A wireless ad hoc network adaptive anti-interference scheduling method and system

Abstract

The present invention discloses a method and system for adaptive anti-interference scheduling of wireless ad hoc networks, which relates to the field of wireless communication technology. The method comprises the following steps: real-time acquisition of service flows in wireless ad hoc networks and monitoring of data environment parameters, wherein the data environment parameters include interference intensity and network load rate; calculation of basic resource rate using the Michaelis equation according to the interference intensity, and dynamic adjustment of the Michaelis equation parameters according to the network load rate to generate a dynamic total amount of resources; construction of an orthogonal ARU matrix based on the dynamic total amount of resources, and generation of a conflict-free ARU allocation matrix by constraining the ARU correlation coefficients of adjacent nodes through the Hadamard matrix; splitting service flows into atomic data blocks, and using the Hungarian algorithm to map the atomic data blocks to the conflict-free ARU allocation matrix to generate a three-dimensional resource scheduling table. The present invention improves the accuracy of resource allocation and system robustness; reduces the probability of multi-dimensional resource conflicts, and improves spectrum reuse efficiency and network stability.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communications, and in particular to a method and system for adaptive anti-interference scheduling of a wireless ad hoc network. Background Art

[0002] With the rapid development of wireless communication technology, wireless ad hoc networks (WANs), owing to their advantages such as lack of fixed infrastructure and rapid deployment, have gained widespread application in military communications, emergency rescue, and the Internet of Things. In particular, achieving efficient and reliable dynamic resource scheduling and interference mitigation in complex electromagnetic environments has become a key research focus. In recent years, the development of orthogonal multiple access (OMA) technologies based on time-frequency resource allocation and intelligent scheduling algorithms has provided new approaches for improving network capacity and interference mitigation.

[0003] Existing wireless ad hoc network scheduling methods have common shortcomings: First, the resource allocation model fails to fully consider the dynamic coupling relationship between real-time interference intensity and network load rate, resulting in low resource utilization or increased overload risk; second, the resource conflict control mechanism between nodes is relatively simple and lacks effective modeling of the resource correlation constraints of adjacent nodes, which affects the stability and throughput performance of the overall network. Summary of the Invention

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

[0005] Therefore, the present invention provides a wireless ad hoc network adaptive anti-interference scheduling method to solve the problems of low resource utilization and poor network stability.

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

[0007] In a first aspect, the present invention provides a method for adaptive anti-interference scheduling in a wireless ad hoc network, which comprises:

[0008] The system collects service flows in a wireless ad hoc network in real time and monitors data environment parameters, including interference intensity and network load rate. The system calculates the basic resource rate using the Michaelis equation based on the interference intensity and dynamically adjusts the Michaelis equation parameters based on the network load rate to generate a dynamic total resource amount. An orthogonal ARU matrix is ​​constructed based on the dynamic total resource amount, and the ARU correlation coefficients of adjacent nodes are constrained using the Hadamard matrix to generate a conflict-free ARU allocation matrix. The system splits the service flow into atomic data blocks, maps the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generates a three-dimensional resource scheduling table. Anti-interference scheduling is performed based on the three-dimensional resource scheduling table, and bit error rate, end-to-end delay, and throughput indicators are collected to verify the interference suppression effect and optimize the scheduling, thereby generating an optimized anti-interference scheduling scheme.

[0009] As a preferred solution of the wireless ad hoc network adaptive anti-interference scheduling method of the present invention, the service flow includes a tactical instruction flow, a video flow and a sensor flow.

[0010] As a preferred solution of the wireless ad hoc network adaptive anti-interference scheduling method of the present invention, wherein: the monitoring data environment parameters, the specific steps are as follows:

[0011] Collect broadband noise interference, pulse interference and co-frequency interference, and obtain interference intensity through weighted summation;

[0012] Generate network load ratio by quantifying service resource requirements and combining physical layer capacity and processing latency;

[0013] The business resource requirements include tactical instruction flow requirements, video flow requirements and sensor flow requirements.

