Wireless communication data storage method and system

Abstract

The invention belongs to the technical field of wireless communication and data transmission, and relates to a wireless communication data storage method and system, and the method comprises the steps: a transmitting end packages original service data into a structured data frame, generates an implicit integrity fingerprint, carries out the parametric coding of a key field through employing the fingerprint as an index, and carries out the storage of the key field; the coding field and the other plaintext fields are combined into a composite transmission frame, related data in a memory of a sending end are cleaned after sending, and a receiving end analyzes the received frame, reconstructs and verifies the implicit fingerprint and generates a trusted data packet; if the transmission or verification fails, directional decoding and verification are carried out on the retransmission data based on the confirmed fingerprint value, and an updated trusted data packet is generated; according to the method, the problems that the effective load rate is reduced due to the fact that an explicit check field must be added in a traditional scheme, the system stability risk is caused due to the fact that a sending end occupies a limited memory for a long time to support retransmission, and the wireless bandwidth and node power consumption extra burden is caused by a complete frame retransmission mode are solved.

Description

Technical Field

[0001] This invention belongs to the technical field of wireless communication and data transmission, and relates to a wireless communication data storage method and system. Background Technology

[0002] In current IoT and industrial automation applications, massive numbers of sensor nodes need to report monitoring data at high frequency via wireless networks. These nodes are typically battery-powered and have extremely limited processing and storage resources. However, the inherent instability and error-prone nature of wireless channels necessitate communication protocols with reliable error control and data recovery mechanisms to ensure the accuracy and integrity of business data. Therefore, it is necessary to ensure reliable data transmission under strictly limited resource constraints, minimizing communication overhead and node power consumption.

[0003] Existing technologies generally employ a scheme of appending explicit check fields, such as Cyclic Redundancy Check (CRC) or hash values, to data frames and setting up a buffer at the sending end to cache transmitted data. When the receiving end fails to verify or detects packet loss, a retransmission mechanism is triggered, requesting the sending end to retrieve the original data frame from its local buffer for complete retransmission. While some improved schemes introduce data compression, they still essentially rely on the sending end to retain copies of historical data for a long period or add additional sequence numbers, check bits, and other control information to the frame structure to maintain communication synchronization.

[0004] However, this traditional approach, which relies on explicit verification and full frame buffering, has significant drawbacks in resource-constrained short-frame communication scenarios: the explicit verification field directly occupies part of the wireless frame payload space, reducing the effective data throughput of the channel; the transmitter must keep a complete copy of the transmitted data in memory for a long time to support retransmission, which puts enormous storage pressure on microcontrollers or low-power nodes with only a few KB of storage resources, easily leading to buffer overflow or even system failure; and the mode of retransmitting the entire data frame once the transmission fails not only repeatedly consumes valuable wireless bandwidth, but also increases the power consumption of the transmitting node due to frequent radio frequency operations, which is not conducive to the long-term battery life of the device. Summary of the Invention

[0005] In a first aspect, the present invention provides a wireless communication data storage method, which adopts the following technical solution: A wireless communication data storage method includes the following steps: S1. The sending end obtains all the original business data to be sent and encapsulates it into a structured raw data frame containing multiple predefined data fields. S2. Based on the structured original data frame, a verification value is generated through a preset association calculation function, which represents the inherent relationship of the data and is calculated based on a predetermined number of selected field data within the frame. This is the implicit integrity fingerprint. S3. Using the implicit integrity fingerprint as the index parameter, parameterize and encode at least one key data field in the structured original data frame to generate the encoded key field. S4. Combine the encoded key field with the remaining plaintext fields in the structured original data frame to construct a composite transmission frame that does not contain the implicit integrity fingerprint. After sending the composite transmission frame, clear the structured original data frame and the encoded key field from the sender's memory and retain the implicit integrity fingerprint in the status register as the historical session state. S5. At the receiving end, receive and parse the composite transmission frame, extract the encoded part and plaintext part to form a set of data to be verified. S6. Based on the dataset to be verified, execute a hypothesis-verification decoding loop to reconstruct and verify the implicit integrity fingerprint, and generate a trusted data packet containing the verified original key field values ​​and the confirmation fingerprint value when the verification is successful. S7. When the composite transmission frame fails to transmit or the verification fails, the receiver initiates a retransmission request to the sender and receives semantic retransmission data generated by the sender after encoding the latest key fields based on the implicit integrity fingerprint in the historical session state. The receiver performs targeted decoding and verification based on the historical context on the semantic retransmission data based on the confirmed fingerprint value in the trusted data packet to generate an updated trusted data packet.

[0006] A further aspect of the present invention generates a structured raw data frame, comprising the following steps: Collect or generate raw business data, which includes the device's unique identification information, data generation time information, and at least one sensor measurement value; According to the fixed format defined by the communication protocol, each part of the original business data is sequentially filled into the corresponding field positions; Generate a byte sequence as a structured raw data frame, in which the order of the fields and the bit length are fixed.

[0007] A further aspect of the present invention, obtaining an implicit integrity fingerprint, includes the following steps: Call a pre-defined related calculation function that takes the values ​​of multiple data fields as input and outputs a single value; Extract a preset number of values ​​from selected fields from a structured raw data frame; Perform weighted and summation operations on the values ​​of the selected field based on the associated calculation function; Divide the summation result by a preset modulus and take the remainder to obtain the implicit integrity fingerprint.

[0008] A further aspect of this invention involves generating encoded key fields, including the following steps: Use the value of the implicit integrity fingerprint as the query index; The query index is used to find and select a unique encoding mapping relationship from a pre-set multi-rule encoding mapping table, where the multi-rule encoding mapping table stores the correspondence between multiple index values ​​and encoding mapping relationships; The selected encoding mapping relationship is applied to transform the original values ​​of key data fields; The encoded key fields are generated based on the numerical values ​​obtained from the conversion process.

[0009] A further aspect of the present invention, step S4, includes the following steps: Extract all fields except key data fields from the structured raw data frame and use them as plaintext fields; According to the agreed final frame format, the encoded key fields are arranged and combined with all plaintext fields; The combined fields are concatenated and assembled into a complete composite transmission frame; After the composite transmission frame is sent, an irreversible memory release operation is performed to clear the structured original data frame and the encoded key fields, and the implicit integrity fingerprint is retained in the status register as storage space occupied by the historical session state.

[0010] A further aspect of this invention involves constructing a dataset to be verified, comprising the following steps: Receive bit streams transmitted via wireless channels; The bitstream is parsed according to a predefined frame format definition to identify field boundaries; Based on the identified field boundaries, the encoded portion corresponding to the encoded key field is separated from the bitstream; Based on the identified field boundaries, a set of plaintext portions corresponding to all plaintext fields is separated from the bitstream; The data set to be verified consists of the encoded part and the plaintext part.

