Low-orbit satellite spectrum sharing method, device, computer equipment and storage medium

Abstract

The embodiment of the present application belongs to the field of cloud technology / big data / information security technology of artificial intelligence, and relates to a low-orbit satellite spectrum sharing method, device, computer equipment and storage medium, the method comprising: performing a first allocation process on the target spectrum according to a spectrum allocation algorithm based on the Stackelberg game model to obtain a first allocation result; if there is no idle spectrum in the first allocation result, maintaining the current allocation strategy of the target spectrum; if there is an idle spectrum in the first allocation result, placing the idle spectrum into a public spectrum pool; performing a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model. The present application achieves a significant improvement in the utilization rate of idle spectrum in both the time domain and the frequency domain.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a low-orbit satellite spectrum sharing method, apparatus, computer equipment and storage medium. Background Art

[0002] The large-scale deployment of low-orbit constellations has brought high-throughput, low-latency communication services to global users, but it has also brought challenges to the use of spectrum resources. How to reasonably allocate and manage spectrum resources and avoid interference has become an important research topic. Summary of the invention

[0003] The purpose of the embodiments of the present application is to propose a low-orbit satellite spectrum sharing method, device, computer equipment and storage medium to solve the problem of how to reasonably allocate and manage spectrum resources to avoid interference.

[0004] In order to solve the above technical problems, the embodiment of the present application provides a low-orbit satellite spectrum sharing method, which adopts the following technical solution:

[0005] Performing a first allocation process on the target spectrum according to a spectrum allocation algorithm based on the Stackelberg game model to obtain a first allocation result;

[0006] If there is no idle spectrum in the first allocation result, maintaining the current allocation strategy of the target spectrum;

[0007] If there is idle spectrum in the first allocation result, putting the idle spectrum into a public spectrum pool;

[0008] The idle spectrum is subjected to a second allocation process according to a spectrum allocation algorithm based on a bilateral bidding auction game model.

[0009] Furthermore, the spectrum allocation algorithm based on the Stackelberg game model is expressed as:

[0010]

[0011] in, The utility function maximum expression of the strategy set representing the high priority constellation; Indicates the unit spectrum pricing of the high priority constellation to the original users; Indicates the total spectrum capacity; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; represents the cost compensation function; represents the strategy for selecting the i-th high priority constellation; A constant that represents the value of how much spectrum preference coefficient can be accessed.

[0012] Furthermore, the spectrum allocation algorithm based on the bilateral bidding auction game model is expressed as:

[0013]

[0014] in, represents the utility function of low priority constellation satellites; Indicates the spectrum width required by low priority constellation satellites; : represents the bidding information set of low-priority constellation satellites; Represents the revenue function generated by low priority constellation satellite service users; Indicates the duration that the satellites of the low-priority constellation occupy the idle spectrum of the high-priority constellation; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the duration during which idle spectrum of high-priority constellations can be used.

[0015] Furthermore, the step of performing a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model specifically includes the following steps:

[0016] Obtaining the current idle spectrum quantity, auction demand quantity and bidding information of the public spectrum pool;

[0017] Performing a first round of filtering on the bidding information and the idle spectrum according to preset restriction conditions to obtain first filtered bidding information and first filtered idle spectrum;

[0018] If the number of idle spectrums is greater than or equal to the number of bidding requirements, the bidding matching degree of the first filtered bidding information is calculated, the second filtered bidding information with a bidding matching degree greater than 0 is retained in the first filtered bidding information, the bidding utility value of the second filtered bidding information is calculated, and the second filtered bidding information with the largest bidding utility value is matched with the first filtered idle spectrum with the largest spectrum;

[0019] If the number of idle spectrums is less than the number of bidding requirements, calculate the spectrum matching degree of the first filtered idle spectrum, retain the second filtered idle spectrum with a spectrum matching degree greater than 0 in the first filtered idle spectrum, calculate the spectrum utility value of the second filtered idle spectrum, and match the second filtered idle spectrum with the largest spectrum utility value with the first filtered bidding information with the largest demand.

[0020] Further, the bidding matching degree or the spectrum matching degree is expressed as:

[0021]

[0022] in, Indicates the spectrum width required by low priority constellation satellites; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction.

[0023] In order to solve the above technical problems, the embodiment of the present application further provides a low-orbit satellite spectrum sharing device, which adopts the following technical solution:

[0024] A first allocation module, configured to perform a first allocation process on the target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result;

[0025] A first allocation result module, configured to maintain the current allocation strategy of the target spectrum if there is no idle spectrum in the first allocation result;

[0026] A second allocation result module, configured to put the idle spectrum into a public spectrum pool if there is an idle spectrum in the first allocation result;

[0027] The second allocation module is used to perform a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model.

[0028] Furthermore, the spectrum allocation algorithm based on the Stackelberg game model is expressed as:

[0029]

[0030] in, The utility function maximum expression of the strategy set representing the high priority constellation; Indicates the unit spectrum pricing of the high priority constellation to the original users; Indicates the total spectrum capacity; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; represents the cost compensation function; represents the strategy for selecting the i-th high priority constellation; A constant that represents the value of how much spectrum preference coefficient can be accessed.

