A method for transmitting Internet of Things services in a low-orbit satellite mobile communication system

Abstract

The present invention discloses a method for transmitting Internet of Things services in a low-orbit satellite mobile communication system, and relates to the technical field of Internet of Things. The method comprises: a satellite base station starts and divides resources, performs initial resource configuration and terminal broadcast messages; the Internet of Things terminal receives the broadcast message and performs initial connection with the satellite base station, and sends a handshake packet to the satellite base station for intention recognition and service parameter configuration; according to the prediction result, a spectrum allocation strategy is dynamically adjusted to generate an optimized spectrum allocation scheme and resource scheduling instructions; based on the optimized spectrum allocation scheme and resource scheduling instructions, relevant state information is switched; after a data center receives the business data uploaded by the terminal, it judges whether a confirmation signal needs to be sent to the Internet of Things terminal in combination with the switched state information; the present invention establishes a direct communication link through an inter-satellite link, and ensures data continuity and low latency characteristics during the switching process.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a method for transmitting Internet of Things services in a low-orbit satellite mobile communication system. Background Art

[0002] Low-orbit satellite mobile communication systems have developed rapidly in recent years, especially in the field of Internet of Things (IoT) business transmission. With the growing global demand for low-latency, high-bandwidth and wide-coverage communications, low-orbit satellite networks are favored because they can provide a wider service area and better signal penetration. In existing technologies, ground base stations work together with satellite base stations to support the connection of IoT devices, but these systems usually rely on fixed spectrum allocation strategies and lack the ability to dynamically adjust according to real-time traffic changes. In addition, traditional switching mechanisms perform poorly when facing fast-moving IoT terminals, which can easily lead to service interruptions or data loss. These problems limit the efficiency and service quality of low-orbit satellite communication systems.

[0003] In view of the above shortcomings, the present invention pays special attention to the effective use of spectrum resources and service continuity. Most of the existing spectrum allocation methods are based on static configuration and cannot flexibly respond to sudden growth or decrease in data traffic, which not only wastes precious spectrum resources but also reduces the overall performance of the system. At the same time, the seamless switching technology in a multi-base station environment is not yet mature, especially in predicting that the IoT terminal is about to leave the current coverage area and selecting the best replacement base station in advance. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for transmitting Internet of Things services in a low-orbit satellite mobile communication system to solve the problems of dynamic allocation of spectrum resources and seamless switching of Internet of Things terminals in a low-orbit satellite mobile communication system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for transmitting Internet of Things services in a low-orbit satellite mobile communication system, which includes starting a satellite base station and dividing resources, performing initial resource configuration and terminal broadcasting messages;

[0008] The IoT terminal receives the broadcast message and establishes an initial connection with the satellite base station, and sends a handshake packet to the satellite base station for intent recognition and service parameter configuration;

[0009] Based on the results of intent recognition and service parameter configuration, the current spectrum occupancy is continuously monitored and data traffic statistics of different IoT terminals are collected to predict the changes in spectrum demand in the future and form prediction results. At the same time, status information is regularly exchanged between satellite base stations.

[0010] According to the prediction results, the spectrum allocation strategy is dynamically adjusted to generate optimized spectrum allocation plans and resource scheduling instructions;

[0011] Based on the optimized spectrum allocation scheme and resource scheduling instructions, relevant status information is switched;

[0012] After receiving the business data uploaded by the IoT terminal, the data center determines whether it needs to send a confirmation signal to the IoT terminal based on the status information after the switch.

[0013] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, wherein: the satellite base station starts and divides resources, performs initial resource configuration and terminal broadcast messages, including the following steps:

[0014] Start the satellite base station, automatically join the nearest constellation network, and register its geographical location and service range;

[0015] Dividing the wireless resources according to a predetermined rule to form a division result, wherein the division result includes Internet of Things resources and mobile communication resources;

[0016] Based on the division results, the frequencies and time slots of IoT broadcast channels, random access channels and access permission channels are preliminarily allocated;

[0017] The configuration information after preliminary allocation is updated to the information broadcast and sent to all registered IoT terminals through the IoT broadcast channel.

[0018] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, wherein: the Internet of Things terminal receives the broadcast message and connects to the satellite base station for the first time, and sends a handshake packet to the satellite base station for intention recognition and service parameter configuration, including the following steps:

[0019] Start the IoT terminal, monitor the IoT broadcast channel, and receive the broadcast message sent by the satellite base station;

[0020] The IoT terminal parses the configuration information in the broadcast message and extracts the first configuration information of the random access frequency and time slot;

[0021] According to the parsed first configuration information, the IoT terminal constructs a special handshake packet including its own identifier and service request type;

[0022] In the specified random access time slot, the IoT terminal sends a handshake packet to the satellite base station through the random access channel;

[0023] After receiving the handshake packet, the satellite base station uses the deep reinforcement learning intent recognizer to predict the probability distribution of the service intent, which is expressed as:

[0024] ;

[0025] in, represents the predicted service intention probability distribution vector, express function, represents the weight of the second fully connected layer, represents the hyperbolic tangent activation function, represents the weight matrix of the first fully connected layer, represents the feature vector in the handshake packet, represents the behavioral pattern features extracted from historical interactions, represents the bias vector of the first fully connected layer, Represents the bias vector of the second fully connected layer;

[0026] Dynamically adjust physical layer parameter settings based on the identified service intent probability distribution.

