0.5-bit/s/Hz fine-grained adaptive OFDM modulation for bandlimited underwater VLC.

In this paper, we propose and demonstrate a 0.5-bit/s/Hz fine-grained adaptive orthogonal frequency division multiplexing (OFDM) modulation scheme for bandlimited underwater visible light communication (UVLC) systems. Particularly, integer spectral efficiency is obtained by conventional OFDM with quadrature amplitude modulation (QAM) constellations, while fractional spectral efficiency is obtained by two newly proposed dual-frame OFDM designs. More specifically, OFDM with dual-frame binary phase-shift keying (DF-BPSK) is designed to achieve a spectral efficiency of 0.5 bit/s/Hz, while OFDM with dual-frame dual-mode index modulation (DF-DMIM) is designed to realize the spectral efficiencies of 0.5+n bits/s/Hz with n being a positive integer (i.e., n = 1, 2, …). The feasibility and superiority of the proposed 0.5-bit/s/Hz fine-grained adaptive OFDM modulation scheme in bandlimited UVLC systems are successfully verified by simulations and proof-of-concept experiments. Experimental results demonstrate that a significant achievable rate gain of 18.6 Mbps can be achieved by the proposed 0.5-bit/s/Hz fine-grained adaptive OFDM modulation in comparison to the traditional 1-bit/s/Hz granularity adaptive OFDM scheme, which corresponds to a rate improvement of 22.1%.

Optimized pilot structure for PS-PDM ultrahigh-order QAM coherent optical transmission.

We proposed and experimentally demonstrated a general pilot structure for probabilistic shaped (PS)-polarization division multiplexing (PDM) M-ary quadrature amplitude modulation (MQAM) coherent optical transmission, where a portion of PS-MQAM symbols is exploited as the pilot symbols with the same information entropy as the transmitted signal. The pilot symbols are simultaneously used in the entire digital signal processing (DSP) modules for polarization de-multiplexing, frequency offset estimation, carrier phase recovery, nonlinear equalization, and linear equalization. Compared to the conventional quadrature phase shift keying (QPSK) pilot structure, the proposed MQAM pilot structure can yield the nonlinear properties of the overall signal so that nonlinear equalization can effectively improve the performance of the normalized generalized mutual information. The remarkable performance has been achieved at the shaping parameters of 3.25 and 4.35 for 1024QAM and 4096QAM signals based on the proposed pilot scheme, which corresponds to the raw spectral efficiency of 16.190 and 20.381 bit/s/Hz, respectively. The pilot ratio is optimized to 5% for higher achievable information rates (AIRs).

Theoretical investigations of weakly- and strongly-coupled multi-core fibers for the applications of optical submarine communications under power and fiber count limits.

The practical cable design for optical submarine communications has a limited fiber pair count due to the mechanical considerations of cable weight and size. Consequently, multi-core fibers (MCFs) could exhibit higher capacity than conventional single-mode fibers (SMFs) thanks to space division multiplexing (SDM). That is because the power supply to a submarine cable is fed by the voltage difference between shores. Under the power-limited condition, SDM improves the cable capacity by using more paths which outperforms the SMF link whose capacity approximately complies with a logarithmic relationship to optical power. At the same time, fiber nonlinearity can be alleviated by the reduced power density of transmitted light in MCFs, due to the increased spatial diversity and mode coupling among coupled cores. In this work, we theoretically investigate the potentials of MCFs including weakly-coupled multicore fiber (WC-MCF) and strongly-coupled multicore fiber (SC-MCF) as the propagation media for submarine communications across the Atlantic and the Pacific. To fairly compare the performances of SMFs- and MCFs-based submarine cables, the Gaussian noise (GN) model for SDM links is employed to optimize the systematic settings including spatial multiplicity and single span length. Then, we develop an SDM and wavelength division multiplexing (WDM) fiber transmission model based on coupled nonlinear Schrodinger equations (CNSE) to investigate the optical filed coupling effect in MCFs-based cables. The developed transmission model has been self-examined by measuring the inter-core crosstalk (IC-XT) and spatial mode dispersion (SMD), referring to the set values. As indicated by the theoretical analysis, the WC-MCFs cable exhibits a larger capacity than the SMFs cable, when the fiber pair count is limited below 32. Moreover, the SC-MCFs cable outperforms the WC-MCFs cable thanks to the reduced fiber nonlinearity due to the random mode coupling and the assistance of multiple-input and multiple-output digital signal processing (MIMO-DSP). At last, the marginal influences of IC-XT, SMD, and insertion loss of Fan-in and Fan-out couplers are also analyzed for the MCFs cable.

Demonstration of an 800G CDM-SDM coherent PON utilizing weakly coupled multicore fibers with CDM tributary manipulation.