[0031] Furthermore, the spectrum allocation algorithm based on the bilateral bidding auction game model is expressed as:

[0032]

[0033] in, represents the utility function of low priority constellation satellites; Indicates the spectrum width required by low priority constellation satellites; : represents the bidding information set of low-priority constellation satellites; Represents the revenue function generated by low priority constellation satellite service users; Indicates the duration that the satellites of the low-priority constellation occupy the idle spectrum of the high-priority constellation; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the duration during which idle spectrum of high-priority constellations can be used.

[0034] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0035] The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the low-orbit satellite spectrum sharing method as described above when executing the computer-readable instructions.

[0036] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0037] The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps of the low-orbit satellite spectrum sharing method described above are implemented.

[0038] The present application provides a spectrum sharing method for low-orbit satellites, including: performing a first allocation process on a target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result; if there is no idle spectrum in the first allocation result, maintaining the current allocation strategy of the target spectrum; if there is an idle spectrum in the first allocation result, putting the idle spectrum into a public spectrum pool; performing a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model. Compared with the prior art, the present application proposes a dynamic matching algorithm for idle spectrum of multiple low-orbit satellites based on step-by-step game in a cognitive radio system by studying the dynamic spectrum allocation strategy under non-co-frequency use between multiple low-orbit constellations. The first layer uses a dynamic non-cooperative game under complete information between high-priority constellations and low-priority constellations, and obtains a conclusion that the spectrum sharing strategy can increase the spectrum utilization rate by obtaining the Nash equilibrium; the second layer of the game, by using the bilateral bidding auction game model under incomplete information between multiple low-priority constellation requirements and idle spectrum of high-priority constellations, based on the properties of the greedy algorithm (local optimal solution to global optimal solution), greatly improves the idle spectrum utilization rate in both the time domain and the frequency domain. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0041] Figure 2 is a flow chart for implementing the low-orbit satellite spectrum sharing method provided in Embodiment 1 of the present application;

[0042] Figure 3 This is an environmental schematic diagram of a low-orbit satellite constellation interference scenario provided in Example 1 of the present application;

[0043] Figure 4 It is a structural diagram of an embodiment of a two-layer game model provided in Embodiment 1 of the present application;

[0044] Figure 5 It is a structural diagram of an embodiment of the bilateral bidding auction game model provided in the first embodiment of the present application;

[0045] Figure 6 It is a schematic diagram of M idle frequency bands of high-priority constellations in different states provided in Embodiment 1 of the present application;

[0046] Figure 7 is a flowchart of the second allocation process provided in Example 1 of the present application;

[0047] Figure 8 It is a schematic diagram of an example of time-domain and frequency-domain occupancy of an idle spectrum provided in Embodiment 1 of the present application;

[0048] Fig. 9 is a schematic diagram of a matching degree simulation provided in Example 1 of the present application;

[0049] Fig.10 It is a schematic diagram comparing the idle spectrum utilization rates of three different strategies provided in Example 1 of the present application;

[0050] Fig.11 It is a structural schematic diagram of a low-orbit satellite spectrum sharing device provided in Embodiment 2 of the present application;

[0051] Fig.12 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0052] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as those commonly understood by technicians in the technical field of this application; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0053] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0054] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0055] like Figure 1As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0056] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0057] The terminal device 101 can be any electronic device with a display screen and supporting web browsing. In addition to a laptop computer 1011, a tablet computer 1012 or a mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV), a laptop computer, a desktop computer, etc.

[0058] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0059] It should be noted that the low-orbit satellite spectrum sharing method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the low-orbit satellite spectrum sharing device is generally arranged in the server / terminal device.

[0060] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to the implementation requirements. Embodiment 1

[0061] Continue to refer Figure 2 , shows a flow chart of an embodiment of a low-orbit satellite spectrum sharing method according to the present application. The low-orbit satellite spectrum sharing method includes: step S201, step S202, step S203 and step S204.

[0062] In step S201, a first allocation process is performed on the target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result;

[0063] In step S202, if there is no idle spectrum in the first allocation result, the current allocation strategy of the target spectrum is maintained;

[0064] In step S203, if there is idle spectrum in the first allocation result, the idle spectrum is put into a public spectrum pool;

[0065] In step S204, a second allocation process is performed on the idle spectrum according to a spectrum allocation algorithm based on a double-bid auction game model.

[0066] In the embodiments of this application, see Figure 3 In the interference scenario of the low-orbit satellite constellation shown in the figure, the distance between low-orbit satellite constellations of different priorities is close, the main lobe interference is serious, the coverage area overlaps, and there is strong interference. Due to the frequency conflict, time domain or frequency domain multiplexing is impossible. Therefore, when satellites of constellations of different priorities participate in the game, only the use of different frequencies and at different times is considered.

[0067] In the embodiment of the present application, a system model must be established under the premise of ensuring the quality of service (QOS) of high-priority constellation users. In a certain area, the number of users using satellite communications is certain, and the spectrum used by low-orbit satellites is limited. In this low-orbit satellite network model, n high-priority constellations SAT (Q={1, 2..., N}) (spectrum authorization) and m low-priority constellations CRS (V={1, 2,..., M}) (spectrum cognition) are included. Figure 4 As shown in the figure, SAT, as a spectrum authorization constellation, puts the idle spectrum into the public spectrum pool through real-time spectrum sensing, and then prices the idle spectrum in real time according to market demand. CRS, as a spectrum cognitive constellation, proposes a value strategy for SAT, and CRSs dynamically adjust access strategies through competition.

