CN118317371A - Semantic-differentiated star-ground fusion network scheduling method - Google Patents
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Abstract
The invention relates to a semantic-differentiated satellite-ground fusion network scheduling method, and belongs to the field of satellite Internet of things. The method comprises the following steps: s1: sensing satellite-ground link attribute; s2: evaluating service flow and user service quality; s3: satellite-ground access and switching decision; s4: DDPG intelligent flow distribution. S1, calculating satellite-ground link attributes between ground nodes and visible satellites in real time; s2, sensing semantic features of service flow to be transmitted by the ground user and evaluating QoS requirements of the ground user on different network performance indexes; s3, selecting a proper satellite to make an access or switching decision based on satellite-to-ground link attributes of the visible satellite and QoS requirements of users; s4 allocates in advance the traffic to be transmitted on the to-be-switched or access link. The invention can effectively reduce the switching times and the switching failure rate, and maintain the on-board load balance and higher user QoS level.
Description
Technical Field
The invention belongs to the field of satellite Internet of things, and relates to a semantic-differentiated satellite-ground fusion network scheduling method.
Background
The third generation partnership project (3 GPP) standard TR38.913 proposes a scenario in which satellite networks are utilized to assist in terrestrial communications. In 3gpp TS 22.261, the satellite access technology is determined as one of the underlying access technologies of the 5G network. These documents define the development direction of the mobile communication network and lay the foundation for the development of the satellite-ground fusion network (STIN). However, due to the isomerism of the satellite network and the ground cellular network system, and the dual mobility caused by the regular movement of the satellite and the random movement of the user nodes, how to realize seamless and smooth satellite-ground intelligent switching and ensure the service continuity between the isomerism satellite and the ground system is a key problem to be solved in the STIN mobility management, and is also an important embodiment of the STIN to really realize the integrated service.
Although the cell handoff technology of terrestrial cellular networks is well established, the number of users covered by a single satellite will far exceed the number of users of a terrestrial base station, meaning that the handoff requirements for users on a single satellite will be hundreds of times that of a single terrestrial base station, which will lead to a more massive signaling and decision-making scale. Unlike medium and high earth orbit satellites, the LEO satellite orbit period is only 85-150 min, and the continuous visible time of a single satellite is greatly reduced. Taking Starlink constellation as an example, the longest overhead time of its satellite is about 4 minutes, which means that even stationary users must be handed over at least once every 4 minutes, while today's MCN supports Gbps-level data transmission rates and internet access services for massive users, compared to earlier satellite networks, which also makes the low-orbit satellite network need to handle satellite-to-ground traffic with larger data volumes and more complex types. Therefore, it is necessary to research an intelligent traffic scheduling algorithm oriented to satellite-to-ground interconnection, reasonably select an optimal switching mode according to different channel conditions, network congestion conditions and network index requirements of specific traffic, reduce communication interruption and error rate, and improve communication quality.
Disclosure of Invention
Therefore, the invention aims to provide a semantic-differentiated satellite-ground fusion network scheduling method, which comprises the steps of firstly providing a perception and evaluation method of satellite-ground link attribute, then dividing according to the type characteristics of different service flows, determining the priority of the satellite-ground link attribute to different network performance indexes, further designing a customized QoS evaluation function, finally designing an intelligent flow distribution strategy based on DDPG, utilizing the predictability of satellite periodic operation, analyzing the link state information of available satellites in advance, distributing the flow to be transmitted, and ensuring service continuity and user service quality. DDPG (DEEP DETERMINISTIC Policy Gradient) is a reinforcement learning algorithm that combines the Actor-Critic architecture with a Deep Neural Network (DNN).
In order to achieve the above purpose, the present invention provides the following technical solutions:
a semantic-differentiated star-ground fusion network scheduling method specifically comprises the following steps:
S1: sensing satellite-ground link attribute;
S11: firstly, determining respective accurate positions of a ground node and a satellite node based on a Global Positioning System (GPS), calculating a ground-satellite elevation angle, and further calculating residual visible time T m,n (T) between the ground node n and a visible satellite m by combining a satellite height and a satellite operation period, wherein the LEO satellite operation period is as follows according to a kepler third law:
the remaining visible time of the satellite to the earth can be expressed as
Wherein the method comprises the steps ofIs the radian of the movement track of the satellite under the satellite.
