Spectrum detection method based on mtm-svd adaptive sensor number

A spectrum detection and sensor technology, applied in transmission monitoring, transmission systems, electrical components, etc., can solve the problems that the number of sensors in the cognitive radio system is not mentioned, and has not been studied, so as to achieve fast algorithm speed and reduce complexity , the effect of accurate detection

Inactive Publication Date: 2014-10-08
SHANGHAI NORMAL UNIVERSITY
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Problems solved by technology

[0005] Although the MTM-SVD-based method is currently being studied to increase the number M of sensors to improve the accuracy of spectrum detection, the ability to resist interference and multipath effects, there is no research on how much M should be taken in the actual environment, and no provision has been made. to the number of sensors required in a cognitive radio system

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  • Spectrum detection method based on mtm-svd adaptive sensor number
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  • Spectrum detection method based on mtm-svd adaptive sensor number

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[0027] Below in conjunction with accompanying drawing and embodiment the present invention will be further described

[0028] The specific design steps of the spectrum detection method based on the number of MTM-SVD adaptive sensors are as follows:

[0029] 1. to x m (t) is sampled, assuming x m (t) is the continuous time signal received by the mth sensor, with the sampling rate as f s The sampling time is T s =1 / f s , then the discrete signal received on the mth sensor is y m (n)=x m (nT s ); n=0, 1, ..., N; v (k) (n) is a K-order Slepian sequence (DPSS) (n=0, 1, ..., N-1; k = 1, 2, ..., K), and γ represents the variance ratio of the primary user signal to noise.

[0030] 2. Calculate the number of sensors required M = ψ ′ ( K ) ln ( 1 ...

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Abstract

The invention discloses a spectrum detection method based on the number of MTM-SVD adaptive sensor, and relates to the technical field of cognitive radio spectrum detection method. The MTM-SVD spectrum detection technology has the advantages that the prior information of a primary user is not needed, the detection and the reconstruction of signals submerged in colour noises are processed effectively, algorithm velocity is fast and the like, so the method of the invention can derive a threshold formula according to Neyman-Pearson standard based on MTM-SVD algorithm and determine the optimal number of real needed sensors. The receiving signals on each sensor are sampled, the characteristic spectrum of each sampled signal is calculated, and a new judgment amount TM(fi) is calculated according to the obtained characteristic spectrum; the new judgment amount TM(fi) is compared with a threshold th satisfying a false-alarm probability Pf to judge whether the spectrum is occupied or not. Compared with traditional energy detection, the method of the invention reduces the complexity of system while detecting the signal of the primary user correctively.

Description

technical field [0001] The invention relates to the technical field of cognitive radio spectrum detection methods, in particular to a broadband spectrum detection method based on the number of MTM-SVD adaptive sensors in a cognitive radio system. Background technique [0002] The rapidly growing demand for broadband wireless services puts forward higher requirements for wireless networks. Factors such as environmental changes, demand differences, technological progress, business growth, and investment protection have created a situation where many heterogeneous wireless network subsystems coexist, which poses a threat to network development. And construction brings great difficulties, and can not meet the growing application needs of users; at the same time, there are common problems in the wireless network, such as static management of resources, fragmented use, etc., the distribution of available resources is highly uneven, resource shortage and waste coexist, and use metho...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B17/00H04B17/382
Inventor 黄立辉李莉
Owner SHANGHAI NORMAL UNIVERSITY
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