[0014] As a preferred solution of the wireless ad hoc network adaptive anti-interference scheduling method of the present invention, wherein: the basic resource rate is calculated using the Michaelis equation according to the interference intensity, and the Michaelis equation parameters are dynamically adjusted according to the network load rate to generate the dynamic resource total amount. The specific steps are as follows:

[0015] Read the total physical layer capacity of the wireless ad hoc network and initialize the parameters of the Michaelis equation based on the historical average interference intensity;

[0016] Based on the initialized Michaelis equation parameters, combined with the interference intensity and network load rate, the basic resource rate is calculated;

[0017] The network load rate threshold trigger mechanism is used to adjust the parameters of the Michaelis-Menten equation, and the total dynamic resource amount is obtained through the adjusted Michaelis-Menten equation parameters.

[0018] As a preferred solution of the wireless ad hoc network adaptive anti-interference scheduling method of the present invention, wherein: the orthogonal ARU matrix is ​​constructed according to the total amount of dynamic resources, and the ARU correlation coefficients of adjacent nodes are constrained by the Hadamard matrix to generate a conflict-free ARU allocation matrix. The specific steps are as follows:

[0019] The total amount of dynamic resources is processed by the resource quantization converter, and the number of ARU units is obtained by combining the rounding-up function;

[0020] Based on the number of ARU units, the time slot offset list, subcarrier group allocation table, and beam index codebook are obtained through resource block allocation and spatial beamforming, and the initial ARU matrix is ​​generated through assembly.

[0021] Based on the number of nodes in the initial ARU matrix, the Hadamard basis matrix is ​​matched to generate an orthogonalized ARU matrix, and a three-dimensional conflict detection report is generated through three-dimensional joint conflict detection.

[0022] The 3D conflict detection report is processed by the conflict resolution engine to generate a conflict-free allocation matrix.

[0023] As a preferred solution of the wireless ad hoc network adaptive anti-interference scheduling method of the present invention, the three-dimensional conflict joint detection includes time domain conflict detection, frequency domain conflict detection and space domain conflict detection.

[0024] As a preferred solution of the wireless ad hoc network adaptive anti-interference scheduling method of the present invention, wherein: the service flow is split into atomic data blocks, the atomic data blocks are mapped to the conflict-free ARU allocation matrix using the Hungarian algorithm, and a three-dimensional resource scheduling table is generated. The specific steps are as follows:

[0025] Split the business flow into atomic data blocks through a fixed block algorithm to generate an atomic data block set;

[0026] Based on the set of atomic data blocks, a data block cost matrix is ​​constructed, and the optimal mapping relationship is obtained through the Hungarian algorithm optimal matching;

[0027] The atomic data blocks are mapped to the conflict-free ARU allocation matrix through the optimal mapping relationship to generate a three-dimensional resource scheduling table.

[0028] In a second aspect, the present invention provides a wireless ad hoc network adaptive anti-interference scheduling system, comprising a data acquisition module, a metabolic calculation module, a matrix construction module, a service mapping module and an execution optimization module;

[0029] A data acquisition module is used to collect traffic in the wireless ad hoc network in real time and monitor data environment parameters, including interference intensity and network load rate;

[0030] The metabolic calculation module is used to calculate the basic resource rate using the Michaelis-Menten equation according to the interference intensity, and dynamically adjust the Michaelis-Menten equation parameters according to the network load rate to generate the dynamic total resource amount;

[0031] The matrix construction module is used to construct an orthogonal ARU matrix based on the total amount of dynamic resources and constrain the ARU correlation coefficients of adjacent nodes through the Hadamard matrix to generate a conflict-free ARU allocation matrix;

[0032] The service mapping module is used to split the service flow into atomic data blocks, map the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generate a three-dimensional resource scheduling table;

[0033] The execution optimization module is used to perform anti-interference scheduling according to the three-dimensional resource scheduling table, collect bit error rate, end-to-end delay and throughput indicators, verify the interference suppression effect and optimize the scheduling, and generate an optimized anti-interference scheduling plan.

