Multilevel Modulation Research Articles

Mitigation of PAM4 rolling shuttered pattern grayscale ambiguity in demodulation utilizing long short term memory neural network (LSTM-NN) in optical wireless communication systems

One realization of optical wireless communication (OWC) is optical camera communication (OCC), which utilizes mobile-phone and surveillance cameras for communication. One main limitation of OCC system is the low frame rate of typical cameras. To enhance the OCC data rate with limited frame rate cameras, rolling shuttered camera mode can be utilized. However, decoding the rolling shuttered pattern is very challenging. In addition, utilizing multi-level modulation formats, such as four-level pulse-amplitude-modulation (PAM4) can increase the OCC bit-per-symbol; however, it would be a great challenge to identify the multiple intensity levels owing to the uneven aggregated light exposure of each pixel-row. In this work, we put forward and demonstrate utilizing the Long-Short-Term Memory neural-network (LSTM-NN) to alleviate the decoding of high inter-symbol-interference (ISI) of PAM4 rolling shuttered pattern. The experiment is performed in a practical room with 3-m free-space transmission distance. Results show that the proposed LSTM-NN method can significantly enhance the decoding of multiple intensity level rolling shuttered pattern. The proposed scheme also allows a large tilting angle of ±70° between the transmitter (Tx) and receiver (Rx).

Multidimensional Pulsewidth Modulation for Cascaded Split-Source Inverter

Cascaded split-source inverter (CSSI) is a single-stage modular multilevel structure. This article proposes the multidimensional pulsewidth modulation (MD-PWM) for this topology. All multilevel modulations are a particular version of this approach. The principles of this geometrical method are based on selecting the optimal points and determining the switching sequences and time intervals. By considering the operational principles of CSSI, this method is modified to accurately control the voltage of dc links, charge inductors with constant duty cycles, control dc and ac sides of cells independently, and reduce the reverse recovery effects of input diodes. MD-PWM, with a low computational burden, can be implemented for CSSI with any number of voltage levels. The output power can be distributed equally or unequally among cells, and both buck and boost operation modes are realized for each cell. Also, this method is extended for the operation of the converter with unequal input sources. For an asymmetric topology with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> cells, harmonics are located at multiples of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> times switching frequency. Thus, this strategy eliminates low-frequency distortions from the output voltage of asymmetric CSSI. The simulation and experimental results verify the performance and accuracy of the proposed technique and mathematical relations.

Sliding Window Soft-SCL Decoders for Asynchronous Polar-Coded Modulation

Asynchronous polar-coded modulation (A-PCM) outperforms multilevel polar-coded modulation by taking advantage of spatial coupling among several coded blocks. To further improve the performance of A-PCM, a cyclic-redundancy-check (CRC) aided sliding window soft successive cancellation list (CA-SWSCL) decoder is proposed to exploit the benefits of spatial coupling and CRC-aided iterative message passing. This approach includes both soft-output and hard-output iteration processes, where the CRC results are not only used for early termination but also served as an execution flag of the hard-output iteration process. In the case of rate half polar-coded modulation with frame length 128, A-PCM with the proposed CA-SWSCL achieves the best block-error-rate (BLER) performance among the state-of-art polar-coded modulation schemes.

Broadband hyperbolic thermal metasurfaces based on the plasmonic phase-change material In3SbTe2.

Thermal radiation modulation facilitated by phase change materials (PCMs) needs a large thermal radiation contrast in broadband as well as in a non-volatile phase transition, which are only partially satisfied by conventional PCMs. In contrast, the emerging plasmonic PCM In3SbTe2 (IST) that undergoes a non-volatile dielectric-to-metal phase transition during crystallization offers a fitting solution. Here, we have prepared IST-based hyperbolic thermal metasurfaces and demonstrated their capabilities to modulate thermal radiation. By laser-printing crystalline IST gratings with different fill factors on amorphous IST films, we have achieved multilevel, large-range, and polarization-dependent control of the emissivity modulation (0.07 for the crystalline phase and 0.73 for the amorphous phase) over a broad bandwidth (8-14 μm). With the convenient direct laser writing technique that supports large-scale surface patterning, we have also demonstrated promising applications of thermal anti-counterfeiting with hyperbolic thermal metasurfaces.

Gate-tunable plasticity in artificial synaptic devices based on four-terminal amorphous gallium oxide memristors

This paper reports on the demonstration of gate-tunable plasticity in artificial synaptic devices based on four-terminal planar memristors with amorphous gallium oxide as a memristive material. Reproducible resistance switching properties were obtained by applying voltages to the four terminals, indicating two-dimensional modulation of oxygen vacancy distribution. Based on the resistive switching properties, gate-tunable synaptic plasticity was successfully implemented by assigning read/write and gate roles to two pairs of diagonally arranged electrodes. Multilevel modulation of conductance change efficiency was demonstrated, mimicking neural functions of both excitatory principal neurons and inhibitory interneurons required for homeostatic plasticity in biological neural networks.

