An artificial intelligence-based communication equipment command and dispatch system

Abstract

The application relates to the technical field of wireless communication, and discloses a communication equipment command and dispatch system based on artificial intelligence. The system maps the state of a communication equipment into a standardized carrier phase disturbance mode, controls a radio frequency front end to inject the disturbance mode after adaptive adjustment of the disturbance mode is performed in combination with channel noise sensing and conflict arbitration logic, and adjacent communication equipment directly detects the disturbance mode by monitoring a physical error signal of a carrier synchronization loop of the adjacent communication equipment to trigger a cooperative dispatch action. The application constructs an implicit cooperation mode based on a physical layer beacon, avoids complex high-layer signaling interaction required by a traditional dispatch, brings the cooperative response time between equipment from the millisecond level determined by a software protocol to the microsecond level determined by a hardware physical layer response decision, and enables the system to maintain reliable transmission of a dispatch instruction when facing high-density concurrent conflicts and strong channel noise, thereby providing a technical implementation path for super-low-delay high-reliability communication.

Description

TECHNICAL FIELD

[0001] The application relates to an artificial intelligence-based communication device command and dispatch system and belongs to the technical field of wireless communication. BACKGROUND

[0002] In the current wireless communication network design, whether it is a public cellular network or a special network for a specific industry, the command and dispatch generally follows a decision-centralized operation mode, that is, a central node with global information and powerful computing capability, such as a base station or a cloud server, is used to uniformly collect the state information of each communication device in the network, and a decision is made based on a preset dispatch algorithm or an artificial intelligence model, and then the instruction is issued to each device for execution. This mode ensures the orderliness of resource allocation in the early development stage when the number of network nodes is limited and the business type is relatively single. However, with the evolution of application scenarios to the fields such as vehicle networking and industrial Internet of Things, which have massive device access, high dynamic topology change and strict requirements for collaborative delay, the inherent and inherent limitations of the above-mentioned centralized dispatch mode due to its architectural design have become increasingly prominent, and have gradually become a common technical bottleneck restricting the overall performance improvement and application boundary expansion of the network.

[0003] The reason is that any inter-device collaboration requirement, such as the instantaneous interaction required by two high-speed running cars to avoid collision, must go through the round trip of local device-center node-local device for its decision information flow. The delay caused by this inherent communication detour is unacceptable for safety-critical applications. At the same time, in order to maintain the so-called global view of the center node, a large number of devices must periodically report their own state to the center, which will form a continuous signaling overhead when the network scale is large. Not only does it occupy valuable spectrum resources, but also makes the computing and connection load of the center node approach its physical limit, thereby limiting the scalability of the entire network.

[0004] Specifically, the prior art mainly has the following deficiencies: 1. In the emergency coordination scene requiring microsecond-level response, the inherent communication and decision delay of the existing centralized scheduling mode constitutes an inherent safety risk; 2. The huge signaling overhead generated by a large number of devices to maintain the connection with the center and the state synchronization leads to the waste of wireless spectrum resources and becomes a direct bottleneck limiting the network capacity and terminal access scale; the existing mode degrades a large number of edge devices to simple data probes and instruction executors, systematically idling the growing local computing power of these devices, resulting in waste of network resources. Therefore, how to avoid the traditional mode of information transfer and decision-making through the center node, and establish a localized coordination mechanism between communication devices that responds almost instantaneously without additional signaling overhead, so as to meet the needs of large-scale high-dynamic network while fully utilizing the inherent hardware capabilities of the device, has become a technical problem to be solved by the present application. SUMMARY

[0005] The present application provides a communication device command scheduling system based on artificial intelligence, which mainly aims to solve the problems of high communication delay, large signaling overhead and waste of edge resources in the existing centralized scheduling mode.

[0006] To achieve the above purpose, the present application provides a communication device command scheduling system based on artificial intelligence, which is configured in a communication device in a wireless communication network, and the system comprises:

[0007] A state mapping module is configured to associate the current business state or resource state of the communication device with a corresponding standardized carrier phase perturbation mode in a mapping table in which the business state or resource state is associated with the standardized carrier phase perturbation mode.

[0008] A channel noise sensing module is configured to determine a noise floor index reflecting the background noise level of the channel during the channel quiet period by monitoring the error signal of the carrier synchronization loop of the communication device, and output the noise floor index to the state mapping module, so that it selects a perturbation mode suitable for the noise floor index from at least two standardized carrier phase perturbation modes with different robustness levels based on the noise floor index.

[0009] A conflict arbitration module is configured to first listen to the communication channel to determine whether there is an existing perturbation mode before entering the standardized carrier phase perturbation mode corresponding to the high-priority business state. If it is determined that there is, at least one least significant bit of the local hardware clock counter of the communication device is read, and a backoff delay time in microseconds is determined according to the value of the at least one least significant bit.

