CN114337930A

CN114337930A - Network data prediction method

Info

Publication number: CN114337930A
Application number: CN202210017641.2A
Authority: CN
Inventors: 许兆渊
Original assignee: Realtek Semiconductor Corp
Current assignee: Realtek Semiconductor Corp
Priority date: 2018-02-14
Filing date: 2018-02-14
Publication date: 2022-04-12
Also published as: CN110166166A; CN110166166B

Abstract

The invention discloses a network data prediction method. The network data prediction method is applied to a data processing device of an interconnection model of an actual operation open system, the data processing device is communicated with a target network device of the interconnection model of the actual operation open system, and the network data prediction method comprises the following steps: generating a transmission data according to a communication protocol of a first abstraction layer, wherein the transmission data can be processed by a first peer abstraction layer of the target network device, the first peer abstraction layer corresponding to the first abstraction layer and conforming to the communication protocol; generating a prediction data according to the communication protocol and the transmission data; and transferring the transfer data and the prediction data to a second abstraction layer.

Description

Network data prediction method

The present application is a divisional application of an invention patent application having an application number of 201810151621.8, an application date of 2018, 2/14/h, and an invention name of "network data prediction method, network data processing apparatus, and method".

Technical Field

The present invention relates to the Internet, and more particularly to the Internet of Things (IoT).

Background

When a terminal device of the internet receives data, reception may fail due to insufficient signal strength or poor quality. Different kinds of data reception failures may lead to different consequences. Take narrow-band Internet of Things (NB-IoT) as an example:

(1) when data (e.g., a Narrowband Physical Downlink Shared Channel (NPDSCH) or Downlink Control Information (DCI)) repeatedly transmitted by a receiving base station (eNB) fails, the terminal device must continue to turn on or enable circuits such as a receiver and a decoder, which causes more power consumption of the terminal device;

(2) when receiving data transmitted by the bs in non-repeated manner fails, the ue may need to perform a larger procedure than in case (1), resulting in larger communication delay and larger power consumption. For example, when receiving a System Information Block (SIB) fails, the terminal device waits for a longer period and retries. For another example, when receiving a Transport Block (TB) with user plane data (user plane data) fails, the terminal device needs to wait for a Hybrid Automatic Repeat request (HARQ) retransmission or a Radio Link Control (RLC) retransmission.

In addition to the above-mentioned situation, the communication delay and power consumption of the terminal device may increase, and when the terminal device cannot receive the signal all the time, the terminal device may not complete the task.

Disclosure of Invention

In view of the foregoing, an object of the present invention is to provide a network data prediction method, a network data processing apparatus and a network data processing method, so as to improve the performance of a network termination apparatus.

The invention discloses a network data processing method, which is applied to a device of an Open Systems Interconnection (OSI) model for actual operation, and comprises the following steps: generating a first data block and a second data block according to the open system interconnection model; processing the first data block based on an error detection method to generate a first check code; encoding the first data block and the first check code to generate first network data; transmitting the first network data; receiving second network data, wherein the second network data comprises a second check code; decoding according to a part of the second data block and a part of the second network data to generate target data; and checking the target data according to the second check code.

The invention also discloses a network data processing device, which comprises a data processing circuit, an error detection data generating circuit, an encoding circuit, a data transmitting and receiving circuit and a decoding circuit. The data processing circuit generates a first data block and a second data block according to the open system interconnection model. The error detection data generating circuit is coupled to the data processing circuit and used for processing the first data block based on an error detection method to generate a first check code. The encoding circuit is coupled to the error detection data generating circuit and used for encoding the first data block and the first check code to generate first network data. The data transceiver is coupled to the encoding circuit and used for transmitting the first network data and receiving a second network data, wherein the second network data comprises a second check code. The decoding circuit is coupled to the data processing circuit and the data transceiving circuit, and is configured to generate target data according to a part of the second data block and a part of the second network data by decoding, and check the target data according to the second check code.

The invention also discloses a network data prediction method, which is applied to a device of the interconnection model of the actual operation open system, and the device is communicated with a target network device of the interconnection model of the actual operation open system. The method comprises the following steps: generating a transmission data according to a communication protocol of a first abstraction layer, wherein the transmission data can be processed by a first peer abstraction layer of the target network device, the first peer abstraction layer corresponding to the first abstraction layer and conforming to the communication protocol; generating a prediction data according to the communication protocol and the transmission data; and transferring the transfer data and the prediction data to a second abstraction layer.

