A fast spectrum allocation method based on composite criteria for multi-user arbitrary bandwidth access

Abstract

The present invention discloses a composite criterion rapid spectrum allocation method for multi-user arbitrary bandwidth access, and the composite criterion rapid spectrum allocation method for multi-user arbitrary bandwidth access comprises: S1: determining a main user and a cognitive user group, wherein the cognitive user group comprises a plurality of cognitive users; S2: constructing a spectrum allocation model for an arbitrary bandwidth access scenario according to frequency band information occupied by the main user and cognitive user information; S3: obtaining a plurality of available sub-frequency bands corresponding to the working bandwidth according to the working frequency band information and inherent frequency band of the main user and using the working bandwidth; S4: solving the spectrum allocation model according to the plurality of available sub-frequency bands and the priority of each cognitive user using a greedy algorithm to obtain the working frequency band of each cognitive user; and S5: allocating spectrum to each cognitive user according to the working frequency band of each cognitive user.

Description

Technical Field

[0001] The present invention relates to the technical field of spectrum allocation, and in particular to a composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access. Background Art

[0002] With the rapid development of wireless communication technology, the scale of mobile Internet and Internet of Things is increasing day by day, and the number of wireless access user devices is huge and diversified. Different types of frequency-using terminal devices have different functions, and there are obvious differences in device parameters and spectrum requirements. The working frequencies and occupied bandwidths of these terminal devices are often fixed and different, which has caused an increasingly severe shortage of spectrum resources. Cognitive radio technology can effectively improve spectrum utilization by sensing the usage status of the electromagnetic spectrum of the main user and dynamically allocating the available spectrum to cognitive users who apply for frequency use. As a basic key link of cognitive radio, dynamic spectrum allocation is urgently needed for the study of practical spectrum allocation technology for multi-user arbitrary bandwidth access scenarios.

[0003] In recent years, various domestic research institutions have conducted extensive research on spectrum allocation technology under the framework of cognitive radio models. Peng Zhen from the School of Communication Engineering of Hangzhou Dianzi University and Zhao Zhijin, Zheng Shilian and other researchers from China Electronics 36th Institute proposed a cognitive radio spectrum allocation algorithm based on the hybrid frog leaping algorithm. The basic idea is to take the availability of each abstract spectrum resource for each cognitive user and the interference relationship between users as constraints, and to maximize the total transmission benefit of the network as the optimization goal for modeling, and use an improved binary hybrid frog leaping algorithm for solution. Liu Juntong, Wang Keren and others from the PLA Electronic Engineering College proposed an improved dynamic spectrum allocation algorithm based on different demand levels. The basic idea is to take the availability of each abstract spectrum resource for each cognitive user and the interference relationship between users as constraints, and to maximize the number of high-priority users for modeling, and use a genetic algorithm for solution.

[0004] The above algorithms propose solutions to the problem of dynamic spectrum allocation of cognitive radio, but the following problems still exist in practical scenarios for multi-user arbitrary bandwidth access: First, the electromagnetic spectrum is abstracted into resource units, and the spectrum allocation algorithm does not consider user access scenarios with different frequency resource requirements. It simply abstracts the spectrum allocation into several already cut frequency bands with the same bandwidth, and assumes that all cognitive users can use these frequency bands with the same bandwidth normally. In actual application scenarios, this may cause a waste of frequency resources or cause the device to fail to work normally because the allocated frequency band bandwidth is less than the working bandwidth of the user device, which lacks practical application value; second, there are many types of cognitive users, and the access priority levels of cognitive users are also different. Summary of the invention

[0005] The purpose of the present invention is to address the deficiencies of the above-mentioned existing spectrum allocation technology and to provide an algorithm for instantly providing a spectrum allocation method for a large number of cognitive users based on initial frequency information such as the priority of each cognitive user, the applied frequency band, the inherent frequency band and the main user's working frequency band, so as to avoid waste of spectrum resources, ensure the normal operation of each cognitive user in a large-scale multi-user arbitrary bandwidth access scenario, and improve the collaborative work efficiency of the network.

[0006] The technical solution of the present invention to solve the above technical problems is as follows:

[0007] The present invention provides a composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access, the composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access comprising:

[0008] S1: Determine a main user and a cognitive user group, wherein the cognitive user group includes a plurality of cognitive users;

[0009] S2: constructing a spectrum allocation model for any bandwidth access scenario according to the frequency band information occupied by the primary user and the cognitive user information;

[0010] S3: obtaining a plurality of available sub-frequency bands corresponding to the working bandwidth using the working bandwidth according to the working frequency band information and the inherent frequency band of the primary user;

[0011] S4: solving the spectrum allocation model using a greedy algorithm according to the available sub-frequency bands and the priority of each cognitive user to obtain a working frequency band for each cognitive user;

[0012] S5: Allocate spectrum to each cognitive user according to the working frequency band of each cognitive user.

