Abstract
This paper presents Lattice Sphere Decoding (LSD) with regularization techniques for block data transmission systems. It has shown that a small condition number (\(\tau \)) results in better detection performance. This paper aims to reduce this value to its smallest possible value. Regularization technique offers reduction in condition number (\(\tau \)) that improves LSD performance. In this work, two regularization techniques are utilized on LSD. First, \(\hbox {L}_{1}\)-regularization method is introduced, which sums the mixed norms. Second, \(\hbox {L}_{2}\)- regularization method, which is the most commonly used method of regularization for ill-conditioned problems in mathematics. We derive the exact relationship between the LSD performance and condition number (\(\tau \)) as well as the relationship between LSD initial radius (d) and condition number (\(\tau \)). The derived equations show their convergence to the fact that the performance increases as the radius (d) increases. Simulation results show that the LSD with \(\hbox {L}_{1}\)-regularization technique offers smaller condition number (\(\tau \)), and therefore, produces better system performance. From the performance results and the complexity analysis, it is apparent that the proposed techniques achieve a good balance between complexity and performance.
Similar content being viewed by others
References
Albreem, M. A. M., & Salleh, M. F. M. (2014). Lattice sphere decoding technique for block data transmission systems with special channel matrices. Wireless Personal Communications, 79(1),265–277.
Li, X., & Cui, X. (2004). Application of lattice code decoder to SC-CP for short block length. Electronics Letters, 40(15), 954–956.
Albreem, M. A. M., Salleh, M. F. M., & Babu, S. P. K. (2011). Reduced complexity optimum detector for block data transmission systems using lattice sphere decoding technique. IEICE Electronics Express (ELEX), 8(9), 644–650.
Higham, D. J. (1995). Condition numbers and their condition numbers. Linear Algebra and its Applications, 214, 193–214.
Artes, H., Seethaler, D., & Hlawatsch, F. (2003). Efficient detection algorithms for MIMO channels: A geometrical approach to approximate ML detection. IEEE Transactions on Signal Processing, 51(11), 2808–2820.
Conway, J. H., & Sloane, N. J. A. (1999). Sphere packings: Lattices and groups. New York: Springer.
Stewart, G. W. (1973). Introduction to matrix computations. London and New York: Academic Press.
Karayiannis, N. B., & Chookiarti, J. (2005). Regularized adaptive detectors for code-division multiple-access signals. IEEE Transactions on Wireless Communications, 4(4), 1749–1758.
Rugini, L., Banelli, P., & Cacopardi, S. (2005). A full-rank regularization technique for MMSE detection in multiuser CDMA systems. IEEE Communication Letters, 9(1), 34–36.
Jalden, J., & Elia, P. (2010). DMT optimality of LR-aided linear decoders for a general class of channels, lattice designs, and system models. IEEE Transactions on Information Theory, 56(10), 4765–4779.
Kim, S. J., Koh, K., Boyd, S., & Gorinevsky, D. (2007). An interior-point method for large-scale \({L}_{1}\)-regularized least squares. IEEE Journal of Selected Topics in Signal Processing, 1(4), 606–617.
Zhu, H., & Giannakis, G. (2011). Exploiting sparse user activity in multiuser detection. IEEE Transactions on Communications, 59(2), 454–465.
Hassibi, B., & Vikalo, H. (2008). On the sphere-decoding algorithm I. expected complexity. IEEE Transactions on Signal Processing, 53(8), 2806–2818.
Kora, A., Saemi, A., Cances, J., & Meghdadi, V. (2008). New list sphere decoding (LSD) and iterative synchronization algorithms for MIMO-OFDM detection with LDPC FEC. IEEE Transactions on Vechular Technology, 57(6), 3510–3524.
Damen, M. O., Gamel, H. E., & Caire, G. (2003). On maximum-likelihood detection and the search for the closest lattice point. IEEE Transactions on Information Theory, 49(10), 2389–2402.
Agrell, E., Eriksoon, T., Vardy, A., & Zeger, K. (2002). Closest point search in lattices. IEEE Transactions on Information Theory, 48(8), 2201–2214.
Zhao, F. (2009). Adaptive sphere decoding and radius selection with error analysis in sphere decoding. MSc. Thesis, McMaster University.
Albreem, M. A. M., & Salleh, M. F. M. (2013). Near-\(A_n\)-lattice sphere decoding technique assisted optimum detection for block data transmission systems. IEICE Transaction on Communications, E96–B(01), 356–359.
Kreyszig, E. (2011). Advanced engineering mathematics (10th ed.). New York: Wiley.
Lee, E. A. (1994). Digital communication. Alphen aan den Rijn: Kluwer Academic.
Tse, D., & Viswanath, P. (2005). Fundamental of wireless communication. Cambridge: Cambridge University Press.
Acknowledgments
The authors would like to thank the University Malaysia Perlis (UniMAP), University Science Malaysia (USM) and Ministry of Higher Education “Malaysia” for their financial supports.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Albreem, M.A.M., Salleh, M.F.M. Regularized Lattice Sphere Decoding for Block Data Transmission Systems. Wireless Pers Commun 82, 1833–1850 (2015). https://doi.org/10.1007/s11277-015-2317-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-015-2317-2