Universal Lattice Detection / Sphere Decoding / Lattice Sequence Estimation

Pohst's lattice point enumeration algorithm (widely known as sphere decoding, and also called universal lattice decoding) has recently attracted much attention in the communications community. We pioneered the idea of formulating a communication detection problem as a closest (lattice) vector problem in the early 1990's. Instead of invoking the Markovian property of the ISI channel as in Forney's trellis-based MLSE solution (commonly called Viterbi equalizer), the linearity of the channel and the lattice structure of the modulation are exploited leading to what-we-called the lattice sequence estimator. The latter has been rediscovered for multiuser detection, MIMO ISI channels, etc. To the best of our knowledge, the following list included the earliest publication on the topic. 

1. W.H. Mow,《 Maximum Likelihood Sequence Estimation from the Lattice Viewpoint》, MPhil Thesis, Dept. of Information Engineering, Chinese University of Hong Kong, June 1991.

2. W.H. Mow, "Maximum Likelihood Sequence Estimation from the Lattice Viewpoint," Proc. 1992 International Symposium on Information Theory and its Applications (ISITA'92), Singapore, November 1992, pp. 127-131.

3. W.H. Mow, "Performance of the Lattice Sequence Estimator", Proc. 1994 IEEE International Symposium on Information Theory (ISIT'94), Norway, June/July 1994, pp. 176.

4. W.H. Mow, "Maximum Likelihood Sequence Estimation From the Lattice Viewpoint", IEEE Transactions on Information Theory, Vol. 40, September 1994, pp. 1591-1600. 

5. Wong Kwan Wai, Chi-Ying Tsui, Roger S. Cheng, Wai Ho Mow, "Reduced-Complexity Maximum Likelihood Lattice Decoder for MIMO Channels", Proc. 7^th Asia-Pacific Conference on Communications (APCC'2001), Tokyo, Japan, September 17-20, 2001. 

6. Wong Kwan Wai, Chi-Ying Tsui, Roger S. Cheng, Wai Ho Mow, "A VLSI Architecture of a K-Best Lattice Decoding Algorithm for MIMO Channels", Proc. IEEE International Symposium on Circuits and Systems (ISCAS'2002), Scotsdale, Arizona, U.S.A, May 26-29, 2002. 

7. W.H. Mow, "Universal Lattice Decoding: Principle and Recent Advances", Wireless Communications and Mobile Computing, Special Issue on Coding and Its Applications in Wireless CDMA Systems, Vol.3, Issue 5, August 2003, pp. 553-569.

8. Wai Ho Mow, "Principle of Universal Lattice Decoding," Proceedings of the 13^th Annual Wireless & Optical Communication Conference (WOCC'04), Taipei & Tainan, Taiwan, Mar. 8-10, 2004. Available at http://www.wocc.org/wocc2004/2004program_doc/930309P-W1.pdf.

9. Wai Ho Mow, "Universal Lattice Decoding: a Review and Some Recent Results," Proc. 2004 International Conference on Communications (ICC'04), Paris, France, June 20-24, 2004.

10. Wai Ho Mow, "Universal Lattice Decoding," 2005 IEEE Taiwan/Hong Kong Joint Workshop on Information Theory and Communications, Hong Kong, Jan. 20-21, 2005.

11. Cong Ling, Wai Ho Mow, Kwok H. Li and Alex C. Kot, "Differential Lattice Decoding in Noncoherent MIMO Communication", International Conference on Communications (ICC'05), Seoul, Korea, May 16-20, 2005. 

12. Jie Jin, C. Y. Tsui and W. H. Mow, "A Threshold-based Algorithm and VLSI Architecture of a K-Best Lattice Decoder for MIMO Systems," 2005 IEEE International Symposium on Circuits and Systems (ISCAS'05), Kobe, Japan, May 23-26, 2005.

13. Ying Hung Gan and Wai Ho Mow, "Accelerated Complex Lattice Reduction Algorithms Applied to MIMO Detection", 2005 IEEE Global Telecommunications Conference (Globecom'05), Missouri, USA, Nov. 28- Dec. 2, 2005.

14. Wai Ho Mow, "Lattice Decoding in Communications: Complex is Less Complex," 2006 Taiwan-Hong Kong Joint Workshop on Information Theory & Communications, Hsinchu, Taiwan, August 28-29, 2006.

15. Ling Cong, Lu Gan and Wai Ho Mow, "A Dual Lattice View of V-BLAST Detection", 2006 IEEE Information Theory Workshop (ITW'06), Chengdu, China, October 22-26, 2006. 

16. Ying Hung Gan and Wai Ho Mow, "Novel Joint Sorting and Lattice Reduction for Delay-Constrained LLL-reduction-aided MIMO Detection", IEEE Signal Processing Letters, vol. 15, 2008, pp. 194-197.

17. Ying Hung Gan, Cong Ling and Wai Ho Mow, "Complex Lattice Reduction Algorithm for Low-Complexity MIMO Detection", IEEE Transactions on Signal Processing, Vol.57, No.7, July 2009.

18. Wai Ho Mow and Ling Cong, "A Class of Efficient MIMO Detectors Based on the Notion of Partial Lattice Reduction," 2009 Taiwan/Hong Kong/Macau Joint Workshop on Information Theory & Communications, Macau, China, 10-11 August 2009.

19. Ling Cong and Wai Ho Mow, "A Unified View of Sorting in Lattice Reduction: From V-BLAST to LLL and Beyond," 2009 IEEE Information Theory Workshop (ITW'09), Taormina, Sicily, Italy, Oct 11-16, 2009.

20. Ling Cong, Wai Ho Mow, and Lu Gan, "Dual-Basis Ordering and Partial Lattice Reduction for MIMO Detection", IEEE Journal on Selected Topics in Signal Processing, Special Issue on Managing Complexity in Multiuser MIMO Systems, Vol.3, No.6, December 2009, pp. 975-985.

21. Ling Cong, Wai Ho Mow and Nick Howgrave-Graham, "Reduced and Fixed-Complexity Variants of the LLL Algorithm for Communications", IEEE Transactions on Communications, Vol. 61, No. 3, Mar 2013, pp. 2104-2113.