Abstract
In this paper we propose the design of communication systems based on using periodic nonlinear Fourier transform (PNFT), following the introduction of the method in the Part I. We show that the famous "eigenvalue communication" idea [A. Hasegawa and T. Nyu, J. Lightwave Technol. 11, 395 (1993)] can also be generalized for the PNFT application: In this case, the main spectrum attributed to the PNFT signal decomposition remains constant with the propagation down the optical fiber link. Therefore, the main PNFT spectrum can be encoded with data in the same way as soliton eigenvalues in the original proposal. The results are presented in terms of the bit-error rate (BER) values for different modulation techniques and different constellation sizes vs. the propagation distance, showing a good potential of the technique.
Highlights
IntroductionIn the Part I of this work we described the periodic nonlinear Fourier transform (PNFT) peculiarities, introduced the most important quantities (main and auxiliary spectra) resulting from the PNFT periodic signal decomposition, and explained the differences arising when dealing with the PNFT compared to its “ordinary” counterpart — the NFT attributed to burst-mode (or truncated at the time interval boundaries) signals
In the Part I of this work we described the periodic nonlinear Fourier transform (PNFT) peculiarities, introduced the most important quantities resulting from the PNFT periodic signal decomposition, and explained the differences arising when dealing with the PNFT compared to its “ordinary” counterpart — the NFT attributed to burst-mode signals
Using the PNFT it is possible to map data on the nonlinear spectrum (NS) according to some deterministic one-to-one mapping rule, synthesize the signal corresponding to this modulated NS in time domain, and launch the signal into the fiber; at the receiver side one uses the direct PNFT and retrieves the encoded data from the NS
Summary
In the Part I of this work we described the PNFT peculiarities, introduced the most important quantities (main and auxiliary spectra) resulting from the PNFT periodic signal decomposition, and explained the differences arising when dealing with the PNFT compared to its “ordinary” counterpart — the NFT attributed to burst-mode (or truncated at the time interval boundaries) signals. We itemized the potential advantages of using the PNFT against the burst-mode NFT in the optical transmission As it was explained in Part I, the utilization of periodic signals can bring noticeable benefits in terms of the reduction of the processing complexity and the capability of control over the generated signal time-extent, much less attention has been paid to the PNFT applications due to a more complex mathematical background involved. In this regard we would like to mention a very resent paper of Wahls and Poor [1], where a quite exhaustive survey of the PNFT theory and numerical methods including the newest fast direct PNFT decomposition algorithms, was presented, perhaps aside from the computation of theta-functions (see subsection 4.2 of our Part I).
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