Research Article
Efficient Implementation of Complex Matrix Inversion for LMMSE Decoder
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 178 - Issue 20 |
| Published: Jun 2019 |
| Authors: Vijaykumar S. Shirwal, Mahesh S. Chavan |
10.5120/ijca2019918991
|
Vijaykumar S. Shirwal, Mahesh S. Chavan . Efficient Implementation of Complex Matrix Inversion for LMMSE Decoder. International Journal of Computer Applications. 178, 20 (Jun 2019), 12-17. DOI=10.5120/ijca2019918991
@article{ 10.5120/ijca2019918991,
author = { Vijaykumar S. Shirwal,Mahesh S. Chavan },
title = { Efficient Implementation of Complex Matrix Inversion for LMMSE Decoder },
journal = { International Journal of Computer Applications },
year = { 2019 },
volume = { 178 },
number = { 20 },
pages = { 12-17 },
doi = { 10.5120/ijca2019918991 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2019
%A Vijaykumar S. Shirwal
%A Mahesh S. Chavan
%T Efficient Implementation of Complex Matrix Inversion for LMMSE Decoder%T
%J International Journal of Computer Applications
%V 178
%N 20
%P 12-17
%R 10.5120/ijca2019918991
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In the high speed wireless communication system most commonly used linear detector is a linear minimum mean square error (LMMSE) due to its low complexity. In this paper the decoder is designed for the MIMO-OFDM based system considering the mobile terminal downlink scenario. This MIMO decoder demands the complex matrix inversion. To invert large matrices, systolic array based QR decomposition (QRD) is usually used. However, the matrices involved in MIMO-OFDM based mobile terminal is generally small, hence QRD is not necessarily efficient. In this paper a proposed complex matrix inversion method is Alamouti blockwise analytic matrix inversion (ABAMI), which achieves good trade-off between performance and silicon area compared to the prior work. This matrix inversion method used to implement LMMSE decoder makes it more flexible and faster.
References
- S. M. Alamouti, “A simple transmit diversity technique for wireless communications,” IEEE Journal on Sel. Areas in Comm., vol. 16, no. 8, pp. 451–1458, Oct. 1998.
- J. Andrews, A. Ghosh and R. Muhamed, “ Fundamentals of WiMAX: Understanding Broadband Wireless Networking”, Prentice Hall, Mar 2007.
- Golub, Gene H. and Charles F. Van Loan, “Matrix Computations”, Vol. 3, JHU Press, 2012.
- Lei Ma; Kevin Dickson; John McAllister; John McCanny, “QR Decompostion based matrix inversion for high performance embedded MIMO receivers”, IEEE Transactions on Signal Processing Volume 59, Issue -4 , April 2011, pp 1858 – 1867.
- D. Wu, J. Eilert, D. Liu, D. Wang, N. AI-Dhahir and H. Minn, “Fast Complex Valued Matrix Inversion for Multi-User STBC-MIMO Decoding”, Proc. IEEE ISVLSI, 2007.
- F. Edman, V. Ӧwall, “ A Scalable Pipelined Complex Valued Matrix Inversion Architecture”, Proc. IEEE ISCAS, 2005.
- M. Myllylӓ, J. Hintikka, J. R. Cavallaro and M. Junti, M. Limingoja, A. Byman, “Complexity Analysis of MMSE Detector Architectures for MIMO OFDM Systems”, Proc. 39th Asilomer Conference on Signals, Systems and Computers, 2005.
- J. Eilert, D. Wu, D. Liu, “Implementation of a Programmable Linear MMSE Detector for MIMO-OFDM”, invited paper, IEEE ICASSP 2008.
- J. Eilert, D Wu, D. Liu, “ Real-Time Alamouti STBC Decoding on A Programmable Baseband Processor”, Proc. IEEE ICCSC, 2008.
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