[0027] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, wherein: based on the results of intent recognition and service parameter configuration, continuously monitoring the current spectrum occupancy and collecting data traffic statistics of different Internet of Things terminals, predicting the spectrum demand changes in the future period of time includes the following steps:

[0028] Based on the results of intent recognition and service parameter configuration, the satellite base station starts the spectrum monitoring system to monitor the current usage of each channel in real time, and monitor the traffic of the connected IoT terminals, recording the uplink data volume, downlink data volume and transmission rate of each IoT terminal in a specific time period;

[0029] Extract the average daily active times of each IoT terminal, the average data transmission volume in each time period, the location distribution of IoT terminals and their mobility patterns, and the traffic characteristics under specific service intent from historical traffic data;

[0030] Based on the extracted average daily active times of each IoT terminal, the average data transmission volume in each time period, the location distribution of IoT terminals and their mobility patterns, and the traffic characteristics under specific service intentions, a spectrum demand prediction model is constructed to predict the changes in spectrum demand in the future. The expression is:

[0031] ;

[0032] in, Indicates at time The spectrum demand forecast value is Indicates the current time point. represents a time offset into the future, Indicates the index of the IoT terminal. Indicates the number of IoT terminals, Indicates The weight coefficient of the average daily activity times of IoT terminals, Indicates The weight coefficient of the average data transmission volume of IoT terminals is Indicates IoT terminals at a time The average number of daily active times, Indicates time The average data transfer volume, represents the adjustment factor that controls the degree of nonlinear transformation, represents the slope parameter that affects the speed of nonlinear transformation, Indicates time The service intent feature vector, Indicates time The service intention probability distribution vector, The weight coefficient representing the influence of the location distribution of IoT terminals, represents the scaling factor that adjusts the importance of the location distribution feature, Indicates time The location distribution of IoT terminals and their mobility pattern feature vectors.

[0033] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, the periodic exchange of status information between the satellite base stations includes the following steps:

[0034] Based on the prediction results, identify the peak traffic periods that may occur in the future and the corresponding tasks involved;

[0035] By analyzing historical traffic data, the spectrum demand threshold is determined according to the distribution of spectrum demand under normal circumstances. When it is predicted that the spectrum demand in any time period exceeds the spectrum demand threshold, the bandwidth allocation ratio of that time period is automatically increased;

[0036] Each satellite base station regularly summarizes its own geographical location, load conditions, and available resource bandwidth allocation ratio to form a comprehensive status report;

[0037] Each satellite base station exchanges comprehensive status reports with other satellite base stations via inter-satellite links to form a global view.

[0038] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, wherein: dynamically adjusting the spectrum allocation strategy according to the prediction results, generating the optimized spectrum allocation plan and resource scheduling instructions includes the following steps:

[0039] According to the spectrum demand prediction results, bandwidth is allocated to the frequency band. The expression is:

[0040] ;

[0041] in, Indicates frequency band in time The allocated bandwidth, Represents the index used to identify a specific frequency band. Represents the index variable for traversing all available frequency bands, Indicates the total number of available frequency bands, Indicates frequency band in time The spectrum demand forecast value is Indicates The total bandwidth of the frequency band;

[0042] Continuously monitor the bit error rate of each channel, enable error correction capabilities based on the allocated bandwidth of each frequency band, and select the corresponding error correction coding scheme to adjust the transmit power;

[0043] Based on the adjusted transmission power, the qualified small data is transparently transmitted to the data center through the public channel, and the shortest path is selected for transparent transmission according to the current spectrum occupancy and the location of the IoT terminal;

[0044] For big data, enable temporary dedicated channels, and clearly specify the frequency band, time slot and power settings of the temporary dedicated channels to generate optimized spectrum allocation plans and resource scheduling instructions.

[0045] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, wherein: based on the optimized spectrum allocation scheme and resource scheduling instructions, switching related state information includes the following steps:

[0046] Based on the optimized spectrum allocation scheme and resource scheduling instructions, the location distribution characteristics of each IoT terminal are continuously monitored to predict the time when it is about to leave the current coverage area, and the next best base station is pre-selected and the IoT terminal is notified to prepare for switching;

[0047] Activate the intersatellite link, establish a direct communication link between the current base station and the pre-selected best base station, and generate a handover instruction;

[0048] After receiving the switching instruction, the IoT terminal establishes a connection with the new base station and disconnects from the current base station;

[0049] After the switch is completed, the new base station takes over the communication service of the IoT terminal and updates the relevant status information;

[0050] The master control station integrates the status information of all satellite base stations, updates the global view, and completes the switching of relevant status information.

[0051] As a preferred solution of the low-orbit satellite mobile communication system Internet of Things service transmission method of the present invention, wherein: after the data center receives the service data uploaded by the terminal, combined with the state information after the switch, judging whether it is necessary to send a confirmation signal to the Internet of Things terminal includes the following steps:

[0052] The data center receives the service data uploaded by the IoT terminal, performs integrity and correctness checks, and combines the status information after the switch to evaluate whether there are any abnormal conditions that affect data transmission during the switch process;

[0053] According to the preset configuration strategy, decide whether to send a confirmation signal to the IoT terminal;

[0054] When confirmation is required, a data confirmation response message is generated. The satellite base station is responsible for converting the data confirmation response message into a message suitable for wireless transmission format and sending it to the corresponding IoT terminal through the access permission channel;

[0055] After receiving the data confirmation response message, the IoT terminal checks whether the content has been received correctly, and closes the session after confirming that it has been received correctly.

