Blind Polarization Demultiplexing of Shaped QAM Signals Assisted by Temporal Correlations

作     者：Bajaj, Vinod Van de Plas, Raf Wahls, Sander 

作者机构：Delft Univ Technol Delft Ctr Syst & Control NL-2628 CD Delft Netherlands Vanderbilt Univ Mass Spectrometry Res Ctr Nashville TN 37240 USA Vanderbilt Univ Dept Biochem Nashville TN 37240 USA Karlsruhe Inst Technol KIT Inst Ind Informat Technol Karlsruhe TN Germany 

出 版 物：《JOURNAL OF LIGHTWAVE TECHNOLOGY》 (J Lightwave Technol)

年 卷 期：2024年第42卷第2期

页      面：560-571页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0702[理学-物理学] 

基　　金：National Institutes of Health#x0027 s Common Fund 

主　　题：Signal processing algorithms Symbols Quadrature amplitude modulation Demultiplexing Correlation Optical fiber dispersion Programmable logic arrays Digital signal processing optical fiber communication polarization demultiplexing probabilistic constellation shaping 

摘      要：While probabilistic constellation shaping (PCS) enables rate and reach adaption with finer granularity [1] (Cho and Winzer, 2009), it imposes signal processing challenges at the receiver. Since the distribution of PCS-quadrature amplitude modulation (QAM) signals tends to be Gaussian, conventional blind polarization demultiplexing algorithms are not suitable for them [2] (Johnson et al., 1998). It is known that independently and identically distributed (iid) Gaussian signals, when mixed, cannot be recovered/separated from their mixture. For PCS-QAM signals, there are algorithms such as [3] and [4] Dris et al. (2019) and Athuraliya et al. (2004) which are designed by extending conventional blind algorithms used for uniform QAM signals. In these algorithms, an initialization point is obtained by processing only a part of the mixed signal, which have non-Gaussian statistics. In this article, we propose an alternative method wherein we add temporal correlations at the transmitter, which are subsequently exploited at the receiver in order to separate the polarizations. We will refer to the proposed method as frequency domain (FD) joint diagonalization (JD) probability aware-multi modulus algorithm (pr-MMA), and it is suited to channels with moderate polarization mode dispersion (PMD) effects. Furthermore, we extend our previously proposed JD-MMA [5] (Bajaj et al., 2022) by replacing the standard MMA with a pr-MMA, improving its performance. Both FDJD-pr-MMA and JD-pr-MMA are evaluated for a diverse range of PCS (entropy {H ) of 64-QAM over a first-order PMD channel that is simulated in a proof-of-concept setup. A MMA initialized with a memoryless constant modulus algorithm (CMA) is used as a benchmark. We show that at a differential group delay (DGD) of 10% of symbol period T (symb) and 18 dB SNR/pol., JD-pr-MMA successfully demultiplexes the PCS signals, while CMA-MMA fails drastically. Furthermore, we demonstrate that the newly proposed FDJD-pr-MMA is robust against mo