Abstract
Given that signal is weakened to a certain extent in the process of noise suppression using mainstream method, and that new noise is introduced by signal processing system, causing the decrease of detection performance, to improve the performance of detection to BPSK signal under the condition of strong noise and no prior information, the detection algorithm of BPSK signal of bistable stochastic resonance model based on scale change is proposed in this study. Using classical bistable stochastic resonance (BSR) system, only low-amplitude and low-frequency periodic signal can be processed. Scale change is first made to BSR in this study, verifying that BSR can be applied to high-frequency BPSK signal under high sampling frequency condition, and nonlinear threshold detection system is designed following Neyman-Pearson criterion to deduce and quantitatively show error rate of detector. Besides, complete flow for signal detection was built by taking it as feedback quantity to adjust the system parameters adaptively. Scale change feasibility and applicability of algorithm proposed in this study were verified through simulation experiment, which lays the theoretical basis for the detection of weak BPSK signal under low signal-to-noise ratio (SNR).
Highlights
Binary Phase Shift Keying (BPSK) has been broadly adopted in numerous existing communication protocols, e.g., IEEE 802.11a [1] and the second generation digital terrestrial television broadcasting system [2], to ensure the quality of service (QoS) against poor wireless channels
The contribution of this study is to extend the traditional stochastic resonance (SR) algorithm for small amplitude periodic signals to the detection of non-periodic high-frequency signals based on scale transformation, which broadens the application range of the algorithm, and significantly improves the ability of weak signal detection
It can be seen that increase of a is conducive to improvement of signal signal-to-noise ratio (SNR), and scaling proposed in this study requires a to be large as much as possible, suggesting that applicability of stochastic resonance can be expanded by increasing a, and system gain can be enhanced simultaneously, which is one advantage of scaling method proposed in this study
Summary
Binary Phase Shift Keying (BPSK) has been broadly adopted in numerous existing communication protocols, e.g., IEEE 802.11a [1] and the second generation digital terrestrial television broadcasting system [2], to ensure the quality of service (QoS) against poor wireless channels. Literature [33] proposed a method combining adaptive bistable stochastic resonance and multi-scale noise tuning based on the noise characteristics to improve the detection ability for weak signals. Based on the above literatures, this paper studies the BPSK statistical characteristics under the condition of no prior information, unknown noise types and signal parameters, and performs signal detection based on Neiman-Pearson criterion. D(n) denotes binary sequence and d(n) ∈{0,1}, with equal probability valuing
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