The network data prediction method, the network data processing device and the network data processing method of the invention improve the decoding efficiency by predicting the data to be received. Compared with the prior art, the scheme is beneficial to ending the decoding process in advance, so that the network device has lower power consumption and larger receiving range.

The features, practical operation and effects of the present invention will be described in detail with reference to the drawings.

Drawings

FIG. 1 is a functional block diagram of a network data processing apparatus according to an embodiment of the present invention;

FIG. 2 is a flow chart of an embodiment of a network data processing method of the present invention;

FIG. 3 is a functional block diagram of another embodiment of a network data processing apparatus according to the present invention;

FIG. 4 is a flow chart of another embodiment of a network data processing method of the present invention;

FIG. 5 is a schematic diagram of an open systems interconnection model;

FIG. 6 is a flow chart of an embodiment of a method for network data prediction according to the present invention;

fig. 7 is a detailed flow of step S624;

fig. 8 is a data structure of a broadcast packet corresponding to a narrowband master information block of a narrowband internet of things; and

fig. 9 is a detailed flow of step S626.

Detailed Description

In the following description, the technical terms refer to the common terms in the technical field, and some terms are explained or defined in the specification, and the explanation of the some terms is based on the explanation or the definition in the specification.

The disclosure of the present invention includes a network data prediction method, a network data processing apparatus, and a network data processing method. Since some of the components included in the network data processing apparatus of the present invention may be known components alone, the following description will omit details of the known components without affecting the full disclosure and feasibility of the present invention. In addition, part or all of the flow of the network data prediction method and the network data processing method of the present invention may be in the form of software and/or firmware, and the following description of the method invention will focus on the content of steps rather than hardware without affecting the full disclosure and feasibility of the method invention.

Wireless communication devices focus on signal reception range (coverage) and power saving, and if reception capability is improved, may achieve better power saving (e.g., early receiver and/or decoder shutdown or even the entire system) than other devices with the same signal strength and quality, or have a larger reception range (i.e., data reception is successful even in case of poor signal).

Although the channel coding (channel coding) technique employed in the wireless communication system and the decoder used in the terminal device have their theoretical and practical limits, the decoding performance can be effectively improved if a part of the data to be received can be known in advance. Wireless communication applications that are typically intended for human use are not easily predictable because of the diversity of data that is transmitted and received, and the ease with which information pertaining to multiple different applications can be interleaved (e.g., multiple applications on a terminal device are transmitting and receiving data at the same time). However, the content and pattern (pattern) of the information exchange of the internet of things tend to be monotonous (e.g., tracker returns location, electricity meter returns power for a fixed time), which makes the prediction feasible and easy. Based on the predictability of the communication of the internet of things, the invention provides a predictive decoding (predictive decoding) technology capable of predicting part or all data, and the predictive decoding technology is applied to data receiving processing capable of performing error detection (error detection) so as to improve the efficiency of data receiving. The types of error detection include, for example, Cyclic Redundancy Checks (CRC), checksums (checksums), parity bits (parity bits), and/or Error Correction Codes (ECC). For more Error detection information, refer to https:// en. wikipedia. org/wiki/Error _ detection _ and _ correction # Error _ detection _ schemes.

Fig. 1 is a functional block diagram of a network data processing apparatus according to an embodiment of the present invention, and fig. 2 is a flowchart of a network data processing method according to an embodiment of the present invention. Please refer to fig. 1 and fig. 2. The network data processing apparatus 100 includes a data processing circuit 110, an error detection data generating circuit 120, an encoding circuit 130, a data transceiving circuit 140, and a decoding circuit 150. The data processing circuit 110 generates a first data block and a second data block according to the open system interconnection model (step S210). The first data block is data to be transmitted to a target network device, and the second data block is prediction data. The second data block includes at least one predicted bit, and the predicted bit is determined according to the first data block. The data processing circuit 110 also generates auxiliary data (step S215). The auxiliary data indicates whether a bit in the second data block is a predicted bit; in other words, the auxiliary data may indicate the trustworthiness of the bits in the second data block. The details of the data processing circuit 110 to generate the second data block and the auxiliary data will be described later. The error detection data generating circuit 120 processes the first data block based on an error detection method to generate a first check code (step S220). For example, the detection method may be a cyclic redundancy check, and the generated first check code may be used to perform error detection on the first data block. The encoding circuit 130 encodes the first data block and the first check code to generate a first network data (step S225). The data transceiver circuit 140 transmits the first network data to the target network device via the network (step S230). The data transceiver circuit 140 also receives second network data from the target network device, wherein the second network data is a response of the target network device to the first network data, and the second network data includes a second check code (step S235).

