Beidou satellite short message communication data unpacking transmission method

Abstract

The application relates to the technical field of satellite communication data transmission, and discloses a Beidou satellite short message communication data unpacking transmission method. The method comprises the following steps: a dynamic adaptive transmission framework is established, and a virtual container is generated for pre-configuration of the split data packet. Firstly, a real-time quality spectrum reflecting the time-frequency availability distribution of a channel is acquired, and the data packet is matched with the quality spectrum point by point to generate a preliminary transmission plan. Then, the plan is deduced in a future period, the stability indexes of multiple potential paths are calculated, and a transmission path selection tree is constructed according to the indexes to select a final transmission path and encode information into a packet header. Finally, the sending queue is time-sequenced fine-tuned and power ratioed according to the path attributes. The method realizes accurate planning and forward-looking decision of transmission resources in a two-dimensional space of time and frequency, and improves the reliability and spectrum utilization efficiency of data transmission in a complex time-varying channel.

Description

Technical Field

[0001] This invention relates to the field of satellite communication data transmission technology, specifically a method for disassembling and transmitting short message communication data from the BeiDou satellite system. Background Technology

[0002] BeiDou satellite short message communication plays an irreplaceable role in emergency response, maritime, and remote area communications. However, its channel environment exhibits significant time-varying and frequency-selective fading characteristics. Traditional packet fragmentation transmission methods typically employ fixed-rule fragmentation or adaptive modulation and coding techniques based on simple channel state information. These methods treat data packets as passive transmission entities, adjusting only at the moment of transmission according to broad channel conditions, lacking refined perception and utilization of future trends in time and frequency resources.

[0003] Existing solutions have shortcomings. Traditional methods provide a coarse-grained and delayed understanding of the channel, failing to identify and avoid deep fading points or interference in advance across both the time and frequency domains. This can lead to data packets being assigned to resource blocks that are about to deteriorate, resulting in high retransmission rates and low spectral efficiency. Furthermore, the selection of transmission paths or strategies is often based on instantaneous or historical states, with simple decision models that lack a systematic assessment and comparison of the stability of multiple potential paths over a future period. This makes it difficult to guarantee the robustness and continuity of end-to-end transmission in complex and dynamic channels. A transmission method is needed that can proactively match subtle channel characteristics and make intelligent decisions based on multi-path extrapolation to improve the reliable transmission efficiency of short messages in adverse channel conditions. Summary of the Invention

[0004] The purpose of this invention is to provide a method for disassembling and transmitting short message communication data from BeiDou satellites, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for disassembling and transmitting short message communication data from the BeiDou satellite system, the method comprising:

[0006] Establish a dynamic adaptive transmission framework for short message data packets;

[0007] Under the aforementioned dynamic adaptive transmission framework, an independent virtual transmission container is generated for each split data packet;

[0008] In the virtual transmission container, based on preset channel environment parameters and data packet characteristic parameters, the data packets are pre-configured and adaptively trained before transmission.

[0009] Obtain the real-time channel quality spectrum within the dynamic adaptive transmission framework, the real-time channel quality spectrum reflecting the channel availability distribution at different times and frequencies;

[0010] The data packets that have completed pre-configuration and adaptive training in the virtual transmission container are matched and coupled point by point with the real-time channel quality spectrum to generate a preliminary transmission plan.

[0011] The transmission process of the preliminary transmission plan is simulated within a preset future time period, and the stability evaluation index of multiple potential transmission paths is calculated based on the simulation results.

[0012] Based on the stability evaluation index, a transmission path selection tree for decision-making is constructed;

[0013] Based on the transmission path selection tree, a final transmission path is selected for each data packet, and the path selection information is encoded into the data packet header;

[0014] The encoded data packets are placed into the entity sending queue in sequence, and the sending timing and power ratio of the data packets in the entity sending queue are fine-tuned according to the attributes of the selected final transmission path. The sending timing and power of subsequent data packets are dynamically adjusted.

[0015] Preferably, generating an independent virtual transport container for each split data packet includes:

[0016] Extract the metadata of the data packet, which includes at least the data packet length, the logical position of the data packet in the original data stream, and the identifiers of the preceding and following dependent packets of the data packet;

[0017] Based on the aforementioned metadata, a virtual structure containing a state simulation unit and a parameter register unit is constructed, and the virtual structure is a virtual transmission container.

[0018] In the parameter register unit of the virtual transmission container, basic transmission requirement parameters of the data packet are written, including the expected maximum latency, the acceptable bit error rate threshold, and the priority label.

[0019] Preferably, the pre-configuration and adaptive training of the data packets before transmission includes:

[0020] Load successful transmission samples of past data packets with similar characteristic parameters to the current data packet from the historical transmission records;

[0021] In the state simulation unit of the virtual transmission container, the successful transmission samples of past data packets are used as a training set to simulate the behavior response of data packets under different channel disturbance modes.

[0022] Based on the simulation results, a set of adaptive parameters inside the virtual transport container are adjusted and solidified.

[0023] Preferably, the step of performing point-by-point matching and coupling of the pre-configured and adaptively trained data packets in the virtual transmission container with the real-time channel quality spectrum includes:

[0024] The real-time channel quality spectrum is discretized into multiple time-frequency resource units;

[0025] Calculate the coupling degree between the channel quality score of each time-frequency resource unit and the adaptability parameters of the data packets in the virtual transport container;

[0026] For each data packet, time-frequency resource units with a coupling degree exceeding a set threshold are selected as candidate transmission resources for the data packet.

[0027] Preferably, the generation of the preliminary transmission plan includes:

[0028] Each data packet is associated with its corresponding alternative transmission resource to form a preliminary resource mapping table;

[0029] Based on the resource mapping table, the start and end points of all data packets are arranged in the time dimension to generate an initial transmission timeline.

[0030] Check whether there is a resource mapping conflict in the initialized transmission timeline. The resource mapping conflict is defined as different data packets scheduled to be transmitted on the same time-frequency resource unit.

[0031] If a resource mapping conflict exists, the alternative transmission resources for the conflicting data packets are reselected and replaced based on the priority label of the data packets and the degree of coupling, until the conflict is eliminated and a conflict-free preliminary transmission plan is generated.