[0056] In a second aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the method for transmitting Internet of Things services in a low-orbit satellite mobile communication system as described in the first aspect of the present invention.

[0057] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the method for transmitting Internet of Things services in a low-orbit satellite mobile communication system as described in the first aspect of the present invention.

[0058] The beneficial effects of the present invention are as follows: by introducing a deep reinforcement learning intention identifier and a spectrum demand prediction model, an accurate understanding of the service intention of the IoT terminal and an accurate prediction of the changes in spectrum demand in the future are achieved; the satellite base station can dynamically adjust the spectrum allocation strategy according to actual needs, maximizing spectrum utilization while ensuring service quality; a direct communication link is established through an inter-satellite link, ensuring data continuity and low latency during the switching process; the data center performs an integrity check on the received business data and analyzes it in combination with the status information after the switch, further improving the reliability and security of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0060] Figure 1 This is a flow chart of the Internet of Things service transmission method of the low-orbit satellite mobile communication system in Example 1.

[0061] Figure 2 This is a flow chart of periodically exchanging status information between satellite base stations in Example 1. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0063] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0064] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0065] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a method for transmitting Internet of Things services in a low-orbit satellite mobile communication system, comprising the following steps:

[0066] S1. The satellite base station starts and allocates resources, performs initial resource configuration and terminal broadcast messages.

[0067] S1.1. Start the satellite base station, automatically join the nearest constellation network, and register its geographical location and service range.

[0068] Specifically, joining the constellation network means that the satellite base station sends its own GPS coordinates and service coverage range to the master control station through the inter-satellite link, which is managed and scheduled by the master control station.

[0069] S1.2. Divide the wireless resources into Internet of Things resources and mobile communication resources according to predetermined rules.

[0070] Specifically, IoT resources are public channel resources, which are mainly used for broadcast, random access, access permission, etc. Mobile communication resources are used to support conventional voice and data services.

[0071] S1.3. Based on the division results, the frequencies and time slots of the IoT broadcast channel, random access channel and access permission channel are preliminarily allocated; the configuration information after the preliminary allocation is updated to the information broadcast and sent to all registered IoT terminals through the IoT broadcast channel.

[0072] Furthermore, the predetermined rule refers to a set of fixed ratios or dynamic adjustment strategies that are pre-set to allocate spectrum resources according to the overall design objectives and requirements, for example:

[0073] Fixed ratio allocation: Allocate bandwidth to different types of channels according to a fixed percentage, such as:

[0074] The IoT broadcast channel accounts for 20% of the total bandwidth and is used to broadcast configuration information to terminals.

[0075] The random access channel occupies 15% of the total bandwidth and is used when the terminal initiates a connection request.

[0076] The access permission channel occupies 10% of the total bandwidth and is used to send service permissions and control instructions.

[0077] The remaining bandwidth (55%) is used as a data transmission channel and is dynamically allocated to terminals that need to upload or download.

[0078] Dynamic adjustment strategy: Dynamically adjust the bandwidth proportion of each channel according to the real-time monitored network load. For example, when a surge in the number of random access requests in a certain area is detected, the bandwidth of the random access channel can be temporarily increased and the proportion of other channels can be reduced to ensure service quality.

[0079] S2. The IoT terminal receives the broadcast message and establishes an initial connection with the satellite base station, and sends a handshake packet to the satellite base station for intent recognition and service parameter configuration.

[0080] S2.1. Start the IoT terminal, listen to the IoT broadcast channel, and receive the configuration information sent by the satellite base station; the IoT terminal parses the configuration information in the broadcast message and extracts the first configuration information of the random access frequency and time slot; based on the parsed first configuration information, the IoT terminal constructs a special handshake packet containing its own identifier and service request type, the identifier is used to uniquely identify the IoT terminal, and the service request type describes the operation that the IoT terminal wants to perform (such as uploading a small amount of data or downloading a large number of files); within the specified random access time slot, the IoT terminal sends a handshake packet to the satellite base station through the random access channel; after receiving the handshake packet, the satellite base station uses the deep reinforcement learning intention recognizer to predict the probability distribution of the service intention, which is expressed as:

[0081] ;

[0082] in, represents the predicted service intent probability distribution vector, each element of which represents the probability that the IoT terminal belongs to a specific service intent. For example, if there are three possible service intents (upload a small amount of data, download a large amount of files, and real-time monitoring), then will be a vector of length 3, with each element corresponding to the probability of an intent. express function, represents the weight matrix of the second fully connected layer, which is responsible for mapping the hidden layer output to the final service intent probability distribution. represents the hyperbolic tangent activation function, Represents the weight matrix of the first fully connected layer, which is responsible for mapping the concatenated features to the hidden layer. Represents the feature vector in the handshake packet, which contains information such as the IoT terminal identifier and service request type. These features are used to describe the basic properties and communication requirements of the current IoT terminal. It represents the behavior pattern features extracted from historical interactions, capturing the behavior patterns of IoT terminals in the past period of time, such as access frequency, common time periods, etc., which helps to more accurately predict their current intentions. represents the bias vector of the first fully connected layer, Represents the bias vector of the second fully connected layer.

