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Time-frequency spectrum sensing method based on limited innovation rate

A time-spectrum and innovation rate technology, applied in the field of time-spectrum sensing based on limited innovation rate, which can solve the problems of high algorithm complexity and large number of samples.

Active Publication Date: 2020-03-31
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0010] Aiming at the problems that the existing broadband signal spectrum sensing technology requires a large number of samples and high algorithm complexity, a time-spectrum sensing method based on finite innovation rate is proposed

Method used

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  • Time-frequency spectrum sensing method based on limited innovation rate
  • Time-frequency spectrum sensing method based on limited innovation rate
  • Time-frequency spectrum sensing method based on limited innovation rate

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Embodiment Construction

[0063] The present invention will be further described below in conjunction with the accompanying drawings.

[0064] refer to Figure 1 to Figure 5 , the specific steps of a time-spectrum sensing method based on a finite innovation rate are as follows:

[0065] Step 1: Model the time-frequency spectrum of the received signal. In actual communication, it is common that the time-frequency spectrum of the received signal x(t) appears as several independent two-dimensional time-frequency pulses, such as figure 1 Shown is a typical time-spectrum diagram. After short-time Fourier transform STFT of the received signal x(t), it is modeled as:

[0066]

[0067] Among them, K represents the number of pulses in the frequency spectrum at X(t,f), h l (t, f) two-dimensional time-frequency pulse waveform function, Indicates 3K unknown parameters: c k is the Fourier coefficient, t k is the delay parameter of the time window, f k is the frequency shift parameter;

[0068] Step 2, ap...

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Abstract

A time-frequency spectrum sensing method based on a finite innovation rate (FRI) comprises the following steps: firstly, modeling a received main user signal into a two-dimensional time-frequency domain FRI signal after time-frequency conversion; then, performing frequency mixing and filtering processing on the two-dimensional time-frequency FRI signal under an FRI sampling framework, and performing uniform sampling on the two-dimensional time-frequency FRI signal at an extremely low sampling rate to obtain a small amount of coefficients of secondary Fourier transform; and finally, reconstructing the time-frequency spectrum information of the original signal from the obtained few Fourier coefficients by using a zero filter. According to the method, unknown parameters of the Lorentz pulse are estimated from a small number of Fourier coefficients, so that the time-frequency spectrum information of the original signal is recovered.

Description

technical field [0001] The invention relates to the field of communication signal processing, in particular to a time-spectrum sensing method based on a limited innovation rate. Background technique [0002] Spectrum sensing is a process of detecting the utilization of radio spectrum resources in a cognitive radio network to obtain the spectrum information of the primary user signal, which is a key technology in cognitive radio. Most of the current spectrum sensing systems are designed and implemented based on the Nyquist sampling theorem. According to the Nyquist sampling theorem, in order to fully reconstruct an analog signal from sampled samples, the sampling rate must be greater than or equal to twice the signal bandwidth. With the development of modern communication technology, the bandwidth of radio signals has gradually increased, and the pressure on sampling equipment has also increased. At the same time, high-speed sampling will inevitably generate a large amount ...

Claims

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Application Information

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IPC IPC(8): H04W16/10
CPCH04W16/10Y02D30/70
Inventor 黄国兴杨泽铭陈林林卢为党彭宏
Owner ZHEJIANG UNIV OF TECH