[0032] Preferably, the step of performing a transmission process simulation of the preliminary transmission plan within a preset future time period includes:

[0033] Establish a simulation environment that includes noise injection, multipath time-varying, and disturbance burst models;

[0034] The preliminary transmission plan is imported into the simulation environment, and the simulated transmission process is gradually advanced according to the timeline;

[0035] At each critical point in the simulated transmission process, the simulated transmission status of each data packet is recorded. The simulated transmission status includes the simulated received signal strength, the simulated bit error rate, and the simulated transmission progress.

[0036] Preferably, the step of calculating the stability evaluation index of multiple potential transmission paths based on the deduction results includes:

[0037] For each data packet, analyze the fluctuations in its simulated transmission state during the simulation process;

[0038] The number of times, duration, and severity of abnormal fluctuations occurred in the statistical simulation of the transmission status;

[0039] Based on the statistical results, a quantitative stability evaluation index is calculated for each data packet in the transmission path corresponding to the initial transmission plan. The value of the stability evaluation index is negatively correlated with the frequency, duration and severity of abnormal fluctuations.

[0040] Preferably, constructing a transmission path selection tree for decision-making includes:

[0041] The global goal of data transmission is taken as the root node, and the global goal includes at least the minimum overall transmission latency and the maximum overall transmission success rate;

[0042] The alternative transmission resources for each data packet and their corresponding stability evaluation indicators are used as branch nodes;

[0043] Constrain the connection rules of branch nodes based on the logical dependencies between data packets;

[0044] By using a traversal algorithm, among all possible path combinations that satisfy the connection rules, several candidate paths that optimize the global goal of the root node are searched, and these candidate paths are organized in a tree structure to form a transmission path selection tree.

[0045] Preferably, the step of selecting a final transmission path for each data packet based on the transmission path selection tree and encoding the path selection information into the data packet header includes:

[0046] Select the candidate path that best achieves the global objective from the transmission path selection tree as the final execution plan;

[0047] Analyze the final execution plan to determine the specific time-frequency resource unit sequence corresponding to each data packet in the plan;

[0048] The specific time-frequency resource unit sequence, the predetermined transmission power level, and the corresponding stability evaluation index are jointly encoded into a set of encrypted identifiers;

[0049] The ciphertext identifier is added to the header extension field of the corresponding data packet.

[0050] Preferably, the step of fine-tuning the transmission timing and power allocation of data packets in the entity's transmission queue based on the attributes of the selected final transmission path, and dynamically adjusting the transmission timing and power of subsequent data packets, includes:

[0051] Before sending data packets in the sending entity's sending queue, read the ciphertext identifier in the packet header and decode it to obtain the predetermined sending power level;

[0052] Configure the transmitter's instantaneous transmit power according to the predetermined transmit power level;

[0053] During transmission, status summary information fed back from the receiving end is received in real time, and the status summary information includes a channel mutation warning identifier.

[0054] If a channel mutation warning flag appears in the status summary information, the original timing is paused, and the preset adjustment strategy table is queried according to the channel mutation type at the current time. The adjustment strategy table defines the adjustment rules for transmission timing and power under different types of channel mutations.

[0055] Based on the corresponding rules in the adjustment strategy table, the sending time and power level of the data packets that have not yet been sent in the entity's sending queue are modified in real time, and then the sending continues.

[0056] Compared with the prior art, the beneficial effects of the present invention are:

[0057] By acquiring the real-time channel quality spectrum reflecting the distribution of channel availability at different times and frequencies, and then performing point-by-point matching and coupling of preprocessed data packets with this spectrum, this operation achieves optimal pre-allocation of transmission resources in a two-dimensional space of time and frequency domains. This allows the transmission of each data packet to precisely align with the high-quality "time-frequency window" identified in the channel quality spectrum, actively avoiding interference and deep fading regions. Through two-dimensional analysis and pre-matching of channel states, data transmission shifts from passive adaptation to active planning, improving the utilization efficiency of spectrum resources and reducing the probability of transmission failures due to instantaneous resource degradation.

[0058] After generating an initial transmission plan, the process of multiple potential transmission paths is further simulated over a preset future time period. Based on the simulation results, stability evaluation indicators for each path are calculated, thereby constructing a structured transmission path selection tree. This mechanism upgrades single-point decision-making to a systematic selection based on multi-step look-ahead simulation. It allows the transmission system to not only consider the current state of a path but also quantitatively assess its stable transmission potential over a future period. Decision-making based on the selection tree can filter out the path with the highest expected stability and encode this path information into the data packet header. This enables the data transmission process to withstand sudden changes in the channel, proactively avoiding potentially unstable paths, ensuring the continuity and success rate of data packet transmission in complex time-varying channels, and improving the overall resilience of the communication link. Attached Figure Description

[0059] Figure 1 This is a schematic diagram illustrating the working principle of the BeiDou satellite short message communication data unpacking and transmission method described in this invention.

[0060] Figure 2 A flowchart for data packet pre-configuration and adaptive training;

[0061] Figure 3 A flowchart illustrating the coupling of data packets with time-frequency resources;

[0062] Figure 4 A diagram illustrating the fluctuations in the simulated transmission status of BeiDou short messages;

[0063] Figure 5 A comparison chart of stability evaluation indicators for BeiDou short message transmission paths. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] Please see Figure 1 This invention provides a method for splitting and transmitting short message communication data from BeiDou satellites. The method includes: establishing a dynamic adaptive transmission framework based on the transmission characteristics of short message data packets; generating an independent virtual transmission container for each split data packet; pre-configuring and adaptively training the data packets before transmission based on preset channel environment parameters and data packet characteristic parameters; obtaining the real-time channel quality spectrum within the framework to reflect the channel availability distribution at different times and frequencies; performing point-by-point matching and coupling between the pre-configured and adaptively trained data packets and the real-time channel quality spectrum to generate a preliminary transmission plan; performing transmission process simulation on the preliminary transmission plan within a preset future time period; calculating the stability evaluation index of multiple potential transmission paths based on the simulation results; constructing a transmission path selection tree based on the stability evaluation index; selecting a final transmission path for each data packet based on the transmission path selection tree and encoding the path selection information into the data packet header; placing the encoded data packets into an entity transmission queue in sequence; fine-tuning the transmission timing and power allocation of the data packets in the entity transmission queue according to the attributes of the selected final transmission path; and dynamically adjusting the transmission timing and power of subsequent data packets.

