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In the process of digital image acquisition, color inconsistency is a common issue due to the influence of photographic conditions. The inconsistency of color affects the quality of digital orthophoto products and subsequent applications significantly, and this issue remains challenging both in the academia and industry. This paper proposes a color equalization method for aerial image based on block adjustment and an improved color balance model based on the analysis of causes for color deviation. Two nonlinear functions are used to simulate the process of color deviation and correct the color of images. Due to the existence of error, the color corrected images still have minor deviations in the color of the overlapped regions. Therefore, this research introduces an error equation to address this issue and uses the least square principle to calculate the adjustment. The simulation experiments and real experiments are carried out on several groups of aerial image data respectively. The results show that the method not only achieves better visual effect but also has a higher adjustment precision. Finally, the rationality and parameters of the model proposed in this paper are discussed.

The multi-hop protocols are proved effective in the railway disaster wireless monitoring system. However, farther transmission distance with the larger data will decline the valid lifetime and reliability of the system. Most existing studies focused primarily on the communication protocols optimization, and some works tried to utilize the limited computation ability at the network-level or node-level, which are insufficient for the stiff disaster information monitoring demands. This paper presents an adaptive hybrid computation and communication strategy to fully taking advantage of the sensor processing ability, and improve the energy efficiency at the link-level. Furthermore, an adaptive optimization model is designed to meet the different monitoring demands of the system, and the valid lifetime is improved accordingly. Numerical examples with various operational scenarios are developed to demonstrate the superiority and practicality of the proposed protocol in the lifetime improvement, energy consumption minimization and equalization compared with other outstanding protocols.

Data-dependent superimposed training (DDST) scheme has shown the potential to achieve high bandwidth efficiency, while encounters symbol misidentification caused by hardware imperfection. To tackle these challenges, a joint model and data driven receiver scheme is proposed in this paper. Specifically, based on the conventional linear receiver model, the least squares (LS) estimation and zero forcing (ZF) equalization are first employed to extract the initial features for channel estimation and data detection. Then, shallow neural networks, named CE-Net and SD-Net, are developed to refine the channel estimation and data detection, where the imperfect hardware is modeled as a nonlinear function and data is utilized to train these neural networks to approximate it. Simulation results show that compared with the conventional minimum mean square error (MMSE) equalization scheme, the proposed one effectively suppresses the symbol misidentification and achieves similar or better bit error rate (BER) performance without the second-order statistics about the channel and noise.

This work deals with the design and validation of a control strategy for hybrid balancing systems (HBSs), an emerging concept that joins battery equalization and hybridization with supercapacitors (SCs) in the same system. To control this system, we propose a two-layer model predictive control (MPC) framework. The first layer determines the optimal state-of-charge (SoC) reference for the SCs considering long load forecasts and simple pack-level battery models. The second MPC layer tracks this reference and performs charge and temperature equalization, employing more complex module-level battery models and short load forecasts. This division of control tasks into two layers, running at different time scales and model complexities, enables us to reduce computational effort with a small loss of control performance. Experimental validation in a small-scale laboratory prototype demonstrates the effectiveness of the proposed approach in reducing charge, temperature, and stress in the battery pack.

High-performance and safe operation of a serially connected lithium-ion battery pack in the electric vehicle necessitates effective cell equalization to maintain the state-of-charge of each cell at the same level. In this work, an improved module-based cell-to-pack-to-cell (CPC) equalization system is developed, where the module-level (ML)/cell-to-module-to-cell (CMC) equalizers are utilized for equalization of the battery modules/cells in each module. Compared with the conventional CPC balancing system, it has the advantages of simple modular structure and convenient maintainability. Then, a two-layer model predictive control (MPC) strategy is proposed, in which the ML equalizers are controlled by the top-layer MPC and the controlled CMC equalizing currents in each module are designed by the bottom-layer MPC algorithms in parallel. Its computational complexity is much less than the centralized MPC, which makes it more feasible for real-time cell equalization implementation in practical applications. A rigorous mathematical convergence proof of the proposed equalization control strategy is provided based on the Lyapunov stability theorem. At last, extensive results are provided to verify the proposed improved module-based CPC equalization system and the two-layer MPC-based equalization control approach with excellent equalization performance being demonstrated.

This article proposes a new design approach of the wideband passive equalizer for improving the gain flatness with multiple peaks which often appears in the modern transmitter systems, and the general design formulas of this passive equalizer under different practical circumstances are obtained through theoretical analysis. The proposed equalizer mainly adopts multi-stage RCL series or parallel resonant circuit structure. According to the actual multi-peak gain flatness, the structure of the single-stage equalizer, the combination mode of each stage, and the required number of stages can be determined. The proposed equalizer can design the equalization frequency, bandwidth and attenuation flexibly according to the actual situation. Finally, the proposed design approach has been well verified by experimental tests of two four-stage broadband passive equalizers with different structures operating in 0.5-2 GHz.

An optical transmitter (TX) data path is demonstrated in 28-nm CMOS which drives an 850-nm vertical-cavity surface-emitting laser (VCSEL) up to 56 Gb/s non-return-to-zero (NRZ). A dc-coupled single-ended voltage-mode driver employs area- and energy-efficient equalization techniques including slew-rate-based pulse-shaping at 2x more energy- and area-efficient than optical TXs reported to date. The highly digital circuit architecture enables the supply scalability to 0.7 and 0.85 V to operate the TX at 32 and 40 Gb/s at 0.56 and 0.77 pJ/b, respectively, which is ≥ 4x more energy-efficient than the prior art.