[0034] Data acquisition module, metabolic calculation module, matrix construction module, business mapping module and execution optimization module;

[0035] A data acquisition module is used to collect traffic in the wireless ad hoc network in real time and monitor data environment parameters, including interference intensity and network load rate;

[0036] The metabolic calculation module is used to calculate the basic resource rate using the Michaelis-Menten equation according to the interference intensity, and dynamically adjust the Michaelis-Menten equation parameters according to the network load rate to generate the dynamic total resource amount;

[0037] The matrix construction module is used to construct an orthogonal ARU matrix based on the total amount of dynamic resources and constrain the ARU correlation coefficients of adjacent nodes through the Hadamard matrix to generate a conflict-free ARU allocation matrix;

[0038] The service mapping module is used to split the service flow into atomic data blocks, map the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generate a three-dimensional resource scheduling table;

[0039] The execution optimization module is used to perform anti-interference scheduling according to the three-dimensional resource scheduling table, collect bit error rate, end-to-end delay and throughput indicators, verify the interference suppression effect and optimize the scheduling, and generate an optimized anti-interference scheduling plan.

[0040] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the adaptive anti-interference scheduling method for wireless ad hoc networks as described in the first aspect of the present invention is implemented.

[0041] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the wireless ad hoc network adaptive anti-interference scheduling method as described in the first aspect of the present invention.

[0042] The beneficial effects of the present invention are as follows: by dynamically modeling resource rates through the Michaelis equation and adjusting parameters in real time in combination with the network load rate, the accuracy of resource allocation and the robustness of the system are improved; at the same time, the Hadamard matrix is ​​used to orthogonalize the ARU correlation of adjacent nodes to construct a conflict-free resource allocation matrix, which reduces the probability of multi-dimensional resource conflicts and improves spectrum reuse efficiency and network stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 The flowchart of the adaptive anti-interference scheduling method for wireless ad hoc networks.

[0045] Figure 2 Schematic diagram of the adaptive anti-interference scheduling system for wireless ad hoc networks.

[0046] Figure 3 Flowchart for generating a flow chart for a conflict-free ARU allocation matrix.

[0047] Figure 4 Flowchart for anti-interference scheduling execution and optimization. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0049] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0050] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0051] Reference Figures 1 to 4 , is an embodiment of the present invention, which provides a wireless ad hoc network adaptive anti-interference scheduling method, comprising the following steps:

[0052] S1: real-time collection of traffic flows in the wireless ad hoc network and monitoring of data environment parameters, including interference intensity and network load rate;

[0053] S1.1: Real-time acquisition of service flows in wireless ad hoc networks, including tactical command flows, video flows, and sensor flows;

[0054] Through deep packet inspection, the source IP (Internet Protocol) address, destination MAC (Media Access Control) address, and packet length in the packet header are analyzed and marked as tactical instruction streams. The arrival rate of statistical packets is calculated using a sliding time window analysis method, and the maximum allowable delay and urgency are extracted from the QoS (Quality of Service) field in the packet header.

[0055] The video stream is locked through transport layer port filtering and payload length. The bit rate is obtained based on the transmission interval and size of the data packet. The delay jitter is calculated based on the variance of the packet arrival timestamp. The resolution parameter in the video payload header of the video stream is parsed and divided by the base value to obtain the resolution factor.

[0056] The data packets and packet lengths are analyzed through the application layer protocol to identify sensor flows. The sampling frequency is calculated based on the inverse of the interval between consecutive data packets. The standard deviation of the payloads of the last 10 data packets is analyzed and the data validity period is extracted from the data packet header.

[0057] S1.2: Monitoring data environment parameters include interference intensity and network load rate;

[0058] Use a spectrum analyzer to select 8 sampling points symmetrically on both sides of the central operating frequency and record the received power. Perform 10 noise floor power measurements in a dedicated silent time slot and take the arithmetic average as the noise floor. Calculate the absolute difference between the received power at each sampling point and the noise floor, and take the arithmetic average to generate broadband noise interference. Perform a second-order differential operation on the instantaneous received power signal within a 10-microsecond time window, and record the maximum peak value of the differential result as pulse interference. Send a known test signal at three friendly operating frequencies. The receiver calculates the cross-correlation coefficient between the transmitted signal and the received signal, and takes the arithmetic average of the cross-correlation coefficients of the three frequency points as co-channel interference. The noise interference, pulse interference, and co-channel interference are weighted and summed to generate the interference intensity.

[0059] Based on the business resource requirements of business traffic, including tactical command flow requirements, video flow requirements and sensor flow requirements, combined with the physical layer capacity and processing delay, the network load rate is synthesized.

