CN103248443B - Method for sensing OFDM spectrum under conditions of time asynchronization and known cyclic prefix length - Google Patents

Abstract

The invention discloses a method for sensing an OFDM (Orthogonal Frequency Division Multiplexing) spectrum under conditions of time asynchronization and known cyclic prefix length. The processing procedure of the method comprises the following steps: at first, sampling a receipt signal from a monitoring channel to obtain a sampled signal; then, computing an autocorrelation function of the sampled signal according to the sampled value in the sampled signal; next, computing test statistic according to an autocorrelation coefficient in the autocorrelation function of the sampled signal under the condition of time asynchronization; and at last, judging whether the monitoring channel is in the idle state or not according to the test statistic and the judgment threshold. The method has the advantages that the spectrum sensing can be carried out by directly using the sampled signal, without the need of time synchronization, so that the computation complexity is reduced effectively. During the process of computing the test statistic, due to the use of the nonnegative characteristic of the autocorrelation coefficient corresponding to the cyclic premix part of the OFDM signal in the autocorrelation function of the sampled signal, the spectrum sensing performance of the OFDM signal is improved effectively.

Description

Time asynchronous and OFDM frequency spectrum sensing method under circulating prefix-length known case

Technical field

The present invention relates to the frequency spectrum perception technology in a kind of cognitive radio system, especially relate to asynchronous and OFDM frequency spectrum sensing method under circulating prefix-length known case of a kind of time.

Background technology

Along with the fast development of various radio communication service, importance and the scarcity of frequency spectrum resource highlight day by day.Large quantifier elimination shows, current spectrum shortage present situation is not due to frequency resource deficiency physically, and mainly because fixed frequency spectrum allocation manager mechanism causes that the availability of frequency spectrum is low to be caused.Cognitive radio is attempted by improving the availability of frequency spectrum just, and the problem inherently solving the resource of radio communication more and more in short supply proposes.It can communication environment around real-time perception, identify available idle channel, then adjust the system parameters of cognition wireless network according to frequency spectrum perception result adaptively, make cognitive radio system have intelligent identification and change the ability that frequency spectrum uses chance.In order to prevent producing interference to existing communication system, cognitive radio system effectively reliably must can identify idle channel, and therefore frequency spectrum perception is one of key technology in cognitive radio.

OFDM (Orthogonal frequency division multiplexing, OFDM) technology has availability of frequency spectrum high, and this technology is current and that future, wireless communication standard was widely adopted technology.Therefore the frequency spectrum perception (namely judging whether there is ofdm signal in channel) of ofdm signal is had very important significance.The existing frequency spectrum sensing method for ofdm signal mainly can be divided into frequency domain detection method and tim e-domain detection method two class.Wherein, frequency domain detection method needs the frequency spectrum calculating collection signal, therefore has larger amount of calculation; Tim e-domain detection method mainly utilizes the autocorrelation performance of Cyclic Prefix in ofdm signal to realize frequency spectrum perception.The people such as Chaudhari proposed the autocorrelation performance utilizing Cyclic Prefix in 2009 in " based on the distributed Sequential Detection of autocorrelative ofdm signal in Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios(cognitive radio) ", realize frequency spectrum perception by the auto-correlation function calculating Received signal strength, but the method does not consider the non-stationary property of auto-correlation function.For this problem, the people such as Axell proposed a kind of frequency spectrum sensing method of the auto-correlation function based on Received signal strength newly in " OFDM during the known and unknown noise variance of Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance(optimum and suboptimum frequency spectrum sensing method) " in 2011, compared with the method that the method and the people such as Chaudhari propose, the method has more excellent detection perform, but the method requires time synchronized.

Summary of the invention

Technical problem to be solved by this invention is to provide asynchronous and OFDM frequency spectrum sensing method under circulating prefix-length known case of a kind of time, and it can improve the frequency spectrum perception performance of ofdm signal effectively, and computation complexity is low.

The present invention solves the problems of the technologies described above adopted technical scheme: asynchronous and OFDM frequency spectrum sensing method under circulating prefix-length known case of a kind of time, it is characterized in that its processing procedure is: first, Received signal strength from supervisory channel is sampled, obtains sampled signal; Then, according to the sampled value in sampled signal, the auto-correlation function of calculating sampling signal; Then, under time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, test statistics is calculated; Finally, according to the size of test statistics and decision threshold, judge whether supervisory channel is in idle condition.