This paper presents a gain-equalized Ka-band Rotman lens-fed antenna by using phase gradient transmission lines (PGTLs). With PGTLs, the variation trend of the output progressive phase differences among the feeding ports are inverted. The aperture loss of the planar antenna array is then partially compensated by the efficiency of the lens when performing a wide-angle beam scanning. Hence, gain equalization is achieved among multiple beams with an acceptable gain degradation. To reduce the total size, the Rotman lens with PGTLs, the feeding networks, and the antenna array are stacked vertically. Meanwhile, the feeding network is implemented with substrate integrated coaxial lines, suppressing the parallel-plate-mode inside the multilayer structure. In order to validate the proposed design, a compact Rotman lens fed antenna operating at 24.75-27.5 GHz (FBW=10.5%) is designed and fabricated. The results show that the gain drop of the Rotman lens-fed multibeam antenna is reduced from 4.4 dB to 1.5 dB at the design frequency of 26 GHz, covering a wide angular range between ±56∘.

Semiconductor optical amplifier (SOA) is a promising solution for future O-band optical amplification. However, the SOA-induced nonlinearity will affect the quality of the signals and cause bit errors. Nowadays, the neural network is a hot topic in communication networks and has been considered a practical algorithm for signals equalization. In this paper, we investigate the performance of the three types of neural networks: deep neural networks (DNN), convolutional neural network (CNN), and long short term memory (LSTM) neural networks for the compensation of the SOA-induced nonlinearity. We first compare the fitting ability of the three neural networks on the saturated response of SOA. Based on the simulation result, LSTM has the best nonlinear expressiveness for the SOA-induced nonlinearity. Subsequently, we do some experimental validations in an intensity modulation and direct-detection (IM/DD) system, where the 100 Gbit/s pulse-amplitude-modulation-4 (PAM4) signals are transmitted over 80 km at O-band using an 18 GHz electro-absorption modulated laser (EML). The bit-error-ratio (BER) results show that the cell states in LSTM play a crucial role in nonlinearity compensation. Furthermore, LSTM offers the best equalization performance and can achieve a receiver sensitivity of -18.0 dBm.

Addressing the nonlinearity induced signal degradation is of critical importance for harvesting the transparent benefits of analog radio over fiber (A-RoF architecture, to support mobile fronthaul (MFH with high spectral efficiency and reduced latency. Here, for linearizing the low-latency A-RoF MFH using digital-domain fast Fourier transform /inverse fast Fourier transform (FFT/IFFT assisted channel aggregation/de-aggregation (CA/DA, we propose and experimentally demonstrate a compatible adaptive frequency-domain (FD nonlinear equalization scheme with much lower computational complexity, while delivering comparable performance to the popular time-domain Volterra nonlinear equalizer. The proposed low-complexity equalization scheme is implemented using the FD two-box cascaded Hammerstein structure, which is capable of simplifying coefficients estimation, achieving computational efficient equalization, reusing the FFT/IFFT calculation in channel DA and sharing legacy simple one-tap FD linear equalization strategy in OFDM system. Experimental validations of our proposal are carried out in typical electroabsorption modulator (EAM and Mach-Zehnder modulator (MZM based intensity modulation and direct detection (IMDD A-RoF links. Cost-effective fiber-optic (with EAM and optical up-conversion enabled V-band millimeter-wave (mm-wave fiber-wireless (with MZM transmissions are demonstrated. Experimental results show that the proposed scheme can effectively improve the performances of both EAM and MZM based 10-km fiber-optic A-RoF MFH links, in terms of adjacent channel leakage ratio reduction (>8 dB, error-vector magnitude amelioration (>10 dB and EVM-compliant input IF power range enhancement (>5 dB, with an input signal aggregating 8 125-MHz 64-QAM OFDM channels. Furthermore, our scheme enables the transmission of a 5-Gbit/s aggregated intermediate-frequency 64-QAM signal over 10-km fiber link and 1.2-m 60-GHz wireless channel, wherein a >12 dB improved input power margin is observed.

The performance of high-speed intensity modulation direct detection (IM-DD) transmissions is severely degraded by the linear inter-symbol interference (ISI), due to both bandwidth-constrained optoelectrical components and the chromatic dispersion (CD). Meanwhile, nonlinear ISI due to intensity modulation and square-law detection can further deteriorate the IM-DD system performance significantly. Here, we first propose three metrics to quantify those impairments in IM-DD transmissions. Then, we compared both the BER performance and computational complexity of different DSP schemes, using a C-band PAM-4 experimental test-bed with an end-to-end 10-dB bandwidth of 17 GHz. Those DSP schemes include receiver-side feedforward equalization (FFE), receiver-side Volterra filter equalization (VFE), transmitter-side Tomlinson-Harashima precoding (THP) together with receiver-side FFE, transmitter-side THP together with receiver-side VFE, channel-shortening filter (CSF) together with maximum likelihood sequence estimation implemented with linear branch metrics (MLSE-LI-BM), and CSF together with MLSE implemented with nonlinear branch metrics (MLSE-NL-BM). Our experimental results indicate that, only the combination of CSF and MLSE-NL-BM enables a 112 Gbit/s transmission over 5 km fiber at the KP4-FEC threshold, but with an increased computational complexity.

Serial decoding algorithms of low-density parity-check (LDPC) code converge efficiently with low errors. Previously, a serial decoding algorithm, named a shuffled belief-propagation (SBP), was applied in turbo equalization of bit-patterned magnetic recording (BPMR) systems. With the SBP algorithm, an LDPC decoder converged twice as fast as one using conventional BP algorithms. We further improved the convergence speed of SBP by updating the messages in an adaptive order, which played a flexible role throughout decoding. We proposed two adaptive-serial algorithms for LDPC codes in turbo equalization. One updated the messages using the extrinsic loglikelihood ratio (LLR) and the result of the parity-check equation checking. The second contained an additional rule that tracked the LLR sign changes in each iteration. Both algorithms converged faster and with lower bit error rates (BERs) than the SBP and previous adaptive-serial algorithms in a BPMR system with media noise.

