TU Darmstadt / ULB / TUprints

MIMO Equalization for Space Division Multiplexing in Optical Communications

Jha, Saumya (2024)
MIMO Equalization for Space Division Multiplexing in Optical Communications.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00027803
Master Thesis, Primary publication, Publisher's Version

This is the latest version of this item.

[img] Text
ThesisSaumya (1).pdf
Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

Download (27MB)
Item Type: Master Thesis
Type of entry: Primary publication
Title: MIMO Equalization for Space Division Multiplexing in Optical Communications
Language: English
Date: 29 July 2024
Place of Publication: Darmstadt
Collation: 66 Seiten
DOI: 10.26083/tuprints-00027803
Abstract:

The evolution of technology has led to an increasing demand for data in both customer- and industry-specific applications. The current infrastructure is capable of meeting the present requirements. However, as data- centric applications continue to advance, recent statistics on consumer behavior indicate an exponential growth in bandwidth requirements. This necessitates the adoption of new technologies that can exploit more efficient methods in addition to the existing architecture. Optical communications currently heavily rely on single-mode fibers (SMF) with wavelength division multiplexing (WDM), which is efficient but needs to address the issue of "Capacity crunch" in the coming years. One proposed solution involves exploring other dimensions with optimized algorithms to achieve higher data rates. A particularly promising multiplexing scheme that has been extensively researched in recent years is space division multiplexing (SDM), which involves transmitting data through multiple spatial paths in the space domain. This can be achieved using multimode fibers (MMF), multi-core fibers (MCFs), or a combination of these techniques, such as few mode fibers (FMF), which utilize a single fiber with a sufficiently large core to carry multiple modes. Upgrading the transmitter, receiver, and various processing schemes allows for spatial filtering, resulting in increased capacity and reduced cost per bit. To reconstruct the transmitted signal and mitigate challenges or impairments in the network, digital signal processing (DSP) offers a variety of algorithms with pre- and post-processing techniques. One interesting approach is to blindly reconstruct the signal from the transmitted signal without knowledge of the training sequence, using popular blind algorithms adaptively. In this thesis work, we study and discuss the constant modulus algorithm (CMA), multi-modulus algorithm (MMA), and decision-directed feed-forward equalization (DDFFE) for PS QPSK (polarization-switched QPSK) and PDM 16 QAM (polarization-division multiplexed 16 QAM). The proof of concept for few-mode fibers in the back-to-back case is validated through simulations and an experimental setup. The primary focus of this work is on linear effects such as chromatic dispersion, polarization modal loss, additional noise, and crosstalk. The performance of the adaptive blind equalization schemes is measured using the bit error rate (BER) and error vector magnitude (EVM) metrics for all modes with X and Y polarization.

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-278037
Classification DDC: 600 Technology, medicine, applied sciences > 600 Technology
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Microwave Engineering and Photonics (IMP) > Photonics and Optical Communications
18 Department of Electrical Engineering and Information Technology > Institute for Microwave Engineering and Photonics (IMP)
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Communications Engineering
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Communication Systems
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Signal Processing
Study Areas > Study area Computational Engineering
Study Areas > Study Area Information System Engineering
Date Deposited: 29 Jul 2024 08:11
Last Modified: 04 Sep 2024 13:47
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/27803
PPN: 519971086
Export:

Available Versions of this Item

Actions (login required)
View Item View Item