Method, apparatus and device for spectrum coordination and endogenous motivation of license chain, and medium

Abstract

This invention discloses a method, apparatus, device, and medium for permissioned blockchain spectrum collaborative sensing and endogenous incentives. The method includes: a task management server generating task configuration data; sensing terminal nodes parsing the task configuration data, sending a transaction request to the blockchain node to lock a deposit, and switching to an active working state after confirming the deposit lock; collecting spectrum signals according to the task configuration data and generating a local sensing confidence vector; generating an encrypted sensing evidence package; the blockchain node receiving the encrypted sensing evidence package, verifying the signature, extracting the local sensing confidence vectors of multiple sensing terminal nodes, determining the global spectrum judgment result of the target frequency band through a preset weighted fusion algorithm, and obtaining a node quality score; and issuing reward tokens or deducting deposits from the account address of the sensing terminal nodes according to the node quality score and the deposit lock status recorded in the distributed ledger.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, specifically relating to a method, apparatus, device, and medium for licensed chain spectrum collaborative sensing and endogenous excitation. Background Technology

[0002] With the arrival of the 6G era of the Internet of Everything, spectrum resources, as the new oil of the digital society, are experiencing explosive growth in demand. However, current spectrum management models are still largely stuck in the static licensing stage, leading to increasingly acute contradictions between low frequency band utilization and congestion in hotspot areas. Although Distributed Spectrum Sensing (DSS) technology can utilize secondary users (SUs) to collaboratively detect idle frequency bands to improve resource utilization, it still faces severe technical challenges in large-scale deployment.

[0003] First, the credibility and security of spectrum data are difficult to guarantee. In open and non-cooperative distributed environments, sensing nodes are often owned by different entities, making the system highly vulnerable to Spectrum Sensing Data Forgery (SSDF) attacks launched by malicious nodes. Malicious nodes may mislead global decisions by forging, tampering with, or speculatively reporting false sensing results. Existing solutions often rely on the weak security assumption that nodes are honest and legitimate, lacking an effective mechanism for confirming ownership of the data source. Furthermore, traditional centralized converged architectures are prone to single points of failure when faced with high concurrency requests from massive connections, and centralized processing methods are insufficient to meet the performance requirements for millisecond-level sensing response and trusted auditing.

[0004] Secondly, there is a lack of long-term and effective endogenous incentive mechanisms. Sensing nodes need to consume their own computing and energy resources to participate in spectrum collaboration, and the lack of a reasonable compensation mechanism leads to insufficient motivation for node participation. Existing incentive models are mostly based on static rules, which cannot be precisely adjusted according to dynamic quality indicators such as data timeliness, spatial coverage, and consistency, resulting in nodes contributing high-quality data not receiving commensurate rewards. Although some research has attempted to introduce blockchain or game theory to solve the incentive problem, the high consensus overhead of traditional public blockchains and the failure of most inventions to integrate the sensing process, rights confirmation mechanism, and dynamic transactions into a closed loop still pose significant challenges in achieving trusted spectrum autonomy that balances high throughput, low latency, and strong robustness.

[0005] Therefore, there is an urgent need for a spectrum collaborative sensing system that can achieve data source ownership confirmation, strong resistance to malicious attacks, and has a dynamic quality incentive closed loop. Summary of the Invention

[0006] In view of this, the main objective of the present invention is to provide a method, apparatus, device and medium for licensed chain spectrum collaborative sensing and endogenous excitation.

[0007] To achieve the above objectives, the technical invention of this invention is implemented as follows:

[0008] A permissioned chain spectrum collaborative sensing and endogenous incentive method, characterized in that the method includes:

[0009] The task management server generates task configuration data, including target frequency band, time window, and incentive budget, based on spectrum monitoring requirements, and broadcasts it to the blockchain network.

[0010] The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock.

[0011] The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector;

[0012] The sensing terminal node digitally signs the local sensing confidence vector using a locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node.

[0013] The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger.

[0014] The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score.

[0015] The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

[0016] Preferably, the set of constraint parameters for the task configuration data includes: ,in Indicates the target frequency band desired by the mission. It is the time window for perception. This indicates the pre-defined perceived reward. This indicates the incentive fund pool reserved by the system. This indicates the minimum deposit percentage that participating nodes must lock, used to deter malicious behavior.