For the open-end winding permanent magnet synchronous motor (OEW-PMSM) fed by dual 3-level inverters with common DC bus, it is necessary to balance the neutral point voltage and suppress the zero-sequence current to improve system performance. The traditional methods to solve these two problems are usually contradictory, and are difficult to obtain satisfactory results. This paper proposes a novel modulation strategy to deal with this dilemma. In this strategy, the neutral point voltage balance is achieved by automatically equalizing the distribution proportion of the reference voltage of OEW-PMSM between the two inverters. At the same time, the strategy makes full use of the control freedom brought by dual inverters to control the three phase voltages of OEW-PMSM independently, so as to ensure that the average value of zero sequence voltage in a sampling period is zero in any case, and thus greatly reducing the ZSC. The experimental results verify the effectiveness and feasibility of this strategy.

This article proposes a low-complexity frequency equalization technique for pulsewidth modulation (PWM)-residual-aliasing reduction in closed-loop Class-D audio amplifiers to achieve both low total harmonic distortion plus noise (THD+N) and low quiescent current. Based on the comprehensive analysis on the phase shift delay between the audio input and the loop filter's output for the prior PWM-residual-aliasing reduction technique, the proposed technique minimizes the non-idealities via a frequency-equalization path to enhance the cancellation ability of high-frequency PWM switching components. In this way, the PWM-residual-aliasing distortion is greatly suppressed, thereby permitting Class-D audio amplifiers to achieve a further-reduced THD+N for the entire audio band while operating at a low switching frequency ( $f_{SW}$ ), leading to less quiescent current consumption. Moreover, due to the minimized phase shift delay, the required bias current of the loop filter's first operational amplifier for the target THD+N can be reduced, resulting in even lower quiescent current. Compared with other state of the arts, this work's high-fidelity second-order Class-D audio amplifier, fabricated with cost-efficient 0.5-μm CMOS technology, not only achieves a competitive minimal THD+N of 0.00091% for a 1-kHz input as well as the lowest maximal THD+N of 0.0027% over the entire audio band while operating at a low $f_{SW}$ of 168 kHz but also features both the highest figure of merit (FOM) of 2536 and the lowest quiescent current of 0.4 mA, surpassing the prior arts by a factor of 2.3.

We present a new technique to self-mitigate the RF power variations in microwave photonic phase shifters (MPPS) based on microring resonators by exploiting the root problem of varying optical intensities at different optical phase shifts to harness a varying and opposing optical equalization gain. Whilst optical gain mediums are commonly present in microwave photonic systems to overcome optical loss, choosing an appropriate equalization gain point to strike a balance between the optical gain transformation of weak and preservation of strong signals allows the proposed system to effectively achieve minimal radio frequency (RF) power variation across all signals without interfering with the RF phase shifting operation. Simulation results show an inline MPPS based on the phase and amplitude of conventional resonant structures with a capability to successfully minimize the RF power variations by 80% for up to 25 dB of phase-dependent power variations throughout the full 360° phase tuning range. Experimental results verify the MPPS operation based on a single microring resonator by significantly reducing the large RF power variations from 9 dB to less than ±1.25 dB, while maintaining the same RF phase shifting operation. We then verify the use of the proposed inline MPPS to adaptively minimize the self-interference by optimizing the phase compensation in a self-interference cancellation system. We demonstrate a cancellation bandwidth of 100 MHz with peak in-band cancellation of up to 40 dB while exhibiting the capability to recover weak signals of interest at operating center frequencies ranging from 5-20 GHz.

A plethora of new applications will be enabled by next generation wireless networks. These demand sophisticated medium access control and physical layer (PHY) protocols in order to fulfill the requirements in terms of spectral efficiency, bit error rate (BER), energy efficiency, reliability, and security, among others. This paper develops an advanced space-time multiple-input, multiple-output (MIMO) solution that builds on the concept of space-time shift keying (STSK) for single-carrier frequency domain equalization (SC-FDE). STSK-aided SC-FDE, or SSF, ensures space-time and frequency diversity in dispersive channels, but can only support suboptimal linear receiver schemes. We therefore introduce a turbo equalizer for SSF in frequency-selective multipath channels. It enables inter-symbolinterference (ISI) cancellation by means of iterative space-time processing. We coin it the iterative space-time block equalizer (SSF-ISTBE). We provide the mathematical formulation for the proposed SSF-ISTBE framework in non-linear channel conditions. We demonstrate that the SSF-ISTBE achieves a substantial 4 dB gain in terms of BER over the linear minimum mean square error equalizer while significantly reducing the computational complexity of the optimal maximum likelihood SSF. When considering practical transceivers, in particular nonlinear power amplifiers, the gain of the SSF-ISTBE becomes more prominent over state-of-the-art approaches, demonstrating its robustness against non-linear distortion.

This paper presents the design and bit error rate (BER) analysis of a phase-independent non-orthogonalmultiple access (NOMA) system. The proposed NOMA system can utilize amplitude-coherent detection(ACD) which requires only the channel amplitude for equalization purposes. In what follows, threedifferent designs for realizing the detection of the proposed NOMA are investigated. One is based on themaximum likelihood (ML) principle, while the other two are based on successive interference cancellation(SIC). Closed-form expressions for the BER of all detectors are derived and compared with the BER ofthe coherent ML detector. The obtained results, which are corroborated by simulations, demonstrate that,in most scenarios, the BER is dominated by multiuser interference rather than the absence of the channelphase information. Consequently, the BER using ML and ACD are comparable for various cases ofinterest. The paper also shows that the SIC detector is just an alternative approach to realize the MLdetector, and hence, both detectors provide the same BER performance.

