In the current era of telecommunication the usage of cellular network has increased rapidly. Number of different new services are introduced i.e. navigation, friend finder, internet browsing, nearby filling stations, shopping centers, traffic information and emergency services. Most of these services are location based and needs the information of particular area to provide the exact services. The addition of location based services in 3G network opens the new ways of using Mobile devices due to which cellular networks has faced number of challenges in providing better positioning accuracy which is the main requirement for location based services. To bear these challenges everyday new ways of finding the accurate position are introduced but most them required upgraded networks or highly equipped terminal. In this thesis the purpose is to find the potential in UMTS signaling data to estimate the position of the user equipment as accurate as possible using the legacy terminals. In this thesis SFN-SFN observed time difference is explored and used in Database Correlation Method (DCM) in network based positioning. This thesis is done by first analyzing the RSCP for the particular area to verify the conditions of FCC. The data is collected in real environment through test drive using TEMS investigation tool and the available measurement reports from the terminal are used to design and implement the DCM Algorithm. Two new approaches are introduced in this thesis SFN-SFN OTD and Hybrid. In Hybrid RSCP and SFN-SFN OTD are used together. In conclusion, the final results from the performed experiments show improvement in estimated position accuracy by Hybrid technique which is a new step in finding the position of user equipment by DCM.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-73120 |
Date | January 2011 |
Creators | Akram, Awais, Ahmad, Hamad |
Publisher | Linköpings universitet, Institutionen för teknik och naturvetenskap, Linköpings universitet, Institutionen för teknik och naturvetenskap |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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