In this Letter, we present an experimental demonstration of downstream signaling in a 16 × 50 Gbit/s coherent passive optical network (CPON) using the code and space division multiplexing (CDM-SDM) approach. We realize optical SDM through the utilization of a 4-core weakly coupled multicore fiber (WC-MCF), enhancing the total available optical launch power at the optical line terminal (OLT). This enhancement significantly improves the power budget for CPONs that connect with a large number of optical network units (ONUs). At the second stage of the CPON, four CDM-assigned ONUs are connected to individual cores of the WC-MCF, thereby supporting the connectivity of up to 16 ONUs. Through experiments, we have noted substantial disparities in the downstream signaling performance among individual CDM-assigned ONUs, particularly as the capacity is increased to 800 Gbit/s. To address this issue, we have employed an innovative approach by leveraging space-time coding techniques to manipulate the CDM tributaries, to achieve a balanced reception performance for all ONUs within the CPON. We believe that the proposed CDM-SDM CPON scheme, complemented by the advanced DSP flow chart, holds significant promise for future PON systems characterized by substantial capacity and extensive connectivity.

Low-latency and efficient retiming and equalizing scheme for a 112-Gbps bandwidth-limited optical PAM-4 system.

The bandwidth limitation of optoelectronic devices is a key constraint for realizing higher capacity short-reach optical communication systems. In this work, we show that the performance of the timing recovery algorithm will significantly impact the performance of bandwidth-limited optical PAM-4 signals. To address this problem, we introduce a moving average filter (MAF) into the Gardner retiming loop to realize ultra-stable retiming without any pilot symbols. It enables a significantly reduced timing jitter, especially for bandwidth-limited conditions. Based on simulations, we show that the proposed retiming scheme will give a stable sampling phase, which is beneficial to the performance of the decision feedback equalizer. Compared to the system based on the traditional Gardner timing synchronization algorithm, the 2-dB power budget gain is realized. The proposed method improves the equalization performance of short-reach optical communication systems where complexity and processing latency are important concerns.

Complex-valued decision feedback equalizer for optical IMDD signals with adaptive manipulations in time and amplitude domains.

In this work, we innovatively equalize optical intensity-modulated and directly detected (IMDD) four-level pulse amplitude modulation (PAM-4) signals using a complex-valued decision feedback equalizer (CDFE). Through mapping adjacent symbols of PAM-4 signals onto the complex domain, the influence of strongest inter-symbol interference (ISI) can be alleviated during the decision process in a decision feedback equalizer (DFE), effectively combating burst-error propagation when signals are noisy. Moreover, signal-adaptive manipulations of DFE parameters in both the time and the amplitude domain are performed by using an ultra-stable timing recovery and level-adaptive decision. Performance evaluations are made on vertical cavity surface emitting laser (VCSEL) modulated and multimode fiber (MMF) transmitted 100-Gbit/s optical PAM-4 signals. Based on experimental results of the short-reach optical communication, the proposed DFE outperforms the traditional DFE with a 0.5-dB system power budget gain at the 7% overhead (OH) forward error correction (FEC) bit error rate (BER) threshold.

Improving the spectral efficiency of visible light communications by a super-Nyquist multi-band CAP modulation.

In this Letter, we propose a flexible bandwidth compression scheme for visible light communication (VLC) systems employing multi-band carrierless amplitude and phase (CAP) modulation. The scheme combines a narrow filtering for every subband at the transmitter and an N-symbol look-up-table (LUT) based maximum likelihood sequence estimation (MLSE) at the receiver. The N-symbol LUT is generated by recording pattern-dependent distortions induced by inter-symbol-interference (ISI), inter-band-interference (IBI), and the other channel effects upon the transmitted signal. The idea is experimentally demonstrated on a 1 m free space optical transmission platform. The results show that the proposed scheme can improve the subband overlap tolerance up to 42% in subband overlapping scenarios, that is, 3 bit/s/Hz, which is the highest spectral efficiency (SE) among the experimented schemes.

Collaborative spectrum sensing for cognitive visible light communications.

Cognitive visible light communication (VLC) has attracted increasing attention. By sharing underutilized VLC spectrum resources of primary users (PUs) with secondary users (SUs) opportunistically, improved spectrum utilization can be achieved without interfering with PUs. As an essential component in cognitive VLC, reliable spectrum sensing is crucial to ensure accurate cognition of PU's signal. However, due to limiting factors such as low signal-to-noise ratio (SNR) and link blocking in VLC systems, it would be difficult for a single SU to identify the status of PUs accurately and rapidly. To tackle this issue, we propose a new collaborative sensing (CS) scheme which can enhance sensing accuracy effectively by coordinating multiple SUs to participate in spectrum sensing. To evaluate the performance of the proposed CS scheme, we first develop an analytical model for the scenario of a single SU, subject to various factors such as indoor reflections and signal sampling size. Next, based on the single-SU evaluation, we further analyze the performance of the CS scheme by extending the single-SU analytical models to the multi-SU scenario. It is found that the analytical models can accurately predict the performance of the proposed CS scheme and match the results obtained by simulations. Moreover, the proposed CS scheme is effective in improving the sensing accuracy by about 40% and 10% compared with the local-sensing and the conventional CS schemes, respectively.

