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International audience; Single section quantum dash (QDash) mode locked lasers (MLL) can provide a flat and broadband optical frequency comb with low energy consumption, operational simplicity and large-scale low-cost production possibilities. MLL longitudinal modes can be employed as single carriers with a regular spectral spacing in a dense wavelength division multiplexing (DWDM) link, making them promising components for next generation DWDM transceivers. However, individual modes of a MLL suffer from relatively high phase noise while high capacity coherent transmission requires carriers with low phase noise. Optical feedback, which is a well-known method to reduce the linewidth of a single mode laser, can be used to stabilize comb lasers. This paper reports on the investigation of phase noise properties of comb lines delivered from a single section QDash MLL under optical feedback and shows that each MLL longitudinal mode optical linewidth can be drastically narrowed. It enables coherent transmission with extended link budget over 50 km at Tbit/s line rates.

International audience; In this survey, we analyze the newest machine learning (ML) techniques applied in modern optical orthogonal frequency division multiplexing (O-OFDM) systems for access, core networks, and multi-channel transmission. From rudimentary to more advanced approaches, ML is proven to be a gold standard technique for signal quality improvement when low transmitter modulation extinction ratio dominates in coherent O-OFDM, and when stochastic-induced nonlinearities are present such as parametric noise amplification in long-haul transmission and the interplay between polarization-mode dispersion and the Kerr-induced nonlinearity. In addition, ML algorithms can effectively tackle determinist nonlinear distortions in O-OFDM networks, as well as inter-subcarrier nonlinear effects (ie, inter-subcarrier four-wave mixing and cross-phase modulation). In essence, ML techniques could be potentially beneficial for any multi-carrier approach (eg, filter bank modulation). The survey illustrates an extensive ML taxonomy for O-OFDM based networks, covering supervised, reinforcement learning and unsupervised ML categories. The transmission performance of various ML-assisted O-OFDM systems is presented taking into account the ML computational complexity toward real-time implementation. We also highlight the strict operating conditions for such systems under which a ML algorithm should perform classification, regression or clustering. Finally, the survey opens research issues and future directions toward ML implementation in radio-over-fiber (RoF) and 5G new radio (NR) systems.

Allocation of resources between femtocell and macrocell is essential to counter the effects of interference in the dense femtocell. The significant increase in the number of internet users and the demand for higher data capacity per user mandates the development of complex and expensive telecommunication infrastructure that includes spectrum and power management, increased operation power and high-quality. In this work, we investigate the performance of femtocells in outdoor and indoor space based on the network’s capacity and resource management by extensive numerical modeling and simulations for different conditions of user’s location and femtocells in one cell.

In this article, we experimentally demonstrate the combined benefit of artificial neural network-based nonlinearity compensation and probabilistic shaping for the first time. We demonstrate that the scheme not only compensates for transceiver's nonlinearity, enabling the full benefits of shaping to be achieved, but also the combined effects of transceiver and fiber propagation nonlinearities. The performance of the proposed artificial neural network is demonstrated at 28 Gbaud for both 64-QAM and 256-QAM probabilistically shaped systems and compared to that of uniformly distributed constellations. Our experimental results demonstrate: the expected performance gains for shaping alone; an additional SNR performance gain up to 1 dB in the linear region; an additional mutual information gain of 0.2 bits per channel use in the constellation-entropy limited region. In the presence of coupled transceiver and fiber-induced nonlinearities, an additional mutual information enhancement of $\sim$ 0.13 bits/symbol is experimentally observed for a fiber link of up to 500 km with the aid of the proposed artificial neural network.

We experimentally demonstrate a system-agnostic and training-data-free nonlinearity compensator, using affinity propagation (AP) clustering in single- and multi-channel coherent optical OFDM (CO-OFDM) for up to 3200 km transmission. We show that AP outperforms benchmark deterministic and clustering algorithms by effectively tackling stochastic nonlinear distortions and inter-channel nonlinearities. AP offers up to almost 4 dB power margin extension over linear equalization in single-channel 16-quadrature amplitude-modulated CO-OFDM and a 1.4 dB increase in Q-factor over digital back-propagation in multi-channel quaternary phase-shift keying CO-OFDM. Simulated results indicate transparency to higher modulation format orders and better efficiency when a multi-carrier structure is considered.