It specifically comprises the following steps:

1. utilize the sampling module in cognitive radio system to carry out M sampling to the Received signal strength from supervisory channel, obtain the sampled signal be made up of the sampled value of M sampled point, wherein, M=K × (N _c+ N _d)+N _d, K represents any positive integer, N _crepresent the length of the Cyclic Prefix of ofdm signal, N _drepresent the number of the subcarrier of ofdm signal;

2. according to the sampled value in sampled signal, the auto-correlation function of calculating sampling signal, is designated as ρ (t) by t auto-correlation coefficient in the auto-correlation function of sampled signal, $\mathrm{\ρ}\left(t\right)=\frac{\frac{1}{K}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}x((k-1)\×(N_c+N_d)+t)x((k-1)\×(N_c+N_d)+N_d+t)}{\frac{1}{M}\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{x}^2\left(m\right)},$ Wherein, the number of the auto-correlation coefficient in the auto-correlation function of sampled signal is N _c+ N _d, t is positive integer, and 1≤t≤N _c+ N _d, k is positive integer, and 1≤k≤K, x ((k-1) × (N _c+ N _d)+t) represent ((k-1) × (N in sampled signal _c+ N _d)+t) individual sampled value, x ((k-1) × (N _c+ N _d)+N _d+ t) represent ((k-1) × (N in sampled signal _c+ N _d)+N _d+ t) individual sampled value, m is positive integer, and 1≤m≤M, x (m) represents m sampled value in sampled signal;

3. under time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics, be designated as T, $T=\frac{1}{N_c+N_d}\underset{t=1}{\overset{N_c+N_d}{\mathrm{\Σ}}}\mathrm{\ρ}\left(t\right)\×\left|\mathrm{\ρ}\left(t\right)\right|,$ Wherein, symbol " || " is the symbol that takes absolute value;

4. test statistics T and decision threshold λ is compared, if T is greater than λ, then judge that supervisory channel is in busy condition, if T is less than or equal to λ, then judge that supervisory channel is in idle condition, wherein, λ=[F ^-1(P _f)] ², P _frepresent false alarm probability, span is 0<P _f<0.5, F ^-1() is the inverse function of F (),

$F\left(\mathrm{\&lambda;}\right)=\frac{\sqrt{K(N_c+N_d)}}{\sqrt{\mathrm{\&pi;}}}{\&Integral;}_{\mathrm{\&lambda;}}^{+\&infin;}{e}^{-K(N_c+N_d)y^2}\mathrm{dy},$ E is nature radix, e=2.71828 ..., y is variable.

Compared with prior art, the invention has the advantages that:

1) the inventive method is not owing to needing time synchronized, directly utilizes sampled signal to carry out frequency spectrum perception, therefore significantly reduces computation complexity.

2) the inventive method is in the process calculating test statistics, due to make use of sampled signal auto-correlation function in the non-negative characteristic that has of the auto-correlation coefficient corresponding with the Cyclic Prefix part of ofdm signal, therefore effectively improve the frequency spectrum perception performance of ofdm signal.

Accompanying drawing explanation

Fig. 1 is the FB(flow block) of frequency spectrum sensing method of the present invention;

The frequency spectrum sensing method that the people such as Fig. 2 is under different state of signal-to-noise, Axell propose compares schematic diagram with the detection probability of the inventive method.

Embodiment

Below in conjunction with accompanying drawing embodiment, the present invention is described in further detail.

Asynchronous and OFDM frequency spectrum sensing method under circulating prefix-length known case of a kind of time that the present invention proposes, as shown in Figure 1, its main processes is its FB(flow block): first, samples, obtain sampled signal to the Received signal strength from supervisory channel; Then, according to the sampled value in sampled signal, the auto-correlation function of calculating sampling signal; Then, under time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, test statistics is calculated; Finally, according to the size of test statistics and decision threshold, judge whether supervisory channel is in idle condition.

Ofdm signal frequency spectrum sensing method of the present invention, it specifically comprises the following steps:

1. utilize the sampling module in cognitive radio system to carry out M sampling to the Received signal strength from supervisory channel, obtain the sampled signal be made up of the sampled value of M sampled point, wherein, M=K × (N _c+ N _d)+N _d, K represents any positive integer, as got K=10, and N _crepresent the length of the Cyclic Prefix of ofdm signal, N _drepresent the number of the subcarrier of ofdm signal.

2. according to the sampled value in sampled signal, the auto-correlation function of calculating sampling signal, is designated as ρ (t) by t auto-correlation coefficient in the auto-correlation function of sampled signal, $\mathrm{\&rho;}\left(t\right)=\frac{\frac{1}{K}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}x((k-1)\&times;(N_c+N_d)+t)x((k-1)\&times;(N_c+N_d)+N_d+t)}{\frac{1}{M}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}^2\left(m\right)},$ Wherein, the number of the auto-correlation coefficient in the auto-correlation function of sampled signal is N _c+ N _d, t is positive integer, and 1≤t≤N _c+ N _d, k is positive integer, and 1≤k≤K, x ((k-1) × (N _c+ N _d)+t) represent ((k-1) × (N in sampled signal _c+ N _d)+t) individual sampled value, x ((k-1) × (N _c+ N _d)+N _d+ t) represent ((k-1) × (N in sampled signal _c+ N _d)+N _d+ t) individual sampled value, m is positive integer, and 1≤m≤M, x (m) represents m sampled value in sampled signal.

