CN111786715A - Method for automatically sensing quality of experience of Chinese user on satellite constellation - Google Patents

Method for automatically sensing quality of experience of Chinese user on satellite constellation Download PDF

Info

Publication number
CN111786715A
CN111786715A CN202010500534.6A CN202010500534A CN111786715A CN 111786715 A CN111786715 A CN 111786715A CN 202010500534 A CN202010500534 A CN 202010500534A CN 111786715 A CN111786715 A CN 111786715A
Authority
CN
China
Prior art keywords
communication
area
satellite
quality
experience
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010500534.6A
Other languages
Chinese (zh)
Other versions
CN111786715B (en
Inventor
戴翠琴
张明健
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chongqing University of Post and Telecommunications
Original Assignee
Chongqing University of Post and Telecommunications
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Chongqing University of Post and Telecommunications filed Critical Chongqing University of Post and Telecommunications
Priority to CN202010500534.6A priority Critical patent/CN111786715B/en
Publication of CN111786715A publication Critical patent/CN111786715A/en
Application granted granted Critical
Publication of CN111786715B publication Critical patent/CN111786715B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851—Systems using a satellite or space-based relay
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851—Systems using a satellite or space-based relay
    • H04B7/18513—Transmission in a satellite or space-based system
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/1851—Systems using a satellite or space-based relay
    • H04B7/18519—Operations control, administration or maintenance

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Astronomy & Astrophysics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Radio Relay Systems (AREA)

Abstract

The invention relates to a method for automatically sensing the experience quality of a Chinese user on a satellite constellation, which belongs to the technical field of wireless communication and comprises the following steps: dividing the area of the Chinese land into a plurality of regions by using the STK, and acquiring a region coverage performance parameter V (i) by using the STK; judging whether the satellite covers a target area, if so, acquiring the equipment density of the Internet of things in each area; calculating a communication blocking rate B (i) and a communication quality Q (i); calculating the required capacity C (i) of each area; calculating the communication cost and the profit performance W (i) of each area; automatically generating experience quality performance indexes in each grid area in China by using a weighted overall evaluation formula; and establishing an experience quality evaluation model by taking the QoE factors as optimization target indexes, and solving the optimal experience quality E by a multi-layer tabu search algorithm MTLS. The method and the device improve the experience degree of the user in satellite communication and realize quantitative evaluation of experience quality.