International audience; All‐optical orthogonal frequency division multiplexing (AO‐OFDM) and optical code‐division multiple‐access system (OCDMA) are combined in the first analytical model, which considers subcarrier hopping by means of advanced two‐dimensional (2D) hybrid‐coded (2D‐HC) signature. The model incorporates probabilistic subcarrier overlapping, multiple‐access interferences and is tested, for the first time, over amplifier‐free long‐reach passive optical networks (LR‐PONs) using cost‐effective intensity modulations and direct detection. For the upstream direction at 40 Gb/s, AO‐OFDM‐OCDMA outperforms a ‘classical’ multi‐channel OCDMA system for low received powers and any number of simultaneous users. In comparison to conventional 1D Walsh–Hadamard, 1D prime code and 2D prime hop system, coding with 2D‐HC can improve the performance of AO‐OFDM‐CDMA, thus allowing a higher number of simultaneous users in LR‐PON without optical amplification. From numerical simulations, the authors show that 16‐quadrature amplitude modulation (16‐QAM) AO‐OFDM‐CDMA with 45 users has comparable performance to conventional multi‐channel 16‐QAM coherent optical OFDM in the downstream direction and up to 58 km with 1:45 split ratio, without employing complex coherent technology. Similarly, based on the feasibility of physical implementation configuration, a budget power calculation is performed showing 108 km as maximum reachability distance for 40 Gb/s QAM signal, 1:64 split ratio when considering standard forward‐error‐correction.

A hybrid coherent optical (CO) orthogonal frequency division multiplexing-code division multiplexing access (OFDM-CDMA) system is numerically demonstrated for long-reach passive optical networks (LR-PONs) at 100 Gb/s using an advanced 2D-OCDMA signature. To this end, we investigate key parameters limitations, such as the overlap of OFDM subcarriers, the peak-to-average power ratio (PAPR), and the multiple access interference (MAI) for up to 180 users and 64-quadrature amplitude modulation (64-QAM). It is shown that the maximum achievable transmission-reach of CO-OFDM-CDMA with 2D-hybrid coding is 83.5 km, which is almost double compared to a conventional OCDMA-wavelength division multiplexing (OCDMA-WDM) system. Likewise, our proposed technique can enhance the total power budget by 17 dB compared to 2D-OCDMA-WDM.

Modern fiber-optic coherent communications employ advanced, spectrally efficient modulation formats that require sophisticated narrow-linewidth local oscillators (LOs) and complex digital signal processing (DSP). Self-coherent optical orthogonal frequency-division multiplexing (self-CO-OFDM) is a modern technology that retrieves the frequency and phase information from the extracted carrier without employing a LO or additional DSP. However, a wide carrier guard is typically required to easily filter out the optical carrier at the receiver, thus discarding many OFDM middle subcarriers that limit the system data rate. Here, we establish an optical technique for carrier recovery, harnessing large-gain stimulated Brillouin scattering (SBS) on a photonic chip for up to 116.82 Gbit·s−1 self-CO-OFDM signals, without requiring a separate LO. The narrow SBS linewidth allows for a record-breaking small carrier guard band of ∼265 MHz in self-CO-OFDM, resulting in higher capacity than benchmark self-coherent multi-carrier schemes. Chip-based SBS-self-coherent technology reveals comparable performance to state-of-the-art coherent optical receivers while relaxing the requirements of the DSP. In contrast to on-fiber SBS processing, our solution provides phase and polarization stability. Our demonstration develops a low-noise and frequency-tracking filter that synchronously regenerates a low-power narrowband optical tone, which could relax the requirements on very-high-order modulation signaling for future communication networks. The proposed hybrid carrier filtering-and-regeneration technique could be useful in long-baseline interferometry for precision optical timing or reconstructing a reference tone for quantum-state measurements.