[0066] Example 1: See Figure 2The preset channel environment parameters include channel noise power spectral density, channel multipath delay distribution, interference frequency distribution, signal fading type, fading rate, and Doppler shift value. The channel noise power spectral density is determined based on statistical analysis of typical background noise in the satellite channel. The multipath delay distribution is extracted from terrain reflection path data during historical transmissions. The interference frequency distribution is derived from past interference events recorded in the same frequency band. The signal fading type and rate are preset based on regional channel characteristics. The Doppler shift value is estimated based on the relative motion speed between the satellite and the terminal. Meta-information of the data packets is extracted. This meta-information includes at least the data packet length, the logical position of the data packet in the original data stream, and the identifiers of the preceding and following dependent packets. Based on this meta-information, a virtual structure containing a state simulation unit and a parameter register unit is constructed. This virtual structure is the virtual transmission container. The basic transmission requirement parameters of the data packets are written into the parameter register unit of the virtual transmission container. These basic transmission requirement parameters include the expected maximum delay, the acceptable bit error rate threshold, and the priority label. The virtual transmission container is a virtual structure composed of a state simulation unit and a parameter register unit. The parameter register unit stores the basic transmission requirement parameters of the data packets, including the expected maximum delay, acceptable bit error rate threshold, and priority label. The expected maximum delay defines the maximum allowed time for a data packet to travel from transmission to reception; the acceptable bit error rate threshold specifies the upper limit of the tolerable error rate during transmission. The priority label identifies the importance of the data packets so that high-priority data is prioritized during resource allocation. The state simulation unit is a simulation engine used to predict the behavior of data packets under different channel conditions before transmission. It simulates the response of data packets to disturbances such as noise and fading by loading successful samples from historical transmission records, thus providing a basis for subsequent adaptive training. These two units together constitute the core of the virtual transmission container: the parameter register unit statically stores requirements, while the state simulation unit dynamically simulates behavior, ensuring that data packets are optimally configured before actual transmission. When performing pre-configuration and adaptive training on data packets before transmission, successful transmission samples of past data packets with similar characteristic parameters to the current data packet are loaded from historical transmission records. In the state simulation unit of the virtual transmission container, the successful transmission samples of past data packets are used as the training set to simulate the behavior response of data packets under different channel disturbance modes. Based on the simulation results, a set of adaptive parameters inside the virtual transmission container is adjusted and solidified.

[0067] The construction of the virtual structure begins with extracting the metadata of data packets and creating a state simulation unit based on this. Within the state simulation unit, the process of simulating data packet behavior responses is achieved by loading historical successful transmission samples as a training set. These samples are selected from historical records with characteristics similar to the current data packet, such as past transmission instances matching packet length and priority tags. During simulation, the system injects different channel perturbation modes, such as Rayleigh fading, Doppler shift, and impulse noise interference. The state simulation unit runs these perturbation scenarios sequentially, recording changes in signal strength, bit error rate fluctuations, and transmission progress of data packets in the simulated environment. Based on the simulation results, the system adjusts the adaptive parameters within the virtual transmission container, such as increasing the transmission tendency of data packets during high-quality channel periods or optimizing retransmission strategies. The virtual structure is constructed through software-defined modules; the state simulation unit acts as a computational module, and the parameter register unit acts as a storage module. Both are integrated within the virtual container, ensuring that data packets undergo adaptive configuration before transmission.

[0068] In practical implementation, the metadata of BeiDou short message data packets is extracted. The metadata includes the data packet length, the logical position of the data packet in the original data stream, and the identifiers of the preceding and following dependent packets. Taking a sensor data upload task containing geographic location, ambient temperature, and battery status as an example, the original data stream is split into three data packets with lengths of 100 bytes, 80 bytes, and 50 bytes, respectively. The logical positions of the data packets in the original data stream are 1, 2, and 3, respectively. The identifier of the preceding dependent packet indicates that data packet 2 depends on the successful transmission of data packet 1, and data packet 3 depends on the successful transmission of data packet 2. The identifier of the following dependent packet is marked in the opposite way. A virtual structure containing a state simulation unit and a parameter register unit is constructed based on the metadata. This virtual structure is the virtual transmission container. The basic transmission requirement parameters of the data packet are written into the parameter register unit of the virtual transmission container. The basic transmission requirement parameters include the expected maximum delay, the acceptable bit error rate threshold, and the priority label. For data packets with a logical position of 1, the expected maximum delay is set to 5 seconds, the acceptable bit error rate threshold is 1E-6, and the priority label is high. For data packets with logical positions of 2 and 3, the expected maximum delay is set to 8 seconds, the acceptable bit error rate threshold is 1E-5, and the priority label is medium.

[0069] In practical implementation, during the pre-configuration and adaptive training of data packets before transmission, successful transmission samples of past data packets with similar characteristic parameters to the current data packet are loaded from historical transmission records. The characteristic parameters of these successful transmission samples are historical transmission records with data packet lengths between 90 and 110 bytes and high priority tags. In the state simulation unit of the virtual transmission container, these successful transmission samples are used as the training set to simulate the behavioral response of data packets under different channel disturbance modes, including Rayleigh fading, Doppler shift, and impulse noise interference.

[0070] In practical implementation, a set of adaptive parameters within the virtual transmission container are adjusted and solidified based on simulation results. These adaptive parameters include a transmission rate preference factor, a retransmission sensitivity factor, and a power adjustment step factor. The transmission rate preference factor indicates the tendency of data packets to be transmitted during high-quality channel periods. The retransmission sensitivity factor reflects the sensitivity of data packets to retransmission triggered by packet loss events. The power adjustment step factor defines the adjustment range of transmit power during signal fluctuations. Adjusting these parameters is based on simulation results from the state simulation unit. The system analyzes the statistical behavior of data packets under simulated channel disturbances, such as statistically analyzing the power changes or bit error rate improvements required to maintain stable reception in historical samples. The adjustment process is achieved through weighted averaging or threshold comparison. For example, for the power adjustment step factor, the system calculates the ratio of signal strength change to bit error rate in multiple historical samples and takes the average as the solidified value. After parameter adjustment, the parameters are solidified in the virtual transmission container for subsequent transmission matching.