[0011] A further aspect of the present invention generates a trusted data packet, comprising the following steps: Construct a candidate fingerprint set based on a preset range of fingerprint values; Iterate through the candidate fingerprint set and select the current candidate fingerprint in turn; Using the current candidate fingerprint as an index, the corresponding reverse decoding mapping relationship is obtained from the preset mapping table, and the encoded part is decoded to obtain the candidate original key field value; Using the candidate original key field values ​​and the plaintext portion as input, the association calculation function is executed again to calculate the current verification fingerprint; Compare the current verification fingerprint with the current candidate fingerprint. If they match, break out of the loop, confirm that the candidate original key field value is the true original key field value, and use the current candidate fingerprint as the confirmation fingerprint value. The original key field values ​​and the confirmation fingerprint values ​​are encapsulated to generate a trusted data packet.

[0012] A further aspect of the present invention generates an updated trusted data packet, comprising the following steps: When retransmission is required, receive semantic retransmission data containing only the encoded values ​​of the most recently acquired key fields. Read the confirmed fingerprint value from the trusted data packet generated after the most recent successful verification; Using the confirmed fingerprint value as an index, the corresponding reverse decoding mapping relationship is obtained from the preset mapping table, and the semantic retransmission data is decoded to obtain the updated key field content. Perform a business logic compliance check on the updated key field content, including verification of numerical reasonableness. When the check passes, the updated key field content and related information are integrated to generate an updated trusted data packet.

[0013] A further aspect of the present invention includes a business logic compliance check that includes: checking whether the updated key field content is within a preset physical range; and checking whether the numerical change of the updated key field content relative to the semantic content in the trusted data packet at the previous moment is less than a preset numerical change rate threshold.

[0014] Secondly, the present invention provides a wireless communication data storage system, which adopts the following technical solution: A wireless communication data storage system includes the following modules: The structured frame encapsulation module is used to obtain all the original business data to be sent from the sending end and encapsulate it into a structured raw data frame containing multiple predefined data fields. The implicit fingerprint generation module, based on structured raw data frames, generates a verification value, i.e., an implicit integrity fingerprint, which represents the inherent relationship between the data and is calculated based on a predetermined number of selected fields within the frame, through a preset association calculation function. The parameterized encoding module uses the implicit integrity fingerprint as the index parameter to parameterize at least one key data field in the structured original data frame, generating the encoded key field. The composite frame construction and cleanup module is used to combine the encoded key fields with the remaining plaintext fields in the structured original data frame to construct a composite transmission frame that does not contain implicit integrity fingerprints. After sending the composite transmission frame, the structured original data frame and the encoded key fields are cleared from the sender's memory, and the implicit integrity fingerprint is retained in the status register as the historical session state. The receiving and parsing module is used at the receiving end to receive and parse the composite transmission frame, extract the encoded part and plaintext part, and form a set of data to be verified. The verification decoding loop module performs a hypothesis-verification decoding loop based on the dataset to be verified in order to reconstruct and verify the implicit integrity fingerprint, and generates a trusted data packet containing the verified original key field values ​​and the confirmation fingerprint value when the verification is successful. The semantic retransmission processing module initiates a retransmission request to the sender when the composite transmission frame fails to transmit or the verification fails. It also receives semantic retransmission data generated by the sender after encoding the latest key fields based on the implicit integrity fingerprint in the historical session state. The receiver performs targeted decoding and verification of the semantic retransmission data based on the historical context based on the confirmed fingerprint value in the trusted data packet to generate an updated trusted data packet.

[0015] In summary, the present invention has the following beneficial technical effects: 1. By generating an implicit integrity fingerprint from multiple data fields and using this fingerprint as an index to encode key fields, integrity verification information is implicitly embedded in the encoding relationship. The transmission frame does not need to carry an independent checksum or hash value, thereby reducing the number of bits transmitted per frame and helping to improve the effective payload ratio of short data frames and the utilization rate of wireless channels.

[0016] 2. After the composite transmission frame is sent, the original data and intermediate variables at the sending end are cleared. There is no need to cache historical frame data at the sending end for possible retransmission. When retransmission is required, the receiving end can use the successfully verified historical fingerprint value to perform targeted decoding of the simplified retransmission data. This mechanism frees the sending end from dependence on the retransmission buffer, reduces the occupation of device memory resources, and helps to improve the operational stability of resource-constrained devices.

[0017] 3. The receiver recovers data and completes integrity verification by traversing and verifying possible fingerprint values ​​without the need for additional coordination from the sender. In the event of an error, only a simplified encoded data needs to be retransmitted. The receiver can then quickly recover and verify the data by combining the historical context. While ensuring data reliability, this reduces data traffic and communication time during retransmission, thereby helping to reduce the wireless communication power consumption of sensor nodes and extend their working time. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. The drawings are used to provide a further understanding of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating an embodiment of this application is disclosed.

[0020] Figure 2 Structural schematic diagrams of embodiments of this application are disclosed. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, not all embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] The following is in conjunction with the appendix Figure 1 - Figure 2 A preferred description of the present invention is provided below.

[0023] See attached document Figure 1 This invention proposes a wireless communication data storage method, comprising the following steps: S1. The sending end obtains all the original business data to be sent and encapsulates it into a structured raw data frame containing multiple predefined data fields. S2. Based on the structured original data frame, a verification value is generated through a preset association calculation function, which represents the inherent relationship of the data and is calculated based on a predetermined number of selected field data within the frame. This is the implicit integrity fingerprint. S3. Using the implicit integrity fingerprint as the index parameter, parameterize and encode at least one key data field in the structured original data frame to generate the encoded key field. S4. Combine the encoded key field with the remaining plaintext fields in the structured original data frame to construct a composite transmission frame that does not contain the implicit integrity fingerprint. After sending the composite transmission frame, clear the structured original data frame and the encoded key field from the sender's memory and retain the implicit integrity fingerprint in the status register as the historical session state. S5. At the receiving end, receive and parse the composite transmission frame, extract the encoded part and plaintext part to form a set of data to be verified. S6. Based on the dataset to be verified, execute a hypothesis-verification decoding loop to reconstruct and verify the implicit integrity fingerprint, and generate a trusted data packet containing the verified original key field values ​​and the confirmation fingerprint value when the verification is successful. S7. When the composite transmission frame fails to transmit or the verification fails, the receiver initiates a retransmission request to the sender and receives semantic retransmission data generated by the sender after encoding the latest key fields based on the implicit integrity fingerprint in the historical session state. The receiver performs targeted decoding and verification based on the historical context on the semantic retransmission data based on the confirmed fingerprint value in the trusted data packet to generate an updated trusted data packet.

[0024] In one embodiment of the present invention, step S1 includes the following steps: Collect or generate raw business data, which includes the device's unique identifier, data generation time information, and at least one sensor measurement value; according to the fixed format defined by the communication protocol, fill each part of the raw business data into the corresponding field positions in sequence; generate a byte sequence as a structured raw data frame, wherein the order of each field and the bit length in the byte sequence are fixed.

