Effect Of Error Propagation Research Articles

Deep Learning-Aided OFDM-Based Generalized Optical Quadrature Spatial Modulation

In this paper, we propose an orthogonal frequency division multiplexing (OFDM)-based generalized optical quadrature spatial modulation (GOQSM) technique for multiple-input multiple-output optical wireless communication (MIMO-OWC) systems. Considering the error propagation and noise amplification effects when applying maximum likelihood and maximum ratio combining (ML-MRC)-based detection, we further propose a deep neural network (DNN)-aided detection for OFDM-based GOQSM systems. The proposed DNN-aided detection scheme performs the GOQSM detection in a joint manner, which can efficiently eliminate the adverse effects of both error propagation and noise amplification. The obtained simulation results successfully verify the superiority of the deep learning-aided OFDM-based GOQSM technique for high-speed MIMO-OWC systems.

BER Performance Analysis for Downlink Nonorthogonal Multiple Access With Error Propagation Mitigated Method in Visible Light Communications

In order to mitigate the error propagation (EP) effect on the bit error rate (BER) performance due to the imperfect successive interference cancellation for the non-orthogonal multiple access (NOMA)-based visible light communication (VLC) downlinks, adjustable bit rate superposition coding (ABRSC) and sample-and-sum successive interference cancellation (SSSIC) decoding schemes are proposed in this paper. Based on the modified fixed-power allocation (MFPA) strategy, the closed-form expressions of BER are derived for the two-user case with on-off keying, and further extended to the multi-user scenario. The residual probability of EP is introduced and derived to theoretically assess the effectiveness of the proposed ABRSC and SSSIC schemes. Monte Carlo simulation is also conducted to validate the analytical BER results. The BER performance of the NOMA-based VLC system with multiple users is further analyzed and discussed in detail. It is found that under the total average optical transmission power constraint, the allocated average optical transmission power to current user should be higher than that to all rest of users, i.e., the power allocation factor (PAF) is supposed to be greater than 1/2, in order to avoid the error floor issue of current user, hence facilitating the successful implementation of SSSIC. Besides, increasing the bit-rate factor (BRF) could mitigate the effect of EP, and larger BRF leads to more efficient outcomes in alleviating the effect of EP.

On the simultaneous reconstruction of boundary Robin coefficient and internal source in a slow diffusion system

Consider an inverse problem of simultaneous reconstruction of boundary impedance coefficient and space-dependent source term from the final measurement data for a slow diffusion system, which is governed by a diffusion equation with time-fractional order derivative and Robin boundary condition. We firstly prove the uniqueness of this inverse problem by the maximum principle for the slow diffusion system. Then a regularizing scheme combining the mollification method and the Tikhonov regularization is proposed to recover the two unknowns, with a rigorous analysis on the choice strategies for the regularizing parameters and the error estimates on the regularizing solutions, revealing the error propagation effects due to recovering the boundary Robin coefficient firstly. Numerical examples are presented to illustrate the validity of the proposed method and support our theoretical analysis.

Estimation of High-Frequency Vibration Parameters for Terahertz SAR Imaging Based on FrFT With Combination of QML and RANSAC

High-frequency vibration of motion platform leads to paired echo for synthetic aperture radar (SAR) imaging, especially in terahertz band due to its shorter wave length. Different from most existing parameters estimation methods only considering single component high-frequency vibration, in this paper a novel method considering multi-components vibration model is proposed based on fractional Fourier transform (FrFT) with combination of quasi-maximum likelihood (QML) and random sample consensus (RANSAC). Based on the model establishment of high-frequency vibration error in the echo, its instantaneous chirp rate (ICR) is firstly estimated by FrFT in sliding sub-aperture, followed which the vibration parameters are coarsely obtained through spectrum analysis and least square (LS) regression. To further refine the parameters estimates, QML is developed for compensating the deviation both caused by the frequency spectrum leakage and the error propagation effects by one-dimensional search over the vibration frequency. Meanwhile, RANSAC is adopted for avoiding the outlier of the ICR estimates in LS regression, especially at low signal-to-noise ratio (SNR). Thus, the refinement strategy based on the combination of QML and RANSAC is developed, whose utilization improves the estimation accuracy of vibration parameters. Finally, the paired echo in terahertz SAR (THz-SAR) imaging is effectively suppressed by the proposed method, and the high-quality THz-SAR imaging results are achieved. Both simulations of single component and multi-components high-frequency vibration are used to verify the validity of the proposed method. The simulation results show that the proposed method has higher estimation accuracy even at low SNR.

