A mobile communication multi-satellite multi-beam overlapping coverage resource efficient allocation method

Abstract

The present application relates to a kind of mobile communication multi-star multi-beam overlap coverage area resource efficient allocation method, belong to satellite communication technical field.The present application is directed to the mobile communication satellite of multi-point beam coverage, in the region of multi-star overlap coverage, due to frequency reuse between beams, when the frequency resource needed to be occupied is more in large traffic, it is easy to appear the problem of larger co-frequency interference, generate the resource demand of overlap coverage area using the way of normalization, by establishing the co-frequency interference power calculation model including resource allocation matrix, co-frequency beam angle matrix and the function of received power and satellite beam angle parameter, design the planning algorithm with the minimum co-frequency interference of overlap coverage area as target, calculate the resource use scheme of overlap coverage area, can maximize the satellite resource of multi-star overlap coverage region, provide decision basis for the resource use of entire overlap coverage area.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to a method for efficient allocation of resources in multi-satellite, multi-beam overlapping coverage areas for mobile communication. Background Technology

[0002] With the gradual application of fixed-coverage multi-beam satellites, the scientific and rational use of overlapping coverage areas to obtain satellite resources will become a key technology and challenge in system resource allocation.

[0003] Currently, the main method for resource allocation in overlapping coverage areas is to use a resource allocation approach where frequencies are not shared between beams of the same frequency. This method considers fewer constraints, has a relatively simple algorithm, but suffers from low resource utilization efficiency and cannot solve the problem of high resource demand in overlapping coverage areas. Summary of the Invention

[0004] To maximize the utilization of satellite resources in overlapping coverage areas of multiple satellites, this invention proposes an efficient resource allocation method for such areas in mobile communication. This method employs a normalization process, converting resource requirements into basic frequency units for easier allocation. To ensure reasonable resource allocation results, a genetic algorithm is introduced, aiming to minimize co-channel interference in overlapping coverage areas. This algorithm constructs a co-channel interference power calculation model that includes parameters such as the resource allocation matrix, beam angle, and received power. This approach minimizes the impact of co-channel interference while ensuring resource requirements are met, resulting in a scientifically sound resource allocation scheme.

[0005] The technical solution adopted in this invention is as follows:

[0006] A method for efficient resource allocation in multi-satellite, multi-beam overlapping coverage areas of mobile communications includes the following steps:

[0007] Step 1: Calculate the traffic volume of the beam in the overlapping coverage area and obtain the resource requirements of the overlapping coverage area through normalization.

[0008] Step 2: Allocate resources using a resource allocation method where frequencies are not shared between beams of the same frequency, and determine whether the resource requirements can be met. If they can be met, generate a resource allocation scheme according to the current resource allocation method; otherwise, proceed to Step 3.

[0009] Step 3: Using a planning method aimed at minimizing co-frequency interference in overlapping coverage areas, resource planning is carried out in the overlapping coverage areas to generate planning schemes that meet resource requirements.

[0010] Furthermore, step 1 specifically includes the following steps:

[0011] Step 101, the traffic volume of the overlapping coverage area beam is calculated as: total call duration F per unit time. iand total data traffic T per unit time i , wherein i represents a beam number;

[0012] step 102: counting historical operation data to obtain the service volume that can be carried by one basic frequency point per unit time: call duration and data traffic

[0013] step 103: calculating the number of basic frequency points C required by each beam i :

[0014]

[0015] Further, step 3 specifically comprises the following steps:

[0016] step 301: setting a population size f, assuming that there are p beams in an overlapping coverage area, each beam has n basic frequency points, and encoding resources of the overlapping coverage area into a character string with p×n binary numbers, each bit has a value of 0 or 1, 1 indicates that the frequency point has been allocated, and 0 indicates that the frequency point has not been allocated;

[0017] step 302: randomly generating chromosomes according to an encoding rule, screening the generated chromosomes, and selecting chromosomes in which the number of 1s in the chromosomes is equal to until the number of individuals in the initial population is f;

[0018] step 303: defining a fitness function as total co-channel interference power, calculating a fitness value of each chromosome, and sorting the chromosomes in ascending order of the fitness values;

[0019] step 304: selecting g chromosomes in a roulette manner, wherein g<f, to form a temporary population;

