WO2021012859A1 - Spectrum sensing method based on symmetric peaks of cyclic autocorrelation function of modulation signal - Google Patents
Spectrum sensing method based on symmetric peaks of cyclic autocorrelation function of modulation signal Download PDFInfo
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Definitions
- the present invention relates to the field of cognitive wireless communication, in particular to a spectrum sensing method in a cognitive radio environment.
- the energy detection method is simple and does not require a priori information of the primary user signal. It judges whether the primary user signal exists according to the energy or power of the received signal, but its decision threshold is easily affected by channel noise. In low signal-to-noise ratio or The spectrum detection performance is poor in a noise fluctuating environment.
- the matched filter detection method constructs a matched filter according to the characteristics of the main user signal to achieve the best detection effect, but it requires a priori information of the main user signal, which cannot be satisfied in a general environment.
- the eigenvalue detection method performs spectrum detection based on the eigenvalues of the received signal matrix. It has good robustness to noise fluctuations, but it is complicated to calculate and requires a longer observation time to obtain the received signal matrix. The real-time performance of spectrum detection is relatively high. difference.
- the cyclic autocorrelation feature detection method detects the inherent periodicity or cyclic autocorrelation function of the modulation signal of the primary user, which can effectively eliminate the influence of noise fluctuations on the spectrum detection performance.
- how to make full use of the characteristics of the cyclic autocorrelation function of the modulation signal of the primary user in the cognitive communication network to further improve the accuracy of spectrum sensing in a low signal-to-noise ratio and noise fluctuation environment is a problem that has not been completely resolved.
- the present invention proposes a spectrum sensing method based on the symmetric peak of the cyclic autocorrelation function of the modulated signal. This method has robust spectrum detection performance in a low signal-to-noise ratio and noise fluctuation environment, and effectively solves the problem of spectrum detection in current cognitive wireless communication networks in a low signal-to-noise ratio and noise fluctuation environment.
- the present invention is based on the spectrum sensing method of the symmetric peak of the cyclic autocorrelation function of the modulated signal.
- Step 1 Set the significance level factor
- the significance level factor ⁇ is set, so that the following formula holds:
- Step 2 Calculate cyclic autocorrelation function
- ⁇ is the delay
- ⁇ is the cyclic frequency of the detection signal
- "*" represents its conjugate
- j is the imaginary unit
- Step 4 Calculate the characteristic value of the detection signal
- > ⁇ 2 + ⁇ 2 If yes, l 1, then it is determined that the primary user signal exists, otherwise the primary user signal does not exist.
- a further design of the present invention is that in step 1, the significance level factor ⁇ is set according to the cognitive network false alarm rate P fa , and the value of the significance level factor ⁇ only satisfies That is, the smaller the ⁇ , the higher the detection rate of the cognitive network.
- a further design of the present invention is that in step 2, the calculation of the cyclic autocorrelation function can also be calculated based on the sampling signal y(k) of the signal y(t) received by the cognitive user in a detection period T.
- step 3 the signal detection domain It can be the entire domain or subdomain of the cyclic autocorrelation function R ⁇ ( ⁇ ) calculated in step 2.
- step 3 the signal detection domain It is a two-dimensional Gaussian process.
- a further design of the present invention is that in step 5, the search for the symmetric peak point is in the signal detection domain On the two-dimensional space.
- a further design of the present invention is that in step 5, the symmetrical peak points can be one pair or multiple pairs.
- the method of the present invention applies the symmetric peak characteristic of the cyclic autocorrelation function of the modulation signal to the spectrum detection of the cognitive network, and uses the peak symmetry of the cyclic autocorrelation function of the primary user modulation signal to combine the primary user signal and channel noise in the detected signal.
- the significance level factor is set according to the false alarm rate of the cognitive network, which effectively balances the two spectrum detection performance indicators of the spectrum detection rate and the false alarm rate, which is beneficial to realize the global optimization of the cognitive network;
- the system structure is simple and can be applied to any kind of spectrum sensing of modulated signals.
- Fig. 1 is a schematic diagram of the cognitive network system model of the present invention.
- Fig. 2 is a flowchart of the spectrum sensing method of the present invention.