The Applications of Digital Signal Processing Techniques for Enhancing the Performance of High Speed Optical Communication Systems

This paper presents Improving performance of 112 Gbits optical coherent communications systems using digital signal processing techniques to compensate linear impairments that are exposed to the signal during its propagation in optical fiber. In this paper, different multi-level modulation formats (DP-QPSK, DP 8PSK, DP- 16PSK and DP-16-QAM) were compared for the same data rate at different distances from the transmitter without amplification. the comparison was done by measuring bit error rate value. We used digital signal processing techniques for linear effects compensation. Where chromatic dispersion was compensated using a simple digital filter, and Polarization mod dispersion was realized by applying the constant-modulus algorithm (CMA). The phase and frequency mismatch between the transmitter and the local oscillator in the receiver was compensated using the modified Viterbi-Viterbi algorithm. We used the Optical simulator Opti-system , which was linked with MATLAB R2011 in order to implementation DSP algorithms and analyze obtained results.

Sub-column pixel neural network scheme for modulation format shifting based optical camera communications.

In this Letter, a sub-column pixel neural network (SCPNN) scheme is proposed to label the pixel patterns in modulation format shifting based optical camera communication (MFS-OCC) systems. The MFS scheme, by identifying on-off keying (OOK) and Manchester signal formats, can additionally harvest one-bit information without sacrificing the pixel width per bit, resulting in a higher transmission rate for OCC without multi-level modulation. Compared with the conventional multi-threshold decision (MTD) scheme, the proposed SCPNN can effectively mitigate the impact of inter-symbol interference (ISI) and noise on signal decision by making full use of all pixels in one-bit period. The experimental results show that, in the case of the illuminance as low as 300 lux, the SCPNN scheme can attain a data rate of 8.16 Kbps with an average bit-error-rate (BER) of 2.2 × 10-3 below the HD-FEC limitation of 3.8 × 10-3. Meanwhile, the SCPNN scheme achieves remarkable BER performance improvement compared to both MFS-OCC with MTD scheme and conventional OOK-OCC system.

Self-rolling of vanadium dioxide nanomembranes for enhanced multi-level solar modulation

Thermochromic window develops as a competitive solution for carbon emissions due to comprehensive advantages of its passivity and effective utilization of energy. How to further enhance the solar modulation ({triangle T}_{{{{{{{rm{sol}}}}}}}}) of thermochromic windows while ensuring high luminous transmittance ({T}_{{{{{{{rm{lum}}}}}}}}) becomes the latest challenge to touch the limit of energy efficiency. Here, we show a smart window combining mechanochromism with thermochromism by self-rolling of vanadium dioxide (VO2) nanomembranes to enhance multi-level solar modulation. The mechanochromism is introduced by the temperature-controlled regulation of curvature of rolled-up smart window, which benefits from effective strain adjustment in VO2 nanomembranes upon the phase transition. Under geometry design and optimization, the rolled-up smart window with high {triangle T}_{{{{rm{sol}}}}} and {T}_{{{{{{rm{lum}}}}}}} is achieved for the modulation of indoor temperature self-adapted to seasons and climate. Furthermore, such rolled-up smart window enables high infrared reflectance after triggered phase transition and acts as a smart lens protective cover for strong radiation. This work supports the feasibility of self-rolling technology in smart windows and lens protection, which promises broad interest and practical applications of self-adapting devices and systems for smart building, intelligent sensors and actuators with the perspective of energy efficiency.

Multi-level pulse position modulation scheme for enhancing link capacity in electromagnetic nanocommunication networks

In this letter, a new nanocommunication modulation scheme termed multi-level pulse position modulation (ML-PPM) is proposed. The ML-PPM approach will boost the link capacity of a nanocommunication system while achieving a processing gain in reception. The bit error rate and link capacity of the scheme are evaluated using a non-coherent energy detection nanoreceiver. Simulation results show that the proposed scheme has a substantially greater link capacity than the existing schemes including time-spread on–off keying (TS-OOK) and M -ary pulse position modulation (PPM).