Estimation of uncertainty in transmutation rates of LLFPs in a fast reactor transmutation system via an estimation of the cross-section covariances

ABSTRACT A new concept of transmutation system for six long-lived fission products (LLFPs: 79Se, 93Zr, 99Tc, 107Pd, 129I, and 135Cs) consisting of three small-size fast reactor cores was proposed. In order to establish a method to estimate the effects of cross-section uncertainties on the transmutation rates of the LLFPs, cross section covariances for the six LLFPs were estimated using a T6 system which includes resonance and statistical models via propagation of model uncertainties, and the uncertainties of transmutation rates and support factors of the six LLFPs in the three fast reactors were estimated based on a Total Monte Carlo (TMC) method. It was made clear that some of the transmutation rates of these LLFPs have large uncertainties indicating that the accuracy of cross sections for them is not enough, and hence the strategy for efficient transmutation may have to be reconstructed. It is concluded that the T6 system and the TMC method used in this study are quite effective not only to estimate the uncertainties of cross sections but also to assess the effect of error propagation throughout the series of calculations conducting in this study.

Error Propagation Mitigation in Sliding Window Decoding of Braided Convolutional Codes

We investigate error propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or one that continuously outputs blocks in a streaming fashion. In this case, decoder error propagation, due to the feedback inherent in BCCs, can be a serious problem. To mitigate the effects of error propagation, we propose several schemes: a window extension algorithm where the decoder window size can be extended adaptively, a resynchronization mechanism where we reset the encoder to the initial state, and a retransmission strategy where erroneously decoded blocks are retransmitted. In addition, we introduce a soft BER stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm, resynchronization mechanism, and retransmission strategy, the BER performance of BCCs can be improved by up to four orders of magnitude in the signal-to-noise ratio operating range of interest, and the soft BER stopping rule can be employed to reduce computational complexity.

On Efficient Concatenation of LDPC Codes With Constrained Codes

In this article, an efficient concatenation of error correction codes with constrained codes is proposed. Generally, constrained codes are designed to match specified channels, whereas error correction coding schemes are designed to correct the channel errors. Both play important roles to ensure the integrity of data in data storage systems. In this study, we first investigate the design of k-constrained codes combined with a low-density parity-check (LDPC) code, and then we extend the idea to the design of dc-free k-constrained LDPC codes. Simulation results show that the proposed designs achieve an improved bit error rate (BER) performance, compared to prior art schemes. In particular, the proposed design for the dc-free k-constrained codes not only fully eliminates the effect of error propagation in a reverse configuration but also achieves significant dc suppression.

DFE Error Propagation and FEC Interleaving for 400GbE PAM4 Electrical Lane

This paper analyzes the effect of error propagation of decision feedback equalizer (DFE) for PAM4 based 400Gb/s Ethernet. First, an analytic model for the error propagation is proposed to estimate the probability of different burst error length due to error propagation for PAM4 link system with multi-tap TX FFE (Feed Forward Equalizer) + RX DFE architecture. After calculating the symbol error rate (SER) and bit error rate (BER) based on the probability model, the theoretical analysis about the impact of different equalizer configurations on BER is compared with the simulation results, and then BER performance with FEC (Forward Error Correction) is analyzed to evaluate the effect of DFE error propagation on PAM4 link. Finally, two FEC interleaving schemes, symbol and bit interleaving, are employed in order to reduce BER further and then the theoretical analysis and the simulation result of their performance improvement are also evaluated. Simulation results show that at most 0.52dB interleaving gain can be achieved compared with non-interleaving scheme just at a little cost in storing memory and latency. And between the two interleaving methods, symbol interleaving performs better compared with the other one from the view of tradeoff between the interleaving gain and the cost and can be applied for 400Gb/s Ethernet.

