Self-adaptive polarization code anti-interference communication method for wood processing

Abstract

The invention provides a self-adaptive polarization code anti-interference communication method for wood processing, and belongs to the technical field of industrial Internet of Things communication. The method comprises the following steps: firstly, acquiring electromagnetic noise intensity, multipath time delay and mechanical vibration frequency parameters of a wood processing environment in real time through a multi-source sensor; an optimal coding scheme in a pre-constructed polarization code library is dynamically matched based on a channel state, the code length is 256-1024, and the frozen bit proportion is 20%-60%; embedding equipment state information through a frozen bit multiplexing mechanism; and combining frequency offset compensation, multi-path signal weighted fusion and layered priority decoding at a receiving end to realize composite interference suppression. According to the invention, high-reliability communication can be realized in a complex wood processing environment, the bit error rate is effectively reduced, and the stability and the anti-interference capability of the system are improved.

Description

Technical Field

[0001] This invention relates to an adaptive polar code anti-interference communication method for wood processing, belonging to the field of industrial Internet of Things communication technology. Background Technology

[0002] In the wood processing industry, the application of the Industrial Internet of Things (IIoT) is becoming increasingly widespread, aiming to automate and intelligentize the production process through efficient communication between smart devices. However, the wood processing environment is highly complex and unique, posing numerous challenges to communication systems.

[0003] First, wood processing equipment such as planers, saws, and milling machines typically generate strong electromagnetic noise. During operation, the starting, stopping, and variable frequency speed control of these machines produce broadband electromagnetic interference, with intensity reaching several V / m and a spectrum ranging from hundreds of kHz to several GHz, severely interfering with the transmission of communication signals.

[0004] Secondly, the mechanical structures and material stacking within the wood processing workshop can trigger severe multipath propagation effects. Wireless signals encounter obstacles such as metal frames and stacks of wood during propagation, resulting in reflection, refraction, and scattering, thus forming multipath signals. Multipath delays can reach several microseconds to tens of microseconds, leading to signal delay spread and frequency-selective fading, distorting the received signal and increasing the difficulty of signal detection.

[0005] Furthermore, the mechanical vibration of wood processing equipment is also a significant interference factor. For example, large sawmills generate mechanical vibrations ranging from tens of hertz to thousands of hertz when cutting wood. These vibrations are transmitted to sensors and antennas installed on the equipment, causing distortion of the antenna's radiation pattern and thus affecting signal transmission and reception.

[0006] In existing industrial IoT communication solutions, traditional modulation and demodulation techniques and channel coding methods are ill-equipped to handle such complex interference environments. For example, while some spread spectrum-based communication solutions offer some anti-interference capabilities, their performance degrades significantly when faced with high-intensity electromagnetic noise and multipath interference. Furthermore, traditional forward error correction (FEC) codes, such as convolutional codes and Turbo codes, often require a high signal-to-noise ratio to achieve a low bit error rate when dealing with multipath effects and time-varying noise under high-dynamic channel conditions, which is difficult to meet in a wood processing environment.

[0007] Furthermore, most existing communication systems do not fully utilize equipment status information to optimize communication. Equipment status information, such as parameters like temperature, pressure, and rotational speed, reflects the operating status of the equipment. Incorporating this information into communication coding would help improve the reliability and efficiency of communication, but research and application in this area are currently lacking.

[0008] Therefore, there is an urgent need for a communication method that can adapt to the complex environment of wood processing, effectively resist interference, and utilize equipment status information to meet the development needs of the Industrial Internet of Things in the wood processing field. Summary of the Invention

[0009] The purpose of this invention is to solve the problems existing in the prior art and to provide an adaptive polar code anti-interference communication method for wood processing.