With the rapid development of machine learning technologies in recent years, different types of neural network (NN)-based equalizers have been proposed and proved to be efficient digital signal processing tools to deal with the nonlinear impairments in short-reach direct detection optical interconnects. However, one major concern for these NN-based equalizers is their computational complexity (CC), since only a few tens of multiplications per symbol can be practically handled considering real-time implementation. In this paper, we propose an NN-based multi-symbol equalization scheme inspired by multi-task learning. Compared with traditional single-output NN-based equalizers, the CC can be significantly reduced with the help of the proposed scheme. A 50-Gb/s 25-km pulse amplitude modulation (PAM)-4 direct detection optical link is experimentally carried out and 3 different types of NNs, i.e., feedforward NN (FNN), cascade FNN (C-FNN), and recurrent NN (RNN), are employed for the proposed multi-symbol equalization scheme. Experimental results show that a maximum CC reduction of 43.2%/41.1%/44.0% can be achieved with FNN/C-FNN/RNN-based multi-symbol equalization to achieve their best performance, compared with the corresponding single-output NNs. The best performance of the proposed and the traditional FNN/-C-FNN-based schemes are the same, while the RNN-based scheme sacrifices a slight system performance. Aided by multi-symbol equalization, the CC needed to recover 1 symbol for various NNs can all be reduced to about a few tens of multiplications, indicating the feasibility of real-time implementation of these NN-based equalizers.

Single-sideband (SSB) signaling is a promising technology for short and medium reach optical transmission. We propose a novel architecture of linear network-assisted long short-term memory network (LN-LSTM) to mitigate optical transmission impairments in SSB systems. With a combination of a linear network and an input-pruned LSTM network, LN-LSTM achieves better performance and lower computation complexity compared with conventional LSTM equalization. With LN-LSTM, we achieve 6.4 Tb/s ( $32\times 200$ Gb/s) wavelength division multiplexing (WDM) SSB transmission over 320km standard single-mode fiber (SSMF) with a bit error rate (BER) below the 20% soft-decision forward error-correction (SD-FEC) threshold of $2.4\times 10^{-2}$ .

In this paper a transimpedance amplifier is presented, which features a bandwidth of 97 GHz, 66 dBΩ maximum transimpedance gain, and 6.3 pA/√Hz integrated noise current density, operating at up to 120 Gb/s and consuming only 145mW. Reaching a higher bandwidth at a noise performance comparable to the state-of-the-art, is the novelty of this work. It was achieved by combining a low-bandwidth input stage, reducing the total noise, and a multi-stage post equalization. The gain peaking technique through cascading emitter follower stages is employed in a broadband transimpedance amplifier as a post equalizer. To the best of the author’s knowledge, the presented design shows the best performance in terms of overall gain, bandwidth, and noise for the lowest power consumption compared to state-of-the-art designs.

This letter focuses on the design of multiuser uplink multiple-input multiple-output (MIMO) communications assisted by multiple reconfigurable intelligent surfaces (RISs), where we consider both linear minimal mean-squared error (MMSE) and nonlinear MMSE-decision feedback equalization (DFE) receivers. The RISs, consisting of massive low-cost passive elements, can reflect the incident signals with either continuous or discrete phase shifts. Adopting the sum mean-squared error (MSE) minimization criterion, we jointly optimize the RIS phase shifts, the linear or nonlinear receiving matrices, and the source precoding matrices in iterative manner. Simulation results show that, when the signals in direct user-access point (AP) links suffer severe attenuation, the introduction of indirect user-RIS-AP links can significantly improve the system performance.

In this paper, a robust iterative block decision feedback equalization (DFE) algorithm is developed for uplink Single-Carrier Frequency Division Multiple Access (SC-FDMA) systems. Three important problems that can adversely affect the performance of the DFE in a SC-FDMA system are to be addressed here, i.e., the feedback symbols reliability, the feedback correlation metric, and the phase noise due to inaccuracies in the fabrication process of the crystal oscillator. Instead of using all the detected symbols in the feedback loop of the DFE, only the highly reliable symbols are selected to be fed-back. This results in the improvement of the error propagation, one of the common problem in a DFE. Also, the feedback correlation of the detected symbols is an important metric in the design of the DFE, and hence an elegant method is proposed in this design and found to perform better than the available existing designs in the literature. Finally, the transmitter and receiver phase noise is iteratively compensated using its corresponding time and frequency domains properties. Simulation results demonstrate the robustness of our designed iterative block DFE.

Eigenvalue-based communication technologies using inverse scattering transform (IST) have gained attention as a new transmission strategy in optical fiber communications. In recent years, several studies on artificial neural network (ANN)-based equalization and demodulation schemes for eigenvalue-modulated signal have been conducted to enhance the receiver sensitivity. However, in the case of a presence of a carrier frequency offset (CFO) at receiver, the effects of the CFO on ANN receiver of eigenvalue-modulated signal is yet to be reported. In this study, we numerically and experimentally investigated the generalization performances of eigenvalue domain ANN-based demodulator on CFO. Furthermore, we proposed to combine an ANN-based demodulator with a CFO compensation method based on IST and a relation between frequency and eigenvalue shifts. The proposed method, based on an appropriate soliton pulse, achieves a high CFO estimation accuracy of submegahertz order even if the CFO reaches 2.5 GHz under the noiseless condition. In the presence of noise and a large CFO of 2.5 GHz, the method attains a CFO estimation accuracy below 60 MHz for OSNR=10 dB with a low pilot pulse rate, such as 0.064%. We show the simulation results obtained after applying the proposed CFO compensation to the ANN demodulator, which is valid for 2.5 GHz CFO and long-haul transmission over 5000 km. Experiments performed in this study demonstrate successful demodulation of an eigenvalue-modulated signal with OSNR penalty < 1 dB in the presence of CFO within 1 GHz at 2.5 Gb/s.