- a cognitive network includes at least one primary user and one cognitive user.
- s(t) is a binary phase modulated signal with a bit rate of 250Kbits/s and a carrier of 320MHz.
- n(t) is the channel noise, 0 ⁇ t ⁇ T, T is the spectrum detection time of the cognitive user.
- the implementation of the spectrum sensing method based on the symmetrical peak of the modulated signal cyclic autocorrelation function of the present invention includes the following steps:
- Step 2 Calculate the cyclic autocorrelation function, and calculate the cyclic autocorrelation function of the signal y(t) received by the cognitive user in a detection period T:
- ⁇ is the delay
- ⁇ is the cycle frequency of the signal
- "*" represents its conjugate
- j is the imaginary unit.
- Step 3 Construction of the signal detection domain. According to the cyclic autocorrelation function R ⁇ ( ⁇ ) obtained in Step 2, remove the function domains of R ⁇ (0) and R 0 ( ⁇ ) to construct the cognitive network signal detection domain
- Step 4 Calculate the characteristic value of the detection signal, respectively calculate the signal detection domain function For the mean and variance of the variable ⁇ set ⁇ 1 and For the mean and variance of the variable ⁇ set ⁇ 2 and
- > ⁇ 2 + ⁇ 2 holds, l 1,2, it is determined that the primary user signal exists, otherwise the primary user signal does not exist.
- a simulation test is performed on the spectrum detection method of this embodiment, and the result shows that the spectrum detection method of this case can distinguish whether the main user signal appears according to the symmetric peak value of the received signal cyclic autocorrelation function, and the spectrum detection accuracy is improved. It can be seen that, compared with the existing spectrum detection method, the embodiment of the present invention significantly improves the spectrum detection performance.
- the present invention is not only suitable for single-carrier signal sensing, but also suitable for multi-carrier signal sensing or mixed signal sensing of single-carrier signal sensing and multi-carrier signal.
- the present invention may also have other embodiments. All technical solutions formed by equivalent replacements or equivalent transformations fall within the protection scope of the present invention.
Abstract
The present invention relates to a spectrum sensing method based on symmetric peaks of a cyclic autocorrelation function of a modulation signal. A cognitive user performs cyclic autocorrelation function calculation on a received signal to accordingly form a two-dimensional signal detection domain, and finally searches for symmetric peak points in the signal detection domain to determine whether there is a main user signal, and if there are symmetric peak points in the two-dimensional signal detection domain, the cognitive user determines that there is a main user signal, otherwise, determines that there is no main user signal. In order to ensure the false alarm probability of spectrum sensing, in the present invention, a symmetric peak point significance level factor is introduced into a process of searching for the symmetric peak points. According to the method of the present invention, whether there is a main user signal is determined according to the symmetry of peaks of a cyclic autocorrelation function of a modulation signal, and no prior knowledge of any main user signal and channel is required, thereby eliminating the impact of channel noise fluctuation on the performance of spectrum sensing, and solving the problem of signal spectrum sensing in an environment with a small signal-to-noise ratio and channel noise fluctuation.
Description
本发明涉及认知无线通信领域，具体地说涉及一种认知无线电环境下的频谱感知方法。The present invention relates to the field of cognitive wireless communication, in particular to a spectrum sensing method in a cognitive radio environment.
无线通信的日益发展，特别是5G时代的到来，越来越多的无线数据传输业务需求导致了频谱资源的日渐紧张。提高频谱利用率是有效缓解频谱资源紧张的办法之一。认知无线电技术利用人工智能感知无线通信环境，动态地检测其周围的频谱资源使用信息，实时自适应地改变自身系统工作参数以有效利用空闲频谱，提高频谱利用率。With the ever-increasing development of wireless communications, especially the arrival of the 5G era, more and more wireless data transmission service requirements have led to increasingly tight spectrum resources. Improving spectrum utilization is one of the ways to effectively alleviate the shortage of spectrum resources. Cognitive radio technology uses artificial intelligence to perceive the wireless communication environment, dynamically detects the use of spectrum resources around it, and adaptively changes its own system operating parameters in real time to effectively use free spectrum and improve spectrum utilization.