[0010] The objective of this invention is achieved through the following technical solution:

[0011] An adaptive polar code anti-interference communication method for wood processing includes the following steps:

[0012] Step S1: Real-time acquisition of environmental parameters:

[0013] The signal-to-noise ratio (SNR) and mechanical vibration frequency (F) in the wood processing environment are acquired in real time using electromagnetic noise sensors, triaxial vibration sensors, and multipath detection antenna arrays. vib and multipath delay D delay ;

[0014] Step S2: Dynamic polar code configuration:

[0015] The code length N and the frozen bit ratio R of the polar code are calculated based on the following formulas:

[0016]

[0017]

[0018] in, The symbol period; This is a rounding up operation; based on the frozen bit ratio R, the number of frozen bits is obtained as follows: ,when When the value is not an integer, the rounding method is used to ensure that the frozen bits have sufficient redundancy;

[0019] Based on the calculated code length and frozen bit ratio, the optimal encoding scheme is queried from the pre-built polar code library. If a match is found, the corresponding polar code sequence is directly generated; otherwise, the default code length N=512 is used, and the R value is dynamically adjusted to generate the polar code sequence.

[0020] Step S3: Freeze bit multiplexing transmission:

[0021] The status information of industrial Internet devices in the wood processing environment is mapped to frozen bits to generate coded data containing redundant information, and the coded data is sent to the antenna receiver through the transmitting antenna.

[0022] Step S4: Joint suppression of multiple interferences:

[0023] After receiving the coded data signal, the antenna receiver corrects the carrier offset using a frequency offset compensation algorithm, employing weighting coefficients. Fusion of multipath signals;

[0024] in, For the first Weighting of multipath signals, For indexing multipath signals, For the first Multipath delay of a multipath signal;

[0025] Step S5: Layered SCL decoding:

[0026] The encoded data is decoded and processed by the antenna receiver to extract the control commands and monitoring data of the industrial Internet devices in the wood processing environment. The control commands and monitoring data are then decoded using hierarchical SCL with list sizes L=4 and L=16, respectively.

[0027] Preferably, the multipath detection antenna array in step S1 is a 4×4 patch array, installed at a 45° tilt angle, with an array spacing of 1 / 2 working wavelength, and a multipath signal acquisition rate ≥95%.

[0028] Preferably, the method for constructing the pre-built polar code library in step S2 includes the following steps:

[0029] Step S21: Define the multidimensional parameter space:

[0030] Define a parameter space that includes the following dimensions:

[0031] Code length N: The range of values ​​is ;

[0032] Freeze bit ratio R: The value ranges from 0.20 to 0.60, with a step value of 0.05;

[0033] Signal-to-noise ratio (SNR): The value ranges from 0 to 30 dB, divided into 16 intervals, each with a width of 2 dB;

[0034] Multipath delay D delay The value range is 0.1–50 μs, divided into 25 intervals, each interval being 2 μs wide;

[0035] Step S22: Generate a channel reliability sequence:

[0036] For each set of parameter combinations in the parameter space:

[0037] (1) Calculate the initial channel capacity using the density evolution method:

[0038]

[0039] where \(I\) is the channel capacity, \(W\) is the transition probability distribution model of a binary-input discrete memoryless channel; \(N\) is the code length of the polar code; \(i\), \(j\), \(k\) are all sub-channel index parameters, taking positive integers; \(i\) is the sub-channel number generated after polarization, \(j\), \(k\) are the numbers of the two original sub-channels participating in the combination during the polarization process, and \(j < k\), and satisfy or ;

[0040] (2) Apply Gaussian approximation for optimization:

[0041]

[0042] where ;

[0043] (3) Generate a channel reliability ranking sequence based on the optimization result;

[0044] Step S23: Construct a three-level index structure:

[0045] Establish a hierarchical indexing mechanism:

[0046] (1) First-level index: Divide by SNR interval;

[0047] (2) Second-level index: Divide by delay interval within the SNR interval;

[0048] (3) Third-level index: Divide by \((N, R)\) combination within the delay interval;

[0049] Step S24: Bitmap compression storage:

[0050] For each coding scheme:

[0051] (1) Generate a frozen bit bitmap, an information bit bitmap, and a CRC protection bitmap;

[0052] (2) Compress the bitmap data using run-length encoding;

[0053] (3) Store in the physical format of 12-byte header + compressed bitmap;