Nonlinear Channel Equalization Using Gaussian Processes Regression in IMDD Fiber Link

Gaussian processes regression (GPR)-aided nonlinear channel equalizer (CE) is experimentally demonstrated in a multi-level intensity modulation and direct detection fiber link. In this scheme, the GPR model is used to estimate the transmitted symbols or the corresponding nonlinear distortions after pre-processing. The experimental results show that GPR-aided nonlinear CE has better nonlinear tolerance than conventional linear and nonlinear filter-based CE. It is also shown that the GPR model in the nonlinear channel equalization process can be understood as an optimized single-layer neural network model with infinite width. Finally, we reveal the relationship between the key coefficients in GPR model and parameters in fiber link through both experiment and simulation.

Biosensor-assisted titratable CRISPRi high-throughput (BATCH) screening for over-production phenotypes

With rapid advances in the development of metabolic pathways and synthetic biology toolkits, a persisting challenge in microbial bioproduction is how to optimally rewire metabolic fluxes and accelerate the concomitant high-throughput phenotype screening. Here we developed a biosensor-assisted titratable CRISPRi high-throughput (BATCH) screening approach that combines a titratable mismatch CRISPR interference and a biosensor mediated screening for high-production phenotypes in Escherichia coli. We first developed a programmable mismatch CRISPRi that could afford multiple levels of interference efficacy with a one-pot sgRNA pool (a total of 16 variants for each target gene) harboring two consecutive random mismatches in the seed region of sgRNA spacers. The mismatch CRISPRi was demonstrated to enable almost a full range of gene knockdown when targeting different positions on genes. As a proof-of-principle demonstration of the BATCH screening system, we designed doubly mismatched sgRNA pools targeting 20 relevant genes in E. coli and optimized a PadR-based p-coumaric acid biosensor with broad dynamic range for the eGFP fluorescence guided high-production screening. Using sgRNA variants for the combinatorial knockdown of pfkA and ptsI, the p-coumaric acid titer was increased by 40.6% to o 1308.6 mg/l from glycerol in shake flasks. To further demonstrate the general applicability of the BATCH screening system, we recruited a HpdR-based butyrate biosensor that facilitated the screening of E. coli strains achieving 19.0% and 25.2% increase of butyrate titer in shake flasks with sgRNA variants targeting sucA and ldhA, respectively. This work reported the establishment of a plug-and-play approach that enables multilevel modulation of metabolic fluxes and high-throughput screening of high-production phenotypes.

Individualized Short-Term Electric Load Forecasting Using Data-Driven Meta-Heuristic Method Based on LSTM Network.

Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units. Thus, it is imperative to present new incentive methods to motivate such power system operations for electricity management. This paper proposes an approach for short-term electric load forecasting using long short-term memory networks and an improved sine cosine algorithm called MetaREC. First, using long short-term memory networks for a special kind of recurrent neural network, the dispatching commands have the characteristics of storing and transmitting both long-term and short-term memories. Next, four important parameters are determined using the sine cosine algorithm base on a logistic chaos operator and multilevel modulation factor to overcome the inaccuracy of long short-term memory networks prediction, in terms of the manual selection of parameter values. Moreover, the performance of the MetaREC method outperforms others with regard to convergence accuracy and convergence speed on a variety of test functions. Finally, our analysis is extended to the scenario of the MetaREC_long short-term memory with back propagation neural network, long short-term memory networks with default parameters, long short-term memory networks with the conventional sine-cosine algorithm, and long short-term memory networks with whale optimization for power load forecasting on a real electric load dataset. Simulation results demonstrate that the multiple forecasts with MetaREC_long short-term memory can effectively incentivize the high accuracy and stability for short-term power load forecasting.

Adaptive PAM-4/PAM-8 graphene-based electro-optical modulator integrated into a polymer waveguide platform for data-center communication

This paper presents a new concept of a graphene-based adaptive modulator for multilevel amplitude modulation on polymer technology platform. This component consists of an electro-optical modulator with a distributed five segments capacitive structure, based on two single-layers of graphene (SLG) and a thin layer of silicon nitride (Si3N4) in the form (SLG-Si3N4-SLG), which shows a dynamic configuration of the modulation scheme, PAM-4/PAM-8, by the applied logic voltage sequence (3Vpp) for an operating wavelength at 1550 nm. Considering an extinction ratio of 5.6 dB for PAM-4, and 6.0 dB for PAM-8, a compact device with 179.6 µm total length, and the maximum simulated cut-off frequency of 48.12 GHz with 122.9 fF of capacitance and total device resistance of 26.9 Ω, were achieved. This cut-off frequency results in a transmission rate of 96.24 Gbps at PAM-4 and 144.4 Gb/s at PAM-8. The simulated insertion loss is 12.0 dB (PAM-4) and 11.5 dB for PAM-8, and the power consumption is 0.54 pJ/bit for PAM-4 and 0.81 pJ/bit for PAM-8. Combining an innovative design with the unique electro-optical characteristics widely demonstrated by the materials used in the construction of the proposed adaptive device, allows it to be seen as a candidate to contribute to the nanotechnology integration and high-performance communication requirements.