[0010] a signal injection module, connected with the state mapping module and the conflict arbitration module, configured to control the radio frequency front end of the communication device to inject a selected standardized carrier phase perturbation pattern on the carrier of the communication signal sent out, when the conflict arbitration module does not judge that there exists the same existed perturbation pattern or after the back-off delay time;

[0011] a perturbation detection module, configured to detect whether there exists a standardized carrier phase perturbation pattern on the carrier of the communication signal received from the neighboring communication device by monitoring the error signal of the carrier synchronization loop of itself;

[0012] a cooperative response module, connected with the perturbation detection module, configured to execute a preset cooperative scheduling action based on the standardized carrier phase perturbation pattern detected by the perturbation detection module.

[0013] Preferably, the state mapping module is configured to select a mapping table in which the high priority service state is mapped to a first specific pattern of phase perturbation and the low energy resource state is mapped to a second specific pattern of phase perturbation; the perturbation amplitude, frequency or waveform of the first specific pattern of phase perturbation is different from that of the second specific pattern of phase perturbation.

[0014] Preferably, the conflict arbitration module is configured to determine the back-off delay time by mapping the binary value of the at least one least significant bit of the local hardware clock counter directly or after scaling by a preset linear scaling factor to a time value in microseconds, so as to convert the clock micro-unsynchronization inherent in the communication device hardware into a back-off delay for realizing distributed, non-coordinated conflict resolution or having individual uniqueness.

[0015] Preferably, the channel noise perception module and the state mapping module are further configured to: select a standard perturbation pattern with a first amplitude when the noise floor index is lower than a first preset threshold; select an enhanced perturbation pattern with a second amplitude when the noise floor index is between the first preset threshold and a second preset threshold, wherein the second amplitude is greater than the first amplitude; select a high-robustness perturbation pattern with the second amplitude and a composite waveform feature when the noise floor index is higher than the second preset threshold.

[0016] Preferably, the system further comprises a transmission link health self-checking module, which is configured to: when the signal injection module injects the standardized carrier phase perturbation pattern, monitor the envelope of the transmission signal synchronously by a power detector to obtain an unintended amplitude modulation energy, and calculate the transmission link health index according to the following relationship , , an unexpected magnitude modulation energy, an expected energy of the standardized carrier phase perturbation injected by the signal injection module; a transmission link health index is used to assess whether the radio frequency power amplifier of the communication device has nonlinear distortion.

[0017] Preferably, the perturbation detection module is further configured to compare the instantaneous value of the error signal of its own carrier synchronization loop with a preset perturbation detection threshold by a hardware comparator, and directly trigger a hardware interrupt to the cooperative response module when the error signal is determined to exceed the perturbation detection threshold and its variation law conforms to the preset waveform template of any standardized carrier phase perturbation mode.

[0018] Preferably, the cooperative response module is configured to perform a preset cooperative scheduling action, specifically, when the perturbation detection module detects a standardized carrier phase perturbation mode representing a high-priority service state, the cooperative response module immediately controls the communication device to reduce the transmission power of its own non-safety-critical service or suspend transmission in the direction of the signal source.

[0019] Preferably, the system further comprises a neighborhood physical connectivity verification module configured to periodically control the signal injection module to inject and broadcast a phase detection pulse with device uniqueness and non-standardization on the carrier of the communication device; and control the perturbation detection module to monitor the communication signal from the neighboring communication device in the subsequent period to detect whether there is an embedded phase echo feature in the communication signal as a response to the phase detection pulse, and based on the detection result, confirm the instant connectivity of the physical channel with the neighboring communication device.

[0020] Preferably, the neighborhood physical connectivity verification module is further configured to control the neighboring communication device to embed a phase echo feature related to the waveform of the received phase detection pulse in the preamble part of the communication signal when it transmits the communication signal next time after receiving the phase detection pulse, so as to achieve a zero-overhead physical existence response in an information piggybacking manner.

[0021] Preferably, the system further comprises a receiving link health diagnosis module configured to control the signal injection module to synchronously inject a standardized or high-frequency phase jitter excitation pulse while injecting the standardized carrier phase perturbation mode; and control the perturbation detection module to monitor the severity of the response feature of its own carrier synchronization loop to the phase jitter excitation pulse while detecting the standardized carrier phase perturbation mode, so as to determine its own power supply stability state, and adjust its subsequent cooperative scheduling behavior based on the power supply stability state, for example, actively reduce the priority of participating in cooperative tasks when the power supply stability state is determined to be lower than a preset health threshold.

[0022] Compared with the prior art, the beneficial effects of the present application are:

[0023] 1. By directly encoding the high-level service or resource state of the communication device into a standardized phase disturbance pattern of the communication signal carrier, and directly detecting the disturbance pattern by the hardware physical layer of the adjacent device to trigger a coordinated response, an implicit coordination mode based on the physical layer beacon is established, which avoids the complete process of signaling encapsulation, transmission, demodulation and decoding through the high-level software protocol stack to realize inter-device coordination in traditional wireless communication, thereby bringing the response time of the coordination decision from the millisecond level determined by software and network transmission to the microsecond level determined by the hardware physical layer response, providing a technical implementation path with low delay characteristics at the working principle level for application scenarios such as vehicle networking collision avoidance and industrial real-time control, which have strict requirements on time determinacy; and before entering the phase disturbance corresponding to the high priority state, the channel is first listened to to perceive and conflict, and when a conflict is perceived, the unique clock counter value of each device is used as the basis for generating a microsecond-level backoff delay time, which converts a ubiquitous hardware flaw into an endogenous random source that does not require any additional algorithms and negotiations, enabling multiple devices to naturally form an ordered transmission sequence on the microscale of time in high-density high-concurrency conflict scenarios. This approach avoids the complex random backoff algorithm or signaling coordination in traditional multiple access control protocols, and does not increase the computational overhead and hardware cost, so that the entire coordinated communication system exhibits group robustness when under pressure, ensuring effective transmission of critical information.