Description

Method for automatically sensing quality of experience of Chinese user on satellite constellation
Technical Field
The invention belongs to the technical field of wireless communication. In particular to a method for automatically sensing the experience quality of Chinese users to satellite constellations.
Background
Compared with the traditional communication mode, the satellite communication becomes an important component of the next generation network due to the advantages of wide coverage range, large communication capacity, high communication quality and the like. However, a single satellite can only cover a part of the earth surface, and multiple low-orbit satellites are required to be arranged on different orbits according to a certain phase requirement to realize the coverage of the whole area of China, and the overall performance of the satellite communication system is improved through reasonable orbit design and constellation configuration. Therefore, a primary task in the design of satellite communication systems is the satellite constellation design. The reasonable constellation structure and the orbit design can fully utilize satellite resources, thereby reducing the complexity of the system and improving the performance of the satellite communication system.
According to the existing research on constellation design, the satellite coverage can be divided into global satellite constellation design and regional satellite constellation design. However, the focus of current research is the selection and optimization of algorithms. Due to the wide coverage and large cardinality of the global satellite constellation optimization target, the research target of the global satellite constellation design mainly focuses on the optimization performance of the satellite itself. In contrast, regional satellite constellation design is limited to a specific region, facilitating the study of optimization objectives outside of the satellite. Due to the fact that users are insufficient, the iridium companies are bankruptcy, and in the current satellite design, the actual quality of user experience is concerned more and more. However, due to the diversity of satellite communication user requirements and the difficult matching of satellite resources, it is difficult for users to directly evaluate the experience quality of the satellite constellation.
The invention provides a QoE-based satellite constellation user satisfaction evaluation system, which integrates four QoE factors including coverage performance, communication quality, area demand capability and profitability. Firstly, a SIoT system model containing a LEO satellite constellation and ground Internet of things equipment is established. The QoE problem is then given, which consists of four direct impact factors of communication connectivity, blocking rate, transmission rate and cost. On the basis, a multi-layer tabu search algorithm (MLTS) is designed to improve the QoE factor, and comprises a classical tabu search algorithm (CTS), a greedy tabu search algorithm (GTS) and a Tabu Search Genetic Algorithm (TSGA). CTS aims to improve communication quality, GTS aims to expand area demand capability, and TSGA aims to improve profitability. The experimental result shows that the designed constellation has the characteristic of automatic sensing performance in QoE optimization compared with the traditional constellation, and reasonable and effective prejudgment evaluation is carried out on the user experience quality after the commercial satellite constellation is put into practical use.
Disclosure of Invention
The present invention is directed to solving the above problems of the prior art. A method for automatically sensing the experience quality of Chinese users to satellite constellations is provided. The technical scheme of the invention is as follows:
a method for automatically sensing the experience quality of Chinese users to satellite constellations comprises the following steps:
dividing the area of the Chinese land into a plurality of areas by using the STK, and acquiring area coverage performance parameters by using the STK;
judging whether the satellite covers a target area, if so, acquiring the equipment density of the Internet of things in each area;
calculating a communication blocking rate B (i) and a communication quality Q (i);
calculating the required capacity C (i) of each area;
calculating the communication cost and the profit performance W (i) of each area;
automatically generating experience quality performance indexes in each grid area in China by using a weighted overall evaluation formula; the QoE factor is used as an optimization target index, an experience quality evaluation model is established,
optimizing communication quality Q (i) by adopting a classical tabu search algorithm CTS, and searching for maximum communication quality Q (i) under the limit of a communication blocking rate B (i); adopting a greedy tabu search algorithm GTS to optimize the area demand capacity C (i), and searching the maximized area demand capacity C (i) on the basis of a CTS initial solutiontotal(ii) a Searching for the optimal solution Wmax with the maximum profitability W (i) by adopting a tabu search genetic algorithm TSGA; and solving the optimal experience quality E by the three multi-layer tabu search algorithms MTLS.
Further, the QoE factors include four QoE factors of coverage performance, communication quality, area demand capability and profit capability.
Further, the defining and calculating the coverage performance includes the steps of:
1) judging the coverage performance of the Chinese area grids by using a user-defined theorem 1;
theorem 1: the ground area grid is in the satellite coverage area as the necessary condition: thetaEATheta, where thetaEAIs the angle between the ground station E and the sub-satellite point A, and theta is the half geocentric angle, then if the ground user coordinates are known
Figure BDA0002524634950000031
Coordinate of point under satellite
Figure BDA0002524634950000032
The following can be obtained:
Figure BDA0002524634950000033
Figure BDA0002524634950000034
the constraint condition for obtaining the coverage performance is formula (3),
Figure BDA0002524634950000035
wherein V (i) coverage performance in the ith China area. And the formula (3) is used as a precondition of a user experience quality perception system to judge whether to perform the following information processing and acquisition.