Histogram equalization (HE) is one of the most important techniques for contrast enhancement of digital images. Conventional HE methods persuade excessive enhancement, unnatural artifacts and brightness transform resulting abnormal and unusual appearance. To solve such problems, a novel tri-plateau limit-oriented tri-histogram equalization technique is suggested for digital image enhancement, where histogram of the input image is initially separated in three sub-histograms using separation threshold parameters. Next, plateau limit criteria for sub-histograms are formulated using the average of the mean and the median of each sub-histogram, and subsequently, a redistributed parameter is calculated and merged with each sub-histogram to restrict over-enhancement. Finally, modified sub-histograms are equalized separately and the enhanced image is produced by incorporating the images accomplished by the transformation function. Experimental results demonstrate that the proposed technique efficiently enhances the contrast of images, while visual quality assessments and quantitative measures, like average information content (AIC), feature similarity index measure (FSIM), multi scale structural similarity index measure (MS-SSIM), visual saliency-induced index (VSI), and gradient magnitude similarity deviation (GMSD) effectively validate the superiority of the proposed algorithm with respect to the other traditional state-of-the-art HE methods.

5G defines below 100 GHz as the millimeter-wave bands, whereas 100 GHz - 3 THz is categorized as THz band in 6G. Deep leraning (DL) is expected to enable a significant paradigm shift in 6G wireless networks. In this paper, D-band 90-Gbps single channel PAM-4 signal generation and transmission over 10-km SMF and 3-m wireless link at 140-GHz can be achieved. A novel complex-valued neural network (CVNN) equalizer using ‘CReLU’ activation function to directly recover PAM-4 signals from received noised signals is demonstrated. There are three DSP options in the experiment. In Opt .1, firstly conducted cascaded multi-modulus algorithm (CMMA) pre-equalization (pre-EQ) at transmitter, then processed via frequency offset estimation (FOE), carrier phase recovery (CPR) and finally real-valued neural network (RVNN) equalization at receiver. Here, the RVNN equalizers include DNN with a softmax output layer, two-step joint-DNN equalizer and LSTM. The experimental results show that LSTM-based equalizer outperforms the other real NN-based equalizers by average 0.5 to 1.5 dB at BER of 10−3 magnitude. Differently from Opt . 1, real-valued CMMA pre-EQ at transmitter is unexpected for CVNN in the other two options. In Opt . 2, we only combine down-conversion and CVNN regarded as ‘pure data-driven’ training at receiver. This pure data-driven CVNN equalizer improves BER a lot and also has a larger computation burden, especially BER is as low as 1 × 10−4 with n 0 = 571 and n 1 = 200 training cells and the time complexity reaches 350000 in one iteration. Thanks to the aid of traditional mathematical-oriented models including FOE and CPR, the computation burden of CVNN in Opt . 3 is released significantly. Furthermore, we compare the performance of CVNN and RVNN in terms of BER decision accuracy, time complexity and receiver sensitivity. Followed by the same DSP with the same complexity, the comparison result between DNN and CVNN in the same structure of [371-260-1] with 11000 samples and 300 epochs shows that CVNN performs better due to its reservation of phase information. Therefore, we believe that the joint use of model-based, e.g., FOE, CPR steps and complex DL-based techniques has a potential for the future 6G wireless physical layer algorithms.

Solar energy is one of the most promising energy types, but photovoltaic (PV) mismatches have several negative effects. Finding an efficient and low-cost method to reduce or eliminate the power loss caused by the mismatch in PV power generation systems is necessary. In this paper, we propose a PV submodule-distributed maximum power point tracking (DMPPT) scheme based on a multi-port DC converter. In-depth analysis and research are performed on the PV model and mismatch characteristics, the PV module voltage equalization (VE) strategy, and implementation with the multi-port buck–boost converter. We discuss the trade-off between true DMPPT and VE on control overhead and tracking accuracy, and a detailed derivation is created to illustrate the differences between them. The VE can reduce the cost and complexity of the system at the expense of a small PV energy capture. The proposed implementation reduces the number of semiconductor components and current sensors, which is conducive to the integrated design of the hardware. A prototype based on a multi-port buck–boost converter for a 36 V/200 W PV module was designed and built. The feasibility and progress of the proposed scheme were verified through experiments.

In this paper, the emerging orthogonal time frequency space (OTFS) modulation is firstly restructured as a precoded orthogonal frequency division multiplexing (OFDM) system, so that the well-established frequency-domain approach can be applied to perform signal in fast fading channels. Then a frequency-domain minimum mean squared error (MMSE) equalizer for OTFS is introduced and its performance is analyzed based on the eigenvalue decomposition of the channel matrix. Inspired by the frequency-domain precoding structure, an adaptive transmission scheme with frequency-domain precoding matrix composed of the eigenvectors of the channel matrix is proposed to improve the system performance under MMSE equalization, and its optimized performance is derived with simple expression. Finally, considering two extreme channel conditions, the lower and upper bounds for the diversity performance of the adaptive transmission scheme are derived. Simulation results show that the proposed adaptive transmission achieves significantly better performance for short signal frames and can work well with imperfect channel state information (CSI). The derived performance bounds can serve as benchmarks for OTFS and other precoded OFDM systems.

In this paper, we consider single carrier system with transmit diversity and a new multi-antenna transmission waveform is carefully designed to enable low-complexity anti-interference adaptive equalization. We propose a new space-frequency adaptive equalization method which makes use of the mutual interferences among different antennas from the desired user rather than attempts to completely remove them. We further propose two different ways to significantly reduce the computational complexity based on the idea of subband-wise processing with little sacrifice of equalization performance. Simulation results show that the proposed method exhibits a significant gain over conventional anti-interference schemes.

