Cognitive network selection mechanism for multiple wireless broadband technologies /
The advancement in communication technology has allowed many wireless broadband services to be introduced into the market. Among them are enhanced data rates for GSM evolution (EDGE), high speed packet access (HSPA), global packet radio system (GPRS), universal mobile telecommunications system (UMTS...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
Kuala Lumpur:
Kulliyyah of Engineering, International Islamic University Malaysia,
2013
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| Subjects: | |
| Online Access: | Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library. |
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| Summary: | The advancement in communication technology has allowed many wireless broadband services to be introduced into the market. Among them are enhanced data rates for GSM evolution (EDGE), high speed packet access (HSPA), global packet radio system (GPRS), universal mobile telecommunications system (UMTS), wireless fidelity (WiFi), worldwide interoperability for microwave access (WiMAX) and the newest is long term evolution (LTE) services. A good connectivity is expected to be realized for users within the multitude of wireless broadband networks. However, there is disagreement among service providers to merge various broadband connections into a system. Therefore, there should be an embedded mechanism capable of intelligently select the best networks without adding the complexity at user‟s terminal. This concept can be a trade-off to achieve best connectivity. The main motivation of this research is to develop the solution that has the capability to optimize the decision making of the best network. This research establishes four selection algorithms to be embedded in the access point mechanism while considering the mobile broadband technologies such as HSPA, WiMAX and WiFi. These four algorithms were formulated according to the principle of heuristic selection algorithm. Speed variation can be observed through the average connection speed gathered for one month using non-mobile terminal. This proves the initial assumption of this research that data connection varies even when the user/terminal is stationary. Thus, connection speed was established as the indicator for good connectivity. The research findings had shown that the first and third algorithm have shown the capability to achieve good connectivity. The fourth algorithm has shown better connection delay as compared to the other algorithms. In a nutshell, this research had proven that cognitive network selection mechanism deploying the concept of cognitive radio (CR) and artificial intelligence (AI) embedded in actual user platform can be realized. |
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| Physical Description: | xvii, 118 leaves : ill. ; 30cm. |
| Bibliography: | Includes bibliographical references (leaves 97-101). |