Further, when the grid area meets the coverage performance, defining and calculating the device density for the grid point specifically includes: the IoT device density represents the number of devices which are potentially connected with an LEO-IoT network in a specific area, and is calculated by counting the satellite communication population in China;
i represents the grid number, the current grid average population density value is calculated, and Ni represents the number of all grids. G (i) represents the total population in the ith grid, and the population for operating the internet of things device to perform satellite communication is as in formula (4):
S(i)＝G(i)·ρcom·ρsat(4)
where is ρcomProportion of communicating users, psatRepresenting the proportion of users who can use internet of things devices and can communicate with satellites, knowing the number of satellite user devices s (i) in an area, the communication activation rate is α, and obtaining the IoT device density according to the formula (5):
Sα(i)＝α·S(i) (5)
devices S for simultaneous use in a determined areaα(i) Then, the communication quality Q (i) of the satellite constellation communication can be calculated, the main factor for calculating Q (i) is the communication blocking rate, and when the number of people needing to simultaneously talk in the total beam exceeds the maximum number of people available for simultaneously talking, the communication blocking rate B (i) can be generated;
Figure BDA0002524634950000036
where λ is the probability of a user communication failure, μ is the expected value of multiple access interference, σ2Variance of the expected value μ, erfcIs an error function. Since the higher the communication blocking rate is, the lower the communication quality is, and the communication blocking rate is a prerequisite for affecting the communication quality, the true simultaneous talker S is given in consideration of the communication blocking rater(i) Is a formula (7)
Sr(i)＝Sα(i)·Q(i) (7)
Further, the step of calculating the required capacity c (i) of each area specifically includes:
according to the Shannon formula, the capacity C of a single channeluserIs formula (8):
Figure BDA0002524634950000041
in the above formula, BiIndicates the bandwidth, P, of the ith devicesatFor satellite transmission power, GsatFor satellite antenna gain, GusersIs the user side antenna gain, LotherFor other fades in free space, including fades in rain, water vapour, clouds, etc., diDistance of the ith device to the satellite, daverageAveraging the distance of the device to the satellite, N0Noise power density, B bandwidth.
Therefore, the total required capacity C (i) of users in a single area and the maximum throughput C which can be accommodated by a single satellite can be obtainedsatMaximum throughput of one track is Ctotal：
C(i)＝Cuser·Sr(i) (9)
Csat＝Cuser·NS(10)
Ctotal＝NsatCsat(11)
Wherein N isSRepresenting maximum capacity, N, of a multibeam satellitesatFor maximum number of channels for a single satellite
Further, the calculating the communication cost and the profit performance w (i) of each area specifically includes:
according to the real number of people who talk, the income performance can be obtained:
Figure BDA0002524634950000042
wherein the content of the first and second substances,
Figure BDA0002524634950000051
average amount of consumption per year of users on communication per grid:
Figure BDA0002524634950000052
wherein k represents the city k-line grade standard, E (k) represents the per-capita GDP (ten thousand yuan/year) of the k-line city, rho (k) represents the proportion of the k-line city in the grid, and rho represents the proportion of the communication fee in the per-capita GDP.
Further, the experience quality performance indexes in each grid area of China are automatically generated by applying a weighted overall evaluation formula; the QoE factor is used as an optimization target index, and an experience quality evaluation model is established, wherein the specific formula is as follows:
Figure BDA0002524634950000053
the following conditions are met:
Figure BDA0002524634950000054
ρcweight, rho, representing the area demand capacitywWeight, ρ, representing the contribution of the profitabilityqIndicates the assigned communication quality, and n (i) indicates the ith area in china.
Further, after an experience quality evaluation model is established, a multi-layer tabu search algorithm is introduced, and for different QoE factors, a classical tabu search algorithm is respectively utilized to optimize the maximum communication quality Q (i) under the limitation of a communication blocking rate B (i); intelligently optimizing the regional demand capacity C (i) by a greedy tabu search algorithm; the tabu search genetic algorithm maximizes the profitability w (i). And solving the optimal experience quality E through an integral weighting formula by using a multi-layer tabu search algorithm MTLS (maximum likelihood search) consisting of the three seed algorithms.
The invention has the following advantages and beneficial effects:
the scheme of the invention provides a constellation design scheme with an experience quality evaluation system by analyzing the actual situations of overlarge user base number and uneven satellite resource distribution in the satellite Internet of things and the problem of the quality of experience of users on the satellite constellation, and combining the communication demand and the experience quality of Internet of things users in China. The main innovation of the invention is that from the perspective of users, concepts and calculation formulas of the equipment density, the communication quality, the area demand capacity and the constellation profitability of the Internet of things are provided, so that the experience quality of Chinese users on constellations is comprehensively evaluated. Firstly, the density of the Internet of things equipment is calculated by taking a China satellite Internet of things network as a research object and counting China satellite communication population. Fully embodies the uniqueness of the invention in the Chinese area. Secondly, the quality of the communication is related to the satisfaction degree of the user on the satellite communication. Most of the prior art people research the effectiveness and reliability of communication, but are not suitable for satellite communication with serious interference. In particular, the present invention proposes a method for judging communication quality