Linear Support Vector Machines for Error Correction in Optical Data Transmission
Reduction of bit error rates in optical transmission systems is an important task that is difficult to achieve. As speeds increase, the difficulty in reducing bit error rates also increases. Channels have differing characteristics, which may change over time, and any error correction employed must be capable of operating at extremely high speeds. In this paper, a linear support vector machine is used to classify large-scale data sets of simulated optical transmission data in order to demonstrate their effectiveness at reducing bit error rates and their adaptability to the specifics of each channel. For the classification, LIBLINEAR is used, which is related to the popular LIBSVM classifier. It is found that it is possible to reduce the error rate on a very noisy channel to about 3 bits in a thousand. This is done by a linear separator that can be built in hardware and can operate at the high speed required of an operationally useful decoder.
KeywordsError correction classification optical communication adaptive signal processing
Unable to display preview. Download preview PDF.
- 1.Bernstein, G., Rajagopalan, B., Saha, D.: Optical Network Control: Architecture, Protocols, and Standards. Addison Wesley (August 2003)Google Scholar
- 2.Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines (2001)Google Scholar
- 3.Collobert, R., Bengio, S.: Links between perceptrons, mlps and svms. In: Brodley, C.E. (ed.) ICML. ACM International Conference Proceeding Series, vol. 69. ACM (2004)Google Scholar
- 4.Harry, J.R.: Dutton. Understanding optical communications. Prentice Hall PTR (1998)Google Scholar
- 6.Hunt, S., Sun, Y., Shafarenko, A., Adams, R., Davey, N., Slater, B., Bhamber, R., Boscolo, S., Turitsyn, S.K.: Correcting Errors in Optical Data Transmission Using Neural Networks. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds.) ICANN 2010, Part II. LNCS, vol. 6353, pp. 448–457. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 7.Hunt, S., Sun, Y., Shafarenko, A., Adams, R., Davey, N., Slater, B., Bhamber, R., Boscolo, S., Turitsyn, S.K.: Adaptive Electrical Signal Post-processing with Varying Representations in Optical Communication Systems. In: Palmer-Brown, D., Draganova, C., Pimenidis, E., Mouratidis, H. (eds.) EANN 2009. CCIS, vol. 43, pp. 235–245. Springer, Heidelberg (2009)CrossRefGoogle Scholar
- 8.Maliuk, D., Stratigopoulos, H.-G., Makris, Y.: An analog vlsi multilayer perceptron and its application towards built-in self-test in analog circuits. In: Proceedings of the 2010 IEEE 16th International On-Line Testing Symposium, IOLTS 2010, pp. 71–76. IEEE Computer Society, Washington, DC (2010)CrossRefGoogle Scholar
- 9.Nielsen, J.: Nielsen’s law of internet bandwidth (1998), http://www.useit.com/alertbox/980405.html
- 10.Sun, Y., Shafarenko, A., Adams, R., Davey, N., Slater, B., Bhamber, R., Boscolo, S., Turitsyn, S.K.: Adaptive electrical signal Post-Processing in optical communication systems (2008)Google Scholar