为了解决传统随机共振系统在微弱正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号解调应用中存在的人工选择参数困难、解调效果差的问题,提出一种基于粒子群优化(Particle Swarm Optimization,PWO)算法的GP(Gaussian Potential)-周期随机共振系统的微弱OFDM信号检测方法.该方法利用GP-周期随机系统对OFDM信号经正交变换后的两路高频信号分别进行随机共振,同时运用阻尼参数与信号频率之间的关系对两路信号进行降频处理,使得上下两路信号都能够发生随机共振;然后使用PWO算法对随机共振的系统参数进行优化处理,以使得上下两路信号达到最优的共振效果;最后,将上下两路共振之后的信号合成完成OFDM信号解调,得到最终的数字序列.本文探讨了优化前后GP-周期随机共振系统的共振效果,研究了优化前后GP-周期随机共振诱导下的OFDM系统星座图的聚集程度以及误码率情况,对比分析了经典双稳随机共振、经典三稳随机共振和所提模型对OFDM信号检测的影响.仿真结果表明:相比常用的传统随机共振模型,该方法用于OFDM信号检测的星座图中信号点的聚集程度更高,同时OFDM系统误码率在同样的信噪比下降低50％左右.
OFDM signal detection of GP-periodic stochastic resonance system under PSO algorithm
In order to solve the problems of difficult manual parameter selection and poor demodulation effect in the application of weak OFDM(Orthogonal Frequency Division Multiplexing)signal demodulation in traditional stochastic resonance systems,a weak OFDM signal detection method for GP(Gaussian Potential)-periodic stochastic resonance system based on Particle Swarm Optimization(PWO)algorithm is proposed.This method uses the GP-periodic stochastic system to randomly resonate the two high-frequency signals after the quadrature transformation of the OFDM signal,and uses the relationship between the damping parameters and the signal frequency to downfrequency the two signals,so that the upper and lower signals can have random resonance.Then,the PWO algorithm is used to optimize the system parameters of random resonance to achieve the optimal resonance effect of the upper and lower signals.Finally,the signals after the upper and lower resonances are synthesized to complete the demodulation of the OFDM signal to obtain the final digital sequence.In this paper,the resonance effect of GP-period stochastic resonance system before and after optimization is discussed,the aggregation degree and bit error rate of the constellation diagram of OFDM system induced by GP-periodic random resonance before and after optimization are studied,and the effects of classical bistable random resonance,classical tristability random resonance and the proposed model on OFDM signal detection are compared and analyzed.The simulation results show that compared with the commonly used traditional stochastic resonance model,the degree of aggregation of signal points in the constellation diagram used for OFDM signal detection is higher,and the bit error rate of the OFDM system is reduced by about 50％under the same signal-to-noise ratio.
GP-periodic stochastic resonancesignal detectionparticle swarm optimization algorithmorthogonal frequency division multiplexingadjust the damping parameters
万方数据
维普