[0025] Specifically, at the transmitting device, the operator or automatic control system first acquires all the service data that needs to be transmitted. Service data refers to a collection of discrete information units that need to be transmitted over the network. This data originates from sensor measurements or system-generated numerical or character data, such as device address, timestamp, temperature value, and humidity value. This data comes from sensor modules or internal business logic units connected to the transmitting device, such as real-time temperature readings from temperature sensors, real-time humidity readings from humidity sensors, device address codes read from the device's unique identifier memory, and data generation time information obtained from the system clock. These discrete values ​​are collected and temporarily stored to form the service data set to be transmitted.

[0026] Subsequently, the operator or equipment firmware performs further processing according to the predefined communication protocol specifications stored in the device's memory. This communication protocol specification clearly defines the fixed format of the structured raw data frame, including the total frame length, the order of each data field, the number of bytes occupied by each field, and the data type of the field. Based on this format, the system sequentially fills each data item in the business data set into its corresponding field position in the structured raw data frame template. For example, the device address code is filled into the initial address field, the timestamp into the immediately following time field, and the temperature and humidity values ​​into the subsequent data fields. After all fields are filled, a complete byte sequence containing all predefined data fields and their corresponding business values ​​is generated. This byte sequence is the structured raw data frame, which can be directly handed over to the subsequent communication module for transmission and processing. The structured raw data frame is a complete data block organized according to a fixed format, containing all predefined fields and their specific business values, and it has a unified and parsable byte stream structure.

[0027] The device address is a unique identifier for the sending device within the network. Its data structure is typically a fixed-length byte array, usually a hardware identifier assigned during device manufacturing or a logical address configured during network deployment. The timestamp identifies the moment business data is generated or collected, and its data structure is the number of seconds or milliseconds calculated from a given epoch. The temperature value is a physical quantity representing the degree of hotness or coldness of an environment or object; its data structure is an integer or floating-point number, set based on the analog-to-digital conversion measurement results from the connected temperature sensor. The humidity value is a physical quantity representing the water vapor content in the air; its data structure is an integer or floating-point number, and it is the analog-to-digital conversion measurement result from the connected humidity sensor.

[0028] For example, assuming the sending end is a temperature and humidity sensor node, the service data it collects includes: a device address of hexadecimal value 0x1A2B, a timestamp of Unix timestamp 1731234567, a temperature sensor reading of 25, and a humidity sensor reading of 60. According to a predefined communication protocol, the structured raw data frame contains four fields: a 2-byte device address field, a 4-byte timestamp field, a 1-byte temperature value field, and a 1-byte humidity value field. The operation process is as follows: the device address 0x1A2B is converted to a 2-byte sequence [0x1A, 0x2B] and filled into the beginning of the frame; the timestamp 1731234567 is converted to a 4-byte sequence [0x67, 0x28, 0xB9, 0x60] and filled into subsequent positions; the temperature value 25 is converted to a 1-byte 0x19 and filled into the next position; and the humidity value 60 is converted to a 1-byte 0x3C and filled into the last position. The final generated structured raw data frame is a byte sequence [0x1A, 0x2B, 0x67, 0x28, 0xB9, 0x60, 0x19, 0x3C]. This example directly verifies the process of generating a structured raw data frame from specific business data, where characteristic terms such as device address, timestamp, temperature value, and humidity value are filled into the specified field positions according to the fixed format of the communication protocol.

[0029] In one embodiment of the present invention, step S2 includes the following steps: Call a preset association calculation function that takes the values ​​of multiple data fields as input and outputs a single value; extract a preset number of values ​​of selected fields from the structured raw data frame; perform weighted and summation operations on the values ​​of the selected fields according to the association calculation function; divide the result of the summation operation by a preset modulus and take the remainder to obtain the implicit integrity fingerprint.

[0030] After generating the structured raw data frame, the sending device performs the implicit integrity fingerprint calculation operation. Specifically, the operator or device firmware first calls the predefined and stored association calculation function from the program memory for subsequent calculation processing. The association calculation function is a mathematical operation rule that takes multiple data field values ​​as input and outputs a single fingerprint value to realize the mapping from multiple variables to a single variable. It is used to condense the internal correlation of the frame data into a short identifier. This association calculation function is a calculation method that is agreed upon and used by the sending end and the receiving end before communication.

[0031] The system extracts the values ​​of one or more pre-defined data fields from the structured raw data frame as input parameters for the correlation calculation function. These selected fields are pre-defined statically by the communication protocol, such as always selecting the "device address field" and "timestamp field"; or they are selected according to dynamic rules, such as selecting the "temperature value field" in a temperature data frame and the "humidity value field" in a humidity data frame. The selection rules must be configured synchronously during the initialization of both communicating parties. These selected input fields can cover all fields in the frame, or a subset thereof, such as a combination of the device address, timestamp, and temperature value fields. Next, the system executes the correlation calculation function, which processes the received values ​​of multiple input fields according to its built-in computational logic. The processing includes, but is not limited to, assigning preset weight coefficients to the values ​​of different fields and then performing a weighted summation, or performing a modulo operation on the weighted summation result to map it to a specific range, or performing a cyclic redundancy check operation. Through these operations, the values ​​of multiple input fields are merged, calculated, and finally output as a single, fixed-length value. This unique output value represents the inherent, non-explicit relationship between the values ​​of each field within that specific structured raw data frame, and is known as the implicit integrity fingerprint.

[0032] Implicit integrity fingerprint It is calculated using the following formula: ; in, This represents the calculated implicit integrity fingerprint, which is an integer. Indicates the first The weight coefficients of each field are set according to the communication protocol and are used to adjust the strength of the contribution of different fields to the fingerprint. They are usually integers. Represents the first extracted from the structured raw data frame. The original value of a specific field; mod represents the modulo operator; The modulus is a positive integer, and its value is set based on the expected range of fingerprint values, for example... =256 allows F to take values ​​between 0 and 255. The formula means: multiply each input field value by its corresponding weight, sum the results, and then divide the sum by the modulus. Taking the remainder, the implicit integrity fingerprint is finally obtained. .

[0033] The implicit integrity fingerprint is a short, fixed-length numerical value representing the inherent uniqueness of the data in a frame, obtained by performing an association calculation function on specific data fields. It is strongly correlated with the input data. Data fields are data units with independent meaning within the structured raw data frame; here, it specifically refers to those fields selected as input to the association calculation function, which have numerical values. Cyclic Redundancy Check (CRC) is an algorithm that generates short check values ​​by performing a specific polynomial division operation on the data block. CRC is a well-known verification algorithm in the art, which generates a fixed-length check code by performing modulo-2 division on the data using a generator polynomial. In this invention, CRC can be used as an implementation of the association calculation function to generate the implicit integrity fingerprint.