[0068] In the embodiments of this application, see Figure 4 The structural diagram of the two-layer game model shown in FIG. 1 references the two-layer game model, including the Stackelberg game model (first-layer game) and the bilateral bidding auction game model (second-layer game). In the two-layer game, the first-layer game is based on the utility function of SAT, that is, to ensure the maximization of the utility of SAT. The second-layer game uses the auction model and the greedy algorithm to traverse the matching, taking the local optimal utility of each auction as the benchmark, so as to obtain the maximum overall utility.

[0069] In the embodiment of the present application, in the Stackelberg game model, the low-orbit satellite constellations participating in the game must meet the following points: 1. It is based on the conditions of a perfectly competitive market, that is, there are a large number of demand parties (SAT) and supply parties (CRT) in the market; 2. The quality of the products provided is the same, that is, the shared spectrum can be used by CRT for normal communication; 3. Resources are fluid, that is, any CRT is eligible to participate in the competition; 4. The information is complete, that is, the unit spectrum selling value of SAT in the spectrum pool is the same, and the value has a constraint factor, so that SAT cannot maliciously increase prices.

[0070] In the embodiment of the present application, the high priority constellation The utility function expression of the system is:

[0071] (1)

[0072] Low priority constellations The utility function expression of the system is:

[0073] (2)

[0074] The three items in formula (1) represent the high priority constellation SAT selection respectively. The original user benefits after the strategy, the benefits of sharing idle spectrum with the low-priority constellation CRS, and the compensation of the low-priority constellation satellite for the original user QOS by selling spectrum resources to achieve spectrum sharing. Since the spectrum demand and the amount of idle spectrum jointly determine the value of idle spectrum, the inverse demand function is:

[0075] (3)

[0076] a: total spectrum capacity

[0077] b: Value constant for how much spectrum preference coefficient can be accessed

[0078] : Cost compensation function

[0079] : A set of strategies for selecting high-priority constellations SAT

[0080] : A set of strategies for selecting CRS for low-priority constellations

[0081] P: The pricing of idle spectrum of high-priority constellations based on market capacity and needs after selecting high-priority constellations and low-priority constellations

[0082] : Unit spectrum pricing for existing users of high-priority constellations

[0083] : represents the market value generated by low-priority constellation satellites acquiring idle spectrum

[0084] This application adopts a quadratic cost compensation function , the specific formula is expressed as:

[0085] (4)

[0086] Frequency Band Utilization The expression is:

[0087] (5)

[0088] (6)

[0089] : Constant coefficient of the cost compensation function

[0090] : Number of users of high priority constellation SAT

[0091] :The minimum bandwidth required by users of the high-priority constellation SAT to ensure services

[0092] : Bandwidth utilization

[0093] : Spectrum width of high priority constellation SAT authorization

[0094] : Low priority constellation in The spectrum width that can be obtained when using strategy

[0095] In the embodiment of the present application, in the spectrum allocation algorithm based on the Stackelberg game model, the Stackelberg model is a dynamic game, and it is known that the priority of CRS is lower than that of SAT, that is, the strategy set of the low-priority constellation Depends on the strategy set of the high priority constellation , there is a constraint relationship between the strategies. If we want to calculate the dynamic game of two strategy sets, we need to first assume that the high-priority constellation strategy set For known quantities, solve the low-priority constellation strategy set , and then the solved low priority constellation strategy set Back-substitution to solve the high-priority constellation strategy set .

[0096] The cost compensation function of the high priority constellation SAT is: , the cost function of the low priority constellation CRS is . Set a low priority constellation The value of makes the low priority constellation To maximize the utility of, we can substitute (3) into (2) to obtain:

[0097] (7)

[0098] right Find the first-order partial derivative to make the derivative equal to 0, and we get:

[0099] (8)

[0100] Substituting (3) into (1), the current strategy set of the low-priority constellation is recorded as , the strategy set of the high priority constellation is recorded as , then the strategy set of the high priority constellation is The maximum expression of the utility function is simplified to:

[0101] (9)

[0102] Substituting (8) into (9) and simplifying it, we obtain:

[0103] (10)

[0104] In the embodiment of the present application, it can be obtained from the above calculation that the high priority constellation The utility function of the system and the strategy set selected at this moment According to the existence proof of Nash equilibrium, the strategy is bounded, where About The quadratic function belongs to the elementary function. From the properties of elementary functions, we know that elementary functions are continuous within their meaningful domains. Therefore, we only need to prove exist The upper part is concave. right The first-order derivative of is as follows:

[0105] (11)

[0106] Let (11) be equal to zero, and the stationary point is:

[0107] (12)

[0108] From (12), we can see Will follow The change of value is linear, and from (4) we can know Among them, Y is the unit spectrum pricing of the high priority constellation for the original user, a is the total spectrum capacity, and b is the value constant of the value of the spectrum preference coefficient that can be accessed. It represents the market value generated after low-priority constellation satellites acquire idle spectrum.

[0109] right The second-order partial differential of is:

[0110] (13)

[0111] b is a constant, then , it can be seen The above is a convex function (the preference is a convex function, which means quasi-concave on the upper side), so the utility function There exists a Nash equilibrium.

[0112] Through the derivation of the above formula and the proof of Nash equilibrium, it is obtained that this game model has an optimal solution, that is, this spectrum sharing strategy can maximize the benefits of the high-priority constellation SAT, and the low-priority constellation can share the idle spectrum of the high-priority constellation to improve the spectrum utilization.