[0071] In practical implementation, the calculation of the transmission rate preference factor, retransmission sensitivity factor, and power adjustment step factor is based on the simulation analysis of historical transmission records by the state simulation unit in the virtual transmission container. The transmission rate preference factor is quantified by the ratio of the number of data packets transmitted during high-quality channel periods to the total number of transmissions in the historical successful transmission samples, and the formula is:

[0072]

[0073] A higher value indicates that data packets are more likely to be transmitted over high-quality resources. The retransmission sensitivity factor is calculated by analyzing the probability of a data packet triggering a retransmission after the initial transmission failure in historical samples. The formula is:

[0074]

[0075] The solidification process of adaptive parameters is calculated based on the statistical characteristics of packet behavior response during simulated training. The formula for calculating the power adjustment step factor of packets with a logic position of 1 is as follows:

[0076]

[0077] in: It is the power adjustment step factor. It is the number of historical training samples. It is the first The suggested signal strength variation for each sample in the simulation to maintain stable reception. This is the bit error rate achieved by the sample under the corresponding adjustment. It can be understood that this formula aims to quantify the amount of signal strength adjustment required to improve the bit error rate per unit, thus solidifying it as a power adjustment step factor. Optionally, the selection criteria for successful transmission samples of past data packets also include the logical position of the data packet and the identifier of the preceding dependent packet to ensure the correlation of training samples. Optionally, the simulation process of the state simulation unit can introduce typical channel condition profiles of different seasons and times to enhance the generalization ability of the adaptive parameters. It can be understood that the simulation process is a reproduction and learning of historical experience, aiming to assign each independent virtual transmission container a preliminary transmission strategy that conforms to its data packet characteristic parameters and basic transmission requirement parameters. This algorithm simulates channel disturbance patterns in the state simulation unit by inputting data packet metadata, such as a data packet length of 100 bytes, logical position 1, and high priority tag, as well as successful sample data from historical transmission records, such as past records with data packet lengths of 90-110 bytes and high priority tags. The algorithm processes this input data and calculates the power adjustment step factor using the formula:

[0078] ∆p

[0079] in, It is the recommended signal strength variation in the historical samples to maintain stable reception. This corresponds to the bit error rate. This represents the number of samples. The output consists of adaptive parameters, which are embedded in a virtual transmission container to guide subsequent transmission strategies and improve the anti-interference capability of data packets in real channels.

[0080] Example 2: See Figure 3The real-time channel quality spectrum is discretized into multiple time-frequency resource units (TFLUs). The coupling degree between the channel quality score of each TFLU and the adaptability parameters of the data packets within the virtual transmission container is calculated. For each data packet, TFLUs with coupling degrees exceeding a set threshold are selected as candidate transmission resources. Generating a preliminary transmission plan involves associating each data packet with its corresponding candidate transmission resource to form a preliminary resource mapping table. Based on the resource mapping table, the transmission start and end points of all data packets are arranged in the time dimension to generate an initial transmission timeline. The initial transmission timeline is checked for resource mapping conflicts. A resource mapping conflict is defined as different data packets scheduled to be transmitted on the same TFLU. If a resource mapping conflict exists, the candidate transmission resources for the conflicting data packets are reselected and replaced based on the data packet priority label and coupling degree until the conflict is resolved, generating a conflict-free preliminary transmission plan.

[0081] In practical implementation, the real-time channel quality spectrum is discretized into multiple time-frequency resource units. The real-time channel quality spectrum reflects the predicted signal-to-noise ratio and packet error rate at different times and frequencies within a future scheduling cycle. The discretization process divides the time axis into grids with 10-millisecond intervals and the frequency axis with 1-kilohertz intervals. Each time-frequency grid is defined as a time-frequency resource unit, and each time-frequency resource unit is associated with a quantified channel quality score. The coupling degree between the channel quality score of each time-frequency resource unit and the adaptive parameters of the data packets within the virtual transmission container is calculated. The adaptive parameters of the data packets within the virtual transmission container include a transmission rate preference factor, a retransmission sensitivity factor, and a power adjustment step factor. Taking a data packet with a logical bit of 1 as an example, its transmission rate preference factor is 0.9, its retransmission sensitivity factor is 0.3, and its power adjustment step factor is 2.1. For a time-frequency resource unit with a channel quality score of 8.5, the coupling degree between the two is calculated. The formula for calculating the coupling degree M is:

[0082]

[0083] in: It represents the coupling degree between the k-th data packet and the l-th time-frequency resource unit. It is the channel quality score of the time-frequency resource unit. It is the data packet transmission rate preference factor. It is the retransmission sensitivity factor for data packets. It is the prediction packet error rate of the time-frequency resource unit. and These are preset weighting coefficients. and The determination of the density is guided by the core needs of data transmission, combined with the characteristics of BeiDou short message communication scenarios and transmission objectives. It is based on the priority preference of transmission for channel quality assurance or packet error rate reduction, and the contribution ratio is extracted from the statistical analysis results of historical transmission data to set specific values. These values ​​are dynamically adjusted according to the transmission scenario to match the transmission requirements under different scenarios. For each data packet, time-frequency resource units with coupling degrees exceeding a set threshold are selected as candidate transmission resources. The threshold value is set to 0.7. The coupling degree calculation results for data packet 1 are 0.85, 0.72, 0.68, and 0.91. Therefore, three time-frequency resource units corresponding to coupling degrees of 0.85, 0.72, and 0.91 are selected as candidate transmission resources for data packet 1. In some embodiments, the discretized grid density can be dynamically adjusted according to the total available bandwidth and the length of the scheduling cycle.

[0084] In practical implementation, generating a preliminary transmission plan involves associating each data packet with its corresponding alternative transmission resources to form a preliminary resource mapping table. This table records the data packet identifier, a list of alternative time-frequency resource units, and the corresponding coupling degree. Based on the resource mapping table, the start and end points of all data packets are arranged in the time dimension. For each data packet, a start resource unit and an end resource unit are selected from its alternative transmission resources. The transmission duration is estimated based on the data packet length and a preset transmission rate, thus marking the expected transmission window of each data packet on a unified timeline. The initial transmission timeline is then checked for resource mapping conflicts. A resource mapping conflict is defined as different data packets scheduled to be transmitted on the same time-frequency resource unit. For example, if data packet 1 selects time-frequency resource unit A, and data packet 2's alternative resources also include time-frequency resource unit A, and their expected transmission windows overlap on the timeline, then a resource mapping conflict is determined to exist. If a resource mapping conflict exists, the candidate transmission resources for the conflicting data packets are reselected and replaced based on the priority label and coupling degree of the data packets. Data packet 1 has a high priority label and a coupling degree of 0.85 with resource unit A, while data packet 2 has a medium priority label and a coupling degree of 0.75 with resource unit A. Since data packet 1 has a higher priority, its occupation of resource unit A is retained, and data packet 2 is replaced by resource unit B, which has the second highest coupling degree in its candidate resource list and a coupling degree of 0.70. Optionally, the conflict resolution process is iterative until the time-frequency resource units occupied by the transmission windows of all data packets on the timeline do not overlap, generating a conflict-free preliminary transmission plan. Optionally, the preliminary transmission plan is stored in the form of a time-frequency resource allocation matrix, where the rows of the matrix correspond to time-frequency resource units, the columns correspond to time slices, and the matrix element values ​​identify the data packet number occupying that resource.