S12: due to the relative motion between the LEO satellites and the UEs and the inter-channel interference, the channel quality of the satellite-to-earth link varies rapidly, which is another factor in ensuring the quality of service of the terminal. Considering free space loss and multipath effect of satellite-to-ground link long-distance transmission, the channel gain between the ground node n and the visible satellite m is denoted as h m,n (t), and further, the signal-to-interference-and-noise ratio (SINR) P m,n (t) of the user n selecting to access or switch to the satellite m at the time t is calculated.
S13: in order to maintain the load balance of the satellites and reduce the switching failure rate, the number of idle channels of one satellite is used as one of switching criteria and the satellite with more free channels is preferentially selected. The UE acquires load information according to the periodical broadcast of the satellite, and l m (t) is set as the free channel number of the LEO satellite m at the time t, and the idle channel number of the satellite is expressed asWhere 0.ltoreq.l m(t)≤Cmax,Cmax is the maximum number of free channels owned by the satellite.
S2: the service flow and user QoS evaluation specifically comprises the following steps:
s21: the ground node perceives the semantic features of the service to be transmitted and classifies different service flows, including:
session-type traffic: the real-time requirement is higher, but short blocking, such as voice and video call, can be accepted;
streaming media type service: the main requirement is low time delay and time delay jitter, the real-time requirement is not high, and the transmission is usually unidirectional, such as audio, video on demand and the like;
Interaction class/control class traffic: the single transmission data volume is smaller, but the transmission accuracy requirement is higher, such as Web browsing, network games, short messages and other services;
Transmission class: the requirements on time delay and time delay jitter are low, and the highest possible bandwidth and the lowest packet loss rate are required, such as mail transmission, file downloading, uploading and other services;
message class/collection class: the data transmission frequency is high, the data volume is small, the bandwidth requirement is low, such as data acquisition of the Internet of things, communication software chat service and the like.
S22: the demands of specific types of service flows on network performance indexes such as available bandwidth, time delay, packet loss rate and the like are evaluated to different degrees, and the specific grades are determined and are divided into four grades which are no-demand, low, higher and high. According to shannon's theorem, the bandwidth between the user n and the visible satellite m can be calculated as:
Wherein the method comprises the steps of Representing the number of users associated with the mth satellite; w m is the total bandwidth that the satellite can provide.
The switching delay is greatly affected because different access satellites can cause corresponding changes in the data transmission path. Therefore, to guarantee QoS requirements of users, the delay overhead is a constraint condition for selecting candidate access satellites, expressed as the sum of average waiting delay, propagation delay and processing delay:
Dm,n(t)＝dwait+dprop+dproc
the packet loss rate is calculated as the ratio between the amount of data lost per unit time transmitted and the total amount of data transmitted:
s3: satellite-to-ground access and handoff decisions
S31: the ground user node continuously monitors satellite-ground link wireless signals, generates a measurement report, and feeds back measurement information to the RRC node of the current satellite at regular intervals;
S32: after receiving the switching request, the source RRC makes a switching decision according to a measurement report of the terminal and other system information (such as on-board load, energy consumption and the like); the QoS measurement obtained by different service flows for the satellite-ground links with the same attribute is considered to be different, and the user QoS of the service flows with different types is calculated as follows:
Wherein eta 1＞η2 measures the preference degree of different service flows to corresponding network performance indexes.