In order to meet the increasing capacity requirements, network operators are extending their optical infrastructure closer to the end-user while making more efficient use of the resources. In this context, long reach passive optical networks (LR-PONs) are attracting increasing attention.Coherent LR-PONs based on high speed digital signal processors represent a high potential alternative because, alongside with the inherent mixing gain and the possibility of amplitude and phase diversity formats, they pave the way to compensate linear impairments in a more efficient way than in traditional direct detection systems. The performance of coherent LR-PONs is then limited by the combined effect of noise and nonlinear distortion. The noise is particularly critical in single channel systems where, in addition to the the elevated fibre loss, the splitting losses should be considered. In such systems, Kerr induced self-phase modulation emerges as the main limitation to the maximum capacity. In this work, we propose a novel clustering algorithm, denominated histogram based clustering (HBC), that employs the spatial density of the points of a 2D histogram to identify the borders of high density areas to classify nonlinearly distorted noisy constellations. Simulation results reveal that for a 100 km long LR-PON with a 1:64 splitting ratio, at optimum power levels, HBC presents a Q-factor 0.57 dB higher than maximum likelihood and 0.21 dB higher than k-means. In terms of nonlinear tolerance, at a BER of 2&times, 10 - 3 , our method achieves a gain of &sim, 2.5 dB and &sim, 1.25 dB over maximum likelihood and k-means, respectively. Numerical results also show that the proposed method can operate over blocks as small as 2500 symbols.

A fast Newton-based support vector machine (N-SVM) nonlinear equalizer (NLE) is experimentally demonstrated, for the first time, in 40 Gb/s 16-quadrature amplitude modulated coherent optical orthogonal frequency division multiplexing at 2000 km of transmission. It is shown that N-SVM-NLE extends the optimum launched optical power by 2 dB compared to the benchmark Volterra-based NLE. The performance improvement by N-SVM is due to its ability of tackling both deterministic fiber-induced nonlinear effects and the interaction between nonlinearities and stochastic noises (e.g., polarization-mode dispersion). An N-SVM is more tolerant to intersubcarrier nonlinear crosstalk effects than Volterra-based NLE, especially when applied across all subcarriers simultaneously. In contrast to the conventional SVM, the proposed algorithm is of reduced classifier complexity offering lower computational load and execution time. For a low C -parameter of 4 (a penalty parameter related to complexity), an execution time of 1.6 s is required for N-SVM to effectively mitigate nonlinearities. Compared to conventional SVM, the computational load of N-SVM is ∼6 times lower.

We experimentally demonstrate, for the first time, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to improve the receiver performance of wavelength converting 40-Gb/s 16-quadrature amplitude modulation (16-QAM) and 30-Gb/s 64-QAM using four-wave mixing in semiconductor optical amplifier (SOA). Two novel modified DBSCAN methods are proposed, in which “un-clustered” received constellation points that are considered to be noisy points are further processed using method-(1) K-means and method-(2) the minimum distance between an unlabeled point and the clustered points. DBSCAN is more effective for distorted signals due to optical nonlinearities at higher than 25 and 30 dB of optical signal-to-noise ratios (OSNR) for 16- and 64-QAM, respectively. We find that DBSCAN can result in improvements in Q-factor by ~ 0.8 dB at optimum power when compared to linear equalization. The soft-clustering ability of DBSCAN method-(2) is particularly useful at high OSNR (30 dB) and high input signal powers in the SOA where excessive nonlinearity causes rotation of the outer-constellation points. Method-(1)’s hard clustering is valuable at lower input signal powers, where the clusters maintain a Gaussian-circular shape.

Nonlinearities in SOA-based wavelength conversion are experimentally tackled using post-blind-compensation based on machine learning clustering for coherent 16/64-QAM signals. We show that K-means outperforms fuzzy-logic since it tackles more effectively non-circularly-symmetric Gaussian noise and nonlinearity.

Coherent optical orthogonal frequency division multiplexing (CO-OFDM) has attracted a lot of interest in optical fiber communications due to its simplified digital signal processing (DSP) units, high spectral-efficiency, flexibility, and tolerance to linear impairments. However, CO-OFDM’s high peak-to-average power ratio imposes high vulnerability to fiber-induced non-linearities. DSP-based machine learning has been considered as a promising approach for fiber non-linearity compensation without sacrificing computational complexity. In this paper, we review the existing machine learning approaches for CO-OFDM in a common framework and review the progress in this area with a focus on practical aspects and comparison with benchmark DSP solutions.

