Initial Cell Search and Downlink Synchronization Schemes for 3.9G Cellular Systems
| Autor: | Yung-ChuanLin, 林永權 |
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| Rok vydání: | 2012 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 100 In cellular communication systems the mobile station (MS) must perform initial synchronization and search for a base station with best signal quality to set up the downlink access. This process is the well-known initial cell search. The 3.9G mobile wireless wideband technology consists of the Worldwide Interoperability for Microwave Access (WiMAX) and the Long Term Evolution (LTE). IEEE 802.16e is the specifications designed for the WiMAX system in applications of mobile environments. Its time-domain preamble does not have the perfect periodicity for time synchronization. Two synchronization signals, the primary synchronization signal (PSS) and the secondary synchronization signal (SSS), are periodically emitted from the base station in the 3GPP LTE system. In this dissertation all the procedures of synchronization and the initial cell search, including the theoretical analysis and deduction, are provided. Secondly, several innovative algorithms are proposed and their simulations are compared with those of the existing ones. The results confirm that the proposed algorithms are able to reduce the error rates of cell search. Moreover, they can estimate ICFO more accurately and efficiently. Finally, the proposed schemes also reduce the computational complexity. In order to achieve robust performance, one of the most important steps is the channel estimation based on the limited number of pilot signals. Owing to the channel’s time variant characteristics caused by user’s mobility and the irregular arrangement of the pilot signals, the exact channel estimation is more difficult to achieve for the 802.16e system. In this dissertation a DFT-based Channel Estimation is proposed to apply to the WiMAX system. The proposed scheme is capable of providing excellent system performances under various channel environments. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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