Self-adaptive adjustment cooperative spectrum sensing method
Technical Field
The invention relates to the field of wireless communication, in particular to a cooperative spectrum sensing method with self-adaptive adjustment.
Background
As a key technology for solving the shortage of communication spectrum resources, Cognitive Radio (CR) can "servo" use and share idle spectrum, thereby solving the problem of shortage of spectrum resources.
The basic approaches to cognitive radio are: firstly, a cognitive user continuously monitors authorized spectrum resources in the surrounding environment by adopting spectrum sensing, and then the cognitive user adaptively adjusts the transceiver to communicate with the idle spectrum under the condition of ensuring that the authorized user can preferentially occupy the spectrum, so that the idle spectrum resources are effectively and fully utilized. When the cognitive user senses (or detects) the signal of the authorized user, the cognitive user needs to rapidly vacate the channel occupied by the cognitive user in an 'opportunistic' manner so as to be given up to the authorized user for use, thereby avoiding interference with normal communication of the authorized user. Therefore, the spectrum sensing method adopted by the cognitive user requires high detection performance for detecting the authorized user, and the spectrum sensing technology has great significance for detecting the existence condition of the authorized user signal.
In an actual environment, in order to reduce adverse effects of multiple factors such as multipath fading, shadowing effect and noise uncertainty on detection performance, a cooperative spectrum sensing method based on multiple cognitive users is proposed in succession. In the conventional cooperative spectrum sensing method, most cooperative spectrum sensing methods assume that each cognitive user adopts an energy detection method, the received signal energy is detected by presetting a fixed judgment threshold value, and then each cognitive user sends a detection result to a spectrum sensing fusion center for fusion processing, so that the purpose of accurately sensing the spectrum is achieved.
However, the existing cooperative spectrum sensing method still has some disadvantages: on one hand, in actual cooperative spectrum sensing, the energy of a signal received by a cognitive user changes, but the problem that a preset fixed judgment threshold value is not beneficial to the cognitive user to make accurate energy detection when the energy of the signal received by the cognitive user changes is not considered in the conventional cooperative spectrum sensing method, which results in that each cognitive user has lower detection performance in actual energy detection and is not beneficial to improving the overall detection performance of cooperative sensing; on the other hand, the conventional cooperative spectrum sensing method does not consider the problem of huge fusion calculation amount of a spectrum sensing fusion center, so that the efficiency of fusion detection of the spectrum sensing fusion center is reduced, and the sensing time that each cognitive user occupies or quits the idle spectrum in time is delayed.
Disclosure of Invention
The invention aims to solve the technical problem of providing a self-adaptive adjustment cooperative spectrum sensing method which can self-adaptively acquire the optimal threshold value of each cognitive user for energy detection judgment, determine the optimal cooperative cognitive user and reduce the fusion calculation amount of a spectrum sensing fusion center aiming at the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a self-adaptive adjustment cooperative spectrum sensing method is used in a cognitive wireless network composed of authorized users, a spectrum sensing fusion center and N cognitive users, and is characterized by sequentially comprising the following steps:
(1) the N cognitive users carry out local energy detection on the spectrum occupation condition of the authorized user, and respectively send a spectrum sensing result and the signal-to-noise ratio of the cognitive user to a spectrum sensing fusion center; wherein the cognitive user is marked as CRi(i ═ 1,2, …, N), cognitive user CRiSelf signal to noise ratio snr is snriThe authorized user is marked as PU, and the spectrum sensing fusion center is marked as FC;
(2) the frequency spectrum sensing fusion center FC counts the number of the cognitive users sensing the PU frequency spectrum of the authorized user to be in an occupied state in the N cognitive users as m (m is more than or equal to 1 and less than or equal to N) and the number of the cognitive users sensing the PU frequency spectrum of the authorized user to be in an idle state as N-m according to the frequency spectrum sensing results sent by the N cognitive users; the PU frequency spectrum of the authorized user is recorded as H in the occupied state1The PU frequency spectrum of the authorized user is in the idle state and is recorded as H0;
(3) The spectrum sensing fusion center FC calculates m sensing authorized users PU spectrum into an occupied state H according to the signal-to-noise ratios sent by the N sensing users1Cognitive user integrity factor k1,jAnd N-m sensing authorized users PU frequency spectrum to be in idle state H0Cognitive user integrity factor k2,t(ii) a Wherein the integrity factor k1,jAnd kappa2,tThe calculation formula of (a) is as follows:
(4) the spectrum sensing fusion center FC performs fusion according to respective sensing results of m cognitive users and an integrity coefficient kappa1,jRespectively calculating the PU frequency spectrum of the authorized user as the occupation state H1Average detection probability ofGlobal detection probabilityAnd this occupation state H1Corresponding global miss probabilityAnd authorizing the frequency spectrum of the user PU to be in an idle state H0Average detection probability ofGlobal detection probabilityThis idle state H0Corresponding global miss probabilityAnd global false alarm probabilityWherein the process comprises the following steps (4-1) to (4-3):