[0024] 2. By multiplexing the error signal of the carrier synchronization loop during the channel quiet period to quantize the channel background noise level in real time and at no cost, and dynamically adjusting the amplitude and waveform complexity of the subsequent injected phase disturbance pattern based on the noise level, this design enables the communication device of the present system to perceive and actively adapt to its electromagnetic environment. Instead of responding to all working conditions with a fixed signal pattern, it can communicate in the most energy-efficient way when the channel environment is pure, and automatically switch to a more robust signal pattern to ensure the reliability of coordination when entering a strong interference environment such as a factory. This endogenous, closed-loop adaptive mechanism not only expands the application range of the present application in various complex working conditions, but also realizes intelligent on-demand allocation of network energy efficiency.

[0025] 3. By introducing a transmit link health self-check module and a receive link health diagnosis module, each phase-disturbance-based collaborative communication process becomes a bidirectional health check of the physical hardware status of both the transmitter and receiver. The transmitter can self-examine the aging status of its RF power amplifier by monitoring the unexpected amplitude modulation accompanying the injection of its own phase-locked loop signal. At the same time, by synchronously injecting a standardized phase jitter excitation pulse into the signal, the receiver can actively detect and judge the stability of its own power supply by analyzing the response characteristics of its own phase-locked loop to this excitation. This communication-as-diagnosis approach enables devices in the network to identify potential failure risks caused by hardware aging without any additional diagnostic protocols and signaling overhead. This provides a technical foundation for predictive maintenance of large-scale, low-cost networks and the establishment of intelligent scheduling based on physical layer trust. Attached Figure Description

[0026] Fig. 1 This is a schematic diagram of the functional module structure of the present invention;

[0027] Fig. 2 This is a schematic diagram illustrating the change of the transmission link health index of the present invention over operating time;

[0028] Fig. 3 This is a schematic diagram of the workflow of the command and dispatch system of the present invention.

[0029] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0031] The application discloses a communication equipment command and dispatching system based on artificial intelligence, and the core of the application is to construct an implicit cooperative communication mechanism based on a physical layer beacon, which does not depend on the interaction of a high-layer software protocol stack, and the system is configured in a communication equipment in a wireless communication network, and the functions of the system are cooperatively realized by a state mapping module, a channel noise sensing module, a conflict arbitration module, a signal injection module, a disturbance detection module and a cooperative response module, the whole working process starts from the identification of the business or resource state of the equipment itself by the state mapping module, after the adaptive adjustment of the channel environment and the distributed arbitration of potential sending conflicts, the state information is encoded into a standardized carrier phase disturbance mode by the signal injection module, and the disturbance detection module of the adjacent equipment directly detects the mode at the hardware level, and then the cooperative response module executes the preset scheduling action, so as to form an end-to-end low-delay cooperative loop.

[0032] The state mapping module is internally configured with a gradient boosting decision tree (GBDT) model trained offline, which is a machine learning classification algorithm for integrated learning by combining multiple weak decision trees; the model takes the channel noise base index and the transmission link health index and the business priority as an input vector, and directly specifies a disturbance mode index selected from a preset mode library as an output, the mode library is composed of a group of mutually orthogonal Walsh-Hadamard codes, the Walsh-Hadamard code is a sequence composed of +1 and -1, and is used to generate a carrier phase modulation pattern with high discrimination; and the training labels of the GBDT model are batch generated by solving an optimization objective function under a large number of simulation scenarios, the objective of the function is to maximize the transmission success rate of the key instruction and minimize the error vector magnitude of the main communication link, wherein and are preset weight coefficients.

[0033] When the signal injection module injects any standardized carrier phase disturbance mode with an index , the injection amplitude is not arbitrarily set, but is determined by an upper limit of an offline calibration procedure based on the performance constraint of the main communication link , the core of the procedure is to quantify the influence of disturbance injection on the demodulation performance of the main data stream, and the influence is characterized by the error vector magnitude , which is a measure of the difference between the actual received signal constellation point and the ideal constellation point; the specific calibration steps are as follows: first, a disturbance-free reference communication link is established under a standard signal-to-noise ratio condition, and the maximum error vector magnitude threshold that can be tolerated by the main data business is set , then, for each perturbation pattern in the pattern library , the injection amplitude is gradually increased from zero , and the real-time measurement of the main data link is monitored synchronously , when , the value of the first time reaches or exceeds , the injection amplitude at this moment , is recorded as the running maximum amplitude of the pattern , and is solidified in the device configuration parameters for the signal injection module to call.