[0083] S2.2. Dynamically adjust the physical layer parameter settings based on the identified service intent probability distribution. For example, for IoT terminals that need to upload a small amount of data, reduce the transmission power to save energy; for IoT terminals that need to download a large amount of files, increase the bandwidth allocation to ensure transmission efficiency.

[0084] Furthermore, if the IoT terminal is connecting for the first time, the satellite base station will trigger an additional identity verification process. This step is to prevent unauthorized devices from accessing the system and ensure communication security.

[0085] Authentication method: Use authentication technology based on the Elliptic Curve Digital Signature Algorithm (ECDSA). The specific steps are as follows:

[0086] Generate a key pair: The IoT terminal pre-generates a pair of public and private keys, where the private key is saved locally and the public key is uploaded to the authentication server.

[0087] Signature generation: The IoT terminal uses the private key to sign the handshake package and generate a digital signature.

[0088] Send signature: Send the handshake packet together with the digital signature to the satellite base station.

[0089] Verify the signature: After receiving the signature, the satellite base station uses the public key of the IoT terminal to verify the validity of the signature.

[0090] Establish a secure connection: If the signature verification passes, the satellite base station confirms the legitimacy of the IoT terminal, establishes a secure connection, and records the relevant information of the IoT terminal.

[0091] S3. Based on the results of intent recognition and service parameter configuration, continuously monitor the current spectrum occupancy and collect data traffic statistics of different IoT terminals to predict changes in spectrum demand in the future.

[0092] S3.1. Based on the intention identification and service parameter configuration results, the satellite base station starts the spectrum monitoring system to monitor the current usage of each channel in real time, and monitors the traffic of the connected IoT terminals, recording the uplink data volume, downlink data volume and transmission rate of each IoT terminal in a specific time period; extracts the average daily active times of each IoT terminal, the average data transmission volume in each time period, the location distribution of IoT terminals and their mobility patterns, and the traffic characteristics under specific service intentions from the historical traffic data; based on the extracted average daily active times of each IoT terminal, the average data transmission volume in each time period, the location distribution of IoT terminals and their mobility patterns, and the traffic characteristics under specific service intentions, a spectrum demand prediction model is constructed to predict the changes in spectrum demand in the future, and the expression is:

[0093] ;

[0094] in, Indicates at time The spectrum demand forecast value is Indicates the current time point. represents a time offset into the future, Indicates the index of the IoT terminal. Indicates the number of IoT terminals, Indicates The weight coefficient of the average daily activity times of IoT terminals, Indicates The weight coefficient of the average data transmission volume of IoT terminals is Indicates IoT terminals at a time The average number of daily active times, Indicates time The average data transfer volume, represents the adjustment factor that controls the degree of nonlinear transformation, represents the slope parameter that affects the speed of nonlinear transformation, Indicates time The service intent feature vector, Indicates time The service intention probability distribution vector, The weight coefficient representing the influence of the location distribution of IoT terminals, represents the scaling factor that adjusts the importance of the location distribution feature, Indicates time The location distribution of IoT terminals and their mobility pattern feature vectors.

[0095] S3.2. Satellite base stations regularly exchange status information.

[0096] S3.2.1. Extract the average daily active times of each terminal in the past period (such as the past month), the average data transmission volume in each time period, the terminal location distribution feature vector and the traffic characteristics under specific service intent from the historical database; perform time series analysis on the historical traffic data, calculate the average spectrum demand and standard deviation of each time period, and identify the spectrum demand pattern in different time periods; set the spectrum demand threshold according to the calculated average spectrum demand and standard deviation of each time period; classify the tasks into different types according to the historical traffic data and the traffic characteristics under specific service intent, such as uploading a small amount of data, downloading a large number of files, real-time monitoring, etc.; for each peak traffic period, identify the main task types involved; when it is predicted that the spectrum demand in a certain time period exceeds the spectrum demand threshold, automatically increase the bandwidth allocation ratio of the time period, and the expression for setting the bandwidth reservation ratio is:

[0097] ;

[0098] in, Indicates the final bandwidth reservation ratio. Indicates the adjustment factor that controls the growth rate of reserved bandwidth. represents the spectrum demand threshold;

[0099] Each satellite base station regularly summarizes its own geographical location, load conditions and status information of available resource bandwidth allocation ratio to form a comprehensive status report; each satellite base station exchanges comprehensive status reports with other satellite base stations through inter-satellite links to form a global view.

[0100] S4. According to the prediction results, dynamically adjust the spectrum allocation strategy and generate optimized spectrum allocation plan and resource scheduling instructions.

