Intelligent communication method and system based on private network

Abstract

This invention discloses an intelligent communication method and system based on a private network, relating to the field of intelligent communication technology. The method includes: deploying a broadband cognitive radio front-end at each network-connected terminal, continuously scanning the licensed frequency bands and adjacent frequency bands of the private network, reporting the original scan data to a server, and generating a four-dimensional spectrum map; the server receiving the task flow, performing data segmentation and multi-dimensional encoding to determine distributed coded data; based on the task intent of the task flow, forming a dynamic transmission group according to the network-connected terminals in an electromagnetic environment; and using absolute clock constraints at the edge management end, using the dynamic transmission group as the target communication network, and performing adaptive communication allocation management on the distributed coded data. This solves the technical problems of low spectrum utilization and fixed communication resource allocation methods in existing private network communication technologies, leading to low communication efficiency. It achieves the technical effect of improving the efficiency and resource utilization of private network communication by dynamically forming transmission groups and performing adaptive communication allocation management.

Description

Technical Field

[0001] This invention relates to the field of intelligent communication technology, and more specifically to intelligent communication methods and systems based on private networks. Background Technology

[0002] Dedicated communication networks are widely used in scenarios with high requirements for communication reliability and security, such as power, energy, transportation, emergency command, and industrial control. Compared with public network communication, dedicated networks typically operate in licensed or semi-licensed frequency bands, and their network topology, communication resources, and service scheduling strategies are mostly pre-planned and statically configured to ensure the determinism and controllability of communication. However, with the increasing types of services carried by dedicated networks and the continuous expansion of terminal scale, the electromagnetic environment faced by dedicated network communication is becoming increasingly complex, and the contradiction between the scarcity of spectrum resources and the diversification of service demands is becoming increasingly prominent. Existing dedicated network communication systems rely heavily on single-dimensional or low-dimensional spectrum monitoring results in terms of spectrum usage, lacking the ability to jointly perceive the multi-dimensional characteristics of the spectrum in terms of time, space, and usage status. This makes it difficult to fully reflect the actual changes in the electromagnetic environment, resulting in low spectrum resource utilization efficiency. At the same time, existing communication resource allocation and link organization methods are usually based on fixed base stations or preset topologies, and the flexibility of adjusting communication paths and resource scheduling strategies is insufficient, making it difficult to dynamically optimize according to the real-time needs of different service tasks and network load conditions. Furthermore, in multi-terminal collaborative communication scenarios, existing private network systems have limited collaborative control capabilities over communication timing and resource scheduling, which can easily lead to problems such as resource conflicts, link congestion, or unstable communication latency, further restricting the improvement of private network communication efficiency and service quality. Summary of the Invention

[0003] This application provides an intelligent communication method and system based on private networks, which solves the technical problems of low spectrum utilization and fixed communication resource allocation in existing private network communication technologies, resulting in low communication efficiency.

[0004] The first aspect of this application provides an intelligent communication method based on a private network, the method comprising: Broadband cognitive radio front-ends are deployed on each network access terminal to continuously scan the licensed frequency bands of the private network and adjacent frequency bands. The raw scan data is reported to the server to generate a four-dimensional spectrum map. The network access terminals include private network base stations and key terminals. The server receives the task flow, performs data segmentation and multi-dimensional encoding, and determines the distributed coded data. Based on the task intent of the task flow, a dynamic transmission group is formed according to the network access terminals in the electromagnetic environment based on the four-dimensional spectrum map. At the edge management end, absolute clock constraints are adopted, and the dynamic transmission group is used as the target communication network to perform adaptive communication allocation management of the distributed coded data.