by calculating satellite-ground communication blocking rate according to the characteristics of satellite communication, which is difficult for the prior art to think. Then, the area required capacity reflects the data volume of satellite communication in different areas of China, and directly influences the speed of satellite communication. The impact of the communication rate on the quality of the user experience is not appreciated by the prior art. Finally, the profitability is directly related to the establishment of communication tariffs, and the influence of the communication tariffs on whether the user uses satellite communication is not involved in the prior research. The invention designs the indexes after fully researching the concerned direction of Chinese users on future satellite communication. The QoE evaluation system proposed by the present invention is therefore not easily imaginable to the skilled person. Furthermore, the invention discloses an integral QoE weighting formula according to the specific characteristics of China. Therefore, the invention is unique and inventive.
As can be seen from fig. 1, since the QoE optimization scheme is progressive, in order to better embody the characteristics of QoE auto-perception, the invention designs a multi-layer tabu search algorithm (MTLS for short) including a classical tabu search algorithm (CTS), a greedy tabu search algorithm (GTS), and a Tabu Search Genetic Algorithm (TSGA). Firstly, the communication quality Q (i) is optimized by using CTS, and the maximum communication quality Q under the limitation of the communication blocking rate B (i) is searched. Then, adopting GTS to optimize the area demand capacity C (i), and searching the area demand capacity C (i) to be maximized C on the basis of CTS initial solution B (i)total. Finally, the candidate solution C is obtained by using the GTStotalFinding the optimal solution W for maximizing the profitability W (i) as the limiting condition of the TSGAmax. And finally, the indexes are specially processed through an integral weighting formula, and experience quality parameters of Chinese users to the satellite constellation are automatically generated. The automatic perception of the quality of experience of the constellation is comprehensively and efficiently realized. The experience quality brought to the user by the satellite constellation is improved. Meanwhile, according to the actual geographic condition, the satellite resources are reasonably distributed better.
Drawings
FIG. 1 is an overall flow chart of the present invention providing a preferred embodiment of the present invention;
FIG. 2 is a schematic diagram of a quality of experience and intelligent algorithm;
fig. 3 is a coverage performance analysis graph.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail and clearly with reference to the accompanying drawings. The described embodiments are only some of the embodiments of the present invention.
The technical scheme for solving the technical problems is as follows:
a satellite constellation design scheme for automatically sensing user experience quality obtains an optimal QoE performance index through information processing and intelligent algorithm calculation of a QoE factor. The coverage performance V (i) corresponding to the communication connection rate is a precondition, the blocking rate reflects the communication quality Q (i), the communication rate is influenced by the channel capacity C (i), and the communication cost depends on the income performance W (i) of the commercial satellite. Aiming at different QoE indexes, different intelligent optimization algorithms CTS are respectively designed to find the maximum communication quality Q (i) under the limitation of the communication blocking rate B (i). GTS is the search for the maximum C (i) of the area demand capacity C (i) based on the initial solution of CTStotal. The objective of the TSGA is to find the optimal solution Wmax with maximized profitability w (i) based on the candidate solutions generated in the first two steps. And finally, automatically sensing the overall experience quality E of the user on the satellite constellation by using the result through a formula 15. The method comprises the following specific steps:
the first step is as follows: when the target number of areas is set, the area in China is automatically divided into 35 areas by STK software. Respectively calculating the communication blocking rate B (i), the communication quality Q (i), the actual number of people in communication S in each arear(i) User demand capacity C (i), profitability W (i), and the like. The final E value can be obtained.
The second step is that: the coverage performance of the satellite constellation is described and calculated. In the constellation QoE optimization process, coverage performance directly affects the connectivity of the user equipment, and thus the coverage performance is also a precondition for estimating the constellation QoE. The blocking rate of the user equipment is a core problem in the quality of the user experience, and it directly reflects the quality of the communication. Due to the complex population distribution in the Chinese region, the ground IoT equipment density is calculated to accurately calculate the communication blocking rate. And solving the area demand capacity by means of the communication quality in the special area. And the value of the area demand capacity is determined by the transmission rate. The transmission rate of the device is a major issue in the user experience. The last step is the statistical calculation of the communication tariff. The consumption capacity of different areas in China is defined by acquiring the per-capita consumption situation of different areas in different cities in China and by using an innovative formula. Thereby determining the magnitude of the communication gain performance.
The third step: after each information module is defined and calculated, a weighted integral evaluation formula is used to automatically generate experience quality performance indexes in each grid area in China. And taking the QoE factor in the second step as an optimization target index to establish an experience quality evaluation system. And a weighted value formula suitable for the Chinese situation is created, so that the evaluation system is practical and closer to the Chinese situation.