认知无线网络中的频谱感知方法有多种，如能量检测、匹配滤波器检测、特征值检测和循环自相关特征检测等。能量检测方法简单，不需要主用户信号的先验信息，它根据接收信号的能量或功率大小来判断主用户信号是否存在，但它的判决门限容易受到信道噪声的影响，在低信噪比或噪声波动的环境下频谱检测性能很差。匹配滤波器检测法根据主用户信号的特征构建匹配滤波器以达到最佳检测效果，但它需要主用户信号的先验信息，这在一般环境下是无法满足的。特征值检测法根据接收信号矩阵的特征值进行频谱检测，它对噪声波动具有较好的鲁棒性，但它计算复杂，需要较长的观察时间以获取接收信号矩阵，频谱检测的实时性较差。循环自相关特征检测法根据主用户调制信号的内在周期性或循环自相关函数进行检测，可以有效消除噪声波动对频谱检测性能的影响。但是，如何充分利用认知通信网络中主用户调制信号循环自相关函数的特征进行检测，进一步提高在低信噪比和噪声波动环境下频谱感知的准确性，是一个尚未彻底解决的难题。There are a variety of spectrum sensing methods in cognitive wireless networks, such as energy detection, matched filter detection, feature value detection, and cyclic autocorrelation feature detection. The energy detection method is simple and does not require a priori information of the primary user signal. It judges whether the primary user signal exists according to the energy or power of the received signal, but its decision threshold is easily affected by channel noise. In low signal-to-noise ratio or The spectrum detection performance is poor in a noise fluctuating environment. The matched filter detection method constructs a matched filter according to the characteristics of the main user signal to achieve the best detection effect, but it requires a priori information of the main user signal, which cannot be satisfied in a general environment. The eigenvalue detection method performs spectrum detection based on the eigenvalues of the received signal matrix. It has good robustness to noise fluctuations, but it is complicated to calculate and requires a longer observation time to obtain the received signal matrix. The real-time performance of spectrum detection is relatively high. difference. The cyclic autocorrelation feature detection method detects the inherent periodicity or cyclic autocorrelation function of the modulation signal of the primary user, which can effectively eliminate the influence of noise fluctuations on the spectrum detection performance. However, how to make full use of the characteristics of the cyclic autocorrelation function of the modulation signal of the primary user in the cognitive communication network to further improve the accuracy of spectrum sensing in a low signal-to-noise ratio and noise fluctuation environment is a problem that has not been completely resolved.
发明内容Summary of the invention
为了克服上述现有技术的不足，本发明提出了一种基于调制信号循环自相关函数对称峰值的频谱感知方法。该方法在低信噪比和噪声波动的环境下具有 稳健的频谱检测性能，有效解决了当前认知无线通信网络在低信噪比和噪声波动环境下频谱检测的难题。In order to overcome the above shortcomings of the prior art, the present invention proposes a spectrum sensing method based on the symmetric peak of the cyclic autocorrelation function of the modulated signal. This method has robust spectrum detection performance in a low signal-to-noise ratio and noise fluctuation environment, and effectively solves the problem of spectrum detection in current cognitive wireless communication networks in a low signal-to-noise ratio and noise fluctuation environment.