The decoding circuit 150 decodes the second data block according to a portion of the second data block and a portion of the second network data to generate a target data (step S240). More specifically, the second data block is a prediction of the second network data by the network data processing apparatus 100, and the higher the accuracy of the prediction, the closer the second data block is to the second network data. The decoding circuit 150 may refer to the second network data to obtain the non-predicted portion of the second data block. For example, the decoding circuit 150 may (1) replace the unpredicted bits of the second data block with corresponding bit values in the second network data; or (2) decoding the second network data and the prediction part in the second data block after mixing. The decoding circuit 150 is mainly composed of a channel decoder capable of receiving soft input (soft input), and may be, for example, an iterative decoder (iterative decoder), but not limited thereto. When the decoding circuit 150 actually operates as an iterative decoder, the second network data is used as the input data, and the second data block is used as the previous decoding result, but only one decoding operation is needed without iteration, and the soft output value is not needed to be generated.

The decoding circuit 150 includes a soft-input channel decoder (soft-input channel encoder)152 and an error detection circuit 154. The soft input channel decoder 152 processes the soft input values, so step S240 includes sub-step S245: the soft input channel decoder 152 converts the plurality of bit values of the second data block into a soft input value according to the auxiliary data before decoding. For example, the auxiliary data may be a mask (mask) having the same number of bits as the second data block, and a logic 0 indicates that the corresponding bit of the second data block is an unpredicted bit, and a logic 1 indicates that the corresponding bit of the second data block is a predicted bit. If the auxiliary data is (1101110) (the third and seventh bits are non-predicted bits, and the rest are predicted bits), and the second data block is (1001100), the soft input channel decoder 152 can obtain the soft input of (+1, -1,0, +1, +1, -1,0) according to the two.

After generating the target data in step S240, the debug circuit 154 examines the target data according to the second check code to generate a check result (step S250). If the prediction of the second data block is correct, the check result should be correct. When the check result is correct (yes in step S255), the decoding circuit 150 transfers the target data to the data processing circuit 110 to perform subsequent processing (step S260). When the check result is not correct (no at step S255), if there are other second data blocks at this time, the decoding circuit 150 attempts to decode the other second data blocks; if there is no other second data block, the decoding circuit 150 decodes the second network data (step S270), and transmits target data obtained by decoding the second network data to the data processing circuit 110 for subsequent processing.

The aforementioned one data block refers to a data unit to which error detection information/data can be added and channel-coded. For the narrow-band internet of things, one data block refers to one transmission block. For the internet of things standard of Long Range Wide Area Network (LoRaWAN), one data block refers to one payload (payload) of a physical layer.

Fig. 3 is a functional block diagram of a network data processing apparatus according to another embodiment of the present invention, and fig. 4 is a flowchart of a network data processing method according to another embodiment of the present invention. Please refer to fig. 3 and fig. 4. The network data processing apparatus 200 includes a data processing circuit 110, an error detection data generating circuit 120, an encoding circuit 130, a data transceiving circuit 140, and a decoding circuit 160. The data processing circuit 110, the error detection data generating circuit 120, the encoding circuit 130, the data transmitting and receiving circuit 140 in fig. 3 and steps S210 to S235 in fig. 4 have been described, and are not repeated. The decoding circuit 160 is mainly composed of a channel decoder capable of receiving a soft input, such as an iterative decoder, but not limited thereto.

The decoding circuit 160 includes a soft input channel decoder 162, a soft input channel decoder 164, and an error detection circuit 166. The soft input channel decoder 162 performs steps S410 and S415 to generate the first target data. Steps S410 and S415 are similar to steps S240 and S245, respectively, and thus are not described again. Then, the debug circuit 166 examines the first target data according to the second check code to generate a first examining result (step S420). The soft input channel decoder 164 decodes the second network data to generate a second target data (step S430), and the error detection circuit 166 checks the second target data according to the second check code to generate a second check result (step S440).

In the embodiment shown in FIG. 4, the soft input channel decoder 162 and the soft input channel decoder 164 are processed in parallel, i.e., step S410 (including substep S415) and step S430 may be performed simultaneously. When one of the soft input channel decoder 162 and the soft input channel decoder 164 fails to decode or is incorrect, the target data generated by the other one can be used as a backup, so as to increase the processing speed of the network data processing apparatus 200. However, in various embodiments, the soft input channel decoder 164 selectively performs the step S430 according to the first check result. More specifically, when the first check result is incorrect, the debug circuit 166 instructs the soft input channel decoder 164 to execute step S430 with the control signal Ctrl; when the first check result is correct, the soft input channel decoder 164 does not perform step S430.