[0020] step 305: randomly selecting several pairs of chromosomes from the temporary population to perform single-point crossover operation;

[0021] step 306: performing mutation operation on each chromosome in the temporary population after the crossover operation according to a mutation rate;

[0022] step 307: screening chromosomes in the temporary population, calculating a fitness value of each chromosome, and sorting the chromosomes in ascending order of the fitness values;

[0023] step 308: selecting individuals with lower fitness from an original population in proportion to replace individuals with higher fitness in the temporary population, keeping the population size as f to form a new population, and sorting the chromosomes in ascending order of fitness values;

[0024] step 309: judging whether the number of iterations is reached, if yes, going to step 310, otherwise, going to step 304;

[0025] Step 310: The chromosome with the lowest fitness value is the optimal resource allocation scheme for the multi-star overlapping coverage area.

[0026] Furthermore, the fitness function in step 303 is calculated as follows:

[0027] Step 303-1: Based on the resource allocation results of the overlapping coverage area defined in Step 302 and the resource allocation results of other beams, establish an n×m dimensional resource allocation matrix B, where n is the number of beams and m is the number of intermediate frequency points of the beams. Each bit in the matrix takes a value of 0 or 1. st =1 indicates that the t-th frequency of the s-th beam has been assigned, B st =0 indicates that the t-th frequency of the s-th beam is not assigned;

[0028] Step 303-2, establish the directional angle matrix A = (a... sd ), matrix element a sd The angle between the center points of beams s and d at the satellite antenna;

[0029] Step 303-3: Establish the functional relationship between the received power E and the angle between the satellite antenna and the receiver:

[0030] E = E o -E a (a)

[0031] Among them, E o E represents the received power at the beam center. a (a) is the attenuation value of the received power when the angle between the receiver and the beam center is α;

[0032] Step 303-4: Based on the satellite antenna directional angle matrix of the co-frequency beamgroup and the functional relationship between received power and satellite antenna angle, calculate the interference power I received by other beams at the intermediate frequency point t of beam s in the overlapping coverage area. st :

[0033]

[0034] Among them, beams s and d are beams of the same frequency;

[0035] Step 303-5, for I st After normalization, we get V st ;

[0036] Step 303-6: Calculate the sum of the interference powers V of all beams in the overlapping coverage area. sum :

[0037]

[0038] Vsum This is the value of the fitness function.

[0039] Compared with the prior art, the beneficial effects achieved by this invention are as follows:

[0040] 1. This invention proposes to use a normalization process to process the running data into resource requirements in units of basic frequency points, which facilitates the introduction of general optimization search algorithms and makes the resource planning results have high application value.

[0041] 2. This invention employs a genetic algorithm aimed at minimizing co-channel interference in multi-satellite overlapping coverage areas. It constructs a co-channel interference power calculation model that includes parameters such as resource allocation matrix, beam angle, and received power. This model can minimize the impact of inter-satellite and inter-beam co-channel interference when the traffic volume in the overlapping coverage area is large. Attached Figure Description

[0042] Figure 1 This is a flowchart of the steps in an embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of the overlapping coverage area according to an embodiment of the present invention. Detailed Implementation

[0044] The present invention will now be described in further detail with reference to the accompanying drawings.

[0045] like Figure 1 As shown, a method for efficient resource allocation in a multi-satellite, multi-beam overlapping coverage area for mobile communication includes the following steps:

[0046] Step (1): Calculate the traffic volume of the beam in the overlapping coverage area, and obtain the resource requirements of the overlapping coverage area through normalization; Step 1 specifically includes the following steps:

[0047] Step 101, the traffic volume of the overlapping coverage area beam is calculated as: total call duration F per unit time. i Total data flow per unit time T i , where i represents the beam number;

[0048] Step 102: Statistically analyze historical operational data to obtain the service capacity that a basic frequency point can handle per unit time: call duration and data traffic

[0049] Step 103: Calculate the number of fundamental frequency points C required for each beam. i :

[0050]

[0051] Step (2): Use the resource allocation method of not sharing frequencies between beams of the same frequency to allocate resources, and determine whether the resource requirements can be met. If they can be met, generate a resource allocation scheme according to the current resource allocation method; otherwise, proceed to step (3).