[0005] A second aspect of this application provides an intelligent communication system based on a private network, the system comprising: Data Acquisition Module: Deploys broadband cognitive radio front-ends at each network access terminal, continuously scans the licensed frequency bands of the private network and adjacent frequency bands, reports the raw scan data to the server, and generates a four-dimensional spectrum map. The network access terminals include private network base stations and key terminals. Data Processing Module: The server receives the task flow, performs data segmentation and multi-dimensional encoding, and determines the distributed coded data. Transmission Group Construction Module: Based on the task intent of the task flow, in an electromagnetic environment based on the four-dimensional spectrum map, constructs a dynamic transmission group according to the network access terminals. Communication Management Module: At the edge management end, using absolute clock constraints and the dynamic transmission group as the target communication network, performs adaptive communication allocation management for the distributed coded data.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: Broadband cognitive radio front-ends are deployed at each network-accessible terminal to continuously scan the licensed frequency bands and adjacent frequency bands of the private network. The raw scan data is reported to the server to generate a four-dimensional spectrum map. The network-accessible terminals include private network base stations and key terminals. The server receives the task flow, performs data segmentation and multi-dimensional encoding, and determines the distributed coded data. Based on the task intent of the task flow, a dynamic transmission group is formed according to the network-accessible terminals in the electromagnetic environment based on the four-dimensional spectrum map. Absolute clock constraints are used at the edge management end, with the dynamic transmission group as the target communication network, to perform adaptive communication allocation management of the distributed coded data. This solves the technical problems of low spectrum utilization and fixed communication resource allocation methods in existing private network communication technologies, resulting in low communication efficiency. It achieves the technical effect of improving the efficiency and resource utilization of private network communication by dynamically forming transmission groups and performing adaptive communication allocation management. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 A schematic flowchart of a private network-based intelligent communication method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a private network-based intelligent communication system provided in an embodiment of this application.

[0009] Explanation of reference numerals in the attached diagram: Data acquisition module 11, data processing module 12, transmission group assembly module 13, communication management module 14. Detailed Implementation

[0010] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0011] Example 1, as Figure 1 As shown, this application provides an intelligent communication method based on a private network, wherein the method includes: Broadband cognitive radio front-ends are deployed in each network access terminal to continuously scan the licensed frequency bands of the private network and adjacent frequency bands, and the original scan data is reported to the server to generate a four-dimensional spectrum map. The network access terminals include private network base stations and key terminals.

[0012] A broadband cognitive radio front-end is deployed on each network access terminal. The broadband cognitive radio front-end includes at least a broadband RF receiving module, a variable bandwidth analog-to-digital converter module, and a spectrum sensing and processing module. Under normal network access operation, the network access terminal performs continuous or periodic spectrum scanning of the licensed frequency band and its adjacent frequency bands according to a preset scanning cycle, acquiring raw RF signal data at each scanned frequency point at different times. The spectrum sensing and processing module performs down-conversion, energy detection, feature extraction, and interference feature identification processing on the raw RF signal data, generating local scan data containing frequency location, timestamp, received power, signal-to-noise ratio, and preliminary interference feature identifiers. The interference feature identifiers are used to distinguish different interference types such as continuous wave interference, burst interference, broadband noise interference, or modulated signal interference. Each network-connected terminal reports its local scan data to the server via the dedicated network backhaul link. The server performs spatial correlation and fusion processing on the local scan data based on the location information of each network-connected terminal, and organizes and maps the fused scan data according to the frequency dimension, time dimension, spatial dimension, and interference type dimension to construct a four-dimensional spectrum map reflecting the electromagnetic environment status of the dedicated network and its adjacent frequency bands. The four-dimensional spectrum map is used to characterize the availability and interference distribution characteristics of each frequency band under different time and spatial locations.

[0013] The server receives the task stream, performs data segmentation and multidimensional encoding, and determines the distributed encoded data.