[0034] For example, based on the generated structured raw data frame containing the fields: device address 0x1A2B, timestamp 1731234567, and temperature value 25. The preset association calculation function is: F = (device address + timestamp + 2 × temperature value) mod 256, where the weight coefficient of the temperature value is set to 2, and the modulus M is 256. The operation process is as follows: extract the field values: device address converted to decimal V1 = 6699, timestamp V2 = 1731234567, and temperature value V3 = 25. Substitute them into the formula to calculate: weighted sum = 6699 + 1731234567 + 2 × 25 = 6699 + 1731234567 + 50 = 1731241316. Modulo operation: 1731241316 mod 256 = 36. The final calculated implicit integrity fingerprint F = 36. This example directly verifies how the association calculation function combines the values ​​of multiple data fields such as device address, timestamp, and temperature value through weighted and modulo operations to generate a unique implicit integrity fingerprint value 36.

[0035] It should be noted that the above-described correlation calculation function is merely an example. In other embodiments of the present invention, the correlation calculation function may also employ an algorithm such as Cyclic Redundancy Check (CRC). Specifically, the values ​​of multiple selected fields can be concatenated into a byte sequence, and a CRC operation can be performed on the byte sequence. The resulting CRC checksum is used as an implicit integrity fingerprint. The polynomial of the CRC algorithm (such as CRC-8 or CRC-16) needs to be pre-defined in the communication protocol.

[0036] In one embodiment of the present invention, step S3 includes the following steps: The implicit integrity fingerprint value is used as the query index; the query index is used to find and select a unique encoding mapping relationship from the pre-set multi-rule encoding mapping table, where the multi-rule encoding mapping table stores the correspondence between multiple index values ​​and encoding mapping relationships; the selected encoding mapping relationship is applied to transform the original value of the key data field; the encoded key field is generated based on the value obtained from the transformation process.

[0037] After generating the implicit integrity fingerprint, the sending device performs parameterized encoding of key fields in the structured raw data frame. Specifically, the operator or device firmware first uses the obtained implicit integrity fingerprint value as a dynamic index parameter. A multi-rule encoding mapping table is pre-installed in the system and stored in the device's non-volatile memory. This table contains multiple different encoding mapping rules, which are pre-generated and burned into both communicating devices before system deployment. Each encoding mapping relationship defines a specific mathematical transformation rule for mapping the original value of a key data field to an encoded value. For example, a linear transformation encoded value = (a × original value + b) mod M, where parameters a, b, and M vary with the index value; or a non-linear replacement rule based on a lookup table. The purpose is that even if an eavesdropper intercepts the encoded key field, it will be difficult to reconstruct the original value without knowing the current mapping relationship, thus improving data confidentiality while saving bandwidth. For example, assuming the key field is a temperature value (range 0-100), M = 256. The mapping table can be designed such that when the index value is k, the encoding rule is... Since the temperature range (0-100) is much smaller than the modulus space (256), this additive offset mapping is injective within its domain, meaning that no two different valid temperature values ​​can be mapped to the same encoded value. At the receiving end, reverse decoding is performed using the known fingerprint k. If the solved value falls within a reasonable range of 0-100, it is considered a valid candidate value. This combination of domain restriction and mathematical injective testing ensures the uniqueness of the reverse decoding.

[0038] Based on the values ​​of the dynamic index parameters, a unique encoding mapping relationship is selected from the multi-rule encoding mapping table through a lookup operation. This selected encoding mapping relationship defines how to transform one or more pre-designated key data fields into new values. Key data fields are one or more data fields selected in the structured raw data frame that need to be parameterized and encoded. They are of great importance to the business, such as temperature values ​​and control command codes. Their selection is based on the specific requirements of data simplification or security in the application scenario.

[0039] Subsequently, the original values ​​of the selected key data fields, such as temperature values, are extracted from the structured raw data frame. Finally, the selected encoding mapping relationship is applied to perform a transformation operation on the original value of the key data field. The goal of the transformation operation is to generate a new value that is shorter in data length or different in numerical expression from the original value. This new value is the encoded key field, which is the result of transforming the original value of the key data field through the selected encoding mapping relationship, resulting in a shortened data length or a changed numerical expression.

[0040] It should be noted that the multi-rule encoding mapping table is a predefined and stored collection containing multiple independent encoding rules. Each rule can be retrieved through a unique index value, providing various schemes for mapping raw values ​​to encoded values. Specifically, the multi-rule encoding mapping table stores multiple reversible encoding mapping relationships, each mapping relationship uniquely mapping the raw value of one or more key data fields to an encoded value. For example, a series of different linear or nonlinear transformation algorithms can be pre-defined, each algorithm corresponding to a unique index value. In this invention, the core application logic is as follows: after generating the implicit integrity fingerprint F, the sending end uses the value of F as a query index to select the unique encoding mapping relationship corresponding to F from the mapping table. Subsequently, this selected relationship is applied to encode the key fields. When decoding, the receiving end, whether by traversing the candidate fingerprint set or directly using the confirmed fingerprint value, uses the fingerprint value as an index to select the corresponding reverse decoding mapping relationship from the same mapping table as the sending end, thereby completing the data recovery. The specific content of the mapping table, that is, the correspondence between index values ​​and mapping relationships, is pre-defined and kept synchronized by both communicating parties according to the protocol before system deployment. For example, in resource-constrained scenarios, instead of storing the complete table, the index value F is used as a random seed. A pre-defined and identical deterministic algorithm, such as a pseudo-random number generation algorithm, is used to calculate in real-time the parameters of the mapping relationship used for this encoding and decoding, such as a specific offset or coefficient. This implementation achieves the "dynamic encoding using fingerprints as indexes" function while avoiding the storage of a large static table on the device, further saving storage resources.

[0041] For example, based on the previously generated implicit integrity fingerprint F=36, and possessing a structured raw data frame containing device address 0x1A2B, timestamp 1731234567, temperature value 25, and humidity value 60, the preset key data field is the temperature value. Assume a pre-defined multi-rule encoding mapping table contains 256 rules, distinguished by index values ​​0-255. For example, when the index is 36, the corresponding encoding mapping relationship is: divide the original temperature value by 2 and round down. The operation process is as follows: using fingerprint value 36 as a dynamic index, the table is consulted to select encoding mapping relationship number 36. The original value of the key data field, temperature 25, is extracted. Applying the selected mapping relationship: 25 / 2=12.5, rounded down to 12. The final generated encoded key field value is 12. This example demonstrates how, using implicit integrity fingerprint 36 as a dynamic index, a unique encoding mapping relationship is selected from the multi-rule encoding mapping table, and the original value of the key data field, temperature 25, is converted into the encoded key field value 12 through this relationship.

[0042] In one embodiment of the present invention, step S4 includes the following steps: Extract all fields except key data fields from the structured raw data frame as plaintext fields; arrange and combine the encoded key fields with all plaintext fields according to the agreed final frame format; assemble the combined fields into a complete composite transmission frame; after the composite transmission frame is sent, perform an irreversible memory release operation to clear the structured raw data frame and the encoded key fields, and retain the implicit integrity fingerprint in the status register as storage space occupied by the historical session state.