[0013] Optionally, between step S1 and step S2, the composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access further includes:

[0014] Obtain the working frequency band status information of the primary user according to the current electromagnetic environment;

[0015] The information of each cognitive user in the cognitive user group is obtained, wherein the cognitive user information includes cognitive user priority, applied frequency band, inherent frequency band, transmitter power, receiving sensitivity and working bandwidth.

[0016] Optionally, the step S2 includes:

[0017] S21: setting constraints on the working frequency band of each cognitive user;

[0018] S22: Obtaining a frequency domain interference coefficient according to the working bandwidth of the cognitive user and the constraint condition of the working frequency band;

[0019] S23: Obtaining a spatial interference coefficient according to the constraints of the working frequency band, transmitter power, and receiving sensitivity;

[0020] S24: Obtaining a cognitive user interference coefficient according to the frequency domain interference coefficient, the spatial domain interference coefficient and the cognitive user priority;

[0021] S25: obtaining an objective function of a spectrum allocation model according to the cognitive user interference coefficient;

[0022] S26: Obtain the spectrum allocation model according to the constraint conditions of the working frequency band and the objective function of the spectrum allocation model.

[0023] Optionally, in step S21, the constraint condition of the cognitive user working frequency band is:

[0024]

[0025]

[0026] k∈[1,N],n∈[1,A]

[0027] Among them, f sk and f ek They represent the starting frequency and ending frequency of the kth cognitive user working frequency band respectively; f gsk and f gek They represent the starting frequency and ending frequency of the kth cognitive user’s inherent frequency band respectively; f asn and f aen They represent the starting frequency and ending frequency of the working frequency band of the nth primary user, n∈[1,A], A is the number of primary users, abs is the absolute value function, N is the total number of cognitive users, and B k is the working bandwidth.

[0028] Optionally, in step S22, the frequency domain interference coefficient F ij for:

[0029]

[0030] Among them, B i ,B j denote the working bandwidth of the i-th cognitive user and the j-th cognitive user, respectively, and f ci and f cj is the center frequency of the working frequency band of the i-th cognitive user and the j-th cognitive user, and f si ,f sj ,f ei ,f ejThey respectively represent the starting frequency of the i-th cognitive user working frequency band, the starting frequency of the j-th cognitive user working frequency band, the ending frequency of the i-th cognitive user working frequency band, and the ending frequency of the j-th cognitive user working frequency band, i,j∈[1,N],i≠j.

[0031] Optionally, in step S23, the spatial interference coefficient I ij for:

[0032]

[0033] Among them, P i represents the transmitter power of the i-th cognitive user, S j represents the receiver sensitivity of the jth cognitive user, L ij The center frequency transmitted from the i-th cognitive user is f ci The energy lost in the process of signal propagation to the jth cognitive user and L ij =32.44+20*log 10 f ci +20*log 10 D ij , where D ij represents the straight-line distance between the i-th cognitive user and the j-th cognitive user.

[0034] Optionally, in step S24, the cognitive user interference coefficient m i for:

[0035]

[0036] Among them, I ij is the spatial interference coefficient, F ij is the frequency domain interference coefficient, p max is the priority value with the largest absolute value, p j is the priority value of the jth user.

[0037] Optionally, in step S25, the objective function H of the spectrum allocation model is f for:

[0038]

[0039] Where N is the number of cognitive users, m i is the cognitive user interference coefficient, I ij is the spatial interference coefficient, F ij is the frequency domain interference coefficient, p max is the priority value with the largest absolute value, p j is the priority value of the j-th user, and i represents the i-th cognitive user.

[0040] Optionally, step S3 includes:

[0041] S31: Determine available frequency resources for each cognitive user according to the working frequency band information of the primary user and the inherent frequency band;

[0042] S32: performing spectrum cutting on the available frequency resources of each cognitive user according to its working bandwidth to obtain a plurality of available sub-frequency bands of the same size as the working bandwidth.

[0043] Optionally, the step S4 comprises:

[0044] S41: taking the applied frequency band of each of the cognitive users as the initial working frequency band;

[0045] S42: sorting the cognitive users according to their priorities;

[0046] S43: Determine whether the current working frequency band of the current cognitive user interferes with other cognitive users. If so, use the current working frequency band as the working frequency band of the current cognitive user and proceed to step S44; otherwise, proceed to step S49;

[0047] S44: using a greedy algorithm, screening a number of available sub-frequency bands of the currently recognized user to obtain a first available sub-frequency band;

[0048] S45: Determine whether the number of the first available sub-frequency bands is greater than 1, if so, proceed to step S46; otherwise, use the first available sub-frequency band as the working frequency band of the current cognitive user, proceed to the next cognitive user and return to step S43;

[0049] S46: screening all the first available sub-frequency bands by using the minimum accommodation principle to obtain a second available sub-frequency band;

