ADS-B Reception Error Correction Based on the LSTM Neural-Network Model

Standard automatic dependent surveillance broadcast (ADS-B) reception algorithms offer considerable performance at high signal-to-noise ratios (SNRs). However, the performance of ADS-B algorithms in applications can be problematic at low SNRs and in high interference situations, as detecting and decoding techniques may not perform correctly in such circumstances. In addition, conventional error correction algorithms have limitations in their ability to correct errors in ADS-B messages, as the bit and confidence values may be declared inaccurately in the event of low SNRs and high interference. The principal goal of this paper is to deploy a Long Short-Term Memory (LSTM) recurrent neural network model for error correction in conjunction with a conventional algorithm. The data of various flights are collected and cleaned in an initial stage. The clean data is divided randomly into training and test sets. Next, the LSTM model is trained based on the training dataset, and then the model is evaluated based on the test dataset. The proposed model not only improves the ADS-B In packet error correction rate (PECR), but it also enhances the ADS-B In terms of sensitivity. The performance evaluation results reveal that the proposed scheme is achievable and efficient for the avionics industry. It is worth noting that the proposed algorithm is not dependent on conventional algorithms’ prerequisites.

A Harmonic Approach to Handwriting Style Synthesis Using Deep Learning

The challenging task of handwriting style synthesis requires capturing the individuality and diversity of human handwriting.The majority of currently available methods use either a generative adversarial network(GAN)or a recurrent neural network(RNN)to generate new handwriting styles.This is why these techniques frequently fall short of producing diverse and realistic text pictures,particularly for terms that are not commonly used.To resolve that,this research proposes a novel deep learning model that consists of a style encoder and a text generator to synthesize different handwriting styles.This network excels in generating conditional text by extracting style vectors from a series of style images.The model performs admirably on a range of handwriting synthesis tasks,including the production of text that is out-of-vocabulary.It works more effectively than previous approaches by displaying lower values on key Generative Adversarial Network evaluation metrics,such Geometric Score(GS)(3.21×10^(-5))and Fréchet Inception Distance(FID)(8.75),as well as text recognition metrics,like Character Error Rate(CER)and Word Error Rate(WER).A thorough component analysis revealed the steady improvement in image production quality,highlighting the importance of specific handwriting styles.Applicable fields include digital forensics,creative writing,and document security.

Security-Enhanced Directional Modulation Based on Two-Dimensional M-WFRFT

Directional modulation(DM)is one of the most promising secure communication techniques.However,when the eavesdropper is co-located with the legitimate receiver,the conventional DM has the disadvantages of weak anti-scanning capability,anti-deciphering capability,and low secrecy rate.In response to these problems,we propose a twodimensional multi-term weighted fractional Fourier transform aided DM scheme,in which the legitimate receiver and the transmitter use different transform terms and transform orders to encrypt and decrypt the confidential information.In order to further lower the probability of being deciphered by an eavesdropper,we use the subblock partition method to convert the one-dimensional modulated signal vector into a twodimensional signal matrix,increasing the confusion of the useful information.Numerical results demonstrate that the proposed DM scheme not only provides stronger anti-deciphering and anti-scanning capabilities but also improves the secrecy rate performance of the system.

Effects of Multicollinearity on Type I Error of Some Methods of Detecting Heteroscedasticity in Linear Regression Model