[0085] Example 3: A simulation environment is established, incorporating noise injection, multipath time-varying, and interference burst models. The initial transmission plan is imported into the simulation environment, and the simulated transmission process is progressively advanced according to the timeline. At each key time point in the simulated transmission process, the simulated transmission status of each data packet is recorded, including simulated received signal strength, simulated bit error rate, and simulated transmission progress. The simulation environment is established through a software simulation platform that integrates noise injection, multipath time-varying, and interference burst models. The noise injection model uses additive white Gaussian noise to simulate background noise, with parameters such as noise power spectral density set based on typical values ​​for satellite channels. The multipath time-varying model uses dynamic tapped delay lines to simulate signal reflection and delay variations, with parameters including the number of multipath paths and delay time, which are dynamically updated based on the geographical locations of the satellite and the terminal. The interference burst model simulates periodic strong signal impacts in the same frequency band, with parameters such as interference period and intensity preset based on historical interference patterns. Specifically, the system imports the initial transmission plan into the simulation environment, progressively advances the simulation according to the timeline, and records the simulated transmission status at key time points, including received signal strength, bit error rate, and transmission progress. The input is the initial time-frequency resource allocation of the transmission plan, and the output is the simulated state record of each data packet, used for subsequent stability assessment. The simulation environment is designed to ensure realistic simulation, and the parameters are configured based on channel characteristics, requiring no external experimental data.

[0086] Noise injection, multipath time-varying, and interference burst models in the simulation environment were constructed using a software simulation platform. The noise injection model used additive white Gaussian noise to simulate background noise, with parameters such as noise power spectral density set based on typical values ​​for satellite channels, for example, setting the noise variance according to the average noise level of the BeiDou channel. The multipath time-varying model used dynamically tapped delay lines to simulate signal reflection and delay variations in complex terrain, with parameters including the number of multipath paths, delay time, and gain coefficient. These parameters were dynamically updated based on the real-time geometric relationship between the satellite and the terminal. The interference burst model simulated periodic, strong signal impacts in the same frequency band, with parameters such as interference period, duration, and intensity preset based on historical interference patterns; for example, the interference period was set to several hundred milliseconds, and the intensity was 10-20 dB higher than the noise level. During model construction, all parameters were configured based on satellite channel characteristics, requiring no external experimental data, ensuring realistic simulation.

[0087] The initial time-frequency resource allocation in the transmission plan refers to the process of mapping data packets to a sequence of discretized time-frequency resource units. Specifically, this includes: first, discretizing the real-time channel quality spectrum into a grid along the time and frequency axes, defining each grid as a time-frequency resource unit and assigning it a channel quality score; then calculating the coupling degree between the channel quality score and the data packet adaptability parameters for each resource unit, and selecting resource units with coupling degrees exceeding a threshold as candidate transmission resources for data packets; next, forming a resource mapping table to record the association between data packet identifiers and candidate resource units; finally, arranging the transmission start and end points of all data packets along the time dimension to generate an initial transmission timeline, and resolving resource conflicts through priority and coupling degree to generate a conflict-free plan.

[0088] When calculating the stability evaluation index of multiple potential transmission paths based on the simulation results, the fluctuation of the simulated transmission state of each data packet during the simulation process is analyzed. The number of abnormal fluctuations, duration and severity of abnormal fluctuations in the simulated transmission state are counted. Based on the statistical results, a quantitative stability evaluation index is calculated for the transmission path corresponding to each data packet in the preliminary transmission plan. The value of the stability evaluation index is negatively correlated with the frequency, duration and severity of abnormal fluctuations.

[0089] In the specific implementation, a simulation environment was established, incorporating noise injection, multipath time-varying, and interference burst models. The noise injection model used additive white Gaussian noise to simulate background noise, the multipath time-varying model employed dynamic tapped delay lines to simulate signal reflection and delay variations in complex terrain, and the interference burst model simulated periodic strong signal impacts within the same frequency band. The preliminary transmission plan was imported into the simulation environment, and the simulated transmission process was progressively advanced according to a timeline, with the timeline incrementing in milliseconds. The total simulation duration was the 5-second transmission window covered by the preliminary transmission plan. At each critical time point in the simulated transmission process, the simulated transmission status of each data packet was recorded. The critical time points included the start, midpoint, and end times of each time-frequency resource unit. The simulated transmission status included the simulated received signal strength, simulated bit error rate, and simulated transmission progress. For a data packet with a logical bit of 1, at the critical time point of 1020 milliseconds in the timeline, the simulated received signal strength was recorded as -92 dBm, the simulated bit error rate as 8.5E-7, and the simulated transmission progress as 65%.