A support vector machine (SVM)-based classification nonlinear equalizer (NLE) is demonstrated, for the first time, in coherent optical orthogonal frequency-division multiplexing (CO-OFDM). For a 40-Gb/s 16 quadrature amplitude modulated (16QAM) CO-OFDM system at 400 km of transmission, SVM-NLE reduces the fiber-induced nonlinearity penalty by about 1 dB in comparison to the benchmark artificial-neural-network (ANN)-based and inverse-Volterra-series-transfer-function-based NLEs.

Made available in DSpace on 2021-06-25T11:23:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-10-15 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Science Foundation Ireland Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) A novel nonlinear equalizer based on a multiple-input multiple-output (MIMO) deep neural network (DNN) is proposed and experimentally demonstrated for compensation of inter-subcarrier nonlinearities in a 40 Gb/s coherent optical orthogonal frequency division multiplexing system. Experimental results reveal that MIMO-DNN can extend the power margin by 4 dB at 2000 km of standard single-mode fiber transmission when compared to linear compensation or conventional single-input single-output DNN. It is also found that MIMO-DNN outperforms digital back propagation by increasing up to 1 dB the effective Q-factor and reducing by a factor of three the computational cost. (C) 2020 Optical Society of America Sao Paulo State Univ, Campus Sao Joao da Boa Vista, Sao Joao Da Boa Vista, SP, Brazil Dublin City Univ, Sch Elect Engn, Dublin 9, Ireland Univ Hertfordshire, Hatfield, Herts, England Fahad Bin Sultan Univ, Tabuk, Saudi Arabia Beijing Univ Technol, 100 Pingleyuan, Beijing, Peoples R China Huawei Technol Duesseldorf GmbH, European Res Ctr, Riesstr 25, Munich, Germany Tecnol Monterrey, Sch Engn, Monterrey, Mexico Sao Paulo State Univ, Campus Sao Joao da Boa Vista, Sao Joao Da Boa Vista, SP, Brazil FAPESP: 2018/25339-4 Science Foundation Ireland: 12/RC/2276 Science Foundation Ireland: 13/RC/2077 Science Foundation Ireland: 15/US-C2C/I3132 CNPq: 311035/2018-3 CNPq: 432303/2018-9

We live in an era of information explosion and digital revolution that has resulted in rapid technological developments in different aspects of life [...]

We experimentally demonstrate the first field-programmable gate-array-based real-time fiber nonlinearity compensator (NLC) using sparse K-means++ machine learning clustering in an energy-efficient 40-Gb/s 16-quadrature amplitude modulated self-coherent optical system. Our real-time NLC shows up to 3 dB improvement in Q-factor compared to linear equalization at 50 km of transmission., Comment: Submitted to ECOC post-deadline, Sep. 2019, Dublin, Ireland

To address the continuous growth in high-speed ubiquitous access required by residential users and enterprises, Telecommunication operators must upgrade their networks to higher data rates. For optical fiber access networks that directly connect end users to metro/regional network, capacity upgrade must be done in a cost- and energy-efficient manner. 40 Gb/s is the possible lane rate for the next generation passive optical networks (NG-PONs). Ideally, existing 10 G PON components could be reused to support 40 Gb/s lane-rate NG-PON transceiver, which requires efficient modulation format and digital signal processing (DSP) to alleviate the bandwidth limitation and fiber dispersion. The major contribution of this work is to offer insight performance comparisons of 40 Gb/s lane rate electrical three level Duobinary, optical Duobinary, and four-level pulse amplitude modulation (PAM-4) for incorporating low complex DSPs, including linear and nonlinear Volterra equalization, as well as maximum likelihood sequence estimation. Detailed analysis and comparison of the complexity of various DSP algorithms are performed. Transceiver bandwidth optimization is also undertaken. The results show that the choices of proper modulation format and DSP configuration depend on the transmission distances of interest.

Fiber-induced nonlinearities significantly limit the transmission performance of coherent optical signals. Here, a novel adaptive 3D deep learning nonlinear equalizer based on an artificial neural network is experimentally demonstrated for multi-channel coherent optical orthogonal frequency division multiplexing. It is shown that adaptive 3D deep learning outperforms 2D machine learning and the deterministic goldstandard digital back-propagation at 3200 km of single-mode fibre transmission. This occurs since our technique can tackle both deterministic and stochastic nonlinear distortions.