[0043] After generating the encoded key fields, the sending device performs composite transmission frame construction and memory cleanup operations. Specifically, the operator or device firmware first parses the structured raw data frame, identifying all data fields that have not been encoded. These unencoded data fields retain their original numerical form and are collectively referred to as plaintext fields, such as the device address field and the timestamp field. The system then extracts these plaintext fields completely from the structured raw data frame.

[0044] Subsequently, the system arranges and combines the generated encoded key fields with all extracted plaintext fields in a pre-defined final frame format according to the communication protocol. This agreed-upon frame format explicitly specifies the exact position and order of the encoded key fields and each plaintext field in the bitstream to be transmitted. After the arrangement and combination are completed, the system splices and assembles the data contents of these fields into a complete bitstream data block to be transmitted; this data block is the composite transmission frame. The payload of the composite transmission frame contains only the encoded key fields and plaintext fields, and does not include the value of the implicit integrity fingerprint itself.

[0045] At or after the composite transmission frame is assembled and ready to be sent by the underlying wireless communication module, a memory cleanup operation is performed. This operation removes or releases all storage space occupied by the structured original data frame, implicit integrity fingerprint, and encoded key fields used for temporary storage from the memory of the transmitting device. This ensures that the transmitting end does not retain this intermediate data after the frame is sent. The memory cleanup is an operation performed by the transmitting end immediately after the composite transmission frame is assembled, whereby the memory space occupied by the structured original data frame, implicit integrity fingerprint, and encoded key fields is deleted. It is usually performed instantaneously and irreversibly, and is used to achieve storage-free operation of the transmitting end.

[0046] It should be noted that plaintext fields are the set of data fields in the original structured data frame that have not been encoded and are transmitted in their original numerical form. Their data content has not been converted and is visible to the outside world. Composite transmission frames are data blocks used for actual wireless channel transmission, assembled from encoded key fields and all plaintext fields according to the final frame format. They do not contain implicit integrity fingerprints. The final frame format is the final agreement in the communication protocol on the field arrangement order and structure of composite transmission frames, which specifies the organization method of the encoded part and the plaintext part.

[0047] For example, an encoded key field value of 12 has been generated, and the original structured raw data frame contains the following fields: device address 0x1A2B, timestamp 1731234567, temperature value 25, and humidity value 60. The temperature value, a key data field, has been encoded, so the plaintext fields are the device address, timestamp, and humidity value. Assume the agreed-upon final frame format is: the first 2 bytes are the device address, followed by 4 bytes for the timestamp, then 1 byte for the encoded key field, and finally 1 byte for the humidity value. Next, the plaintext fields are extracted: device address 0x1A2B, timestamp 1731234567, and humidity value 60. Arranged according to the final frame format: bytes 1-2 are filled with the device address 0x1A2B, bytes 3-6 with the timestamp 1731234567, byte 7 with the encoded key field 12, and byte 8 with the humidity value 60. The byte sequence of the assembled composite transmission frame is [0x1A, 0x2B, 0x67, 0x28, 0xB9, 0x60, 0x0C, 0x3C]. After the frame is assembled, the system removes all intermediate data from memory, including the original temperature value 25, the implicit integrity fingerprint 36, and the encoded key field value 12.

[0048] In one embodiment of the present invention, step S5 includes the following steps: Receive the bit stream transmitted via the wireless channel; parse the bit stream according to the predefined frame format definition to identify field boundaries; based on the identified field boundaries, separate the encoded portion corresponding to the encoded key field from the bit stream; based on the identified field boundaries, separate the set of plaintext portions corresponding to all plaintext fields from the bit stream; the encoded portion and the plaintext portion together constitute the data set to be verified.

[0049] After the transmitting end sends a composite transmission frame, the receiving end device performs the reception and parsing operations on that frame. Specifically, the receiving end's wireless communication module captures electromagnetic wave signals from the wireless channel and demodulates and converts them into raw bit stream data. The operator or the receiving end firmware then parses the received bit stream according to the predefined frame format definition in the communication protocol, which is consistent with the final frame format of the transmitting end. The predefined frame format definition clearly specifies the start position, length, and data type of each field in the composite transmission frame.

[0050] Based on this definition, the system accurately identifies and separates two main parts from the bit stream: the first part is the encoded part, which represents the key fields after encoding. The encoded part is the binary data segment separated from the parsed bit stream, corresponding to the key fields encoded by the sending end. Its position and length are specified by the format definition. The second part is the plaintext part, which represents all the original data fields that have not been encoded. The number, order and length of the fields it contains are also determined by the format definition.

[0051] After parsing, the system will organize the extracted encoded and plaintext data into a logical data set, which is the data set to be verified. The data set to be verified is a data set composed of the encoded and plaintext parts parsed from the composite transmission frame by the receiving end, and it contains all the information required for subsequent verification and decoding.

[0052] In this context, the bitstream is a sequence of binary bits obtained after demodulation by the wireless communication module. The frame format definition is a precise description of the binary structure of a composite transmission frame in a communication protocol. The receiving end segments and interprets the bitstream according to this definition; the binary structure includes field boundaries and types. The plaintext portion is a set of binary data segments separated from the parsed bitstream, corresponding to all plaintext fields from the sending end.

[0053] For example, the byte sequence of the composite transmission frame sent by the transmitting end is [0x1A, 0x2B, 0x67, 0x28, 0xB9, 0x60, 0x0C, 0x3C]. The receiving end wireless module receives the bit stream corresponding to this frame. According to the pre-agreed frame format definition, the first 2 bytes are the device address, the next 4 bytes are the timestamp, then 1 byte is the encoded key field, and the last 1 byte is the humidity value; The receiving end parses the bit stream as follows: from the first 2 bytes, it parses the plaintext field of the device address 0x1A2B; from the next 4 bytes, it parses the plaintext field of the timestamp 1731234567; from the 7th byte, it parses the encoded part 0x0C (corresponding to decimal 12); and from the 8th byte, it parses the plaintext field of the humidity value 0x3C (corresponding to decimal 60).

[0054] After parsing, the system will combine the encoded part and the plaintext part, namely the value 12, the device address 0x1A2B, the timestamp 1731234567, and the humidity value 60, to form the data set to be verified.

[0055] In one embodiment of the present invention, step S6 includes the following steps: Based on the preset fingerprint value range, a candidate fingerprint set is constructed; the candidate fingerprint set is traversed, and the current candidate fingerprint is selected in turn; using the current candidate fingerprint as an index, the corresponding reverse decoding mapping relationship is obtained from the preset mapping table, and the encoded part is decoded to obtain the candidate original key field value; the candidate original key field value and the plaintext part are used as input, and the association calculation function is executed again to calculate the current verification fingerprint; the current verification fingerprint is compared with the current candidate fingerprint. If they match, the loop is exited, the candidate original key field value is confirmed as the real original key field value, and the current candidate fingerprint is used as the confirmation fingerprint value; the real original key field value and the confirmation fingerprint value are encapsulated to generate a trusted data packet.

