Research on Signal Detection and System Recognition Techniques in Private Internet of Things

P-IoT is an IoT transmission system proposed for users in the private network industry, which has the advantages of high reliability, high security and strong coverage capability compared with the existing IoT system, it has great application potential. However, there is a amount of unused spectrum in sub-1GHz private network band now. How P-IoT can exploit the spectrum holes has become a hot research issue. In order to improve the utilization rate of spectrum resources, P-IoT can obtain the information about whether the spectrum is be used, and about network system which is using the frequency band through signal detection and system recognition. This can provide supports for P-IoT to formulate the utilization strategy of idle spectrum. In this paper, signal detection and system recognition technology of P-IoT are studied. This paper selects energy detection to detect narrowband private network signals and recognize the broad/narrowband private network signals. Taking the modulation modes of TETRA, PDT and dPMR as the classification objects, this paper also implements system recognition algorithms including binary trees and neural network classifiers, and further compares and analyzes the proposed algorithms. The simulation results show that the proposed recognition methods for P-IoT can effectively recognize the three private network signals. The results of this paper provide reference and support for the subsequent works that utilize unused spectrum, such as spectrum allocation and spectrum collaboration.