为了达到上述目的，本发明基于调制信号循环自相关函数对称峰值的频谱感知方法，所述认知网络中至少包括1个主用户和1个认知用户，认知用户接收到的检测信号为y(t)＝s(t)+n(t)，其中，s(t)为主用户传输的信号，n(t)为信道噪声，0≤t≤T，T为认知用户频谱检测时间，其特征在于所述频谱感知方法包括如下步骤：In order to achieve the above objective, the present invention is based on the spectrum sensing method of the symmetric peak of the cyclic autocorrelation function of the modulated signal. The cognitive network includes at least one primary user and one cognitive user, and the detection signal received by the cognitive user is y (t)=s(t)+n(t), where s(t) is the signal transmitted by the main user, n(t) is the channel noise, 0≤t≤T, and T is the cognitive user spectrum detection time, It is characterized in that the spectrum sensing method includes the following steps:
步骤1、设置显著性水平因子Step 1. Set the significance level factor
根据认知网络虚警率P
fa要求设置显著性水平因子β，使得下式成立：
According to the cognitive network false alarm rate P fa, the significance level factor β is set, so that the following formula holds:
步骤2、循环自相关函数计算Step 2: Calculate cyclic autocorrelation function
根据下式计算认知用户在一个检测周期T内接收到的信号y(t)的循环自相关函数：Calculate the cyclic autocorrelation function of the signal y(t) received by the cognitive user in a detection period T according to the following formula:
式中，τ为延时，α为所述检测信号的循环频率，“*”表示其共轭，j为虚数单位；In the formula, τ is the delay, α is the cyclic frequency of the detection signal, "*" represents its conjugate, and j is the imaginary unit;
步骤3、信号检测域构建Step 3. Construction of signal detection domain
根据步骤2得到的循环自相关函数R
α(τ)，去除R
α(0)和R
0(τ)的函数域，构建认知网络信号检测域
According to the cyclic autocorrelation function R α (τ) obtained in step 2, remove the function domains of R α (0) and R 0 (τ) to construct the cognitive network signal detection domain
步骤4、检测信号特征值计算Step 4. Calculate the characteristic value of the detection signal
分别计算信号检测域函数
对变量τ集合的均值和方差μ
1和
对变 量α集合的均值和方差μ
2和
Calculate the signal detection domain function separately For the mean and variance of the variable τ set μ 1 and For the mean and variance of the variable α set μ 2 and
步骤5、频谱判决Step 5. Spectrum judgment
如果能够在信号检测域
中搜索到至少一对以α＝0或者τ＝0为对称的对称峰值点R
1与R
2，使得|R
l|>μ
1+βσ
1成立，或者|R
l|>μ
2+βσ
2成立，l＝1,2，则判定主用户信号存在，否则主用户信号不存在。
If it can be in the signal detection domain At least one pair of symmetrical peak points R 1 and R 2 with α=0 or τ=0 as the symmetry is searched in, so that |R l |>μ 1 +βσ 1 holds, or |R l |>μ 2 +βσ 2 If yes, l=1, then it is determined that the primary user signal exists, otherwise the primary user signal does not exist.
本发明进一步的设计在于，步骤1中，显著性水平因子β是根据认知网络虚警率P
fa设置的，显著性水平因子β的取值只要满足
即可，β越小，认知网络的检测率越高。
A further design of the present invention is that in step 1, the significance level factor β is set according to the cognitive network false alarm rate P fa , and the value of the significance level factor β only satisfies That is, the smaller the β, the higher the detection rate of the cognitive network.
本发明进一步的设计在于，步骤2中，循环自相关函数的计算也可以根据认知用户在一个检测周期T内接收到的信号y(t)的抽样信号y(k)计算。A further design of the present invention is that in step 2, the calculation of the cyclic autocorrelation function can also be calculated based on the sampling signal y(k) of the signal y(t) received by the cognitive user in a detection period T.
本发明进一步的设计在于，步骤3中，信号检测域
可以是步骤2计算得到的循环自相关函数R
α(τ)的全域或者子域。
A further design of the present invention is that in step 3, the signal detection domain It can be the entire domain or subdomain of the cyclic autocorrelation function R α (τ) calculated in step 2.
本发明进一步的设计在于，步骤3中，信号检测域
是一个二维高斯过程。
A further design of the present invention is that in step 3, the signal detection domain It is a two-dimensional Gaussian process.
本发明进一步的设计在于，步骤5中，对称峰值点的搜索是在信号检测域
的二维空间上进行的。
A further design of the present invention is that in step 5, the search for the symmetric peak point is in the signal detection domain On the two-dimensional space.
本发明进一步的设计在于，步骤5中，对称峰值点可以是一对，也可以是多对。A further design of the present invention is that in step 5, the symmetrical peak points can be one pair or multiple pairs.
