1. |
- Irukulapati, Naga Vishnukanth, 1987, et al.
(author)
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Improved Lower Bounds on Mutual Information Accounting for Nonlinear Signal--Noise Interaction
- 2018
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In: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 36:22, s. 5152-5159
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Journal article (peer-reviewed)abstract
- In fiber-optic communications, evaluation of mutual information (MI) is still an open issue due to the unavailability of an exact and mathematically tractable channel model. Traditionally, lower bounds on MI are computed by approximating the (original) channel with an auxiliary forward channel. In this paper, lower bounds are computed using an auxiliary backward channel, which has not been previously considered in the context of fiber-optic communications. Distributions obtained through two variations of the stochastic digital backpropagation (SDBP) algorithm are used as auxiliary backward channels and these bounds are compared with bounds obtained through the conventional digital backpropagation (DBP). Through simulations, higher information rates were achieved with SDBP, which can be explained by the ability of SDBP to account for nonlinear signal--noise interactions
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2. |
- Keykhosravi, Kamran, 1990, et al.
(author)
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How to Increase the Achievable Information Rate by Per-Channel Dispersion Compensation
- 2019
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In: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 37:10, s. 2443-2451
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Journal article (peer-reviewed)abstract
- Deploying periodic inline chromatic dispersion compensation enables reducing the complexity of the digital back propagation (DBP) algorithm. However, compared with nondispersion-managed (NDM) links, dispersion-managed (DM) ones suffer a stronger cross-phase modulation (XPM). Utilizing per-channel dispersion-managed (CDM) links (e.g., using fiber Bragg grating) allows for a complexity reduction of DBP, while abating XPM compared to DM links. In this paper, we show for the first time that CDM links enable also a more effective XPM compensation compared to NDM ones, allowing a higher achievable information rate (AIR). This is explained by resorting to the frequency-resolved logarithmic perturbation model and showing that per-channel dispersion compensation increases the frequency correlation of the distortions induced by XPM over the channel bandwidth, making them more similar to a conventional phase noise. We compare the performance (in terms of the AIR) of a DM, an NDM, and a CDM link, considering two types of mismatched receivers: one neglects the XPM phase distortion and the other compensates for it. With the former, the CDM link is inferior to the NDM one due to an increased in-band signal--noise interaction. However, with the latter, a higher AIR is obtained with the CDM link than with the NDM one owing to a higher XPM frequency correlation. The DM link has the lowest AIR for both receivers because of a stronger XPM.
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3. |
- Keykhosravi, Kamran, 1990, et al.
(author)
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When to Use Optical Amplification in Noncoherent Transmission: An Information-Theoretic Approach
- 2020
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In: IEEE Transactions on Communications. - 0090-6778 .- 1558-0857. ; 68:4, s. 2438-2445
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Journal article (peer-reviewed)abstract
- The standard solution for short-haul fiber-optic communications is to deploy noncoherent systems, i.e., to modulate and detect only the light intensity. In such systems, the signal is corrupted with optical noise from amplifiers and with thermal (electrical) noise. The capacity of noncoherent optical links has been studied extensively in the presence of either optical noise or thermal noise. In this paper, for the first time, we characterize the capacity under an average power constraint with both noise sources by establishing upper and lower bounds. In the two extreme cases of zero optical noise or zero thermal noise, we assess our bounds against some well-known results in the literature; improvements in both cases are observed. Next, for amplified fiber-optic systems, we study the trade-off between boosting signal energy (mitigating the effects of thermal noise) and adding optical noise. For a wide spectrum of system parameters and received power levels, we determine the optimal amplification gain. While mostly either no amplification or high-gain amplification is optimal, the best performance is for some parameter intervals achieved at finite gains.
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