Spatial Information Entropy-Assisted Integrated Sensing and Communication for Integrated Satellite-Terrestrial Networks

被引:0
|
作者
Wang, Xue [1 ]
Lin, Xiaojing [1 ]
Jia, Min [2 ]
机构
[1] Harbin Univ Sci & Technol, Higher Educ Key Lab Measuring & Control Technol &, Harbin 150080, Peoples R China
[2] Harbin Inst Technol, Sch Elect & Informat Engn, Harbin 150080, Peoples R China
关键词
integrated satellite-terrestrial networks; integrated sensing and communication; modulated wideband converter; spatial information entropy; signal process; PERFORMANCE; ALGORITHM;
D O I
10.3390/electronics13153082
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:17
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