Heteroscedasticity and multicollinearity are serious problems when they exist in econometrics data. These problems exist as a result of violating the assumptions of equal variance between the error terms and that of independence between the explanatory variables of the model. With these assumption violations, Ordinary Least Square Estimator (OLS) will not give best linear unbiased, efficient and consistent estimator. In practice, there are several structures of heteroscedasticity and several methods of heteroscedasticity detection. For better estimation result, best heteroscedasticity detection methods must be determined for any structure of heteroscedasticity in the presence of multicollinearity between the explanatory variables of the model. In this paper we examine the effects of multicollinearity on type I error rates of some methods of heteroscedasticity detection in linear regression model in other to determine the best method of heteroscedasticity detection to use when both problems exist in the model. Nine heteroscedasticity detection methods were considered with seven heteroscedasticity structures. Simulation study was done via a Monte Carlo experiment on a multiple linear regression model with 3 explanatory variables. This experiment was conducted 1000 times with linear model parameters of β0 = 4 , β1 = 0.4 , β2= 1.5 and β3 = 3.6. Five (5) levels of mulicollinearity are with seven (7) different sample sizes. The method’s performances were compared with the aids of set confidence interval (C.I.) criterion. Results showed that whenever multicollinearity exists in the model with any forms of heteroscedasticity structures, Breusch-Godfrey (BG) test is the best method to determine the existence of heteroscedasticity at all chosen levels of significance.

Adaptive Linear Filtering Design with Minimum Symbol Error Probability Criterion

Adaptive digital filtering has traditionally been developed based on the minimum mean square error （MMSE） criterion and has found ever-increasing applications in communications. This paper presents an alternative adaptive filtering design based on the minimum symbol error rate （MSER） criterion for communication applications. It is shown that the MSER filtering is smarter, as it exploits the non-Gaussian distribution of filter output effectively. Consequently, it provides significant performance gain in terms of smaller symbol error over the MMSE approach. Adopting Parzen window or kernel density estimation for a probability density function, a block-data gradient adaptive MSER algorithm is derived. A stochastic gradient adaptive MSER algorithm, referred to as the least symbol error rate, is further developed for sample-by-sample adaptive implementation of the MSER filtering. Two applications, involving single-user channel equalization and beamforming assisted receiver, are included to demonstrate the effectiveness and generality of the proposed adaptive MSER filtering approach.

Reducing the Internal Difference Error Rate in Hospital Pharmacies:From the Angle of Quality Control Circle

Objective To improve the management level of pharmacy dispensing center,reduce dispensing errors and promote the safety of drug use.Methods Hospital pharmacies could be managed according to the theory of quality control circle(QCC).Based on the ten steps of QCC,the internal difference error rate in pharmacies could be reduced.Results and Conclusion The error rate of pharmacies was reduced from 2.74‰to 0.57‰,and the goal achievement rate was 108.466.Besides,the progress rate reached 84.82%.The abilities of circle members were improved,and the operation of pharmacy was more standardized.The activity of QCC is helpful to reduce the internal difference error rate,improve the operation level of pharmacy and ensure the safety of drug use.

Effects of error feedback on a nonlinear bistable system with stochastic resonance

In this paper, we discuss the effects of error feedback on the output of a nonlinear bistable system with stochastic resonance. The bit error rate is employed to quantify the performance of the system. The theoretical analysis and the numerical simulation are presented. By investigating the performances of the nonlinear systems with different strengths of error feedback, we argue that the presented system may provide guidance for practical nonlinear signal processing.

A Simulation Based Comparison of Correlation Coefficients with Regard to Type I Error Rate and Power

In this simulation study, five correlation coefficients, namely, Pearson, Spearman, Kendal Tau, Permutation-based, and Winsorized were compared in terms of Type I error rate and power under different scenarios where the underlying distributions of the variables of interest, sample sizes and correlation patterns were varied. Simulation results showed that the Type I error rate and power of Pearson correlation coefficient were negatively affected by the distribution shapes especially for small sample sizes, which was much more pronounced for Spearman Rank and Kendal Tau correlation coefficients especially when sample sizes were small. In general, Permutation-based and Winsorized correlation coefficients are more robust to distribution shapes and correlation patterns, regardless of sample size. In conclusion, when assumptions of Pearson correlation coefficient are not satisfied, Permutation-based and Winsorized correlation coefficients seem to be better alternatives.