[0017] Preferably, the sensing terminal node in an active working state collects spectral signals according to the task configuration data and generates a local sensing confidence vector, specifically including: the sensing terminal node using a deep decision model to process the collected spectral feature matrix. Process the data and output the confidence probability vector of the occupancy status of the primary user (PU). ;in This indicates that the spectrum is occupied. This indicates that the spectrum is idle.

[0018] Preferably, the sensing terminal node digitally signs the local sensing confidence vector using its locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node. Specifically, this includes the sensing terminal node using its unique private key... Digitally sign the complete perception data packet ,in, For including task number Node identity Perceived confidence and geographic timestamp The original data packet;

[0019] Preferably, the step of determining the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm specifically includes: the preset weighted fusion algorithm adopts a weighted log-probability fusion algorithm to calculate the global decision statistic. ,in It is the local perceived confidence level. This represents the sensing results of k frequency bands sensed by N sensing nodes. It is weight;

[0020] Then perform weighting Dynamic adjustment, by taking node reputation into account Spatial correlation and reporting delay Determine weights ;

[0021] when Determine the main user's activity level at any time. Otherwise, the frequency band is considered idle. ).

[0022] Preferably, the blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score, specifically including: based on... Determine node quality score ,in, This represents the Jensen-Shannon distance between the node's reported probability and the global mean. The robust mean is calculated by weighting the values.

[0023] Preferably, the blockchain node issues reward tokens to the account address of the sensing terminal node or deducts the deposit based on the node quality score and the deposit lock status recorded in the distributed ledger, specifically including:

[0024] according to SpecCoin settlement is automatically triggered, and honest nodes receive dynamic rewards. Malicious behavior will trigger a penalty function. To deduct the deposit ,in, This is the basic reward amount. It is an incentive coefficient, used to amplify the reward effect of high-quality data. For node quality, The average quality. The penalty deduction is due to substandard data quality or malicious behavior.

[0025] A permissioned blockchain spectrum collaborative sensing and intrinsic incentive device, the device comprising a task management server, sensing terminal nodes, and blockchain nodes;

[0026] The task management server is used to generate task configuration data, including target frequency band, time window and incentive budget, according to spectrum monitoring requirements, and broadcast it to the blockchain network.

[0027] The sensing terminal node is used to parse the task configuration data and send a transaction request to the blockchain node to lock the deposit; after confirming that the deposit is locked, it switches to an active working state, collects spectrum signals according to the task configuration data to generate a local sensing confidence vector, and uses the locally stored private key to digitally sign the local sensing confidence vector to generate an encrypted sensing evidence package and send it to the blockchain node.

[0028] The blockchain node is used to run smart contracts to perform the following operations: receive the encrypted sensing evidence package and verify the legality of the signature; after verification, extract the local sensing confidence vectors of multiple sensing terminal nodes, determine the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and record the global spectrum decision result in the distributed ledger; based on the verified local sensing confidence vectors and the global spectrum decision result, determine the Jensen-Shannon distance between them to obtain a node quality score; according to the node quality score and the deposit lock status recorded in the distributed ledger, automatically execute asset transfer operations to issue reward tokens to the account address of the sensing terminal node or deduct the deposit.

[0029] A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0030] The task management server generates task configuration data, including target frequency band, time window, and incentive budget, based on spectrum monitoring requirements, and broadcasts it to the blockchain network.

[0031] The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock.

[0032] The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector;

[0033] The sensing terminal node digitally signs the local sensing confidence vector using a locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node.

[0034] The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger.

[0035] The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score.

[0036] The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

[0037] A computer device includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the following steps:

[0038] The task management server generates task configuration data, including target frequency band, time window, and incentive budget, based on spectrum monitoring requirements, and broadcasts it to the blockchain network.

[0039] The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock.

[0040] The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector;

[0041] The sensing terminal node digitally signs the local sensing confidence vector using a locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node.

[0042] The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger.

[0043] The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score.

