Abstract
In recent years, wireless sensor network technology has continued to develop, and it has become one of the research hotspots in the information field. People have higher and higher requirements for the communication rate and network coverage of the communication network, which also makes the problems of limited wireless mobile communication network coverage and insufficient wireless resource utilization efficiency become increasingly prominent. This article is aimed at studying a support vector regression method for long‐term prediction in the context of wireless network communication and applying the method to regional economy. This article uses the contrast experiment method and the space occupancy rate algorithm, combined with the vector regression algorithm of machine learning. Research on the laws of machine learning under the premise of less sample data solves the problem of the lack of a unified framework that can be referred to in machine learning with limited samples. The experimental results show that the distance between AP1 and AP2 is 0.4 m, and the distance between AP2 and Client2 is 0.6 m. When BPSK is used for OFDM modulation, 2500 MHz is used as the USRP center frequency, and 0.5 MHz is used as the USRP bandwidth; AP1 can send data packets. The length is 100 bytes, the number of sent data packets is 100, the gain of Client2 is 0‐38, the receiving gain of AP2 is 0, and the receiving gain of AP1 is 19. The support vector regression method based on wireless network communication for regional economic mid‐ and long‐term predictions was completed well.
Highlights
The wireless sensor network (WSN) is a research field that has attracted widespread attention
The experiment uses LS-SVMlab, which is a software package suitable for the MATLAB experiment toolbox, which can be applied to different computer operating systems
When BPSK is used for OFDM modulation, 2500 MHz is used as the USRP center frequency, 0.5 MHz is used as the USRP bandwidth, and the length of the data packet that can be sent by AP1 is 100 bytes
Summary
The wireless sensor network (WSN) is a research field that has attracted widespread attention. Wireless sensor networks are widely used in daily life, military, industry, and many other fields to help people understand or master the real world more and quickly. Research on wireless sensor networks can be traced back to the 1970s. It was mainly used in the field of military research by the United States. My country has strongly supported the research of wireless sensor networks. The “National Science and Technology Medium and Long-term Development Plan” includes “intelligent technology” and “network self-organizing technology” related to wireless sensor network research
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