[0054] Step S25: Establish an efficient retrieval mechanism:

[0055] Based on Trees are used to construct multi-level index structures to achieve:

[0056] Code library size Search latency at 10,000 records 50μs;

[0057] Code library size Search latency at 100,000 records 100μs;

[0058] Step S26: Dynamic update mechanism:

[0059] During system operation:

[0060] (1) Monitoring conditions: When the bit error rate of the same coding scheme is high for 3 consecutive communications. Updates are triggered on time;

[0061] (2) Collect current channel parameters: signal-to-noise ratio (SNR), multipath delay ;

[0062] (3) Generate and verify the new polar code sequence;

[0063] (4) By update weight , where t is the number of times the encoding scheme is used, and e is a natural constant.

[0064] Preferably, in step S3, the status information of industrial internet devices in the wood processing environment is embedded in frozen bits using a CRC-8 checksum, with a checksum interval of 1 bit inserted every 16 bits.

[0065] Preferably, the specific process of the frequency offset compensation algorithm in step S4 is as follows:

[0066] Step S41: Carrier frequency offset estimation:

[0067] The received encoded data signal is frequency-converted to obtain the baseband signal r(t), and the phase difference of the baseband signal is calculated using a sliding window. Estimate frequency offset T is the sampling period, and the length of the sliding window is n sampling points, the specific value of which is determined according to the signal bandwidth and processing capability.

[0068] Step S42: Frequency offset correction:

[0069] Based on the estimated frequency offset value Dynamic compensation is achieved through a digital phase-locked loop and a voltage-controlled oscillator, with a frequency deviation tracking range of ±50ppm and a compensation accuracy of [missing information]. 0.1ppm.

[0070] Preferably, the specific method for fusing multipath signals using weighted coefficients in step S4 is as follows: The m multipath signals captured by the antenna receiver... , Multiply by the corresponding weighting coefficients respectively The weighted signal is obtained. Then, all the weighted signals are superimposed, that is... The fused signal was obtained. .

[0071] Preferably, the length n of the sliding window in step S41 is determined in the following way:

[0072] (1) The range of n is 100 n 1000, this range is determined based on the signal characteristics and processing requirements in the wood processing environment;

[0073] (2) The specific value of n is determined based on the signal bandwidth B, and the calculation formula is as follows:

[0074]

[0075] in, This indicates a round-down operation;

[0076] (3) When the processing capacity of industrial Internet devices is limited, n is taken as the minimum value between the calculated value of n and the upper limit of the device processing capacity, so as to ensure the real-time processing needs.

[0077] (4) The system recalculates the value of n every 100ms based on the current signal bandwidth and processing load, and adjusts it smoothly in the following ways:

[0078]

[0079] in, The smoothing factor takes values ​​of , The current sliding window length. This is the newly calculated theoretical value.

[0080] Preferably, the digital phase-locked loop in step S42 includes: a phase detector and a loop carrier, wherein the signal output terminal of the phase detector is connected to the signal input terminal of the loop carrier; the specific process of dynamic compensation between the digital phase-locked loop and the voltage-controlled oscillator includes:

[0081] (1) Phase detector, used to compare the phase of the input baseband signal r(t) with the local carrier signal of the voltage-controlled oscillator and output the phase error signal e(t);

[0082] (2) Loop carrier, used to perform low-pass filtering on the phase error signal e(t) to remove high-frequency noise and obtain a smooth control signal u(t);

[0083] (3) Voltage-controlled oscillator, used to adjust the output frequency according to the control signal u(t), so that the local carrier frequency gradually approaches the carrier frequency of the input signal until the phase error e(t) approaches zero, thus completing the frequency offset compensation.

[0084] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0085] This invention utilizes multiple sensors—an electromagnetic noise sensor, a triaxial vibration sensor, and a multipath detection antenna array—to collect in real-time electromagnetic noise intensity, multipath delay, and mechanical vibration frequency parameters of the wood processing environment. It dynamically matches the optimal coding scheme from a pre-constructed polar code library based on channel state, where the code length is 256-1024 and the frozen bit ratio is 20%-60%. Device status information is embedded through a frozen bit reuse mechanism. At the receiving end, combined frequency offset compensation, multipath signal weighted fusion, and hierarchical priority decoding are employed to suppress composite interference.