Made available in DSpace on 2018-11-26T16:01:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-06-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) CONACyT EU Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Science Foundation Ireland (SFI) European Regional Development Fund Survivability is a critical requirement of optical communication networks that is typically addressed implementing path diversity. However, due to the elevated cost of fiber installation, this approach may prove prohibitively expensive in optical access networks. In this paper, a novel cost-efficient photonic millimeter (mm)-wave bridge is proposed, which converts passive optical network (PON) signals to radiofrequency signals at mm-wave bands. The performance of the mm-wave photonic bridge is numerically tested, revealing its feasibility to transmit a 2.5-Gbps PON with -55.6 dB wireless link gain (WLG) using the 81-86 GHz band and 10-Gbps PON with -35 dB at the 102-109.5 GHz band. The effect of fiber is also analyzed, showing that fiber cuts closer to the optical network unit degrades more the system performance. (C) 2018 Elsevier B.V. All rights reserved. Sao Paulo State Univ, Campus Sao Joao da Boa Vista, Sao Paulo, SP, Brazil Univ Panamer, Fac Ingn, Prolongac Calzada Circunvalac, Poniente 49, Zapopan 45010, Jalisco, Mexico Tecnol Monterrey, Sch Engn, Monterrey, Mexico Dublin City Univ, Sch Elect Engn, Dublin 9, Ireland Sao Paulo State Univ, Campus Sao Joao da Boa Vista, Sao Paulo, SP, Brazil FAPESP: 2015/04113-0 EU Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie: 713567 European Regional Development Fund: 13/RC/2077

Survivability is a critical requirement of optical communication networks that is typically addressed implementing path diversity. However, due to the elevated cost of fiber installation, this approach may prove prohibitively expensive in optical access networks. In this paper, a novel cost-efficient photonic millimeter (mm) - wave bridge is proposed, which converts passive optical network (PON) signals to radio frequency signals at mm-wave bands. The performance of the mm-wave photonic bridge is numerically tested, revealing its feasibility to transmit a 2.5-Gbps PON with {55.6 dB wireless link gain (WLG) using the 81-86 GHz band and 10-Gbps PON with {35 dB at the 102-109.5 GHz band. The effect of ber is also analyzed, showing that ber cuts closer to the optical network unit degrades more the system performance.

A novel blind nonlinear equalization (BNLE) technique based on the iterative re-weighted least square is experimentally demonstrated for single and multi-channel coherent optical orthogonal frequency-division multiplexing (CO-OFDM). The adopted BNLE combines, for the first time, a support vector machine-learning cost function with the classical Sato or Godard error functions and maximum likelihood recursive least-squares. At optimum launched optical power, BNLE reduces the fiber nonlinearity penalty by ~1 (16-QAM single-channel at 2000 km) and ~1.7 dB (QPSK multi-channel at 3200 km) compared to a Volterra-based NLE. The proposed BNLE is more effective for multi-channel configuration: 1) it outperforms the ‘gold-standard’ digital-back propagation; 2) for a high number of subcarriers the performance is better due to its capability of tackling inter-subcarrier four-wave mixing.

Fiber-induced intra- and interchannel nonlinearities are experimentally tackled using blind nonlinear equalization (NLE) by unsupervised machine-learning-based clustering (MLC) in ∼46-Gb/s single-channel and ∼20-Gb/s (middle-channel) multichannel coherent multicarrier signals (orthogonal frequency-division multiplexing (OFDM) based). To that end, we introduce, for the first time, hierarchical and fuzzy-logic C -means (FLC)-based clustering in optical communications. It is shown that among the two proposed MLC algorithms, FLC reveals the highest performance at optimum launched optical powers (LOPs), while at very high LOPs, hierarchical can compensate more effectively nonlinearities only for low-level modulation formats. When employing binary phase-shift keying and quaternary phase-shift keying, FLC outperforms K-means, fast-Newton support vector machines, supervised artificial neural networks, and NLE with deterministic Volterra analysis. In particular, for the middle channel of a QPSK wavelength-division multiplexing coherent optical OFDM system at optimum −5 dBm of LOP and 3200 km of transmission, FLC outperforms Volterra-NLE by 2.5 dB in Q-factor. However, for a 16-QAM single-channel system at 2000 km, the performance benefit of FLC over inverse Volterra-series transfer function reduces to ∼0.4 dB at a LOP of 2 dBm (optimum). Even when using novel sophisticated clustering designs in 16 clusters, no more than additional ∼0.3-dB Q-factor enhancement is observed. Finally, in contrast to the deterministic Volterra-NLE, MLC algorithms can partially tackle the stochastic parametric noise amplification .

