The invention discloses a spectrum sensing method and a spectrum sensing system for cognitive radio. The method comprises the steps of respectively decomposing signals received by a preset quantity of secondary users into respective corresponding I signals and Q signals; generating a decomposition matrix according to the I signals and the Q signals, and acquiring a covariance matrix of the decomposition matrix; acquiring a maximum feature value and a matrix trace according to the covariance matrix, and acquiring a judgment statistical magnitude; judging whether the judgment statistical magnitude is more than a judgment threshold; if yes, determining that a master user exists; and if no, determining that no master user exists. According to the method and the system provided by the invention, the signals received by the preset quantity of secondary users are decomposed into the respective corresponding I signals and Q signals, so that the signals are decomposed; the maximum feature value and the matrix trace are acquired by the covariance matrix of the decomposition matrix formed according to the I signals and the Q signals, and the judgment statistical magnitude is acquired, so that signal decomposition can be combined with an algorithm of a ratio of the maximum feature value to the matrix trace, and thus accuracy and reliability of the spectrum sensing method are improved.

Spectrum sensing method and system for cognitive radio

The invention discloses a double-feature spectrum sensing method based on maximum feature values and main feature vectors. The method comprises the steps of calculating the maximum feature values andthe corresponding main feature vectors of covariance matrixes of signals received in a current sensing time slot and a plurality of previous continuous sensing time slots; obtaining the estimated value of the main feature vector of the covariance matrix of a licensed user signal and the estimated value of the maximum feature value of the covariance matrix of white gaussian noise according to the corresponding maximum feature values and the corresponding main feature vectors in the plurality of previous continuous sensing time slots; obtaining a first test statistics value and a second test statistics value according to the maximum feature value, the main feature vector and the two estimated values of the covariance matrix of the signal received in the current sensing time slot; and comparing the first test statistics value with a first judgment threshold, and comparing the second test statistics value with a second judgment threshold, thereby realizing spectrum sensing. The method hasthe advantage of effectively improving the spectrum sensing performance.

Double-feature spectrum sensing method based on maximum feature values and main feature vectors

The invention discloses a frequency spectrum sensing method, which comprises the following steps of acquiring radio sampling signals; carrying out noise reduction processing on the sampling signals inorder to obtain noise reduction signals; carrying out splitting and recombination on the noise reduction signals according to a DAR splitting and recombination technology in order to obtain two signal matrixes; respectively computing a difference of a maximum eigenvalue and a minimum eigenvalue according to the eigenvalues of the two signal matrixes in order to obtain a two-dimensional eigenvalue; and carrying out feature classification and division on the two-dimensional eigenvalue in order to obtain a classification result of the radio sampling signals According to the method, the signalsare subjected to DAR splitting and recombination, and then signal feature information is extracted through THE DMM, the detection performance of a spectrum can be better improved under a condition that the number of cognitive users is small and a signal-to-noise ratio is low, the spectrum sensing performance is improved, the spectrum sensing effect is optimized, and accurate classification of thesampling signals is achieved The invention further discloses a spectrum sensing device, equipment and system and a readable storage medium, which have the beneficial effects

Spectrum sensing method, device, equipment and system, and readable storage medium

The invention provides a spectrum sensing method based on a cyclic matrix characteristic value. Unlicensed users are guaranteed to have relatively high spectrum sensing performance under the same sample point number. The method comprises the steps of sensing signals of licensed users through cooperation of a plurality of unlicensed users; dividing the sensed signals into a plurality of receiving vectors according to sample time and determining a cyclic matrix of each receiving vector; calculating a mean covariance matrix of the cyclic matrix of each receiving vector and solving a characteristic value of the mean covariance matrix; and establishing detection statistics for binary assumption detection according to the characteristic value, judging that the licensed users do not exist if thedetection statistics is greater than a set threshold, otherwise, judging that the licensed users exist. According to the method, whether the licensed users exist or not can be sensed in a cognitive radio network.

Spectrum sensing method based on cyclic matrix characteristic value

The invention relates to a spectrum sensing method based on signal and noise characteristic detection. In a cognitive network including a main user and a cognitive user, the cognitive user carries outsignal characteristic analysis and calculation on a received signal, sends calculated signal characteristics into a signal characteristic detection network to carry out detection so as to discriminate whether a main user signal exists, if the signal characteristic detection network outputs 1, judges that the main user signal exists, or judges that the main user signal does not exist. According tothe method disclosed by the invention, spectrum sensing is carried out by signal and noise characteristics; spectrum judgment has no correlation with power of the signal detected by the cognitive user and power of channel noise; influence of channel noise fluctuation on spectrum sensing performance is eliminated; the spectrum sensing method is particularly suitable for signal spectrum sensing inthe channel noise fluctuation environment.

Spectrum sensing method based on signal and noise characteristic detection

The invention relates to a cooperative frequency spectrum perception method based on a difference between maximum and minimum feature values The method comprises the following steps: a cognition user receiving end randomly sampling received signals and calculating a receiving signal matrix; obtaining a sample covariance matrix through calculation of the receiving signal matrix, and performing feature value decomposition; selecting the difference between the maximum value and the smallest value as a detection statistical amount; calculating a threshold value in case that an authorized user exists; comparing the detection statistical amount with the threshold value, and determining whether primary users exist; and if the statistical amount is greater than or equal to the threshold value, indicating that the primary users exist, and otherwise, indicating that the primary users do not exist, such that secondary users can be conveniently accessed to a frequency range According to the invention, the difference between the maximum and minimum feature values is taken as the detection statistical amount, the distribution function is a distribution rule based on the minimum feature value, and the obtained threshold value can be more accurate Under the condition of cooperative perception of the multiple secondary users, quite high detection precision can be ensured, at the same time, a fewer number of sampling points are needed, and the system complexity is reduced

Cooperative frequency spectrum perception method based on difference between maximum and minimum feature values

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Cooperative frequency spectrum perception method based on difference between maximum and minimum feature values