Algorithmic Exploration and Implementation of a MIMO-OFDM Equalizer
Article
First Online:
Received:
Revised:
Accepted:
- 174 Downloads
Abstract
In this paper we explore algorithms and architectures for the implementation of a MIMO OFDM Equalizer for high speed wireless communications. The algorithmic exploration is based on matrix computations and factorizations. A scalable computational methodology and architecture is proposed for the implementation of a 4×4 MIMO OFDM. A 2×3 Equalizer supporting Maximum Ratio Combining and Zero Forcing equalization for 20/40 MHz 64-QAM OFDM modulation has been implemented in 150 nm technology. The Equalizer area is 133k gates and the maximum throughput achieved is 480Mbits/s. The system described in this paper is compliant with the latest IEEE standard for MIMO wireless communications (802.11n)
Keywords
Wireless communications MIMO-OFDM Equalizers for communication systems Zero Forcing Equalization QR decomposition Matrix factorizations Givens rotations CORDIC arithmeticReferences
- 1.Golub, V. L. (1996). Matrix computations. Baltimore: John Hopkins.MATHGoogle Scholar
- 2.Walther, J. S. (1971). A unified algorithm for elementary functions. In Spring joint computer conf (pp. 379–385).Google Scholar
- 3.Paulaj, et al. (2003). Introduction to space-time wireless communications. Cambridge: Cambridge University Press.Google Scholar
- 4.Hassibi, B., & Vikalo, H. (2003). Maximum-likelihood decoding and integer least-squares: The expected complexity. Providence: American Mathematical Society.Google Scholar
- 5.Heiskala, J., et al. (2001). OFDM wireless LANs: A theoretical and practical guide.Google Scholar
- 6.Paulraj, A. J., et al. (2004). An overview of MIMO communications—a key to gigabit wireless. Proceedings of the IEEE 92(2), 198–218.CrossRefGoogle Scholar
- 7.Zheng, L., & Tse, D. (2003). Diversity and multiplexing: A fundamental tradeoff in multiple-antenna channels. IEEE Transactions on Information Theory, 49(5), 1073–1096.MATHCrossRefGoogle Scholar
- 8.Tarokh, V., et al. (1998). Space-time codes for high data rate wireless communication: Performance criterion and code construction. IEEE Transactions on Information Theory, 44(2), 744–765.MATHCrossRefMathSciNetGoogle Scholar
- 9.Wolniasky, P. W., et al. (1998). V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel. In Proc. URSI ISSSE (pp. 295–300).Google Scholar
- 10.Artes, H., et al. (2003). Efficient detection algorithms for MIMO channels: A geometrical approach to approximate ML detection. IEEE Transactions on Signal Processing, 51(11).Google Scholar
- 11.Tse, D., & Viswanath, P. (2005). Fundamentals of wireless communications.Google Scholar
- 12.Press, W., et al. (1988). Numerical recipes in C. Cambridge: Cambridge University Press.MATHGoogle Scholar
- 13.Trefethen, L., & Bau, D. (1997). Numerical linear algebra. Philadelphia: SIAM.MATHGoogle Scholar
- 14.Rader, C. M. (1996). VLSI systolic arrays for adaptive nulling. IEEE Signal Processing Magazine.Google Scholar
- 15.Burg, A., Felber, N., & Fichter, W. (2003). A 50 Mbps 4×4 maximum likelihood decoder for multiple-input multiple-output systems with QPSK modulation. In Proc. IEEE Int. Conf. Electr., Circuits, Syst. (Vol. 1, pp. 332–335).Google Scholar
- 16.Wong, K., Tsui, C., Cheng, R., & Mow, W. (2002). A VLSI architecture of a K-best lattice decoding algorithm for MIMO channels. In Proc. IEEE ISCAS’02 (Vol. 3, pp. 273–276).Google Scholar
- 17.Guo, Z., & Nilsson, P. (2003). A VLSI implementation of MIMO detection for future wireless communications. In Proc. IEEE PIMRC’03 (Vol. 3, pp. 2852–2856).Google Scholar
- 18.Garrett, D., Woodward, G., Davis, L., Knagge, G., & Nicol, C. (2004). A 28.8 Mb/s 4×4 MIMO 3G high-speed downlink packet access receiver with normalized least mean square equalization. In Proc. IEEE ISSCC’04 (Vol. 1, p. 420).Google Scholar
- 19.Hu, Y. H. (1992). CORDIC based VLSI-architectures for digital signal processing. IEEE Signal Processing Magazine, 16–35.Google Scholar
- 20.Proakis, J. (2000). Digital communications. New York: McGraw-Hill.Google Scholar
- 21.Gore, D., Sandhu, S., & Paulraj, A. (2002). Delay diversity codes for frequency selective channels. In Proceedings of IEEE international conference on communications.Google Scholar
- 22.Bingham, J. (1990). Multicarrier modulation for data transmission: An idea whose time has come. IEEE Communications Magazine, 28(5), 5–14.CrossRefMathSciNetGoogle Scholar
- 23.Burg, A., et al. (2006). Algorithm and VLSI architecture for linear MMSE detection in MIMO-OFDM systems. In IEEE symbosium on circuits and systems, 2006. ISCAS 2006 (pp. 4–8).Google Scholar
- 24.Luethi, P., et al. (2008). Gram-Schmidt-based QR decomposition for MIMO detection: VLSI implementation and comparison. In IEEE Asia Pacific conference on circuits and systems, 2008. APCCAS 2008 (pp. 830–833).Google Scholar
- 25.Luethi, P., et al. (2007). VLSI implementation of a high-speed iterative sorted MMSE QR decomposition. In Proc. of IEEE ISCAS (pp. 1421–1424).Google Scholar
Copyright information
© Springer Science+Business Media, LLC 2009