CN115632728B - Trusted spectrum sensing method based on blockchain technology - Google Patents
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Abstract
The invention discloses an integrated trusted spectrum sensing method based on a blockchain technology, which comprises the following steps: firstly, sensing a user to locally sense the spectrum occupation condition of wireless communication, packaging a sensing result into a transaction and signing, and publishing the transaction to a cognitive radio network, wherein other sensing users receive the transaction and verify the transaction and store the transaction into a local transaction pool; then, a perception user selects a group of transactions to assemble a pre-issued block according to the user credit value on the block chain, global decision is made on the spectrum occupation condition by aggregating the transactions and the corresponding credit values in the block, and the credit value of the perception user is updated according to the global decision result; then, the perception user broadcasts the new area block to the cognitive radio network; and finally, other perception users verify the released new block, and after the verification is successful, the new block is accessed into a local block chain, and the global decision result and the reputation value are stored and updated. The invention improves the safety of spectrum sensing and the timeliness and reliability of global decision.
Description
Technical Field
The invention relates to the technical field of spectrum sensing, in particular to a trusted spectrum sensing method based on a blockchain technology.
Background
With the rapid growth of wireless communication traffic, wireless spectrum resources are increasingly scarce. Aiming at the contradiction between limited spectrum resources and continuously-increased spectrum demands, the cognitive radio technology has the core ideas of realizing dynamic spectrum allocation and spectrum sharing through the learning and cognitive abilities of the spectrums, thereby optimizing the utilization rate of the wireless spectrums.
Spectrum sensing is the basis for achieving spectrum allocation and spectrum sharing. Because of the effects of noise and channel fading (e.g., multipath fading and shadow fading), spectrum sensing results based on a single sensing user are not reliable, and thus multiple sensing users are required to perform cooperative spectrum sensing. However, due to the distributed characteristics of the cognitive radio network, malicious perception users easily fictitiously perceive results, and therefore accuracy of global decisions is affected. In order to solve the problems, the collaborative spectrum sensing technology introduces a trust evaluation mechanism, evaluates the reputation value of a sensing user through a sensing result, and selects a high-reputation user to participate in global decision, so that the harmfulness of malicious behaviors is reduced.
Currently, collaborative spectrum sensing based on trust management mainly relies on a centralized node to manage the reputation values of various sensing users. And each perception user independently carries out local spectrum perception and uploads the perception result to the fusion center. And after the fusion center finishes the collection of the data, the fusion center obtains a global decision by weighting and aggregating the perception result according to the reputation value of the perception user. However, once the fusion center is subjected to malicious attack and single-point failure occurs, not only the cognitive radio system is crashed, but also the privacy of the perceived user can be revealed. The distributed trust management does not rely on coordination of the centralized nodes, and the problem of single point failure in the centralized trust management is solved. However, spectrum sensing based on traditional distributed trust management faces the following two aspects: firstly, due to the dynamic property and autonomy of the network, the perception user cannot be guaranteed to adopt a unified trust management rule, so that the difference exists in the reputation value of the perception user in the whole network range, and the consistency of the global decision is affected; secondly, due to the distributivity of trust management, malicious perception users can unilaterally maliciously make sense or tamper with reputation data, so that honest perception users cannot judge the authenticity and effectiveness of the reputation data in a network, and the reliability of global decision is reduced.
Disclosure of Invention
The invention aims to provide a trusted spectrum sensing method based on a blockchain technology, which is high in safety, consistency and timeliness.