[0101] S4.1. According to the spectrum demand prediction results, bandwidth is allocated to the frequency band. The expression is:

[0102] ;

[0103] in, Indicates frequency band in time The allocated bandwidth, Indicates the index used to identify a specific frequency band. For example, if there are three available frequency bands, The value can be 1, 2 or 3, corresponding to the first, second and third frequency bands respectively. Represents the index variable for traversing all available frequency bands, Indicates the total number of available frequency bands, Indicates frequency band in time The spectrum demand forecast value is Indicates The total bandwidth of the frequency band;

[0104] Continuously monitor the bit error rate of each channel (an important indicator of the quality of the communication link, reflecting the frequency of errors in the data transmission process), enable the error correction capability in combination with the allocated bandwidth of each frequency band, and select the corresponding error correction coding scheme (a technology used in communication systems to correct errors that may occur during data transmission. In wireless communications, due to factors such as channel noise, interference and fading, errors may occur in the data received by the receiving end. In order to improve the reliability of data transmission, data is usually encoded at the sending end and decoded at the receiving end to detect and correct these errors. Error correction coding can be divided into two categories: forward error correction and automatic retransmission request. In satellite communication environments, forward error correction is usually preferred due to higher latency) , based on the bit error rate and other performance indicators, such as throughput, latency, etc., select the error correction coding scheme that best suits the current situation. For example, if the bit error rate is high, a more powerful but slightly less efficient coding method may be selected; conversely, a more efficient method can be selected to adjust the transmit power; based on the adjusted transmit power, for small data packets that meet the conditions (such as less than 1KB and non-critical tasks), they are transparently transmitted to the data center through public channels, and the shortest path is selected for transparent transmission based on the current spectrum occupancy and the location of the IoT terminal; for large data streams (such as critical tasks greater than 1MB), temporary dedicated channels are enabled, and the frequency bands, time slots and power settings of the temporary dedicated channels are clearly specified to generate optimized spectrum allocation plans and resource scheduling instructions.

[0105] Specifically, the transmit power adjustment is performed by setting a bit error rate threshold. When the bit error rate of a channel exceeds the bit error rate threshold, the transmit power adjustment control mechanism is triggered. The expression is:

[0106] ;

[0107] in, Indicates time The transmission power, Indicates time The transmission power, Indicates the power adjustment step size, is a sign function indicating positive and negative directions, Indicates time The bit error rate, Indicates the bit error rate threshold.

[0108] S5. Based on the optimized spectrum allocation scheme and resource scheduling instructions, relevant status information is switched.

[0109] S5.1. Based on the optimized spectrum allocation scheme and resource scheduling instructions, the location distribution characteristics of each IoT terminal are continuously monitored, and a terminal mobility model is established in combination with historical data. For each IoT terminal, a real-time updated location record is maintained, including but not limited to parameters such as longitude, latitude, altitude, and moving speed and direction. The regression analysis method is used to predict when the IoT terminal will leave the coverage of the current satellite base station. Potential target base stations located on the expected path of the IoT terminal are preliminarily screened out based on geographical proximity, and signal strength tests are performed on the potential target base stations. The test can be completed by sending a detection signal to the potential target base stations, and they return received signal strength indication (RSSI), signal-to-noise ratio (SNR) and other indicators to determine their service capabilities for the IoT terminal. The straight-line distance between the IoT terminal and each potential target base station is calculated to ensure that the selected base station is within a reasonable communication range and can provide the best service quality. Signal quality, load conditions, and distance are quantified as scoring criteria, and each potential target base station is scored. The base station is sorted according to the score, and the base station with the highest score is selected as the next best base station. Once the best base station is determined, the current serving base station will send a switching preparation instruction to the IoT terminal to inform it of the upcoming switching operation.

[0110] S5.2. Activate the intersatellite link, establish a direct communication link between the current base station and the pre-selected best base station, and generate a switching instruction.

[0111] Specifically, when it is decided that a switch is needed, the master control station or the gateway responsible for regional coordination will activate the intersatellite link and establish a direct communication link between the current base station and the pre-selected best base station. The necessary switching parameters, including but not limited to the IoT terminal's identity, current service status, required bandwidth and other information, are transmitted through this link. A switching instruction containing the new base station ID, frequency configuration and other necessary information is generated and sent to the IoT terminal.

[0112] It should be noted that the intersatellite link provides a stable and low-latency data transmission path, ensuring the security and integrity of key information during the switching process; the switching instruction contains all the necessary configuration details, allowing the IoT terminal to complete the switching operation quickly and accurately, reducing the switching time.

[0113] S5.3. After receiving the switching command, the IoT terminal establishes a connection with the new base station and disconnects from the current base station. After the switching is completed, the new base station takes over the communication service of the IoT terminal and updates the relevant status information. The master control station integrates the status information of all satellite base stations, updates the global view, and completes the switching of relevant status information.

[0114] It should be noted that the dual connection strategy ensures continuity throughout the switching process and avoids any possible communication interruption. The success reporting mechanism allows the master station to understand the switching status in a timely manner, facilitates subsequent management and troubleshooting, and provides services to IoT terminals quickly and effectively, maintaining communication continuity and service quality.

[0115] S6. After receiving the business data uploaded by the IoT terminal, the data center determines whether it needs to send a confirmation signal to the IoT terminal based on the status information after the switch.

[0116] S6.1. The data center receives the business data uploaded by the IoT terminal, performs integrity and correctness checks, and combines the status information after switching to evaluate whether there are any abnormal conditions that affect data transmission during the switching process.

[0117] Specifically, the integrity check can use CRC or MD5 hash to confirm that the data has not been tampered with or damaged during transmission; the correctness check is to check the sequence number and timestamp in the data packet to ensure that the data packets arrive in the correct order and without obvious delays or duplications.

