The Experts below are selected from a list of 30 Experts worldwide ranked by ideXlab platform
S K Turitsyn - One of the best experts on this subject based on the ideXlab platform.
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optimal Input Signal distribution and capacity for nondispersive nonlinear optical fiber channel at large Signal to noise ratio
Nonlinear Optics and its Applications 2018, 2018Co-Authors: I S Terekhov, Alexey Reznichenko, S K TuritsynAbstract:We consider a model nondispersive nonlinear optical fiber channel with additive Gaussian noise at large SNR (Signal-to-noise ratio) in the intermediate power region. Using Feynman path-integral technique we find the optimal Input Signal distribution maximizing the channel's per-sample mutual information. The finding of the optimal Input Signal distribution allows us to improve previously known estimates for the channel capacity. We show that in the intermediate power regime the per-sample mutual information for the optimal Input Signal distribution is greater than the per-sample mutual information for the Gaussian and half-Gaussian Input Signal distributions.
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optimal Input Signal distribution and per sample mutual information for nondispersive nonlinear optical fiber channel in large snr limit
arXiv: Information Theory, 2015Co-Authors: I S Terekhov, A V Reznichenko, Ya A Kharkov, S K TuritsynAbstract:We consider a model nondispersive nonlinear optical fiber channel with additive white Gaussian noise at large $\mathrm{SNR}$ (Signal-to-noise ratio) in the intermediate power region. Using Feynman path-integral technique we for the first time find the optimal Input Signal distribution maximizing the channel's per-sample mutual information. The finding of the optimal Input Signal distribution allows us to improve previously known estimates for the channel capacity. The output Signal entropy, conditional entropy, and per-sample mutual information are calculated for Gaussian, half-Gaussian and modified Gaussian Input Signal distributions. We explicitly show that in the intermediate power regime the per-sample mutual information for the optimal Input Signal distribution is greater than the per-sample mutual information for the Gaussian and half-Gaussian Input Signal distributions.
I S Terekhov - One of the best experts on this subject based on the ideXlab platform.
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optimal Input Signal distribution and capacity for nondispersive nonlinear optical fiber channel at large Signal to noise ratio
Nonlinear Optics and its Applications 2018, 2018Co-Authors: I S Terekhov, Alexey Reznichenko, S K TuritsynAbstract:We consider a model nondispersive nonlinear optical fiber channel with additive Gaussian noise at large SNR (Signal-to-noise ratio) in the intermediate power region. Using Feynman path-integral technique we find the optimal Input Signal distribution maximizing the channel's per-sample mutual information. The finding of the optimal Input Signal distribution allows us to improve previously known estimates for the channel capacity. We show that in the intermediate power regime the per-sample mutual information for the optimal Input Signal distribution is greater than the per-sample mutual information for the Gaussian and half-Gaussian Input Signal distributions.
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optimal Input Signal distribution and per sample mutual information for nondispersive nonlinear optical fiber channel in large snr limit
arXiv: Information Theory, 2015Co-Authors: I S Terekhov, A V Reznichenko, Ya A Kharkov, S K TuritsynAbstract:We consider a model nondispersive nonlinear optical fiber channel with additive white Gaussian noise at large $\mathrm{SNR}$ (Signal-to-noise ratio) in the intermediate power region. Using Feynman path-integral technique we for the first time find the optimal Input Signal distribution maximizing the channel's per-sample mutual information. The finding of the optimal Input Signal distribution allows us to improve previously known estimates for the channel capacity. The output Signal entropy, conditional entropy, and per-sample mutual information are calculated for Gaussian, half-Gaussian and modified Gaussian Input Signal distributions. We explicitly show that in the intermediate power regime the per-sample mutual information for the optimal Input Signal distribution is greater than the per-sample mutual information for the Gaussian and half-Gaussian Input Signal distributions.
Aris L Moustakas - One of the best experts on this subject based on the ideXlab platform.
