Near optimal performance joint semi-blind channel estimation and data detection techniques for Alamouti coded single-carrier (SC) MIMO communication systems |
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| Institution: | 1. Department of Electronics & Communication Engineering, Charotar University of Science and Technology, Changa-388421, Gujarat, India;2. Marwari group of Institute, Rajkot, Gujarat, India;3. Department of Electrical Engineering, Faculty of Technology M.S. University, Baroda, Gujarat, India;1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China;2. IoT Research Center, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China;3. Centre for VLSI and Embedded System Technologies, International Institute of Information Technology, Hyderabad, Telangana 500032, India;4. Department of Science and Engineering, Novel Global Community Educational Foundation, Hebersham, NSW 2770, Australia;5. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China;6. Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Technology Research Center, Chengdu University of Technology, Chengdu, China;7. Department of Studies in Computer Science, University of Mysore, Manasagangothri, Mysore, India;8. Department of Artificial Intelligence, College of Software & Convergence Technology, Daeyang AI Center, Sejong University, Seoul 05006, Republic of Korea;1. College of Computer and Information, Hohai University, Nanjing, Jiangsu, 210098, PR China;2. Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huaian, Jiangsu, 223003, PR China;2. Turku University of Applied Sciences, Turku, Finland;3. Nokia, Espoo, Finland |
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| Abstract: | In this paper, two novel joint semi-blind channel estimation and data detection techniques are proposed and investigated for Alamouti coded single-carrier (SC) multiple-input multiple-output (MIMO) communication system using Rayleigh flat fading channel model. In the first novel semi-blind technique, blind channel estimation can be performed by using singular value decomposition (SVD) of received output autocorrelation matrix and training based channel estimation for orthogonal training symbols can be performed by using orthogonal pilot maximum likelihood (OPML) algorithm. Further using, that semi-blind channel estimate and received output, data detection is performed by using Maximum likelihood (ML) detection. Finally we derived new training symbols from error covariance matrix of estimated data and known orthogonal training symbols, which further applied to OPML algorithm for final channel estimate. In the second novel semi-blind technique, blind channel estimation can be performed by using matrix triangularization based on householder QR decomposition (H-QRD) of received output autocorrelation matrix instead of SVD decomposition. Other steps are same as the first novel technique to calculate data detection and final channel estimation. Simulation results are presented under 2-PSK, 4-PSK, 8-PSK and 16-QAM data modulation schemes using 2 transmitters and different combinations of receiver antennas to investigate the performances of novel techniques compare to conventional whitening rotation (WR) and rotation optimization maximum likelihood (ROML) based semi-blind channel estimation techniques. Result demonstrates that novel techniques outperform others by achieving near optimal performance. |
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