[0050] S47: Determine whether the number of the second available sub-frequency bands is greater than 1. If so, proceed to step S48; otherwise, use the second available sub-frequency band as the working frequency band of the current cognitive user, proceed to the next cognitive user and return to step S43;

[0051] S48: screening all the second available sub-frequency bands by using the leftmost placement principle to obtain a third available sub-frequency band;

[0052] S49: Determine whether the current recognized user is the last recognized user, if so, proceed to step S410; otherwise, proceed to the next recognized user and return to step S43;

[0053] S410: Determine whether the current working frequency band of each cognitive user is different from the working frequency band of each cognitive user in the previous iteration. If so, take the working frequency band of each cognitive user in this iteration as the starting point and return to step S43; otherwise, save the current working frequency band of each cognitive user.

[0054] The present invention has the following beneficial effects:

[0055] Compared with the prior art, the present invention has the following advantages:

[0056] 1. The present invention establishes a spectrum allocation model for any bandwidth access scenario, which can accurately describe the parameter information of cognitive user equipment with different working bandwidths;

[0057] 2. The present invention solves the spectrum allocation problem of irregular arbitrary bandwidth access scenarios by solving the spectrum allocation model of arbitrary bandwidth access scenarios, thereby obtaining specific information of the working frequency band of each cognitive user when the interference between cognitive users is low;

[0058] 3. In the objective function of the arbitrary bandwidth access mathematical model constructed by the present invention, the priority value of each cognitive user is used as the contribution weight to the function value, that is, the higher the priority, the greater the contribution, which can make the solution algorithm tend to obtain a solution that is beneficial to high-priority cognitive users, thereby realizing the priority guarantee of the spectrum demand of high-priority cognitive users;

[0059] 4. The present invention comprehensively considers conflict avoidance and global resource allocation. The algorithm not only considers the minimum conflict criterion to minimize conflicts, but also selects the optimal frequency band that saves more frequency resources through the minimum accommodation criterion and the leftmost placement criterion when there are multiple frequency bands that meet the minimum conflict criterion, leaving space for spectrum allocation of other users as much as possible, thereby improving the global resource utilization efficiency;

[0060] 5. The process of the present invention is concise and has a fast convergence speed, and can quickly realize frequency resource guarantee in scenarios with a large number of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A flow chart of the composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access provided by the present invention;

[0062] Figure 2 for Figure 1 The step-by-step flow chart of step S2;

[0063] Figure 3 for Figure 1 A step-by-step flow chart of step S3;

[0064] Figure 4 for Figure 1 Flow chart of step S4 in FIG. DETAILED DESCRIPTION

[0065] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0066] Example 1

[0067] A composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access, reference Figure 1 As shown, the composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access includes:

[0068] S1: Determine a main user and a cognitive user group, wherein the cognitive user group includes a plurality of cognitive users;

[0069] S2: constructing a spectrum allocation model for any bandwidth access scenario according to the frequency band information occupied by the primary user and the cognitive user information;

[0070] S3: obtaining a plurality of available sub-frequency bands corresponding to the working bandwidth using the working bandwidth according to the working frequency band information and the inherent frequency band of the primary user;

[0071] S4: solving the spectrum allocation model using a greedy algorithm according to the available sub-frequency bands and the priority of each cognitive user to obtain a working frequency band for each cognitive user;

[0072] S5: Allocate spectrum to each cognitive user according to the working frequency band of each cognitive user.

[0073] Between step S1 and step S2, the composite criterion rapid spectrum allocation method for multi-user arbitrary bandwidth access also includes: obtaining the working frequency band status information of the main user according to the current electromagnetic environment; obtaining the information of each cognitive user in the cognitive user group, wherein the cognitive user information includes cognitive user priority, applied frequency band, inherent frequency band, transmitter power, receiving sensitivity and working bandwidth.

[0074] refer to Figure 2 As shown, step S2 includes:

[0075] S21: setting constraints on the working frequency band of each cognitive user;

[0076] S22: Obtaining a frequency domain interference coefficient according to the working bandwidth of the cognitive user and the constraint condition of the working frequency band;

[0077] S23: Obtaining a spatial interference coefficient according to the constraints of the working frequency band, transmitter power, and receiving sensitivity;

[0078] S24: Obtaining a cognitive user interference coefficient according to the frequency domain interference coefficient, the spatial domain interference coefficient and the cognitive user priority;

[0079] S25: obtaining an objective function of a spectrum allocation model according to the cognitive user interference coefficient;

[0080] S26: Obtain the spectrum allocation model according to the constraint conditions of the working frequency band and the objective function of the spectrum allocation model.