[0113] In the embodiment of the present application, in the first layer of the game, it is proved that the use of spectrum sharing strategy can maximize the benefits of the high-priority constellation SAT. The high-priority constellation satellite puts the shareable idle spectrum into the spectrum pool through real-time spectrum sensing. At the same time, the second layer starts the bilateral bidding auction game under incomplete information. Auction theory is a branch of game theory and economics. The core goal is to understand the value formation mechanism, resource allocation efficiency and auctioneer income maximization under the auction rules.

[0114] In the embodiment of the present application, the bilateral bidding auction game model is different from the first-layer dynamic game. There is no priority between the low-priority constellation satellites participating in the competition for idle spectrum in the second layer. Considering that the number of users served by each satellite is different, the business needs are different, and the usage time is different, how to more effectively meet the needs of each satellite, by quantifying the spectrum width requirements, frequency band usage time, frequency band usage income, etc. of each low-orbit satellite, the corresponding economic benefits are calculated. Ultimately, the maximum utilization rate of idle frequency bands is achieved.

[0115] In the embodiment of the present application, the flow chart of the bilateral bidding auction game model is as follows: Figure 5 As shown, the core is to dynamically allocate spectrum through the "Spectrum Resource Allocation Center". High-priority constellation satellites put the shareable idle spectrum into the spectrum pool, and multiple low-priority constellation satellites will put the required spectrum information into the center to match the idle spectrum according to their own business needs.

[0116] In the embodiment of the present application, the following two factors need to be considered during the bilateral bidding auction game:

[0117] 1. In each bidding time slot, if a low-priority constellation satellite bids for the idle spectrum of a high-priority constellation and continues to occupy it, it will have an impact on the original users of the high-priority constellation. It is necessary to set that once the available time is exceeded, the low-priority constellation satellite can no longer use the frequency band, and the spectrum resource allocation center will directly disconnect it, and put the remaining demand of the low-priority constellation into the spectrum pool at the next moment to re-participate in the bidding.

[0118] 2. In order to simplify the algorithm, before the auction, multiple satellites can only bid once in a competition, and their bid values ​​cannot be changed in real time. This can simplify the bidding strategy and greatly simplify the complexity of the system.

[0119] In the spectrum allocation algorithm based on the bilateral bidding auction game model in the embodiment of the present application, a multi-user scenario is modeled, such as Figure 6 As shown, M idle frequency bands of high-priority constellations in different states are set in the spectrum pool, is the idle frequency band width, the length of the blue block is the available time of the idle frequency band, and the length of the distance horizontal axis is the time of entering the spectrum pool.

[0120] In the embodiment of the present application, N low-priority constellation satellites compete for spectrum resources, and the bandwidth of each idle spectrum in the spectrum pool is In addition to calculating the economic benefits of accessing idle spectrum for communication services, low-priority constellation satellites also need to consider two factors in each bidding:

[0121] 1. The bid price of the low-priority constellation satellites for the idle spectrum auction must be greater than or equal to the sale value of the high-priority constellation idle spectrum ( );

[0122] 2. The matching degree between the bidding demand of low-priority constellation satellites and the idle spectrum of high-priority constellations ( ).

[0123] From formula (2), we can see that the low priority constellation The utility function expression of the system is:

[0124]

[0125] Taking into account many factors such as the size of idle spectrum, the size of the required frequency band, the bid price, the available time and the actual usage time, the utility function of the low-priority constellation satellite is expressed as:

[0126]

[0127] (14)

[0128] : Indicates the spectrum width required by low-priority constellation satellites

[0129] : represents the revenue function generated by low-priority constellation satellite service users

[0130] : The duration that low-priority constellation satellites occupy the idle spectrum of high-priority constellations

[0131] : represents the bidding information set of low-priority constellation satellites

[0132] : Existing idle spectrum bandwidth

[0133] : The value of low-priority constellation satellites per unit spectrum auction

[0134] : represents the market value generated by low-priority constellation satellites acquiring idle spectrum

[0135] : The duration of time that idle spectrum of high-priority constellations can be used

[0136] : Value of selling idle spectrum for high priority constellations

[0137] In an embodiment of the present application, a low-orbit satellite spectrum sharing method is provided, including: performing a first allocation process on a target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result; if there is no idle spectrum in the first allocation result, maintaining the current allocation strategy of the target spectrum; if there is an idle spectrum in the first allocation result, putting the idle spectrum into a public spectrum pool; performing a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model. Compared with the prior art, the present application proposes a dynamic matching algorithm for idle spectrum of multiple low-orbit satellites based on step-by-step game in a cognitive radio system by studying the dynamic spectrum allocation strategy under non-co-frequency use between multiple low-orbit constellations. The first layer uses a dynamic non-cooperative game under complete information between high-priority constellations and low-priority constellations, and obtains a conclusion that the spectrum sharing strategy can increase the spectrum utilization rate by obtaining the Nash equilibrium; the second layer of the game, by using the bilateral bidding auction game model under incomplete information between multiple low-priority constellation requirements and idle spectrum of high-priority constellations, based on the properties of the greedy algorithm (local optimal solution to global optimal solution), greatly improves the idle spectrum utilization rate in both the time domain and the frequency domain.