[0034] In a typical vehicle-to-vehicle collision avoidance application scenario, when the emergency braking system of vehicle A is activated, i.e. a high-priority service state that needs to be broadcast immediately is generated, given the inherent millisecond-level delay of the traditional communication mode via the round-trip path of the center node, which is insufficient for avoiding the risk of instantaneous collision in high-speed driving. To address this challenge, the state mapping module in the system is configured to respond immediately to this high-priority service state, select a phase perturbation representing a first specific pattern of emergency braking warning from a mapping table that associates service states with standardized carrier phase perturbation patterns, which is solidified in the device memory, and its data structure is an associative array, where the key is the enumeration value of the internal service state of the device, and the value is a data structure that defines the parameters of the perturbation waveform such as frequency, amplitude, modulation sequence, thereby directly anchoring the high-level service semantics to a physically realizable signal form.

[0035] Before injecting the signal, the system needs to evaluate the electromagnetic environment of the current channel to ensure the reliability of signal transmission. For this purpose, the channel noise perception module is configured to determine a noise floor index reflecting the background noise level of the channel during the channel quiet period by monitoring the error signal of the carrier synchronization loop of the communication device itself. The specific calculation procedure of the noise floor index is as follows: in the continuous non-signal receiving time slots, the error voltage signal output by the phase discriminator of the carrier synchronization loop is sampled at high speed, and the root mean square value of the signal in the preset time window is calculated. This root mean square value is quantified as the noise floor index. The state mapping module then adaptively selects from at least two standardized carrier phase perturbation patterns with different robustness levels based on the noise floor index, and the determination procedure is defined as follows: when the noise floor index is below the first preset threshold, it indicates that the channel environment is pure, and the standard perturbation pattern with the first amplitude is selected to optimize energy efficiency; when the index is between the first and second preset thresholds, the enhanced perturbation pattern with the second amplitude is selected, where the second amplitude is greater than the first amplitude; when the index is higher than the second preset threshold, a high-robustness perturbation pattern with the second amplitude and specific waveform characteristics is selected to resist strong noise interference. In this way, the system has the endogenous adaptive ability to dynamically adjust the signal mode according to the real-time channel quality.

[0036] Furthermore, in a dense traffic environment, multiple vehicles may trigger emergency braking in quick succession, if multiple devices inject the same disturbance pattern into the channel at the same time, it will likely cause mutual interference of signals, to avoid such high-density concurrent collision, the collision arbitration module is configured to listen to the communication channel before injecting the disturbance pattern corresponding to the high-priority service state, to determine whether there is a same disturbance pattern, if the channel is clear, the signal injection module immediately performs injection; if it is determined that there is a collision, the collision arbitration module reads at least one least significant bit of the local hardware clock counter of the communication device, and maps the read binary value to a backoff delay time in microseconds after scaling by a preset linear scaling factor. Due to the inherent microscopic asynchronization of hardware clocks of different devices, this mechanism utilizes this hardware feature to transform a completely distributed collision resolution random source without signaling, so that each colliding device can autonomously form an ordered transmission sequence on the microsecond time scale.

[0037] After the above adaptive selection and collision arbitration process, the signal injection module controls the radio frequency front end of the communication device to inject the selected standardized carrier phase disturbance pattern on the carrier of the communication signal transmitted outwardly. At this time, the communication device of the adjacent vehicle B, when receiving the communication signal from vehicle A, the carrier synchronization loop of its own generates a corresponding error signal due to tracking the disturbed carrier. The disturbance detection module continuously compares the instantaneous value of the error signal with a preset disturbance detection threshold value through a hardware comparator. When it is determined that the error signal exceeds the threshold value and its change rule matches any preset waveform template of the standardized carrier phase disturbance pattern, a hardware interrupt is triggered to the cooperative response module. This detection method based on hardware comparison and interrupt bypasses the software demodulation and decoding process, and brings the response time to the microsecond level.

[0038] Finally, the cooperative response module, upon receiving the hardware interrupt, performs the preset cooperative scheduling action based on the detected disturbance pattern representing the high-priority service state. For example, when detecting the emergency braking pattern, the cooperative response module immediately controls the communication system of the vehicle to reduce the transmission power of non-safety-critical services or suspend transmission in the direction of the signal source, to give channel resources to the critical safety information of vehicle A. At the same time, the module can also deliver this alarm information to the automatic driving or assisted driving system of the vehicle through the vehicle bus, to trigger the corresponding avoidance action, thereby completing a complete implicit cooperative scheduling.

[0039] To further enhance the robustness and maintainability of the system, the system can also integrate a transmission link health self-checking module and a receiving link health diagnosis module. When a phase disturbance is injected, the transmission link health self-checking module synchronously monitors the envelope of its own transmitted signal through a power detector to capture the unexpected amplitude modulation energy generated by the non-linear distortion of the radio frequency power amplifier , and calculates the transmission link health index according to the relationship , wherein is the expected energy of the injected phase disturbance. The index can be used to evaluate the aging state of the power amplifier in real time. At the same time, the signal injection module can also synchronously inject a standardized and high-frequency phase jitter excitation pulse. The receiving link health diagnosis module at the receiving end infers the stability state of its own power supply by monitoring the severity of the response characteristics of the carrier synchronization loop to the excitation pulse, and actively reduces the priority of participating in collaborative tasks when the stability is lower than the preset health threshold. This communication and diagnosis mechanism enables network devices to predictively identify potential failure risks of hardware without additional signaling overhead.