[0081] In step S21, the constraint condition of the cognitive user working frequency band is:

[0082]

[0083]

[0084] k∈[1,N],n∈[1,A]

[0085] Among them, f sk and f ek They represent the starting frequency and ending frequency of the kth cognitive user working frequency band respectively; f gsk and f gek They represent the starting frequency and ending frequency of the kth cognitive user’s inherent frequency band respectively; f asn and f aen They represent the starting frequency and ending frequency of the working frequency band of the nth primary user, n∈[1,A], A is the number of primary users, abs is the absolute value function, N is the total number of cognitive users, and B k is the working bandwidth.

[0086] In step S22, the frequency domain interference coefficient F ij for:

[0087]

[0088] Among them, B i ,B j denote the working bandwidth of the i-th cognitive user and the j-th cognitive user, respectively, and f ci and f cj is the center frequency of the working frequency band of the i-th cognitive user and the j-th cognitive user, and f si ,f sj ,f ei ,f ej They respectively represent the starting frequency of the i-th cognitive user working frequency band, the starting frequency of the j-th cognitive user working frequency band, the ending frequency of the i-th cognitive user working frequency band, and the ending frequency of the j-th cognitive user working frequency band, i,j∈[1,N],i≠j.

[0089] In step S23, the spatial interference coefficient I ij for:

[0090]

[0091] Among them, P i represents the transmitter power of the i-th cognitive user, S j represents the receiver sensitivity of the jth cognitive user, L ij The center frequency transmitted from the i-th cognitive user is f ci The energy lost in the process of signal propagation to the jth cognitive user and L ij =32.44+20*log 10 f ci +20*log 10 D ij , where D ij represents the straight-line distance between the i-th cognitive user and the j-th cognitive user;

[0092] In step S24, the cognitive user interference coefficient m i for:

[0093]

[0094] Among them, I ij is the spatial interference coefficient, F ij is the frequency domain interference coefficient, p max is the priority value with the largest absolute value, p j is the priority value of the jth user;

[0095] In step S25, the objective function H of the spectrum allocation model f for:

[0096]

[0097] Where N is the number of cognitive users, m i is the cognitive user interference coefficient, I ij is the spatial interference coefficient, F ij is the frequency domain interference coefficient, p max is the priority value with the largest absolute value, p j is the priority value of the j-th user, and i represents the i-th cognitive user.

[0098] The spectrum allocation model is:

[0099]

[0100]

[0101]

[0102] k∈[1,N],n∈[1,A]

[0103] Among them, H f is the fitness function to measure the performance of the allocation scheme, N is the number of cognitive users, m i is the degree to which the i-th cognitive user interferes with other cognitive users; I ij Indicates whether the i-th cognitive user interferes with the j-th cognitive user in the airspace. If there is interference, I ij When it is 1, there is no interference. ij is 0; F ij is the ratio of the bandwidth of the overlapping part of the working frequency band of the i-th cognitive user and the j-th cognitive user to the total bandwidth of the working frequency band of the j-th cognitive user; p max is the maximum value of the priority value of each cognitive user; p j is the priority value of the jth cognitive user; f sk and f ek They represent the starting frequency and ending frequency of the kth cognitive user working frequency band respectively; B k is the working bandwidth of the kth cognitive user; f gsk and f gek They represent the starting frequency and ending frequency of the kth cognitive user’s inherent frequency band respectively; f asn and f aen They respectively represent the starting frequency and ending frequency of the working frequency band of the nth primary user, n∈[1,A], A is the number of primary users; i,j∈[1,N], i≠j.

[0104] refer to Figure 3 As shown, step S3 includes:

[0105] S31: Determine available frequency resources for each cognitive user according to the working frequency band information of the primary user and the inherent frequency band;

[0106] S32: performing spectrum cutting on the available frequency resources of each cognitive user according to its working bandwidth to obtain a plurality of available sub-frequency bands of the same size as the working bandwidth.

[0107] refer to Figure 4 As shown, step S4 includes:

[0108] S41: taking the applied frequency band of each of the cognitive users as the initial working frequency band;

[0109] S42: sorting the cognitive users according to their priorities;

[0110] S43: Determine whether the current working frequency band of the current cognitive user interferes with other cognitive users. If so, use the current working frequency band as the working frequency band of the current cognitive user and proceed to step S44; otherwise, proceed to step S49;

[0111] S44: using a greedy algorithm, screening a number of available sub-frequency bands of the currently recognized user to obtain a first available sub-frequency band;

[0112] S45: Determine whether the number of the first available sub-frequency bands is greater than 1, if so, proceed to step S46; otherwise, use the first available sub-frequency band as the working frequency band of the current cognitive user, proceed to the next cognitive user and return to step S43;

[0113] S46: screening all the first available sub-frequency bands by using the minimum accommodation principle to obtain a second available sub-frequency band;

[0114] S47: Determine whether the number of the second available sub-frequency bands is greater than 1. If so, proceed to step S48; otherwise, use the second available sub-frequency band as the working frequency band of the current cognitive user, proceed to the next cognitive user and return to step S43;

[0115] S48: screening all the second available sub-frequency bands by using the leftmost placement principle to obtain a third available sub-frequency band;

[0116] S49: Determine whether the current recognized user is the last recognized user, if so, proceed to step S410; otherwise, proceed to the next recognized user and return to step S43;

[0117] S410: Determine whether the current working frequency band of each cognitive user is different from the working frequency band of each cognitive user in the previous iteration. If so, take the working frequency band of each cognitive user in this iteration as the starting point and return to step S43; otherwise, save the current working frequency band of each cognitive user.

