Channel optimization in mode division multiplexing using neural networks

Fazea, Yousef; Sajat, Mohd Samsu; Ahmad, Amran; Alobaedy, Mustafa Muwafak

doi:10.1109/cspa.2018.8368707

Cited by 7 publications

(1 citation statement)

References 16 publications

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“…As mentioned above, mode coupling is inevitable in MDM system which causes channel crosstalk and DMD. Thanks to deep learning, ANN can be used as a MIMO equalizer to mitigate these channel impairments [84]. A two mode MDM transmission system with an ANN equalizer is illustrated in Figure 20a, the ANN equalizer is placed at the receiver side and consists of three layers as depicted in Figure 20b.…”

Section: Artificial Intelligence (Ai) Technology For Mimo Equalizationmentioning

confidence: 99%

Recent Progress on Novel DSP Techniques for Mode Division Multiplexing Systems: A Review

Yang

Peng

et al. 2021

Applied Sciences

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This paper provides an overview of latest progress on the novel advanced digital signal processing (DSP) techniques for long-haul mode division multiplexing (MDM) systems with high capacity. Space-division multiplexing (SDM) techniques have been developed for a period to increase the capacity of optical communication system by at least one order of magnitude through MDM techniques using few-mode fibers (FMFs) or multi-core multiplexing (MCM) using multi-core fibers (MCFs). The signals in MDM links are mainly impaired by the linear and nonlinear effects in FMFs, making DSP techniques become necessary to undo these impairments. In this paper, we not only review the advanced multiple-input multiple-output (MIMO) DSP techniques for compensating linear impairments in FMFs, but also enclose the state of the art of novel DSP techniques to deal with nonlinear effects. Firstly, we introduce the MIMO schemes for equalizing modal crosstalk and modal dispersion. Then, we focus on the fast tracking of time-varying (TV) channels in FMF links through frequency-domain (FD) recursive least square (RLS) algorithm. Besides, we also cover the mainstream DSP solutions for mode-dependent loss (MDL) and several possible methods to compensate nonlinearity in FMF. Moreover, artificial intelligence (AI) technologies are also discussed for its high nonlinearity tolerance and may bring a revolution in MDM systems on the process of channel equalization, link monitoring, etc. In the end, a brief conclusion and perspective will be provided.

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Section: Artificial Intelligence (Ai) Technology For Mimo Equalizationmentioning

confidence: 99%