In this article, a reduced-component-count centralized equalization system based on a novel integrated cascade equalization topology is proposed to achieve the equalizing of series-connected battery packs. The proposed converter topology is the integration of the polarity switches and the bidirectional converter in traditional centralized battery equalization systems, and can also be regarded as a cascade structure composed of a bidirectional buck-boost converter and a bidirectional flyback converter. Compared with existing centralized equalizers, the number of components applied in the proposed scheme is significantly reduced, which obtains higher cost performance and reliability, and is more suitable for the equalization of large-capacity battery packs. Meanwhile, this integrated cascade structure enables the proposed topology to achieve an ultra-high voltage conversion ratio, hence the efficiency can be significantly enhanced by employing a transformer with a smaller turns ratio and reduced leakage inductance. Furthermore, the operating principles, design considerations and comparative analysis are presented in detail. Finally, an experimental prototype based on a 13-cell lithium-ion battery pack is established to verify the superior performance of the proposed equalization system.

We propose and experimentally demonstrate a distributed digital pre-equalization (DPE) technique for orthogonal frequency division multiplexing (OFDM)-based bandlimited visible light communication (VLC) systems. In the VLC system applying distributed DPE, the subcarriers are divided into two bands, where the bandwidth and the power of each band can be flexibly adjusted to maximize the achievable data rate of the system. Hence, distributed DPE exhibits much higher tolerance against light-emitting diode (LED) nonlinearity than conventional centralized DPE. Experimental results verify the superiority of distributed DPE for OFDM-based bandlimited VLC systems. More specifically, a data rate of 976.6 Mbit/s is achieved by using distributed DPE, which corresponds to an achievable rate improvement of 25% in comparison to centralized DPE.

This article presents a fully integrated IEEE 802.11aj direct-conversion transceiver system in a 120-nm SiGe:C BiCMOS technology. The system includes a transmitter, a receiver, and two onboard substrates integrated waveguide-fed Yagi-Uda antennas. In the millimeter-wave frequency band, the common-mode (CM) signal in a transformer-based balun is a limiting factor for the linearity of differential devices. In this work, we analyze the cause of the CM effect and provide fast impedance equalization with a passive component compensation method to resolve this problem, which improves the linearity of the transmitter. A T-type second-order harmonic termination method is applied at the power amplifier (PA) output to further improve the linearity of the transmitter. The self-mixing method-based power detector is adopted at the output of the transmitter to have an accurate image signal and local oscillator (LO) leakage calibration. The transmitter reaches an output 1-dB compression point (OP1,dB) of 14.6-16.4 dBm and a conversion gain (CG) higher than 24 dB in the IEEE 802.11aj frequency band, operating from 42.3 to 48.4 GHz. The receiver achieves a 3.8-4.1-dB noise figure, -18.7- to -22-dBm input 1-dB compression point, and a CG better than 43.8 dB in the IEEE 802.11aj frequency band. In the system wireless data transmission test, the transceiver is fully compliant with the error vector magnitude (EVM) requirement of the IEEE 802.11aj standard up to the 64-quadrature amplitude modulation (QAM) operating mode, and the measured transmitter-to-receiver EVM is better than -28.5 dB at a 1-m distance over the IEEE 802.11aj frequency band. Compared to other states of the art, the transmitter's OP1,dB is the highest, and the demonstrated transceiver system delivers the highest performance in the IEEE 802.11aj wireless link.

The Arctic Ocean and its various shallow passages are rapidly changing due to global warming. The development of a large-scale wireless network that collects and distributes oceanographic data remotely would be an extremely valuable asset to researchers. This concept, however, is completely dependent upon the ability to acoustically transmit digital information under water over long ranges, which is not currently available. In this work, we investigate the performance of four transceivers that are based on frequency-hopping binary frequency-shift keying and multilevel phase-shift keying (M-PSK) signaling in the 300 $-$ 400-Hz acoustic band. The transceivers use low-rate coding that provides bit rates from 1.8 to 13.3 b/s (bits per second). Their bit error rates are computed based on real data recorded in Barrow Strait (NU). During the 2019 experimental activities, the transmitter was towed by a supporting vessel at an average speed of 4 kn. The receiver, a vertical hydrophone array, was at distance between 14 and 33 km. Additionally, the received signals experienced extended multipath propagation and strong in-band impulsive interferences. For a single-hydrophone receiver, our postprocessing analysis shows reliable bit rates up to 6.7 b/s. When processing uses the array and performs multichannel decision feedback equalization (DFE), the maximum designed rate, i.e., 13.3 b/s, is confirmed. Further analysis reveals that the experimental links could support higher data rates. Our results demonstrate that 2-PSK signaling combined with single-channel DFE and 4-PSK signaling combined with multichannel DFE could reliably achieve 100 and 200 b/s, respectively.

The discussion about the loss of nationalism values in the Indonesian migrant workers’ (IMW’s) children in border areas, has become an important issue in the world of Indonesian education. The purpose of this study is to describe the role of Community Learning Center (CLC) in fostering nationalism values in IMW’s children, as well as to reveal the teaching experience and meaning of nationalism from the perspective of teachers at CLC Sarawak, Malaysia. The research uses qualitative method with case study approach that focuses on factors that can foster nationalism of IMW’s children. Data collection obtained through observation techniques, in-depth interviews, and documentation. The results showed meaningful findings according to the conditions in the education system in CLC, as well as socio-cultural conditions that affect every activity in the border area. The first finding indicates that CLC has an important (central) role in fostering the nationalism of IMW’s children in border areas. The second finding shows the fact that teachers are still experiencing some problems in the field, such as; limited access to information and communication, teacher education background, school conditions, limited educational units, learning facilities, and family and social environments. The third finding emphasizes the importance of nationalism for teachers who devote themselves to teaching in border areas, because teachers have a crucial role in transferring knowledge, providing meaningful learning experiences, and fostering the nationalism of IMW’s children.