The fourth step: we found by study of different QoE factors that the optimal algorithm for each factor was not consistent. Therefore, a multi-layer tabu search algorithm (MLTS) is adopted to intelligently calculate the overall performance of the QoE of the satellite constellation. And finally, a constellation design scheme suitable for the best user experience quality in China is obtained.
Preferably, in the second step, QoE factors such as coverage performance, internet of things equipment density, area demand capacity, profit performance and the like are defined and calculated respectively. The method comprises the following steps:
1) judging the coverage performance of the Chinese area grids by using theorem 1;
theorem 2: the ground area grid is in the satellite coverage area as the necessary condition: thetaEATheta is less than or equal to theta. Wherein theta isEAIs the angle between the ground station E and the sub-satellite point A, and theta is the half geocentric angle, then if the ground user coordinates are known
Figure BDA0002524634950000081
Coordinate of point under satellite
Figure BDA0002524634950000082
The following can be obtained:
Figure BDA0002524634950000083
Figure BDA0002524634950000084
therefore we can derive the constraint of coverage performance as formula (3), where v (i) coverage performance in the ith chinese region. And taking the formula (3) as a precondition of a user experience quality perception system, and judging whether to perform the following information processing and acquisition:
Figure BDA0002524634950000091
2) and if the grid area is judged to accord with the coverage performance, defining and calculating the equipment density of the grid point. IoT device density represents the number of devices potentially connecting the LEO-IoT network in a particular area. Since the present invention is studying LEO-IoT networks in china, we calculate IoT device density by counting the satellite communication population in china.
Because most of the current internet-of-things equipment is controlled by people (except unmanned vehicles, unmanned aerial vehicles and the like), the density of the ground internet-of-things equipment is basically determined according to the ground population density. i represents the grid number, the current grid average population density value is calculated, and Ni represents the number of all grids. G (i) represents the total population in the ith grid, and the population for operating the internet of things device to perform satellite communication is as in formula (4):
S(i)＝G(i)·ρcom·ρsat(4)
where is ρcomProportion of communicating users, psatKnowing the number of satellite user devices in an area s (i), the communication activation rate is α, and the IoT device density is obtained from equation (5):
Sα(i)＝α·S(i) (5)
devices S for simultaneous use in a determined areaα(i) The communication quality q (i) of the satellite constellation communication can then be calculated. Calculating Q (i)The main factor is the communication blocking rate. When the number of persons requiring simultaneous calls in the total beam exceeds the maximum number of persons available for simultaneous calls Sr(i) Then, a communication blocking rate b (i) is generated.
Figure BDA0002524634950000092
Where λ is the probability of a user communication failure, μ is the expected value of multiple access interference, σ2The variance of the expected value μ, erfc is the error function. Since the higher the communication blocking rate, the lower the communication quality, the communication blocking rate is a prerequisite for affecting the communication quality. So the number of real simultaneous talking persons S after considering the communication blocking rater(i) Is a formula (7)
Sr(i)＝Sα(i)·Q(i) (7)
3) The satellite equally divides the channel resources according to the number of users in the coverage area, and because the number NZ of channels which can be provided by the satellite is fixed, the total required capacity of the users in the ground area can be obtained after the single-channel capacity is obtained. According to the shannon formula, the capacity of a single channel is formula (8):
Figure BDA0002524634950000101
in the above formula, BiIndicates the bandwidth, P, of the ith devicesatFor satellite transmission power, GsatFor satellite antenna gain, GusersIs the user side antenna gain, LotherFor other fades in free space, including fades in rain, water vapour, clouds, etc., diDistance of the ith device to the satellite, daverageAveraging the distance of the device to the satellite, N0Noise power density, B bandwidth.
Therefore, the total required capacity C (i) of users in a single area and the maximum throughput C which can be accommodated by a single satellite can be obtainedsat, maximum throughput of one track is Ctotal：
C(i)＝Cuser·Sr(i) (9)
Csat＝Cuser·NS(10)
Ctotal＝NsatCsat(11)
Wherein N isSRepresenting maximum capacity, N, of a multibeam satellitesatFor maximum number of channels for a single satellite
4) The revenue performance represents a source of revenue for the satellite communications service. Only after the income performance is determined, the communication charge can be determined according to the population number of China.
The source of revenue for satellite communication services is based on the amount of data successfully transmitted and the time of equipment usage, but is limited by communication delays and blocking rates. China is a typical non-uniform population country, and therefore these factors cannot be ignored for discussing the profitability of the constellation. Therefore, according to the real number of the call, the income performance can be obtained:
Figure BDA0002524634950000111
wherein the content of the first and second substances,
Figure BDA0002524634950000112
average amount of consumption per year of users on communication per grid:
Figure BDA0002524634950000113
wherein k represents the city k-line grade standard, E (k) represents the per-capita GDP (ten thousand yuan/year) of the k-line city, rho (k) represents the proportion of the k-line city in the grid, and rho represents the proportion of the communication fee in the per-capita GDP. How to price the satellite communication charges in the country will therefore directly affect the number of users used.
Preferably, the third step establishes the following formula (14) for the overall quality of experience assessment system:
Figure BDA0002524634950000114