3. under time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics, be designated as T, $T=\frac{1}{N_c+N_d}\underset{t=1}{\overset{N_c+N_d}{\mathrm{\&Sigma;}}}\mathrm{\&rho;}\left(t\right)\&times;\left|\mathrm{\&rho;}\left(t\right)\right|,$ Wherein, symbol " || " is the symbol that takes absolute value.

4. test statistics T and decision threshold λ is compared, if T is greater than λ, then judge that supervisory channel is in busy condition, if T is less than or equal to λ, then judge that supervisory channel is in idle condition, wherein, λ=[F ^-1(P _f)] ², P _frepresent false alarm probability, span is 0<P _f<0.5, F ^-1() is the inverse function of F (), $F\left(\mathrm{\&lambda;}\right)=\frac{\sqrt{K(N_c+N_d)}}{\sqrt{\mathrm{\&pi;}}}{\&Integral;}_{\mathrm{\&lambda;}}^{+\&infin;}{e}^{-K(N_c+N_d)y^2}\mathrm{dy},$ E is nature radix, e=2.71828 ..., y is variable.

By following emulation to further illustrate feasibility and the validity of frequency spectrum sensing method of the present invention.

Suppose that the number of the subcarrier of ofdm signal is N _d=32, the length of the Cyclic Prefix of ofdm signal is N _c=8, get K=10, then total sampling number is M=432, and sets the value of false alarm probability as P according to the requirement of IEEE802.22 standard _f=0.1.The frequency spectrum sensing method that the people such as Fig. 2 gives signal to noise ratio when changing from-20dB to 5dB, Axell propose and the inventive method pass through comparing of the detection probability that 100000 Monte Carlo simulations obtain.As can be seen from Figure 2, the detection probability of the inventive method is far superior to the detection probability of the frequency spectrum sensing method that the people such as Axell propose.Analysis chart 2, when signal to noise ratio is-1dB, the detection probability of the inventive method is 0.94, reach detection probability in IEEE802.22 standard and be more than or equal to the requirement of 0.9, and the detection probability of frequency spectrum sensing method that now people such as Axell proposes can only reach 0.8, this detection probability do not reached in IEEE802.22 standard is more than or equal to the requirement of 0.9; When signal to noise ratio is 1dB, the detection probability 0.93 of the frequency spectrum sensing method that the people such as Axell propose, and now the detection probability of the inventive method is close to 1, this is enough to feasibility and validity that the inventive method is described.

Claims (1)

1. a time asynchronous and OFDM frequency spectrum sensing method under circulating prefix-length known case, is characterized in that its processing procedure is: first, sample, obtain sampled signal to the Received signal strength from supervisory channel; Then, according to the sampled value in sampled signal, the auto-correlation function of calculating sampling signal; Then, under time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, test statistics is calculated; Finally, according to the size of test statistics and decision threshold, judge whether supervisory channel is in idle condition;

This OFDM frequency spectrum sensing method specifically comprises the following steps:

1. utilize the sampling module in cognitive radio system to carry out M sampling to the Received signal strength from supervisory channel, obtain the sampled signal be made up of the sampled value of M sampled point, wherein, M=K × (N _c+ N _d)+N _d, K represents any positive integer, N _crepresent the length of the Cyclic Prefix of ofdm signal, N _drepresent the number of the subcarrier of ofdm signal;

2. according to the sampled value in sampled signal, the auto-correlation function of calculating sampling signal, is designated as ρ (t) by t auto-correlation coefficient in the auto-correlation function of sampled signal, $\mathrm{\&rho;}\left(t\right)=\frac{\frac{1}{K}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}x((k-1)\&times;(N_c+N_d)+t)x((k-1)\&times;(N_c+N_d)+N_d+t)}{\frac{1}{M}\underset{m=1}{\overset{M}{\mathrm{\&Sigma;}}}{x}^2\left(m\right)},$ Wherein, the number of the auto-correlation coefficient in the auto-correlation function of sampled signal is N _c+ N _d, t is positive integer, and 1≤t≤N _c+ N _d, k is positive integer, and 1≤k≤K, x ((k-1) × (N _c+ N _d)+t) represent ((k-1) × (N in sampled signal _c+ N _d)+t) individual sampled value, x ((k-1) × (N _c+ N _d)+N _d+ t) represent ((k-1) × (N in sampled signal _c+ N _d)+N _d+ t) individual sampled value, m is positive integer, and 1≤m≤M, x (m) represents m sampled value in sampled signal;

3. under time asynchronous condition, according to the auto-correlation coefficient in the auto-correlation function of sampled signal, calculate test statistics, be designated as T, ρ (t) × | ρ (t) |, wherein, symbol " || " is the symbol that takes absolute value;

4. test statistics T and decision threshold λ is compared, if T is greater than λ, then judge that supervisory channel is in busy condition, if T is less than or equal to λ, then judge that supervisory channel is in idle condition, wherein, λ=[F ^-1(P _f)] ², P _frepresent false alarm probability, span is 0<P _f<0.5, F ^-1() is the inverse function of F (), e is nature radix, e=2.71828 ..., y is variable.