本发明方法将调制信号循环自相关函数的对称峰值特征应用于认知网络的频谱检测中，利用主用户调制信号循环自相关函数的峰值对称性，将被检信号中的主用户信号和信道噪声进行有效分辨，实现信号在低信噪比或噪声波动环境下的频谱检难题。由此可产生如下的有益效果：The method of the present invention applies the symmetric peak characteristic of the cyclic autocorrelation function of the modulation signal to the spectrum detection of the cognitive network, and uses the peak symmetry of the cyclic autocorrelation function of the primary user modulation signal to combine the primary user signal and channel noise in the detected signal. Perform effective resolution and realize the difficult problem of spectrum detection of signal in low signal-to-noise ratio or noise fluctuation environment. This can produce the following beneficial effects:
(1)通过接收信号的循环自相关函数的对称峰值识别，实现低信噪比或噪 声波动环境下的主用户信号和信道噪声的有效分辨；(1) Through the symmetric peak identification of the cyclic autocorrelation function of the received signal, the effective discrimination between the primary user signal and the channel noise in a low signal-to-noise ratio or noise fluctuation environment is realized;
(2)通过接收信号的循环自相关函数对称峰值点的二维空间搜索，提高了认知网络的频谱检测率，降低了主用户与认知用户之间的冲突概率；(2) Through the two-dimensional space search of the symmetric peak point of the cyclic autocorrelation function of the received signal, the spectrum detection rate of the cognitive network is improved, and the probability of conflict between the primary user and the cognitive user is reduced;
(3)根据认知网络虚警率设置显著性水平因子，有效平衡了频谱检测率和虚警率两个频谱检测的性能指标，有利于实现认知网络的全局优化；(3) The significance level factor is set according to the false alarm rate of the cognitive network, which effectively balances the two spectrum detection performance indicators of the spectrum detection rate and the false alarm rate, which is beneficial to realize the global optimization of the cognitive network;
(4)系统结构简单，可以应用与任何一种调制信号的频谱感知。(4) The system structure is simple and can be applied to any kind of spectrum sensing of modulated signals.
下面结合附图对本发明作进一步的说明。The present invention will be further explained below in conjunction with the drawings.
图1是本发明认知网络系统模型示意图。Fig. 1 is a schematic diagram of the cognitive network system model of the present invention.
图2是本发明频谱感知方法流程框图。Fig. 2 is a flowchart of the spectrum sensing method of the present invention.
下面结合附图和具体实施例对本发明做进一步说明。The present invention will be further described below in conjunction with the drawings and specific embodiments.
在一个认知网络中至少包括1个主用户和1个认知用户，如图1所示，认知用户接收到的检测信号为y(t)＝s(t)+n(t)，其中，s(t)为主用户传输的信号，在本例中s(t)是一个比特率为250Kbits/s、载波为320MHz的二进制调相信号，n(t)为信道噪声，0≤t≤T，T为认知用户频谱检测时间，本发明实施基于调制信号循环自相关函数峰值对称的频谱感知方法，包括如下步骤：A cognitive network includes at least one primary user and one cognitive user. As shown in Figure 1, the detection signal received by the cognitive user is y(t)=s(t)+n(t), where , S(t) is the signal transmitted by the main user. In this example, s(t) is a binary phase modulated signal with a bit rate of 250Kbits/s and a carrier of 320MHz. n(t) is the channel noise, 0≤t≤ T, T is the spectrum detection time of the cognitive user. The implementation of the spectrum sensing method based on the symmetrical peak of the modulated signal cyclic autocorrelation function of the present invention includes the following steps:
步骤1、设置显著性水平因子，根据认知网络虚警率P
fa要求设置显著性水平因子β，使得
成立，本实施例中，认知网络虚警率要求为P
fa≤0.001，设置β＝4。
Step 1. Set the significance level factor, and set the significance level factor β according to the cognitive network false alarm rate P fa , so that Yes, in this embodiment, the false alarm rate of the cognitive network is required to be P fa ≤ 0.001, and β=4 is set.
步骤2、循环自相关函数计算，计算认知用户在一个检测周期T内接收到的信号y(t)的循环自相关函数：Step 2. Calculate the cyclic autocorrelation function, and calculate the cyclic autocorrelation function of the signal y(t) received by the cognitive user in a detection period T:
其中，τ为延时，α为信号的循环频率，“*”表示其共轭，j为虚数单位。Among them, τ is the delay, α is the cycle frequency of the signal, "*" represents its conjugate, and j is the imaginary unit.