[0014] After receiving a task flow from the business system or the upper-level scheduling module, the server first parses the task flow to obtain task attribute information such as data scale, timeliness requirements, and reliability level. Based on this task attribute information, the server segments the original data in the task flow according to preset data segmentation rules, dividing the task flow into multiple independent data segments, each containing a unique segment identifier and sequence mark. Subsequently, the server performs encoding processing on each data segment according to a predefined multi-dimensional encoding strategy, wherein the multi-dimensional encoding strategy includes at least frequency slice dimension, time slot dimension, spatial flow dimension, and power weight dimension. During the encoding process, the server assigns a corresponding frequency resource index, time transmission order, spatial transmission path identifier, and power allocation weight parameters to each data segment, and associates and encapsulates these parameters with the data segment to form a corresponding encoding vector. The server aggregates and organizes the encoding vectors of each data segment to generate distributed encoded data for subsequent communication scheduling, thereby enabling the task flow to be transmitted in parallel or collaboratively across multiple frequency, time, and spatial resource dimensions.

[0015] Furthermore, data segmentation and multidimensional encoding are performed to determine the distributed encoded data, including: The task flow is segmented into N data segments; each of the N data segments is encoded according to a predefined encoding dimension to determine N encoding vectors, wherein the encoding dimension includes frequency slices, time slots, spatial flow, and power weights; the N encoding vectors are integrated to determine distributed encoded data.

[0016] The server performs structured parsing on the received task flow. Based on the total amount of data, data type, and transmission constraints of the task flow, it splits the task flow into N data segments according to preset data segmentation rules. These data segments are independent of each other and each carries a segment sequence number for reassembly. After data segmentation, the server performs encoding processing on each of the N data segments according to a pre-configured set of encoding dimensions. Specifically, for each data segment, a corresponding frequency band index is assigned in the frequency slice dimension, a transmission timing position is assigned in the time slot dimension, a corresponding transmission path or node sequence is identified in the spatial flow dimension, and a transmit power weight parameter matching the task priority and link conditions is configured in the power weight dimension. This generates an encoding vector containing multi-dimensional resource mapping relationships for each data segment. The server integrates and encapsulates these N encoding vectors to form distributed encoded data for subsequent communication scheduling and data transmission based on dynamic transmission groups.

[0017] Based on the task intent of the task flow, a dynamic transmission group is formed according to the network-connected terminals in an electromagnetic environment based on the four-dimensional spectrum map.

[0018] The server parses the task flow to extract communication-related task intent parameters, which include at least task priority, data timeliness requirements, reliability level, and expected communication coverage. Based on these parameters, the server locates the spatiotemporal range corresponding to the task execution area in a four-dimensional spectrum map and analyzes the availability, interference type distribution, and time-varying trends of each frequency band within this range. Subsequently, the server acquires the network access status and capability information of each network-connected terminal, including at least communication capability, computing capability, reachability, and remaining energy status. Under the electromagnetic environment constraints represented by the four-dimensional spectrum map, the server combines the task intent parameters and the capability information of the network-connected terminals to filter and combine them, determining a set of terminals that meet the task intent constraints. Within this set, temporary communication relationships are established between source nodes, cooperating nodes, and sink nodes, thereby constructing a dynamic transmission group oriented towards the task flow.

[0019] Furthermore, the formation of a dynamic transport group includes: Each network access terminal reports its network access capabilities, which are defined jointly based on communication, computing, mobility, and energy. Based on the network access capabilities and the task flow, an adaptive terminal node group is established under the constraints of interference behavior patterns to determine the dynamic transmission group.

[0020] During network access or operation, each terminal periodically or when triggering conditions are met reports its network access capability information to the server. This network access capability is jointly defined by communication capability, computing capability, mobility capability, and energy status. Specifically, the communication capability includes at least the supported bandwidth range, modulation scheme, and link stability indicators; the computing capability includes available computing resources and processing load levels; the mobility capability includes the terminal's current location, speed, and reachable range; and the energy status includes remaining battery power or available energy consumption budget. After receiving the network access capability information reported by each terminal, the server, based on the task intent and data transmission requirements of the task flow and the electromagnetic environment reflected in the four-dimensional spectrum map, determines the interference behavior pattern constraints for the corresponding task scenario. Based on these interference behavior pattern constraints, the server performs adaptive grouping decisions for the terminals, selecting terminal nodes that meet communication reliability, timing requirements, and energy consumption constraints. Under the premise of meeting interference avoidance conditions, the server combines and assigns roles to these terminal nodes, ultimately determining the dynamic transmission group for the task flow.