S4: DDPG intelligent flow distribution
S41: after receiving the switching request, the target RRC sends switching request confirmation to the source RRC; after the confirmation is finished, the target satellite reserves channel resources for the switching user, generates a switching command containing information such as a random access channel and switching time, and forwards the switching command to the user node through the current service satellite;
s42: satellite-ground link attribute of M visible satellites is used as reinforcement learning state space { Ρ 1(t),ρ2(t),...,ρM (t) }, where ρ m(t)＝{Tm,n(t),Pm,n(t),lm (t) } is allocated as the motion space with actual satellite selection and traffic on the corresponding path{ Rou t,scht }, user QoS: Θ (T) is a reward function, satellite-to-ground switching decision capability of an intelligent agent is trained based on DDPG algorithm, and in a time slot to be switched, according to the residual visible time T m,n (T) and the channel bandwidth B m,n (T) of the satellite, a data stream which can be sent in the duration of a link is calculated in advance, so that selection of a next satellite can be evaluated before the current satellite moves out of the visible range;
s43: and stopping uplink and downlink data transmission of the current satellite by the ground node, randomly accessing the target base station according to the random access information and the synchronous signaling of the target node, releasing the resources of the current satellite, disconnecting the resources and completing the switching.
The invention has the beneficial effects that: aiming at the demands of different service flows on different degrees of network performance indexes such as bandwidth, time delay and the like, a customized QoS evaluation function is designed, and the satellite-to-ground switching strategy can be adjusted in a targeted manner, so that the high QoS of a user and the on-satellite load balance are maintained; by designing the intelligent flow scheduling algorithm based on DDPG, the maximum data volume transmitted by the time slot to be switched is planned in advance, the switching times are obviously reduced, and meanwhile, the switching success rate is ensured.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
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For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a diagram of a star-ground fusion network architecture according to the present invention;
fig. 2 is a flow chart of star-to-ground switching and traffic scheduling according to the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Fig. 1 shows a star-ground fusion network architecture, which includes the following constituent modules:
Ground part: the system comprises a ground cellular network and provides access services such as conventional mobile communication, internet of vehicles and the Internet; secondly, the ground control center is responsible for monitoring and adjusting the running state of the satellite, providing ground service support for a satellite network, and simultaneously, the ground station can also provide communication coverage for surrounding local areas; finally, some communication applications that are difficult to cover by conventional land networks are also included, such as ocean communication, emergency communication, environmental monitoring, logistics management, and the like.
The high altitude platform network mainly comprises flight nodes such as airship, unmanned aerial vehicle, hot air balloon. On one hand, the nodes can transmit back some observation and sensing data by means of the wide area coverage capability of the satellite network layer, and on the other hand, the nodes can also serve as a buffer access layer between the satellite network and the ground network, so that switching caused by periodic movement of the satellite is reduced. Meanwhile, the HAP can also construct a dynamic self-organizing network according to task demands, and provide finer and flexible communication access service for users in the atmosphere.
The satellite network layer mainly comprises satellites covering high, medium and low orbits, and the satellites in different orbits form a constellation according to a certain rule so as to provide a global-oriented service. The required positioning of different satellite communication systems varies greatly in terms of satellite orbit height, number of satellites, number of orbital planes and manner of satellite deployment, but in any way it is necessary to have the ability to forward or exchange signals for terrestrial devices.
Fig. 2 is a satellite-to-ground handover and traffic scheduling flow, comprising the steps of:
(0) The ground user node continuously monitors satellite-ground link wireless signals, generates a measurement report, and periodically feeds back measurement information to a Radio Resource Control (RRC) node of a current satellite; the measurement information comprises the satellite-ground remaining visible time, the received signal strength and the number of idle channels of the satellite. Firstly, determining respective accurate positions of a ground node and a satellite node based on a Global Positioning System (GPS), calculating a ground-satellite elevation angle, and further calculating residual visible time T m,n (T) between the ground node n and a visible satellite m by combining a satellite height and a satellite operation period, wherein the LEO satellite operation period is as follows according to a kepler third law:
The remaining visible time of the satellite to the earth can be expressed as
Wherein the method comprises the steps ofIs the radian of the movement track of the satellite under the satellite.
The signal-to-interference-and-noise ratio (SINR) of user n with satellite m at time t is expressed as
Wherein p m is the signal transmission power; Representing aggregate interference from other coverage signals; Indicating that satellite m is associated with user n at time t; ζ 2 represents noise power.