[0060] Obtain tactical command flow requirements based on the arrival rate, maximum allowable delay, and urgency of the tactical command flow; obtain video flow requirements based on the bit rate and delay jitter of the video flow; and generate sensor flow requirements by extracting the sampling frequency, data validity period, and data fluctuation standard deviation from the sensor flow.

[0061] The business resource requirements will be generated by weighted summing of tactical instruction flow requirements, video flow requirements and sensor flow requirements, and the network load rate will be synthesized by combining the physical layer capacity and processing delay.

[0062] S2: Calculates the basic resource rate using the Michaelis-Menten equation based on the interference intensity, and dynamically adjusts the Michaelis-Menten equation parameters based on the network load rate to generate a dynamic resource total.

[0063] S2.1: Read the total capacity of the physical layer and initialize the parameters of the Michaelis equation based on the historical average interference intensity;

[0064] Furthermore, the total capacity of the physical layer is loaded from the non-volatile memory, the historical average interference strength is obtained by calculating the arithmetic mean of the interference strength in the last 100 sampling cycles, and the parameters of the Michaelis equation are initialized according to the total capacity of the physical layer and the historical average interference strength, including the initial value of the maximum resource supply and the initial value of the half-saturation coefficient.

[0065] S2.2: Based on the initialized Michaelis equation parameters, combined with the interference intensity and network load rate, the basic resource rate is calculated. The expression is:

[0066] ;

[0067] in, is the basic resource rate, is the initial value of the maximum resource supply, is the interference intensity, is the curvature factor (range: [0.0, 10.0]), is the network load rate, is the network load rate threshold, is the initial value of the half-saturation coefficient, is the interference mutation sensitivity coefficient (the value range is [0.0, 1.0]), is the interference intensity gradient;

[0068] It should be noted that the network load rate of three hundred sampling cycles is continuously collected through the resource monitoring unit of the wireless ad hoc network node; the fast selection algorithm is called to perform the top five percentile calculation on the network load rate of the complete three hundred cycles, and the peak load characterization value is output; the network load rate subset of the last two hundred cycles is intercepted to perform the eightieth percentile calculation, and the steady-state load characterization value is output; based on the peak load characterization value and the steady-state load characterization value, the initial value of the network load threshold is obtained by weighted summation; the initial value of the network load threshold is input into the boundary protector, and the network load rate threshold is output.

[0069] S2.3: Use the network load rate threshold trigger mechanism to adjust the parameters of the Michaelis-Menten equation, and obtain the total dynamic resource amount based on the adjusted Michaelis-Menten equation parameters;

[0070] The network load rate value is input into the dual threshold comparator to generate the maximum resource supply:

[0071] When the network load rate exceeds the network load threshold, the maximum resource supply capacity is expanded;

[0072] When the network load rate is less than the network load threshold, the maximum resource supply is reduced.

[0073] The interference intensity array of the latest ten sampling periods is collected to obtain the interference intensity variance-mean ratio, and the semi-saturation coefficient is generated through coefficient superposition operation.

[0074] Substitute the adjusted Michaelis-Menten equation parameters into the Michaelis-Menten equation to generate the resource rate, and use the resource rate to obtain the total dynamic resource amount.

[0075] S3: Construct an orthogonal ARU matrix based on the total amount of dynamic resources, and constrain the ARU correlation coefficients of adjacent nodes using the Hadamard matrix to generate a conflict-free ARU allocation matrix;

[0076] S3.1: Process the total amount of dynamic resources through the resource quantization converter and combine it with the rounding function to obtain the number of ARU units;

[0077] Furthermore, the capacity of a single ARU (atomic resource unit) is read, the total amount of dynamic resources and the capacity of a single ARU are converted into numerical values ​​through floating-point processing, and an integer result is generated in combination with a rounding function. The integer result is input into the ARU allocation control unit and marked as the number of ARU units.

[0078] S3.2: Based on the number of ARU units, the time slot offset list, subcarrier group allocation table, and beam index codebook are obtained through resource block allocation and spatial beamforming, and the initial ARU matrix is ​​generated through assembly.

