Research on Spectrum Sensing System Based on Composite Neural Network

Abstract

Electromagnetic spectrum sensing is an important component of electromagnetic spectrum capability. With the development of spectrum sensing technology, there are still many problems and challenges in practical applications. For example, though the spectrum sensing field has diversified, the system is still based on manual operation; there are massive and diverse data, but the depth and breadth of data mining are insufficient; there is a large amount of historical data, multiple heterogeneous and unlabeled data types, and multidimensional non fusion platforms. The above difficulties hinder the construction of electromagnetic spectrum sensing ability and efficiency. Therefore, we propose a spectrum sensing system based on composite neural network architecture, the overall architecture includes three layers; spectrum sensing layer, data processing layer and situation analysis layer, which realizes the bottom data processing and high-dimensional spectrum sensing analysis. With the development of artificial intelligence technology [1], the above problems can be further improved and the development from artificial to intelligent can be realized gradually by using deep learning algorithm framework and exploring the advanced artificial intelligence technology. Finally, a three-dimensional electromagnetic situation map is formed from the time dimension, space dimension and spectrum dimension, so as to realize intelligence.