Thesis Type: Postgraduate
Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Electrical and Electronics Engineering, Turkey
Approval Date: 2008
Student: MUHAMMET AVAN
Supervisor: ÇAĞATAY CANDANAbstract:
In this thesis study, joint frequency offset and channel estimation methods for single-input single-output (SISO) systems are examined. The performance of maximum likelihood estimate of the parameters are studied for different training sequences. Conventionally training sequences are designed solely for the channel estimation purpose. We present a numerical comparison of different training sequences for the joint estimation problem. The performance comparisons are made in terms of mean square estimation error (MSE) versus SNR and MSE versus the total training energy metrics. A novel estimation scheme using complementary sequences have been proposed and compared with existing schemes. The proposed scheme presents a lower estimation error than the others in almost all numerical simulations. The thesis also includes an extension for the joint channel-frequency offset estimation problem to the multi-input multi-output systems and a brief discussion for multiple frequency offset case is also given.