[0086] This invention achieves efficient and reliable communication in complex wood processing environments by dynamically configuring polar code parameters, embedding device status information through a frozen bit multiplexing mechanism, and employing multi-interference joint suppression technology. This effectively reduces the bit error rate, improves system stability and anti-interference capabilities, and is compatible with the Modbus RTU protocol. It also supports seamless upgrades of existing equipment and reduces deployment costs. Attached Figure Description

[0087] Figure 1 This is a system architecture diagram of an adaptive polar code anti-interference communication method for wood processing according to the present invention.

[0088] Figure 2 This is a flowchart of the dynamic polar code configuration process of the present invention.

[0089] Figure 3 This is a flowchart of the frequency offset compensation DPLL-VCO of the present invention.

[0090] Figure 4 This is a flowchart of the multipath signal weighted fusion process of the present invention.

[0091] Figure 5 This is a flowchart of the layered SCL decoding process of the present invention.

[0092] Figure 6 This is a schematic diagram of the antenna array configuration of the present invention.

[0093] Figure 7 This is a flowchart of the frozen bit multiplexing transmission mechanism of the present invention.

[0094] Figure 8 This is a flowchart of the pre-built polar code library of the present invention. Detailed Implementation

[0095] The present invention will be further described in detail below with reference to the accompanying drawings: This embodiment is implemented under the premise of the technical solution of the present invention, and detailed implementation methods are given, but the protection scope of the present invention is not limited to the following embodiments. Specific implementation method one:

[0097] like Figure 1 The diagram shown is the overall system architecture diagram, illustrating the overall architecture of the wood processing adaptive polar code anti-interference communication method, including the main components of the transmitter and receiver and their interrelationships.

[0098] Transmitter:

[0099] 1. First, environmental parameters were collected. Electromagnetic noise intensity signal-to-noise ratio (SNR) and mechanical vibration frequency (F) in the wood processing environment were collected using electromagnetic noise sensors, triaxial vibration sensors, and a multipath detection antenna array. vib and multipath delay D delay Among them, such as Figure 6 The diagram shows a schematic of the antenna array configuration, detailing the arrangement of a 4×4 patch array for the multipath antenna array and its installation configuration. This includes a 45° tilt installation angle, an array spacing of 1 / 2 working wavelength, and a multipath signal capture rate of ≥95%. The diagram also explains the advantages of this installation method: the 45° tilt installation angle optimizes vertical coverage, the 1 / 2 working wavelength array spacing reduces mutual coupling effects, and the ≥95% multipath signal capture rate enhances signal stability.

[0100] 2. Then, polar code configuration is performed. The collected environmental parameters are digitized, and the code length N and frozen bit ratio R of the polar code are calculated according to the set formula. The calculation formula is:

[0101]

[0102]

[0103] in, The symbol period; This is a rounding up operation; the code length N is an integer; after calculating the frozen bit ratio R, the number of frozen bits is... ,when When the integer is not an integer, it is rounded up (i.e., if the integer is not an integer). decimal part If , then add 1 to the integer part to ensure that the frozen bits have sufficient redundancy;

[0104] Based on the calculated code length and frozen bit ratio, the optimal encoding scheme is queried from the pre-built polar code library. If a match is found, the corresponding polar code sequence is directly generated; otherwise, the default code length N=512 is used, and the R value is dynamically adjusted to generate the polar code sequence. Figure 2 The diagram shows the dynamic polar code configuration flowchart, which details the specific steps from sensor data acquisition to the output encoding scheme, including environmental parameter preprocessing, calculating the code length N, calculating the frozen bit ratio R, polar code library query, and generating polar code sequences.

