Lora signal monitoring system and method for multi-node software radio platform

Abstract

The invention discloses a Lora signal monitoring system and method for a multi-node software radio platform. The Lora signal monitoring system comprises a Lora signal monitoring part and a data fusioncenter part; the Lora signal monitoring part comprises a plurality of Lora signal monitoring nodes, and each Lora signal monitoring node comprises a radio frequency front-end processing module, a software radio platform hardware processing module, a signal data processing module and a monitoring node upper computer software module; and the data fusion center part comprises a cloud server module and a user application software module. A radio frequency front end is used for preprocessing the wireless signals, an energy detection and convolutional neural network modulation recognition algorithmis used for recognizing the LoRa signals, and the multi-node monitoring is deployed to upload the data to a data fusion center to judge whether the LoRa signals exist or not and estimate the parameters. According to the invention, the identification and parameter estimation can be carried out on the LoRa signal with the unknown frequency point information, and the probability of the LoRa signal detection is improved.

Description

technical field [0001] The present invention relates to the technical field of communication, and further relates to a monitoring system and method for a long-distance wide-area Lora (Long-Range) signal based on a multi-node software radio platform in the technical field of wireless communication. Under the condition of ensuring the detection performance, the present invention detects and identifies the Lora signal on the software radio platform, and estimates the parameter information such as the center frequency and bandwidth of the signal, and implements multi-node cooperative detection to improve the detection probability, thereby completing the monitoring of the Lora signal . Background technique [0002] Lora is an emerging communication technology for the Internet of Things. It is widely used in factories, factories, mines, farms and other places because of its long transmission distance and low power consumption. With the continuous expansion of its application field...

AI Technical Summary

Problems solved by technology

The shortcomings of this test system are: the test system uses MCU (micro control unit) to drive the Lora module for testing, and the processing speed of MCU (micro control unit) is not high, resulting in the inability to quickly detect the Lora signal

The disadvantage of this method is: since this method uses the method of detecting known frequency points to detect LoRa signals, parameter information such as frequency must be configured when performing LoRa signal testing, resulting in this method can only detect known frequency point information Whether there is a LoRa signal on a single fixed frequency point, it is impossible to detect a LoRa signal with unknown frequency point information in a certain frequency band

The steps of the method are to use Field-Programmable Gate Array FPGA (Field-Programmable Gate Array) to carry out data communication and logical control of multiple Lora modules, to realize the function of parallel data acquisition and transmission, after the data is aggregated into the FPGA, the FPGA then The parallel data is sent to the microcontroller through the high-speed serial interface for processing. After the microcontroller receives the data, it analyzes the data and judges the information of a certain channel. The disadvantage of this method is: because this method uses multiple LoRa modules For channel detection, this method can only detect whether there are LoRa signals on multiple fixed-frequency points with known multi-frequency point information, and cannot detect LoRa signals with unknown frequency point information, and the detection probability is greatly affected by the deployment position of the monitoring device , the probability of LoRa signal detection is low

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