步骤3、信号检测域构建，根据步骤2得到的循环自相关函数R
α(τ)，去除R
α(0)和R
0(τ)的函数域，构建认知网络信号检测域
Step 3. Construction of the signal detection domain. According to the cyclic autocorrelation function R α (τ) obtained in Step 2, remove the function domains of R α (0) and R 0 (τ) to construct the cognitive network signal detection domain
步骤4、检测信号特征值计算，分别计算信号检测域函数
对变量τ集合的均值和方差μ
1和
对变量α集合的均值和方差μ
2和
Step 4. Calculate the characteristic value of the detection signal, respectively calculate the signal detection domain function For the mean and variance of the variable τ set μ 1 and For the mean and variance of the variable α set μ 2 and
步骤5、频谱判决，如果能够在信号检测域
中搜索到一对以α＝0或者τ＝0为对称的对称峰值点R
1与R
2，使得|R
l|>μ
1+βσ
1或者|R
l|>μ
2+βσ
2成立，l＝1,2，则判定主用户信号存在，否则主用户信号不存在。
Step 5. Spectrum judgment, if it can be in the signal detection domain A pair of symmetrical peak points R 1 and R 2 with α=0 or τ=0 as the symmetry is searched in, so that |R l |>μ 1 +βσ 1 or |R l |>μ 2 +βσ 2 holds, l =1,2, it is determined that the primary user signal exists, otherwise the primary user signal does not exist.
对本实施例的频谱检测方法进行仿真测试，结果表明采用本案的频谱检测方法，可以根据接收信号循环自相关函数的对称峰值辨别主用户信号是否出现，提高了频谱检测精度。可见，本发明实施例与已有的频谱检测方法相比显著提高了频谱检测性能。本发明既适用于单载波信号感知，也适用于多载波信号感知或者单载波信号感知与多载波信号的混合信号感知。A simulation test is performed on the spectrum detection method of this embodiment, and the result shows that the spectrum detection method of this case can distinguish whether the main user signal appears according to the symmetric peak value of the received signal cyclic autocorrelation function, and the spectrum detection accuracy is improved. It can be seen that, compared with the existing spectrum detection method, the embodiment of the present invention significantly improves the spectrum detection performance. The present invention is not only suitable for single-carrier signal sensing, but also suitable for multi-carrier signal sensing or mixed signal sensing of single-carrier signal sensing and multi-carrier signal.
除上述实施例外，本发明还可以有其他实施方式。凡采用等同替换或等效变换形成的技术方案，均落在本发明要求的保护范围。In addition to the foregoing embodiments, the present invention may also have other embodiments. All technical solutions formed by equivalent replacements or equivalent transformations fall within the protection scope of the present invention.
Claims (7)
- 基于调制信号循环自相关函数对称峰值的频谱感知方法，所述认知网络中至少包括1个主用户和1个认知用户，认知用户接收到的检测信号为y(t)＝s(t)+n(t)，其中，s(t)为主用户传输的信号，n(t)为信道噪声，0≤t≤T，T为认知用户频谱检测时间，其特征在于所述频谱感知方法包括如下步骤：The spectrum sensing method based on the symmetric peak of the cyclic autocorrelation function of the modulated signal, the cognitive network includes at least one primary user and one cognitive user, and the detection signal received by the cognitive user is y(t)=s(t )+n(t), where s(t) is the signal transmitted by the main user, n(t) is the channel noise, 0≤t≤T, and T is the cognitive user spectrum detection time, which is characterized by the spectrum sensing The method includes the following steps:步骤1、设置显著性水平因子Step 1. Set the significance level factor根据认知网络虚警率P fa要求设置显著性水平因子β，使得下式成立： According to the cognitive network false alarm rate P fa, the significance level factor β is set, so that the following formula holds:
步骤2、循环自相关函数计算Step 2: Calculate cyclic autocorrelation function根据下式计算认知用户在一个检测周期T内接收到的信号y(t)的循环自相关函数：Calculate the cyclic autocorrelation function of the signal y(t) received by the cognitive user in a detection period T according to the following formula:
式中，τ为延时，α为所述检测信号的循环频率，“*”表示其共轭，j为虚数单位；In the formula, τ is the delay, α is the cyclic frequency of the detection signal, "*" represents its conjugate, and j is the imaginary unit;步骤3、信号检测域构建Step 3. Construction of signal detection domain根据步骤2得到的循环自相关函数R α(τ)，去除R α(0)和R 0(τ)的函数域，构建认知网络信号检测域According to the cyclic autocorrelation function R α (τ) obtained in step 2, remove the function domains of R α (0) and R 0 (τ) to construct the cognitive network signal detection domain
τ≠0且α≠0
τ≠0 and α≠0步骤4、检测信号特征值计算Step 4. Calculate the characteristic value of the detection signal分别计算信号检测域函数对变量τ集合的均值和方差μ 1和
对变量α集合的均值和方差μ 2和
Calculate the signal detection domain function separately
For the mean and variance of the variable τ set μ 1 andFor the mean and variance of the variable α set μ 2 and步骤5、频谱判决Step 5. Spectrum judgment如果能够在信号检测域中搜索到至少一对以α＝0或者τ＝0为对称的对 称峰值点R 1与R 2，使得|R l|>μ 1+βσ 1成立，或者|R l|>μ 2+βσ 2成立，l＝1,2，则判定主用户信号存在，否则主用户信号不存在。 If it can be in the signal detection domain
At least one pair of symmetrical peak points R 1 and R 2 with α=0 or τ=0 as the symmetry is searched in, so that |R l |>μ 1 +βσ 1 holds, or |R l |>μ 2 +βσ 2 If yes, l=1, then it is determined that the primary user signal exists, otherwise the primary user signal does not exist. - 根据权利要求1所述基于调制信号循环自相关函数对称峰值的频谱感知方法，其特征在于：步骤1中，显著性水平因子β是根据认知网络虚警率P fa设置的，显著性水平因子β的取值只要满足即可，β越小，认知网络的检测率越高。 The spectrum sensing method based on the symmetric peak of the modulated signal cyclic autocorrelation function according to claim 1, characterized in that: in step 1, the significance level factor β is set according to the cognitive network false alarm rate P fa , and the significance level factor As long as the value of β satisfies
That is, the smaller the β, the higher the detection rate of the cognitive network. - 根据权利要求1所述基于调制信号循环自相关函数对称峰值的频谱感知方法，其特征在于：步骤2中，循环自相关函数根据认知用户在一个检测周期T内接收到的信号y(t)的抽样信号y(k)计算获得。The spectrum sensing method based on the symmetric peak of the cyclic autocorrelation function of the modulated signal according to claim 1, wherein: in step 2, the cyclic autocorrelation function is based on the signal y(t) received by the cognitive user in a detection period T The sampled signal y(k) is calculated.
- 根据权利要求1所述基于调制信号循环自相关函数对称峰值的频谱感知方法，其特征在于：步骤3中，信号检测域是步骤2计算得到的循环自相关函数R α(τ)的全域或者子域。 The spectrum sensing method based on the symmetric peak of the cyclic autocorrelation function of the modulated signal according to claim 1, characterized in that: in step 3, the signal detection domain
It is the full range or sub-domain of the cyclic autocorrelation function R α (τ) calculated in step 2. - 根据权利要求1所述基于调制信号循环自相关函数对称峰值的频谱感知方法，其特征在于：步骤3中，信号检测域是一个二维高斯过程。 The spectrum sensing method based on the symmetric peak of the cyclic autocorrelation function of the modulated signal according to claim 1, characterized in that: in step 3, the signal detection domain
It is a two-dimensional Gaussian process. - 根据权利要求1所述基于调制信号循环自相关函数对称峰值的频谱感知方法，其特征在于：步骤5中，对称峰值点的搜索是在信号检测域的二维空间上进行的。 The spectrum sensing method based on the symmetric peak of the modulated signal cyclic autocorrelation function according to claim 1, characterized in that: in step 5, the search for the symmetric peak point is in the signal detection domain
On the two-dimensional space. - 根据权利要求1所述基于调制信号循环自相关函数对称峰值的频谱感知方法，其特征在于：步骤5中，对称峰值点为一对或者多对。The spectrum sensing method based on symmetric peaks of the modulated signal cyclic autocorrelation function according to claim 1, wherein in step 5, the symmetric peak points are one or more pairs.
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