preferably, the fourth step of automatically sensing the overall experience quality of the user on the satellite constellation is characterized by introducing a multi-layer tabu search algorithm. The function is to adopt different intelligent algorithms aiming at different QoE factors. And respectively optimizing the maximum communication quality Q (i) under the limitation of the communication blocking rate B (i) by using a classical tabu search algorithm. The region demand capacity c (i) is intelligently optimized by a greedy tabu search algorithm. The tabu search genetic algorithm maximizes the profitability w (i). The specific flow is shown in fig. 2.
When the target number of areas is set, the area of China is automatically divided into 35 areas by STK software. Respectively calculating the communication blocking rate B (i), the user satisfaction degree R (i), the actual number of communication persons S in each arear(i) Demand capacity C (i), profitability W (i), and the like. On the basis, a multi-layer tabu search algorithm (MLTS) is designed to improve the QoE factor. And finally, the final overall user experience quality in the Chinese region can be obtained by using a formula (14).
The concepts and models involved in the present disclosure are as follows:
1. network model
The main research scene of the invention is the constellation coverage of the ground internet of things in the Chinese area. The space part of the network scene of the satellite internet of things is composed of a low-orbit small satellite constellation, and the ground part is composed of a large number of various user terminals. And inter-satellite links are arranged among the satellites in the space part, and ground network connection is arranged among the ground terminals. The satellite and the ground user terminal are connected by a satellite-ground link. The network characteristic of the interconnection of everything is realized. The ground IoT device density is not uniform due to the uneven distribution of chinese population and the like. Therefore, if the conditions such as the device density in the ground area are not fully considered, the problems such as uneven communication link distribution, increased communication blocking rate and the like occur, and the service quality of the constellation is seriously influenced.
2. The technical scheme of the invention is as follows:
the invention provides a QoE-based satellite constellation user satisfaction evaluation system, which integrates four QoE factors including coverage performance, communication quality, area demand capability and profitability. Firstly, a SIoT system model containing a LEO satellite constellation and ground Internet of things equipment is established. The QoE problem is then given, which consists of four direct impact factors of communication connectivity, blocking rate, transmission rate and cost. On the basis, a multi-layer tabu search algorithm (MLTS) is designed to improve the QoE factor, and comprises a classical tabu search algorithm (CTS), a greedy tabu search algorithm (GTS) and a Tabu Search Genetic Algorithm (TSGA). CTS aims to improve communication quality, GTS aims to expand area demand capability, and TSGA aims to improve profitability. Generally, the scheme comprises two modules, namely an information processing module and an intelligent algorithm module, and is specifically described as follows:
1. information processing module
In the process of optimizing the QoE of the constellation, the coverage performance directly affects the connectivity of the user equipment, and therefore the coverage performance is also a precondition for evaluating the QoE of the constellation, for example, FIG. 3 is a single-satellite-to-ground coverage model diagram, wherein S is a satellite, E is the position of a ground station or a center point of a ground area, A is the coordinates of a satellite subsatellite point, h is the satellite orbit height, r is the earth orbit radius, d is the satellite-to-ground distance, α is the satellite half view angle, and theta is the half-geocentric angle,
Figure BDA0002524634950000124
is the user elevation angle.
Therefore, the single star-to-ground coverage area can be obtained:
Figure BDA0002524634950000121
and (3) proving that: from the geometric relationship of fig. 3, the half-geocentric angle θ and the half satellite view angle α are:
Figure BDA0002524634950000122
Figure BDA0002524634950000123
knowing the half-geocentric angle θ and the half satellite view angle α, the single-satellite-to-ground coverage diameter can be obtained:
Figure BDA0002524634950000131
the distance of the satellite from the ground equipment can be obtained and used for solving the free space loss in the next section:
d2＝r2+(r+h)2-2r(r+h)cosθ (20)
2. intelligent algorithm module
We introduce a multi-layer tabu search algorithm into the constellation QoE optimization model. As shown in fig. 2, we define and explain the respective QoE factors in the optimization scheme, and set forth the specific structure and function of the MLTS. Due to the characteristic that the loops of the constellation QoE optimization model are buckled, each stage has the optimal algorithm, and the algorithms are extracted, so that a multi-layer tabu search algorithm is formed. The multi-layer tabu search algorithm is composed of CTS, TGS and TSGA. After a set of multi-layer tabu search algorithm, a satellite resource allocation scheme for maximizing QoE can be obtained. Respectively carrying out optimal allocation on resources on the QoE factors by utilizing an MLTS algorithm according to different requirements of different areas on the QoE factors;
inputting:
v (i) the star-to-ground connectivity of the ith region;
(i) the area demand capacity of the ith area;
b, (i) the communication blockage rate of the ith area;
q (i) communication quality of the ith area;
Sγ(i) the actual internet of things equipment density of the ith area;
w (i) benefit performance in the area of the ith zone;
and E (i) the quality of experience of the user in the area of the ith area.
And (3) outputting:
Csat: single-satellite maximum capacity within the orbit sub-satellite point trajectory;
Qmax: maximum communication quality within the orbit sub-satellite point trajectory;
w: maximum profit in orbit subsatellite point trajectory;
and E, optimizing the maximum QoE value corresponding to the optimal track by using an MLTS algorithm.
An objective function:
Figure BDA0002524634950000141
the above examples are to be construed as merely illustrative and not limitative of the remainder of the disclosure. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.