[0138] In some optional implementations of the embodiments of the present application, the above step S204 specifically includes the following steps:

[0139] Obtain the current number of idle spectrums, the number of auction requirements, and bidding information in the public spectrum pool;

[0140] Perform a first round of filtering on the bidding information and the idle spectrum according to preset restriction conditions to obtain first filtered bidding information and first filtered idle spectrum;

[0141] If the number of idle spectrums is greater than or equal to the number of bidding requirements, the bidding matching degree of the first filtered bidding information is calculated, the second filtered bidding information with a bidding matching degree greater than 0 is retained in the first filtered bidding information, the bidding utility value of the second filtered bidding information is calculated, and the second filtered bidding information with the largest bidding utility value is matched with the first filtered idle spectrum with the largest spectrum;

[0142] If the number of idle spectrums is less than the number of bidding requirements, calculate the spectrum matching degree of the first filtered idle spectrum, retain the second filtered idle spectrum with a spectrum matching degree greater than 0 in the first filtered idle spectrum, calculate the spectrum utility value of the second filtered idle spectrum, and match the second filtered idle spectrum with the largest spectrum utility value with the first filtered bidding information with the largest demand.

[0143] In the embodiments of this application, see Figure 7 As shown in the flowchart, the specific steps of step S204 are as follows:

[0144] 1. Determine the amount of idle spectrum and the amount of auction demand at time T0.

[0145] 2. Outer sorting: If the number of idle spectrum is greater than or equal to the number of auction requirements, the idle spectrum will be sorted according to the size of the frequency band. Sort by frequency band, put the one with the largest frequency band first, and mark the available time. , rental value If the number of idle spectrum is less than the number of auction requirements, the auction requirements will be sorted by spectrum size Bi and marked with spectrum bids. , and takes time t.

[0146] 3. Filter: All the items that meet the restriction conditions: If the number of idle spectrum is greater than or equal to the number of bidding requirements, calculate the matching degree of all qualified bidding information. If the number of idle spectrum is less than the number of auction requirements, calculate the matching degree of all eligible idle spectrum The value of is used as the second round of screening. If the matching degree calculation result is less than or equal to 0, it is judged as vicious competition and will not participate in this round of spectrum pool auction. Only the matching degree is retained. Data greater than 0.

[0147] 4. Utility value: Calculate the utility value of the data after two rounds of screening If the number of idle spectrum is greater than or equal to the number of bidding requirements, the bidding information with the first utility value result and the idle spectrum The first one is matched and used; if the number of idle spectrum is less than the number of bidding requirements, the idle spectrum with the first utility value result is matched and used with the first bidding requirement Bi. Based on the nature of the greedy algorithm: the local optimum solves the global optimum. In the spectrum resource allocation center, in order to maximize the current spectrum utility, the result of each game is the best at that moment, so as to maximize the utility of the overall strategy.

[0148] 5. The embodiment of the present application only represents the decision-making process within a unit of time. This strategy can be used in actual situations. Several of the above-mentioned decision-making processes can be included in any continuous time period to achieve dynamic scheduling.

[0149] 6. After the matching output is used, if the demand time of the low-priority constellation satellite is greater than the available time of the idle spectrum, when the matched idle spectrum time expires, the system will put the low-priority constellation satellite back into the next round of spectrum pool for bidding to meet its remaining demand. Similarly, when the available time of the idle spectrum is greater than the demand time of the low-priority constellation satellite, when the matched low-priority constellation satellite demand time expires, the system will put the idle spectrum back into the next round of spectrum pool for bidding to meet its remaining demand.

[0150] Considering the specific scenarios, idle spectrum and bidding demand may have multiple competitors, a single competitor, or unsold in different supply and demand relationships. The superiority of the strategy proposed in this application is verified by comparing the other two groups of strategies in three different scenarios. In order to verify the stability and intelligence of this system, this application uses MATLAB2023a for simulation.

[0151] Since the spectrum resource allocation center operates dynamically in an infinite cycle over time, and the idle spectrum information and auction demand at any time are randomly generated, in order to process the simulation results, this application will randomly capture the results of 60 unit times multiple times during the continuous operation of the system, and select an example for illustration.

[0152] like Figure 8As shown in the figure, in any 60 unit time, taking the idle spectrum ranked as No. 1 in the first round of outer layer at time T0 as an example, the y-axis indicates the available frequency band size of this idle spectrum is 200M, the x-axis indicates the available time of this idle spectrum is 45 unit time, and the idle spectrum No. 1 has matched 2 bidding demands in 45 unit time, namely, bidding demands No. 7 and No. 4. Using different color blocks can clearly show the occupancy of this idle spectrum in the frequency domain and time domain.

[0153] In the embodiment of the present application, under the premise of satisfying the first round of screening, the No. 7 bidding demand enters the spectrum pool at time T0, with a required bandwidth of 200M and a required time of 20 units of time; the No. 4 bidding demand enters the spectrum pool at the 30th unit time, with a required bandwidth of 188M and a required time of 15 units of time. As can be seen from the figure, in the 0th-20th unit time, it is matched and used by the No. 7 bidding demand; in the 30th-45th unit time, it is matched by the No. 4 bidding demand.

[0154] In summary, the system will match the idle spectrum with the auction demand with the largest frequency domain occupancy at the current moment among multiple auction demands, and after the idle spectrum No. 1 is used by bidder No. 7, it will enter the spectrum pool again and participate in the auction again, and then be matched and used again by bidder No. 4. This dynamic operation strategy can effectively improve the utilization rate of idle spectrum in time and frequency domains.

