Detection Algorithm of BPSK Signal of Parameter-Adjusted Bistable Stochastic Resonance Model Based on Scale Change

Fan, Xiangyu; Bai, Peng; Liang, Xiaolong; Zhang, Jiaqiang; Liu, Bin

doi:10.1109/access.2020.2997705

Cited by 10 publications

(9 citation statements)

References 43 publications

(60 reference statements)

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“…Overall Hardware Design Scheme. In order to realize the adaptive control and adjustment of the parameters of the bistable system, this article uses the AVR single-chip microcomputer to drive and control the digital potentiometer AD7376, adjust the resistance divider ratio in the bistable stochastic resonance circuit through the code of AD7376, and then change the bistable system parameters a and b, making the system produce stochastic resonance [8,9]. e system is mainly composed of AD7376 bistable stochastic resonance circuit, A/D conversion circuit, voltage polarity conversion circuit, power supply circuit, and AVR singlechip microcomputer module.…”

Section: 3mentioning

confidence: 99%

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Cui

Yang

Wang

et al. 2021

Security and Communication Networks

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Stochastic resonance is a new type of weak signal detection method. Compared with traditional noise suppression technology, stochastic resonance uses noise to enhance weak signal information, and there is a mechanism for the transfer of noise energy to signal energy. The purpose of this paper is to study the theory and application of weak signal detection based on stochastic resonance mechanism. This paper studies the stochastic resonance characteristics of the bistable circuit and conducts an experimental simulation of its circuit in the Multisim simulation environment. It is verified that the bistable circuit can achieve the stochastic resonance function very well, and it provides strong support for the actual production of the bistable circuit. This paper studies the stochastic resonance phenomenon of FHN neuron model and bistable model, analyzes the response of periodic signals and nonperiodic signals, verifies the effect of noise on stochastic resonance, and lays the foundation for subsequent experiments. It proposes to feedback the link and introduces a two-layer FHN neural network model to improve the weak signal detection performance under a variable noise background. The paper also proposes a multifault detection method based on the total empirical mode decomposition of sensitive intrinsic mode components with variable scale adaptive stochastic resonance. Using the weighted kurtosis index as the measurement index of the system output can not only maintain the similarity between the system output signal and the original signal but also be sensitive to impact characteristics, overcoming the missed or false detection of the traditional kurtosis index. Experimental research shows that this method has better noise suppression ability and a clear reproduction effect on details. Especially for images contaminated by strong noise (D = 500), compared with traditional restoration methods, it has better performance in subjective visual effects and signal-to-noise ratio evaluation.

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Section: 3mentioning

confidence: 99%

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Cui

Yang

Wang

et al. 2021

Security and Communication Networks

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“…For a (n,k,d) linear block code, if any code M=(m n ,m n−1 ,……,m 0 ) shifts circularly and then obtain the new code M (i) =(m n+1 ,m n ,……,m 1 ) which also belongs to the original linear block code, this (n,k,d) code is called cyclic code. This kind of codes have a regular algebraic structure and they are subclosed, usually the code polynomial is used to present them [6,7].…”

Section: Cyclic Channel Codementioning

confidence: 99%

Comparative Analysis of Channel Coding in Communication Technology

2024

HSET

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The performance analysis of Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) employing error-correcting code is highlighted in this work. Several error-correcting code types were employed via an Additive White Gaussian Noise (AWGN) channel to determine the bit error rate. Two techniques were utilized as encoders and decoders: hamming code and cyclic code. Source coding used Huffman coding. Essentially, signal energy to noise power density ratio (Eb/No) and the bit rate error (BER) were used to measure performance. Comparisons were also made between BPSK and QPSK in terms of symbol error capability. MATLAB R2022b was the program used for all the simulations. The conclusion is that different coding methods have a certain error correction range, and the signal-to-noise ratio (SNR) can only reduce the BER in the error correction range, and if it is not within the error correction range, it will increase the bit error rate.

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“…The simulated system is an extended version of the system found in [50] and transmits information with using polar coding and BPSK modulation through an AWGN channel with generalized correlated fading [51]. The random interleaver [26] used in this work has the same length N of the polar code.…”

Section: System Modelmentioning

confidence: 99%

Performance of Polar Codes over Generalized Correlated Fading Channels

Barros

Oliveira²,

Alcoforado³

et al. 2022

JCIS

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Polar coding, as introduced by Arikan in 2009, is an error correcting code scheme that uses the polarization technique to obtain almost noise-free channels that are suitable for transmission. Polar codes are being widely studied due to their applications on the 5th Generation (5G) of mobile communication systems. In 5G communications, the wireless channel is subject to fading that can significantly degrade the quality of the transmitted signals. In this context, the generalized fading models are useful due to their capacity to model a variety channel conditions ranging from moderate to severe fading by adjusting some parameters. In this work, the authors investigate the performance of polar codes considering the transmission over generalized fading channels. Additionally, the effect of channel correlation is analyzed and a random interleaver is proposed to mitigate the negative impact of the correlation on the system performance. For the system with generalized fading modeled by η-µ distribution and Cyclic Redundancy Check (CRC) Aided Successive Cancellation List (CA-SCL) decoding, the scenario with correlated fading channel and interleaving shows a performance improvement compared to the system without interleaving. In this case, a gain of approximately 3.5 dB is obtained considering a Bit Error Rate (BER) of 10 −2 . Considering the α-µ (α = 2 and µ = 1) and the κ-µ (κ = µ = 2) fading channels, the uncorrelated systems outperform the correlated ones. Among them, the interleaver improves the performance of the systems. For BER of 10 −2 , as an example, the use of fading correlated channel and interleaver shows a performance improvement of 12 dB and 0.5 dB for the α-µ and κ-µ fading channels, respectively.

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Detection Algorithm of BPSK Signal of Parameter-Adjusted Bistable Stochastic Resonance Model Based on Scale Change

Cited by 10 publications

References 43 publications

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Theory and Application of Weak Signal Detection Based on Stochastic Resonance Mechanism

Comparative Analysis of Channel Coding in Communication Technology

Performance of Polar Codes over Generalized Correlated Fading Channels

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