Application Of Weak OFDM Signal Detection With GP-Period Bistable Stochastic Resonance

With the wide application of 4G technology,orthogonal frequency division multiplexing(OFDM),as a unique carrier modulation technology,has attracted much attention because it can resist symbol interference and carrier interference caused by multipath effects while having efficient spectral efficiency.Stochastic resonance uses the nonlinear mechanism of nonlinear systems to convert noise energy into signal energy to enhance weak signals,which is eye-catching in the field of weak signal detection.Considering the insufficient performance of the classical traditional stochastic resonance model in the detection of weak OFDM signals and the randomness of manually selected system parameters,this paper proposes a weak OFDM signal detection method based on the Gaussian potential(GP)Gaussian-periodic bistable random resonance algorithm based on the Particle Swarm Optimization(PSO)algorithm to increase the detection effect of weak OFDM signals.The full text of the study is as follows:(1)The research status of stochastic resonance theory at home and abroad,the development process of OFDM technology and the research status of OFDM signal detection are introduced,and a weak OFDM signal detection method for GP-period bistable stochastic resonance system based on particle swarm optimization algorithm is proposed.(2)The classical bistable stochastic resonance theory model is elaborated and the corresponding Langevin equation is derived.According to the Langevin equation,the output response of stochastic resonance in different states was studied;The influence of signal,noise and signal noise on the potential function and output response of classical bistable stochastic resonance system is analyzed in detail.The output response of classical bistable stochastic resonance systems under different conditions of adiabatic approximation theory and linear response theory is explored in detail.Finally,the principle of modulation and demodulation of OFDM signals is discussed.(3)The influence of the potential function of Gaussian stochastic resonance system and periodic stochastic resonance system under system parameters was analyzed,and the Langevin equation of GP-period bistable stochastic resonance model was derived.Four downscaling methods under the condition of large-parameter signals are discussed,and the downscaling process that matches the damping parameters to the signal frequency is derived.The advantages and disadvantages of Euler’s method and Rungekuta method are analyzed,and a fourth-order Rungekuta method for solving GP-period bistable stochastic resonance system models is given.(4)The general law of noise affecting the signal-to-noise ratio of stochastic resonance output was studied.The relationship between the probability density characteristics of Gaussian white noise and the parameters σ and parameters μ was explored.The relationship between the probability density characteristics of levy noise and the characteristic parameters α and skew parameters β was explored.The output response of single-carrier noisy signal and multi-carrier noisy signal in GP-period bistable random resonance under Gaussian white noise and levy noise is simulated and analyzed.(5)Study the basic process of particle swarm optimization algorithm in parameter optimization.The block diagram of OFDM signal detection of GP-period bistable stochastic resonance system under PSO algorithm is given,and a weak OFDM signal detection method based on GP-period bistable random resonance under PSO algorithm is proposed and the specific process is given.The output time domain map and power spectrum of GP-period bistable stochastic resonance before and after optimization were compared and analyzed.The constellation plot and bit error rate of the traditional stochastic resonance model and the proposed model after demodulation of weak OFDM signals were analyzed.The results show that compared with the weak OFDM signal detection method of the traditional bistable stochastic resonance system,this method can effectively enhance the weak OFDM signal detection effect,reduce the bit error rate of OFDM signal,and improve the noise resistance performance of OFDM system.