The number of idle channels of the satellite isWherein 0 is less than or equal to l m(t)≤Cmax, which is the free channel number of LEO satellite m at time t, and C max is the maximum free channel number owned by the satellite.
(1) The source RRC node determines a target access point according to the link state information of the ground node visible satellite;
(2) Inquiring global identifiers of nodes where an access and mobility management function (AMF) of a target access satellite and an RRC function are located, and sending a switching request to a source RRC node;
(3) And after receiving the switching request, the source RRC makes a switching decision according to the measurement report of the terminal and other system information (such as satellite load, energy consumption and the like). The evaluation criterion mainly considers the demands of the service flow on different degrees of network performance indexes such as available bandwidth, time delay, packet loss rate and the like, and determines the concrete grades of the service flow, and the service flow is divided into four grades of no requirement, low, higher and high. According to shannon's theorem, the bandwidth between the user n and the visible satellite m can be calculated as:
Wherein the method comprises the steps of Representing the number of users associated with the mth satellite; w m is the total bandwidth that the satellite can provide.
The switching delay is greatly affected because different access satellites can cause corresponding changes in the data transmission path. Therefore, to guarantee QoS requirements of users, the delay overhead is a constraint condition for selecting candidate access satellites, expressed as the sum of average latency, propagation delay and processing delay:
Dm,n(t)＝dwait+dprop+dproc
the packet loss rate is calculated as the ratio between the amount of data lost per unit time transmitted and the total amount of data transmitted:
Considering that different service flows have different QoS metrics for star-to-ground links with the same attribute, the QoS calculation of users of different types of service flows is as follows:
Wherein eta 1＞η2 measures the preference degree of different service flows to corresponding network performance indexes.
(4) The source RRC forwards the handover request to the RRC of the target satellite;
(5) The target satellite node RRC provides access permission and allocates resources for the UE to be switched;
(6) After receiving the switching request, the target RRC sends switching request confirmation to the source RRC;
(7) The source RRC further acknowledges the handover to the user node;
(8) After the confirmation is finished, the target satellite reserves channel resources for the switching user, generates a switching command containing information such as a random access channel and switching time, and forwards the switching command to the user node through the current service satellite;
(9) After receiving the resource allocation information of the target satellite, the user calculates the data stream which can be sent within the duration of the allocation link according to the residual visible time and the channel bandwidth of the satellite. The specific calculation mode relies on DDPG-based reinforcement learning intelligent agent, and satellite-ground link attribute of M visible satellites is used as reinforcement learning state space { Ρ 1(t),ρ2(t),...,ρM (t) }, where ρ m(t)＝{Tm,n(t),Pm,n(t),lm (t) } is allocated as the motion space with actual satellite selection and traffic on the corresponding path{ Rou t,scht }, user QoS: Θ (T) is a reward function, by continuously training the satellite-to-ground switching decision capability of an intelligent agent, in a time slot to be switched, according to the residual visible time T m,n (T) and the channel bandwidth B m,n (T) of the satellite, the data stream which can be sent in the link duration is calculated in advance, and the selection of the next satellite can be evaluated before the current satellite moves out of the visible range;
(10) Extracting the identifier of the target node and the random access channel information, and stopping the uplink and downlink data transmission with the current satellite;
(11) According to the random access information and the synchronous signaling of the target node, randomly accessing the target base station to complete the synchronous process;
(12) Releasing the resources of the current satellite by the user node and disconnecting the connection;
(13) The new satellite RRC node distributes a service channel for the current user, updates the user position and the identification information, generates a switching completion signaling and completes satellite-to-ground switching.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (5)
1. A semantic-differentiated star-ground fusion network scheduling method is characterized by comprising the following steps of: the method specifically comprises the following steps:
S1: sensing satellite-ground link attribute;
S2: evaluating service flow and user QoS;
s3: satellite-ground access and switching decision;
s4: traffic distribution based on DDPG algorithm.