[0044] The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

[0045] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0046] This invention combines a deposit locking mechanism with dynamic token settlement. It not only distributes rewards based on quality scores but also automatically deducts deposits for malicious behavior based on the deposit locking status in the distributed ledger. This forces nodes to honestly report high-quality data in order to protect their deposits and obtain higher rewards. Compared to a fixed reward mechanism, this quality-based dynamic incentive significantly improves the average participation rate and data quality of nodes, solving the problem of insufficient node participation motivation in distributed scenarios. Attached Figure Description

[0047] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and, together with their descriptions, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0048] Figure 1 This is a schematic diagram of the overall structure of the licensed chain spectrum collaborative sensing and endogenous excitation device provided in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of the state transition logic of the perception task state machine provided in an embodiment of the present invention;

[0050] Figure 3 This is a comparison chart of the average execution latency of the embodiments of the present invention and the traditional solution;

[0051] Figure 4 This is a comparison chart of throughput (TPS) between embodiments of the present invention and conventional solutions;

[0052] Figure 5 This is a comparison chart of reconstruction probabilities between the present invention and the traditional model;

[0053] Figure 6 This is a comparison chart of spectrum utilization and TPS performance between the present invention embodiment and the traditional solution under different proportions of malicious nodes. Detailed Implementation

[0054] To make the objectives, technical features, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of the invention.

[0055] In the accompanying drawings of this embodiment, the same or similar reference numerals correspond to the same or similar components. In the description of this invention, it should be understood that the terms "up," "down," "left," "right," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the accompanying drawings are only for illustrative purposes and should not be construed as limiting this patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0056] It should be noted that, in this document, the terms include, encompass, or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "including a…" does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0057] This invention provides a method for licensed chain spectrum collaborative sensing and endogenous incentives, such as... Figure 1 , 2 As shown, the method includes:

[0058] Step 101: The task management server generates task configuration data, including target frequency band, time window and incentive budget, based on the spectrum monitoring requirements, and broadcasts it to the blockchain network;

[0059] Specifically, the task management server (typically deployed by spectrum service providers or regulatory agencies) publishes sensing tasks on the blockchain network based on real-time spectrum demand through task management contracts deployed in the network. The publisher needs to set a specific set of constraint parameters for the sensing task. ,in Indicates the target frequency band desired by the mission. It is the time window for perception. This indicates the pre-defined perceived reward. This indicates the incentive fund pool reserved by the system. This indicates the minimum deposit percentage that participating nodes must lock, used to deter malicious behavior.

[0060] After the task configuration data is generated, the smart contract will create a corresponding task record on the blockchain ledger, use the state machine module to automatically migrate the life cycle state of the task to the CREATED stage, and broadcast the task information to the sensing nodes of the entire network, waiting for the nodes to claim it.

[0061] Step 102: The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock.

[0062] Specifically, after receiving the broadcast task information, the distributed sensing terminal node (SU) initiates a task claim request by calling the ClaimTask interface provided by the smart contract.

[0063] To prevent malicious nodes from damaging the system at no cost, participating nodes are required to lock a certain amount of tokens as a deposit. The amount of deposit that a node must lock must meet the minimum threshold defined in the task configuration parameters, that is, not less than the product of a preset ratio and the task reward;

[0064] Once the blockchain node confirms that the sensing terminal node has sufficient account balance and successfully locks the deposit, the smart contract establishes a defined node-task mapping relationship on the chain. At this point, the state machine module (FSM) deployed inside the contract automatically recognizes the locking event and drives the node's lifecycle state in the current task to formally migrate to the ACTIVE stage, thereby authorizing the sensing terminal node to start subsequent physical spectrum sensing operations.

[0065] Step 103: The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector;

[0066] Specifically, the sensing terminal node in an active working state performs spectrum sampling and decision-making tasks at its physical location. The node uses a locally pre-trained deep decision-making model to process the collected spectrum feature matrix. The processing aims to transform analog spectral signals at the physical layer into computable and verifiable evidence in the digital world. After model computation, the sensing terminal node outputs a confidence probability vector for the occupancy status of the primary user (PU). ;in This indicates that the spectrum is occupied. This indicates that the spectrum is idle.

[0067] Step 104: The sensing terminal node digitally signs the local sensing confidence vector using the private key stored locally, generates an encrypted sensing evidence package, and sends it to the blockchain node;

[0068] Specifically, the sensing terminal node utilizes its unique private key. Digitally sign the complete perception data packet ,in, For including task number Node identity Perceived confidence and geographic timestamp The original data packet;

[0069] After the perception layer transmits the uploaded data to the blockchain, the on-chain ledger only stores its hash digest. The node uploads the signature and original perception data to the blockchain network; the data has traceability and tamper-proof content before entering the ledger; the task status automatically transitions to the VERIFYING stage.

[0070] Step 105: The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger.

[0071] Specifically, after receiving data, the blockchain verification node performs automated verification and multi-source data fusion through smart contracts.

[0072] First, signature and compliance verification are performed based on the public key. Automated verification To ensure the legitimacy of the data and prevent it from being tampered with during transmission.

[0073] The verified data hash digest is written into the ledger.

[0074] Then, a weighted fusion decision is made. Data from multiple nodes is extracted through verification and incentive settlement contracts, and a weighted log-probability fusion algorithm is executed to calculate the global statistic. ,in It is the local perceived confidence level. This represents the sensing results of k frequency bands sensed by N sensing nodes. It is weight;

[0075] Then perform weighting Dynamic adjustment, by taking node reputation into account Spatial correlation and reporting delay Determine weights ;

[0076] Finally, a global decision is made and output. Determine the main user's activity level at any time. Otherwise, the frequency band is considered idle. Compared to non-state machine inventions, the average execution latency of this invention is reduced by approximately 53% (e.g., Figure 3 Throughput (TPS) increased by approximately 40% (e.g.) Figure 4 ).

[0077] Step 106: The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score;

[0078] Specifically, a robust global mean vector is first constructed to provide a truth benchmark resistant to interference for quality assessment. Blockchain nodes (or their running verification smart contracts) will comprehensively consider the spatial correlation of each sensing terminal node (to identify spatial outliers), reporting latency (to ensure data timeliness), and historical reputation (based on Beta distribution parameters) to dynamically calculate the fusion weight of each node in the current sensing cycle.

[0079] Subsequently, the fusion weights are used to perform a weighted average on the multiple local awareness confidence vectors that have passed signature verification, thereby generating a robust global mean vector, which can effectively dilute the impact of malicious or low-quality nodes on the global decision benchmark.

[0080] Next, the reporting deviation of each node is calculated based on this robust benchmark. Each blockchain node calculates the Jensen-Shannon distance between its local perception confidence vector and the robust global mean vector. The Jensen-Shannon distance, as a symmetric and smooth divergence measure, can accurately quantify the degree of difference between two probability distributions (i.e., the probability of the spectrum state reported by the node and the global consensus probability), and has high sensitivity for identifying spoofed spectrum data (SSDF attacks).

[0081] The specific formula for calculating the Jensen–Shannon distance is as follows: This distance metric effectively measures the deviation between node-reported data and global consensus, thus providing a quantitative basis for subsequent reward and punishment settlements.

[0082] To accurately quantify node contributions based on perceived objective performance and achieve incentive compatibility, blockchain nodes utilize verification contracts to calculate data quality scores, based on... Determine node quality score ,in, This represents the Jensen-Shannon distance between the node's reported probability and the global mean. The robust mean is calculated by weighting the values.

[0083] Step 107: The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

[0084] Specifically, according to SpecCoin settlement is automatically triggered, and honest nodes receive dynamic rewards. Malicious behavior will trigger a penalty function. To deduct the deposit ,in, This is the basic reward amount. It is an incentive coefficient, used to amplify the reward effect of high-quality data. For node quality, The average quality. The penalty deduction is due to substandard data quality or malicious behavior.

[0085] This dynamic incentive mechanism establishes a profit gap between honest and malicious nodes, and the task status then transitions to either SETTLED (settled) or SLASHED (penalized) stages.

[0086] Based on perceived quality, the long-term reputation parameters of nodes are dynamically adjusted using a Beta distribution model. Based on the updated reputation parameters, the node's fusion weight in the next perception cycle is adjusted, and the task state transitions to either the SETTLED or SLASHED stage. Reputation parameters Updated dynamically based on task verification results: ,in To update the step size, update To adjust the real-time reputation based on the Beta distribution, the expected reputation is: This information is then fed back into the next round of weight allocation, while also supporting automated bidding and leasing of verified spectrum resources to achieve value recycling.

