques. On the other hand, the proposed coverage algorithm outperforms the existing algorithm in terms of both space and time complexities. The proposed coverage algorithm also proves that the computation time is much less than that of the existing algorithm and the difference of computation time between the existing and the proposed algorithm is proportional to the number of total receiving points used in the indoor environment. Moreover, it is also revealed that the proposed coverage algorithm is capable of reducing the computation time as high as 99% because of strong bounding functions as well as the concept of magnificent coverage pattern.

    Item Type: Thesis (Masters)
    Additional Information: Dissertation (M.Eng.)- Faculty of Engineering, University of Malaya, 2011.
    Uncontrolled Keywords: Indoor radio signal prediction; Wireless Radio Networks and Personal Communication Systems (PCS); Signal propagation
    Subjects: T Technology > T Technology (General)
    T Technology > TA Engineering (General). Civil engineering (General)
    Divisions: Faculty of Engineering
    Depositing User: Mr Prabhakaran Balachandran
    Date Deposited: 24 Feb 2018 15:19
    Last Modified: 24 Feb 2018 15:20

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