[0118] Example 2

[0119] 1. Obtain the channel status and obtain the working frequency band information of the primary user according to the channel status.

[0120] In cognitive radio networks, users are divided into primary users and secondary users. Secondary users are also called cognitive users. Cognitive users cannot interfere with the normal work of primary users. Therefore, the working frequency band of secondary users cannot overlap with the working frequency band of primary users.

[0121] The main user working frequency band information includes: the total number of main users A, the starting frequency f of the main user working frequency band asn and the stop frequency f aen ; n∈[1,A].

[0122] 2. Obtain information about each cognitive user.

[0123] The parameter information of the cognitive user equipment includes: cognitive user priority p k , working bandwidth B k , natural frequency band start frequency f gsk , natural frequency band end frequency f gek , geographic location longitude coordinate x k , geographic location latitude coordinate y k , geographic location height coordinate z k , transmitter power P k , receiver sensitivity S k , the starting frequency of the working frequency band is f sk , operating frequency band end frequency f ek ; Application frequency band starting frequency f rsk and the stop frequency f rek ; k∈[1,N];

[0124] Where the cognitive user priority p k Indicates the relative importance of each cognitive user among all cognitive users. There may be multiple cognitive users with the same priority. The inherent frequency band is the inherent attribute of the user device. The user's working frequency band must be within the inherent frequency band range, otherwise the user device cannot work normally. The working frequency band refers to the frequency band used when the user device is turned on. The starting frequency f of the working frequency band of the same device sk and the stop frequency f ek Can change within the inherent frequency band, but the working bandwidth B k =f ek -f sk Constant, working bandwidth B for different users k May be different; transmitter power P k Refers to the RF power provided by the user's transmitter to the antenna; receiver sensitivity S k Refers to the minimum signal strength that the user's receiver can identify; the applied frequency band refers to the frequency band that each user applies to use;

[0125] 3. Establish a mathematical model for spectrum allocation in arbitrary bandwidth access mathematical model scenarios.

[0126] The known data of the model are the information of each cognitive user and the working frequency band information of the primary user obtained in step 1. The optimization goal is to find a suitable working frequency band for each cognitive user to avoid interference between users as much as possible. If interference cannot be avoided, the interference to high-priority cognitive users is minimized:

[0127] 3.1 Set constraints on the working frequency band of cognitive users:

[0128] 3.1.1 According to the requirement that the working frequency band must be within the inherent frequency band, the first constraint condition is set: the absolute value of the difference between the center frequency of the inherent frequency band of the cognitive user and the center frequency of the working frequency band Half the bandwidth of cognitive users sum Only if it is less than or equal to the value, then compare it with the inherent frequency band bandwidth of the cognitive user When the working frequency band is within the inherent frequency band, that is:

[0129]

[0130] 3.1.2 According to the regulation that the cognitive user operating frequency band cannot overlap with the primary user operating frequency band, a third constraint is set: only when the absolute value of the difference between the center frequency of the primary user operating frequency band and the center frequency of the cognitive user operating frequency band overlaps, the cognitive user can Greater than or equal to the cognitive user working bandwidth B k Half of the primary user operating frequency bandwidth f aen -f asn The sum of half When , the working frequency band of the cognitive user does not overlap with the working frequency band of the primary user, that is:

[0131]

[0132] 3.1.3 Construct the constraints of the working frequency band of cognitive users. The working frequency band of each cognitive user must make the above two inequalities hold simultaneously:

[0133]

[0134]

[0135] k∈[1,N],n∈[1,A]

[0136] 3.2 Analyze the frequency domain interference. If the working frequency bands of two users overlap, it is considered that there is frequency domain interference between the two users:

[0137] 3.2.1 First, according to the starting frequency f of each cognitive user's working frequency band sk and the stop frequency f ek , calculate the center frequency f of the working frequency band ck :

[0138]

[0139] According to f ck and working bandwidth B k Determine whether the working frequency bands of any two users overlap. If the working frequency bands of two users overlap, it is considered that there is frequency domain interference between the two users:

[0140] If the inequality If (i,j∈[1,N],i≠j) holds true, the working frequency bands of the two users overlap and there is frequency domain interference. The spectrum overlap is used to Characterize the severity of frequency domain interference of the i-th user to the j-th user;

[0141] Otherwise, the working frequency bands of the two users do not overlap, that is, there is no frequency domain interference, and the severity of frequency domain interference is 0;