[0079] Time domain resource block allocation: The network topology information is obtained from the neighbor node list obtained from the routing protocol OSPF (Open Shortest Path First) / OLSR (Optimized Link State Routing). This network topology information is processed using a distributed graph coloring algorithm, and a time slot conflict graph is generated based on the neighbor node distance constraints. A greedy coloring strategy is used to allocate continuous time slot blocks to each node, ensuring that the time slot interval between adjacent nodes is greater than three times the length of a single time slot. The time slot block length is adjusted based on the maximum allowable delay in the service flow requirements, and a time slot offset list is generated.

[0080] Frequency domain resource block allocation: Fast Fourier transform is applied to spectrum scanning results to identify clean frequency bands with interference intensity below -100 decibel milliwatts. The best matching algorithm is executed to calculate the required number of subcarriers based on the service flow bit rate requirements. Contiguous non-overlapping subcarrier groups are allocated, prioritizing low-frequency resources to reduce path loss, and a subcarrier group allocation table is generated.

[0081] Spatial beamforming: A multiple signal classification algorithm is used to process the three-dimensional coordinate data of the node and calculate the direction of arrival of the target receiving node. The beam steering algorithm is used to generate a radiation pattern with the main lobe aligned with the target node and the null pointing to the strongest interference source. The optimal beam index is selected based on the antenna array response characteristics and a beam index codebook is generated.

[0082] The time slot offset list, subcarrier group allocation table and beam index codebook are assembled to generate the initial ARU matrix.

[0083] S3.3: Based on the number of nodes in the initial ARU matrix, match the Hadamard basis matrix to generate the orthogonalized ARU matrix, and perform three-dimensional conflict joint detection and three-dimensional conflict detection report;

[0084] The resource parameters of each node are processed using a binary vector encoding method. The time slot offset is converted into a binary time slot vector, the frequency band range is encoded as a frequency domain mask vector, and the beam index is mapped to a beam state vector. The Hadamard dot product calculation protocol is called to process all node vector pairs and perform correlation coefficient calculation. When the correlation coefficient exceeds 0.3, the random perturbation algorithm is activated to adjust the time slot offset of the conflicting node, and the encoding calculation is re-performed until all node pairs meet the orthogonality constraint (correlation coefficient < 0.3).

[0085] Three-dimensional conflict joint detection includes time domain conflict detection, frequency domain conflict detection and spatial domain conflict detection;

[0086] Furthermore, time domain conflict detection: the time slot overlap analysis algorithm is used to process the time slot offset list, calculate the time slot overlap percentage of any two neighboring nodes, and mark the conflicting node pairs with an overlap rate greater than 30%;

[0087] Frequency domain conflict detection: Apply the frequency band isolation verification method to process the subcarrier group allocation table, calculate the frequency band overlap ratio of adjacent nodes (number of overlapping subcarriers / total number of subcarriers), and mark conflicting node pairs with an overlap ratio greater than 15%;

[0088] Spatial conflict detection: Execute the beam spatial angle calculation method to process the beam index codebook, calculate the main lobe axis angle using the direction cosine formula, and mark conflicting node pairs with angles less than 30 degrees;

[0089] All conflicting node pairs are organized into a conflicting node pair list, and a three-dimensional conflict detection report is generated.

[0090] S3.4: Process the 3D conflict detection report through the conflict resolution engine to generate a conflict-free ARU allocation matrix;

[0091] It should be noted that the list of conflicting node pairs in the three-dimensional conflict detection report is read; for time domain conflicts, the time slot offset adjuster is called to perform random perturbation of the time slot offset; for frequency domain conflicts, the frequency point reallocator is called to perform suboptimal clean frequency band selection; for spatial domain conflicts, the beam optimizer is called to perform main lobe fine-tuning and zero-steering enhancement to generate adjusted resource parameters; based on the adjusted resource parameters, the node resource records are reconstructed through resource reorganization, and triple real-time verification is performed through conflict elimination verification to generate a conflict-free ARU allocation matrix.

[0092] S4: Split the service flow into atomic data blocks, map the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generate a three-dimensional resource scheduling table;

[0093] S4.1: Split the service flow into atomic data blocks using a fixed block algorithm to generate an atomic data block set;

[0094] Furthermore, the service flow is processed through a fixed block algorithm, and the number of blocks is calculated based on the single ARU capacity value to generate atomic data blocks. The timestamp marker is called to add a generation timestamp for each atomic data block; the transmission deadline is calculated for each atomic data block based on the service priority and the maximum allowable delay value; and a set of atomic data blocks with priority tags is generated.