SR-DCSK Cooperative Communication System with Code Index Modulation:A New Design for 6G New Radios

This paper proposes a high-throughput short reference differential chaos shift keying cooperative communication system with the aid of code index modulation,referred to as CIM-SR-DCSK-CC system.In the proposed CIM-SR-DCSK-CC system,the source transmits information bits to both the relay and destination in the first time slot,while the relay not only forwards the source information bits but also sends new information bits to the destination in the second time slot.To be specific,the relay employs an N-order Walsh code to carry additional log_(2)N information bits,which are superimposed onto the SRDCSK signal carrying the decoded source information bits.Subsequently,the superimposed signal carrying both the source and relay information bits is transmitted to the destination.Moreover,the theoretical bit error rate(BER)expressions of the proposed CIMSR-DCSK-CC system are derived over additive white Gaussian noise(AWGN)and multipath Rayleigh fading channels.Compared with the conventional DCSKCC system and SR-DCSK-CC system,the proposed CIM-SR-DCSK-CC system can significantly improve the throughput without deteriorating any BER performance.As a consequence,the proposed system is very promising for the applications of the 6G-enabled lowpower and high-rate communication.

Direct measurement of an energy-dependent single-event-upset cross-section with time-of-flight method at CSNS

To predict the soft error rate for applications, it is essential to study the energy dependence of the single-event-upset(SEU) cross-section. In this work, we present a direct measurement of the SEU cross-section with the Back-n white neutron source at the China Spallation Neutron Source. The measured cross section is consistent with the soft error data from the manufacturer and the result suggests that the threshold energy of the SEU is about 0.5 Me V, which confirms the statement in Iwashita’s report that the threshold energy for neutron soft error is much below that of the(n, α) cross-section of silicon.In addition, an index of the effective neutron energy is suggested to characterize the similarity between a spallation neutron beam and the standard atmospheric neutron environment.

Arbitrary Decode-Forward Relaying with Re-Encoded Bits Selection Strategy for Polar Codes

In this paper,we propose an arbitrary decode-forward single-relay scheme for finite blocklength polar codes,which can be applied to the general symmetric discrete memoryless relay channel with orthogonal receiver components.The relay node decodes the received message.The relay node selectively re-encodes the message and transmits it to the destination node.Furthermore,in order to minimize the upper-bound of the block error probability,we propose a selection strategy to decide the proper re-encoded bit set by the relay.Simulation results are presented to illustrate the improvement in decoding performance of the proposed scheme compared to conventional relay schemes in both additive white Gaussian noise(AWGN)channel and Rayleigh fading channel(RFC).

Minimizing FWM Impact in DWDM ROF DP-DQPSK System for Optical

The demonstration of a higher data rate transmission system was amajor aspect to be considered by researchers in recent years. The most relevantaspect to be studied and analyzed is the need for a reliable system to handlenonlinear impairments and reduce them. Therefore, this paper examines theinfluence of Four-Wave Mixing (FWM) impairment on the proposed highdata rate Dual polarization–Differential Quadrature phase shift keying (DPDQPSK)system using the Optisystem software. In the beginning, the impactof varied input power on the proposed system’s performance was evaluated interms of QF and BER metrics. More power is used to improve system performance.However, increasing power would raise theFWMeffects. Accordingly,a−10dBminput power and the proposed system are used to reduce the impactof FWM. Additionally, a hybrid amplification method is proposed to enhancesystem performance by utilizing the major amplification methods of erbiumdopedfiber amplifier (EDFA): semiconductor optical amplifier (SOA) andRadio optical amplifier (ROA). The evaluation demonstrates that the OAEDFAoutperformed the other two key amplification techniques of (EDFASOA)and (EDFA-ROA) in improving Quality factor (QF) and Bit error rate(BER) system results for all distances up to 720 km. Consequently, the methodcontributes to minimizing the impact of FWM. In the future, other forms ofnonlinearity will be investigated and studied to quantify their impact on theproposed system.