[0040] Embodiment 1: The technical solution of the present application in a continuously running high-density automated warehouse environment, the specific operation example is as follows, the characteristics of this environment are that hundreds of autonomous mobile robots work collaboratively in a compact space and the running space is filled with strong electromagnetic interference generated by motors, control cabinets and metal shelves, which poses an objective challenge to the delay and reliability of collaborative action between robots; in this scenario, a robot A carrying a high-priority order needs to pass through a core passage where multiple robot trajectories intersect, and the communication link delay of the request and instruction of the traditional centralized scheduling-based communication mode for obtaining reliable passage right will force the system to systematically reduce the running speed of all robots to reserve safety redundancy, which contradicts the logistics efficiency pursued by the warehouse system; at the same time, the radio frequency power amplifier of another robot B appears early non-linear distortion due to long-time operation, which is a physical layer health state deterioration that cannot be perceived by the upper software protocol.

[0041] ​When robot A approaches the core passage, its state mapping module selects a high-priority passage state according to a preset mapping table, and selects a first specific mode of phase disturbance. Since the channel noise sensing module has determined that the noise floor index of the current passage is higher than a second preset threshold by analyzing the carrier synchronization loop error signal, the state mapping module automatically adjusts the disturbance mode to a high-robustness form with a composite waveform feature. This adjustment enables the subsequent conflict arbitration module to effectively listen to and utilize the hardware clock-based backoff mechanism to inject a conflict-free transmission time slot for the disturbance signal of robot A in a strong noise background. The disturbance detection module of other robots in the adjacent area detects the high-robustness disturbance mode representing a high-priority passage in microseconds by monitoring the physical error signal of its own carrier synchronization loop, and the cooperative response module immediately executes the preset avoidance action to give robot A a path. This series of physical layer beacon-based interactions converts the inherent contradiction between efficiency and reliability in traditional technology into a cooperative mechanism that is compatible in a single architecture. Instead of directly optimizing the response speed of the centralized scheduling system, which has physical limitations, the high-time-efficiency information is directly encoded at the physical layer, thereby converting the centralized scheduling reliability problem into a neighborhood physical state broadcast problem.

[0042] In this process, the transmission link health self-check module of robot B synchronously calculates the transmission link health index every time it communicates externally When the power amplifier non-linear distortion intensifies, the unexpected amplitude modulation energy Rises, causing its Value to be lower than the preset health threshold. At this time, the state mapping module of robot B is forced to map and inject a second specific mode of phase disturbance representing a low-energy resource state, which is detected by adjacent robots and the main monitoring node of the warehouse management system. The latter immediately updates the task priority of robot B and schedules it to go to the maintenance station. Finally, robot A passes through the core passage without reducing its own speed and affecting the overall traffic flow, while robot B is identified in advance for hardware health risks and guided to the maintenance area before the communication link interruption fault occurs. The entire warehouse robot cluster maintains high throughput operation without relying on the central node for high-frequency micro coordination, and the health status of the hardware physical layer is endogenously integrated into each cooperative communication cycle.

[0043] Embodiment 2: To objectively verify the cooperative response time and instruction transmission reliability of the command and scheduling system of the present application in response to high-density concurrent conflicts and strong channel noise, a hardware-in-the-loop simulation test is built and carried out. This test aims to quantitatively compare the differences in key performance indicators between the present application scheme and the traditional scheduling method based on high-level software protocol.

[0044] The test platform is composed of a group of software defined radios, all of which are configured with the command and dispatch system of the application and are synchronously controlled and data collected by a central test controller, the communication channel is generated by a programmable channel simulator which can inject additive white Gaussian noise with different power levels to simulate different noise floor indexes, in the test, the starting point of the measurement of the cooperative response time is the time when the test controller issues the injection instruction to the sending end device, and the ending point is the time when the receiving end device generates a hardware interrupt due to the detection of the disturbance pattern, the time resolution is nanosecond level; the instruction transmission success rate is defined as the proportion of the events successfully detected by the receiving end in a specified number of consecutive injection events; the core parameter of the test, the number of concurrent conflict devices, is set to evaluate the scalability and robustness of the distributed conflict arbitration mechanism used in the system when the load pressure increases, for this purpose, the number of conflict devices simultaneously initiating injection requests in the test is increased from 2 to 16 to observe the trend of system performance, the control group uses the same SDR hardware platform, but runs a high-level signaling interaction protocol based on carrier sense multiple access and conflict avoidance mechanism to simulate the prior art.

[0045] During the test, the test controller instructs a specified number of conflict devices to attempt to inject a standardized carrier phase disturbance pattern representing a high priority service state at the same time, and the receiving end device records the response time of the instruction and whether the detection is successful, this process is repeated under different conflict device numbers and channel noise conditions, the observed phenomenon is that as the number of conflict devices increases, the average cooperative response time of the control group increases exponentially due to channel competition avoidance and retransmission, and the instruction transmission success rate decreases; in contrast, the test group using the scheme of the application maintains the average cooperative response time in the order of microseconds and grows slowly, and the instruction transmission success rate is maintained at a high level, for specific data, see Table 1.

