MétaCan
Menu
Retour à la cohorte
Enregistrement W3086857118 · doi:10.1364/cleo_si.2020.sth3l.2

Experimental Demonstration of Hybrid OFDM-Digital Filter Multiple Access PONs for 5G and Beyond Networks

2020· article· en· W3086857118 sur OpenAlexaff
Wei Jin, Zhuqiang Zhong, Yixian Dong, Jiaxiang He, Leyan Li, Abdulai Sankoh, Su Hu, R. P. Giddings, Yanhua Hong, Maurice O’Sullivan, J. Lee, Tim Durrant, Jianming Tang

Notice bibliographique

RevueConference on Lasers and Electro-Optics · 2020
Typearticle
Langueen
DomaineEngineering
ThématiqueAdvanced Photonic Communication Systems
Établissements canadiensCiena (Canada)
Organismes subventionnairesnon disponible
Mots-clésOrthogonal frequency-division multiplexingPassive optical networkElectronic engineeringComputer scienceOptical line terminationDigital signal processingMultiplexingAccess networkRobustness (evolution)EngineeringTelecommunicationsWavelength-division multiplexingChannel (broadcasting)WavelengthOptics

Résumé

récupéré en direct d'OpenAlex

Aggregated 16.6Gbit/s@26km upstream hybrid OFDM-DFMA IMDD PONs utilizing low-cost optical/electrical devices are demonstrated, for the first time, which significantly improve the performance robustness and differential ONU optical launch power dynamic range, compared to published work. © 2020 The Author(s) OCIS code: (060.0060) Fiber optics and optical communications; (060.4250) Networks; 1. Introduction To realize the seamless convergence of the existing optical metro/access networks and mobile front-haul/mid- haul/back-haul networks for 5G and beyond networks, recently, a hybrid orthogonal frequency division multiplexing-digital filter multiple access (OFDM-DFMA) PON has been proposed and theoretically investigated [1,2], where for upstream signal transmission, various digital in-phase (I) shaping filters (SFs) are employed in the ONUs to dynamically locate their OFDM signals at the required sub-wavelengths. Whilst in the OLT, the OFDM signals from various ONUs are de-multiplexed and demodulated simultaneously by a single FFT operation without utilizing digital matching filters. Compared with the previously reported DFMA PON [3-5], its unique advantages are summarized as follows: 1) >100-fold reduction in the overall OLT DSP complexity when accommodating 36 ONUs [6], 2) considerable relaxation of ONU-embedded digital SF DSP complexity requirements for achieving specific transmission performances, 3) significant improvements in upstream system power budget and upstream performance robustness against both component/system impairments and channel interferences, 4) inherent transparency to existing OFDM-based 4G networks, and 5) excellent transparency to ONU design parameters. In this paper, experimental explorations of the more challenging upstream signal transmission performance of the hybrid OFDM-DFMA PONs are reported, for the first time, utilizing off-the-shelf low-cost optical/electrical devices. The experimentally measured results confirm our numerical predictions, and more importantly, reveal that the proposed PON not only has improved upstream performance robustness against transmission system impairments and channel interferences, but also possesses a large differential ONU optical launch power dynamic range (Diff- ONU OLPDR), compared to the previously published work [4]. 2. Experimental setup and measured upstream transmission performances Based on the hybrid OFDM-DFMA PON operating principle explicitly described in [1], the experimental setup of a representative two-channel upstream hybrid OFDM-DFMA PON is illustrated in Fig. 1. In the transmitter, two independent digitally-filtered analogue OFDM signals are produced by a dual-channel AWG (Keysight M8195A) operating at 30GS/s@8-bit. In the AWG-embedded Matlab program, two real OFDM signals are first generated and Fig. 1 Experimental upstream setup of the IMDD hybrid OFDM-DFMA PON without utilizing digital matching filters. Fig. 2 (a) Back-to-back and 26km SSMF transmission performance, (b) impact of channel interference on transmission performance and (c) differential ONU optical launch power dynamic range. then digitally up-sampled by a factor of M=4 (4 1), and finally digitally filtered by two in-phase SFs. The adopted SFs