[0090] In practical implementation, when calculating the stability evaluation index of multiple potential transmission paths based on the simulation results, the fluctuation of the simulated transmission state of each data packet during the simulation process is analyzed. This includes analyzing the number and magnitude of deviations of the simulated received signal strength from the preset strength threshold, and the number and amount of exceedances of the simulated bit error rate (BER) from the acceptable BER threshold. The number, duration, and severity of abnormal fluctuations in the simulated transmission state are statistically analyzed. Abnormal fluctuations are defined as events where the simulated received signal strength is below -100 dBm or the simulated BER is above the acceptable BER threshold. For data packets with logical position 2, it was found that abnormal fluctuations occurred 3 times within a 5-second simulation window, with a cumulative duration of 320 milliseconds, and an average BER exceeding the threshold by a factor of 5.2 per fluctuation. Based on the statistical results, a quantitative stability evaluation index is calculated for each data packet corresponding to the transmission path in the initial transmission plan. The value of the stability evaluation index is negatively correlated with the frequency, duration, and severity of abnormal fluctuations. The stability evaluation index is then calculated. The formula is:

[0091]

[0092] in: It is a stability evaluation index. It refers to the number of times abnormal fluctuations occur. It is the ratio of the total duration of abnormal fluctuations to the total estimated duration. It is the sum of the average bit error rate exceeding the threshold multiple during periods of abnormal fluctuations. , and These are preset weighting coefficients for the number of occurrences, duration, and severity. Optionally, fluctuations in the simulated transmission progress during the simulated transmission state can also be used as one of the criteria for judging abnormal fluctuations. When the simulated transmission progress does not increase within two consecutive key time points, it can be judged as an abnormal progress stagnation. Optionally, the simulation environment can introduce specific spatiotemporal interference patterns based on historical data to enhance the realism of the simulation. In some embodiments, the parameters of the multipath time-varying model can be dynamically updated according to the real-time geometric relationship between the satellite and the terminal. In some embodiments, the density of key time points can be adjusted, using a higher recording frequency during periods of drastic changes in the simulated bit error rate. It can be understood that the simulation process is a stress test of the preliminary transmission plan in a simulated channel environment. It can be understood that the calculation of stability evaluation indicators aims to quantify the differences in robustness of different transmission paths when facing disturbances.

[0093] See Figure 4This figure is a visualization of the transmission process simulation, using a dual Y-axis line graph to present the changes in the transmission state of data packets under a simulated channel environment. It is a visual output of the simulation environment, including noise and multipath propagation, recording the transmission state at key time points. The value of this figure lies in its intuitive presentation of the impact of channel disturbances on the transmission state, providing data support for subsequent statistics on the number and duration of abnormal fluctuations. It forms the basis for calculating transmission path stability evaluation indicators and embodies the core design of evaluating transmission robustness through forward-looking simulation.

[0094] Example 4: Taking the global data transmission objective as the root node, which includes at least minimizing overall transmission latency and maximizing overall transmission success rate, and using the candidate transmission resources and their corresponding stability evaluation indicators for each data packet as branch nodes, the connection rules of the branch nodes are constrained according to the logical dependencies between data packets. A traversal algorithm searches for several candidate paths that optimize the global objective of the root node among all possible path combinations that satisfy the connection rules, and organizes these candidate paths into a tree structure to form a transmission path selection tree. The traversal algorithm is a depth-first or breadth-first search algorithm used to explore all possible path combinations in the transmission path selection tree. In operation, the algorithm takes the global objective as the root node and then traverses the candidate transmission resource branch nodes of the data packets layer by layer. Specifically, the algorithm starts from the candidate resource node with data packet identifier 1 and connects the next layer of nodes according to the logical dependencies between data packets. For each complete path, the algorithm calculates a comprehensive utility value based on the path's stability evaluation indicator and latency estimate.

[0095] The overall utility value is calculated using a weighted summation model, and the formula is as follows:

[0096]

[0097] in: and It is weight and , It is the path stability utility value. It is the time delay utility value. This is the normalized value of the product of the stability evaluation metrics of all data packets in the path, and the formula is: .in It is a stability evaluation metric for a single data packet. The normalized value of the time delay is given by the formula: .in It is the overall transmission delay of the path. and These are the minimum and maximum delays for all candidate paths, respectively.

[0098] During the search process, the algorithm prunes invalid paths, ultimately selecting several candidate paths and organizing them into a tree structure. The execution of the traversal algorithm does not depend on a specific optimization library, but is based on rule iteration, ensuring that path selection conforms to dependency constraints and the global objective.

[0099] In practical implementation, the global data transmission objective is taken as the root node. The global objective includes at least minimizing the overall transmission delay and maximizing the overall transmission success rate. The overall transmission delay is defined as the time elapsed from the start of transmission of all data packets to the successful reception of the last data packet. The overall transmission success rate is defined as the product of the probabilities of all data packets being successfully received within a preset maximum number of retransmissions. Each data packet's candidate transmission resources and their corresponding stability evaluation indicators are taken as branch nodes. Each branch node includes a data packet identifier, a specific time-frequency resource unit sequence allocated to it, and the corresponding stability evaluation indicator. For example, data packets with identifier 1 have candidate resource sequences A1 and A2, with stability evaluation indicators of 0.87 and 0.72, respectively. Data packets with identifier 2 have candidate resource sequences B1, B2, and B3, with stability evaluation indicators of 0.91, 0.65, and 0.80, respectively. The connection rules for branch nodes are constrained by the logical dependencies between data packets. The logical dependencies stipulate that a data packet with the identifier 2 can only start transmitting after the data packet with the identifier 1 has been successfully transmitted, and a data packet with the identifier 3 can only start transmitting after the data packet with the identifier 2 has been successfully transmitted. Therefore, the connection of branch nodes must follow the order from the node with the identifier 1 to the node with the identifier 2, and then to the node with the identifier 3. Connections across data packet identifiers are not allowed.

[0100] In practice, a traversal algorithm searches for several candidate paths that optimize the global objective of the root node among all possible path combinations that satisfy the connection rules. The traversal algorithm starts with all candidate branch nodes representing data packet 1, explores candidate branch nodes for data packet 2 according to the connection rules, and then explores candidate branch nodes for data packet 3, forming a complete path from the root node to the leaf node. Each complete path corresponds to a scheme for allocating specific transmission resources to all data packets. See Table 1 for the candidate resources and indicators for each data packet.

[0101] Table 1: Evaluation Indicators for Alternate Data Packet Transmission Resources and Stability

[0102]

[0103] By traversing all possible combinations and calculating their respective U values, several paths with the highest U values ​​can be selected. These candidate paths are organized into a tree structure to form a transmission path selection tree. The root node of the transmission path selection tree represents the global goal. The first-level branches from the root node represent alternative solutions (A1, A2) for data packet 1. The second-level branches from each first-level branch node represent feasible alternative solutions for data packet 2 given that data packet 1 selects this solution, and so on, until the leaf nodes represent the complete transmission scheme. Each path from the root to a leaf in the tree is a candidate path, and each path is associated with its calculated comprehensive utility value U. Optionally, the transmission path selection tree is constructed by considering the estimated overall transmission delay. Exceed Prune the path.