Claims (8)

1. A method for automatically sensing the experience quality of Chinese users to satellite constellations is characterized by comprising the following steps:
dividing the area of the Chinese land into a plurality of regions by using the STK, and acquiring a region coverage performance parameter V (i) by using the STK;
judging whether the satellite covers a target area, if so, acquiring the equipment density of the Internet of things in each area;
calculating a communication blocking rate B (i) and a communication quality Q (i);
calculating the required capacity C (i) of each area;
calculating the communication cost and the profit performance W (i) of each area;
automatically generating experience quality performance indexes in each grid area in China by using a weighted overall evaluation formula; the QoE factor is used as an optimization target index, an experience quality evaluation model is established,
optimizing communication quality Q (i) by adopting a classical tabu search algorithm CTS, and searching for maximum communication quality Q (i) under the limit of a communication blocking rate B (i); adopting a greedy tabu search algorithm GTS to optimize the area demand capacity C (i), and searching the maximized area demand capacity C (i) on the basis of a CTS initial solutiontotal(ii) a Finding the optimal solution W of the maximum profitability W (i) by adopting a tabu search genetic algorithm TSGAmax(ii) a Calculating by the above three kinds of multi-layer tabu searchThe method MTLS solves the best experience quality E.
2. The method of claim 1, wherein the QoE factors include four QoE factors of coverage performance, communication quality, area demand capability, and profitability.
3. The method according to claim 1, wherein the defining and calculating the coverage performance comprises the steps of:
judging the coverage performance of the Chinese area grids by using theorem 1;
theorem 1: the ground area grid is in the satellite coverage area as the necessary condition: thetaEATheta, where thetaEAIs the angle between the ground station E and the sub-satellite point A, and theta is the half geocentric angle, then if the ground user coordinates are known
Figure FDA0002524634940000011
Coordinate of point under satellite
Figure FDA0002524634940000012
The following can be obtained:
Figure FDA0002524634940000013
Figure FDA0002524634940000014
the constraint condition for obtaining the coverage performance is shown as a formula (3)
Figure FDA0002524634940000021
Wherein V (i) coverage performance in the ith China area. And taking the formula (3) as a precondition of a user experience quality perception system, and judging whether to perform the following information processing and acquisition.
4. The method according to claim 3, wherein when the grid area conforms to the coverage performance, the method for automatically sensing the quality of experience of the chinese user on the satellite constellation defines and calculates the device density for the grid point, specifically comprising: the IoT device density represents the number of devices which are potentially connected with the SIoT network in a specific area, and is calculated by counting the satellite communication population in China;
i represents the grid number, the current grid average population density value is calculated, and Ni represents the number of all grids. G (i) represents the total population in the ith grid, and the population for operating the internet of things device to perform satellite communication is as in formula (4):
S(i)＝G(i)·ρcom·ρsat(4)
where is ρcomProportion of communicating users, psatRepresenting the proportion of users who can use internet of things devices and can communicate with satellites, knowing the number of satellite user devices s (i) in an area, the communication activation rate is α, and obtaining the IoT device density according to the formula (5):
Sα(i)＝α·S(i) (5)
devices S for simultaneous use in a determined areaα(i) Then, the communication quality Q (i) of the satellite constellation communication can be calculated, the main factor for calculating Q (i) is the communication blocking rate, and when the number of people needing to simultaneously talk in the total beam exceeds the maximum number of people available for simultaneously talking, the communication blocking rate B (i) can be generated;
Figure FDA0002524634940000022
where λ is the probability of a user communication failure, μ is the expected value of multiple access interference, σ2The variance of the expected value μ, erfc is the error function. Since the higher the communication blocking rate is, the lower the communication quality is, and the communication blocking rate is a prerequisite for affecting the communication quality, the number of real simultaneous calls after considering the communication blocking rateSr(i) Is a formula (7)
Sr(i)＝Sα(i)·Q(i) (7)
5. The method according to claim 4, wherein the step of calculating the required capacity C (i) of each area specifically comprises:
according to the shannon formula, the capacity of a single channel is formula (8):
Figure FDA0002524634940000033
in the above formula, BiIndicates the bandwidth, P, of the ith devicesatFor satellite transmission power, GsatFor satellite antenna gain, GusersIs the user side antenna gain, LotherFor other fades in free space, including fades in rain, water vapour, clouds, etc., diDistance of the ith device to the satellite, daverageAveraging the distance of the device to the satellite, N0Noise power density, B bandwidth;
therefore, the total required capacity C (i) of users in a single area and the maximum throughput C which can be accommodated by a single satellite can be obtainedsatMaximum throughput of one track is Ctotal：
C(i)＝Cuser·Sr(i) (9)
Csat＝Cuser·NS(10)
Ctotal＝NsatCsat(11)
Wherein N isSRepresenting maximum capacity, N, of a multibeam satellitesatThe maximum number of channels for a single satellite.
6. The method according to claim 5, wherein the calculating of the communication cost and the profit performance w (i) in each area specifically comprises:
according to the real number of people who talk, the income performance can be obtained:
Figure FDA0002524634940000031
wherein the content of the first and second substances,
Figure FDA0002524634940000032
average amount of consumption per year of users on communication per grid:
Figure FDA0002524634940000041
wherein k represents the city k-line grade standard, E (k) represents the per-capita GDP (ten thousand yuan/year) of the k-line city, rho (k) represents the proportion of the k-line city in the grid, and rho represents the proportion of the communication fee in the per-capita GDP.
7. The method according to claim 6, wherein the method for automatically sensing the quality of experience of the users of China on the satellite constellation is characterized in that the performance index of the quality of experience in each grid area of China is automatically generated by applying a weighted overall evaluation formula; the QoE factor is used as an optimization target index, and an experience quality evaluation model is established, wherein the specific formula is as follows:
Figure FDA0002524634940000042
the following conditions are met:
Figure FDA0002524634940000043
ρcweight, rho, representing the area demand capacitywWeight, ρ, representing the contribution of the profitabilityqIndicates the assigned communication quality, and n (i) indicates the ith area in china.
8. The method according to claim 7, wherein after the experience quality assessment model is established, a multi-layer tabu search algorithm is introduced, and for different QoE factors, a classical tabu search algorithm is respectively used to optimize the maximum communication quality q (i) under the restriction of the communication blocking rate b (i); intelligently optimizing the regional demand capacity C (i) by a greedy tabu search algorithm; the tabu search genetic algorithm carries out maximum calculation on the profit performance W (i); and solving the optimal experience quality E through an integral weighting formula by using a multi-layer tabu search algorithm MTLS (maximum likelihood search) consisting of the three seed algorithms.
CN202010500534.6A 2020-06-04 2020-06-04 Method for automatically sensing quality of experience of Chinese user on satellite constellation Active CN111786715B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010500534.6A CN111786715B (en) 2020-06-04 2020-06-04 Method for automatically sensing quality of experience of Chinese user on satellite constellation