[0056] After the receiving end generates the data set to be verified, the system initiates a hypothesis-verification decoding loop to recover the original key fields and verify integrity. Specifically, the operator or device firmware first extracts the encoded and plaintext portions from the data set to be verified. Based on predefined parameters shared with the sending end, all possible candidate values ​​for the implicit integrity fingerprint are determined; for example, if the modulus M is 256, the candidate fingerprint values ​​are all integers from 0 to 255.

[0057] Subsequently, each candidate fingerprint value is traversed sequentially. In each loop iteration, the system uses the current candidate fingerprint value as a dynamic index to query the multi-rule encoding mapping table that is the same as that of the sender and is preset in the receiver, thereby selecting the corresponding reverse decoding mapping relationship. The reverse decoding mapping relationship is a rule retrieved from the multi-rule encoding mapping table using the candidate fingerprint as an index, which is used to convert the encoded part back to the original key field value. It is the inverse operation of the encoding mapping relationship.

[0058] The selected reverse decoding mapping is applied to the encoded portion to convert the encoded value back into the candidate's original key field value. This candidate's original key field value is the hypothetical original value of the key field obtained by decoding the encoded portion using the reverse decoding mapping. Then, the system uses this candidate's original key field value, along with other field values ​​extracted from the plaintext portion, as input parameters, and substitutes them into the same association calculation function to perform calculations, obtaining a verification fingerprint value. The verification fingerprint is a new fingerprint value calculated by substituting the candidate's original key field value and the plaintext portion into the association calculation function, used to verify whether the hypothesis of the candidate fingerprint is correct.

[0059] The calculated verification fingerprint value is precisely compared with the candidate fingerprint value used in the current loop iteration. If the two values ​​are equal, the current loop terminates successfully. At this point, the system confirms that the original key field value of the current candidate is the true and valid semantic content, and the candidate fingerprint value currently used is the correct verification fingerprint value. Finally, the system packages the verified original key field value and the verification fingerprint value into a new data structure, generating a trusted data packet. The trusted data packet is a data structure containing the verified and correct semantic content of the original key field value and the verification fingerprint value.

[0060] The hypothesis-verification decoding loop is an iterative process that reconstructs data and verifies integrity by traversing all possible fingerprint candidate values ​​and verifying their consistency. It includes traversal, decoding, verification calculation, and alignment steps. Candidate fingerprints are possible implicit integrity fingerprint values ​​that are hypothesized and tried in the loop, and their range is determined by the modulus M in the association calculation function.

[0061] For example, continuing the example above, the dataset to be verified contains encoded part 12, and plaintext parts: device address 6699, timestamp 1731234567, and humidity value 60. Given that the modulus of the association calculation function is M=256, the candidate fingerprint traversal range is 0 to 255. A loop is started; for example, when attempting a candidate fingerprint value of 36, the receiver's pre-stored multi-rule encoding mapping table is queried using 36 as the index. Assume the selected reverse decoding mapping relationship is "multiply the encoded value by 2". Applying this relationship, encoded part 12 is decoded: 12×2=24, yielding the candidate's original key field value (temperature value) 24. Substituting the candidate temperature value 24, device address 6699, and timestamp 1731234567 into the association calculation function F=(6699+1731234567+2×24) mod256, we calculate F=1731241314 mod 256=2. The verification fingerprint value 2 is not equal to the current candidate fingerprint value 36, the comparison fails, and the loop continues.

[0062] When attempting a candidate fingerprint value of 36, if the actual reverse decoding mapping in the mapping table is "multiply the encoded value by 2 and add 1", then the decoded result is: 12×2+1=25, yielding the candidate temperature value 25. Substituting this into the association calculation function F=(6699+1731234567+2×25) mod 256, we calculate F=1731241316 mod 256=36. The fingerprint value 36 is verified to be equal to the current candidate fingerprint value 36; the comparison is successful, and the loop terminates. The system confirms that the original key field value 25 is valid semantic content and confirms the fingerprint value as 36. Finally, the semantic content 25 and the confirmed fingerprint value 36 are encapsulated to generate a trusted data packet.

[0063] In one embodiment of the present invention, the operation of the sending end responding to the retransmission request between steps S6 and S7 includes the following steps: when the communication module of the sending end receives a retransmission request from the receiving end, the retransmission request indicates that a previously transmitted frame of data was lost or failed to be verified; the sending end does not attempt to recover the old data from the cleared memory, but instead accesses the status register of the sending end to obtain the implicit integrity fingerprint value generated and used when the composite transmission frame was successfully transmitted most recently, which serves as a historical fingerprint value synchronized with the fingerprint value confirmed by the receiving end; the sending end uses the historical fingerprint value as an index parameter to query a preset multi-rule encoding mapping table and selects the corresponding The encoding mapping relationship is used to re-acquire or obtain the original value of the latest key data field at the current moment, such as the latest temperature reading, and apply the selected encoding mapping relationship to parameterize and encode it to generate a retransmission encoding field. The sending end encapsulates the retransmission encoding field into semantic retransmission data including the latest semantic information and sends it to the receiving end through a wireless channel. This mechanism ensures that during the retransmission process, the sending end uses historical fingerprints to maintain the synchronization of the communication context and transmits the latest data to make up for the time lag, thereby solving the problem that traditional retransmission cannot be performed after the memory data is cleared, and realizing the latest data update based on the historical reliable state.

[0064] In one embodiment of the present invention, step S7 includes the following steps: When retransmission is required, the system receives semantic retransmission data containing only the most recently acquired key field encoded values; it reads the confirmed fingerprint value from the trusted data packet generated after the most recent successful verification; using the confirmed fingerprint value as an index, it retrieves the corresponding reverse decoding mapping relationship from a pre-set mapping table and decodes the semantic retransmission data to obtain the updated key field content; it performs a business logic compliance check on the updated key field content, including numerical reasonableness verification; when the check passes, it integrates the updated key field content with relevant information to generate an updated trusted data packet.

[0065] After generating a trusted data packet, if subsequent composite transmission frames are lost or verification fails, the receiving device performs targeted decoding and verification operations based on historical context. Specifically, when the receiving end detects data loss or verification failure, it initiates a retransmission request to the sending end. Subsequently, the receiving end receives semantic retransmission data sent back by the sending end in response to this request. This data only contains the latest key field encoded values ​​and does not contain the complete frame structure or other plaintext fields. Semantic retransmission data consists of concise data units, including only the latest key field encoded values, that are retransmitted by the sender after the receiver requests retransmission. These data units are small in size and rely on historical context for parsing. The latest key field encoded values ​​are the key field values ​​carried in the semantic retransmission data and re-encoded by the sender. Historical context refers to the state information acquired and saved by the receiver during previous successful communication cycles; in this step, it specifically refers to the confirmation fingerprint value stored in the trusted data packet. Directed decoding directly uses the known confirmation fingerprint value as a parameter to perform a one-time decoding operation on the semantic retransmission data. This decoding process is deterministic and efficient, requiring no traversal or guessing.