2. The semantic distinguished star-to-ground fusion network scheduling method according to claim 1, wherein the method comprises the following steps: the S1 specifically comprises the following steps:
S11: firstly, determining the respective accurate positions of a ground node and a satellite node based on a global positioning system GPS, calculating the elevation angle of the ground node, and calculating the residual visible time T m,n (T) between the ground node n and a visible satellite m by combining the satellite height and the satellite operation period;
S12: considering free space loss and multipath effect of satellite-to-ground link long-distance transmission, the channel gain between the ground node n and the visible satellite m is expressed as h m,n (t), and the signal-to-interference-and-noise ratio (SINR) P m,n (t) of the user n for selecting to access or switch to the satellite m at the moment t is calculated;
S13: the user equipment UE acquires load information according to the periodical broadcast of the satellite, and l m (t) is set as the free channel number of the LEO satellite m at the time t, and the idle channel number of the satellite is set as Where 0.ltoreq.l m(t)≤Cmax,Cmax is the maximum number of free channels owned by the satellite.
3. The semantic distinguished star-to-ground fusion network scheduling method according to claim 2, wherein the method comprises the following steps: the step S2 specifically comprises the following steps:
S21: the ground node perceives the semantic features of the service to be transmitted and classifies different service flows, including: session class services, streaming media class services, interaction class/control class services, transmission class services and message class/acquisition class services;
S22: the method comprises the steps of evaluating the demands of specific types of service flows on different degrees of network performance indexes, and determining specific grades of the service flows, wherein the specific grades are divided into four grades of no-demand, low, higher and high; the transmission rate of the bandwidth between the user n and the visible satellite m is calculated as follows according to shannon's theorem:
Wherein the method comprises the steps of Representing the number of users associated with the mth satellite; w m is the total bandwidth that the satellite can provide;
To guarantee QoS requirements for users, the delay overhead is a constraint condition for selecting candidate access satellites, expressed as the sum of average latency, propagation latency, and processing latency:
Dm,n(t)＝dwait+dprop+dproc
the packet loss rate is calculated as the ratio between the amount of data lost per unit time transmitted and the total amount of data transmitted:
4. A semantic distinguished star-to-ground fusion network scheduling method according to claim 3, characterized in that: the step S3 specifically comprises the following steps:
S31: the ground user node continuously monitors satellite-ground link wireless signals, generates a measurement report, and periodically feeds back measurement information to a Radio Resource Control (RRC) node of the current satellite;
S32: after receiving the switching request, the source RRC makes a switching decision according to the measurement report of the terminal and other system information; the QoS measurement obtained by different service flows for the satellite-ground links with the same attribute is considered to be different, and the user QoS of the service flows with different types is calculated as follows:
Wherein eta 1＞η2 measures the preference degree of different service flows to corresponding network performance indexes.
5. The semantic distinguished star-to-ground fusion network scheduling method according to claim 4, wherein the method comprises the following steps: the step S4 specifically comprises the following steps:
S41: after receiving the switching request, the target RRC sends switching request confirmation to the source RRC; after the confirmation is finished, the target satellite reserves channel resources for the switching user, generates a switching command containing the random access channel and switching time information, and forwards the switching command to the user node through the current service satellite;
s42: satellite-ground link attribute of M visible satellites is used as reinforcement learning state space Wherein ρ m(t)＝{Tm,n(t),Pm,n(t),lm (t) } is the action space with the actual satellite selection and the traffic allocation on the corresponding pathThe QoS of a user is a reward function, an agent is trained based on DDPG algorithm, and in the time slot to be switched, according to the residual visible time T m,n (T) and the channel bandwidth B m,n (T) of the satellite, the data stream which can be sent in the duration of the link is calculated in advance, and the selection of the next satellite is evaluated before the current satellite moves out of the visible range;
s43: and stopping uplink and downlink data transmission of the current satellite by the ground node, randomly accessing the target base station according to the random access information and the synchronous signaling of the target node, releasing the resources of the current satellite, disconnecting the resources and completing the switching.
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