[0046] Table 1: Performance comparison table of different schemes under different conflict device numbers.

[0047]

[0048] The test data show that the response time stability of the scheme of the application is due to the mechanism of the conflict arbitration module which converts the microscopic asynchronization of the device hardware clock into a microsecond level avoidance delay, which avoids the complex signaling coordination and data frame exchange process in the high-level protocol; the high reliability of the instruction transmission is realized under the cooperation of this conflict arbitration mechanism and the channel noise sensing module, the latter dynamically adjusts the robustness of the disturbance pattern according to the noise level, which guarantees the detectability of the signal from the physical layer.

[0049] Embodiment 3: This embodiment combines Figs. 1 to 3An implementation of an artificial intelligence-based communication device command and dispatch system is described. As shown in Fig. 1 the system's operation begins with the perception of service state / resource state, this information is input to the state mapping module, which simultaneously receives the noise floor index from the channel noise perception module to jointly determine the adaptive perturbation mode; the channel noise perception module determines the channel condition by analyzing the error signal output by the carrier synchronization loop, the selected perturbation mode is then passed to the conflict arbitration module, which performs channel listening before injection, and calculates the backoff time according to the clock counter value read from the local hardware clock if necessary; the module can also interact with the neighborhood physical connectivity verification module to confirm channel availability; after arbitration, the signal injection module is responsible for loading the final determined injection perturbation mode to the radio frequency front end, and the transmission link health self-checking module synchronously monitors the health of the injection process, and finally sends signals to the outside through the radio frequency front end; after the received signal from the adjacent communication device enters the device, it is processed by the carrier synchronization loop, the error signal generated by the loop is sent to the perturbation detection module, which analyzes the signal with the assistance of the reception link health diagnosis module, and outputs the detection result to the cooperative response module, which finally executes the preset cooperative dispatch action, thus completing a complete command and dispatch closed loop based on the physical layer beacon.

[0050] As shown in Fig. 2 , the horizontal axis of the graph is the running time (hours), and the vertical axis is the health index ; the graph contains two curves, where the solid line represents the actual measurement value of the device transmission link health index, and the dashed line represents the preset health threshold; as can be seen from the graph, as the running time accumulates, the transmission link health index shows a slow downward trend, and at the node of about 7000 hours, its value crosses and falls below the preset health threshold, which intuitively indicates that the device's radio frequency power amplifier and other key components may have performance degradation due to long-term use, thus triggering the system's predictive maintenance or resource state adjustment mechanism.

[0051] As shown in Fig. 3 , the system is usually in the baseline state of listening and monitoring, when high / low priority service state triggers, the process enters the state evaluation and mode selection link, and generates an adaptive channel perturbation mode, then enters the channel conflict arbitration; in the arbitration link, if the channel is idle, it directly enters the injection phase perturbation step, and returns to the listening and monitoring state after injection is completed, if a conflict is detected, it needs to calculate the backoff time and enter the backoff delay state, after the backoff time ends, it returns to the channel conflict arbitration link to reattempt access; on the other hand, if a neighboring device perturbation is detected in the listening and monitoring state, the system directly enters the cooperative response module, and returns to the initial state of listening and monitoring after the cooperative action is completed.

[0052] In order to ensure the performance of the command and dispatch system of the present application in different hardware individuals and diverse deployment environments, all the communication devices perform a set of offline and standardized parameter calibration and configuration procedures before being put into use, which are carried out in a controlled electromagnetic shielding environment. The procedure first defines and generates a library of standardized carrier phase perturbation patterns and its mapping table used by the device to ensure the distinguishability between different perturbation patterns. In a specific implementation of the embodiment, the high-priority service state is mapped to a 1 kHz continuous sinusoidal phase modulation of the carrier, and the low-energy resource state is mapped to a 2 kHz continuous sinusoidal phase modulation. The initial perturbation amplitudes of the two modes are set according to the link budget evaluation. This frequency-orthogonal design enables the receiver to distinguish different patterns through correlation filtering processing. The mapping relationship is generated at the beginning of calibration and is fixed to the non-volatile memory of the device.

[0053] Subsequently, the procedure accurately calibrates the perturbation detection threshold of each device. At the beginning of calibration, the device is placed in an electromagnetic shielding darkroom. First, the root mean square value of the carrier synchronization loop error signal of the device over a period of time is collected and calculated under the condition of no signal injection, denoted as the inherent background noise voltage of the device . Then, a carrier signal containing only the weakest standard perturbation mode is injected into the device through a standard signal source, and the root mean square value of the loop error signal is measured again, denoted as the minimum signal response voltage . Finally, the perturbation detection threshold of the device is determined by the formula .

