Research Information System
Thesis Type: Postgraduate
Institution Of The Thesis: Gazi University, Fen Bilimleri Enstitüsü, Turkey
Approval Date: 2018
Thesis Language: Turkish
Student: Uğur Yeşilyurt
Supervisor: Özgür Ertuğ
Open Archive Collection: AVESIS Open Access Collection
Abstract:Orthogonal Frequency Division Multiplexing is parallel transmission scheme that is well known for its efficient high-speed transmission and robustness to frequency selective fading channels. On the other hand, Space Division Multiple Access based techniques as a subclass of multiple input multiple output systems have the ability to increase capacity and reliability of a wireless communication system. Hence, the integration of the two technologies have emerged as a most competitive technology for future wireless communication system. At the receiver end of the SDMA-OFDM systems, channel estimation and multiuser detection are very crucial to demodulate the data coherently. For the given receiver structure, various Multiuser Detection schemes have been proposed. Due to the detailed search mechanism, the optimal Maximum Likelihood detector is limited to high computational complexity. On the other hand, Minimum Mean Square Error detector with low complexity has limited performance due to multiple access interference. Different combinations of multiuser detectors focus on the complexity- performance tradeoff for the receiver configurations. In this thesis, hybrid ML-MMSE with SIC adaptive multiuser detection based on joint channel estimation has been proposed and the disadvantages of the above-mentioned classical algorithms have been abolished. Proposed method have achieved significant performance improvement over classical Minimum Mean Square Error at high SNR values and complexity gain over Maximum Likelihood at low SNR values.