[0021] Before constructing the dynamic transmission cluster, the server determines the interference behavior pattern of the electromagnetic environment in which the private network communication is located based on the four-dimensional spectrum map. Specifically, this includes: First, in the frequency dimension, statistical analysis is performed on the received power sequence of the target frequency band within a continuous time window, calculating the average power, power fluctuation amplitude, and occupancy duration of each frequency point. If a frequency point is continuously in a high power occupancy state within a preset time window and the fluctuation amplitude is small, it is determined that the frequency point has persistent interference behavior; if the power level shows a short-term high-amplitude sudden change and the occupancy duration is lower than a preset threshold, it is determined to be sudden interference behavior. Second, in the time dimension, the periodic characteristics of the interference occurrence are analyzed. When the interference shows a fixed or nearly fixed occurrence interval within multiple time windows, the interference behavior is determined to have periodic characteristics and is marked as periodic interference behavior. Furthermore, in the spatial dimension, the server combines the location information of different network-connected terminals to perform spatial comparative analysis of the interference power distribution in the same frequency band. If the interference power shows a concentrated distribution in space or changes significantly with location, the interference source is determined to have spatial directional characteristics. If the interference power appears simultaneously in multiple spatial locations with small differences, it is determined to be regional interference behavior. In the interference type dimension, the server performs rule matching on the interference signal based on modulation characteristics, bandwidth occupancy characteristics, and signal-to-noise ratio variation trends to distinguish between continuous wave interference, broadband noise interference, and modulated signal interference, and uses the determination result as an interference type label. The server integrates the determination results from the above frequency, time, space, and interference type dimensions to form an interference behavior pattern description, which is used as a constraint condition for subsequent dynamic transmission group construction and communication resource allocation.

[0022] Furthermore, the dynamic transmission group consists of source nodes, cooperating nodes, and sink nodes; wherein, the construction of the dynamic transmission group includes: in the terminal cluster composed of network-connected terminals, network-connected terminals are screened according to preset conditions to determine task flow terminals, wherein spatial avoidance, capability matching, and topology optimization are used as screening constraints; in the task flow terminals, the dynamic transmission group is formed by the arrangement of source nodes, cooperating nodes, and sink nodes and the establishment of temporary communication.

[0023] The dynamic transmission group consists of source nodes, cooperating nodes, and sink nodes. The source node is the network terminal that generates task flow data, the cooperating node is the network terminal with data relay and computing capabilities, and there can be one or more cooperating nodes. The sink node is the dedicated network base station or gateway node that ultimately receives the task flow data.

[0024] The construction process of the dynamic transmission group includes: The server filters the network-connected terminals in a terminal cluster composed of all connected terminals based on preset terminal filtering conditions to determine the task flow terminals participating in the current task flow. The preset terminal filtering conditions include at least spatial avoidance constraints, capability matching constraints, and topology optimization constraints. Spatial avoidance constraints prevent terminals from being located in high-interference or unreachable areas. Capability matching constraints ensure that the communication, computing, and energy capabilities of the terminals meet the task flow requirements. Topology optimization constraints reduce end-to-end hop count and improve link stability. After completing the task flow terminal filtering, the server assigns roles to source nodes, cooperating nodes, and sink nodes within the task flow terminals based on the data generation and reception locations of the task flow. Temporary communication associations are established between these nodes to form a multi-node collaborative communication structure oriented towards the task flow, thereby constituting the dynamic transmission group.

[0025] Spatial avoidance constraints are used to avoid high-interference, high-risk, or unreachable spatial areas during the construction of dynamic transmission groups. Specifically, based on the spatial dimension and interference type dimension represented by the four-dimensional spectrum map, the server identifies spatial areas with strong interference, continuous interference, or rapid interference spread within the current task time window and marks the corresponding spatial areas as avoidance areas. The server combines the location information and reachability information reported by each network-connected terminal to determine whether each network-connected terminal is within the avoidance area or whether its communication path needs to pass through the avoidance area. If a network-connected terminal is located within the avoidance area or its communication path crosses the avoidance area, the priority of that network-connected terminal in the group construction process is reduced or it is excluded from the current task flow terminal set, thereby reducing the impact of interference on the communication stability of the dynamic transmission group.