Purpose This study aimed to evaluate the effect of equalization filters (EFs) on the kerma-area product ( K A P Q K M ) and incident air-kerma ( K a , i , Q K M ) using a kerma-area product (KAP) meter. In addition, potential underestimations of the K a , i , Q K M values by EFs were identified. Materials and methods A portable flat-panel detector (FPD) was placed to measure the X-ray beam area (A) and EFs dimension at patient entrance reference point (PERP). Afterward, a 6-cm3 external ionization chamber was placed to measure incident air-kerma ( K a , i , Q e x t ) at PERP instead of the portable FPD. KAP reading and K a , i , Q e x t were simultaneously measured at several X-ray beam qualities with and without EFs. The X-ray beam quality correction factor by KAP meter ( k Q , Q 0 K M ) was calculated by A, K a , i , Q e x t and KAP reading to acquire the K A P Q K M and K a , i , Q K M . Upon completion of the measurements, K A P Q K M , K a , i , Q K M , and K a , i , Q e x t were plotted as functions of tube potential, spectral filter, and EFs dimension. Moreover, K a , i , Q K M / K a , i , Q e x t values were calculated to evaluate the K a , i , Q K M underestimation. Results The k Q , Q 0 K M values increased with an increase in the X-ray tube potential and spectral filter, and the maximum k Q , Q 0 K M was 1.18. K A P Q K M and K a , i , Q K M decreased as functions of EFs dimension, whereas K a , i , Q e x t was almost constant. K a , i , Q K M / K a , i , Q e x t decreased with an increase in EFs dimension but increased with an increase in tube potential and spectral filter, and the range was 0.55-1.01. Conclusions K a , i , Q K M value was up to approximately two times lower than the K a , i , Q e x t values by EFs. When using the K a , i , Q K M value, the potential K a , i , Q K M underestimation with EFs should be considered.

This paper analyses the investment in digital tools and the allocation of communication expenses in a Global South country with an uneven digital penetration rate. Data were collected for 2,563 can...

This article proposes a real-time electrochemical impedance spectroscopy (EIS) technique that can provide high accurate estimation of the impedance of each lithium-ion (Li-ion) cell of a battery (BT) stack, even for less than mΩ. Thus, the suggested EIS technique can be used in high demanding applications, such as nearly zero-energy buildings, microgrids, and electric vehicles. This is attained because a smooth cell excitation current is utilized that is provided by the proper control of the gate-source of each cell's parallel-connected MOSFET and thus, effective harmonic analysis can be accomplished. Since the circuit topology of the EIS is implemented without requiring expensive electronic equipment, it is affordable to be applied in the BT system of any application. The proposed EIS system can cooperate with a BT cell equalization (BCE) system that utilizes the same MOSFET control scheme to provide the excitation current. Thus, a combined EIS–BCE system is developed that can be used to improve the performance of a Li-ion BT management system. The accuracy of the EIS technique and its high performance by operating within a combined EIS–BCE system are experimentally validated.

Spectrally efficient frequency division multiplexing (SEFDM) is a bandwidth-compressed non-orthogonal multicarrier communication scheme, which provides improved spectral efficiency compared to orthogonal frequency division multiplexing (OFDM) system. The loss of orthogonality yields the self-introduced inter-carrier interference (ICI) complicating the equalizer design. In this work, a deep learning (DL) -based SEFDM equalization scheme is proposed to characterize the ICI and to detect the transmitted information bits. The DL-based equalization scheme is trained offline using randomly-generated data and then deployed online. The performance of the equalization scheme is tested by extensive numerical simulations. The results show that the proposed equalization scheme outperforms the linear equalization based equalization scheme, such as zero forcing (ZF), minimum mean squared error (MMSE) and truncated singular value decomposition (TSVD), under additive white Gaussian noise (AWGN) channel in terms of the bit-error rate (BER). Especially for BPSK, the uncoded BER performance approaches the traditional OFDM even for the compression ratio of 0.7, which saves the bandwidth by 30%.

In this paper, a new class of soft-input soft-output block decision feedback equalizer (BDFE) for turbo equalization over inter-symbol interference (ISI) channels under minimum mean-square error (MMSE) criterion is proposed. First, the BDFE which employs both the a posteriori moments of estimated symbols and the a priori moments of unestimated symbols is investigated, and two recursive schemes are derived to reduce the complexity. Then, to mitigate error propagation, the bidirectional BDFE (Bi-BDFE) consisting of a forward BDFE and a backward BDFE is proposed. Furthermore, a threshold is employed to reduce the number of inverse matrix update process for the BDFE (T-BDFE), which can attain a flexible trade-off between complexity and performance. Finally, the bidirectional equalization is introduced into a low-complexity approximate solution of the BDFE (Bi-LC-BDFE) to further reduce the complexity and obtain time diversity gain, which utilizes a time-invariant covariance matrix. Simulation results show that the proposed equalizers significantly outperform the block linear equalizer (BLE), the exact MMSE-based linear equalizer (Exact-MMSE-LE) and the soft-decision feedback equalizers (SDFE), while keeping a similar complexity as the BLE. In addition, the Bi-BDFE can achieve better performance than the Max-Log-MAP equalizer while its complexity is on the same order as the BDFE.

