Table of Contents Author Guidelines Submit a Manuscript
International Journal of Antennas and Propagation
Volume 2012 (2012), Article ID 192964, 9 pages
http://dx.doi.org/10.1155/2012/192964
Research Article

Controlling Initial and Final Radii to Achieve a Low-Complexity Sphere Decoding Technique in MIMO Channels

1Developing Research and Strategic Planning Department, Mobile Communication Company of Iran (MCI), Tehran 199195-4651, Iran
2Digital Communications Signal Processing (DCSP) Research Lab., Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University (SRTTU), Tehran 16788-15811, Iran

Received 2 August 2011; Revised 18 October 2011; Accepted 6 November 2011

Academic Editor: Wenhua Chen

Copyright © 2012 Fatemeh Eshagh Hosseini and Shahriar Shirvani Moghaddam. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G. J. Foschini and M. J. Gans, “On limits of wireless communications in a fading environment when using multiple antennas,” Wireless Personal Communications, vol. 6, no. 3, pp. 311–335, 1998. View at Google Scholar · View at Scopus
  2. R. Kannan, “Improved algorithms on integer programming and related lattice problems,” in Proceedings of the 15th Annual ACM Symposium on Theory of Computing, pp. 193–206, 1983. View at Scopus
  3. J. C. Lagarias, H. W. Lenstra, and C. P. Schnorr, “Korkin-Zolotarev bases and successive minima of a lattice and its reciprocal lattice,” Combinatorica, vol. 10, no. 4, pp. 333–348, 1990. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Pohst, “On the computation of lattice vectors of minimal length, successive minima and reduced bases with applications,” ACM SIGSAM Bulletin, vol. 15, pp. 37–44, 1981. View at Google Scholar
  5. U. Fincke and M. Pohst, “Improved methods for calculating vectors of short length in a lattice, including a complexity analysis,” Mathematics of Computation, vol. 44, pp. 463–471, 1985. View at Google Scholar
  6. E. Viterbo and J. Boutros, “A universal lattice code decoder for fading channels,” IEEE Transactions on Information Theory, vol. 45, no. 5, pp. 1639–1642, 1999. View at Google Scholar · View at Scopus
  7. C. P. Schnorr and M. Euchner, “Lattice basis reduction: improved practical algorithms and solving subset sum problems,” Mathematical Programming, vol. 66, no. 2, pp. 181–191, 1994. View at Google Scholar · View at Scopus
  8. W. Zhao and G. B. Giannakis, “Reduced complexity closest point decoding algorithms for random lattices,” IEEE Transactions on Wireless Communications, vol. 5, no. 1, pp. 101–111, 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. W. Xu, Y. Wang, Z. Zhou, and J. Wang, “A computationally efficient exact ML sphere decoder,” in Proceedings of the IEEE Global Communications Conference, pp. 2594–2598, December 2004. View at Scopus
  10. A. Li, W. Xu, Y. Wang, Z. Zhou, and J. Wang, “A faster ML sphere decoder with competing branches,” in Proceedings of the 61st IEEE Vehicular Technology Conference (VTC '05), pp. 438–441, June 2005. View at Scopus
  11. J. W. Choi, B. Shim, A. C. Singer, and N. I. Cho, “Low-complexity decoding via reduced dimension maximum-likelihood search,” IEEE Transactions on Signal Processing, vol. 58, no. 3, pp. 1–14, 2010. View at Publisher · View at Google Scholar
  12. W. Zhao and G. B. Giannakis, “Sphere decoding algorithms with improved radius search,” IEEE Transactions on Communications, vol. 53, no. 7, pp. 1104–1109, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. R. Gowaikar and B. Hassibi, “Statistical pruning for near-maximum likelihood decoding,” IEEE Transactions on Signal Processing, vol. 55, no. 6 I, pp. 2661–2675, 2007. View at Publisher · View at Google Scholar · View at Scopus
