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Erschienen in: Wireless Personal Communications 4/2015

01.06.2015

Signal Detection in MIMO-OFDM Systems Based on SSDE Algorithm

verfasst von: Fengye Hu, Yu Du, Ling Cen, Kai Ma, Lu Wang

Erschienen in: Wireless Personal Communications | Ausgabe 4/2015

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Abstract

Device-to-device communication enables to improve the application performance of multi-input multi-output (MIMO) technology. In a multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system, its performance is largely reflected by the signal detection algorithm used in receiver. As a sub-optimal maximum likelihood (ML) detection method, the Selective Spanning with Fast Enumeration algorithm can be successfully applied in MIMO-OFDM systems with high-order modulation. However, its Fast Enumeration scheme calculates constellation points based on fixed formula, which tends to yield pseudo constellation points outside of constellation maps, and consequently cannot work well in low-order modulation. To address this, a selective spanning with direct enumeration (SSDE) algorithm is proposed in this paper. Simulation results proved that the SSDE can achieve similar detection performance at a much lower computational cost in comparison with the ML method. The performance in terms of bit error rate (BER) obtained by SSDE method is also superior to those from the Minimum mean square error and Zero forcing detection algorithms with a huge savings in computational load. By adjusting the parameters used in the SSDE, the tradeoff between BER and computation complexity can be flexibly changed to satisfy specific design requirements in different applications.