[0142] 3.2.2 Definition of frequency domain interference coefficient F ij , to characterize the severity of the frequency domain interference of any i-th user to the j-th user:

[0143]

[0144] Among them, i,j∈[1,N],i≠j;

[0145] 3.3 Analysis of airspace interference:

[0146] 3.3.1 First, according to the center frequency f of the working frequency band of the transmitting end user ic The energy L lost in the process of signal propagation from the source to the receiver is calculated based on the geographical location and the geographical location of the user receiving the signal. ij , the loss mechanism is described by the free space path fading formula:

[0147] L ij =32.44+20*log 10 f ci +20*log 10 D ij

[0148] Among them, D ij Represent the straight-line distance between the i-th user and the j-th user respectively; i,j∈[1,N],i≠j;

[0149] According to L ij , the transmitter power P of the transmitting user i and the receiver sensitivity S of the receiving end user j , determine the signal strength of the signal transmitted by the transmitting end when it propagates to the receiving end and the receiver sensitivity S of the receiving end user j Size relationship:

[0150] If the inequality P i -L ij ≥S j If true, the i-th user interferes with the j-th user;

[0151] Otherwise, the i-th user has no interference with the j-th user;

[0152] 3.3.2 Definition of airspace interference coefficient I ij , to characterize whether there is spatial interference between any two users:

[0153]

[0154] 3.4 Using the frequency domain interference coefficient F ij , airspace interference coefficient I ij And the priority of each user, define the interference coefficient m of each user i :

[0155]

[0156] where p max is the priority value with the largest absolute value, p j is the priority value of the jth user;

[0157] Interference coefficient quantization m i Characterizes the degree to which each user interferes with other users, m i The larger the value, the greater the interference of this user to other users;

[0158] 3.5 Use interference coefficient m i Define the fitness function H f , to represent the sum of interference coefficients of all users:

[0159]

[0160] Use the fitness function as the objective function of the model;

[0161] 3.6 Construct a mathematical model for arbitrary bandwidth access scenarios based on constraints and optimization objectives:

[0162]

[0163]

[0164]

[0165] k∈[1,N],n∈[1,A]

[0166] 4. Determine the available working frequency bands for each cognitive user.

[0167] This step searches for all available frequency bands for each cognitive user based on the cognitive user parameter information, inherent frequency bands, and primary user working frequency band information:

[0168] 4.1 Exclude the part overlapping with the primary user from the inherent frequency band of each cognitive user;

[0169] 4.2 Arrange and save the remaining frequency bands scattered in the inherent frequency bands. These frequency bands are the available frequency bands for the cognitive user;

[0170] 5. The available frequency bands of each cognitive user are divided into spectrum according to their working bandwidth.

[0171] This step divides the available frequency band of each cognitive user into a series of available sub-frequency bands according to the available frequency band information and working bandwidth of the cognitive user:

[0172] 5.1 Cut the available frequency band of any user according to the step length s:

[0173] Assume that the starting frequency of any available frequency band of the user is f s , the termination frequency is f e , the user's working bandwidth is B k , then the available frequency band can be divided into Available sub-bands, the starting frequency of the kth available sub-band is f s +(k-1)·s, cutoff frequency is f s + k·s;

[0174] 5.2 Perform spectrum division on the available frequency bands of the remaining N-1 users, and generate an available sub-frequency band set for each user;

[0175] 6. Sort each cognitive user by priority.

[0176] This step finds all the highest priority cognitive users based on the priority information of each cognitive user; generally speaking, the smaller the priority value, the higher the priority level of the cognitive user:

[0177] 6.1 Initialize a priority array of length N and fill the priority values ​​of all users into the array;

[0178] 6.2 Sort the elements in the array from small to large in numerical order;

[0179] 6.3 Initialize a user array of length N, sort each cognitive user according to the priority value, and fill the position of each element in the priority array into the user array;

[0180] 6.4 The order in which the elements of the user array are arranged from the beginning to the end is the processing order of the following algorithm;

[0181] 7. Use the greedy algorithm to solve the mathematical model of spectrum allocation for any bandwidth access scenario.

[0182] This step follows the cognitive user processing order determined in point 6 and uses a greedy algorithm to solve the spectrum allocation model based on the minimum conflict principle, the minimum accommodation principle, and the leftmost placement principle to obtain the working frequency band of each cognitive user:

[0183] 7.1 Input the frequency band information occupied by the primary user and the cognitive user information. The total number of cognitive users is N:

[0184] Cognitive user information includes: priority p k , working bandwidth B k , natural frequency band start frequency f gsk , natural frequency band end frequency f gek , geographic location longitude coordinate x k , geographic location latitude coordinate y k , geographic location height coordinate z k , transmitter power P k , receiver sensitivity S k , the starting frequency of the working frequency band is f sk , operating frequency band end frequency f ek ; k∈[1,N];