  14. A. D. Murugan, H. El Gamal, M. O. Damen, and G. Caire, “A unified framework for tree search decoding: rediscovering the sequential decoder,” IEEE Transactions on Information Theory, vol. 52, no. 3, pp. 933–953, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. W. K. Ma, T. N. Davidson, K. M. Wong, Z. Q. Luo, and P. C. Ching, “Quasi-maximum-likelihood multiuser detection using semi-definite relaxation with application to synchronous CDMA,” IEEE Transactions on Signal Processing, vol. 50, no. 4, pp. 912–922, 2002. View at Publisher · View at Google Scholar · View at Scopus
  16. E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, “Closest point search in lattices,” IEEE Transactions on Information Theory, vol. 48, no. 8, pp. 2201–2214, 2002. View at Publisher · View at Google Scholar · View at Scopus
  17. M. O. Damen, H. E. Gamal, and G. Caire, “On the complexity of ML detection and the search for the closest lattice point,” IEEE Transactions on Information Theory, vol. 59, no. 10, pp. 2400–2414, 2003. View at Google Scholar
  18. B. Hassibi and H. Vikalo, “On the sphere-decoding algorithm I. expected complexity,” IEEE Transactions on Signal Processing, vol. 53, pp. 2806–2818, 2005. View at Google Scholar
  19. J. Jaldén and B. Ottersten, “On the complexity of sphere decoding in digital communications,” IEEE Transactions on Signal Processing, vol. 53, no. 4, pp. 1474–1484, 2005. View at Publisher · View at Google Scholar · View at Scopus
  20. Y. Wang and K. Roy, “A new reduced-complexity sphere decoder with true lattice—boundary—awareness for multi-antenna systems,” in Proceedings of theIEEE International Symposium on Circuits and Systems (ISCAS '05), pp. 4963–4966, May 2005. View at Publisher · View at Google Scholar · View at Scopus
  21. F. Zhao and S. Qiao, “Radius selection algorithms for sphere decoding,” in Proceedings of the Computational Science and Engineering Workshops, pp. 169–174, Montreal, Canada, 2009. View at Publisher · View at Google Scholar
  22. S. Qiao, “Integer least squares: sphere decoding and the LLL algorithm,” in Proceedings of the Computational Science and Engineering Workshops, vol. 273, pp. 23–28, Montreal, Canada, 2008. View at Publisher · View at Google Scholar
  23. B. Cheng, W. Liu, Z. Yang, and Y. Li, “A new method for initial radius selection of sphere decoding,” in Proceedings of the 12th IEEE International Symposium on Computers and Communications, (ISCC '07), pp. 19–24, Aveiro, Portugal, July 2007. View at Publisher · View at Google Scholar · View at Scopus
  24. J. H. Conway and N. J. A. Sloane, Sphere Packings, Lattices and Groups, Springer, New York, NY, USA, 1988.
  25. J. H. Conway and N. Sloane, Sphere Packings, Lattices and Graphs, Springer, New York, NY, USA, 1993.
  26. Q. Liu and L. Yang, “A novel method for initial radius selection of sphere decoding,” in Proceedings of the IEEE 60th Vehicular Technology Conference, (VTC'04)-Fall, pp. 1280–1283, September 2004. View at Scopus
  27. E. Zimmermann, W. Rave, and G. Fettweis, “On the complexity of sphere decoding,” in Proceedings of the International Conference on Wireless Personal and Multimedia Communications (WPMC’04), Abano Terme, Italy, 2004.
  28. F. E. Hosseini and S. S. Moghaddam, “Initial radius selection of sphere decoder for practical applications of MIMO channels,” in Proceedings of the IEEE Conference on Complexity in Engineering (COMPENG'10), pp. 61–63, Rome, Italy, February 2010. View at Publisher · View at Google Scholar · View at Scopus
  29. W. H. Mow, “Universal lattice decoding: principle and recent advances,” Wireless Communications and Mobile Computing, vol. 3, no. 5, pp. 553–569, 2003. View at Publisher · View at Google Scholar
  30. W. Zhao and G. B. Giannakis, “Reduced complexity closest point decoding algorithms for random lattices,” IEEE Transactions on Wireless Communications, vol. 5, no. 1, pp. 101–111, 2006. View at Publisher · View at Google Scholar · View at Scopus
  31. Z. Ma, B. Honary, P. Fan, and E. G. Larsson, “Stopping criterion for complexity reduction of sphere decoding,” IEEE Communications Letters, vol. 13, no. 6, pp. 402–404, 2009. View at Publisher · View at Google Scholar · View at Scopus