Intelligent adaptive coherent optical receiver based on convolutional neural network and clustering algorithm.

In a cognitive, heterogeneous, optical network, it would be important to identify physical layer information, especially the modulation formats of transmitted signals. The modulation format information is also indispensable for carrier-phase-recovery in a coherent optical receiver. Because constellation diagrams of modulation signals are susceptible to various noises, we utilize a convolutional neural network to process the amplitude data after the modulation-format-agnostic clock recovery. Furthermore, for the carrier-phase-recovered data, we use the clustering method based on a fast search and find the density peaks to classify the constellation clusters and use the k-nearest-neighbor method to label the samples. The proposed receiver system has a simple architecture to identify the modulation format based on the amplitude information and can track fast changes of the signals to improve the accuracy of the symbol decision. We have demonstrated this experimentally and have achieved remarkable BER improvement.

K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system.

In this work, we proposed two k-means-clustering-based algorithms to mitigate the fiber nonlinearity for 64-quadrature amplitude modulation (64-QAM) signal, the training-sequence assisted k-means algorithm and the blind k-means algorithm. We experimentally demonstrated the proposed k-means-clustering-based fiber nonlinearity mitigation techniques in 75-Gb/s 64-QAM coherent optical communication system. The proposed algorithms have reduced clustering complexity and low data redundancy and they are able to quickly find appropriate initial centroids and select correctly the centroids of the clusters to obtain the global optimal solutions for large k value. We measured the bit-error-ratio (BER) performance of 64-QAM signal with different launched powers into the 50-km single mode fiber and the proposed techniques can greatly mitigate the signal impairments caused by the amplified spontaneous emission noise and the fiber Kerr nonlinearity and improve the BER performance.

Protection lightpath-based hitless spectrum defragmentation for distance adaptive elastic optical networks.

Spectrum defragmentation can improve spectrum utilization for an elastic optical network (EON). However, most of the existing studies have focused on defragmentation for working lightpaths, which may affect upper-layer network services. This paper considers protection lightpath-based hitless spectrum defragmentation for distance adaptive elastic optical networks. Without affecting working lightpaths, but defragmenting spectra for protection lightpaths, we expect to achieve truly hitless spectrum defragmentation for an EON. Shared backup path protection (SBPP) technique is employed as a representative network protection technique to evaluate the benefit of the proposed defragmentation scheme. To smooth the network spectra for future arriving lightpath requests so as to reduce bandwidth blocking probability (BBP), we propose two defragmentation triggering mechanisms, namely, defragmentation upon blocking (BTD) and batch defragmentation (BD). For each of them, we also propose two spectrum defragmentation algorithms, namely, defragmentation with sequentially releasing and re-establishing protection lightpaths (SR-D) and defragmentation with jointly releasing and re-establishing protection lightpaths (JR-D). The performances of these proposed algorithms are evaluated from perspectives of BBP and average number of reconfigurations per successfully established lightpath service (ANR). Simulation results show that compared to the case without defragmentation, the proposed scheme is effective to reduce BBP, which trades off with ANR.

Benefit of adaptive FEC in shared backup path protected elastic optical network.

We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

Adaptive CL-BFGS Algorithms for Complex-Valued Neural Networks.

Complex-valued limited-memory BFGS (CL-BFGS) algorithm is efficient for the training of complex-valued neural networks (CVNNs). As an important parameter, the memory size represents the number of saved vector pairs and would essentially affect the performance of the algorithm. However, the determination of a suitable memory size for the CL-BFGS algorithm remains challenging. To deal with this issue, an adaptive method is proposed in which the memory size is allowed to vary during the iteration process. Basically, at each iteration, with the help of multistep quasi-Newton method, an appropriate memory size is chosen from a variable set {1,2, ... , M} by approximating complex Hessian matrix as close as possible. To reduce the computational complexity and ensure desired performance, the upper bound M is adjustable according to the moving average of memory sizes found in previous iterations. The proposed adaptive CL-BFGS (ACL-BFGS) algorithm can be efficiently applied for the training of CVNNs. Moreover, it is suggested to take multiple memory sizes to construct the search direction, which further improves the performance of the ACL-BFGS algorithm. Experimental results on some benchmark problems including the pattern classification, complex function approximation, and nonlinear channel equalization problems are given to illustrate the advantages of the developed algorithms over some previous ones.