Frequency spectrum detection method based on characteristic circulation frequency in wireless medical monitoring

Abstract

The invention relates to a frequency spectrum detection method based on characteristic circulation frequency in wireless medical monitoring. In the invention, when signals are processed with limited-length cyclic spectrum treatment, only cyclic spectrum numerical value at the signal characteristic circulation frequency part is processed based on characteristic of fixed frequency points of the wireless medical system, thereby reducing processing complexity and solving low power consumption of wireless medical devices; in addition, the signal detection probability and false-alarm probability are controlled by regulating decision threshold. Based on the basic theory of cyclic spectrum detection, a limited signal length is adopted and frequency spectrum detection is conducted at the signal characteristic circulation frequency part; when the cyclic spectrum numerical value at the characteristic circulation frequency part is greater than a preset threshold value, the frequency spectrum is deemed to be occupied; and when the cyclic spectrum numerical value at the characteristic circulation frequency part is less than a preset threshold value, the frequency spectrum is deemed to be not occupied. The method improves frequency spectrum detection performance greatly, and realizes frequency spectrum detection under extra-low signal to noise ratio.

Description

technical field [0001] The invention relates to a detection method in the technical field of wireless communication, in particular to a frequency spectrum detection method based on a characteristic cycle frequency. Background technique [0002] Wireless medical monitoring refers to the real-time transmission of various physiological electrical signals detected from patients to remote receiving devices through wireless communication technology, which greatly facilitates the use of patients, making the monitoring of patients no longer limited to the front of the bed , Even at home, you can get real-time monitoring from doctors, which has become the development trend of future medical monitoring. [0003] However, in practical applications, the wireless communication technology that wireless medical monitoring relies on must face the complex situation of electromagnetic waves around the human body. The main reasons for this complex situation include but are not limited to the ...

AI Technical Summary

Problems solved by technology

The limitation of low power greatly limits the ability of the spectrum detection unit to process data, so a high-speed, low-complexity and high-performance detection method is required

Although there are many detection methods for spectrum detection, the various detection methods proposed at present do not meet the special requirements of wireless medical monitoring for spectrum detection.

[0004] After searching the existing technology, it is found that none of the existing detection schemes can meet the special needs of medical monitoring for spectrum detection, such as the US Patent No. "US 2008 / 0080604 A1", Youngsik Hur, Chang-Ho Lee et al. in their patent "SPECTRUM-SENSING ALGORITHMS AND METHODS" (Chinese name is "Spectrum Detection Algorithm and Method"), the detection is divided into two steps of rough detection and fine detection to improve detection efficiency, but its detection method is still based on Traditional energy detection does not fundamentally solve the deficiency of energy detection itself

In the patent of Chinese invention with the application number "200610020800.5", the applicant is the University of Electronic Science and Technology of China, and the invention name is "A Distributed Spectrum Detection Method Based on Reliability", a method of assigning reliability to distributed nodes is proposed. However, its single node is still based on energy detection, which fails to solve the problem that energy detection is greatly affected by noise.

Although the cyclic spectrum of the cyclostationary signal can not be affected by noise, many related papers have pointed out that the cyclic spectrum has incomparable advantages over traditional detection methods at low signal-to-noise ratios, but due to the complexity of the cyclic spectrum processing, the processing There are also high requirements for time and equipment power consumption, so the cyclic spectrum characteristics of the signal have not been applied to the actual detection system, let alone the wireless medical monitoring field

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