[0026] Capability matching constraints are used to ensure that participating terminals in a dynamic transport group meet the actual requirements of the task flow in terms of communication capabilities, computing power, mobility, and energy status. Specifically, the server determines the threshold requirements for bandwidth, latency, computational load, and continuous communication time based on the task intent parameters obtained from task flow parsing. Subsequently, these threshold requirements are compared with the network access capability information reported by each participating terminal to select terminals that meet the task requirements in terms of communication rate, available computing resources, location stability, and remaining energy. For terminals that do not meet any of the key capability thresholds, the server restricts their participation in the dynamic transport group or only allows them to assume a low-load collaborative role, thereby avoiding communication interruptions or performance degradation due to insufficient capabilities.

[0027] Topology optimization constraints are used to optimize the communication structure of dynamic transmission groups while satisfying spatial avoidance and capacity matching constraints. Specifically, the server constructs candidate communication topologies based on the reachability relationships between network-connected terminals, link quality parameters, and node role requirements, and evaluates these candidate topologies. Evaluation metrics include at least end-to-end hop count, link stability, transmission latency, and load balancing. The server prioritizes communication topologies with fewer end-to-end hops, higher link quality, and balanced node load distribution, and determines the connection relationships between source nodes, cooperating nodes, and sink nodes accordingly. This ensures communication reliability while reducing communication overhead and improving the overall transmission efficiency of the dynamic transmission group.

[0028] Furthermore, after constituting the dynamic transmission group, it includes: Based on the four-dimensional spectrum map, interference behavior patterns are determined, wherein the interference behavior patterns are determined based on the dynamic propagation and spatiotemporal distribution patterns of interference; the available bandwidth of the private network is virtualized with high granularity in the frequency-time domain to determine the smallest resource unit; the task intent based on the task flow is determined, and combined with the interference behavior patterns, the dynamic transmission group is actively woven into a multi-dimensional resource pattern based on the smallest resource unit to determine the resource weaving pattern, wherein the resource weaving pattern defines the frequency selection, time slots, spatial paths, and power allocation of each network-connected terminal covered by the dynamic transmission group in the next communication cycle.

[0029] Based on a four-dimensional spectrum map, the server analyzes the electromagnetic environment within the target communication area, identifying the propagation characteristics of interference signals in the frequency, time, and spatial dimensions. Combining the duration, intensity changes, and diffusion trends of the interference, the server determines the corresponding interference behavior patterns. These patterns describe the dynamic propagation and spatiotemporal distribution of interference at different time periods and spatial locations. Subsequently, the server performs joint frequency and time domain virtualization processing on the available bandwidth of the private network, dividing the continuous available spectrum resources into multiple minimum resource units with uniform granularity. Each minimum resource unit contains at least a defined frequency range and time slot length, serving as the basic allocation unit for communication scheduling. After completing the minimum resource unit partitioning, the server, based on the task intent of the task flow and combined with the interference behavior pattern, performs proactive multi-dimensional resource weaving processing on each network-connected terminal in the dynamic transmission group. According to multiple resource dimensions such as frequency selection, time slot allocation, spatial transmission path configuration, and transmission power allocation, the minimum resource units are combined and mapped to generate a resource weaving pattern. The resource weaving pattern is used to define the frequency resources, transmission timing, transmission path, and power configuration used by each network-connected terminal in the dynamic transmission group in the next communication cycle, thereby realizing refined and anti-interference allocation of communication resources.

[0030] Furthermore, the resource weaving pattern is compiled into binary control instructions and sent to each network terminal in the dynamic transmission group via the communication bus to perform communication resource initialization.