[0095] S4.2: Based on the set of atomic data blocks, a data block cost matrix is ​​constructed and the optimal mapping relationship is obtained through the Hungarian algorithm optimal matching;

[0096] Furthermore, the timestamp, transmission deadline and service priority in the atomic data block set are obtained; the time slot start time, frequency band position and beam index parameters in the conflict-free ARU allocation matrix are read; the Euclidean distance between the data block source node position and the ARU node position is obtained, and the delay margin value is calculated in combination with the atomic data block deadline and the time slot start time; the weighted comprehensive evaluation model is applied to integrate the Euclidean distance, delay margin value and service priority to generate a cost value; the two-dimensional matrix is ​​filled with the atomic data block index as the row and the ARU resource index as the column to generate a data block cost matrix.

[0097] It should be noted that service priorities include tactical command stream priority, video stream priority, and sensor stream priority:

[0098] Tactical instruction flow priority: Deep packet inspection is used to parse the QoS field in the data packet header and extract the urgency level (such as level 0-3). The urgency level is directly mapped to the tactical instruction flow priority.

[0099] Video stream priority: Combines the stream type identifier and resolution factor in the packet header QoS field, calculates the priority weight through a weighted formula, and generates the video stream priority;

[0100] Sensor flow priority: Based on the validity period field and sampling frequency in the data packet header, the sensor flow priority is generated by using the reciprocal function conversion;

[0101] The generated priority tag is an integer value from 0 to 7, which is used for transmission queue sorting during atomic data block packaging and cost matrix calculation during Hungarian algorithm mapping, ensuring that high-priority services are given priority in low-latency resource allocation.

[0102] Based on the data block cost matrix, row reduction and column reduction operations are performed, and the positions of independent zero elements in the data block cost matrix are marked using the minimum line cover method; when the number of covering lines is equal to the order of the data block cost matrix, the initial matching solution is output; when the number of covering lines is less than the matrix order, the minimum value of the uncovered area is located; all elements of the uncovered rows are subtracted from the minimum value and all elements of the covered columns are added with the minimum value; the zero element cover test is re-executed until the minimum value of the uncovered area is located when the number of covering lines is less than the matrix order; the conflicting items in the mapping relationship are detected whose time slot end time is later than the atomic data block deadline; the backup ARU resource record is called to reallocate the conflicting atomic data blocks to generate the optimal mapping relationship table.

[0103] S4.3: Map the atomic data blocks to the conflict-free ARU allocation matrix through the optimal mapping relationship to generate a three-dimensional resource scheduling table;

[0104] Furthermore, the correspondence between the atomic data block identifier and the ARU resource identifier in the optimal mapping relationship table is parsed; the conflict-free ARU allocation matrix is ​​retrieved to obtain the time slot window parameters, frequency band channel parameters and beam index parameters of the corresponding ARU resources; the source node identifier, priority parameter and deadline parameter in the atomic data block set are extracted; the resource allocation sequence is reorganized in ascending order of the time slot start time through the time axis sorting algorithm; the frequency domain code converter is applied to convert the subcarrier group center frequency point into a physical channel number; the beam index code book is integrated to generate a spatial dimension control instruction set; the time slot window range, physical channel number, beam index value, and atomic data block characteristic parameters are encapsulated to generate a structured scheduling record; the scheduling period identifier is added and the cyclic redundancy check code is calculated for the complete scheduling table; and the binary data stream of the three-dimensional resource scheduling table with the check code is output.

[0105] S5: Execute anti-interference scheduling based on the three-dimensional resource scheduling table, collect bit error rate, end-to-end delay, and throughput indicators, verify the interference suppression effect and optimize scheduling, and generate an optimized anti-interference scheduling plan;

[0106] The time slot window range, physical channel number and beam index value parameters in the three-dimensional resource scheduling table are read as the parameters of the three-dimensional resource scheduling table; the wireless transceiver is controlled to perform data transmission operations according to the parameters of the three-dimensional resource scheduling table; the bit error rate is collected by the bit error rate detection circuit at the receiving end; the end-to-end delay is calculated by the timestamp comparison method; the throughput is counted by the data packet counter; the bit error rate, end-to-end delay and throughput input threshold comparator are compared with the preset performance threshold; the scheduling optimization engine is activated when any indicator exceeds the preset performance threshold; the scheduling optimization engine adjusts the time slot offset, frequency band position and beam index parameters in the conflict-free ARU allocation matrix; and the optimized anti-interference scheduling scheme is regenerated.