[0104] See Figure 5 This figure visualizes the results of the transmission path stability assessment, presenting the product of stability evaluation indicators for five candidate transmission paths in a bar chart format. This figure is one of the key bases for constructing the transmission path selection tree based on the derived stability indicators. Its value lies in intuitively quantifying the disturbance resistance of different paths, assisting in selecting the optimal path with low overall latency and high stability from the transmission path selection tree. It reflects the design concept of proactively assessing path stability and mitigating channel degradation risks, providing visual support for path decisions in reliable short message transmission.

[0105] Example 5: Select the candidate path that optimizes the global objective from the transmission path selection tree as the final execution plan. Analyze the final execution plan to determine the specific time-frequency resource unit sequence corresponding to each data packet in the plan. Encode the specific time-frequency resource unit sequence, the predetermined transmission power level, and the corresponding stability evaluation index into a set of ciphertext identifiers. Add the ciphertext identifiers to the header extension field of the corresponding data packet. Based on the attributes of the selected final transmission path, the timing and power allocation of data packets in the entity's transmission queue are fine-tuned. When dynamically adjusting the timing and power of subsequent data packets, the encrypted identifier in the header of the data packet is read before the data packet in the entity's transmission queue, and the predetermined transmission power level is decoded. The instantaneous transmission power of the transmitter is configured according to the predetermined transmission power level. During transmission, the status digest information fed back from the receiver is received in real time. The status digest information includes a channel mutation warning indicator. If the channel mutation warning indicator appears in the status digest information, the original timing is paused. The preset adjustment strategy table is queried according to the channel mutation type at the current moment. The adjustment strategy table defines the adjustment rules for transmission timing and power under different types of channel mutations. The transmission time and power level of the data packets that have not yet been transmitted in the entity's transmission queue are modified in real time according to the corresponding rules in the adjustment strategy table, and then the transmission continues.

[0106] In the specific implementation, a candidate path that optimizes the global objective is selected from the transmission path selection tree as the final execution plan. The optimization of the global objective is determined based on the comprehensive utility value of each candidate path in the transmission path selection tree. The path with the highest comprehensive utility value is selected as the final execution plan. For example, if the path consisting of sequence A1 for data packet 1, sequence B1 for data packet 2, and sequence C1 for data packet 3 in the transmission path selection tree has the highest comprehensive utility value of 22.8, then this path is selected as the final execution plan. The final execution plan is then analyzed to determine the specific time-frequency resource unit sequence corresponding to each data packet in the plan. The specific time-frequency resource unit sequence corresponding to data packet 1 is [unit (1,5), unit (2,5)], the specific time-frequency resource unit sequence corresponding to data packet 2 is [unit (4,7), unit (5,7)], and the specific time-frequency resource unit sequence corresponding to data packet 3 is [unit (8,10)]. The specific time-frequency resource unit sequence, the predetermined transmission power level, and the corresponding stability evaluation index are jointly encoded into a set of ciphertext identifiers. The predetermined transmission power level is determined based on the historical channel quality of the resource unit and the data packet priority. The predetermined transmission power level of data packet 1 is level 3, and the stability evaluation index is 0.87. The encoding process uses a preset mapping table to convert the time-frequency resource unit number, power level value, and stability evaluation index value into a binary sequence of a specific length and then concatenates them to form the ciphertext identifier "010001010011011111010111". The ciphertext identifier is added to the header extension field of the corresponding data packet. The header extension field reserves 32 bits for storing the ciphertext identifier, and the generated 24-bit ciphertext identifier is written into it.

[0107] In practical implementation, when fine-tuning the transmission timing and power ratio of data packets in the entity's transmission queue based on the attributes of the selected final transmission path, and dynamically adjusting the transmission timing and power of subsequent data packets, the encrypted identifier in the header of the data packet is read before the data packet in the entity's transmission queue. This is then decoded to obtain the predetermined transmission power level. For data packet 1, the decoded transmission power level is level 3. The transmitter's instantaneous transmission power is configured according to the predetermined transmission power level. The transmitter has a built-in mapping relationship between power level and absolute power value; power level 3 corresponds to a transmission power of 23dBm. During transmission, status summary information fed back from the receiving end is received in real time. This status summary information includes a channel mutation warning flag, which is transmitted through the frame structure. A flag bit of '1' indicates a detected channel mutation. If a channel mutation warning flag appears in the status summary information, the original timing is paused. For example, if status summary information containing a channel mutation warning flag is received during the transmission of data packet 2, the preset adjustment strategy table is queried based on the current channel mutation type. The channel mutation type is indicated by the type subfield in the status summary information. The adjustment strategy table defines the adjustment rules for transmission timing and power under different types of channel mutations. The calculation of the adjustment rule involves a compensation factor. Its formula is:

[0108]

[0109] in: It is a compensation factor used to calculate delay time and power adjustment factor. It is the severity coefficient corresponding to the channel mutation type. It is a stability evaluation metric for the next data packet to be sent. It represents the number of data packets in the entity's sending queue that have not yet been sent. This indicates rounding down. Based on the corresponding rules in the adjustment strategy table, the transmission time and power level of untransmitted data packets in the entity's transmission queue are modified in real-time, and transmission continues. Assuming the current channel mutation type is "deep fading," the adjustment strategy table stipulates that under this type, the transmission time of all subsequent untransmitted data packets should be delayed. milliseconds, and temporarily boost its transmission power level. Level, if calculated If the value is 2, the transmission time of data packet 3 will be delayed by 20 milliseconds, and its transmission power level will be temporarily adjusted from the predetermined level 2 to level 4.

[0110] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0111] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for disassembling and transmitting short message communication data using BeiDou satellites, characterized in that, Includes the following steps: Establish a dynamic adaptive transmission framework for short message data packets; Under the aforementioned dynamic adaptive transmission framework, an independent virtual transmission container is generated for each split data packet; In the virtual transmission container, based on preset channel environment parameters and data packet characteristic parameters, the data packets are pre-configured and adaptively trained before transmission. Obtain the real-time channel quality spectrum within the dynamic adaptive transmission framework, the real-time channel quality spectrum reflecting the channel availability distribution at different times and frequencies; The data packets that have completed pre-configuration and adaptive training in the virtual transmission container are matched and coupled point by point with the real-time channel quality spectrum to generate a preliminary transmission plan. The transmission process of the preliminary transmission plan is simulated within a preset future time period, and the stability evaluation index of multiple potential transmission paths is calculated based on the simulation results. Based on the stability evaluation index, a transmission path selection tree for decision-making is constructed; Based on the transmission path selection tree, a final transmission path is selected for each data packet, and the path selection information is encoded into the data packet header; The encoded data packets are placed into the entity sending queue in sequence, and the sending timing and power ratio of the data packets in the entity sending queue are fine-tuned according to the attributes of the selected final transmission path. The sending timing and power of subsequent data packets are dynamically adjusted.