[0105] like Figure 8 The diagram shown illustrates the flowchart for constructing a pre-built polar code library, detailing the method for doing so. This includes defining a multi-dimensional parameter space, generating a channel reliability sequence, constructing a three-level index structure, bitmap compression storage, establishing an efficient retrieval mechanism, and a dynamic update mechanism. The method for constructing the pre-built polar code library includes the following steps:

[0106] Step 1: Define the multidimensional parameter space:

[0107] Define a parameter space that includes the following dimensions:

[0108] Code length N: The range of values ​​is ;

[0109] Freeze bit ratio R: The value ranges from 0.20 to 0.60, with a step value of 0.05;

[0110] Signal-to-noise ratio (SNR): The value ranges from 0 to 30 dB, divided into 16 intervals, each with a width of 2 dB;

[0111] Multipath delay D delay The value range is 0.1–50 μs, divided into 25 intervals, each interval being 2 μs wide;

[0112] Step 2: Generate a channel reliability sequence:

[0113] For each combination of parameters in the parameter space:

[0114] (1) Calculate the initial channel capacity using the density evolution method:

[0115]

[0116] Among them, I represents the channel capacity, which is used to quantify the ability of the sub-channel to transmit information, with the unit of bit / channel use; W represents the transition probability distribution model of the binary-input discrete memoryless channel, which describes the output probability characteristics of the input symbol after being transmitted through the channel; N represents the code length of the polar code (a positive integer), and the code length range is the code length range defined in step one; i, j, and k are all sub-channel index parameters (positive integers), which are used to distinguish different sub-channels. i represents the number of the sub-channel generated after polarization, and j and k represent the numbers of the two original sub-channels participating in the combination during the polarization process (j < k), and satisfy or , reflecting the recursive combination relationship of channel polarization;

[0117] (2) Apply Gaussian approximation optimization:

[0118]

[0119] Among them, (SNR is the signal-to-noise ratio, unit: dB)

[0120] (3) Generate a channel reliability ranking sequence based on the optimization result;

[0121] Step three: Construct a three-level index structure:

[0122] Establish a hierarchical indexing mechanism:

[0123] (1) First-level index: Divide by SNR intervals;

[0124] (2) Second-level index: Divide by delay intervals within the SNR interval;

[0125] (3) Third-level index: Divide by (N, R) combinations within the delay interval;

[0126] Step four: Bitmap compression storage:

[0127] For each coding scheme:

[0128] (1) Generate a frozen bit bitmap, an information bit bitmap, and a CRC protection bitmap;

[0129] (2) Compress the bitmap data using run-length encoding (RLE);

[0130] (3) Store in the physical format of 12-byte header + compressed bitmap;

[0131] Step five: Establish an efficient retrieval mechanism:

[0132] Based on a tree to construct a multi-level index structure to achieve:

[0133] The size of the code library Search latency at 10,000 records 50μs;

[0134] Code library size Search latency at 100,000 records 100μs;

[0135] Step Six: Dynamic Update Mechanism

[0136] During system operation:

[0137] (1) Monitoring conditions: When the bit error rate of the same coding scheme is high for 3 consecutive communications. Updates are triggered on time;

[0138] (2) Collect current channel parameters: signal-to-noise ratio (SNR), multipath delay ;

[0139] (3) Generate and verify the new polar code sequence;

[0140] (4) By update weight , where t is the number of times the encoding scheme is used, and e is a natural constant.

[0141] 3. Next, frozen bit multiplexing transmission is performed. The status information of industrial internet devices in the wood processing environment is embedded into the frozen bits using a CRC-8 checksum, with 1 checksum bit inserted every 16 bits, generating coded data containing redundant information. The industrial internet devices in the wood processing environment include, but are not limited to, wood processing equipment (such as planers, saws, and milling machines), environmental monitoring sensors (such as temperature sensors and pressure sensors), communication controllers, and actuators. Figure 7 The diagram shows the flowchart of the frozen bit multiplexing transmission mechanism, which details the transmission process from preprocessing the industrial internet device status information to extracting the industrial internet device status information at the receiving end. This includes preprocessing the industrial internet device status information, mapping it to frozen bits, generating CRC-8 checksums, inserting 1 checksum bit every 16 bits, and generating redundant encoded data.