Minimization of total harmonic distortion in neutral point clamped multilevel inverter using grey wolf optimizer

&lt;span lang="EN-US"&gt;The inverter has been attracting researchers for their application in renewable energy. So far, multilevel inverter is considered as low distortion class, which produces multilevel output voltage imitating a pure sine waveform. However, the needs for free distortion of output voltage have been motivating to improve multilevel pulse width modulation PWM generation method. In this paper, the modified PWM technique is proposed to reduce the voltage total harmonics distortion (THD) of multilevel inverter. This modulation technique is then applied to control a single-phase threelevel neutral point clamped multilevel inverter (NPC-MLI). Grey wolf optimizer (GWO) algorithm is utilized to generate optimal amplitude and phase shift of modified reference signal. The GWO algorithm is then compared with other optimization algorithms such as differential evolution (DE), human psychology optimization (HPO), and particle swarm optimization (PSO) to evaluate their performance in harmonic minimization. The performance of the proposed work is validated through simulation and experimentation on a prototype. The results show that the modified PWM technique optimized with GWO can reduce THD on NPC-MLI output voltage.&lt;/span&gt;

A New Modeling and Control Scheme for Cascaded Split-Source Converter Cells

Cascaded split-source inverter (CSSI) is a new single-stage modular multilevel topology. Each cell of this converter converts dc to ac power in the buck or boost operation mode without any additional power switch. This article develops a design method based on a detailed model for CSSI. This model shows that energy storage elements experience double-fundamental frequency ripples besides high-frequency ones. It accurately calculates voltage gains and capacitor voltage and inductor current ripples. On the other hand, common carrier-based multilevel modulations have been modified in terms of both reference and carrier signals to control the inverter under symmetric and asymmetric conditions. With proposed simple modulations, the cell inductor is charged with the constant duty cycle. Also, the reverse recovery of diodes occurs in the minimum level of input current once per switching cycle and output power is distributed equally between cells. These characteristics reduce power losses, the input inductance of each cell, and the complexity of the system model. By phase-shifted pulsewidth modulation (PWM), the output voltage harmonics of three-cell CSSI are centralized around multiples of the triple switching frequency. In this method, high-frequency ripples on the network impedance are one-third of those in level-shifted PWM. Also, CSSI has been compared with cascaded multilevel inverters with voltage boosting ability and other SSI-based multilevel topologies. Validity of operation principles, mathematical relations, and modulation schemes are verified through simulation and experimental results.

A robust high-performance electronic synapse based on epitaxial ferroelectric Hf0.5Zr0.5O2 films with uniform polarization and high Curie temperature

Ferroelectric tunnel junction (FTJ) is a promising emerging memristor for the artificial synapse in neuro-inspired computing, which has parallel data processing and low power consumption. The achievement of high-performance electronic synapses requires in-depth exploration of the correlation between the material properties and the device performances as well as the related physical mechanism, which are, however, still quite lacking. We demonstrate here a robust electronic synapse realized by epitaxial ferroelectric Hf0.5Zr0.5O2 (HZO) films with a high Curie temperature of 930 °C and a pristine highly uniform polarization. Based on the optimized ferroelectric HZO film and in-depth understanding of the FTJ mechanism, a robust and high-performance electronic synapse has been successfully realized with high ON/OFF ratio of >500, large continuous conductance regulation range of 1–250 nS and high reliability with the retention of >104 s. Such electronic synapses show good multilevel conductance modulations and synaptic behaviors, such as long-term potentiation (LTP), long-term depression (LTD) and spike-timing dependent plasticity (STDP). A simulated neural network with the synaptic characteristics indicates high recognition accuracy (93.7%) for MNIST database. These results pave a pathway to apply HZO based electronic synapses as the active block in future neuromorphic computing.

Multilevel hysteresis modulation (MHM) for sliding mode controlled dual inverter PV systems

In this article, proposes an adaptive multiband hysteresis modulation and its characterization based on a robust nonlinear sliding-mode control (RNSMC) strategy of a dual two-level inverter topologies for photovoltaic (PV) system subject to robust and fast-tracking characteristics and external disturbance rejection. Using the RNSMC based novel, vector control schemes are designed and implemented to improve its robustness and against the rejection of external disturbances. The control scheme ensures the active power is stable across the whole operation of the PV systems (standalone and grid-connected). The reachability and stability analysis are obtaining the robustness of the controller. Tsypkin’s method is used to realize the switching frequency characterization. The development and implementation approach of the proposed control strategy is thoroughly detailed, and its effectiveness is validated on the simulation and real-time laboratory tests. Moreover, the proposed scheme is superior in keeping the enhanced efficiency, multilevel voltage waveforms, and total harmonic distortion (THD) reduction in current within the necessary standard limitations even under different operating conditions.

