## 1 Introduction  
Orthogonal frequency division multiplexing (OFDM) has been widely used in wireless local area networks, mobile communications, and other fields due to its high-frequency band utilization and ease of engineering implementation. In recent years, scholars have been dedicated to research on the detection of weak OFDM signals in complex electromagnetic environments. Stochastic resonance (SR) has broken the traditional concept that noise is harmful in weak signal detection methods, using noise as an energy source to enhance weak signals. Applying the stochastic resonance theory to the detection of OFDM signals has great research significance and application prospects. Currently, scholars at home and abroad have conducted extensive research on communication signal detection based on stochastic resonance. [PERSON] et al. [1] applied traditional bistable stochastic resonance to OFDM signal detection, improving the detection effect of OFDM signals. However, due to the limitations of the traditional potential function structure, the system suffers from output saturation issues. [PERSON] et al. [2] constructed a new piecewise potential function model to improve the antisaturation performance of the system, but their system model is a first-order system and does not consider the effect of combining a nonsaturating potential function model with a second-order underdamped system. Addressing the poor anti-noise performance of traditional stochastic resonance systems, [PERSON] et al. [3] constructed a second-order underdamped periodic potential resonance system, demonstrating that stochastic resonance can occur in second-order underdamped systems. [PERSON] et al. [4] built a second-order underdamped nonsaturating stochastic resonance system, and the experimental results showed that this system can detect weak signals in different noise environments. [PERSON] et al. [5] proposed a signal detection method based on an underdamped tristable stochastic resonance system which exhibits stronger noise suppression capabilities and better signal enhancement effects. [PERSON] et al. [6] theoretically derived the signal-noise ratio formula for second-order underdamped systems, proving that the anti-noise performance of underdamped systems is superior to that of overdamped systems. The aforementioned literature demonstrates the superiority of underdamped systems in signal enhancement but does not analyze and compare the advantages and disadvantages of underdamped and overdamped systems in terms of response speed. [PERSON] et al. [7] and [PERSON] et al. [8] derived theoretical formulas for the mean first passage time and particle transition rate of second-order underdamped systems, indirectly proving that underdamped systems respond faster than overdamped systems from the perspective of particle transitions. However, they did not directly discuss system response speed from the perspective of system response. [PERSON] et al. [9; 10; 11; 12] proposed a tristable intra-well stochastic resonance system and analyzed its transient stable response, but did not provide a detailed analysis of system response speed and its influencing factors. Therefore, this paper proposes an enhancement and demodulation system for OFDM signals based on SUUBSR. The main contributions and innovations of this study are as follows:  
1. A method for enhancing and demodulating OFDM signals based on SUUBSR is proposed. 2. OFDM signals are divided into in-phase and quadrature components, which are processed separately by stochastic resonance, addressing the limitation that stochastic resonance systems cannot directly process OFDM signals. 3. Analytical expressions for the transient and steady-state responses, as well as time-resolved expressions, of the OFDM signal enhancement and demodulation system based on SUUBSR are theoretically derived. The influence of various parameters on the transient and steady-state responses of the system is analyzed. 4.