[0142] 4. Finally, the encoded data is transmitted through the transmitting antenna.

[0143] Receiver:

[0144] First, frequency offset compensation is performed. After the antenna receiver receives the coded data signal, it first corrects the carrier offset using a frequency offset compensation algorithm. The frequency offset tracking range is ±50ppm, and the compensation accuracy is [not specified]. 0.1ppm, such as Figure 3The diagram shown is a flowchart of a DPLL-VCO frequency offset compensation algorithm, detailing how the algorithm dynamically adjusts frequency offset compensation using a digital phase-locked loop (DPLL) combined with a voltage-controlled oscillator (VCO). The process includes estimating the frequency offset value and correcting the frequency offset, as detailed below:

[0145] (1) Carrier frequency offset estimation: The received coded data signal is down-converted to obtain the baseband signal r(t), and the phase difference of the baseband signal is calculated by a sliding window. Estimate frequency offset (T is the sampling period), the length of the sliding window is n sampling points, the specific value of which is determined according to the signal bandwidth and processing capability, and the value of n ranges from 100. n 1000, the specific value is determined based on the signal bandwidth B (unit: Hz), and the calculation formula is as follows:

[0146]

[0147] in, This indicates a rounding down operation. When the device's processing capacity is limited, n is taken as the smaller of the calculated value of n above and the upper limit of the device's processing capacity to ensure real-time processing requirements; the system recalculates the value of n every 100ms based on the current signal bandwidth and processing load, and adjusts it smoothly in the following way:

[0148]

[0149] in, The smoothing factor takes values ​​of , The current sliding window length. This is the newly calculated theoretical value;

[0150] (2) Frequency offset correction: based on the estimated frequency offset value Dynamic compensation is achieved through a digital phase-locked loop (DPLL) and a voltage-controlled oscillator (VCO). The specific process of dynamic compensation using a DPLL and a VCO includes:

[0151] First is the phase detector, which compares the phase of the input baseband signal r(t) with the local carrier signal of the voltage-controlled oscillator (VCO) and outputs the phase error signal e(t).

[0152] Next is the loop carrier, and the loop filter performs low-pass filtering on the phase error signal e(t) to remove high-frequency noise and obtain a smooth control signal u(t);

[0153] Finally, there is the voltage-controlled oscillator (VCO). The VCO adjusts its output frequency according to the control signal u(t), gradually bringing the local carrier frequency closer to the input signal's carrier frequency until the phase error e(t) approaches zero, thus completing frequency offset compensation. The frequency offset tracking range is ±50ppm, and the compensation accuracy is... 0.1ppm.

[0154] like Figure 4 The diagram shown is a flowchart of multipath signal weighted fusion, which includes separating the input multipath signal, weighting the multipath signal, fusion of the signal, and outputting the fused signal.

[0155] 1. First, use weighting coefficients. Multipath signals are fused to enhance signal reliability and stability.

[0156] in, For the first Weighting of multipath signals, The index of the multipath signal, i.e., the first... multipath signals, The total number of multipath signals. For the first Multipath delay of a multipath signal;

[0157] The specific method is as follows: m multipath signals captured by the receiving end... ( ), respectively multiplied by the corresponding weighting coefficient The weighted signal is obtained. Then, all the weighted signals are superimposed, that is... The fused signal was obtained. ;

[0158] 2. Next, layered SCL decoding is used to achieve efficient decoding of the encoded data. For example... Figure 5 The diagram shows a layered SCL decoding flowchart, detailing the process by which the receiving end performs layered SCL decoding on the extracted control commands and monitoring data using list sizes L=4 and L=16, respectively. Specifically, the encoded data is decoded and processed by the antenna receiver to extract the control commands and monitoring data of the device. Layered SCL decoding with list sizes L=4 and L=16 is then applied to the control commands and monitoring data, respectively. The control commands include device start / stop and parameter adjustment commands, while the monitoring data includes operating parameters such as device temperature, speed, and vibration.

[0159] 3. Finally, output control commands and monitoring data for use by subsequent wood processing equipment control and monitoring systems.