[0107] It should be noted that the service priority and maximum allowable delay in the service flow are read; the service quality level specification table is queried according to the service priority to obtain the corresponding bit error rate threshold; the end-to-end delay threshold is calculated based on the maximum allowable delay; and the throughput threshold is derived by referring to the theoretical maximum throughput of the physical layer and combining it with the service priority.

[0108] This embodiment also provides a wireless ad hoc network adaptive anti-interference scheduling system, including: a data acquisition module, a metabolic calculation module, a matrix construction module, a service mapping module and an execution optimization module;

[0109] A data acquisition module is used to collect traffic in the wireless ad hoc network in real time and monitor data environment parameters, including interference intensity and network load rate;

[0110] The metabolic calculation module is used to calculate the basic resource rate using the Michaelis-Menten equation according to the interference intensity, and dynamically adjust the Michaelis-Menten equation parameters according to the network load rate to generate the dynamic total resource amount;

[0111] The matrix construction module is used to construct an orthogonal ARU matrix based on the total amount of dynamic resources and constrain the ARU correlation coefficients of adjacent nodes through the Hadamard matrix to generate a conflict-free ARU allocation matrix;

[0112] The service mapping module is used to split the service flow into atomic data blocks, map the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generate a three-dimensional resource scheduling table;

[0113] The execution optimization module is used to perform anti-interference scheduling according to the three-dimensional resource scheduling table, collect bit error rate, end-to-end delay and throughput indicators, verify the interference suppression effect and optimize the scheduling, and generate an optimized anti-interference scheduling plan.

[0114] This embodiment also provides a computer device, which is applicable to the case of the adaptive anti-interference scheduling method for wireless ad hoc networks, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the adaptive anti-interference scheduling method for wireless ad hoc networks proposed in the above embodiment.

[0115] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0116] This embodiment also provides a storage medium having a computer program stored thereon. When the program is executed by a processor, the method for implementing adaptive anti-interference scheduling in a wireless ad hoc network as proposed in the above embodiment is implemented. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0117] In summary, the present invention improves the accuracy of resource allocation and system robustness by: dynamically modeling resource rates using the Michaelis equation and adjusting parameters in real time in combination with the network load rate; at the same time, using the Hadamard matrix to orthogonalize the ARU correlation between adjacent nodes to construct a conflict-free resource allocation matrix, thereby reducing the probability of multi-dimensional resource conflicts and improving spectrum reuse efficiency and network stability.

[0118] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for adaptive anti-interference scheduling in a wireless ad hoc network, characterized by: include, Real-time collection of traffic flows in wireless ad hoc networks and monitoring of data environment parameters, including interference intensity and network load rate; The basic resource rate is calculated using the Michaelis-Menten equation based on the interference intensity, and the parameters of the Michaelis-Menten equation are dynamically adjusted according to the network load rate to generate a dynamic total resource amount. An orthogonal ARU matrix is ​​constructed based on the total amount of dynamic resources, and the ARU correlation coefficients of adjacent nodes are constrained by the Hadamard matrix to generate a conflict-free ARU allocation matrix. Split the service flow into atomic data blocks, map the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generate a three-dimensional resource scheduling table; Anti-interference scheduling is performed according to the three-dimensional resource scheduling table. Bit error rate, end-to-end delay and throughput indicators are collected to verify the interference suppression effect and optimize scheduling, and generate an optimized anti-interference scheduling plan.

2. The method for adaptive anti-interference scheduling in a wireless ad hoc network according to claim 1, wherein: The business flow includes a tactical instruction flow, a video flow and a sensor flow.

3. The method for adaptive anti-interference scheduling in a wireless ad hoc network according to claim 2, wherein: The specific steps of monitoring data environment parameters are as follows: Collect broadband noise interference, pulse interference and co-frequency interference, and obtain interference intensity through weighted summation; Generate network load ratio by quantifying service resource requirements and combining physical layer capacity and processing latency; The business resource requirements include tactical instruction flow requirements, video flow requirements and sensor flow requirements.