Next, the debug circuit 166 determines whether the first or second check result is correct (step S450). When the first check result is correct, the debug circuit 166 outputs the first target data to the data processing circuit 110 for subsequent processing (step S460); when the second check result is correct, the debug circuit 166 outputs the second target data to the data processing circuit 110 for subsequent processing (step S470).

For the network data processing apparatus 100 (or 200), using the predicted data in the decoding process helps to finish the decoding process early (e.g., without waiting for the complete second network data to be received), so that the network data processing apparatus 100 (or 200) can shut down the decoding circuit 150 (or 160) and/or the data transceiving circuit 140 early to reduce power consumption. Furthermore, the network data processing apparatus 100 (or 200) knows a portion of the second network data in advance, which also helps to improve decoding performance. For example, assuming that the transmitting end is to transmit 16 bits of data and encoded into 24 bits of data by using 2/3 convolutional code (convolutional code), when the network data processing apparatus 100 (or 200) can know 4 bits of the 16 bits in advance, it is equivalent to transmit 12 bits of data by using 24 encoded bits (coded bits). In other words, the code rate (code rate) is changed from 2/3 to 1/2, which significantly improves decoding performance.

Fig. 5 is a schematic diagram of an open system interconnection model. As shown in fig. 5, the Data processing circuit 110 includes N abstraction layers (abstraction layers), where N is generally equal to six for the open system interconnection model, and the 0 th abstraction Layer to the 6 th abstraction Layer are a Physical Layer (Physical Layer), a Data Link Layer (Data Link Layer), a Network Layer (Network Layer), a Transport Layer (Transport Layer), a Session Layer (Session Layer), a Presentation Layer (Presentation Layer) and an Application Layer (Application Layer) in this order. When receiving data, the layer 0 abstraction layer receives the data PDUin _0, processes (e.g., removes the header) the data PDUin _0, then extracts the data that can be processed by itself, and transmits the other data (i.e., the data PDUin _1) to the layer 1 (not shown). Similarly, the N-1 layer abstract layer receives the data PDUin _ N-1 from the N-2 layer abstract layer, removes the header and takes out the data corresponding to the layer, and then transmits the data PDUin _ N to the N layer abstract layer. The operation of transmitting data is generally the reverse of the operation of receiving data, which is well known in the art and thus will not be described in detail.

FIG. 6 is a flowchart illustrating a method for predicting network data according to an embodiment of the present invention. First, the K-th abstraction layer generates PDUout _ K according to the communication protocol of the layer (step S610) (0. ltoreq. K. ltoreq.N). The transmission data PDUout _ K may be processed by a peer abstraction layer of a target network device communicating with the network data processing device 100 (or 200), i.e., the peer abstraction layer and the K-th layer abstraction layer are corresponding abstraction layers, and both follow the same communication protocol (obey). The K-th layer abstraction layer generates the prediction data pdupdated _ K according to the communication protocol of the K-th layer abstraction layer and the transmission data PDUout _ K (step S620), wherein the prediction data pdupdated _ K is related to the transmission data PDUout _ K. In more detail, since the K-th layer abstraction layer and the peer abstraction layer of the target network device follow the same communication protocol, the K-th layer abstraction layer can predict response data to be generated when the peer abstraction layer receives the transmission data PDUout _ K by simulating the peer abstraction layer. In other words, the K-th abstraction layer takes the transmission data PDUout _ K as the received data, and generates the prediction data pdupstream _ K according to the transmission data PDUout _ K and the communication protocol followed by the K-th abstraction layer. Except for layer 0, each abstraction layer talks to the peer's abstraction layer using the underlying services.

The data processing circuit 110 predicts part or all of the bits of the prediction data pdupdated _ K according to the characteristics of the transmission data PDUout _ K. In more detail, step S620 includes sub-steps S622-S626. The K-th abstraction layer first determines whether the PDUout _ K is broadcast (broadcast) or session (dialog) protocol (step S622). If the response data is the broadcast protocol, the K-th abstraction layer generates the prediction data according to the association between the field of the response data and the time (step S624); if the protocol is a session protocol, the K-th abstraction layer uses the transmitted data as received data and generates predicted data according to the session protocol and the received data (step S626). Details of steps S624 and S626 will be described in detail below.