[0087] As shown in Table 1, even in extreme environments where the proportion of malicious nodes reaches as high as 50%, the malicious node identification rate of this invention can still be maintained at over 93.2%. The revenue of honest nodes is an order of magnitude higher than that of malicious nodes, effectively establishing a revenue "scissors difference".

[0088] Table 1. Effects of the Token Incentive Mechanism

[0089]

[0090] Next, the participation rate, average data quality, and fairness of rewards were compared under three mechanisms: dynamic incentive, fixed reward, and no penalty. All nodes had the same initial reputation, and the deposit ratio was 10% of the task budget; the network size was fixed at 30 nodes, with 30% being malicious nodes. 100 rounds of spectrum sensing tasks were simulated, with nodes able to choose whether to participate in each round. The results are shown in Table 2. Compared to the fixed reward mechanism, this invention improved the participation rate by approximately 34%, the average data quality by 21%, and the reward-quality correlation by more than 2 times, indicating that the token dynamic adjustment mechanism can effectively incentivize high-quality nodes and suppress cheating behavior.

[0091] Table 2 Comparison of Token Incentives

[0092]

[0093] The application layer transforms the perceived results into tradable digital assets, enabling the efficient transfer of spectrum resources. Spectrum asset mapping: Verified idle frequency bands are encapsulated as resource identifiers. Includes available probability and dynamic pricing .

[0094] Spectrum users submit bidding requests via API The smart contract uses a utility-maximizing rule to select the successful bidder and automatically deducts SpecCoin to complete the rental settlement. ,in For margin. When When the minimum bidding threshold is met, the smart contract automatically triggers resource allocation and settlement transactions. The system adjusts the allocation based on real-time demand intensity. Adjust price When the RentExpire event is triggered upon lease expiration, the system automatically releases the resource status, allowing the frequency band to re-enter the sensing loop. The performance test results of this invention are shown in Table 3, including the proportion of malicious nodes. Even in a complex environment where the proportion of malicious nodes is 20% and the number of nodes reaches 40, the system can still maintain a spectrum utilization rate of 90.2% and a stable throughput of 156tx / s.

[0095] Table 3 State Machine Performance Test

[0096]

[0097] Furthermore, this invention compares with centralized architectures under different malicious rates, analyzing spectrum utilization in terms of TPS, with results as follows: Figure 6 As shown, the overall performance of this invention is quite excellent, far exceeding traditional solutions in both spectrum utilization and TPS.

[0098] This invention is based on a permissioned blockchain architecture and smart contract technology. After collecting data, the sensing terminal node must use its private key to digitally sign the sensing confidence vector and generate an encrypted evidence package. The blockchain node verifies the legality of the signature before recording the result in the distributed ledger, ensuring the non-repudiation of the sensing data at the source of collection and realizing full-link traceability of data from generation to fusion, effectively preventing data tampering during transmission. At the same time, the decentralized architecture avoids the single point of failure problem of traditional centralized servers and improves the stability of the system.

[0099] By employing a quality scoring mechanism based on Jensen-Shannon (JS) divergence, the robustness and malicious detection capabilities of the system are significantly improved. This invention uses JS divergence to quantify the difference between locally perceived data and global decision results, thereby obtaining accurate node quality scores. Compared to traditional simple majority voting or averaging methods, JS divergence can more sensitively identify anomalous data that deviates from global consensus. Experimental data shows that even in extreme environments with a high proportion of malicious nodes (e.g., 50%), it can still maintain a high malicious detection rate (e.g., above 93%) and spectrum utilization, effectively resisting SSDF attacks.

[0100] This invention combines a deposit locking mechanism with dynamic token settlement. It not only distributes rewards based on quality scores but also automatically deducts deposits for malicious behavior based on the deposit locking status in the distributed ledger. This forces nodes to honestly report high-quality data in order to protect their deposits and obtain higher rewards. Compared to a fixed reward mechanism, this quality-based dynamic incentive significantly improves the average participation rate and data quality of nodes, solving the problem of insufficient node participation motivation in distributed scenarios.