Guaranteeing Wireless Communication Reliability via an Extended Hybrid Carrier System

In this paper,we propose an extended hybrid carrier system based on the weighted fractional Fourier transform to ensure the reliability of wireless communication.The proposed scheme improves the dispersion and compensation capabilities of the hybrid carrier system for channel fading through the design of the signal power distribution,which has greatly reduced the probability of high-power distortion of the signal and improved the bit error rate performance as a result.Theoretical analysis has shown the superiority of the extended hybrid carrier system.With a lower cost of computational complexity increment,the proposed scheme obtains a performance improvement without occupying additional time-frequency physical resources.Compared with the existing hybrid carrier scheme,numerical simulation results have shown that the proposed extended hybrid carrier scheme has better anti-fading performance under the doubly-selective channel and improves the reliability of the wireless communication system effectively.

Modelling and Performance Analysis of Visible Light Communication System in Industrial Implementations

Visible light communication(VLC)has a paramount role in industrial implementations,especially for better energy efficiency,high speed-data rates,and low susceptibility to interference.However,since studies on VLC for industrial implementations are in scarcity,areas concerning illumination optimisation and communication performances demand further investigation.As such,this paper presents a new modelling of light fixture distribution for a warehouse model to provide acceptable illumination and communication performances.The proposed model was evaluated based on various semi-angles at half power(SAAHP)and different height levels for several parameters,including received power,signal to noise ratio(SNR),and bit error rate(BER).The results revealed improvement in terms of received power and SNR with 30 Mbps data rate.Various modulations were studied to improve the link quality,whereby better average BER values of 5.55×10^(−15) and 1.06×10^(−10) had been achieved with 4 PAM and 8 PPM,respectively.The simulation outcomes are indeed viable for the practical warehouse model.

Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond technologies.The random movement of mobile terminals in the indoor environment is a challenge in the VLC system.The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)algorithm.The optimized optical attocells were examined and compared with previous models.This novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 dB.The bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,respectively.The optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,respectively.As the results of the proposed model are optimal,it is suitable for standard office and room model applications.

Performance Analysis for Orthogonal Time Frequency Space Modulation Systems with Generalized Waveform

Orthogonal time-frequency space(OTFS),which exhibits beneficial advantages in high-mobility scenarios,has been considered as a promising technology in future wireless communication systems.In this paper,a universal model for OTFS systems with generalized waveform has been developed.Furthermore,the average bit error probability(ABEP)upper bounds of the optimal maximum likelihood(ML)detector are first derived for OTFS systems with generalized waveforms.Specifically,for OTFS systems with the ideal waveform,we elicit the ABEP bound by recombining the transmitted signal and the received signal.For OTFS systems with practical waveforms,a universal ABEP upper bound expression is derived using moment-generating function(MGF),which is further extended to MIMO-OTFS systems.Numerical results validate that our theoretical ABEP upper bounds are concur with the simulation performance achieved by ML detectors.

Evaluation of Codebook Design Using SCMA Scheme Based on A_(n) and D_(n) Lattices

The sparse code multiple access(SCMA)scheme is a Non-Orthogonal Multiple Access(NOMA)type of scheme that is used to handle the uplink com-ponent of mobile communication in the current generation.A need of the 5G mobile network is the ability to handle more users.To accommodate this,the SCMA allows each user to deploy a variety of sub-carrier broadcasts,and several consumers may contribute to the same frequency using superposition coding.The SCMA approach,together with codebook design for each user,is used to improve channel efficiency through better management of the available spectrum.How-ever,developing a codebook with a greater number of value sets is still another challenge.With enhanced techniques of encoding and decoding for 5G networks,mapping the multidimensional constellations in the SCMA system plays a signif-icant role in improving the system performance and enhancing the overall system performance.The creation of a codebook utilizing the SCMA approach in con-junction with the lattice theory is suggested in this study.The prototype is shaped using a popular lattice,such as A n and D n,as the basis.Afterward,from the primary lattice constellation,the multidimensional complex mother constellation with the most noticeable variance in power is discovered.The lattice-based cod-ing is generated by combining the codebooks with the mother constellation,and the codes in the matrices are mapped by rotating the constellations in this context.The suggested technique,in conjunction with the investigation of novel SCMA codebook sets,provides improved performance in terms of Bit Error Rate(BER)and complexity with regard to Signal to Noise Ratio(SNR).Finally,the bit error rate is reduced for various SNRs during transmission in the channel.

Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

The optimization of cognitive radio(CR)system using an enhanced firefly algorithm(EFA)is presented in this work.The Firefly algorithm(FA)is a nature-inspired algorithm based on the unique light-flashing behavior of fireflies.It has already proved its competence in various optimization prob-lems,but it suffers from slow convergence issues.To improve the convergence performance of FA,a new variant named EFA is proposed.The effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions,and simulation results show its superior performance compared to biogeography-based optimization(BBO),bat algorithm,artificial bee colony,and FA.As an application of this algorithm to real-world problems,EFA is also applied to optimize the CR system.CR is a revolutionary technique that uses a dynamic spectrum allocation strategy to solve the spectrum scarcity problem.However,it requires optimization to meet specific performance objectives.The results obtained by EFA in CR system optimization are compared with results in the literature of BBO,simulated annealing,and genetic algorithm.Statistical results further prove that the proposed algorithm is highly efficient and provides superior results.

Routing with Cooperative Nodes Using Improved Learning Approaches

In IoT,routing among the cooperative nodes plays an incredible role in fulfilling the network requirements and enhancing system performance.The eva-luation of optimal routing and related routing parameters over the deployed net-work environment is challenging.This research concentrates on modelling a memory-based routing model with Stacked Long Short Term Memory(s-LSTM)and Bi-directional Long Short Term Memory(b-LSTM).It is used to hold the routing information and random routing to attain superior performance.The pro-posed model is trained based on the searching and detection mechanisms to com-pute the packet delivery ratio(PDR),end-to-end(E2E)delay,throughput,etc.The anticipated s-LSTM and b-LSTM model intends to ensure Quality of Service(QoS)even in changing network topology.The performance of the proposed b-LSTM and s-LSTM is measured by comparing the significance of the model with various prevailing approaches.Sometimes,the performance is measured with Mean Absolute Error(MAE)and Root Mean Square Error(RMSE)for mea-suring the error rate of the model.The prediction of error rate is made with Learn-ing-based Stochastic Gradient Descent(L-SGD).This gradual gradient descent intends to predict the maximal or minimal error through successive iterations.The simulation is performed in a MATLAB 2020a environment,and the model performance is evaluated with diverse approaches.The anticipated model intends to give superior performance in contrast to prevailing approaches.

Selective Mapping Scheme for Universal Filtered Multicarrier

The next step in mobile communication technology,known as 5G,is set to go live in a number of countries in the near future.New wireless applica-tions have high data rates and mobility requirements,which have posed a chal-lenge to mobile communication technology researchers and designers.5G systems could benefit from the Universal Filtered Multicarrier(UFMC).UFMC is an alternate waveform to orthogonal frequency-division multiplexing(OFDM),infiltering process is performed for a sub-band of subcarriers rather than the entire band of subcarriers Inter Carrier Interference(ICI)between neighbouring users is reduced via the sub-bandfiltering process,which reduces out-of-band emissions.However,the UFMC system has a high Peak-to-Average Power Ratio(PAPR),which limits its capabilities.Metaheuristic optimization based Selective mapping(SLM)is used in this paper to optimise the UFMC-PAPR.Based on the cognitive behaviour of crows,the research study suggests an innovative metaheuristic opti-mization known as Crow Search Algorithm(CSA)for SLM optimization.Com-pared to the standard UFMC,SLM-UFMC system,and SLM-UFMC with conventional metaheuristic optimization techniques,the suggested technique sig-nificantly reduces PAPR.For the UFMC system,the suggested approach has a very low Bit Error Rate(BER).