[0155] Depend on Figure 8 The color blocks shown show the occupancy method, and the idle spectrum utilization can be expressed as:

[0156] (15)

[0157] From formula (15), we can get that the utilization rate of idle spectrum No. 1 is 75.8% (retain one decimal place).

[0158] In some optional implementations of the embodiments of the present application, the bidding matching degree or spectrum matching degree is expressed as:

[0159]

[0160] in, Indicates the spectrum width required by low priority constellation satellites; Indicates the market value of unused spectrum; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction.

[0161] In the embodiment of the present application, a round of matching degree screening is required before the utility value is calculated. One of the innovative points of the present application is that the matching degree The design of the function not only needs to intuitively express the relationship between the size of the matching value and its related parameters, but also is used to avoid malicious value competition and prevent small-demand users from occupying large bandwidth spectrum, resulting in reduced spectrum utilization. Its expression is:

[0162] (16)

[0163] : Indicates the matching degree of low-priority constellation satellites to the auctioned frequency bands

[0164] If the matching function value is less than or equal to 0, the system determines it as malicious competition, and this user demand will not participate in the next round of screening and sorting. If the matching function value is greater than 0, it is sorted from large to small, and the largest value indicates that the idle spectrum and the bidder have the highest matching degree at this moment.

[0165] In order to verify the accuracy of the matching degree, this application uses MATLAB2023a for simulation. The simulation scenario is set as follows: the idle frequency band is 200M, and the market price of the low-priority constellation after obtaining the idle frequency band is 200 unit value / M / unit time. 1,000 low-priority constellation satellite demands are randomly generated, and the matching value function calculates the demand with the highest matching degree for the idle spectrum.

[0166] In the embodiment of the present application, the calculation of the known matching value is performed under the premise that , the x-axis is the bandwidth required by the CRS satellite, the y-axis is the bid of the CRS satellite for the unit idle spectrum, and the z-axis is the calculated matching value. Fig. 9 As shown in the figure, among the 1,000 randomly generated requirements, the result with the highest matching value is: the bandwidth required is 199.789 Mbps, and the bid is 74.4831 units. In summary, the calculation result of the matching value puts the occupancy of the auction demand represented by the x-axis on the idle spectrum 200M in the first place, and takes the difference between the asking price and the bid as a constraint condition, so that the unit spectrum asking price of the idle spectrum or the bid of the auction spectrum cannot be too high or too low. Therefore, the matching function can meet the screening function of the subsequent algorithm.

[0167] In actual applications, the number of idle spectrum in the spectrum pool, the size of the frequency band, the time of occurrence, the duration of use, and the rental value; the number of bidding demands, the size of the required frequency band, the time of occurrence of the demand, the duration of use, and the bid are all generated randomly. Therefore, the spectrum resource allocation center operates dynamically and in an infinite loop over time. Each constraint factor needs to be configured according to certain strategic rules.

[0168] In the embodiments of the present application, the present application verifies the superiority of the strategy proposed in the present application by studying three different situations that will definitely exist in the supply and demand relationship and comparing them with the other two groups of strategies.

[0169] By calculating the results of the dynamic allocation of spectrum resources in 60 unit time randomly intercepted 100 times according to formula (15), we can get: Fig.10 As shown, when the bidding demand is much greater than the number of idle spectrum, the utilization rate of the idle spectrum is improved by 15.2% (one decimal place is retained) when using the bilateral bidding auction game model strategy proposed in this application, compared with removing the matching degree screening part in the model, and improved by 46.4% when compared with the strategy of intelligent access in the order of time entering the spectrum pool; when the bidding demand is greater than or equal to the number of idle spectrum, the utilization rate of the idle spectrum is improved by 18.4% when using the game model strategy proposed in this application, compared with removing the matching degree screening part, and improved by 8.7% when compared with the strategy of intelligent access in the order of time entering the spectrum pool; when the bidding demand is less than the number of idle spectrum, due to the objective factor of insufficient bidding demand, there will be no difference in spectrum utilization.

[0170] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0171] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0173] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified in the present application, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps. Embodiment 2

[0174] Further references Fig.11 , as a response to the above Figure 2 The present application provides an embodiment of a low-orbit satellite spectrum sharing device. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0175] like Fig.11 As shown, the low-orbit satellite spectrum sharing device 200 of the embodiment of the present application includes:

[0176] A first allocation module 210, configured to perform a first allocation process on the target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result;

[0177] A first allocation result module 220, configured to maintain the current allocation strategy of the target spectrum if there is no idle spectrum in the first allocation result;

[0178] The second allocation result module 230 is configured to put the idle spectrum into a public spectrum pool if there is an idle spectrum in the first allocation result;

[0179] The second allocation module 240 is configured to perform a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a double-bid auction game model.