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010500534.6A CN111786715B (en) 2020-06-04 2020-06-04 Method for automatically sensing quality of experience of Chinese user on satellite constellation

Publications (2)

Publication Number Publication Date
CN111786715A true CN111786715A (en) 2020-10-16
CN111786715B CN111786715B (en) 2022-05-03

Family

ID=72754603

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010500534.6A Active CN111786715B (en) 2020-06-04 2020-06-04 Method for automatically sensing quality of experience of Chinese user on satellite constellation

Country Status (1)

Country Link
CN (1) CN111786715B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112887008A (en) * 2021-01-18 2021-06-01 上海航天测控通信研究所 Space-based VDES (vertical double-layer data storage) based downlink communication link parameter determination system and method
CN113726401A (en) * 2021-05-26 2021-11-30 重庆邮电大学 Satellite constellation reliability assessment method based on satellite survivability and link survivability
CN115276756A (en) * 2022-06-21 2022-11-01 重庆邮电大学 Low-orbit satellite constellation optimization design method for guaranteeing service quality
CN117556579A (en) * 2024-01-11 2024-02-13 中国科学院空天信息创新研究院 Multi-star cooperative optimal observation method

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103236911A (en) * 2013-04-09 2013-08-07 中国科学院计算技术研究所 Multicast cognitive pilot channel message propagation method and device for cognitive system
CN107086888A (en) * 2017-03-02 2017-08-22 重庆邮电大学 A kind of two-layer hybrid satellite network optimization design and its covering performance appraisal procedure
US20180351652A1 (en) * 2016-08-05 2018-12-06 Nxgen Partners Ip, Llc System and method providing network optimization for broadband networks
CN110210700A (en) * 2019-04-19 2019-09-06 中国科学院遥感与数字地球研究所 More star dynamic task planing methods of task based access control priority towards emergency response
CN110913414A (en) * 2019-12-19 2020-03-24 中国卫通集团股份有限公司 QoS guarantee system of 5G satellite convergence network

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103236911A (en) * 2013-04-09 2013-08-07 中国科学院计算技术研究所 Multicast cognitive pilot channel message propagation method and device for cognitive system
US20180351652A1 (en) * 2016-08-05 2018-12-06 Nxgen Partners Ip, Llc System and method providing network optimization for broadband networks
CN107086888A (en) * 2017-03-02 2017-08-22 重庆邮电大学 A kind of two-layer hybrid satellite network optimization design and its covering performance appraisal procedure
CN110210700A (en) * 2019-04-19 2019-09-06 中国科学院遥感与数字地球研究所 More star dynamic task planing methods of task based access control priority towards emergency response
CN110913414A (en) * 2019-12-19 2020-03-24 中国卫通集团股份有限公司 QoS guarantee system of 5G satellite convergence network

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
HYUN LONG KIM: ""A Study on a QoS/QoE Correlation Model for QoE"", 《2010 THE 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT)》 *
段凯峰: "面向低轨卫星的资源调度研究", 《中国优秀硕士学位论文全文数据库》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112887008A (en) * 2021-01-18 2021-06-01 上海航天测控通信研究所 Space-based VDES (vertical double-layer data storage) based downlink communication link parameter determination system and method
CN112887008B (en) * 2021-01-18 2022-05-27 上海航天测控通信研究所 Space-based VDES (vertical double-layer data storage) based downlink communication link parameter determination system and method
CN113726401A (en) * 2021-05-26 2021-11-30 重庆邮电大学 Satellite constellation reliability assessment method based on satellite survivability and link survivability
CN113726401B (en) * 2021-05-26 2023-03-28 重庆邮电大学 Satellite constellation reliability assessment method based on satellite survivability and link survivability
CN115276756A (en) * 2022-06-21 2022-11-01 重庆邮电大学 Low-orbit satellite constellation optimization design method for guaranteeing service quality
CN115276756B (en) * 2022-06-21 2023-09-26 重庆邮电大学 Low orbit satellite constellation optimization design method for guaranteeing service quality
CN117556579A (en) * 2024-01-11 2024-02-13 中国科学院空天信息创新研究院 Multi-star cooperative optimal observation method
CN117556579B (en) * 2024-01-11 2024-03-22 中国科学院空天信息创新研究院 Multi-star cooperative optimal observation method

Also Published As

Publication number Publication date
CN111786715B (en) 2022-05-03

Similar Documents

Publication Publication Date Title
CN111786715B (en) Method for automatically sensing quality of experience of Chinese user on satellite constellation
CN113131989B (en) Design method for frequency spectrum sharing simulation time parameter of NGSO constellation system
Al-Hraishawi et al. Traffic simulator for multibeam satellite communication systems
US20060199546A1 (en) Electro-magnetic propagation modeling
US20050085186A1 (en) Method and apparatus for measuring adjacent satellite interference
Park et al. A tractable approach to coverage analysis in downlink satellite networks
CN105827301B (en) With recognizing star joint spectrum efficiency and the optimal prohibition zone width method of AF panel in integral system
CN113078940B (en) Gateway station site selection method and system of broadband low-orbit satellite communication system
CN112399429B (en) Communication scene modeling method and system for satellite communication system
Mignardi et al. On the performance improvement of a cellular network supported by an unmanned aerial base station
CN113098590B (en) Satellite constellation configuration parameter optimization method facing non-uniform service coverage
Jiang et al. Regional LEO satellite constellation design based on user requirements
CN113114397A (en) Heaven and earth common-frequency sharing lumped interference estimation method for satellite mobile communication system
CN114301510B (en) 6G low-earth-orbit satellite network satellite deployment method based on inter-satellite distance constraint
Al Homssi et al. Deep learning forecasting and statistical modeling for Q/V-band LEO satellite channels
CN106850036A (en) A kind of removable spot beam dispatching method of middle rail satellite system based on priority
Feltrin et al. Potential for deep rural broadband coverage with terrestrial and non-terrestrial radio networks
Talgat et al. Stochastic geometry-based uplink performance analysis of IoT over LEO satellite communication
Ojaniemi et al. Effect of geolocation database update algorithms to the use of TV white spaces
Cheng et al. Study on gateway station deployment for large scale LEO satellite constellation networks
Paternina et al. LoRAWAN network coverage testing design using open-source low-cost hardware
Goodman et al. Quality of service and bandwidth efficiency of cellular mobile radio with variable bit-rate speech transmission
CN114826940B (en) Performance evaluation method and device for world fusion network
CN116321465B (en) Satellite frequency spectrum sensing method and system based on phased array antenna
Singh et al. Refraction reverse learning based hybrid Namib Antenna Beetle Optimization for resource allocation in NB-IoT platform

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant