CN104767577A - Signal detecting method based on oversampling - Google Patents

Abstract

The invention discloses a signal detecting method based on oversampling. The problem that an existing detection algorithm is poor in detection performance is mainly solved. The method includes the following implementation steps that 1, communication signals are oversampled; 2, bias processing different in time is carried out on the oversampled samples, and processing results are weighted and fused to obtain the detection statistics amount of the method; 3, the detection statistics amount is compared with a preset threshold to judge whether a target signal exists or not. Under the condition of the same prior information, the signal detecting method can use related information of the communication signals better and has higher detection performance.

Description

A kind of signal detecting method based on over-sampling

Technical field

The invention belongs to communication technical field, relate to signal detecting method, particularly a kind of signal detecting method based on over-sampling, can be used for the frequency spectrum perception in cognitive radio system.

Background technology

At present, the emphasis of radio communication needs the service of wider bandwidth and higher download speed to shift to wireless Internet, multimedia communication etc.From mobile phone to wireless Internet, people expect that can obtain reliable broadband network whenever and wherever possible connects.But due to the restriction of the condition such as antenna size and power, the frequency range making it possible to effectively utilize is very limited.Therefore, the frequency spectrum resource as a kind of non-renewable resources becomes scarce resource, and frequency spectrum resource becomes more and more nervous.

In order to alleviate the problem of frequency spectrum resource anxiety, improve the utilization ratio of frequency spectrum, the people such as J.MITOLA propose the concept of cognitive radio.Its main thought realizes cognitive user (unauthorized user) primary user's (authorized user) not to be produced to share spectrum resources under the prerequisite of harmful interference.Frequency spectrum perception is one of key technology in cognitive radio, and the key of frequency spectrum perception is the detection of echo signal.

In order to improve detection perform, the method for at present conventional frequency spectrum perception mainly contains matched filter detections, energy measuring, cyclo-stationary detection, detection based on covariance, compressed sensing and cooperative detection.Some prior informations of said method needs more or less, wherein energy measuring is because complexity is low and it is simple to realize and extensive use.But in the wireless communication system of reality, general cognitive user does not know the prior information that primary user transmits, more therefore utilize that the signal detecting method of correlation information and second-order statistic is corresponding to be suggested.But these signal detecting methods do not effectively utilize the different correlation informations of sample, thus detection perform is undesirable.

Summary of the invention

The object of the invention is to overcome above-mentioned the deficiencies in the prior art, a kind of signal detecting method based on over-sampling is proposed, to solve the problem that perceptual performance is poor when signal to noise ratio is lower, in low signal-to-noise ratio situation, also can obtain high detection probability, thus improve overall detection perform.

In order to complete above-mentioned purpose, a kind of signal detecting method based on over-sampling of the present invention, comprises the steps:

(1) use carries out N point over-sampling to received signal much larger than the sample frequency of twice sampled signal bandwidth, obtains sample sequence;

(2), after cyclic shift being carried out to the sample sequence of above-mentioned acquisition, relevant information R is calculated _δ;

(3) according to the relevant information R of above-mentioned acquisition _δ, calculate the first weight A of different relevant information _δ, the second weight B _δ;

(4) according to the weight calculation detection statistic T of the different relevant informations of above-mentioned acquisition:

(4.1) according to the relevant information R of above-mentioned acquisition _δand weight, obtain the statistic T only using single relevant information _δ:

(4.2) only use the statistic of single relevant information to merge above-mentioned gained, obtain detection statistic T:

(5) given detection threshold ε >0, when detection statistic T is greater than detection threshold ε, then judges that echo signal exists, and when detection statistic T is less than detection threshold ε, then judges that echo signal does not exist.

The present invention has the following advantages:

The present invention, by the weighting of sample sequence relevant information, fusion, obtains detection statistic, takes full advantage of the correlation information that sample is different, compared with conventional method, when identical prior information, have better detection perform.

Accompanying drawing explanation

Fig. 1 is the flow chart of a kind of signal detecting method based on over-sampling of the present invention;

Fig. 2 is the performance simulation figure of a kind of signal detecting method based on over-sampling of the present invention.

Embodiment

With reference to Fig. 1, performing step of the present invention is as follows:

Step 1. uses the sample frequency much larger than twice sampled signal bandwidth to carry out N point over-sampling to received signal, obtains sample sequence;

Make y=[y [1], y [2] ..., y [N]] ^trepresent the sample vector after Received signal strength over-sampling, N represents sampling number, y [1], y [2] ..., y [N] represents the 1st, 2 ... N number of sampled point, [] ^trepresent the transposition of vector, under different assumed condition, the following formula of the n-th sampled point represents:

H ₀:y[n]＝w[n]

H ₁:y[n]＝s[n]+w[n] [1]

In formula [1], H ₀represent the supposed situation of only noise signal being carried out to over-sampling, H ₁represent the supposed situation of simultaneously targeted customer's signal and noise signal being carried out to over-sampling, y [n] represents that Received signal strength is through the n-th sampled point of over-sampling under different supposed situation, w [n] represents n-th sampled point of noise signal through over-sampling, and s [n] represents n-th sampled point of targeted customer's signal through over-sampling.

After step 2. carries out cyclic shift to the sample sequence of above-mentioned acquisition, calculate relevant information R _δ;

Relevant information R is calculated with original sample by following formula after cyclic shift is carried out to the sample sequence of above-mentioned acquisition _δ:

R _δ＝y ^HS(y,δ) [2]

In formula [2], y represents the sample vector after over-sampling, y ^hrepresent the conjugate transpose of sample vector y, S (y, δ) represents the vector behind sample vector ring shift right δ position, δ ∈ 0,1 ..., N}, N represent sampling number;

Step 3. is according to the relevant information R of above-mentioned acquisition _δ, calculate the first weight A of different relevant information _δ, the second weight B _δ;

(3.1) according to the relevant information R obtained in (2) _δ, calculate the first weight parameter of different relevant information second weight parameter according to following formulae discovery:

$\begin{array}{c}{\hat{u}}_{\mathrm{\δ},1}=N\frac{N_s-\mathrm{\δ}}{N_s}{\mathrm{\σ}}_s^2\\ {\widehat{\mathrm{\σ}}}_{\mathrm{\δ},1}^2=N^2[{\left(\frac{N_s-\mathrm{\δ}}{N_s}\right)}^2+\frac{2{\mathrm{\δ}}^2}{N{N}_s}]{\mathrm{\σ}}_s^2+N{\mathrm{\σ}}_w^4+2N{\mathrm{\σ}}_s^2{\mathrm{\σ}}_w^2\end{array}---\left[3\right]$

In formula [3], represent the first weight parameter, represent the second weight parameter, N represents sampling number, N _srepresent over-sampling rate, represent signal power, represent noise power;

(3.2) according to the weight parameter of above-mentioned acquisition, the first weight A of different relevant information is calculated _δwith the second weight B _δ, according to following formulae discovery:

$\begin{array}{c}{A}_{\mathrm{\δ}}=\frac{{\widehat{\mathrm{\σ}}}_{\mathrm{\δ},1}^2}{{\mathrm{\σ}}_{\mathrm{\δ},0}^2}\\ B_{\mathrm{\δ}}={\hat{u}}_{\mathrm{\δ},1}\end{array}---\left[4\right]$

In formula [4], A _δrepresent the first weight, B _δrepresent the second weight, represent the second weight parameter, represent noise power, represent the first weight parameter.

Step 4. is according to the weight calculation detection statistic T of the different relevant informations of above-mentioned acquisition;

(4.1) according to the relevant information R of above-mentioned acquisition _δand weight, calculate the statistic T only using single relevant information _δ:

T _δ＝(A _δR _δ+B _δ)(A _δR _δ+B _δ) ^*[5]

In formula [5], T _δrepresent the statistic only using single relevant information, A _δrepresent the first weight, B _δrepresent the second weight, R _δrepresent relevant information, () ^*the conjugate transpose of representing matrix;

(4.2) only use the statistic of single relevant information to merge above-mentioned gained, obtain detection statistic T:

$T=\underset{\mathrm{\δ}=1}{\overset{N_s-1}{\mathrm{\Σ}}}{T}_{\mathrm{\δ}}---\left[6\right]$

In formula [6], T represents detection statistic, and δ represents the figure place of ring shift right, N _srepresent over-sampling rate, T _δrepresent the statistic only using single relevant information;

The given detection threshold ε >0 of step 5., when detection statistic T is greater than detection threshold ε, then judges that echo signal exists, and when detection statistic T is less than detection threshold ε, then judges that echo signal does not exist.

In order to verify the performance of a kind of signal detecting method based on over-sampling that we propose, we adopt detection probability and false alarm probability to carry out its detection perform of quantitative analysis.

From law of great number, only use the statistic T of single relevant information _δbe approximately Gaussian Profile, and detection statistic T is T _δlinear set, then T is also Gaussian distributed, and therefore, we can obtain false alarm probability and detection probability is respectively:

$\begin{array}{c}P(T>\mathrm{\ϵ}|H_0)\≈Q\left(\frac{\sqrt{2\mathrm{\ϵ}}-\sqrt{2C_0}}{\sqrt{N_s-1}{\mathrm{\σ}}_{\mathrm{1,0}}}\right)\\ P(T>\mathrm{\ϵ}|H_1)\≈Q\left(\frac{\sqrt{2\mathrm{\ϵ}}-\sqrt{2C_1}}{\sqrt{{\mathrm{\Σ}}_{k,j}{\mathrm{\Γ}}_1[k,j]}}\right)\end{array}---\left[7\right]$

Wherein,

$\begin{array}{c}{C}_0=\underset{\mathrm{\δ}=1}{\overset{N_s-1}{\mathrm{\Σ}}}{\hat{u}}_{\mathrm{\δ},1}/(\frac{{\widehat{\mathrm{\σ}}}_{\mathrm{\δ},1}^2}{{\mathrm{\σ}}_{\mathrm{\δ},0}^2}-1)\\ C_1=\underset{\mathrm{\δ}=1}{\overset{N_s-1}{\mathrm{\Σ}}}({\hat{u}}_{\mathrm{\δ},1}+{\hat{u}}_{\mathrm{\δ},1}/(\frac{{\widehat{\mathrm{\σ}}}_{\mathrm{\δ},1}^2}{{\mathrm{\σ}}_{\mathrm{\δ},0}^2}-1))\\ {\mathrm{\Γ}}_1[k,j]=\left\{\begin{array}{c}\frac{N{k}^2}{N_s}{\mathrm{\ξ}}^2{\mathrm{\σ}}_s^4+N{\mathrm{\σ}}_w^4+2\mathrm{N\ξ}{\mathrm{\σ}}_s^2{\mathrm{\σ}}_w^2,k=j\\ \frac{N{k}^2}{N_s}{\mathrm{\ξ}}^2{\mathrm{\σ}}_s^4+\frac{2N(N_s-|k-j\left|\right)}{N_s}\mathrm{\ξ}{\mathrm{\σ}}_s^2{\mathrm{\σ}}_w^2,k\≠j\end{array}\right.\end{array}---\left[8\right]$

In formula [7] [8], and P (T > ε | H ₀) represent false alarm probability, and P (T > ε | H ₁) representing detection probability, Q () represents standardized normal distribution Q function, and ε represents detection threshold, N _srepresent over-sampling rate, Γ ₁[] represents auto-correlation function, and k represents Γ ₁first parameter of [] function, j represents Γ ₁second parameter of [] function, represent the first weight parameter, represent the second weight parameter, δ represents the figure place of ring shift right, represent signal power, represent noise power, ξ represents the Rayleigh fading factor of obeys index distribution.

Effect of the present invention can be further illustrated by following emulation:

A, simulated conditions

Sample frequency is 10MHz, and character rate is 1MHz, and signal to noise ratio snr (dB) is-15dB, adopts 8PSK modulation, has carried out the emulation of 1000 times.

B, emulation content

ED representative adopts energy detection algorithm to calculate relevant false dismissal probability P _dwith false alarm probability P _f, Pro1 and Pro2 represents the present invention, the performance curve obtained during (4.2) operation during Pro1 representative do not carry out step 4, and Pro2 represents the performance curve having carried out obtaining after (4.2) operation in step 4; δ=Isosorbide-5-Nitrae, 8,9,10,11, Pro1 represents sample sequence ring shift right Isosorbide-5-Nitrae respectively, 8,9,10,11, utilizes the performance curve of the detection statistic of single relevant information; Σ, Pro2 representative utilizes the performance curve of the detection statistic of different relevant information, and simulation analysis contrasts based on the signal detecting method of over-sampling and relevant information weighting and energy measuring method detection perform, and simulation performance is as Fig. 2.

C, simulation result

As seen from Figure 2, the performance curve of energy measuring method ED is in Pro2 and δ=1, and the below of Pro1 performance curve, the performance curve in Pro2 situation is the upper limit that various detection method obtains performance curve, at false alarm probability P _fmaximum detection probability P can be obtained when certain _d, δ=1, Pro1 only utilize single relevant information curve and Pro2 curve the most close, therefore detection perform is also relatively better, and the two signal detection performance is all better than the detection perform of energy detection algorithm.

Comprehensive above-mentioned simulation result and analysis, a kind of signal detecting method based on over-sampling proposed by the invention is by obtaining detection statistic to relevant information weighting, fusion, make full use of the correlation of sample, effectively avoid signal to noise ratio uncertain time impact, compared with energy measuring method, when equal prior probability, improve signal detection performance.

Claims (3)

1., based on a signal detecting method for over-sampling, comprise the steps:

(1) use carries out N point over-sampling to received signal much larger than the sample frequency of twice sampled signal bandwidth, obtains sample sequence;

(2), after cyclic shift being carried out to the sample sequence of above-mentioned acquisition, relevant information R is calculated _δ;

(3) according to the relevant information R of above-mentioned acquisition _δ, calculate the first weight A of different relevant information _δ, the second weight B _δ;

(4) according to the weight calculation detection statistic T of the different relevant informations of above-mentioned acquisition:

(4.1) according to the relevant information R of above-mentioned acquisition _δand weight, calculate the statistic T only using single relevant information _δ:

T _δ＝(A _δR _δ+B _δ)(A _δR _δ+B _δ) ^*

Wherein, T _δrepresent the statistic only using single relevant information, A _δrepresent the first weight, B _δrepresent the second weight, R _δrepresent relevant information, () ^*the conjugate transpose of representing matrix;

(4.2) only use the statistic of single relevant information to merge above-mentioned gained, obtain detection statistic T:

Wherein, T represents detection statistic, and δ represents the figure place of ring shift right, N _srepresent over-sampling rate, T _δrepresent the statistic only using single relevant information;

(5) given detection threshold ε >0, when detection statistic T is greater than detection threshold ε, then judges that echo signal exists, and when detection statistic T is less than detection threshold ε, then judges that echo signal does not exist.

2. a kind of signal detecting method based on over-sampling according to right 1, is characterized in that, in described step (2), calculates relevant information R _δ, according to following formulae discovery:

R _δ＝y ^HS(y,δ)

Wherein, y represents the sample vector after over-sampling, y ^hrepresent the conjugate transpose of sample vector y, S (y, δ) represents the vector after sample vector ring shift right position δ, δ ∈ 0,1 ..., N}, N represent sampling number.

3. a kind of signal detecting method based on over-sampling according to right 1, is characterized in that, according to relevant information R described in described step (3) _δ, calculate the weight A of different relevant information _δ, B _δ, carry out in accordance with the following steps:

(3a) according to the relevant information R obtained in (2) _δ, calculate the first weight parameter of different relevant information second weight parameter according to following formulae discovery:

Wherein, represent the first weight parameter, represent the second weight parameter, N represents sampling number, N _srepresent over-sampling rate, represent signal power, represent noise power;

(3b) according to the weight parameter of above-mentioned acquisition, the first weight A of different relevant information is calculated _δwith the second weight B _δ, according to following formulae discovery:

Wherein, A _δrepresent the first weight, B _δrepresent the second weight, represent the second weight parameter, represent noise power, represent the first weight parameter.