[0054] Finally, the procedure calibrates the noise floor index threshold for channel adaptation. Based on the completion of the setting, controllable additive white Gaussian noise is injected into the channel through a programmable noise source. First, under the condition of injecting only the standard perturbation mode, the power of the injected noise is gradually increased, and the instruction transmission success rate of the receiver is continuously monitored. When the success rate first falls below a preset performance baseline, the noise floor index measured by the channel noise perception module at this moment is recorded, and this index value is fixed as the first preset threshold. Then, the enhanced perturbation mode with higher energy is injected, and the power of the injected noise is increased from the noise level recorded just now. When the instruction transmission success rate again falls below the performance baseline, the noise floor index at this moment is recorded, and it is fixed as the second preset threshold. After completing the above steps, the communication device is considered to have completed the calibration, and the pattern library and threshold parameters stored in it are the results of optimization customized for its own hardware characteristics. When the device is deployed in the actual working environment, it can perform adaptive command and dispatch functions based on this set of calibrated parameters.

[0055] In order to ensure the robustness of the system in dynamic topology network and the physical layer credibility of the member devices participating in the collaborative task, the device periodically performs neighborhood physical connectivity verification and receives link health self-diagnosis procedures during operation. The neighborhood physical connectivity verification module of the device controls the signal injection module to broadcast a non-standardized phase probe pulse with device-specific characteristics. The waveform characteristics of the pulse, such as the start and end frequencies of the linear frequency modulation, are generated by a preset hash function from the device's own hardware address. After capturing the phase probe pulse via its disturbance detection module, the neighboring device records the received pulse waveform characteristics and embeds a time-reversed conjugate of the phase echo characteristics or the original probe pulse waveform in the preamble part of the signal carrier during its next external communication signal transmission, thereby achieving physical existence response in an information piggybacking manner. The initiating device can confirm the existence of an instantaneous two-way physical channel connection with the neighboring device by monitoring and identifying this specific phase echo.

[0056] At the same time, the receiving link health diagnosis module of the device controls the signal injection module to inject a standardized phase jitter excitation pulse when injecting any standardized carrier phase disturbance pattern. The excitation pulse is a square wave phase modulation with a duration of several symbol periods, which provides a standardized step response excitation for the carrier synchronization loop of the receiving device itself. When detecting the standardized disturbance pattern, the receiving device also synchronously monitors the response characteristics of its own carrier synchronization loop to the excitation pulse. A healthy receiving link presents a damped oscillation with fast convergence of the loop error signal after excitation, while a deteriorated receiving link due to power supply stability presents an overshoot or sustained ringing of the loop error signal. By comparing the integral value of the response signal within a specific time window after the end of excitation with a preset health threshold, the power supply stability state can be quantified, and when the state is judged to be below the health threshold, the subsequent collaborative scheduling behavior is adjusted to suppress the injection of high-priority service state disturbance patterns through the state mapping module, thereby ensuring the overall stability of the collaborative network.

[0057] In order to ensure the reliability of the system under different network densities and boundary conditions, the communication device performs a set of adaptive optimization of operating parameters and online state monitoring of core components when it is started for the first time or joins a new network. The procedure first calibrates the backoff delay time in the conflict arbitration module to optimize the channel time division multiplexing efficiency. During the calibration process, the device creates two virtual threads in the processor level through internal loopback mode, which are parallel and attempt to trigger high-priority disturbance injection at the same time to simulate internal conflict events. The conflict arbitration module performs backoff delay calculation based on the least significant bit of the hardware clock for the two threads, respectively. The device compares the actual interval of the two virtual injection events on the time axis with an optimal time interval target value preset according to the application scenario delay requirement, and based on the comparison result, adjusts the linear scaling factor used to convert the clock count value to microsecond time through iteration until the actual interval converges within the allowable error range of the optimal target value. The finally determined linear scaling factor is then solidified for subsequent operation.

[0058] During the continuous operation of the device, an online integrity monitoring logic continuously monitors the locking state of the carrier synchronization loop, which is the basis of all detection functions of the system. The monitoring logic directly monitors the output voltage of the loop filter, which is stable within a preset nominal range when the loop is normally locked. A loss of lock event is determined to occur when the loop filter output voltage stays in the saturation zone beyond the nominal range for more than a preset maximum tolerance time or the instantaneous frequency change rate of the error signal exceeds the maximum slew rate that the loop can physically follow. Once a loss of lock event is determined to occur, the system immediately enters a preset safe state in which all modules that rely on the loop error signal, including the disturbance detection module and the channel noise perception module, are temporarily suspended until the carrier synchronization loop is rebuilt and maintains stable locking for a preset period of time, after which the system automatically exits the safe state.

[0059] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application 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 application can be modified or replaced by equivalents without departing from the spirit and scope of the present application.