Improved Performance of NOMA: Multilevel Symmetric Superposition Coding under Rayleigh Fading Channel

The main principle of non-orthogonal multiple access (NOMA) recommends that low power is allocated to the strong channel user, in order to guarantee the user fairness. Recently, symmetric superposition coding (SSC) has been proposed to mitigate the effect of error propagation (EP) in NOMA with quadrature phase shift keying (QPSK) for visible light communication (VLC) networks. It has been verified analytically that SSC NOMA with binary phase shift keying (BPSK) achieves the performance of the perfect SIC for the power allocation factor range less than 50%. However, SSC for multilevel modulations has not been reported in the literature in NOMA. As continuing researches, we propose NOMA with the multilevel SSC for the 4-ary pulse amplitude modulation (4PAM). It is shown that the performance of 4PAM SSC NOMA achieves the perfect SIC performance for the power allocation factor range less than about 10 %, while the performance of 4PAM NOMA with the normal superposition coding (NSC) is the same as that of the perfect SIC NOMA for the power allocation factor range less than about 5 %. As a result, the promising feature of SSC, i.e., the improved performance on the low power allocation range, is still preserved for multilevel modulations.

Gradual Channel Pruning While Training Using Feature Relevance Scores for Convolutional Neural Networks

The enormous inference cost of deep neural networks can be scaled down by network compression. Pruning is one of the predominant approaches used for deep network compression. However, existing pruning techniques have one or more of the following limitations: 1) Additional energy cost on top of the compute heavy training stage due to pruning and fine-tuning stages, 2) Layer-wise pruning based on the statistics of a particular, ignoring the effect of error propagation in the network, 3) Lack of an efficient estimate for determining the important channels globally, 4) Unstructured pruning requires specialized hardware for effective use. To address all the above issues, we present a simple-yet-effective gradual channel pruning while training methodology using a novel data-driven metric referred to as feature relevance score. The proposed technique gets rid of the additional retraining cycles by pruning the least important channels in a structured fashion at fixed intervals during the actual training phase. Feature relevance scores help in efficiently evaluating the contribution of each channel towards the discriminative power of the network. We demonstrate the effectiveness of the proposed methodology on architectures such as VGG and ResNet using datasets such as CIFAR-10, CIFAR-100 and ImageNet, and successfully achieve significant model compression while trading off less than $1\%$ accuracy. Notably on CIFAR-10 dataset trained on ResNet-110, our approach achieves $2.4\times$ compression and a $56\%$ reduction in FLOPs with an accuracy drop of $0.01\%$ compared to the unpruned network.

A Partially Coupled LDPC Coded Scheme for the Gaussian Wiretap Channel

In this letter, we propose an effective partially coupled low-density parity-check coded scheme to reduce the security gap for the Gaussian wiretap channel. In our scheme, codewords are partially coupled by exclusive OR adding the message bits from a codeword to the parity check bits from its consecutive codeword. An iterative decoding algorithm is also proposed to utilize the correlations between codewords. Based on this design, error propagation effect between codewords is achieved to worsen the performance at the eavesdropper, which receives messages via a poor conditioned channel. Numerical results demonstrate that the proposed scheme outperforms the punctured scheme in terms of the equivocation rate and the security gap.