[0185] The total number of primary users A, the information of the primary user working frequency band includes: the starting frequency f of the working frequency band of the nth primary user asn and the stop frequency f aen , n∈[1,A];

[0186] 7.2 The frequency band applied for by each cognitive user shall be used as the initial working frequency band;

[0187] 7.3 A new round of iteration begins with the working frequency bands of each cognitive user determined in the previous round of iteration as the starting point;

[0188] 7.4 Determine the next Cognitive User for processing in the order of processing determined in point 6;

[0189] 7.5 Determine whether the cognitive user generates interference with other cognitive users when using the current working frequency band. If so, continue to use the frequency band as the working frequency band and execute 7.6; otherwise, execute 7.9;

[0190] 7.6 Based on the basic idea of ​​the greedy algorithm "making the best choice at the moment", the available sub-bands of the user are screened according to the principle of minimum conflict: all available sub-bands of the cognitive user are traversed, and the conflict coefficient of the user working in each sub-band is calculated when other users are in the current working state, and the available sub-band with the minimum conflict coefficient is found:

[0191] If there is only one available sub-band with the smallest conflict coefficient, this sub-band is used as the working band of the cognitive user and step 7.9 is executed;

[0192] If there are multiple available sub-bands with the smallest conflict coefficient, save the information of these sub-bands and execute 7.7;

[0193] 7.7 Further filter the available sub-bands according to the minimum accommodation principle: traverse all the bands saved in point 7.6 and find the available sub-band with the smallest bandwidth of the corresponding available band:

[0194] If there is only one such sub-band, this sub-band shall be used as the working band of the cognitive user and 7.8 shall be executed;

[0195] If there are multiple such sub-bands, save the information of these bands and execute 7.9;

[0196] 7.8 Further screen the available sub-frequency bands according to the leftmost placement principle: traverse all frequency bands saved in 7.7, find the available sub-frequency band with the smallest center frequency, and use this frequency band as the working frequency band of the cognitive user;

[0197] 7.9 Determine whether there are still users that have not been processed in this iteration:

[0198] If yes, go to 7.4;

[0199] Otherwise, compare whether the working frequency band of each user in this iteration has changed compared with the previous iteration:

[0200] If there is a change, execute 7.3;

[0201] If there is no change, go to 7.10;

[0202] 7.10 Save the working frequency band information of each cognitive user;

[0203] Step 8: Allocate the working frequency band found in the previous step to each user to complete the allocation plan.

[0204] The effect of the present invention can be further illustrated by the following simulation experiment:

[0205] 1. Simulation conditions

[0206] 1. Main user working frequency band parameter setting

[0207] Two main users are set in the simulation experiment. The main user working frequency band parameters are set according to the main user working frequency band information content described in step 1 as shown in Table 1:

[0208] Table 1 Main user working frequency band information

[0209]

[0210] 2. Cognitive user parameter settings

[0211] Ten cognitive users are set in the simulation experiment. The settings of the parameters of the ten cognitive users according to the cognitive user information content described in step 2 are shown in Table 2:

[0212] Table 2 Input cognitive user information

[0213]

[0214]

[0215] 3. Algorithm parameter setting: spectrum cutting step size is 1;

[0216] 4.Simulation software: VS2019.

[0217] 2. Simulation content and results

[0218] 1. Simulation content: Based on the above simulation conditions, the method flow of the present invention was programmed and simulated to generate a spectrum allocation scheme.

[0219] 2. Analysis of simulation results: The spectrum allocation scheme is shown in Table 3:

[0220] Table 3 Algorithm output results

[0221]

[0222]

[0223] It can be seen from Table 3 that the present invention can converge in a very short time, and the spectrum allocation scheme finally generated can reduce interference between users and can give priority to guaranteeing the service needs of high-priority users.

[0224] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access, characterized in that: The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access comprises: S1: Determine a main user and a cognitive user group, wherein the cognitive user group includes a plurality of cognitive users; S2: constructing a spectrum allocation model for any bandwidth access scenario according to the frequency band information occupied by the primary user and the cognitive user information; S3: obtaining a plurality of available sub-frequency bands corresponding to the working bandwidth using the working bandwidth according to the working frequency band information and the inherent frequency band of the primary user; S4: solving the spectrum allocation model using a greedy algorithm according to the available sub-frequency bands and the priority of each cognitive user to obtain a working frequency band for each cognitive user; S5: Allocating spectrum to each cognitive user according to the working frequency band of each cognitive user; Between step S1 and step S2, the composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access further includes: Obtain the working frequency band status information of the primary user according to the current electromagnetic environment; Acquire information of each cognitive user in the cognitive user group, wherein the cognitive user information includes cognitive user priority, applied frequency band, inherent frequency band, transmitter power, receiving sensitivity and working bandwidth; The step S2 comprises: S21: setting constraints on the working frequency band of each cognitive user; S22: Obtaining a frequency domain interference coefficient according to the working bandwidth of the cognitive user and the constraint condition of the working frequency band; S23: Obtaining a spatial interference coefficient according to the constraints of the working frequency band, transmitter power, and receiving sensitivity; S24: Obtaining a cognitive user interference coefficient according to the frequency domain interference coefficient, the spatial domain interference coefficient and the cognitive user priority; S25: obtaining an objective function of a spectrum allocation model according to the cognitive user interference coefficient; S26: Obtaining the spectrum allocation model according to the constraint condition of the working frequency band and the objective function of the spectrum allocation model; The objective function of the spectrum allocation model for: in, N is the total number of cognitive users, is the cognitive user interference coefficient, is the spatial interference coefficient, is the frequency domain interference coefficient, is the priority value with the largest absolute value, For the j The priority value of each user, i Indicates i cognitive users; The spectrum allocation model is: in, and Respectively represent k The starting frequency and ending frequency of the working frequency band of each cognitive user; For the k Working bandwidth of each cognitive user; and Respectively represent k The starting frequency and ending frequency of the inherent frequency band of each cognitive user; and Respectively represent n The starting frequency and ending frequency of the working frequency band of each primary user, , A is the number of primary users; , abs is the absolute value function.