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on the soliton spectral efficiency in non linear optical fibers
International Symposium on Information Theory, 2016Co-Authors: Pavlos Kazakopoulos, Aris L MoustakasAbstract:Optical fiber communications can be modeled using the non-linear Schrodinger equation, which is integrable. In this paper we show how integrability can be exploited to communicate using multisoliton pulses. Starting with a white Gaussian Input Signal, we use the known distributions of eigenvalues and scattering data to derive an analytical expression for a lower bound to the spectral efficiency, taking into account the effects of noise due to amplification explicitly. We show that in the low noise regime, the soliton channel shows two different behaviors, interpolated by a single scalar parameter that controls the nonlinearity of the system. In the linear regime the soliton channel approaches an additive white Gaussian noise channel, while for strongly nonlinear systems the bound declines. The bound reaches a maximum between the two regions.
David J Moss - One of the best experts on this subject based on the ideXlab platform.
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photonic radio frequency and microwave intensity differentiator based on an optical frequency comb source in an integrated micro ring resonator
arXiv: Applied Physics, 2017Co-Authors: Mehrdad Shoeiby, Thach G Nguyen, Sai T Chu, Brent E Little, Roberto Morandotti, Arnan Mitchell, David J MossAbstract:We propose and experimentally demonstrate a microwave photonic intensity differentiator based on a Kerr optical comb generated by a compact integrated micro-ring resonator (MRR). The on-chip Kerr optical comb, containing a large number of comb lines, serves as a high-performance multi-wavelength source for implementing a transversal filter, which will greatly reduce the cost, size, and complexity of the system. Moreover, owing to the compactness of the integrated MRR, frequency spacings of up to 200-GHz can be achieved, enabling a potential operation bandwidth of over 100 GHz. By programming and shaping individual comb lines according to calculated tap weights, a reconfigurable intensity differentiator with variable differentiation orders can be realized. The operation principle is theoretically analyzed, and experimental demonstrations of first-, second-, and third-order differentiation functions based on this principle are presented. The radio frequency (RF) amplitude and phase responses of multi-order intensity differentiations are characterized, and system demonstrations of real-time differentiations for a Gaussian Input Signal are also performed. The experimental results show good agreement with theory, confirming the effectiveness of our approach.
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reconfigurable broadband microwave photonic intensity differentiator based on an integrated optical frequency comb source
APL Photonics, 2017Co-Authors: Mehrdad Shoeiby, Thach G Nguyen, Sai T Chu, Brent E Little, Roberto Morandotti, Arnan Mitchell, David J MossAbstract:We propose and experimentally demonstrate a microwave photonic intensity differentiator based on a Kerr optical comb generated by a compact integrated micro-ring resonator (MRR). The on-chip Kerr optical comb, containing a large number of comb lines, serves as a high-performance multi-wavelength source for implementing a transversal filter, which will greatly reduce the cost, size, and complexity of the system. Moreover, owing to the compactness of the integrated MRR, frequency spacings of up to 200-GHz can be achieved, enabling a potential operation bandwidth of over 100 GHz. By programming and shaping individual comb lines according to calculated tap weights, a reconfigurable intensity differentiator with variable differentiation orders can be realized. The operation principle is theoretically analyzed, and experimental demonstrations of the first-, second-, and third-order differentiation functions based on this principle are presented. The radio frequency amplitude and phase responses of multi-order intensity differentiations are characterized, and system demonstrations of real-time differentiations for a Gaussian Input Signal are also performed. The experimental results show good agreement with theory, confirming the effectiveness of our approach.
Alexey Reznichenko - One of the best experts on this subject based on the ideXlab platform.
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optimal Input Signal distribution and capacity for nondispersive nonlinear optical fiber channel at large Signal to noise ratio
Nonlinear Optics and its Applications 2018, 2018Co-Authors: I S Terekhov, Alexey Reznichenko, S K TuritsynAbstract:We consider a model nondispersive nonlinear optical fiber channel with additive Gaussian noise at large SNR (Signal-to-noise ratio) in the intermediate power region. Using Feynman path-integral technique we find the optimal Input Signal distribution maximizing the channel's per-sample mutual information. The finding of the optimal Input Signal distribution allows us to improve previously known estimates for the channel capacity. We show that in the intermediate power regime the per-sample mutual information for the optimal Input Signal distribution is greater than the per-sample mutual information for the Gaussian and half-Gaussian Input Signal distributions.