Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexer for optical fiber transmission

Abstract

The performance of optical mode division multiplexer (MDM) is affected by inter-symbol interference (ISI), which arises from higher-order mode coupling and modal dispersion in multimode fiber (MMF). Existing equalization algorithms in MDM can mitigate linear channel impairments, but cannot tackle nonlinear channel impairments accurately. Therefore, mitigating the noise in the received signal of MDM in the presence of ISI to recover the transmitted signal is important issue. This paper aims at controlling the broadening of the signal from MDM and minimizing the undesirable noise among channels. A dynamic evolving neural fuzzy inference system (DENFIS) equalization scheme has been used to achieve this objective. Results illustrate that nonlinear DENFIS equalization scheme can improve the received distorted signal from an MDM with better accuracy than previous linear equalization schemes such as recursive‐least‐square (RLS) algorithm. Desirably, this effect allows faster data transmission rate in MDM. Additionally, the successful offline implementation of DENFIS equalization in MDM encourages future online implementation of DENFIS equalization in embedded optical systems.

DWDM over FSO under the effect of different atmospheric attenuations

“…Besides, by 2022 also, the rapid growth of gaming traffic is anticipated to increase, and the gaming will be crucial in limiting the likelihood that video traffic will exceed the projected 82 percent [2]. However, different multiplexing has been developed to overcome as follows [3][4][5][6][7][8][9]: a. Wavelength Division Multiplexing (WDM). b.…”