2. The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access according to claim 1, characterized in that: In step S21, the constraint condition of the cognitive user working frequency band is: in, and Respectively represent k The starting frequency and ending frequency of the working frequency band of each cognitive user; and Respectively represent k The starting frequency and ending frequency of the inherent frequency band of each cognitive user; and Respectively represent n The starting frequency and ending frequency of the working frequency band of each primary user, , A is the number of primary users, abs is the absolute value function, N is the total number of cognitive users, For the k The working bandwidth of each cognitive user.

3. The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access according to claim 1, characterized in that: In step S22, the frequency domain interference coefficient for: in, Respectively represent i cognitive user and j The working bandwidth of cognitive users, and For the i cognitive user and j The center frequency of the operating frequency band of the cognitive user, and , , N is the total number of cognitive users; , ; Respectively represent i The starting frequency of the working frequency band of the cognitive user, j The starting frequency of the working frequency band of the cognitive user, i The end frequency of the working frequency band of the cognitive user, j The end frequency of the working frequency band of each cognitive user, .

4. The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access according to claim 1, characterized in that: In step S23, the spatial interference coefficient for: in, Indicates i The transmitter power of each cognitive user, Indicates j The receiver sensitivity of a cognitive user, Indicates that from i The central frequency of the transmission of a cognitive user is The signal propagates to the j The energy consumed in the process of recognizing users , in, Indicates i Cognitive users and j The straight-line distance between two cognitive users.

5. The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access according to claim 1, characterized in that: In step S24, the cognitive user interference coefficient for: in, is the spatial interference coefficient, is the frequency domain interference coefficient, is the priority value with the largest absolute value, For the j The priority value of each user, N is the total number of cognitive users.

6. The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access according to claim 1, characterized in that: The step S3 comprises: S31: Determine available frequency resources for each cognitive user according to the working frequency band information of the primary user and the inherent frequency band; S32: performing spectrum cutting on the available frequency resources of each cognitive user according to its working bandwidth to obtain a plurality of available sub-frequency bands of the same size as the working bandwidth.

7. The composite criterion fast spectrum allocation method for multi-user arbitrary bandwidth access according to claim 1, characterized in that: The step S4 comprises: S41: taking the applied frequency band of each of the cognitive users as the initial working frequency band; S42: sorting the cognitive users according to their priorities; S43: Determine whether the current working frequency band of the current cognitive user interferes with other cognitive users. If so, use the current working frequency band as the working frequency band of the current cognitive user and proceed to step S44; otherwise, proceed to step S49; S44: using a greedy algorithm, screening a number of available sub-frequency bands of the currently recognized user to obtain a first available sub-frequency band; S45: Determine whether the number of the first available sub-frequency bands is greater than 1, if so, proceed to step S46; otherwise, use the first available sub-frequency band as the working frequency band of the current cognitive user, proceed to the next cognitive user and return to step S43; S46: screening all the first available sub-frequency bands by using the minimum accommodation principle to obtain a second available sub-frequency band; S47: Determine whether the number of the second available sub-frequency bands is greater than 1. If so, proceed to step S48; otherwise, use the second available sub-frequency band as the working frequency band of the current cognitive user, proceed to the next cognitive user and return to step S43; S48: screening all the second available sub-frequency bands by using the leftmost placement principle to obtain a third available sub-frequency band; S49: Determine whether the current recognized user is the last recognized user, if so, proceed to step S410; otherwise, proceed to the next recognized user and return to step S43; S410: Determine whether the current working frequency band of each cognitive user is different from the working frequency band of each cognitive user in the previous iteration. If so, take the working frequency band of each cognitive user in this iteration as the starting point and return to step S43; otherwise, save the current working frequency band of each cognitive user.

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