Ground Maneuvering Targets Imaging for Synthetic Aperture Radar Based on Second-Order Keystone Transform and High-Order Motion Parameter Estimation

With the developments of the synthetic aperture radar (SAR) system, the long dwell time provides high resolution but at the same time it produces large range migration (RM) and Doppler frequency migration, which brings a new challenge for ground moving target imaging. To address those problems, a ground moving target refocusing method based on a novel parameter estimation algorithm, namely second-order Keystone transform (SOKT)-Radon-cubic phase function-Fourier transform (RCFT), is proposed in this work. First, the SOKT is applied to correct the range curvature. After that, the Hough transform is utilized to estimate the trajectory slope for the range walk correction and the across-track velocity acquirement. Finally, a novel coherently integrated parameter estimation method, termed as RCFT, is developed in this work to transform the azimuth quadratic frequency-modulated signal into a peak point in two-dimensional (2-D) time-frequency plane. In the process, the second- and third-order motion parameters are simultaneously obtained, which eliminates the error propagation effect. Due to 2-D coherent integration realization and its bilinear function feature, the proposed RCFT method is capable of obtaining accurate parameter estimates in low signal-to-noise ratio scenario with a relatively low computational burden. Compared with the conventional SAR imaging methods using the second-order phase model, the proposed method produces better imaging quality since the third-order Doppler frequency migration is effectively eliminated. The performance of the proposed method is demonstrated by both the simulated and real data.

The Effect of Error Propagation on the Performance of Polar Codes Utilizing Successive Cancellation Decoding Algorithm

In this paper, we discuss and analyze the effect of error propagation on the performance polar codes decoded using the successive cancellation algorithm. We show that error propagation due to erroneous bit decision is a catastrophic issue for the successive cancellation decoding of polar codes. Even a wrong decision on a single bit may cause an abundance of successor bits to be wrongly decoded. Furthermore, we observe that the performance of polar codes is significantly improved if even single bit errors are detected and corrected before the decoding of successor bits.

A New Data Pilot-Aided Channel Estimation Scheme for Fast Time-Varying Channels in IEEE 802.11p Systems

The channel estimation in the IEEE 802.11p vehicle-to-everything (V2X) communication systems is generally a challenging task due to high mobility and insufficient number of pilots. Conventional data pilot-aided channel estimation schemes are difficult to apply in practice due to high complexity and the error propagation problem. In this correspondence paper, we propose a new data pilot-aided channel estimation scheme to overcome both issues. To this end, we develop a state feedback decision algorithm that enables us to extract reliable data pilots within a few received symbols. As a result, we can minimize both the error propagation effect and the computational complexity. We verify the complexity gain of the proposed scheme through the complexity analysis. Finally, we demonstrate the accuracy of the proposed channel estimation scheme in terms of the packet error rate performance.

Flexible-Rate SIC-Free NOMA for Downlink VLC Based on Constellation Partitioning Coding

Visible light communication (VLC) systems utilizing conventional superposition coding/successive interference cancellation (SPC/SIC)-based non-orthogonal multiple access (NOMA) suffer from the error propagation effect due to imperfect SIC. In this letter, we propose a flexible-rate SIC-free NOMA technique for downlink VLC systems, based on constellation partitioning coding (CPC) and uneven constellation demapping (UCD). By using CPC/UCD, SIC is not required and hence error propagation can be eliminated in NOMA-based VLC systems. Moreover, by selecting a proper bit allocation scheme, flexible-rate multiple access can be supported in the VLC system applying CPC/UCD-based NOMA. Proof-of-concept two-user VLC experiments verify that, compared with conventional SPC/SIC-based NOMA, the bit error rate performance of the near user can be greatly improved by using CPC/UCD-based NOMA, and hence the effective power allocation ratio range can be substantially extended.

Hierarchical-P Reference Picture Selection Based Error Resilient Video Coding Framework for High Efficiency Video Coding Transmission Applications

