Soft-Decision Aided Probabilistic Data Association Based Detection for Mode Division Multiplexing Transmission With Mode-Dependent Loss

Z G Cao,S K Wang,L Miao,Y Q Hei,H X Gu,W T Song

doi:10.1109/access.2019.2956585

Z G Cao, S K Wang + Show 4 more

Open Access

https://doi.org/10.1109/access.2019.2956585

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Journal: IEEE Access	Publication Date: Jan 1, 2019
Citations: 2	License type: CC BY 4.0

Affiliation: Xidian University

Abstract

Few-mode fiber (FMF) based mode division multiplexing (MDM) transmission system has been considered as a potential candidate for future backbone network, unfortunately, the mode-dependent loss (MDL) in MDM system remains to be a tough issue in high speed transmission application. Recently, the optimal maximum-likelihood (ML) detection has demonstrated its potential ability and efficiency in suppressing the capacity-limiting MDL. However, this ML detector employed at the receiver of MDM system achieves the optimal performance at the sacrifice of the exponential growth in complexity. Inspired by the fact that probabilistic data association (PDA) is able to offer near-ML performance without introducing the enormous computational complexity, in this paper, a soft-decision aided PDA detector is proposed for MDM system detection, in which the probabilities of the potential candidate symbols are iteratively estimated by using the approximation of the Bayesian theorem. In addition, only those high reliability symbols are detected to save the computational effort. To validate the proposed scheme, both weakly and strongly coupled modes have been considered. Simulation results show that the proposed PDA based detector can achieve a flexible trade-off between the BER performance and the computational complexity when compared with the optimal ML detection in FMF-based MDM system.

Highlights

The rapid development of wideband data services and personal intelligent terminals poses significant challenges to the backbone network of generation in terms of even higher capacity requirements
The results show that the ML detection achieves the best performance over ZF and minimum mean square error (MMSE) in terms of mode-dependent loss (MDL) mitigation, but at the sacrifice of enormous computational complexity
In this paper, a low complexity probabilistic data association (PDA) based detection method has been proposed for Few-mode fiber (FMF)-based mode division multiplexing (MDM) system

Summary

INTRODUCTION

The rapid development of wideband data services and personal intelligent terminals poses significant challenges to the backbone network of generation in terms of even higher capacity requirements. Since the PDA algorithm has already demonstrated its potential ability in terms of near-optimum performance and low computational cost in wireless MIMO detection, it is of great interests to study the potential application of PDA in the MDL-impaired MDM transmission systems. In the proposed PDA based MDM detection, the posteriori probability of each potential candidate symbol is utilized as soft input/output information and estimated in an iterative process by using the approximate Bayesian formula. Simulation results demonstrate that the proposed PDA based MDM detection achieves much better BER performance when compared with the other existing MDM detection schemes, but with relatively low computational cost.

MDM SYSTEM MODEL

Findings

CONCLUSION