Analysis of digital pre-distortion with I/O interfaces for analog baseband signal over broadcasting satellites

Broadcasting satellite systems currently use multilevel modulation schemes, which are vulnerable to non-linear distortion, while their on-board amplifiers operate near the saturation point. We have developed a digital pre-distortion (DPD) embedded transmitter and demonstrated its effectiveness over a 12-GHz-band satellite transponder. To improve its versatility, we developed an external DPD adder, which enables existing transmitter to give an analog baseband signal its function. In this study, we confirm the effectiveness of the external DPD adder by evaluating the transmission performance of 64APSK over the satellite transponder.

Broadband Optical Heterodyne Millimeter-Wave-over-Fiber Wireless Links Based on a Quantum Dash Dual-Wavelength DFB Laser

We demonstrate real-time broadband multi-Gb/s electrical RF synthesizer-free millimeter-wave (MMW) signals generation and wireless transmission at the 5G new radio (NR) frequency band of 47 GHz based on analog radio-over-fiber (A-RoF) fronthaul. This is enabled by a low noise, highly correlated, monolithic C-band semiconductor InAs/InP quantum-dash (QDash) dual-wavelength distributed feedback (DW-DFB) laser. One laser mode is encoded using 4-/6-GBaud multilevel quadrature amplitude modulation (M-QAM) (16-/32-/64-QAM) baseband data signals, the other lasing mode is used as an optical local oscillator for optical-heterodyne remote up-conversion to a MMW carrier of 47.27 GHz. Consequently, optical baseband modulated data signals with data capacity up to 36 Gb/s (6-GBaud × 64-QAM) are transmitted through back-to-back (BtB) and 25-/50-km of standard single mode fiber (SSMF) before the MMW carrier is optically synthesized remotely for free space wireless data transmission and detection over up to 9-m. The end-to-end MMW-over-fiber (MMWoF) wireless link is thoroughly characterized exhibiting promising error-vector-magnitude (EVM) and bit-error-rate (BER) values. The 4-/6-GBaud 16-QAM MMWoF wireless links achieve EVMs down to 6.32%/7.33%, 6.71%/7.78%, and 7.35%/8.91% through BtB, 25-km, and 50-km SSMF, respectively. Similarly, the EVM for 32-QAM and 64-QAM links is observed to be 5.56%/6.56% and 6.05%/6.62%, respectively. Moreover, in each case, the calculated BER is below the forward error correction (FEC) limit of 3.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . The results corroborate the potential and viability of the QDash DW-DFB laser as a simple, efficient and cost-effective alternative to individual laser sources for deployment in broadband photonic MMWoF fronthaul systems of 5G wireless networks.

Metabolomics and lipidomics insight into the effect of different polyamines on tomato plants under non-stress and salinity conditions

Polyamines (PAs) are key signaling molecules involved in plant growth and stress acclimation processes. This work investigated the effect of spermidine, spermine, and putrescine (alone and in a mixture) in tomato plants using a combined metabolomics and lipidomics approach. The experiments were carried out under non-stress and 100 mM NaCl salinity conditions. Shoot and root biomass, as well as SPAD values, were increased by the application of exogenous PAs but with differences across treatments. Similarly, root length density (F: 34, p < 0.001), average root diameter (F: 14, p < 0.001), and very fine roots (0.0–0.5 mm) increased in PA-treated plants, compared to control. Metabolomics and lipidomics indicated that, despite being salinity the hierarchically prevalent factor, the different PA treatments imposed distinct remodeling at the molecular level. Plants treated with putrescine showed the broader modulation of metabolite profile, whereas spermidine and spermine induced a comparatively milder effect. The pathway analysis from differential metabolites indicated a broad and multi-level intricate modulation of several signaling molecules together with stress-related compounds like flavonoids and alkaloids. Concerning signaling processes, the complex crosstalk between phytohormones (mainly abscisic acid, cytokinins, the ethylene precursor, and jasmonates), and the membrane lipids signaling cascade (in particular, sphingolipids as well as ceramides and other glycerophospholipids), was involved in such complex response of tomato to PAs. Interestingly, PA-specific processes could be observed, with peculiar responses under either control or salinity conditions.