[0101] By integrating task management server-side configuration broadcasting, node automatic response to lock status, and smart contract automatic execution with fund transfer algorithms, this invention deconstructs complex business interactions into deterministic automated processes. Compared to traditional centralized scheduling inventions, this smart contract-based automated execution logic significantly reduces the system's average execution latency (e.g., by approximately 53%) and improves the system's throughput for handling high-concurrency reporting (TPS increase of approximately 40%).

[0102] This invention provides a permissioned blockchain spectrum collaborative sensing and intrinsic incentive device, the device comprising a task management server, sensing terminal nodes, and blockchain nodes;

[0103] The task management server is used to generate task configuration data, including target frequency band, time window and incentive budget, according to spectrum monitoring requirements, and broadcast it to the blockchain network.

[0104] The sensing terminal node is used to parse the task configuration data and send a transaction request to the blockchain node to lock the deposit; after confirming that the deposit is locked, it switches to an active working state, collects spectrum signals according to the task configuration data to generate a local sensing confidence vector, and uses the locally stored private key to digitally sign the local sensing confidence vector to generate an encrypted sensing evidence package and send it to the blockchain node.

[0105] The blockchain node is used to run smart contracts to perform the following operations: receive the encrypted sensing evidence package and verify the legality of the signature; after verification, extract the local sensing confidence vectors of multiple sensing terminal nodes, determine the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and record the global spectrum decision result in the distributed ledger; based on the verified local sensing confidence vectors and the global spectrum decision result, determine the Jensen-Shannon distance between them to obtain a node quality score; according to the node quality score and the deposit lock status recorded in the distributed ledger, automatically execute asset transfer operations to issue reward tokens to the account address of the sensing terminal node or deduct the deposit.

[0106] This invention also provides a computer device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the following steps:

[0107] The task management server generates task configuration data, including target frequency band, time window, and incentive budget, based on spectrum monitoring requirements, and broadcasts it to the blockchain network.

[0108] The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock.

[0109] The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector;

[0110] The sensing terminal node digitally signs the local sensing confidence vector using a locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node.

[0111] The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger.

[0112] The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score.

[0113] The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

[0114] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0115] The task management server generates task configuration data, including target frequency band, time window, and incentive budget, based on spectrum monitoring requirements, and broadcasts it to the blockchain network.

[0116] The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock.

[0117] The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector;

[0118] The sensing terminal node digitally signs the local sensing confidence vector using a locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node.

[0119] The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger.

[0120] The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score.

[0121] The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

[0122] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0123] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for spectrum coordination and endogenous incentive with license chain, characterized in that, The method includes: The task management server generates task configuration data, including target frequency band, time window, and incentive budget, based on spectrum monitoring requirements, and broadcasts it to the blockchain network. The sensing terminal node parses the task configuration data, sends a transaction request to the blockchain node to lock the deposit, and switches to active working state after the blockchain node confirms the deposit lock. The sensing terminal node in an active working state collects spectrum signals according to the task configuration data and generates a local sensing confidence vector; The sensing terminal node digitally signs the local sensing confidence vector using a locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node. The blockchain node receives the encrypted sensing evidence package, calls the smart contract to verify the legality of the signature; after the verification is passed, it extracts the local sensing confidence vectors of multiple sensing terminal nodes, determines the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and records the global spectrum decision result to the distributed ledger. The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score. The blockchain node issues reward tokens or deducts deposits from the account address of the sensing terminal node based on the node quality score and the deposit lock status recorded in the distributed ledger.

2. The permitted chain spectrum collaborative sensing and endogenous incentive method according to claim 1, characterized in that, a set of constraint parameters of the task configuration data: wherein represents a target frequency band expected by the task, is a time window of perception, represents a preset perception reward, represents a system reserved incentive fund pool, represents a minimum proportion of the stake that the participating node needs to lock for restraining malicious behavior.

3. The permitted chain spectrum collaborative sensing and endogenous incentive method according to claim 1 or 2, characterized in that, The active sensing terminal node acquires spectral signals according to the task configuration data and generates a local sensing confidence vector, specifically including: the sensing terminal node using a deep decision model to analyze the acquired spectral feature matrix. Process the data and output the confidence probability vector of the occupancy status of the primary user (PU). ;in This indicates that the spectrum is occupied. This indicates that the spectrum is idle.