[0066] The operator or device firmware directly reads the confirmed fingerprint value from the trusted data packet generated after successful verification, stored locally. This confirmed fingerprint value is used as a unique and definitive decoding parameter, eliminating the need for a loop that iterates through all possible fingerprints.

[0067] Next, using the confirmation fingerprint value as an index, the system queries a multi-rule encoding mapping table pre-set at the receiving end that matches the sending end, thereby selecting a unique reverse decoding mapping relationship. Then, the system applies this selected reverse decoding mapping relationship to perform a one-time decoding operation on the latest key field encoding value in the newly received semantic retransmission data, recovering the updated key field semantic content.

[0068] After successful decoding, the system performs a business logic compliance check on the recovered updated semantic content. The business logic compliance check includes: Range check: Determines whether the updated key field content is within the reasonable range preset by the sensor for that physical quantity. For example, for a temperature sensor, its range is -10℃ to 50℃. This range is determined according to the sensor hardware specifications. Numerical change rate threshold check: Calculate the absolute value of the difference between the updated key field content and the semantic content in the trusted data packet at the previous moment, and determine whether this difference is less than a preset physical numerical change rate threshold. For example, for ambient temperature, its change rate is usually slow, and the numerical change rate threshold can be set to 5℃ / s. This threshold is determined through experimental statistics based on the physical laws of the application scenario and the sampling frequency. If the updated content passes both of the above checks, it is determined to conform to the business logic; Specifically, for example, the system determines whether the value is within the sensor's possible measurement range, or whether the change in value compared to the previous data conforms to physical laws. If this content passes the business logic check, the system determines that the integrity verification of the retransmitted data was successful. Finally, the system integrates the updated semantic content of the key fields with other necessary information obtained from trusted data packets or calculated based on the new context to generate an updated trusted data packet for subsequent data processing or possible further retransmission.

[0069] The business logic involves performing reasonableness checks on the decoded and recovered data, such as numerical range and continuity of change. These checks are based on the physical constraints or business rules of the specific application scenario. The updated trusted data packet is a trusted data packet that integrates the latest semantic content recovered from the semantic retransmission data.

[0070] For example, continuing from the previous example, the receiving end already holds a trusted data packet containing an acknowledgment fingerprint value 36 and a verified semantic content temperature value 25. Assuming that due to channel interference, the receiving end does not receive the next frame of data or the verification fails, it requests a retransmission. Upon receiving the retransmission request, the sending end retrieves the fingerprint value 36 used in the most recent transmission from its internal state as the historical fingerprint value. Using fingerprint value 36 as an index, the sending end queries a multi-rule encoding mapping table and selects the corresponding encoding mapping relationship, such as "subtract 1 from the original value and divide by 2". The sending end reads the latest temperature sensor reading 29 and applies this mapping relationship for encoding: (29-1) / 2 = 14, generating a retransmission encoding value 14. The sending end sends the encoding value 14 as semantic retransmission data. Subsequently, the receiving end receives the semantic retransmission data sent by the sending end, which only contains the latest key field encoding value 14. The operation process is as follows: the system reads the acknowledgment fingerprint value 36 from the trusted data packet. Using 36 as the index, query the multi-rule encoding mapping table pre-stored at the receiving end, select the corresponding reverse decoding mapping relationship, such as "multiply the encoded value by 2 and then add 1". Apply this relationship to decode the latest encoded value 14: 14×2+1=29, and obtain the updated key field semantic content temperature value 29.

[0071] Next, a business logic check is performed to confirm that the temperature value 29 is within the sensor's range of 0-50 degrees Celsius, and that the change from the previous value 25 is within a reasonable range; the verification passes. Finally, the system integrates the updated temperature value 29 with the original confirmation fingerprint value 36 and other information to generate an updated trusted data packet.

[0072] See appendix Figure 2 The present invention also proposes a wireless communication data storage system, comprising the following modules: The structured frame encapsulation module is used to obtain all the original business data to be sent from the sending end and encapsulate it into a structured raw data frame containing multiple predefined data fields. The implicit fingerprint generation module, based on structured raw data frames, generates a verification value, i.e., an implicit integrity fingerprint, which represents the inherent relationship between the data and is calculated based on a predetermined number of selected fields within the frame, through a preset association calculation function. The parameterized encoding module uses the implicit integrity fingerprint as the index parameter to parameterize at least one key data field in the structured original data frame, generating the encoded key field. The composite frame construction and cleanup module is used to combine the encoded key fields with the remaining plaintext fields in the structured original data frame to construct a composite transmission frame that does not contain implicit integrity fingerprints. After sending the composite transmission frame, the structured original data frame and the encoded key fields are cleared from the sender's memory, and the implicit integrity fingerprint is retained in the status register as the historical session state. The receiving and parsing module is used at the receiving end to receive and parse the composite transmission frame, extract the encoded part and plaintext part, and form a set of data to be verified. The verification decoding loop module performs a hypothesis-verification decoding loop based on the dataset to be verified in order to reconstruct and verify the implicit integrity fingerprint, and generates a trusted data packet containing the verified original key field values ​​and the confirmation fingerprint value when the verification is successful. The semantic retransmission processing module initiates a retransmission request to the sender when the composite transmission frame fails to transmit or the verification fails. It also receives semantic retransmission data generated by the sender after encoding the latest key fields based on the implicit integrity fingerprint in the historical session state. The receiver performs targeted decoding and verification of the semantic retransmission data based on the historical context based on the confirmed fingerprint value in the trusted data packet to generate an updated trusted data packet.

[0073] It should be noted that the formulas presented above, through the principle of dimensional consistency and mathematical standardization methods (such as normalization, dimensionless parameter conversion, or unit system unification), can translate physical quantities with different attributes into unitless standard values ​​or parameters that can be superimposed within the same dimension. This eliminates the interference of different dimensions on the computational logic, ensuring that the formulas retain the original data distribution characteristics while possessing mathematical rationality and adaptability to objective laws. Alternatively, in actual calculations, the numerical values ​​of different physical quantity fields (e.g., temperature value 25, humidity value 60, timestamp value, etc.) can be directly taken for calculation, ignoring their physical dimensions, thereby ensuring the feasibility of the mathematical operations. The aforementioned correlation calculation function aims to establish mathematical correlations between data, rather than the consistency of physical dimensions.

[0074] Each of the modules can be implemented in whole or in part through software, hardware, or a combination thereof. It supports hardware embedded in or independent of the processor in the computer device, and also supports software stored in the memory of the computer device, so that the processor can call and execute the operations corresponding to each of the above modules.