[0160] Through the above steps, this invention can achieve highly reliable communication in complex wood processing environments, effectively reduce the bit error rate, improve system stability and anti-interference capabilities, while being compatible with existing equipment and reducing deployment costs. It has high application value and market prospects.

[0161] The above description is merely a preferred embodiment of the present invention. These specific embodiments are different implementations based on the overall concept of the present invention, and the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A wood processing adaptive polar code anti-interference communication method, characterized in that, Includes the following steps: Step S1: Real-time acquisition of environmental parameters: The signal-to-noise ratio (SNR) and mechanical vibration frequency (F) in the wood processing environment are acquired in real time using electromagnetic noise sensors, triaxial vibration sensors, and multipath detection antenna arrays. vib and multipath delay D delay ; Step S2: Dynamic polar code configuration: The code length N and the frozen bit ratio R of the polar code are calculated based on the following formulas: in, The symbol period; This is a rounding up operation; based on the frozen bit ratio R, the number of frozen bits is obtained as follows: ,when When the value is not an integer, the rounding method is used to ensure that the frozen bits have sufficient redundancy; Based on the calculated code length and frozen bit ratio, the optimal encoding scheme is queried from the pre-built polar code library. If a match is found, the corresponding polar code sequence is directly generated; otherwise, the default code length N=512 is used, and the R value is dynamically adjusted to generate the polar code sequence. Step S3: Freeze bit multiplexing transmission: The status information of industrial Internet devices in the wood processing environment is mapped to frozen bits to generate coded data containing redundant information, and the coded data is sent to the antenna receiver through the transmitting antenna. Step S4: Joint suppression of multiple interferences: After receiving the coded data signal, the antenna receiver corrects the carrier offset using a frequency offset compensation algorithm, employing weighting coefficients. Fusion of multipath signals; in, For the first Weighting of multipath signals, For indexing multipath signals, For the first Multipath delay of a multipath signal; Step S5: Layered SCL decoding: The encoded data is decoded and processed by the antenna receiver to extract the control commands and monitoring data of the industrial Internet devices in the wood processing environment. The control commands and monitoring data are then decoded using hierarchical SCL with list sizes L=4 and L=16, respectively.

2. The wood processing adaptive polar code anti-interference communication method according to claim 1, characterized in that, The multipath detection antenna array mentioned in step S1 is a 4×4 patch array, installed at a 45° tilt angle, with an array spacing of 1 / 2 working wavelength, and a multipath signal acquisition rate of ≥95%.

3. The wood processing adaptive polar code anti-interference communication method according to claim 1, characterized in that, The method for constructing the pre-built polar code library in step S2 includes the following steps: Step S21: Define the multidimensional parameter space: Define a parameter space that includes the following dimensions: Code length N: The range of values ​​is ; Freeze bit ratio R: The value ranges from 0.20 to 0.60, with a step value of 0.05; Signal-to-noise ratio (SNR): The value ranges from 0 to 30 dB, divided into 16 intervals, each with a width of 2 dB; Multipath delay D delay The value range is 0.1–50 μs, divided into 25 intervals, each interval being 2 μs wide; Step S22: Generate a channel reliability sequence: For each combination of parameters in the parameter space: (1) Calculate the initial channel capacity using the density evolution method: where \(I\) is the channel capacity, \(W\) is the transition probability distribution model of a binary-input discrete memoryless channel; \(N\) is the code length of the polar code; \(i\), \(j\), and \(k\) are all sub-channel index parameters, taking positive integers; \(i\) is the number of the sub-channel generated after polarization, \(j\) and \(k\) are the numbers of the two original sub-channels participating in the combination during the polarization process, and \(j < k\), and satisfy or ; (2) Applying Gaussian approximation for optimization: in, ; (3) Generate a channel reliability ranking sequence based on the optimization results; Step S23: Construct a three-level index structure: Establish a hierarchical indexing mechanism: (1) First-level index: divided according to SNR interval; (2) Secondary index: Divided into delay intervals within the SNR interval; (3) Three-level index: divided according to (N, R) combinations within the time delay interval; Step S24: Bitmap compression and storage: For each encoding scheme: (1) Generate a frozen bit map, an information bit map, and a CRC protection bit map; (2) Run-length encoding is used to compress bitmap data; (3) Stored in a physical format of a 12-byte header + compressed bitmap; Step S25: Establish an efficient retrieval mechanism: based on Trees are used to construct multi-level index structures to achieve: Code library size Search latency at 10,000 records 50μs; Code library size Search latency at 100,000 records 100μs; Step S26: Dynamic update mechanism: During system operation: (1) Monitoring conditions: When the bit error rate of the same coding scheme is high for 3 consecutive communications. Updates are triggered on time; (2) Collect current channel parameters: signal-to-noise ratio (SNR), multipath delay ; (3) Generate and verify the new polar code sequence; (4) By update weight , where t is the number of times the encoding scheme is used, and e is a natural constant.