4. The method for adaptive anti-interference scheduling in a wireless ad hoc network according to claim 3, wherein: The basic resource rate is calculated using the Michaelis equation according to the interference intensity, and the Michaelis equation parameters are dynamically adjusted according to the network load rate to generate the dynamic resource total amount. The specific steps are as follows: Read the total physical layer capacity of the wireless ad hoc network and initialize the parameters of the Michaelis equation based on the historical average interference intensity; Based on the initialized Michaelis equation parameters, combined with the interference intensity and network load rate, the basic resource rate is calculated; The network load rate threshold trigger mechanism is used to adjust the parameters of the Michaelis-Menten equation, and the total dynamic resource amount is obtained through the adjusted Michaelis-Menten equation parameters.

5. The method for adaptive anti-interference scheduling in a wireless ad hoc network according to claim 4, wherein: The orthogonal ARU matrix is ​​constructed based on the total amount of dynamic resources, and the ARU correlation coefficients of adjacent nodes are constrained by the Hadamard matrix to generate a conflict-free ARU allocation matrix. The specific steps are as follows: The total amount of dynamic resources is processed by the resource quantization converter, and the number of ARU units is obtained by combining the rounding-up function; Based on the number of ARU units, the time slot offset list, subcarrier group allocation table, and beam index codebook are obtained through resource block allocation and spatial beamforming, and the initial ARU matrix is ​​generated through assembly. Based on the number of nodes in the initial ARU matrix, the Hadamard basis matrix is ​​matched to generate an orthogonalized ARU matrix, and a three-dimensional conflict detection report is generated through three-dimensional joint conflict detection. The 3D conflict detection report is processed by the conflict resolution engine to generate a conflict-free allocation matrix.

6. The method for adaptive anti-interference scheduling in a wireless ad hoc network according to claim 5, wherein: The three-dimensional conflict joint detection includes time domain conflict detection, frequency domain conflict detection and space domain conflict detection.

7. The method for adaptive anti-interference scheduling in a wireless ad hoc network according to claim 1, wherein: The business flow is split into atomic data blocks, and the atomic data blocks are mapped to the conflict-free ARU allocation matrix using the Hungarian algorithm to generate a three-dimensional resource scheduling table. The specific steps are as follows: Split the business flow into atomic data blocks through a fixed block algorithm to generate an atomic data block set; Based on the set of atomic data blocks, a data block cost matrix is ​​constructed, and the optimal mapping relationship is obtained through the Hungarian algorithm optimal matching; The atomic data blocks are mapped to the conflict-free ARU allocation matrix through the optimal mapping relationship to generate a three-dimensional resource scheduling table.

8. A wireless ad hoc network adaptive anti-interference scheduling system, based on the wireless ad hoc network adaptive anti-interference scheduling method according to any one of claims 1 to 7, characterized in that: Including data acquisition module, metabolic calculation module, matrix construction module, business mapping module and execution optimization module; A data acquisition module is used to collect traffic in the wireless ad hoc network in real time and monitor data environment parameters, including interference intensity and network load rate; The metabolic calculation module is used to calculate the basic resource rate using the Michaelis-Menten equation according to the interference intensity, and dynamically adjust the Michaelis-Menten equation parameters according to the network load rate to generate the dynamic total resource amount; The matrix construction module is used to construct an orthogonal ARU matrix based on the total amount of dynamic resources and constrain the ARU correlation coefficients of adjacent nodes through the Hadamard matrix to generate a conflict-free ARU allocation matrix; The service mapping module is used to split the service flow into atomic data blocks, map the atomic data blocks to the conflict-free ARU allocation matrix using the Hungarian algorithm, and generate a three-dimensional resource scheduling table; The execution optimization module is used to perform anti-interference scheduling according to the three-dimensional resource scheduling table, collect bit error rate, end-to-end delay and throughput indicators, verify the interference suppression effect and optimize the scheduling, and generate an optimized anti-interference scheduling plan.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the wireless ad hoc network adaptive anti-interference scheduling method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the wireless ad hoc network adaptive anti-interference scheduling method according to any one of claims 1 to 7 are implemented.

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