[0052] Step (3): Using a planning algorithm that minimizes co-channel interference in overlapping coverage areas, resource planning is performed in the overlapping coverage areas to generate a planning scheme that meets resource requirements. Step 3 specifically includes the following steps:

[0053] Step 301: Set the population size f. Assume that there are p beams in the overlapping coverage area and n basic frequency points in each beam. Encode the resources of the overlapping coverage area into a string with p×n binary numbers. Each bit is 0 or 1, where 1 indicates that the frequency point has been allocated and 0 indicates that the frequency point has not been allocated.

[0054] Step 302: According to the encoding rules, randomly generate chromosomes, and then filter the generated chromosomes, selecting those with a number of 1s equal to... The chromosomes are counted until the initial population size is f;

[0055] Step 303: Define the fitness function as the total co-frequency interference power, calculate the fitness value of each chromosome, and sort the chromosomes in ascending order of fitness value;

[0056] The fitness function is calculated as follows:

[0057] Step 303-1: Based on the resource allocation results of the overlapping coverage area defined in Step 302 and the resource allocation results of other beams, establish an n×m dimensional resource allocation matrix B, where n is the number of beams and m is the number of intermediate frequency points of the beams. Each bit in the matrix takes a value of 0 or 1. st =1 indicates that the t-th frequency of the s-th beam has been assigned, B st =0 indicates that the t-th frequency of the s-th beam is not assigned;

[0058] Step 303-2, establish the directional angle matrix A = (a... sd ), matrix element a sd The angle between the center points of beams s and d at the satellite antenna;

[0059] Step 303-3: Establish the functional relationship between the received power E and the angle between the satellite antenna and the receiver:

[0060] E = E o -E a (a)

[0061] Among them, E o E represents the received power at the beam center. a(a) is the attenuation value of received power when the angle between the beam and the beam center is a;

[0062] Step 303-4: according to the satellite antenna direction included angle matrix of the co-frequency beam group and the functional relationship between received power and satellite antenna included angle, calculate the interference power I received by carrier frequency t in beam s in the overlapping coverage area from other beams st :

[0063]

[0064] wherein, beam s and beam d are co-frequency beams;

[0065] Step 303-5, normalize I s t to obtain V st =V(I st );

[0066] wherein:

[0067]

[0068] α is the weighted average of all I st after rounding;

[0069] Step 303-6, calculate the sum V of all beam interference powers in the overlapping coverage area sum :

[0070]

[0071] V sum is the value of the fitness function.

[0072] Step 304, select g chromosomes by roulette wheel method, where g < f, to form a temporary population;

[0073] Step 305, randomly select several pairs of chromosomes from the temporary population for single-point crossover operation;

[0074] Step 306, perform mutation operation on each chromosome in the temporary population after crossover operation according to the mutation rate;

[0075] Step 307, screen the chromosomes in the temporary population, calculate the fitness value of each chromosome, and arrange the chromosomes in ascending order of fitness values;

[0076] Step 308, select individuals with lower fitness from the original population in proportion to replace individuals with higher fitness in the temporary population, keep the population size as f to form a new population, and arrange the chromosomes in ascending order of fitness values;

[0077] Step 309, determine whether the number of iterations has been reached, if yes, go to step 310, otherwise go to step 304;

[0078] Step 310: The chromosome with the lowest fitness value is the optimal resource allocation scheme for the multi-star overlapping coverage area.

[0079] This invention addresses the issue of significant co-channel interference in mobile communication satellites with multi-beam coverage, particularly in areas with overlapping coverage due to frequency reuse between beams and high traffic volumes requiring substantial frequency resources. The invention employs a normalized approach to generate resource requirements for the overlapping coverage area. By establishing a co-channel interference power calculation model incorporating parameters such as a resource allocation matrix, a co-channel beam angle matrix, and a function of received power versus satellite beam angle, a planning algorithm is designed to minimize co-channel interference in the overlapping coverage area. This algorithm calculates resource utilization schemes for the overlapping coverage area, maximizing the utilization of satellite resources and providing a basis for decision-making regarding resource usage across the entire overlapping coverage area.