Visible light communications is a technology with enormous potential for a wide range of applications within next generation transmission and broadcasting technologies. VLC offers simultaneous illumination and data communications by intensity modulating the optical power emitted by LEDs operating in the visible range of the electromagnetic spectrum (similar to 370-780 nm). The major challenge in VLC systems to date has been in improving transmission speeds, considering the low bandwidths available with commercial LED devices. Thus, to improve the spectral usage, the research community has increasingly turned to advanced modulation formats such as orthogonal frequency-division multiplexing. In this article we introduce a new modulation scheme into the VLC domain; multiband carrier-less amplitude and phase modulation (m-CAP) and describe in detail its performance within the context of bandlimited systems.

We propose a novel low-complexity artificial neural network (ANN)-based nonlinear equalizer (NLE) for coherent optical orthogonal frequency-division multiplexing (CO-OFDM) and compare it with the recent inverse Volterra-series transfer function (IVSTF)-based NLE over up to 1000 km of uncompensated links. Demonstration of ANN-NLE at 80-Gb/s CO-OFDM using 16-quadrature amplitude modulation reveals a Q-factor improvement after 1000-km transmission of 3 and 1 dB with respect to the linear equalization and IVSTF-NLE, respectively.

We present our recent results on harnessing the nonlinear stimulated Brillouin scattering effect on a photonic chip for coherent optical communications. At the transmitter-end, an optical frequency comb was regenerated through on-chip Brillouin scattering for 64-level QAM communications. At the receiver-end, low-latency self-homodyne reception was achieved through Brillouin-assisted carrier recovery.

We demonstrate the first all-optical carrier recovery of coherent signals using on-chip Brillouin gain, replacing digital techniques, with sub-nanosecond latency. This demonstration serves as a proof-of-concept for integrated photonic carrier recovery chips for coherent communications.

Nonlinear effects are experimentally tackled, for the first time, in WDM-CO-OFDM by an artificial neural network (ANN)-based equalizer at 3200 km. For the middle 20-Gb/s channel ANN outperforms to Volterra-based equalization by ∼2-dB in Q-factor.

We analyze and compare the complexity of IMDD-based 56-Gb/s Multi-band CAP and DMT over 80-km DCF-free SMFs for data center interconnects. Multi-band CAP with small sub-band count has comparable complexity to DMT at similar OSNR performance.

We experimentally demonstrate the first Hierarchical clustering-based blind nonlinear equalizer for QPSK WDM-CO-OFDM. Hierarchical clustering outperforms to full-step digital-back propagation and artificial neural networks at 3200 km by up to 1.5 and 1.1 dB, respectively.

We experimentally demonstrate 40-Gb/s/λ PAM-4 transmission over a 20-km (30-km) SMF using only 10-G optics and simple post-nonlinear equalizations with a link power budget of 38 dB (30.7 dB) at a threshold BER of 10−3.

We experimentally demonstrate a Newton support vector machine (N-SVM)-based nonlinear equalizer (NLE) of reduced classifier complexity for 40-Gb/s 16-QAM CO-OFDM. At 2000-km N-SVM extends the launched optical power by 2-dB compared to Volterra-based NLE.

A reconfigurable nonlinear equalizer (RNLE) based on inverse Volterra series transfer function is proposed for dual-polarization (DP) and multiband coherent optical orthogonal frequency-division multiplexing (OFDM) signals. It is shown that the RNLE outperforms by 2 dB the linear equalization in a 260-Gb/s DP-OFDM system at 1500 km. The RNLE improves the tolerance to inter/intraband nonlinearities, being independent on polarization tributaries, modulation format, signal bit rate, subcarrier number, and distance.