[0118] The assessment of abnormal situations is to evaluate the impact of the switching process on data transmission, such as whether there is packet loss, increased number of retransmissions, etc., analyze possible network problems such as weakened signal strength, increased interference, etc., and record relevant logs.

[0119] It should be noted that through comprehensive status information evaluation, any potential problems in the switching process can be accurately identified, which helps to take corrective measures in a timely manner.

[0120] S6.2. According to the preset configuration strategy, decide whether to send a confirmation signal to the IoT terminal.

[0121] Specifically, the preset configuration strategy includes service quality requirements and network load conditions. If a problem with data transmission is detected or in order to ensure the needs of specific applications (such as real-time applications), it is decided to send a confirmation signal. For non-critical tasks or low-priority data transmission, you can choose not to send a confirmation signal to save bandwidth resources.

[0122] S6.3. When confirmation is required, a data confirmation response message is generated. The satellite base station is responsible for converting the confirmation response into a message suitable for wireless transmission format and sending it to the corresponding IoT terminal through the access permission channel. After receiving the confirmation message, the IoT terminal checks whether the content has been received correctly and closes the session after correct reception.

[0123] Specifically, when it is determined that a confirmation signal needs to be sent, the data center generates a data confirmation response message including a confirmation code, a sequence number, and other necessary information.

[0124] After receiving the confirmation message, the IoT terminal checks whether the content has been received correctly. If the confirmation is correct, the IoT terminal closes the session and releases related resources. If there is a problem, it takes corresponding measures according to the specific situation, such as requesting to resend the data.

[0125] This embodiment also provides a computer device, which is applicable to the case of the Internet of Things service transmission method of the low-orbit satellite mobile communication system, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the low-orbit satellite mobile communication system Internet of Things service transmission method proposed in the above embodiment.

[0126] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0127] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for transmitting Internet of Things services in a low-orbit satellite mobile communication system is implemented as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a disk or an optical disk.

[0128] In summary, the present invention achieves accurate understanding of the service intentions of IoT terminals and accurate prediction of spectrum demand changes in the future by introducing a deep reinforcement learning intention identifier and a spectrum demand prediction model; enables satellite base stations to dynamically adjust spectrum allocation strategies according to actual needs, maximizing spectrum utilization while ensuring service quality; establishes a direct communication link through an inter-satellite link to ensure data continuity and low latency during the switching process; the data center performs an integrity check on the received business data and analyzes it in combination with the status information after the switch, further improving the reliability and security of data transmission.

[0129] Example 2, referring to Table 1, is the second example of the present invention. To further verify the technical solution of the present invention, experimental simulation data of the Internet of Things service transmission method of the low-orbit satellite mobile communication system is provided.

[0130] The experimental environment includes a simulated low-orbit satellite network consisting of multiple satellite base stations, covering urban and rural areas in different geographical regions. Several test points were set up in two different geographical environments, urban and rural, to examine the changes in spectrum requirements in different environments. Each test point was randomly distributed with 5-10 IoT terminals, which were programmed to regularly upload business data according to preset service request types (such as video surveillance, environmental monitoring, etc.).

[0131] The existing technology adopts a spectrum allocation strategy based on fixed rules, that is, frequency bands are statically allocated according to a pre-set schedule. The present invention adopts an intelligent spectrum monitoring and prediction model, combined with a deep reinforcement learning intention identifier, to achieve an accurate understanding of the service intentions of IoT terminals and dynamically adjust the spectrum allocation strategy according to actual needs.

[0132] The details are shown in Table 1 below:

[0133] Table 1 Experimental data record table

[0134] Test subjects Spectrum utilization (%) Data transmission success rate (%) Average latency (ms) Maximum delay (ms) Energy consumption (mAh / hour) User satisfaction (%) Prior Art_City 78.5 91.2 120 350 125 85 Prior Art_Rural 76.3 90.5 150 400 120 83 The invention_city 92.3 98.5 80 200 110 95 The present invention_rural 90.1 97.8 90 220 105 92 Prior Art_Mixed 77.4 90.8 135 375 123 84 The present invention_mixed 91.2 98.2 85 210 108 94

[0135] Through in-depth analysis of the data in the above table, it can be seen that the present invention is significantly superior to the existing spectrum allocation and IoT service transmission methods in many aspects. First, in terms of spectrum utilization, the present invention has achieved a higher level in both urban and rural environments. For example, in urban environments, the spectrum utilization of the prior art is only 78.5%, while the present invention reaches 92.3%; in rural environments, the gap is even more obvious, with the prior art being 76.3% and the present invention being 90.1%. This shows that the intelligent spectrum monitoring and prediction model of the present invention can manage spectrum resources more efficiently and reduce waste.

[0136] Secondly, the data transmission success rate is one of the important indicators for measuring system stability and reliability. Data shows that the transmission success rate of the present invention in both environments exceeds 97%, which is much higher than the success rate of about 90%-91% of the prior art. This means that the present invention not only improves the quality of data transmission, but also reduces the risk of service interruption due to transmission failure. Especially under high load conditions, such as in urban environments, the data transmission success rate of the present invention is as high as 98.5%, which is a significant improvement over the 91.2% of the prior art.