[0080] The present invention has been described in detail above with reference to the accompanying drawings. However, those skilled in the art should understand that the specification is for interpreting the claims, and the scope of protection of the present invention shall be determined by the claims. Any modifications made based on the present invention shall be within the scope of protection claimed.

Claims

1. A method for efficient resource allocation in multi-satellite, multi-beam overlapping coverage areas of mobile communication, characterized in that, Comprising the following steps: Step 1: counting the service traffic of beams where the overlapping coverage area is located, and obtaining the resource demand of the overlapping coverage area through normalization processing; Step 2: performing resource allocation by adopting a resource allocation mode in which frequencies between co-frequency beams are not shared, and judging whether the resource demand can be met, generating a resource allocation scheme according to the current resource allocation mode if the resource demand can be met, and going to step 3 otherwise; Step 3: performing resource planning on the overlapping coverage area by adopting a planning method targeting at minimum co-frequency interference in the overlapping coverage area, and generating a planning scheme meeting the resource demand; specifically comprising the following steps: Step 301: setting a population size f, supposing that there are p beams in the overlapping coverage area, each beam has n basic frequency points, encoding the resources of the overlapping coverage area into a character string with p×n binary numbers, each bit takes a value of 0 or 1, 1 indicates that the frequency point is allocated, and 0 indicates that the frequency point is not allocated; Step 302: According to the encoding rules, randomly generate chromosomes, and then filter the generated chromosomes, selecting those with a number of 1s equal to... The chromosomes are counted until the initial population size is f; The number of basic frequency points required for each beam; Step 303: defining a fitness function as total co-frequency interference power, calculating the fitness value of each chromosome, and sorting the chromosomes in ascending order according to the fitness values; wherein the calculation mode of the fitness function is as follows: Step 303-1: Based on the resource allocation results of the overlapping coverage area defined in Step 302 and the resource allocation results of other beams, establish an n×m dimensional resource allocation matrix B, where n is the number of beams and m is the number of intermediate frequency points of the beams. Each bit in the matrix takes a value of 0 or 1. This indicates that the t-th frequency of the s-th beam has been assigned. This indicates that the t-th frequency of the s-th beam is unassigned; Step 303-2: Establish the directional angle matrix of the satellite antenna for the same frequency beam. Matrix elements The angle between the center points of beams s and d at the satellite antenna; Step 303-3: establishing a functional relationship between received power E and an included angle of satellite antennas: in, The received power at the beam center. This represents the attenuation of received power when the angle between the receiver and the beam center is α. Step 303-4: Based on the satellite antenna directional angle matrix of the co-frequency beamgroup and the functional relationship between received power and satellite antenna angle, calculate the interference power received by other beams at the intermediate frequency point t of beam s in the overlapping coverage area. : wherein, a beam s and a beam d are co-frequency beams; Step 303-5, for After normalization, we get ; Step 303-6: Calculate the sum of all beam interference powers in the overlapping coverage area. : That is, the value of the fitness function; Step 304: selecting g chromosomes in a roulette mode, wherein g<f, to form a temporary population; Step 305: randomly selecting several pairs of chromosomes from the temporary population to perform single-point crossover operation; Step 306: performing mutation operation on each chromosome in the temporary population after the crossover operation according to a mutation rate; Step 307: screening chromosomes in the temporary population, calculating a fitness value of each chromosome, and sorting the chromosomes in ascending order according to the fitness values; Step 308: selecting individuals with lower fitness from the original population in proportion to replace individuals with higher fitness in the temporary population, keeping the population size as f to form a new population, and sorting the chromosomes in ascending order according to the fitness values; Step 309: judging whether the number of iterations is reached, going to step 310 if yes, and going to step 304 otherwise; Step 310: the chromosome with the lowest fitness value is the optimal resource allocation scheme for the multi-satellite overlapping coverage area.

2. The method for efficient resource allocation in multi-satellite, multi-beam overlapping coverage areas for mobile communication according to claim 1, characterized in that, Step 1 specifically comprises the following steps: Step 101, the traffic volume of the overlapping coverage area beam is calculated as: total call duration per unit time. Total data flow per unit time , where i represents the beam number; Step 102: Statistically analyze historical operational data to obtain the service capacity that a basic frequency point can handle per unit time: call duration and data traffic ; Step 103: Calculate the number of fundamental frequency points required for each beam. : 。

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