In this letter, a novel phase noise estimation scheme has been proposed for coherent optical orthogonal frequency division multiplexing systems, the quasi-pilot-aided method. In this method, the phases of transmitted pilot subcarriers are deliberately correlated to the phases of data subcarriers. Accounting for this correlation in the receiver allows the required number of pilots needed for a sufficient estimation and compensation of phase noise to be reduced by a factor of 2 in comparison with the traditional pilot-aided phase noise estimation method. We carried out numerical simulation of a 40 Gb/s single polarization transmission system, and the outcome of the investigation indicates that by applying quasi-pilot-aided phase estimation, only four pilot subcarriers are needed for effective phase noise compensation.

We present the first numerical investigation and comparison of 40-Gb/s lane rate electrical Duobinary, optical Duobinary and PAM-4 for NG-PONs incorporating low complex linear and nonlinear post-equalizations.

A novel artificial neural network (ANN)-based nonlinear equalizer (NLE) of low complexity is demonstrated for 40-Gb/s CO-OFDM at 2000 km, revealing ∼1.5 dB enhancement in Q-factor compared to inverse Volterra-series transfer function based NLE.

Inter-modal nonlinearity in two-mode fiber (TMF) is tackled by Volterra-based nonlinear equalization. For ~260-Gb/s dual-polarization coherent optical OFDM at 1040 km the TMF inter-modal nonlinearity penalty is reduced by up to ~4 dB.

In this paper, a medium access control (MAC) framework tailored for orthogonal frequency-division multiple access passive optical networks (OFDMA-PONs) is defined which allows exploiting both the subcarrier and time domains in a dynamic and flexible way. A dynamic subcarrier assignment algorithm that respects quality of service by offering decreased average delay is proposed. Moreover, effective methods to improve its performance and reduce its complexity are provided. Additionally, the proposed PON MAC framework for the first time leverages on a cross-layer optimization via adaptive quadrature amplitude modulation (QAM) per optical network unit (ONU). The performance of all schemes is evaluated using computer simulations.

The transmission performance of multichannel adaptively modulated optical orthogonal frequency-division multiplexing (AMOOFDM) signals is investigated numerically, for the first time, in optical-amplification-free and chromatic-dispersion-compensation-free intensity-modulation and direct-detection systems directly incorporating modulated distributed feedback (DFB) lasers (DMLs). It is shown that AMOOFDM not only significantly reduces the nonlinear wavelength-division multiplexing (WDM) impairments induced by the effects of cross-phase modulation and four-wave mixing but also effectively compensates for the DML-induced frequency chirp effect. In comparison with conventional modulated optical orthogonal frequency-division multiplexing (OFDM), which uses an identical signal modulation format across all the subcarriers, AMOOFDM improves the maximum achievable signal transmission capacity of a central WDM channel by a factor of 1.3 and 3.6 for 40- and 80-km standard single-mode fibers, respectively, with the corresponding dynamic input optical power ranges being extended by approximately 5 dB. In addition, AMOOFDM also causes the occurrence of cross-channel complementary modulation format mapping among various WDM channels, leading to considerably improved transmission capacities for all individual WDM channels.

Detailed statistical investigations of the effectiveness of three widely adopted optical orthogonal frequency division multiplexing (OOFDM) adaptive loading algorithms, including power loading (PL), bit loading, and bit-and-power loading (BPL), are undertaken, for the first time, over 1000 statistically constructed worst-case multimode fiber (MMF) links without incorporating inline optical amplification. It is shown that the BPL (PL) algorithm always offers the best (worst) transmission performance. The absolute transmission capacity differences between these algorithms are independent of signal bit rate and increase with both transmission distance and digital-to-analog converter/analog-to-digital converter (DAC/ADC) sampling rate. More importantly, numerical results also indicate that, for both worst-case and normal-case MMF links of less than 300 m, in comparison with the most sophisticated BPL algorithm, the simplest PL algorithm is sufficiently effective in escalating the OOFDM MMF system performance to its maximum potential. The effectiveness of the PL algorithm can be further improved when a large number of subcarriers are utilized. On the other hand, for relatively long MMF links (> 800 m) with their 3-dB bandwidths being much less than the transmitted OOFDM signal spectrum, the BPL algorithm has to be adopted. The aforementioned results have great potential for practical cost-effective OOFDM transceiver architecture design.