[0137] Regarding delay performance, the present invention also performs well. In an urban environment, the average delay of the prior art is 120ms, and the maximum delay can reach 350ms, while the average delay of the present invention is reduced to 80ms, and the maximum delay is shortened to 200ms. The same trend also appears in a rural environment. The average delay of the prior art is 150ms, and the maximum delay reaches 400ms, while the average delay of the present invention is 90ms, and the maximum delay is 220ms. Lower latency means faster response time and better user experience, which is especially important for real-time applications.

[0138] Energy consumption is also a key factor in evaluating the performance of IoT devices. The present invention significantly reduces the energy consumption of terminal devices by optimizing spectrum allocation strategies and reducing unnecessary switching operations. For example, in an urban environment, the energy consumption of the prior art is 125mAh / hour, while that of the present invention is only 110mAh / hour; in a rural environment, the energy consumption of the prior art is 120mAh / hour, while that of the present invention is 105mAh / hour. Lower energy consumption not only extends the battery life of the device, but also helps protect the environment.

[0139] Finally, user satisfaction is a comprehensive indicator that reflects the degree of end-user recognition of the entire system. According to the experimental results, the present invention can achieve higher user satisfaction in both urban and rural environments. For example, in urban environments, the user satisfaction of the prior art is 85%, while the present invention reaches 95%; in rural environments, the user satisfaction of the prior art is 83%, while the present invention is 92%. The improvement of user satisfaction not only reflects the technical advantages of the present invention, but also lays a solid foundation for its promotion and application.

[0140] In summary, the present invention solves the problems of spectrum resource waste, poor service continuity, high latency and high energy consumption existing in the prior art by introducing an intelligent spectrum monitoring and prediction model, dynamically adjusting the spectrum allocation strategy, optimizing the terminal initial connection process and improving the status information switching process.

[0141] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for transmitting Internet of Things services in a low-orbit satellite mobile communication system, characterized in that: include, The satellite base station starts and allocates resources, performs initial resource configuration and broadcasts messages to the terminals; The IoT terminal receives the broadcast message and establishes an initial connection with the satellite base station, and sends a handshake packet to the satellite base station for intent recognition and service parameter configuration; Based on the results of intent recognition and service parameter configuration, the current spectrum occupancy is continuously monitored and data traffic statistics of different IoT terminals are collected to predict the changes in spectrum demand in the future and form prediction results. At the same time, status information is regularly exchanged between satellite base stations. According to the prediction results, the spectrum allocation strategy is dynamically adjusted to generate optimized spectrum allocation plans and resource scheduling instructions; Based on the optimized spectrum allocation scheme and resource scheduling instructions, the best base station is determined, and the current serving base station sends a switching preparation instruction to the IoT terminal to switch the status information; After receiving the business data uploaded by the IoT terminal, the data center determines whether it needs to send a confirmation signal to the IoT terminal based on the status information after the switch. If a problem with the data transmission is detected, it decides to send a confirmation signal; The IoT terminal receives the broadcast message and connects to the satellite base station for the first time, and sends a handshake packet to the satellite base station for intent recognition and service parameter configuration, including the following steps: Start the IoT terminal, monitor the IoT broadcast channel, and receive the broadcast message sent by the satellite base station; The IoT terminal parses the configuration information in the broadcast message and extracts the first configuration information of the random access frequency and time slot; According to the parsed first configuration information, the IoT terminal constructs a special handshake packet including its own identifier and service request type; In the specified random access time slot, the IoT terminal sends a handshake packet to the satellite base station through the random access channel; After receiving the handshake packet, the satellite base station uses the deep reinforcement learning intent recognizer to predict the probability distribution of the service intent, which is expressed as: ； in, represents the predicted service intention probability distribution vector, express function, represents the weight of the second fully connected layer, represents the hyperbolic tangent activation function, represents the weight matrix of the first fully connected layer, represents the feature vector in the handshake packet, represents the behavioral pattern features extracted from historical interactions, represents the bias vector of the first fully connected layer, Represents the bias vector of the second fully connected layer; According to the identified service intent probability distribution, the physical layer parameter settings of the IoT terminal are dynamically adjusted.

2. The method for transmitting Internet of Things services in a low-orbit satellite mobile communication system according to claim 1, characterized in that: The satellite base station starts and allocates resources, performs initial resource configuration and broadcasts messages to the terminal, including the following steps: Start the satellite base station, automatically join the nearest constellation network, and register its geographical location and service range; Dividing the wireless resources according to a predetermined rule to form a division result, wherein the division result includes Internet of Things resources and mobile communication resources; Based on the division results, the frequencies and time slots of IoT broadcast channels, random access channels and access permission channels are preliminarily allocated; The configuration information after preliminary allocation is updated to the information broadcast and sent to all registered IoT terminals through the IoT broadcast channel.