(4-1) establishing global error detection probability P of cooperative perception of m cognitive userseObtaining an energy detection optimization function gamma with respect to a decision threshold*And an optimum threshold value gamma for energy detectionoptAnd calculating the PU frequency spectrum of the authorized user as an occupation state H1Average detection probability ofWherein,
global error detection probability P of cooperative perception of m cognitive userseThe calculation formula is as follows:
wherein,PU frequency spectrum is in idle state H for authorized user0The probability of (a) of (b) being,PU frequency spectrum is in occupied state H for authorized user1The probability of (d); pfIs the global false alarm probability, PdFor global detection probability, PmIs the global miss probability;PU frequency spectrum is in occupied state H for corresponding authorized user1Q (z) represents a normal gaussian complementary integral function; wherein,snrifor cognitive users CRiThe signal-to-noise ratio of the device itself; energy detection optimization function gamma with respect to decision threshold*Is defined as:
optimal threshold value gamma for energy detectionoptComprises the following steps:
authorizing user PU frequency spectrum to be in occupied state H1Average detection probability ofThe calculation formula is as follows:
(4-2) according to the obtained right user PU frequency spectrum, the PU frequency spectrum is in an occupied state H1Average detection probability ofAnd the integrity factor k of m cognitive users1,jCalculating the PU frequency spectrum of the authorized user as the occupation state H1Global detection probability ofAnd this occupation state H1Corresponding global miss probabilityWherein the global detection probabilityAnd global miss probabilityThe calculation formula is as follows:
(4-3) according to the obtained PU frequency spectrum of the authorized user, the PU frequency spectrum is in an idle state H0Average detection probability ofAnd the integrity factor k of N-m cognitive users2,tCalculating the PU frequency spectrum of the authorized user to be in an idle state H0Global detection probability ofAnd this idle state H0Corresponding global miss probabilityGlobal false alarm probabilityWherein the average detection probabilityGlobal detection probabilityGlobal miss probabilityAnd global false alarm probabilityThe calculation formulas of (A) are respectively as follows:
(5) the frequency spectrum sensing fusion center FC takes the PU frequency spectrum of the authorized user as an occupation state H1Corresponding global miss probabilityAnd authorizing the user PU frequency spectrum to be in an idle state H0Corresponding global false alarm probabilityEstablishing a spectrum sensing error function Fun (m) based on the number of the cognitive users; the spectral perception error function fun (m) is calculated as follows:
wherein, PpuRepresenting the probability of the PU signal of the authorized user appearing in its authorized spectrum;
(6) calculating a minimum value Fun (m) of the spectrum sensing error function Fun (m)0) And using the minimum value Fun (m) of the spectrum sensing error function0) Corresponding number m0(m0Less than or equal to m) as the optimal number of the cooperative cognitive users participating in cooperative sensing, and the m cognitive users are subjected to signal-to-noise ratio snr according to the corresponding signal-to-noise ratio snriPerforming descending order arrangement to obtain descending order arrangement groups of m cognitive users;
(7) selecting the first m in a cognitive user descending order arrangement group0The cognitive users are used as the optimal cooperative cognitive users participating in cooperative sensing; wherein the selected optimal collaborative cognitive users are respectively marked as CR'rWherein r is 1,2, …, m0;
(8) According to m in step (7)0Optimal cooperative cognitive user CR'rThe spectrum sensing fusion center FC uses the global detection probability after the cooperation of the weighted OR criterion as the final detection result of the cooperative sensing of the N cognitive users; wherein the weighted OR criterion is as follows:
wherein, Pd,rIs the best cooperative cognitive user CR'rProbability of detection of, Pfa,rIs the best cooperative cognitive user CR'rFalse alarm probability of (d); qdFor global detection probability after cooperative sensing, QfaThe global false alarm probability after cooperative sensing is obtained; m is0The number of users for optimal cooperative cognitive; omegarIs the best cooperative cognitive user CR'rThe weighting coefficient of (2).
Compared with the prior art, the invention has the advantages that: after acquiring the integrity coefficient of each cognitive user and establishing the global error detection probability of cognitive user cooperative sensing, acquiring an energy detection optimization function related to a decision threshold and an optimal threshold value of energy detection judgment to adapt to the change of signal energy received by each cognitive user, and acquiring the detection probability of each cognitive user by the optimal threshold value; and then establishing a spectrum sensing error function based on the number of the cognitive users, taking the number of the cognitive users corresponding to the minimum value of the spectrum sensing error function as the optimal number of the cooperative cognitive users, and obtaining the optimal cooperative cognitive users, thereby reducing the fusion calculation amount of a spectrum sensing fusion center while ensuring the cooperative sensing performance, and finally finishing the cooperative sensing. The cooperative spectrum sensing method can adaptively adjust and acquire the optimal threshold value of the energy detection judgment of the cognitive users, and can determine the optimal cooperative cognitive users with the cooperative number smaller than the total number of the cognitive users and reduce the fusion calculation amount of a spectrum sensing fusion center on the premise of ensuring the cooperative sensing performance.