The technical solution for realizing the purpose of the invention is as follows: a trusted spectrum sensing method based on a blockchain technology comprises the following steps:
step 1, a sensing user locally senses the spectrum occupation condition of wireless communication through energy detection, and packages a sensing result into a transaction;
step 2, the perceived user signs the transaction by using the private key of each perceived user and then issues the transaction to the cognitive radio network;
Step 3, the perceived user receives and verifies the transactions from other users in the cognitive radio network, and the verified transactions are stored in a local transaction pool of the perceived user;
Step 4, the perception user selects a group of transactions to assemble a pre-issued block according to each user credit value recorded on the block chain, global decision is made on the spectrum occupation condition by aggregating the transactions and the corresponding credit values in the block, and the credit values of the perception user are updated according to the global decision result;
The perceived user makes a global decision on the spectrum occupation situation by aggregating the transactions and the corresponding reputation values in the block, specifically as follows:
The calculation formula of the global decision is as follows:
wherein Γ j (k) represents the log-likelihood ratio of the kth perceived time slot perceived user j;
Lambda is a detection threshold value, omega j (k) represents the reputation weight of a kth perception time slot perception user j, and a calculation formula is as follows:
Wherein r j (k-1) represents the reputation value of perceived user j at the (k-1) th perceived time slot; Representing a collection The set of reputation values corresponding to the perceived user at the kth-1 perceived time slot,Representing a set of perceived users corresponding to transactions contained in a kth perceived time slot pre-release block; omega' j (k) represents the normalized reputation value of the kth perceived slot perceived user j;
step 5, a mixed consensus protocol based on workload certification and rights and interests certification is adopted among perceived users to acquire the right of issuing a new block, and then the new block is broadcasted to a cognitive radio network;
and 6, verifying the released new block by other perceived users in the cognitive radio network, accessing the new block into a local block chain after verification is successful, and storing and updating a global decision result and a reputation value according to the content of the block.
Compared with the prior art, the invention has the remarkable advantages that: (1) The transactions issued by the perception users with high reputation values are selected to be assembled into the pre-issued blocks, so that the possibility that malicious users participate in global decisions is reduced, the reliability of consensus on a chain is improved, and the safety of spectrum perception is improved; (2) The reputation value of the perception user is taken as the benefit, the higher the reputation value accumulated by the perception user is, the smaller the corresponding block-out difficulty is, compared with a workload proof consensus protocol, the block-out efficiency is improved, and the timeliness of global decision is improved; (3) The introduction of the workload evidence increases the randomness of the output blocks, reduces the harm caused by monopoly of the credit value and improves the reliability of global decision compared with the rights and interests evidence consensus protocol.
Drawings
FIG. 1 is a flow chart of a trusted spectrum sensing method based on blockchain technology.
FIG. 2 is a graph of time-dependence of different common protocol blockchain exit blocks in an embodiment of the invention.
Fig. 3 is a diagram showing comparison of security performance of different consensus protocols under a malicious user attack in an embodiment of the present invention.
Detailed Description
The invention will now be described in further detail with reference to the drawings and to specific examples.
As shown in fig. 1, the trusted spectrum sensing method based on the blockchain technology of the invention comprises the following steps:
step 1, a sensing user locally senses the spectrum occupation condition of wireless communication through energy detection, and packages a sensing result into a transaction;
step 2, the perceived user signs the transaction by using the private key of each perceived user and then issues the transaction to the cognitive radio network;
Step 3, the perceived user receives and verifies the transactions from other users in the cognitive radio network, and the verified transactions are stored in a local transaction pool of the perceived user;
Step 4, the perception user selects a group of transactions to assemble a pre-issued block according to each user credit value recorded on the block chain, global decision is made on the spectrum occupation condition by aggregating the transactions and the corresponding credit values in the block, and the credit values of the perception user are updated according to the global decision result;
step 5, a mixed consensus protocol based on workload certification and rights and interests certification is adopted among perceived users to acquire the right of issuing a new block, and then the new block is broadcasted to a cognitive radio network;
and 6, verifying the released new block by other perceived users in the cognitive radio network, accessing the new block into a local block chain after verification is successful, and storing and updating a global decision result and a reputation value according to the content of the block.
Further, the sensing user in step 1 senses the spectrum occupation locally through energy detection, and packages the sensing result into a transaction, which is specifically as follows:
Step 1.1, using u i (k) to represent the result of energy detection on the authorized user signal by the perceived user i (i=1, 2,., N) in the kth perceived time slot, the energy detection result of the perceived user i in the kth perceived time slot is represented as:
Wherein, AndRepresenting the assumption that the spectrum is free and occupied, respectively; m represents the sampling times of a sensing time slot; s (m) is a signal sent by an authorized user; h i (k) is a channel fading coefficient and is set to be constant for at least one perceived time slot; the detection process is interfered by Gaussian white noise v i(m)～CN(0,σi 2); in order not to lose generality, s (m) and v i (m) are independent of each other;
in the formula (1), u i (k) is the sum of squares of M Gaussian random variables, and when M is more than or equal to 10, u i (k) gradually obeys normal distribution, namely:
Wherein, gamma i(k)＝|hi(k)|2/σi 2 represents the local signal-to-noise ratio obtained by observing the authorized user signal by the perceived user i in the kth perceived time slot;
Step 1.2, using the nesmann pearson criterion to decide the energy detection result u i (k), specifically as follows:
The log-likelihood ratio Γ i (k) for the kth perceived time slot perceived user i is:
Wherein, Is shown inThe probability density of the energy detection result u i (k) under the condition of true; Is shown in Under the condition of false, the probability density of the energy detection result u i (k);
Based on the log-likelihood ratio Γ i (k), the local decision criteria of the perceived user are:
Wherein λ is a local detection threshold of the sensing user, if Γ i (k) is less than or equal to λ, it is assumed that H 0 is true, that is, the sensing user i detects that the spectrum is idle in the kth sensing time slot, and the local decision of the sensing user i is denoted as d i (k) =0; similarly, if Γ i (k) > λ, it is assumed that H 1 is true, that is, the perceived user i detects that the spectrum is occupied in the kth perceived time slot, and the local decision of the perceived user i is denoted as d i (k) =1;
Step 1.3, the perceived user i packages the perceived result of the perceived user i in the kth perceived time slot, which comprises the log likelihood ratio and the local decision, into a transaction, which is represented by Tx i(k)＝<Γi(k),di (k), >.
Further, the perceived user signs the transaction with the private key of the perceived user in step 2, and then issues the transaction to the cognitive radio network, specifically as follows:
Perceiving that user i encrypts the transaction with the private key and generates a digital signature is represented as follows:
Wherein, Representing the private key of the perceived user i, the signature algorithm receives the private key and the transaction and outputs a signature O i.
Further, the step 3 of receiving and verifying the transactions from other users in the cognitive radio network by the sensing user, and storing the verified transactions into the local transaction pool thereof, specifically as follows:
step 3.1, because in the asymmetric encryption algorithm, public keys of all perceived users are public, the signature is verified by inquiring the public key corresponding to the signature, and the verification algorithm is expressed as:
Wherein, Representing that the public key of the user i is perceived, receiving the public key, the transaction and the signature by a verification algorithm, and if the public and private key pair accords with the used digital signature scheme, passing the verification;
and 3.2, sensing that the user stores the verified transaction into a local transaction pool of the user.
Further, in step 4, the perceived user selects a group of transactions to assemble a pre-issued block according to each user reputation value recorded on the blockchain, global decision is made on the spectrum occupation condition by aggregating the transactions and the corresponding reputation values in the block, and the reputation values of the perceived user are updated according to the global decision result, specifically as follows:
Step 4.1, a perception user selects a group of transactions to assemble a pre-issued block according to the credit value of each user recorded on the block chain, and the method specifically comprises the following steps:
s (k) represents a set of perceived users corresponding to the transaction included in the kth perceived time slot pre-issue block, namely:
Wherein η represents a reputation threshold, i.e. transactions contained in the pre-release block are released by a perceived user whose reputation value is higher than the reputation threshold; j represents the upper limit on the number of transactions contained in each block specified by the system. ; r j (k) represents the reputation value of perceived user j at the kth perceived time slot.
Step 4.2, the perceived user makes a global decision on the spectrum occupation situation by aggregating the transactions and the corresponding reputation values in the block, specifically as follows:
The calculation formula of the global decision is as follows:
wherein Γ j (k) represents the log-likelihood ratio of the kth perceived time slot perceived user j;
Lambda is a detection threshold value, omega j (k) represents the reputation weight of a kth perception time slot perception user j, and a calculation formula is as follows:
Wherein r j (k-1) represents the reputation value of perceived user j at the (k-1) th perceived time slot; Representing a collection The set of reputation values corresponding to the (k-1) th perception time slot of the perception user; representing a set of perceived users corresponding to transactions contained in a kth perceived time slot pre-release block; omega' j (k) represents the normalized reputation value of the kth perceived slot perceived user j;
step 4.3, the perception user updates the reputation value of the perception user according to the global decision result, and the method specifically comprises the following steps:
Each perceived user updates its own reputation value according to the global decision result of equation (8):
d j (k) represents the local decision to perceive user j at the kth perceived time slot;
Because each block has a limited size, the block can only contain a limited number of transactions, and meanwhile, in order to improve the reliability of global decision results, the perceived user is specified to preferentially select transactions issued by the perceived user with high reputation when the block is assembled, and the reputation value of the perceived user, which is not corresponding to the transactions contained by the block, is kept unchanged in the current block, namely the reputation value recorded by the previous block is kept.
Further, in step 5, a mixed consensus protocol based on workload certification and rights certification is adopted between the perceived users to obtain the right of issuing the new block, and then the new block is broadcasted to the cognitive radio network, specifically as follows:
Step 5.1, the consensus protocol provides that the workload proving difficulty of the perceived user is inversely proportional to the reputation value accumulated by the perceived user, and the relation between the workload proving difficulty and the reputation value is as follows:
Wherein D i (k) represents the difficulty of perceiving the block of user i in the kth perceiving time slot; r i (k-1) represents the reputation value of perceived user i at the (k-1) th perceived time slot; alpha and beta are adjusting parameters, and the influence degree of the reputation value on the block-out difficulty and the final convergence value of the block-out difficulty can be controlled respectively;
step 5.2, based on a mixed consensus protocol of workload certification and rights certification, perceiving the right of the user to compete for the issuing block by solving the following hash problems:
Wherein H (·) represents a hash function (e.g., SHA 256); block header represents other information of the Block header (such as hash of Merkle tree root, timestamp, etc.); d (k) represents a global decision at the kth perceived time slot; nonce represents a random number; representing the public key of the perceived user i; t (-) represents the target value corresponding to the block; d i (k) represents the difficulty of block out of the perceived user i in the kth perceived time slot;
step 5.3, when the perceived user searches the random number meeting the formula (13), obtaining the right of the issuing block;
And 5.4, the perception user broadcasts the new block to the cognitive radio network.
Further, step 6, verifying the released new block by other perceived users in the cognitive radio network, accessing the new block into the local block chain after successful verification, and storing and updating the global decision result and the reputation value according to the content of the block, wherein the method specifically comprises the following steps:
and (3) verifying the released new block by other perception users in the cognitive radio network, wherein the verification comprises the verification of random numbers, the verification of the legality of packaging transactions, the verification of reputation values of the perception users and the verification of the accuracy of global decision results, and after the verification is successful, the new block is accessed into a local block chain, and the global decision results and the reputation values are stored and updated according to the content of the block.
Example 1
The embodiment combines simulation results to illustrate the performance of the proposal provided by the invention, and the simulation conditions are as follows: assuming that the cognitive radio network comprises 50 sensing users, each sensing user uses energy detection to perform spectrum sensing, and the sampling point of one sensing time slot is M=30; the local signal to noise ratio of the primary user signal received by the sensing user is gamma i (k) = -16dB; reputation threshold η=4; setting each perception user to be trusted in the initial stage, wherein the initial reputation value is ri (0) =5, and the adjustment parameter alpha=0.15 and beta= -6; a maximum of 30 transactions issued by the perceived user, i.e., j=30, is set for each perceived user pre-issued block.
To compare the timeliness between the present invention and the conventional consensus algorithm, fig. 2 shows the variation of the block-out time with the block height of different consensus protocols based on the trusted spectrum sensing of the blockchain under the same condition. It can be seen that under the proof of work (PoW) protocol, the graph has a large fluctuation of the block-out time curve, but is always maintained near a certain value, because of the difficulty adjustment mechanism of the PoW, the block-out time can be kept dynamically balanced. Under the proof of rights (PoS) protocol, the chunking time is fixed to a small value in the figure. This is because in PoS, each round of block accounting rights is obtained by the perceived user with the highest reputation value, the process does not need to mine, and the block can be removed after verification transaction, so the block removal time is extremely short and fixed. Under the mixed consensus protocol of PoW and PoS, the block discharging time in the graph is continuously reduced along with the increase of the block height, and simultaneously, certain fluctuation is accompanied, because the mixed consensus protocol links the mining difficulty with the reputation value of the perception user, the block discharging difficulty of the perception user is reduced through the continuous accumulation of the reputation value, and the whole block discharging time is continuously reduced. Therefore, compared with PoW, the efficiency of block output is improved, and therefore the timeliness of global decision is improved.
In order to compare the safety performance between the invention and the traditional consensus algorithm, malicious perception users exist in the cognitive radio network, and the reliability of global decision is reduced by packing low-reputation transactions. Fig. 3 illustrates the security performance of a blockchain-based trusted spectrum awareness for different consensus protocols under malicious awareness user attacks. It can be seen from the figure that under the same false alarm probability, as the number of malicious perceived users increases, the detection probability of the system is continuously reduced, i.e. the success rate of maliciously perceived users is continuously increased. The detection probability of the block chain system adopting the PoS is obviously lower than that of the mixed consensus protocol designed by the PoW and the invention. Because in the PoS, the block accounting right is completely determined by the reputation value of the perceived user, the malicious perceived user can more easily obtain the block right after accumulating the reputation value, and the computing power of the malicious perceived user is increased along with the increase of the number of the malicious perceived users, so that the possibility of the malicious perceived user being wrongly successful is increased, and the perception performance is reduced. Compared with the PoS, the mixed consensus protocol based on the PoW and the PoS reduces the hazard caused by monopoly of the credit value under the condition of guaranteeing the timeliness of the block, thereby improving the safety of global decision.
Claims (9)
1. The trusted spectrum sensing method based on the blockchain technology is characterized by comprising the following steps of:
step 1, a sensing user locally senses the spectrum occupation condition of wireless communication through energy detection, and packages a sensing result into a transaction;
step 2, the perceived user signs the transaction by using the private key of each perceived user and then issues the transaction to the cognitive radio network;
Step 3, the perceived user receives and verifies the transactions from other users in the cognitive radio network, and the verified transactions are stored in a local transaction pool of the perceived user;
Step 4, the perception user selects a group of transactions to assemble a pre-issued block according to each user credit value recorded on the block chain, global decision is made on the spectrum occupation condition by aggregating the transactions and the corresponding credit values in the block, and the credit values of the perception user are updated according to the global decision result;
The perceived user makes a global decision on the spectrum occupation situation by aggregating the transactions and the corresponding reputation values in the block, specifically as follows:
The calculation formula of the global decision is as follows:
wherein Γ j (k) represents the log-likelihood ratio of the kth perceived time slot perceived user j;
Lambda is a detection threshold value, omega j (k) represents the reputation weight of a kth perception time slot perception user j, and a calculation formula is as follows:
Wherein r j (k-1) represents the reputation value of perceived user j at the (k-1) th perceived time slot; representing the set of reputation values for perceived users contained in set S (k) corresponding to the kth-1 perceived time slot, Representing a set of perceived users corresponding to transactions contained in a kth perceived time slot pre-release block; omega j' (k) represents the normalized reputation value of the kth perceived slot perceived user j;
step 5, a mixed consensus protocol based on workload certification and rights and interests certification is adopted among perceived users to acquire the right of issuing a new block, and then the new block is broadcasted to a cognitive radio network;
and 6, verifying the released new block by other perceived users in the cognitive radio network, accessing the new block into a local block chain after verification is successful, and storing and updating a global decision result and a reputation value according to the content of the block.
2. The method for perceiving a trusted spectrum based on a blockchain technology according to claim 1, wherein the perceiving user in step 1 perceives the occupation situation of the spectrum of the wireless communication locally through energy detection, and packages the perceiving result into a transaction, specifically as follows:
Step 1.1, using u i (k) to represent the result of energy detection on the authorized user signal by the sensing user i in the kth sensing time slot, where i=1, 2, …, N, the energy detection result of the sensing user i in the kth sensing time slot is:
Wherein, AndRepresenting the assumption that the spectrum is free and occupied, respectively; m represents the sampling times of a sensing time slot; s (m) is a signal sent by an authorized user; h i (k) is a channel fading coefficient, and h i (k) is set to be constant at least in one perceived time slot; the detection process is interfered by Gaussian white noise v i(m)～CN(0,σi 2); in order not to lose generality, s (m) and v i (m) are independent of each other;
In the formula (1), u i (k) is the sum of squares of M Gaussian random variables, and when M is more than or equal to 10, u i (k) gradually obeys normal distribution, namely:
Wherein, gamma i(k)＝|hi(k)|2/σi 2 represents the local signal-to-noise ratio obtained by observing the authorized user signal by the perceived user i in the kth perceived time slot;
Step 1.2, using the nesmann pearson criterion to decide the energy detection result u i (k), specifically as follows:
The log-likelihood ratio Γ i (k) for the kth perceived time slot perceived user i is:
Wherein, Is shown inThe probability density of the energy detection result u i (k) under the condition of true; Is shown in Under the condition of false, the probability density of the energy detection result u i (k);
Based on the log-likelihood ratio Γ i (k), the local decision criteria of the perceived user are:
Wherein λ is a local detection threshold of the sensing user, if Γ i (k) is less than or equal to λ, it is assumed that H 0 is true, that is, the sensing user i detects that the spectrum is idle in the kth sensing time slot, and the local decision of the sensing user i is denoted as d i (k) =0; similarly, if Γ i (k) > λ, it is assumed that H 1 is true, that is, the perceived user i detects that the spectrum is occupied in the kth perceived time slot, and the local decision of the perceived user i is denoted as d i (k) =1;
Step 1.3, the perceived user i packages the perceived result of the perceived user i in the kth perceived time slot, including the log likelihood ratio and the local decision, into a transaction, which is represented by Tx i(k)＝<Γi(k),di (k), >.
3. The method for trusted spectrum sensing based on blockchain technology as defined in claim 2, wherein the sensing user in step 2 signs the transaction with the private key of each of the sensing users, specifically as follows:
the method for perceiving the user i to encrypt the transaction through the private key and generating the digital signature comprises the following steps:
Wherein, Representing the private key of the perceived user i, the signature algorithm receives the private key and the transaction and outputs a signature O i.
4. The method for trusted spectrum sensing based on blockchain technology as in claim 3, wherein the sensing user in step 3 receives and verifies transactions from other users in the cognitive radio network, and stores the verified transactions into its own local transaction pool, specifically as follows:
Step 3.1, because the public key of each perceived user is public in the asymmetric encryption algorithm, the signature is verified by inquiring the public key corresponding to the signature, and the verification algorithm is as follows:
Wherein, Representing that the public key of the user i is perceived, receiving the public key, the transaction and the signature by a verification algorithm, and if the public and private key pair accords with the used digital signature scheme, passing the verification;
and 3.2, sensing that the user stores the verified transaction into a local transaction pool of the user.
5. The method for perceiving a trusted spectrum based on a blockchain technology according to claim 1, wherein the perceiving user in step 4 selects a group of transactions to assemble a pre-issued block according to each user reputation value recorded on the blockchain, makes a global decision on the spectrum occupation condition by aggregating the transactions and the corresponding reputation values in the block, and updates the own reputation value according to the global decision result, specifically as follows:
step 4.1, a perception user selects a group of transactions to assemble a pre-issued block according to each user credit value recorded on the block chain;
step 4.2, the perceived user makes a global decision on the spectrum occupation situation by aggregating the transactions and the corresponding reputation values in the block;
and 4.3, the perception user updates the reputation value of the perception user according to the global decision result.
6. The method for trusted spectrum sensing based on blockchain technology as defined in claim 5, wherein the sensing user in step 4.1 selects a group of transactions to assemble into pre-issued blocks according to each user reputation value recorded on the blockchain, specifically as follows:
By using Representing a set of perceived users corresponding to the transaction contained in the kth perceived time slot pre-issue block, namely:
Wherein η represents a reputation threshold, i.e. transactions contained in the pre-release block are released by a perceived user whose reputation value is higher than the reputation threshold; j represents an upper limit on the number of transactions contained in each block specified by the system; r j (k) represents the reputation value of perceived user j at the kth perceived time slot.
7. The method for trusted spectrum sensing based on blockchain technology as in claim 5, wherein the step 4.3 of sensing the user updates the reputation value of the user according to the global decision result is as follows:
Each perceived user updates its own reputation value according to the global decision result of equation (8):
d j (k) represents the local decision to perceive user j at the kth perceived time slot;
because each block has a limited size, the block can only contain a limited number of transactions, and meanwhile, when the block is assembled, a perceiving user is specified to preferentially select transactions issued by perceiving users with high reputation, and the reputation value of the perceiving user, which is not corresponded to the transactions contained by the block, is kept unchanged in the current block, namely the reputation value recorded by the previous block is kept.
8. The method for trusted spectrum sensing based on blockchain technology according to claim 1, wherein the sensing users in step 5 adopt a mixed consensus protocol based on workload certification and rights certification to obtain the right to issue new blocks, and then broadcast the new blocks to the cognitive radio network, specifically as follows:
step 5.1, sensing the relation between the workload proving difficulty of the user and the reputation value accumulated by the user as follows:
Wherein D i (k) represents the difficulty of perceiving the block of user i in the kth perceiving time slot; r i (k-1) represents the reputation value of perceived user i at the (k-1) th perceived time slot; alpha and beta are adjusting parameters, and the influence degree of the reputation value on the block-out difficulty and the final convergence value of the block-out difficulty are respectively controlled;
step 5.2, based on a mixed consensus protocol of workload certification and rights certification, perceiving the right of the user to compete for the issuing block by solving the following hash problems:
Wherein H (·) represents a hash function; block header indicates other information of Block header; d (k) represents a global decision at the kth perceived time slot; nonce represents a random number; representing the public key of the perceived user i; t (-) represents the target value corresponding to the block; d i (k) represents the difficulty of block out of the perceived user i in the kth perceived time slot;
step 5.3, when the perceived user searches the random number meeting the formula (13), obtaining the right of the issuing block;
And 5.4, the perception user broadcasts the new block to the cognitive radio network.
9. The method for trusted spectrum sensing based on blockchain technology according to claim 1, wherein the step 6 is characterized in that other sensing users in the cognitive radio network verify the released new block, and after the verification is successful, the new block is accessed to the local blockchain, and the global decision result and the reputation value are stored and updated according to the content of the block, specifically as follows:
and (3) verifying the released new block by other perception users in the cognitive radio network, wherein the verification comprises the verification of random numbers, the verification of the legality of packaging transactions, the verification of reputation values of the perception users and the verification of the accuracy of global decision results, and after the verification is successful, the new block is accessed into a local block chain, and the global decision results and the reputation values are stored and updated according to the content of the block.
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