2. The method for disassembling and transmitting BeiDou satellite short message communication data according to claim 1, characterized in that, The step of generating an independent virtual transport container for each split data packet includes: Extract the metadata of the data packet, which includes at least the data packet length, the logical position of the data packet in the original data stream, and the identifiers of the preceding and following dependent packets of the data packet; Based on the aforementioned metadata, a virtual structure containing a state simulation unit and a parameter register unit is constructed, and the virtual structure is a virtual transmission container. In the parameter register unit of the virtual transmission container, basic transmission requirement parameters of the data packet are written, including the expected maximum latency, the acceptable bit error rate threshold, and the priority label.

3. The method for disassembling and transmitting BeiDou satellite short message communication data according to claim 2, characterized in that, The pre-configuration and adaptive training of data packets before transmission includes: Load successful transmission samples of past data packets with similar characteristic parameters to the current data packet from the historical transmission records; In the state simulation unit of the virtual transmission container, the successful transmission samples of past data packets are used as the training set to simulate the behavior response of data packets under different channel disturbance modes. Based on the simulation results, a set of adaptive parameters inside the virtual transport container are adjusted and solidified.

4. The method for unpacking and transmitting BeiDou satellite short message communication data according to claim 3, characterized in that, The step of performing point-by-point matching and coupling of the pre-configured and adaptively trained data packets in the virtual transmission container with the real-time channel quality spectrum includes: The real-time channel quality spectrum is discretized into multiple time-frequency resource units; Calculate the coupling degree between the channel quality score of each time-frequency resource unit and the adaptability parameters of the data packets in the virtual transport container; For each data packet, time-frequency resource units with a coupling degree exceeding a set threshold are selected as candidate transmission resources for the data packet.

5. A method for disassembling and transmitting BeiDou satellite short message communication data according to claim 4, characterized in that, The generation of the preliminary transmission plan includes: Each data packet is associated with its corresponding alternative transmission resource to form a preliminary resource mapping table; Based on the resource mapping table, the start and end points of all data packets are arranged in the time dimension to generate an initial transmission timeline. Check whether there is a resource mapping conflict in the initialized transmission timeline. The resource mapping conflict is defined as different data packets scheduled to be transmitted on the same time-frequency resource unit. If a resource mapping conflict exists, the alternative transmission resources for the conflicting data packets are reselected and replaced based on the priority label of the data packets and the degree of coupling, until the conflict is eliminated and a conflict-free preliminary transmission plan is generated.

6. A method for unpacking and transmitting BeiDou satellite short message communication data according to claim 5, characterized in that, The step of performing a transmission process simulation of the preliminary transmission plan within a preset future time period includes: Establish a simulation environment that includes noise injection, multipath time-varying, and disturbance burst models; The preliminary transmission plan is imported into the simulation environment, and the simulated transmission process is gradually advanced according to the timeline; At each critical point in the simulated transmission process, the simulated transmission status of each data packet is recorded. The simulated transmission status includes the simulated received signal strength, the simulated bit error rate, and the simulated transmission progress.

7. A method for disassembling and transmitting BeiDou satellite short message communication data according to claim 6, characterized in that, The stability evaluation indicators for multiple potential transmission paths calculated based on the simulation results include: For each data packet, analyze the fluctuations in its simulated transmission state during the simulation process; The number of times, duration, and severity of abnormal fluctuations occurred in the statistical simulation of the transmission status; Based on the statistical results, a quantitative stability evaluation index is calculated for each data packet in the transmission path corresponding to the initial transmission plan. The value of the stability evaluation index is negatively correlated with the frequency, duration and severity of abnormal fluctuations.

8. A method for disassembling and transmitting BeiDou satellite short message communication data according to claim 7, characterized in that, The construction of a transmission path selection tree for decision-making includes: The global goal of data transmission is taken as the root node, and the global goal includes at least the minimum overall transmission latency and the maximum overall transmission success rate; The alternative transmission resources for each data packet and their corresponding stability evaluation indicators are used as branch nodes; Constrain the connection rules of branch nodes based on the logical dependencies between data packets; By using a traversal algorithm, among all possible path combinations that satisfy the connection rules, several candidate paths that optimize the global goal of the root node are searched, and these candidate paths are organized in a tree structure to form a transmission path selection tree.

9. A method for disassembling and transmitting BeiDou satellite short message communication data according to claim 8, characterized in that, The step of selecting a final transmission path for each data packet based on the transmission path selection tree and encoding the path selection information into the data packet header includes: Select the candidate path that best achieves the global objective from the transmission path selection tree as the final execution plan; Analyze the final execution plan to determine the specific time-frequency resource unit sequence corresponding to each data packet in the plan; The specific time-frequency resource unit sequence, the predetermined transmission power level, and the corresponding stability evaluation index are jointly encoded into a set of encrypted identifiers; The ciphertext identifier is added to the header extension field of the corresponding data packet.

10. A method for disassembling and transmitting BeiDou satellite short message communication data according to claim 9, characterized in that, The step of fine-tuning the transmission timing and power allocation of data packets in the entity's transmission queue based on the attributes of the selected final transmission path, and dynamically adjusting the transmission timing and power of subsequent data packets, includes: Before sending data packets in the sending entity's sending queue, read the ciphertext identifier in the packet header and decode it to obtain the predetermined sending power level; Configure the transmitter's instantaneous transmit power according to the predetermined transmit power level; During transmission, status summary information fed back from the receiving end is received in real time, and the status summary information includes a channel mutation warning identifier. If a channel mutation warning flag appears in the status summary information, the original timing is paused, and the preset adjustment strategy table is queried according to the channel mutation type at the current time. The adjustment strategy table defines the adjustment rules for transmission timing and power under different types of channel mutations. Based on the corresponding rules in the adjustment strategy table, the sending time and power level of the data packets that have not yet been sent in the entity's sending queue are modified in real time, and then the sending continues.

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