Drawings
Fig. 1 is a schematic flow chart of a cooperative spectrum sensing method with adaptive adjustment in this embodiment.
Detailed Description
The invention is described in further detail below with reference to the accompanying examples.
As shown in fig. 1, the cooperative spectrum sensing method with adaptive adjustment in this embodiment is used in a cognitive wireless network composed of authorized users, a spectrum sensing fusion center, and N cognitive users, and sequentially includes the following steps:
(1) the N cognitive users carry out local energy detection on the spectrum occupation condition of the authorized user, and respectively send a spectrum sensing result and the signal-to-noise ratio of the cognitive user to a spectrum sensing fusion center; wherein the cognitive user is marked as CRi(i ═ 1,2, …, N), cognitive user CRiSelf signal to noise ratio snr is snriThe authorized user is marked as PU, and the spectrum sensing fusion center is marked as FC; n cognitive users are respectively CR1、CR2、CR3、…、CRN-1、CRN(ii) a N cognitive users CR1To CRNThe corresponding self signal-to-noise ratios are snr1、snr2、snr3、…、snrN-1、snrN;
(2) The frequency spectrum sensing fusion center FC counts the number of the cognitive users sensing the PU frequency spectrum of the authorized user to be in an occupied state in the N cognitive users as m (m is more than or equal to 1 and less than or equal to N) and the number of the cognitive users sensing the PU frequency spectrum of the authorized user to be in an idle state as N-m according to the frequency spectrum sensing results sent by the N cognitive users; the PU frequency spectrum of the authorized user is recorded as H in the occupied state1The PU frequency spectrum of the authorized user is in the idle state and is recorded as H0;
(3) The spectrum sensing fusion center FC calculates m sensing authorized users PU spectrum into an occupied state H according to the signal-to-noise ratios sent by the N sensing users1Cognitive user integrity factor k1,jAnd N-m sensing authorized users PU frequency spectrum to be in idle state H0Cognitive user integrity factor k2,t(ii) a The integrity coefficient represents the credibility of detection made by the corresponding cognitive user and also represents the detection capability of the cognitive user; the higher the integrity coefficient is, the higher the detection probability of the corresponding cognitive user is; integrity factor k1,jAnd kappa2,tThe calculation formula of (a) is as follows:
(4) the spectrum sensing fusion center FC performs fusion according to respective sensing results of m cognitive users and an integrity coefficient kappa1,jRespectively calculating the PU frequency spectrum of the authorized user as the occupation state H1Average detection probability ofGlobal detection probabilityAnd this occupation state H1Corresponding global miss probabilityAnd authorizing the frequency spectrum of the user PU to be in an idle state H0Average detection probability ofGlobal detection probabilityThis idle state H0Corresponding global miss probabilityAnd global false alarm probabilityWherein the process comprises the following steps (4-1) to (4-3):
(4-1) establishing global error detection probability P of cooperative perception of m cognitive userseObtaining an energy detection optimization function gamma with respect to a decision threshold*And an optimum threshold value gamma for energy detectionoptAnd calculating the PU frequency spectrum of the authorized user as an occupation state H1Average detection probability ofThe threshold of the energy detection is a judgment threshold in the energy detection; wherein, the global error detection probability of the cooperative perception of the m cognitive usersPeThe calculation formula is as follows:
wherein,PU frequency spectrum is in idle state H for authorized user0The probability of (a) of (b) being,PU frequency spectrum is in occupied state H for authorized user1The probability of (d); pfIs the global false alarm probability, PdFor global detection probability, PmIs the global miss probability;PU frequency spectrum is in occupied state H for corresponding authorized user1The average signal-to-noise ratio of the m cognitive users, wherein,snrifor cognitive users CRiThe signal-to-noise ratio of the device itself;
energy detection optimization function gamma with respect to decision threshold*Is defined as:
by optimizing the function gamma for energy detection with respect to decision thresholds*Obtaining an extreme value to obtain an optimal threshold value gamma of energy detection judgmentoptComprises the following steps:
that is, in the process of detecting the energy utilization of each cognitive user, when the judgment threshold value aiming at the energy of the received signal is the optimal threshold value gammaoptIn the process, the cognitive user can accurately detect the existence of the received signal, and the condition of dynamic change of the energy of the received signal is met and adapted, so that a more accurate energy detection judgment threshold value is obtained, and the accuracy of independent detection and cooperative detection of subsequent cognitive users is improved;
authorizing user PU frequency spectrum to be in occupied state H1Average detection probability ofThe calculation formula is as follows:
(4-2) according to the obtained right user PU frequency spectrum, the PU frequency spectrum is in an occupied state H1Average detection probability ofAnd the integrity factor k of m cognitive users1,jCalculating the PU frequency spectrum of the authorized user as the occupation state H1Global detection probability ofAnd this occupation state H1Corresponding global miss probabilityWherein the global detection probabilityAnd global missed detection summaryRate of changeThe calculation formula is as follows:
(4-3) according to the obtained PU frequency spectrum of the authorized user, the PU frequency spectrum is in an idle state H0Average detection probability ofAnd the integrity factor k of N-m cognitive users2,tCalculating the PU frequency spectrum of the authorized user to be in an idle state H0Global detection probability ofAnd this idle state H0Corresponding global miss probabilityGlobal false alarm probabilityWherein the average detection probabilityGlobal detection probabilityGlobal miss probabilityAnd global false alarm probabilityThe calculation formulas of (A) are respectively as follows:
(5) the frequency spectrum sensing fusion center FC takes the PU frequency spectrum of the authorized user as an occupation state H1Corresponding global miss probabilityAnd authorizing the user PU frequency spectrum to be in an idle state H0Corresponding global false alarm probabilityEstablishing a spectrum sensing error function Fun (m) based on the number of the cognitive users; the spectrum sensing error function fun (m) represents the error condition of cooperative spectrum sensing corresponding to the number of m cognitive users(ii) a The smaller the frequency spectrum sensing error value is, the better the detection performance of the cooperative frequency spectrum sensing is; the spectral perception error function fun (m) is calculated as follows:
wherein, PpuRepresenting the probability of the PU signal of the authorized user appearing in its authorized spectrum;
(6) calculating a minimum value Fun (m) of the spectrum sensing error function Fun (m)0) And is combined withWith the minimum value Fun (m) of the spectrum sensing error function0) Corresponding number m0(m0Less than or equal to m) as the optimal number of the cooperative cognitive users participating in cooperative sensing, and the m cognitive users are subjected to signal-to-noise ratio snr according to the corresponding signal-to-noise ratio snriPerforming descending order arrangement to obtain descending order arrangement groups of m cognitive users;
wherein, the number of the cognitive users participating in the cooperative sensing is m0Then, cooperative sensing among the cognitive users has the smallest spectrum sensing error, and at this time, the cooperative spectrum sensing has stronger detection performance, and at this time, m is0The number of the cognitive users can reduce the calculation amount during subsequent FC fusion of the spectrum sensing fusion center on the premise of ensuring smaller spectrum sensing errors, and the cooperative detection efficiency is improved;
because the signal-to-noise ratio of each cognitive user is still the key for influencing the spectrum detection performance of each cognitive user, the cognitive users are arranged in a descending order according to the magnitude sequence of the signal-to-noise ratio, and the signal-to-noise ratio can be conveniently used as an identifier for distinguishing the detection performance so as to select the cognitive user with high detection performance;
(7) selecting the first m in a cognitive user descending order arrangement group0The cognitive users are used as the optimal cooperative cognitive users participating in cooperative sensing; wherein the selected optimal collaborative cognitive users are respectively marked as CR'rWherein r is 1,2, …, m0;
For example, the cognitive user descending order group obtained when the cognitive users are arranged in descending order of the signal-to-noise ratio is { CR }1,CR2、…、CRm0、CRm0+1,…,CRmAt this time, the front m is selected0Individual cognitive users, { CR1,CR2、…、CRm0The symbols are used as the optimal cooperative cognitive users participating in cooperative sensing and respectively correspond to the marks CR1To CRm0Is the best cooperative cognitive user CR'1To CR'm0;
(8) According to m in step (7)0Optimal cooperative cognitive user CR'rDetection probability of (2), spectrum sensing fusion center FC to addTaking the global detection probability after the OR criterion of the weights is cooperated as a final detection result of N cognitive users in cooperative perception; wherein the weighted OR criterion is as follows:
wherein, Pd,rIs the best cooperative cognitive user CR'rProbability of detection of, Pfa,rIs the best cooperative cognitive user CR'rFalse alarm probability of (d); qdFor global detection probability after cooperative sensing, QfaThe global false alarm probability after cooperative sensing is obtained; m is0The number of users for optimal cooperative cognitive; omegarIs the best cooperative cognitive user CR'rThe weighting coefficient of (2). Wherein, ω isrThe larger the weight coefficient is, the stronger the detection performance of the optimal cooperative cognitive user corresponding to the weight coefficient is.