[0180] In an embodiment of the present application, a low-orbit satellite spectrum sharing device 200 is provided, including: a first allocation module 210, used to perform a first allocation process on a target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result; a first allocation result module 220, used to maintain the current allocation strategy of the target spectrum if there is no idle spectrum in the first allocation result; a second allocation result module 230, used to put the idle spectrum into a public spectrum pool if there is an idle spectrum in the first allocation result; a second allocation module 240, used to perform a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model. Compared with the prior art, this application proposes a dynamic matching algorithm for idle spectrum of multiple low-orbit satellites based on step-by-step game in a cognitive radio system by studying the dynamic spectrum allocation strategy under the condition of non-co-frequency use between multiple low-orbit constellations. The first layer uses the dynamic non-cooperative game under complete information between high-priority constellations and low-priority constellations, and obtains the conclusion that the spectrum sharing strategy can increase the spectrum utilization rate by obtaining the Nash equilibrium; the second layer of the game, by using the bilateral bidding auction game model under incomplete information between multiple low-priority constellation requirements and high-priority constellation idle spectrum, based on the properties of the greedy algorithm (local optimal solution to global optimal solution), greatly improves the idle spectrum utilization rate in both time domain and frequency domain.

[0181] In some optional implementations of the embodiments of the present application, the spectrum allocation algorithm based on the Stackelberg game model is expressed as follows:

[0182]

[0183] in, The utility function maximum expression of the strategy set representing the high priority constellation; Indicates the unit spectrum pricing of the high priority constellation to the original users; Indicates the total spectrum capacity; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; represents the cost compensation function; represents the strategy for selecting the i-th high priority constellation; A constant that represents the value of how much spectrum preference coefficient can be accessed.

[0184] In some optional implementations of the embodiments of the present application, the spectrum allocation algorithm based on the bilateral bidding auction game model is expressed as follows:

[0185]

[0186]

[0187] in, represents the utility function of low priority constellation satellites; Indicates the spectrum width required by low priority constellation satellites; : represents the bidding information set of low-priority constellation satellites; Represents the revenue function generated by low priority constellation satellite service users; Indicates the duration that the satellites of the low-priority constellation occupy the idle spectrum of the high-priority constellation; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the duration during which idle spectrum of high-priority constellations can be used.

[0188] To solve the above technical problems, the present application also provides a computer device. Fig.12 , Fig.12 This is a basic structural block diagram of a computer device according to an embodiment of the present application.

[0189] The computer device 300 includes a memory 310, a processor 320, and a network interface 330 that are interconnected and communicated through a system bus. It should be noted that the figure only shows a computer device 300 having components 310-330, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0190] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0191] The memory 310 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 310 can be an internal storage unit of the computer device 300, such as a hard disk or memory of the computer device 300. In other embodiments, the memory 310 can also be an external storage device of the computer device 300, such as a plug-in hard disk equipped on the computer device 300, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card, etc. Of course, the memory 310 can also include both the internal storage unit of the computer device 300 and its external storage device. In the embodiment of the present application, the memory 310 is generally used to store an operating system and various application software installed on the computer device 300, such as computer-readable instructions of a low-orbit satellite spectrum sharing method, etc. In addition, the memory 310 can also be used to temporarily store various data that have been output or are to be output.

[0192] The processor 320 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 320 is generally used to control the overall operation of the computer device 300. In the embodiment of the present application, the processor 320 is used to run the computer-readable instructions stored in the memory 310 or process data, such as computer-readable instructions for running the low-orbit satellite spectrum sharing method.

[0193] The network interface 330 may include a wireless network interface or a wired network interface. The network interface 330 is generally used to establish a communication connection between the computer device 300 and other electronic devices.

[0194] The computer device provided in this application studies the dynamic spectrum allocation strategy under the condition of non-co-frequency use between multiple low-orbit constellations, and proposes a dynamic matching algorithm for idle spectrum of multiple low-orbit satellites based on step-by-step game in a cognitive radio system. The first layer uses the dynamic non-cooperative game under complete information between high-priority constellations and low-priority constellations, and obtains the conclusion that the spectrum sharing strategy can increase the spectrum utilization rate by obtaining the Nash equilibrium; the second layer of the game, by using the bilateral bidding auction game model under incomplete information between multiple low-priority constellation requirements and high-priority constellation idle spectrum, based on the properties of the greedy algorithm (local optimal solution to global optimal), greatly improves the idle spectrum utilization rate in both time domain and frequency domain.

[0195] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the low-orbit satellite spectrum sharing method as described above.

[0196] The computer-readable storage medium provided in the present application proposes a dynamic matching algorithm for idle spectrum of multiple low-orbit satellites based on step-by-step game in a cognitive radio system by studying the dynamic spectrum allocation strategy under the condition of non-co-frequency use between multiple low-orbit constellations. The first layer uses the dynamic non-cooperative game under complete information between high-priority constellations and low-priority constellations, and obtains the conclusion that the spectrum sharing strategy can increase the spectrum utilization rate by obtaining the Nash equilibrium; the second layer of the game, by using the bilateral bidding auction game model under incomplete information between multiple low-priority constellation requirements and the idle spectrum of high-priority constellations, based on the properties of the greedy algorithm (local optimal solution to global optimal solution), greatly improves the idle spectrum utilization rate in both time domain and frequency domain.