In some embodiments, the K-th layer abstraction layer also generates an auxiliary data mask _ K indicating predicted bits and/or unpredicted bits in the prediction data pdupdated _ K (step S630). The details of the auxiliary data can be referred to the examples presented above. If the prediction data pdupdated _ K is Q bits more than the prediction data pdupdated _ K +1, the auxiliary data mask _ K is Q bits more than the auxiliary data mask _ K +1 in the same manner.

Finally, the K-th layer abstraction layer transfers the transfer data PDUout _ K, the prediction data pdupdated _ K, and the auxiliary data mask _ K to the K-1-th layer abstraction layer (step S640). The data PDUin _ K, the transmission data PDUout _ K, and the prediction data pdupdated _ K may be regarded as Protocol Data Units (PDUs). The transmission data PDUout _0 and the prediction data pdupdated _0 are the first data block and the second data block generated by the data processing circuit 110, respectively.

Fig. 7 is a detailed flow of step S624. Assume that the K-th abstraction layer generates a previous transmission data PDUout _ K based on the broadcast protocol before generating the transmission data PDUout _ K, and the peer abstraction layer of the target network device generates the data PDUin _ K in response to the previous transmission data, i.e. the data PDUin _ K is response data based on the broadcast protocol. Since the time-independent fields of the response data PDUin _ K' responding to the transmission data PDUout _ K are substantially the same as the corresponding fields of the data PDUin _ K when the transmission data PDUout _ K conforms to the broadcast protocol, the K-level abstraction layer can determine how to generate the prediction data PDUin _ K according to the attributes of the fields.

The response data PDUin _ K and the response data PDUin _ K' each include a plurality of fields. First, the K-th abstraction layer determines whether the target field of the response data PDUin _ K is not time-dependent (step S710). If so, the K-th abstraction layer sets a field of the prediction data pdupdated _ K corresponding to the target field to be equal to the target field, in other words, the K-th abstraction layer may set bits of a time-independent field of the prediction data pdupdated _ K to be equal to bits of a corresponding field (e.g., the target field) of the data PDUin _ K (step S720). If the result of the step S710 is negative, the K-th abstraction layer determines a temporal dependency of the target field (step S730), and then sets at least one bit of a field corresponding to the target field in the prediction data pdupdated _ K to be equal to a corresponding bit of the target field according to the temporal dependency (step S740). For example, if more bits in the target field are time-dependent, the degree of time-dependence of the target field is higher, and vice versa. The higher (lower) degree of temporal dependency means that the more (fewer) bits of the field in the K-th layer abstraction layer setting prediction data pdupdated _ K are equal to the corresponding bits in the target field.

As shown in fig. 7, when predicting the network data based on the broadcast protocol, the K-th abstraction layer may predict the entire field according to the time dependency of the field (step S720), or predict only some bits (e.g., the most significant bits) in the field (steps S730, S740). For example, fig. 8 is a data structure of a broadcast packet corresponding to a Narrowband Master Information Block (MIB-NB) (masterinformation Block-NB) of the Narrowband internet of things. Since the system framenumber-MSB-r13 and hyperSFN-LSB-r13 are time information, no prediction is made. Because the systemlnfovaluetag-r 13 varies slowly (i.e., has a low degree of time dependence), it can be predicted to not vary (i.e., to be identical to the previous response data), or to predict only a portion of the MSB thereof. The remaining fields are time independent and therefore can be predicted to be the same as the previous response data.

Fig. 9 is a detailed flow of step S626. First, the K-th abstraction layer generates an intermediate data according to the received data (step S910). The intermediate data is transmitted data PDUout _ K as received data at the K-th abstraction layer, and response data responding to the received data is generated according to a protocol of the K-th abstraction layer. In other words, the K-th layer abstraction layer generates the intermediate data by acting as a peer abstraction layer. Next, the K-th abstraction layer determines whether the intermediate data needs to be encrypted (step S920). More specifically, if the protocol of the K-th abstraction layer includes encrypting the pdu, the determination of step S920 is yes, and the K-th abstraction layer encrypts the intermediate data according to the protocol in step S930. If encryption is not required (No in step S920) or step S930 is completed, the K-th abstraction layer determines whether integrity check (integrity check) is required (step S940).