The band-limited and power fading effects are two main limitations to intensity-modulation direct-detection (IM-DD) transmission systems due to the low-cost transceivers and interactions from fiber dispersion. Entropy loading (EL) has the ability to squeeze out the last bit by continuous adjustment of entropy. However, it is a passively process to adapt to the channel response. Moreover, the normalized generalized mutual information (NGMI) target based EL may be overestimated because the practical binary forward error correction (FEC) codes have a gap to the theoretic limit, which may result in unsatisfied transmission capacity or post-FEC performance. To optimize the NGMI, we analyze the NGMI upper and lower boundaries defined by the achievable information rate (AIR) and FEC overhead (OH). We propose to use the AIR as target and optimize the NGMI with the FEC OH as constraint. We conduct an experiment to target the beyond 200-Gb/s discrete multi-tone signal transmission over 2-km or 10-km single mode fiber using a 32-GHz electro-absorption modulated laser (EML). However, we find that the channel response and generalized mutual information (GMI) cannot support the target AIR even with NGMI optimization. We propose a joint EL and second-order Volterra filter (VF) to alleviate the power fading effects and maximize the transmission capacity. To achieve the AIR target and use below 20% SD-FEC, we find the optimized NGMI is 0.92 to simultaneously meet the 2-km and 10-km transmission requirement. We successfully transmit beyond 200-Gb/s DMT signal over 2-km or 10-km single mode fiber with BER below 2.6 × 10−2 in the EML-based direct-detection system.

In unmanned aerial vehicle (UAV) communications, frequency-selective fading can severely deteriorate the quality of transmitted signal by generating undesired and disordered constellation diagrams due to scatters in the air-to-ground (ATG) mutipath channels. In this paper, we propose a low-overhead blind equalization method to combat frequency-selective fading in air-ground multipath UAV channels. Specifically, a pre-equalization method is proposed based on a constant modulus algorithm to restore the contour of the constellation diagram. Moreover, the similarity measure function and the difference measure function are derived using template matching to identify the constellation of M-ary quadrature amplitude modulation. Furthermore, we propose a weighted constant cross algorithm (WXA) to reduce the residual mean square error and construct a cross-shaped modulus value, by utilizing the statistical information of the identified normalized standard constellation diagrams and the equalizer output decision symbols’ weighting value. The proposed method requires less information and no training sequences and pilots, therefore, if achieves energy and spectrum efficient ATG multipath UAV communications. Simulation results show that the proposed WXA algorithm can reduce the residual mean square error convergence value between -22dB and -25dB, making it very useful for the equalization of the frequency-selective fading channel in typical UAV communication scenarios.

Conventional energy storage systems include a bidirectional converter for charging and discharging the series-connected cells and a separate voltage equalizer. In this article, to simplify the system, the equalizer is integrated into the charging and discharging system. Only one magnetic component is required in the proposed integrated architecture, and more importantly, the equalizer no longer needs a separate converter as the driver. The voltage equalizer is composed of a symmetrical voltage multiplier (SVM) and a series-resonant circuit. The equalizer operates in a discontinuous conduction mode (DCM) and can provide a constant equalization current for the energy storage cells. A detailed operation analysis is performed for integrated architecture, and the steady-state characteristics are mathematically derived. The integrated architecture can automatically equalize the cell voltage when the energy storage is charged or discharged. A prototype for six series-connected cells was built and tested to verify the analytical results and demonstrate the properties of the proposed architecture.

A method for designing salt equalization lines (SEL) in two-sided external saline compartments (SC) with allowance for natural circulation is described. If there is heat imbalance between the left and right SCs, the SEL cannot eliminate the salt imbalance between them because of the natural circulation in the two-sided SCs. The method was validated experimentally for TG-104 boiler with SELs: salt imbalance occurred between the SCs after artificial creation of heat imbalance between the left and right waterwalls of the saline compartments.

The Alpha Magnetic Spectrometer (AMS-02) will continuously collect data for the lifetime of the International Space Station (ISS). On-orbit equalization must be performed to ensure the accuracy of the AMS energy measurement (~ 1%) by the electromagnetic calorimeter (ECAL). The equalization is performed using the most probable value (MPV) of the cosmic-ray proton minimum ionizing particle (MIP). Kalman filter technique is used to improve the precision. The precision of the equalization with proton MIP is (7.206 ± 0.003) % and improved to (2.388 ± 0.002) % after the Kalman filter. From the toy Monte Carlo (MC) simulation, the error of the energy reconstruction is about 1.4% and 0.5% due to the 7.2% and 2.4% equalization accuracy, respectively. About 1.4% error due to ~ 7% equalization precision does not match the AMS requirement. With the improvement from the Kalman filter, the energy reconstruction error from the equalization is reduced to 0.5%, which can fulfill the AMS requirement.

The range of transmitters, detectors and other components that can be used in optical wireless links means that they can have a wide variety of frequency responses. Both pre- and post- equalization have been used in optical wireless systems to increase data rates. Pre-equalization has the advantage that noise impairments due to equalization can be minimised. However, the variety of pre-equalizer transfer functions, which can be easily created using analog circuits, is limited by the frequency responses of these circuits. Consequently, it may not be possible to equalize some optical wireless links with analog circuit-based pre-equalizers. In this paper a flexible digital pre-equalization scheme that can equalize complex frequency responses is described. The flexibility and the applicability of the scheme is also demonstrated using two example systems, including one that incorporates a fluorescent optical fiber to create a wide-field-of-view receiver for handheld devices. In particular, the bandwidths of the two example systems have been increased to over 500 MHz and to 350 MHz, resulting in at least a three-fold increase in data rate without any post-equalization. The authors believe that this is the first time such significant improvements in on-off-keying data rates have been demonstrated in systems with a relatively complex frequency response and a limited dynamic range.