Claims

1. An artificial intelligence-based communication device command and dispatch system, characterized by, The system comprises: a state mapping module configured to select a corresponding standardized carrier phase perturbation pattern from a mapping table associating traffic states or resource states with standardized carrier phase perturbation patterns according to a current traffic state or resource state of the communication device; a channel noise sensing module configured to determine a noise floor index reflecting a background noise level of the channel during a channel quiet period by monitoring an error signal of a carrier synchronization loop of the communication device, and output the noise floor index to the state mapping module for selecting a perturbation pattern from at least two standardized carrier phase perturbation patterns with different levels of robustness that is suitable for the noise floor index based on the noise floor index; a collision arbitration module configured to first listen to the communication channel to determine whether there exists a same existing perturbation pattern before injecting the standardized carrier phase perturbation pattern corresponding to the high priority traffic state, and if so, read at least one least significant bit of a local hardware clock counter of the communication device, and determine a backoff delay time in microseconds according to a value of the at least one read least significant bit; a signal injection module connected to the state mapping module and the collision arbitration module, and configured to control a radio frequency front end of the communication device to inject the selected standardized carrier phase perturbation pattern on a carrier of a communication signal transmitted outwardly after the collision arbitration module determines that there does not exist a same existing perturbation pattern or after the backoff delay time; a perturbation detection module configured to detect whether there exists a standardized carrier phase perturbation pattern on a carrier of a communication signal received from a neighboring communication device by monitoring an error signal of a carrier synchronization loop of the communication device; a cooperative response module connected to the perturbation detection module, and configured to perform a preset cooperative scheduling action based on the standardized carrier phase perturbation pattern detected by the perturbation detection module.

2. The artificial intelligence-based communication device command and dispatch system of claim 1, wherein, The state mapping module is configured to select from a mapping table in which a high priority traffic state is mapped to a first specific pattern of phase perturbation and a low energy resource state is mapped to a second specific pattern of phase perturbation; the perturbation amplitude, frequency or waveform of the first specific pattern of phase perturbation is different from that of the second specific pattern of phase perturbation.

3. The artificial intelligence-based communication device command and dispatch system of claim 1, wherein, The collision arbitration module is configured to determine the backoff delay time by directly or after scaling by a preset linear scaling factor, mapping the binary value of the at least one read least significant bit of the local hardware clock counter to a time value in microseconds, thereby converting the clock micro-unsynchronization inherent to the communication device hardware into a backoff delay with distributed, uncoordinated conflict resolution or individual uniqueness.

4. The artificial intelligence-based communication device command and dispatch system of claim 1, wherein, The channel noise sensing module and the state mapping module are further configured to select a standard perturbation pattern with a first amplitude when the noise floor index is below a first preset threshold, and select an enhanced perturbation pattern with a second amplitude when the noise floor index is between the first preset threshold and a second preset threshold, wherein the second amplitude is greater than the first amplitude. When the noise floor index is higher than a second preset threshold, a high-robustness disturbance pattern with a second amplitude and a complex waveform feature is selected.

5. The artificial intelligence-based communication device command and dispatch system of claim 1, wherein, The system further comprises a transmit link health self-checking module configured to, while the signal injection module injects the standardized carrier phase perturbation pattern, monitor the envelope of the own transmitted signal synchronously through a power detector to obtain an unintended amplitude modulation energy, and calculate a transmit link health index according to the following relationship , wherein, is the unintended amplitude modulation energy, is the expected energy of the standardized carrier phase perturbation injected by the signal injection module; the transmit link health index is used to evaluate whether the radio frequency power amplifier of the communication device has nonlinear distortion.

6. The artificial intelligence-based communication device command and dispatch system of claim 1, wherein, The disturbance detection module is further configured to compare the instantaneous value of the error signal of its own carrier synchronization loop with a preset disturbance detection threshold through a hardware comparator, and directly trigger a hardware interrupt to the cooperative response module when it is determined that the error signal exceeds the disturbance detection threshold and its change rule conforms to the preset waveform template of any standardized carrier phase disturbance pattern.

7. The artificial intelligence-based communication device commanding and dispatching system according to claim 1, characterized in that, The cooperative response module is configured to perform a preset cooperative scheduling action, specifically: when the disturbance detection module detects a standardized carrier phase disturbance pattern representing a high-priority service state, the cooperative response module immediately controls the communication device to reduce the transmission power of non-safety-critical services of itself or suspend transmission in the direction of the signal source.

8. The artificial intelligence-based communication device commanding and dispatching system according to claim 1, characterized in that, The system further comprises a neighborhood physical connectivity verification module configured to periodically control the signal injection module to inject and broadcast a phase detection pulse with device uniqueness and non-standardization on the carrier of the communication device; And control the disturbance detection module to monitor the communication signal from the adjacent communication device in the subsequent period to detect whether there is an embedded phase echo feature in the communication signal as a response to the phase detection pulse, and based on the detection result, confirm the instant connectivity of the physical channel with the adjacent communication device.

9. The artificial intelligence-based communication device command and dispatch system of claim 8, wherein, The neighborhood physical connectivity verification module is further configured to control the adjacent communication device to embed a phase echo feature related to the received phase detection pulse waveform in the preamble part of the communication signal when it transmits the communication signal next time after receiving the phase detection pulse.

10. The artificial intelligence-based communication device commanding and dispatching system according to claim 1, characterized in that, The system further comprises a receiving link health diagnosis module configured to control the signal injection module to synchronously inject a standardized or high-frequency phase jitter excitation pulse while injecting the standardized carrier phase disturbance pattern; and control the disturbance detection module to also monitor the severity of the response feature of its own carrier synchronization loop to the phase jitter excitation pulse while detecting the standardized carrier phase disturbance pattern, to determine its own power supply stability state, and adjust its subsequent cooperative scheduling behavior based on the power supply stability state.

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