In this paper, a new reference picture selection (RPS) is proposed for a high efficiency video coding (HEVC) framework. In recent studies, HEVC has been shown to be sensitive to packet error which is unavoidable in transmission applications especially for wireless networks. RPS is an effective error resilient technique for video transmission systems where a feedback channel with short round trip delay time is available. However, its procedure cannot directly apply to the HEVC framework and thus this paper expands it. In RPS, error propagation can still happen during round trip delay time. To alleviate the effect of error propagation for better quality, the proposed algorithm considers both the RPS technique and the region-based intra mode selection method by using some novel features of HEVC. Experimental results demonstrate that the proposed method outperforms the hierarchical-P RPS algorithm in terms of PSNR and other metrics. The average PSNR improvement of the proposed algorithm over the reference algorithm under 10% packet error rate is 1.56 dB for 1080p sequences, 2.32 dB for 720p sequences and 1.01 dB for wide video graphics array (WVGA) sequences, respectively. The performance of proposed method is also tested for applications where feedback information is not available. The proposed method shows noticeable improvement for video sequences that contain low or moderate level of motions.

Free-Form Surface Analysis and Linking Strategies for High Registration Accuracy in Quality Assurance Applications

Robot-based optical inspection systems have become more affordable and show great potential for measuring geometric features of sheet metal parts in production sites. To deal with the lack of positioning accuracy of current industrial robots for the registration of range images, a stitching algorithm is often applied. This paper presents a concept to improve the fine registration accuracy in order to reduce the effect of error propagation. A geometric analysis of the surface is introduced to identify suitable regions for applying adapted texture projections onto the part. In addition, an approach to develop a corresponding linking strategy is described. The proposed concept promises to measure geometric features on both plane and highly featured surfaces with high accuracy.

Exact Outage Probability Analysis of Dual-Transmit-Antenna V-BLAST With Optimum Ordering

An exact outage probability analysis of zero-forcing V-BLAST technique with two transmit antennas and $r$ receive antennas $(r\geq 2)$ is provided under a decoding order that is optimum in the sense of minimizing the outage probability. Different from the earlier approximated analyses, an exact closed-form expression on the outage probability is attained without neglecting the effect of error propagation. Assuming a one-bit feedback from the receiver to the transmitter, the optimal power and rate allocation values are numerically computed based on the exact outage probability expression under different objective functions. The presented results are also applicable for the corresponding dual scenarios that may involve antenna selection and/or user scheduling.

Improved Detection in Successive Interference Cancellation NOMA OFDM Receiver

A successive interference cancellation receiver is one of the important blocks in non-orthogonal multiple access (NOMA) transmission. The quality of detection of the strongest user signals often decides about the quality of the whole system and minimizes the error propagation effect. In this paper, we propose an improved detection algorithm, which allows for using the NOMA transmission in a much smaller range of power differences between the terminals sharing common radio resources in the uplink, as compared with standard successive cancellation. The idea lies in the application of tentative decisions about weaker signals in the detection of stronger ones and then, after improved detection of stronger user signals, achieving more reliable decisions about the weaker ones. The simulation results reported in the paper confirm our idea, showing a much higher detection quality of the proposed receiver when compared with the standard solution.

Efficient and secure cipher scheme for multimedia contents

The impact of confidentiality and privacy breaches are more pronounced when dealing with multimedia contents. One of the obvious techniques to counter these threats is the use of encryption. A number of algorithms for robust image encryption, targeted for real-time applications with tight resource constraints, has been proposed in the literature. In this paper, first, we analyze two recent cipher schemes for image contents, which are based on two rounds. We show that the schemes are designed to ensure maximum avalanche effect in the whole image by employing the chaining block code mode (CBC) in forward and backward directions. However, they do not lend themselves to parallel implementation and they have a problem with error propagation, which is not desirable for wireless multimedia transmission. As such, we propose to redesign the underlying algorithm to make it practical when used with applications that either suffer from a high error percentage or from real-time constraints. The modified cipher employs the counter mode to eliminate the chaining process (forward and backward), which allows for parallel computations and minimizes the effect of error propagation. According to the security and performance results, the proposed scheme can respond better to the applications and/or system requirements and limitations by ensuring a better performance and an equally high level of security compared to both ciphers in addition to minimum error propagation. To the best of our knowledge, the proposed scheme is the first dynamic key-dependent stream cipher scheme with a pseudo-random key-stream generation for re-ordering of sub-matrices.