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Literatur
1.
Zurück zum Zitat 3GPP (2012). Feasibility study for proximity services (prose), In 3GPP, Technical Report; TR 22.803 V0.2.0. 3GPP (2012). Feasibility study for proximity services (prose), In 3GPP, Technical Report; TR 22.803 V0.2.0.
2.
Zurück zum Zitat Song, L., Han, Z., Zhang, Z., & Jiao, B. (2012). Non-cooperative feedback-rate control game for channel state information in wireless networks. Selected Areas in Communications, IEEE Journal on, 30(1), 188–197.CrossRef Song, L., Han, Z., Zhang, Z., & Jiao, B. (2012). Non-cooperative feedback-rate control game for channel state information in wireless networks. Selected Areas in Communications, IEEE Journal on, 30(1), 188–197.CrossRef
3.
Zurück zum Zitat Liu, D. N., & Fitz, M. P. (2008). Low complexity affine MMSE detector for iterative detection-decoding MIMO OFDM systems. IEEE Transactions on Communications, 56(1), 150–158.CrossRef Liu, D. N., & Fitz, M. P. (2008). Low complexity affine MMSE detector for iterative detection-decoding MIMO OFDM systems. IEEE Transactions on Communications, 56(1), 150–158.CrossRef
4.
Zurück zum Zitat Zhang, R., & Cioffi, J. M. (2008). Appraoching MIMO-OFDM capacity with zero-forcing V-BLAST decoding and optimized power, rate, and antenna-mapping feedback. IEEE Transactions on Signal Processing, 56(10), 5191–5203.CrossRefMathSciNet Zhang, R., & Cioffi, J. M. (2008). Appraoching MIMO-OFDM capacity with zero-forcing V-BLAST decoding and optimized power, rate, and antenna-mapping feedback. IEEE Transactions on Signal Processing, 56(10), 5191–5203.CrossRefMathSciNet
5.
Zurück zum Zitat Maddah-Ali, M., & Sadrabadi, M. (2008). Broadcast in MIMO systems based on a generalized QR decomposition: Signaling and performance analysis. IEEE Transactions on Information Theory, 54(3), 1124–1138.CrossRefMathSciNet Maddah-Ali, M., & Sadrabadi, M. (2008). Broadcast in MIMO systems based on a generalized QR decomposition: Signaling and performance analysis. IEEE Transactions on Information Theory, 54(3), 1124–1138.CrossRefMathSciNet
6.
Zurück zum Zitat Wubben, D., & Rohnke, J. (2001). Efficient algorithm for decoding layered space-time codes. IEEE Electronic Letters, 37(22), 1348–1350.CrossRef Wubben, D., & Rohnke, J. (2001). Efficient algorithm for decoding layered space-time codes. IEEE Electronic Letters, 37(22), 1348–1350.CrossRef
7.
Zurück zum Zitat Wubben D., Rohnke J., Kuhn V., & Kammeyer, K. D. (2003). MMSE extension of V-BLAST based on sorted QR decomposition. In IEEE 58th Vehicular Technology Conference (Vol. 1 pp. 508–512). Wubben D., Rohnke J., Kuhn V., & Kammeyer, K. D. (2003). MMSE extension of V-BLAST based on sorted QR decomposition. In IEEE 58th Vehicular Technology Conference (Vol. 1 pp. 508–512).
8.
Zurück zum Zitat Viterbo, E., & Boutros, J. (1999). Universal lattice decoder for fading channel. IEEE Transactions on Information Theory, 54(5), 1639–1642.CrossRefMathSciNet Viterbo, E., & Boutros, J. (1999). Universal lattice decoder for fading channel. IEEE Transactions on Information Theory, 54(5), 1639–1642.CrossRefMathSciNet
9.
Zurück zum Zitat Zhao, W. L., & Giannakis, G. B. (2005). Sphere decoding algorithms with improved radius search. IEEE Transactions on Communications, 54(7), 1104–1109.CrossRef Zhao, W. L., & Giannakis, G. B. (2005). Sphere decoding algorithms with improved radius search. IEEE Transactions on Communications, 54(7), 1104–1109.CrossRef
10.
Zurück zum Zitat Pham, D., Pattipati, K., Willett, P., & Luo, J. (2004). An improved complex sphere decoder for V-BLAST systems. IEEE Signal Processing Letters, 11(9), 748–751.CrossRef Pham, D., Pattipati, K., Willett, P., & Luo, J. (2004). An improved complex sphere decoder for V-BLAST systems. IEEE Signal Processing Letters, 11(9), 748–751.CrossRef
11.
Zurück zum Zitat Hesham, E. G., Giuseppe, C., & Mohamed, O. D. (2004). Lattice coding and decoding achieve the optimal diversity-multiplexing tradeoff of MIMO channels. IEEE Transactions on Information Theory, 50(6), 968–985.CrossRefMATH Hesham, E. G., Giuseppe, C., & Mohamed, O. D. (2004). Lattice coding and decoding achieve the optimal diversity-multiplexing tradeoff of MIMO channels. IEEE Transactions on Information Theory, 50(6), 968–985.CrossRefMATH
12.
Zurück zum Zitat Kyeong, J. K., Jiang, Y., Ronald, A. I., & Jerry, D. G. (2005). A QRD-M/Kalman filter-based detection and channel estimation algorithm for MIMO-OFDM systems channels. IEEE Transactions on Wireless Communications, 4(2), 710–720.CrossRef Kyeong, J. K., Jiang, Y., Ronald, A. I., & Jerry, D. G. (2005). A QRD-M/Kalman filter-based detection and channel estimation algorithm for MIMO-OFDM systems channels. IEEE Transactions on Wireless Communications, 4(2), 710–720.CrossRef
13.
Zurück zum Zitat Zhan, G., & Peter, N. (2006). Algorithm and implementation of the K-best sphere decoding for MIMO detection. IEEE Journal on Selected Areas in Communications, 24(3), 491–503.CrossRef Zhan, G., & Peter, N. (2006). Algorithm and implementation of the K-best sphere decoding for MIMO detection. IEEE Journal on Selected Areas in Communications, 24(3), 491–503.CrossRef
14.
Zurück zum Zitat Chen, S. Z., Zhang, T., & Xin, Y. (2007). Relaxed K-best MIMO signal detector design and VLSI implementation. IEEE Transactions on Very Large Scale Integation (VLSI) Systems, 15(3), 328–337.CrossRef Chen, S. Z., Zhang, T., & Xin, Y. (2007). Relaxed K-best MIMO signal detector design and VLSI implementation. IEEE Transactions on Very Large Scale Integation (VLSI) Systems, 15(3), 328–337.CrossRef
15.
Zurück zum Zitat Shen, C. A., & Eltawil, A. M. (2010). A radius adaptive K-best decoder with early termination: Algorithm and VLSI architecture. IEEE Transactions on Circuits and Systems I, 57(9), 2476–2486.CrossRefMathSciNet Shen, C. A., & Eltawil, A. M. (2010). A radius adaptive K-best decoder with early termination: Algorithm and VLSI architecture. IEEE Transactions on Circuits and Systems I, 57(9), 2476–2486.CrossRefMathSciNet
16.
Zurück zum Zitat Tae, H. I., Park, I., Kim, J., & Yi, J. (2009). A new signal detection method for spatially multiplexed MIMO systems and its VLSI implementation. IEEE Transactions on Circuits and Systems II, 56(5), 399–403.CrossRef Tae, H. I., Park, I., Kim, J., & Yi, J. (2009). A new signal detection method for spatially multiplexed MIMO systems and its VLSI implementation. IEEE Transactions on Circuits and Systems II, 56(5), 399–403.CrossRef
17.
Zurück zum Zitat Li, M., & Bougard, B., et al. (2008). Selective spanning with fast enumeration: A near maximum-likelihood MIMO detector designed for parallel programmable baseband architectures. In IEEE International Conference on Communications (pp. 737–741). Li, M., & Bougard, B., et al. (2008). Selective spanning with fast enumeration: A near maximum-likelihood MIMO detector designed for parallel programmable baseband architectures. In IEEE International Conference on Communications (pp. 737–741).
18.
Zurück zum Zitat Fasthuber, R., Li, M., Novo, D., & Raghavan, P., et al. (2009). Novel energy-efficient scalable soft-output SSFE MIMO detector architectures. In International Symposium on Systems, Architectures, Modeling, and Simulation (pp. 165–171). Fasthuber, R., Li, M., Novo, D., & Raghavan, P., et al. (2009). Novel energy-efficient scalable soft-output SSFE MIMO detector architectures. In International Symposium on Systems, Architectures, Modeling, and Simulation (pp. 165–171).
19.
Zurück zum Zitat Fasthuber, R., Li, M., Novo, D., Raghavan, P., et al. (2011). Exploration of soft-output MIMO detector implementations on massive parallel processors. Journal of Signal Processing Systems, 64(1), 75–92.CrossRef Fasthuber, R., Li, M., Novo, D., Raghavan, P., et al. (2011). Exploration of soft-output MIMO detector implementations on massive parallel processors. Journal of Signal Processing Systems, 64(1), 75–92.CrossRef
20.
Zurück zum Zitat Berenguer, I., & Wang, X. D. (2004). MIMO antenna selection with lattice reduction aided linear receivers. IEEE Transactions on Vehicular Techology, 53(5), 1298–1302. Berenguer, I., & Wang, X. D. (2004). MIMO antenna selection with lattice reduction aided linear receivers. IEEE Transactions on Vehicular Techology, 53(5), 1298–1302.
Metadaten
Titel
Signal Detection in MIMO-OFDM Systems Based on SSDE Algorithm
verfasst von
Fengye Hu
Yu Du
Ling Cen
Kai Ma
Lu Wang
Publikationsdatum
01.06.2015
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2015
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-015-2374-6

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