Fast Method Nonlinear Fourier Analysis for Optical Communication Systems
Princeton Docket 13-2868-1
Researchers at Princeton University have developed a new fast nonlinear Fourier algorithm for use in optical communication systems. Recent research in the industry has proposed using nonlinear Fourier transform for the extraction of data from the received signal. Similar to the orthogonal frequency division multiplexing (OFDM) used in modern wireless systems, the nonlinear Fourier transform is used to embed data in the eigensignals of the nonlinear channel in this system. Princeton is seeking a commercialization partner to license the technology.
Current optical OFDM technology suppress the nonlinearities of the optical channel so that the usual (liner) Fourier transform can be utilized. This has the major advantage in that the highly efficient fast Fourier transform algorithm can be applied. The downside is that the nonlinearities of the channel cannot be used constructively for the transmission of data. This new method employs the nonlinear Fourier transform so that the nonlinearities of the optical channel can be exploited for data transmission. In the past, the lack of a comparatively fast nonlinear Fourier transform has been identified as a major problem for the practical realization. This new method closes this gap. The method can find the continuous spectrum as well as the discrete spectrum of a signal about an order of magnitude faster than other currently known methods. The method has been implemented and demonstrated via computer simulation.
It is anticipated that this method could be used in optical communication. It may also be useful in scientific software as the method could significantly increase the speed of data analysis or simulations based on the nonlinear Fourier transform.
Applications
· Optical communication
· Scientific software
Advantages
· Able to find continuous and discrete spectrum of a signal
· Faster than current methods
· Improved efficiency
The Faculty Inventor
Vincent Poor is Dean of School of Engineering and Applied Science, and the Michael Henry Strater University Professor of Electrical Engineering at Princeton University. His current research interests lie in the areas of stochastic analysis, statistical signal processing and information theory, and their applications in a number of fields including wireless networks, social networks and smart grid. He is also affiliated with Princeton¿s Program in Applied & Computational Mathematics and its Department of Operations Research and Financial Engineering. Dr. Poor is a member of the National Academy of Engineering and the National Academy of Sciences, a Fellow of the American Academy of Arts & Sciences, and an International Fellow of the Royal Academy of Engineering of the UK. He is also a Fellow of the IEEE, the Institute of Mathematical Statistics, the Optical Society of America, and other scientific and technical organizations. He has served as President of the IEEE Information Theory Society, and as Editor-in-Chief of the IEEE Transactions on Information Theory. He received a Guggenheim Fellowship in 2002 and the IEEE Education Medal in 2005. Recent recognition of his work includes the 2010 IET Ambrose Fleming Medal for Achievement in Communications, the 2011 IEEE Eric E. Sumner Award, the 2011 Society Award of the IEEE Signal Processing Society, and honorary doctorates from the University of Edinburgh and Aalborg University, conferred in 2011 and 2012, respectively.
Intellectual Property status
Patent protection is pending.
Princeton is currently seeking commercial partners for the further development and commercialization of this opportunity.
Contact
Michael R. Tyerech
Princeton University Office of Technology Licensing
(609) 258-6762 tyerech@princeton.edu