Next, if the protocol does not include integrity checking, the K-th abstraction layer processes (e.g., adds a header) the encrypted or unencrypted intermediate data to generate prediction data (step S950). If the protocol includes integrity check, the K-th abstraction layer performs integrity check on the encrypted or unencrypted intermediate data according to the protocol to generate a Message Authentication Code (MAC) (step S960), and then combines the intermediate data and the MAC to generate the predicted data (step S970). In some embodiments, step S970 includes adding a header to the combined data to generate the prediction data.

Note that, when data processing is required in some steps of the flows of fig. 7 and 9, if output bits affected by some input bits intersect output bits affected by other input bits, these intersected output bits are not predicted (for example, may occur in step S960); if the output bit affected by any input bit does not intersect the output bit affected by any other input bit, then a prediction is made.

In some embodiments, multiplexing may also be included when the K-th layer abstraction layer generates the prediction data pdupdated _ K. If there are more than one K +1 abstraction layers and the peer abstraction layers perform multiplexing when transmitting protocol data units, the K-th abstraction layer may also optionally perform multiplexing when generating the prediction data pdupdated _ K. However, not multiplexing is a reasonable prediction.

Since the details of the implementation and variations of the present invention can be understood by those skilled in the art from the disclosure of the present invention, the repetitive description is omitted here for the sake of avoiding unnecessary detail without affecting the requirements and the implementation of the present invention. It should be noted that the shapes, sizes, proportions, and sequence of steps of the elements and steps shown in the drawings are illustrative only and are not intended to be limiting. Furthermore, although the foregoing embodiments are described with reference to the narrow-band Internet of Things, the invention is not limited thereto, and those skilled in the art can apply the invention to other types of Internet of Things, such as Long-Range Internet of Things (LoRa-IoT), as appropriate according to the disclosure of the invention.

Although the embodiments of the present invention have been described above, these embodiments are not intended to limit the present invention, and those skilled in the art can make variations on the technical features of the present invention according to the explicit or implicit contents of the present invention, and all such variations may fall within the scope of the protection sought by the present invention.

Description of the symbols

100. 200 network data processing device

110 data processing circuit

120 debug data generating circuit

130 coding circuit

140 data transmitting and receiving circuit

150. 160 decoding circuit

152. 162, 164 soft input channel decoder

154. 166 error detecting circuit

S210 to S270, S410 to S470, S610 to S640, S710 to S740, and S910 to S970.

Claims

1. A network data prediction method applied to a data processing device of an actual operation open system interconnection model, the data processing device communicating with a target network device of the actual operation open system interconnection model, the network data prediction method comprising the steps of:

generating a transmission data according to a communication protocol of a first abstraction layer, wherein the transmission data can be processed by a first peer abstraction layer of the target network device, the first peer abstraction layer corresponding to the first abstraction layer and conforming to the communication protocol;

generating a prediction data according to the communication protocol and the transmission data; and

the transfer data and the prediction data are transferred to a second abstraction layer.

2. The method of claim 1 wherein the transmission data is a first transmission data and conforms to a broadcast protocol, the data processing device generates a second transmission data conforming to the broadcast protocol before generating the first transmission data, and the target network device generates a response data in response to the second transmission data, the response data including a plurality of fields, the step of generating the prediction data according to the communication protocol and the transmission data comprising:

setting a plurality of bits of a field of the prediction data that is not related to time to be equal to a plurality of bits of a corresponding field of the response data.

3. The method of claim 1 wherein the transmission data is a first transmission data and conforms to a broadcast protocol, the data processing device generates a second transmission data conforming to the broadcast protocol before generating the first transmission data, and the target network device generates a response data in response to the second transmission data, the response data including a plurality of fields, the step of generating the prediction data according to the communication protocol and the transmission data comprising:

determining a time dependence degree of a target field in the response data; and

setting at least one bit of a field corresponding to the target field in the prediction data to be equal to the corresponding bit in the target field according to the time dependence degree.

4. The method of claim 1, wherein the transmitted data conforms to a session protocol, the step of generating the predicted data based on the session protocol and the transmitted data comprising:

the transmitted data is used as a received data, and the predicted data is generated according to the communication protocol and the received data.

5. The method of claim 4 wherein the step of generating the prediction data based on the communication protocol and the transmission data further comprises:

generating an intermediate data according to the received data; and

the intermediate data is encrypted according to the communication protocol.

6. The method of claim 4 wherein the step of generating the prediction data based on the communication protocol and the transmission data further comprises:

generating an intermediate data according to the received data; and

performing integrity check on the intermediate data according to the communication protocol to generate an information authentication code; and

the intermediate data and the message authentication code are combined to generate the predicted data.