[0075] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for storing data for wireless communication, characterized by, The method comprises the following steps: S1, the sending end acquires all the original service data to be sent, and encapsulates the original service data into a structured original data frame containing multiple predefined data fields; S2, based on the structured original data frame, a check value representing the internal correlation of the data is generated by a preset correlation calculation function, that is, an implicit integrity fingerprint calculated based on a predetermined number of selected field data in the frame; S3, using the implicit integrity fingerprint as an index parameter, at least one key data field in the structured original data frame is parameterized and encoded to generate an encoded key field; S4, the encoded key field and the remaining plaintext field in the structured original data frame are combined to construct a composite transmission frame which does not contain the implicit integrity fingerprint, and after sending the composite transmission frame, the structured original data frame and the encoded key field are cleared from the memory of the sending end, and the implicit integrity fingerprint is retained in the state register as a historical session state; S5, at the receiving end, the composite transmission frame is received and parsed, the encoded part and the plaintext part are extracted to form a to-be-verified data set; S6, based on the to-be-verified data set, a hypothesis-verification decoding loop is executed to reconstruct and verify the implicit integrity fingerprint, and when the verification is successful, a trusted data packet containing the verified original key field value and the confirmation fingerprint value is generated; S7, when the composite transmission frame transmission fails or the verification fails, the receiving end initiates a retransmission request to the sending end, and receives the semantic retransmission data generated by the sending end based on the implicit integrity fingerprint in the historical session state to encode the latest collected key field, and the receiving end performs directional decoding and verification based on the historical context based on the confirmed fingerprint value in the trusted data packet to generate an updated trusted data packet.

2. The method of claim 1, wherein, The structured original data frame is generated, comprising the following steps: Collect or generate original service data, which includes device unique identification information, data generation time information, and at least one sensor measurement value; According to the fixed format defined by the communication protocol, each part of the original service data is sequentially filled into the corresponding field position; A byte sequence is generated as the structured original data frame, wherein the arrangement order and bit length of each field in the byte sequence are fixed.

3. The method of claim 1, wherein, The implicit integrity fingerprint is obtained, comprising the following steps: A preset correlation calculation function is called, which takes the values of multiple data fields as input and outputs a single value; The values of the preset number of selected fields are extracted from the structured original data frame; The values of the selected fields are subjected to weighted operation and summation operation according to the correlation calculation function; The result of the summation operation is divided by a preset modulus, and the remainder is taken to obtain the implicit integrity fingerprint.

4. The method of claim 1, wherein, The encoded key field is generated, comprising the following steps: The value of the implicit integrity fingerprint is used as a query index; A unique encoding mapping relationship is selected from the pre-stored multi-rule encoding mapping table using the query index, wherein the multi-rule encoding mapping table stores the correspondence between multiple index values and encoding mapping relationships; The original value of the key data field is converted by applying the selected encoding mapping relationship; The encoded key field is generated based on the value obtained by the conversion processing.

5. The method of claim 1, wherein, Step S4 comprises the following steps: extracting all fields except the key data field from the structured raw data frame as plaintext fields; arranging and combining the encoded key field and all plaintext fields according to the agreed final frame format; splicing and assembling the combined fields into a complete composite transmission frame; after sending the composite transmission frame, performing an irreversible memory release operation to clear the structured raw data frame and the encoded key field, and retaining the implicit integrity fingerprint in the state register as the storage space occupied by the historical session state.

6. The method of claim 1, wherein, comprising the following steps: receiving a bit stream transmitted by a wireless channel; parsing the bit stream according to a predefined frame format definition to identify field boundaries; separating the encoded part corresponding to the encoded key field from the bit stream according to the identified field boundaries; separating the set of plaintext parts corresponding to all plaintext fields from the bit stream according to the identified field boundaries; the set of to-be-verified data is composed of the encoded part and the set of plaintext parts.

7. The method of claim 1, wherein, generating a trusted data packet, comprising the following steps: constructing a candidate fingerprint set according to a preset fingerprint value range; iterating through the candidate fingerprint set to select a current candidate fingerprint; using the current candidate fingerprint as an index, obtaining the corresponding reverse decoding mapping relationship from the preset mapping table, decoding the encoded part to obtain a candidate original key field value; taking the candidate original key field value and the plaintext part as inputs, and performing the association calculation function again to calculate a current verification fingerprint; comparing the current verification fingerprint with the current candidate fingerprint, if they are consistent, then exiting the loop, confirming that the candidate original key field value is the real original key field value, and taking the current candidate fingerprint as a confirmed fingerprint value; encapsulating the real original key field value and the confirmed fingerprint value to generate a trusted data packet.

8. The method of claim 1, wherein, generating an updated trusted data packet, comprising the following steps: when retransmission is needed, receiving semantic retransmission data containing only the latest collected key field encoding value; reading the confirmed fingerprint value from the trusted data packet generated after the last successful verification; using the confirmed fingerprint value as an index, obtaining the corresponding reverse decoding mapping relationship from the preset mapping table, and decoding the semantic retransmission data to obtain the updated key field content; performing a business logic compliance check on the updated key field content, which includes a numerical reasonableness verification; when the check passes, integrating the updated key field content and related information to generate an updated trusted data packet.

9. The method of claim 1, wherein, The business logic compliance check includes: checking whether the updated key field content is within the preset physical range of values; checking whether the numerical change amplitude of the updated key field content relative to the semantic content at the last time in the trusted data packet is less than the preset numerical change rate threshold.

10. A wireless communication data storage system, characterized by comprising the following modules: a structured frame encapsulation module for obtaining all raw service data to be sent from the sending end and encapsulating them into a structured raw data frame containing multiple predefined data fields; The implicit fingerprint generation module generates, based on the structured original data frame, a check value representing the inherent correlation of the data by a preset correlation calculation function, i.e., an implicit integrity fingerprint, which is calculated based on a predetermined number of selected field data in the frame; The parameterized encoding module parameterizes and encodes at least one key data field in the structured original data frame by taking the implicit integrity fingerprint as an index parameter, to generate an encoded key field; The composite frame construction and cleaning module combines the encoded key field with the remaining plaintext field in the structured original data frame, constructs a composite transmission frame that does not contain the implicit integrity fingerprint, and after sending the composite transmission frame, clears the structured original data frame and the encoded key field from the memory of the sending end, and retains the implicit integrity fingerprint in the state register as a historical session state; The receiving and analyzing module receives and analyzes the composite transmission frame at the receiving end, extracts the encoded part and the plaintext part therefrom, and constitutes a to-be-verified data set; The verification and decoding cycle module performs a hypothesis-verification decoding cycle based on the to-be-verified data set, to reconstruct and verify the implicit integrity fingerprint, and generates a trusted data packet containing the verified original key field value and the confirmed fingerprint value when the verification is successful; The semantic retransmission processing module initiates a retransmission request from the receiving end to the sending end when the composite transmission frame fails to be transmitted or fails to be verified, and receives semantic retransmission data generated by the sending end based on the implicit integrity fingerprint in the historical session state to encode the latest collected key field, and performs directional decoding and verification based on the historical context on the semantic retransmission data based on the confirmed fingerprint value in the trusted data packet, to generate an updated trusted data packet.

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