4. The anti-interference communication method for adaptive polar codes in wood processing according to claim 1, characterized in that, In step S3, the status information of industrial internet devices in the wood processing environment is embedded in frozen bits using CRC-8 checksums, with a checksum interval of 1 bit inserted every 16 bits.

5. The wood processing adaptive polar code anti-interference communication method according to claim 1, characterized in that, The specific process of the frequency offset compensation algorithm described in step S4 is as follows: Step S41: Carrier frequency offset estimation: The received encoded data signal is frequency-converted to obtain the baseband signal r(t), and the phase difference of the baseband signal is calculated using a sliding window. Estimate frequency offset T is the sampling period, and the length of the sliding window is n sampling points, the specific value of which is determined according to the signal bandwidth and processing capability. Step S42: Frequency offset correction: Based on the estimated frequency offset value Dynamic compensation is achieved through a digital phase-locked loop and a voltage-controlled oscillator, with a frequency deviation tracking range of ±50ppm and a compensation accuracy of [missing information]. 0.1ppm.

6. The wood processing adaptive polar code anti-interference communication method according to claim 1, characterized in that, The specific method for fusing multipath signals using weighted coefficients in step S4 is as follows: The m multipath signals captured by the antenna receiver... , Multiply by the corresponding weighting coefficients respectively The weighted signal is obtained. Then, all the weighted signals are superimposed, that is... The fused signal was obtained. .

7. The wood processing adaptive polar code anti-interference communication method according to claim 5, characterized in that, The length n of the sliding window mentioned in step S41 is determined in the following way: (1) The range of n is 100 n 1000, this range is determined based on the signal characteristics and processing requirements in the wood processing environment; (2) The specific value of n is determined based on the signal bandwidth B, and the calculation formula is as follows: in, This indicates a round-down operation; (3) When the processing capacity of industrial Internet devices is limited, n is taken as the minimum value between the calculated value of n and the upper limit of the device processing capacity, so as to ensure the real-time processing needs. (4) The system recalculates the value of n every 100ms based on the current signal bandwidth and processing load, and adjusts it smoothly in the following ways: in, The smoothing factor takes values ​​of , The current sliding window length. This is the newly calculated theoretical value.

8. The wood processing adaptive polar code anti-interference communication method according to claim 5, characterized in that, The digital phase-locked loop (PLL) mentioned in step S42 includes a phase detector and a loop carrier, with the signal output terminal of the phase detector connected to the signal input terminal of the loop carrier. The specific process of dynamic compensation between the digital PLL and the voltage-controlled oscillator includes: (1) Phase detector, used to compare the phase of the input baseband signal r(t) with the local carrier signal of the voltage-controlled oscillator and output the phase error signal e(t); (2) Loop carrier, used to perform low-pass filtering on the phase error signal e(t) to remove high-frequency noise and obtain a smooth control signal u(t); (3) Voltage-controlled oscillator, used to adjust the output frequency according to the control signal u(t), so that the local carrier frequency gradually approaches the carrier frequency of the input signal until the phase error e(t) approaches zero, thus completing the frequency offset compensation.

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