###### Abstract  
To better meet communication needs, 6G proposes Integrated Satellite-Terrestrial Networks. Integrated Sensing and Communication (ISAC) is one of the key technologies of Integrated Satellite-Terrestrial Networks, which can reduce the energy consumption of the system, improve communication efficiency, and increase the utilization rate of spectrum resources. In the existing technology, the Modulated Wideband Converter (MWC) system can provide support for the miniaturization and intelligence of wireless device sensing and communication systems. Therefore, the MWC system can be used as a preliminary application of ISAC technology. However, the reconstruction effect of the conventional MWC system under the influence of noise is not stable. Therefore, we propose a signal processing optimization scheme for the MWC system based on spatial information entropy. First, the subsequent reconstruction algorithm is considered to require the dynamic and flexible processing of the sampled signals to reduce the influence of noise. Second, for the shortcomings of the original Orthogonal Matching Pursuit (OMP) algorithm, the concept of the genetic algorithm is used to optimize the algorithm by constructing the feature factor through spatial information gain and spatial information features. According to the simulation results, compared with the traditional MWC system, the scheme proposed in this paper is improved in all indicators. integrated satellite-terrestrial networks; integrated sensing and communication; modulated wideband converter; spatial information entropy; signal process +
Footnote †: journal: Electronics Electronics  
20241  
serious interference problems and affect the system's performance. Therefore, the spectrum utilization scheme and the corresponding interference management technology will be the key technologies for Integrated Satellite-Terrestrial Networks. ISAC technology can mitigate the impact of limited spectrum resources and improve the utilization of spectrum resources. The aim of ISAC is to exploit the highly convergent characteristics of the communication system and the sensing system in terms of hardware and information processing, to make the two independent functions of communication and sensing unified in a single system for mutual benefit [6]. To realize the full integration of communication and sensing, ISAC technology still needs a long stage of development. Among the existing technologies, the MWC based on sub-Nyquist can be used as the basis for the development of ISAC technology [7]. On the one hand, the MWC system fulfills the dynamic sensing function of the spectrum by recovering the signal support set. On the other hand, it achieves communication by reconstructing the signal. This means that the MWC system can support the miniaturization and intelligence of wireless device systems. However, under the influence of noise, the effect of MWC on signal processing is not stable, which affects the accuracy of information transfer in the sensing and communication process [8; 9; 10; 11]. It is necessary to process the sampled signals in a timely manner, which can enhance the accuracy of the subsequent communication and form a virtuous cycle of sensing and communication. Since most actual signals have non-stationary characters, separate time-domain and frequency-domain analyses cannot provide comprehensive information about the signal. The time-frequency analysis method is appropriate for research on non-stationary signals, the corresponding denoising method is also applied in various fields. The main time-frequency analysis methods include short-time Fourier transform (STFT), wavelet transform (WT), Empirical Mode Decomposition (EMD), and Singular Spectrum Analysis (SSA). WT can focus on the local characteristics of the signal by multi-scale analysis. The use of wavelet transform denoising can retain the peaks and mutations of signals while suppressing the interference of high-frequency noise. The wavelet basis function has a large impact on the wavelet denoising effect.