are constructed by using a Hilbert-pair approach [1]. The key parameters of the OFDM signals and the digital filters are listed in Table I. Prior to digital-to-analogue conversion of each OFDM signal, a digital-domain time delay operation is applied to adjust the ONU signal timing for synchronization and an extra 1.5* oversampling operation is also performed for each digitally-filtered OFDM signal. As such, for each analogue signal produced, its signal bandwidth/bitrate is 5GHz/8.3Gbit/s, which gives rise to an overall upstream signal transmission bandwidth of 10GHz and an aggregated upstream signal bitrate of 16.6Gbit/s. To perform optical intensity modulation, a 10GHz EML and a 20GHz MZM are used for the low frequency channel (CH-1) and high frequency channel (CH-2) respectively. To alleviate the optical beating interference effect in the OLT, a minimum wavelength space of 0.28nm between these two ONUs is employed. After a 50:50 passive OC, the fiber launch power is 4.7dBm. After 26km SSMF transmission, a 25GHz linear PIN and an electrical amplifier, a digital sampling oscilloscope (DSO) captures and digitalizes the received electrical signal at a sampling speed of 25GS/s, and finally a signal demodulation process is performed off-line, which includes signal resampling [5], signal synchronization, serial-to- parallel conversion (S/P), CP removal, a single 128 (32*4) point FFT operation, signal sideband identification, sideband processing and data recovery. In the signal sideband identification process after the FFT, the 64 subcarriers in the positive frequency bin are classified into two groups each containing 32 subcarriers (corresponding to one OFDM signal). In each group, its 16 low/high frequency subcarriers occupy the lower sideband (LSB)/the upper sideband (USB) of the signal. As the LSB and USB of a specific OFDM signal convey identical data, for each identified OFDM signal, the sideband processing is then applied to improve signal transmission performance, where a conjugate operation is first performed for the USB subcarriers and subsequently a phase compensation operation is then implemented for both the LSB and USB subcarriers, and finally the subcarriers in the LSB and USB of the same signal are directly summed. The upstream transmission performances and the received signal spectra of the considered hybrid OFDM-DFMA PONs before and after upstream transmitting the aggregated 16.6Gbit/s over 26km SSMF are plotted in Fig. 2(a). The results show that the fiber transmission-induced power penalties at BERs of 1*10-3 are < 0.5dB for both channels, indicating that fiber transmission nonlinearities have negligible impacts on the BER performances of different channels. This agrees very well with our theoretical predictions [1]. The channel interference-induced performance degradations are explored in Fig. 2(b), where the BER performances of each channel with the other channel present/omitted in the optical domain are illustrated. As expected from our numerical results [1], the channel interference-induced power penalties are <1dB. Furthermore, by utilizing the system parameter setting similar to that adopted in Fig. 2(a), the Diff-ONU OLPDR [1] over 26km SSMF transmission is examined in Fig. 2(c), where the received optical power is fixed at -3.5dBm. Fig. 2(c) shows that the Diff-ONU OLPDR as large as 6.7dB is obtainable. In addition, it is also worth highlighting the following two aspects: 1) in Fig. 2, the similarities of the observed ONU OLPDRs and the BER performances between these two considered ONUs with different optical intensity modulators suggest that the hybrid OFDM-DFMA PON has excellent robustness against variations in ONU transceiver designs, and 2) all the subcarriers in each channel have very similar EVM performances, as shown in Fig. 2(b), this implies the effectiveness of the sideband processing adopted in the OLT.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,655
Score d'incertitude au seuil0,515

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,263
Écart entre enseignants0,229 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueConference on Lasers and Electro-OpticsMême sujetAdvanced Photonic Communication SystemsTravaux en français237 207