[0197] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0198] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A low-orbit satellite spectrum sharing method, characterized in that: The steps include: Performing a first allocation process on the target spectrum according to a spectrum allocation algorithm based on the Stackelberg game model to obtain a first allocation result; If there is no idle spectrum in the first allocation result, maintaining the current allocation strategy of the target spectrum; If there is idle spectrum in the first allocation result, putting the idle spectrum into a public spectrum pool; Performing a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model; The spectrum allocation algorithm based on the Stackelberg game model is expressed as: n) in, The utility function maximum expression of the strategy set representing the high priority constellation; Indicates the unit spectrum pricing of the high priority constellation to the original users; Indicates the total spectrum capacity; A constant representing the value of the shared spectrum sold after the low-priority constellation obtains it; represents the cost compensation function; represents the strategy for selecting the i-th high priority constellation; A constant representing the value of how much spectrum preference coefficient can be accessed; The spectrum allocation algorithm based on the bilateral bidding auction game model is expressed as the utility function of the low-priority constellation satellite: ， in, represents the utility function of low priority constellation satellites; Indicates the spectrum width required by low priority constellation satellites; : represents the bidding information set of low-priority constellation satellites; Represents the revenue function generated by low priority constellation satellite service users; Indicates the duration that the satellites of the low-priority constellation occupy the idle spectrum of the high-priority constellation; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the duration for which idle spectrum of high-priority constellations can be used; The step of performing a second allocation process on the idle spectrum according to the spectrum allocation algorithm based on the bilateral bidding auction game model specifically includes the following steps: Obtaining the current idle spectrum quantity, auction demand quantity and bidding information of the public spectrum pool; Performing a first round of filtering on the bidding information and the idle spectrum according to preset restriction conditions to obtain first filtered bidding information and first filtered idle spectrum; If the number of idle spectrums is greater than or equal to the number of bidding requirements, the bidding matching degree of the first filtered bidding information is calculated, the second filtered bidding information with a bidding matching degree greater than 0 is retained in the first filtered bidding information, the bidding utility value of the second filtered bidding information is calculated, and the second filtered bidding information with the largest bidding utility value is matched with the first filtered idle spectrum with the largest spectrum; If the number of idle spectrums is less than the number of bidding requirements, calculate the spectrum matching degree of the first filtered idle spectrum, retain the second filtered idle spectrum with a spectrum matching degree greater than 0 in the first filtered idle spectrum, calculate the spectrum utility value of the second filtered idle spectrum, and match the second filtered idle spectrum with the largest spectrum utility value with the first filtered bidding information with the largest demand.

2. The low-orbit satellite spectrum sharing method according to claim 1, characterized in that: The bidding matching degree or the spectrum matching degree is expressed as: ， in, Indicates the spectrum width required by low priority constellation satellites; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction.

3. A low-orbit satellite spectrum sharing device, characterized in that: include: A first allocation module, configured to perform a first allocation process on the target spectrum according to a spectrum allocation algorithm based on a Stackelberg game model to obtain a first allocation result; A first allocation result module, configured to maintain the current allocation strategy of the target spectrum if there is no idle spectrum in the first allocation result; A second allocation result module, configured to put the idle spectrum into a public spectrum pool if there is an idle spectrum in the first allocation result; A second allocation module, configured to perform a second allocation process on the idle spectrum according to a spectrum allocation algorithm based on a bilateral bidding auction game model; The spectrum allocation algorithm based on the Stackelberg game model is expressed as: n) in, The utility function maximum expression of the strategy set representing the high priority constellation; Indicates the unit spectrum pricing of the high priority constellation to the original users; Indicates the total spectrum capacity; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; represents the cost compensation function; represents the strategy for selecting the i-th high priority constellation; A constant representing the value of how much spectrum preference coefficient can be accessed; The spectrum allocation algorithm based on the bilateral bidding auction game model is expressed as the utility function of the low-priority constellation satellite: ，， in, represents the utility function of low priority constellation satellites; Indicates the spectrum width required by low priority constellation satellites { }: represents the bidding information set of low-priority constellation satellites; Represents the revenue function generated by low priority constellation satellite service users; Indicates the duration that the satellites of the low-priority constellation occupy the idle spectrum of the high-priority constellation; Indicates the existing idle spectrum bandwidth; It represents the value paid by low-priority constellation satellites for a unit of spectrum in the auction; It represents the market value generated after low-priority constellation satellites acquire idle spectrum; Indicates the duration for which idle spectrum of high-priority constellations can be used; The second allocation module specifically includes: a data acquisition submodule, a first round filtering submodule, a first matching submodule and a second matching submodule, wherein: The data acquisition submodule is used to obtain the number of idle spectrums, the number of bidding requirements and bidding information of the public spectrum pool at the current moment; The first round filtering submodule is used to perform a first round of filtering on the bidding information and the idle spectrum according to a preset restriction condition to obtain first filtered bidding information and first filtered idle spectrum; The first matching submodule is used to calculate the bidding matching degree of the first filtered bidding information if the number of idle spectrums is greater than or equal to the number of bidding requirements, retain the second filtered bidding information with a bidding matching degree greater than 0 in the first filtered bidding information, calculate the bidding utility value of the second filtered bidding information, and match the second filtered bidding information with the largest bidding utility value with the first filtered idle spectrum with the largest spectrum; The second matching submodule is used to calculate the spectrum matching degree of the first filtered idle spectrum if the number of idle spectrum is less than the bidding demand number, retain the second filtered idle spectrum with a spectrum matching degree greater than 0 in the first filtered idle spectrum, calculate the spectrum utility value of the second filtered idle spectrum, and match the second filtered idle spectrum with the largest spectrum utility value with the first filtered bidding information with the largest demand.

4. A computer device comprising a memory and a processor, characterized in that: The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the low-orbit satellite spectrum sharing method as described in any one of claims 1 to 2 are implemented.

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the low-orbit satellite spectrum sharing method according to any one of claims 1 to 2 are implemented.

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