3. The method for transmitting Internet of Things services in a low-orbit satellite mobile communication system as claimed in claim 2, characterized in that: Based on the results of intent recognition and service parameter configuration, the current spectrum occupancy is continuously monitored and data traffic statistics of different IoT terminals are collected. The changes in spectrum demand in the future are predicted, including the following steps: Based on the results of intent recognition and service parameter configuration, the satellite base station starts the spectrum monitoring system to monitor the current usage of each channel in real time, and monitor the traffic of the connected IoT terminals, recording the uplink data volume, downlink data volume and transmission rate of each IoT terminal in a specific time period; Extract the average daily active times of each IoT terminal, the average data transmission volume in each time period, the location distribution of IoT terminals and their mobility patterns, and the traffic characteristics under specific service intent from historical traffic data; Based on the extracted average daily active times of each IoT terminal, the average data transmission volume in each time period, the location distribution of IoT terminals and their mobility patterns, and the traffic characteristics under specific service intentions, a spectrum demand prediction model is constructed to predict the changes in spectrum demand in the future. The expression is: ； in, Indicates at time The spectrum demand forecast value is Indicates the current time point. represents a time offset into the future, Indicates the index of the IoT terminal. Indicates the number of IoT terminals, Indicates The weight coefficient of the average daily activity times of IoT terminals, Indicates The weight coefficient of the average data transmission volume of IoT terminals is Indicates IoT terminals at a time The average number of daily active times, Indicates time The average data transfer volume, represents the adjustment factor that controls the degree of nonlinear transformation, represents the slope parameter that affects the speed of nonlinear transformation, Indicates time The service intent feature vector, Indicates time The service intention probability distribution vector, The weight coefficient representing the influence of the location distribution of IoT terminals, represents the scaling factor that adjusts the importance of the location distribution feature, Indicates time The location distribution of IoT terminals and their mobility pattern feature vectors.

4. The method for transmitting Internet of Things services in a low-orbit satellite mobile communication system according to claim 1, wherein: The periodic exchange of status information between the satellite base stations comprises the following steps: Based on the prediction results, identify the peak traffic periods that may occur in the future and the corresponding tasks involved; By analyzing historical traffic data, the spectrum demand threshold is determined according to the distribution of spectrum demand under normal circumstances. When it is predicted that the spectrum demand in any time period exceeds the spectrum demand threshold, the bandwidth allocation ratio of that time period is automatically increased; Each satellite base station regularly summarizes its own geographical location, load conditions, and available resource bandwidth allocation ratio to form a comprehensive status report; Each satellite base station exchanges comprehensive status reports with other satellite base stations via inter-satellite links to form a global view.

5. The method for transmitting Internet of Things services in a low-orbit satellite mobile communication system as claimed in claim 4, characterized in that: According to the prediction results, the spectrum allocation strategy is dynamically adjusted to generate an optimized spectrum allocation plan and resource scheduling instructions, including the following steps: According to the spectrum demand prediction results, bandwidth is allocated to the frequency band. The expression is: ； in, Indicates frequency band in time The allocated bandwidth, Represents the index used to identify a specific frequency band. Represents the index variable for traversing all available frequency bands, Indicates the total number of available frequency bands, Indicates frequency band in time The spectrum demand forecast value is Indicates The total bandwidth of the frequency band; Continuously monitor the bit error rate of each channel, enable error correction capabilities based on the allocated bandwidth of each frequency band, and select the corresponding error correction coding scheme to adjust the transmit power; Based on the adjusted transmission power, the qualified small data is transparently transmitted to the data center through the public channel, and the shortest path is selected for transparent transmission according to the current spectrum occupancy and the location of the IoT terminal; For big data, enable temporary dedicated channels, and clearly specify the frequency band, time slot and power settings of the temporary dedicated channels to generate optimized spectrum allocation plans and resource scheduling instructions.

6. The method for transmitting Internet of Things services in a low-orbit satellite mobile communication system as claimed in claim 5, characterized in that: Based on the optimized spectrum allocation scheme and resource scheduling instructions, the best base station is determined, and the current serving base station sends a switching preparation instruction to the IoT terminal. The state information switching includes the following steps: Based on the optimized spectrum allocation scheme and resource scheduling instructions, the location distribution characteristics of each IoT terminal are continuously monitored to predict the time when it is about to leave the current coverage area, and the next best base station is pre-selected and the IoT terminal is notified to prepare for switching; Activate the intersatellite link, establish a direct communication link between the current base station and the pre-selected best base station, and generate a handover instruction; After receiving the switching instruction, the IoT terminal establishes a connection with the new base station and disconnects from the current base station; After the switch is completed, the new base station takes over the communication service of the IoT terminal and updates the status information; The master control station integrates the status information of all satellite base stations, updates the global view, and completes the switching of status information.

7. The method for transmitting Internet of Things services in a low-orbit satellite mobile communication system as claimed in claim 6, characterized in that: After receiving the service data uploaded by the IoT terminal, the data center determines whether it needs to send a confirmation signal to the IoT terminal in combination with the status information after the switch, including the following steps: The data center receives the business data uploaded by the IoT terminal and performs integrity and correctness checks. Combined with the status information after the switch, it evaluates whether there are any abnormal conditions that affect data transmission during the switch process; According to the preset configuration strategy, decide whether to send a confirmation signal to the IoT terminal; When confirmation is required, a data confirmation response message is generated. The satellite base station is responsible for converting the data confirmation response message into a message suitable for wireless transmission format and sending it to the corresponding IoT terminal through the access permission channel; After receiving the data confirmation response message, the IoT terminal checks whether the content has been received correctly, and closes the session after confirming that it has been received correctly.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the low-orbit satellite mobile communication system Internet of Things service transmission method described in any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the low-orbit satellite mobile communication system Internet of Things service transmission method described in any one of claims 1 to 7 are implemented.

Images