4. The permitted chain spectrum collaborative sensing and endogenous incentive method according to claim 3, characterized in that, The sensing terminal node digitally signs the local sensing confidence vector using its locally stored private key, generates an encrypted sensing evidence package, and sends it to the blockchain node. Specifically, this includes the sensing terminal node using its unique private key... Digitally sign the complete perception data packet ,in, For including task number Node identity Perceived confidence and geographic timestamp The original data packet.

5. The permitted chain spectrum collaborative sensing and endogenous incentive method according to claim 4, characterized in that, The step of determining the global spectrum decision result for the target frequency band through a preset weighted fusion algorithm specifically includes: the preset weighted fusion algorithm employing a weighted log-probability fusion algorithm to calculate the global decision statistic. ,in It is the local perceived confidence level. This represents the sensing results of k frequency bands sensed by N sensing nodes. It is weight; Then perform weighting Dynamic adjustment, by taking node reputation into account Spatial correlation and reporting delay Determine weights ; when Determine the main user's activity level at any time. Otherwise, the frequency band is considered idle. ).

6. The permitted chain spectrum collaborative sensing and endogenous incentive method according to claim 5, characterized in that, The blockchain node determines the Jensen-Shannon distance between the verified local perception confidence vector and the global spectrum decision result to obtain a node quality score, specifically including: The fusion weight is dynamically calculated based on the spatial correlation, reporting latency, and historical reputation of each sensing terminal node. The fusion weights are used to weight multiple local perception confidence vectors to generate a robust global mean vector; Calculate the Jensen-Shannon distance between the locally perceived confidence vector and the robust global mean vector; and according to Determine node quality score ,in, This represents the Jensen-Shannon distance between the node's reported probability and the global mean. The robust mean is calculated by weighting the average values. After determining the node quality score, the method further includes: updating the long-term reputation parameter of the Beta distribution model corresponding to the sensing terminal node based on the node quality score. Adjust the fusion weight of the node in the next perception cycle based on the updated reputation parameters.

7. The permitted chain spectrum collaborative sensing and endogenous incentive method according to claim 6, characterized in that, The blockchain node, based on its quality score and the deposit lock status recorded in the distributed ledger, issues reward tokens to the account address of the sensing terminal node or deducts the deposit, specifically including: according to SpecCoin settlement is automatically triggered, and honest nodes receive dynamic rewards. Malicious behavior will trigger a penalty function. To deduct the deposit ,in, This is the basic reward amount. It is an incentive coefficient, used to amplify the reward effect of high-quality data. For node quality, The average quality. The penalty deduction is due to substandard data quality or malicious behavior.

8. A permissioned chain spectrum collaborative sensing and intrinsic excitation device, characterized in that, The device includes a task management server, a sensing terminal node, and a blockchain node. The task management server is used to generate task configuration data, including target frequency band, time window and incentive budget, according to spectrum monitoring requirements, and broadcast it to the blockchain network. The sensing terminal node is used to parse the task configuration data and send a transaction request to the blockchain node to lock the deposit. After confirming the deposit is locked, the system switches to an active working state, collects spectrum signals according to the task configuration to generate a local perception confidence vector, and uses the locally stored private key to digitally sign the local perception confidence vector, generating an encrypted perception evidence package and sending it to the blockchain node. The blockchain node is used to run smart contracts to perform the following operations: receive the encrypted sensing evidence package and verify the legality of the signature; after the verification is passed, extract the local sensing confidence vectors of multiple sensing terminal nodes, determine the global spectrum decision result of the target frequency band through a preset weighted fusion algorithm, and record the global spectrum decision result to the distributed ledger. Based on the verified local perception confidence vector and the global spectrum decision result, the Jensen-Shannon distance between the two is determined to obtain the node quality score; according to the node quality score and the deposit lock status recorded in the distributed ledger, the asset transfer operation is automatically executed to issue reward tokens to the account address of the perception terminal node or deduct the deposit.

9. A computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 7.

10. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 7.

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