[0031] After generating the resource weaving pattern, the server performs instruction processing on the pattern, encapsulating and compiling the frequency selection parameters, time slot allocation parameters, spatial transmission path identifiers, and power allocation parameters defined in the pattern according to a preset control instruction format to generate corresponding binary control instructions. These binary control instructions include at least a terminal identifier field, a resource unit index field, a transmission timing field, and a power control field. The server distributes these binary control instructions to each network-connected terminal within the dynamic transmission group via the internal communication bus of the private network. Each terminal receives the binary control instructions, parses them, and initializes its local radio frequency parameters, scheduling queue, and transmit power based on the parsing results. This allows it to enter a communication preparation state under a unified resource configuration, thus achieving the initialization of communication resources for the dynamic transmission group.

[0032] Absolute clock constraints are used at the edge management end, and the dynamic transmission group is used as the target communication network to perform adaptive communication allocation management of the distributed coded data.

[0033] The edge management terminal synchronizes its time with the server and all network-connected terminals within the dynamic transmission group to obtain a unified absolute clock reference, which is then used as the global time reference for communication scheduling. Upon receiving distributed coded data from the server, the edge management terminal, based on the associated coded vector information within the distributed coded data and the resource weaving pattern of the dynamic transmission group, performs unified scheduling control over the transmission time, transmission order, and resource units occupied by each data segment under absolute clock constraints. Specifically, the edge management terminal divides continuous communication cycles according to the absolute clock, and within each communication cycle, based on the time slots and frequency slices corresponding to each coded vector, issues corresponding communication allocation instructions to the source nodes, cooperating nodes, and sink nodes within the dynamic transmission group, enabling each network-connected terminal to perform data transmission, relay, or reception operations under the same time reference. Through this adaptive communication allocation management constrained by the absolute clock, orderly scheduling of distributed coded data within the dynamic transmission group is achieved, reducing communication conflicts and timing deviations, and improving the determinism and stability of multi-node collaborative communication.

[0034] Furthermore, using the dynamic transmission group as the target communication network, adaptive communication allocation management of the distributed coded data includes: The server encapsulates the distributed encoded data and sends it to the edge management terminal of the dynamic transmission group. The edge management terminal receives the distributed encoded data and, based on the timestamp constraint issued by the absolute clock of the edge management terminal, performs communication allocation drive management based on the dynamic transmission group.

[0035] After generating distributed coded data, the server performs communication encapsulation processing, encapsulating the coding vectors, target dynamic transmission group identifiers, and scheduling parameters corresponding to each data segment into a data unit to be distributed. This data unit is then distributed to the edge management terminal corresponding to the dynamic transmission group via a dedicated network control link. Upon receiving the data unit, the edge management terminal parses it to obtain the distributed coded data and its associated time scheduling information. Based on a locally maintained absolute clock reference, the edge management terminal adds timestamp constraints to the distributed coded data and generates communication allocation driving instructions under these constraints. These instructions instruct each network-connected terminal within the dynamic transmission group to perform corresponding data transmission, relay, or reception operations within a specified time slot, thereby achieving adaptive communication allocation management based on the dynamic transmission group.

[0036] Furthermore, after performing adaptive communication allocation management on the distributed encoded data, the process includes: Based on the communication records of the dynamic transmission group, the transmission performance is determined by mining the group signal-to-noise ratio and service completion rate; if the transmission performance does not meet the preset threshold, the dynamic transmission group is reconstructed; based on the communication records, if there is a failed network access terminal in the dynamic transmission group, the dynamic transmission group is reconstructed based on the remaining network access terminals, wherein the failed network access terminal is any one of the source node, cooperating node or sink node configured.

[0037] The system records the operational status of the dynamic transmission group during communication. These records include at least the received signal-to-noise ratio (SNR), data packet success rate, latency information, and task completion status of each network-connected terminal. Based on these records, the system aggregates and analyzes the SNR statistics of each link within the dynamic transmission group, and combines this with the task flow's service completion index to calculate the transmission performance of the dynamic transmission group. This transmission performance characterizes the effectiveness of current communication scheduling and resource allocation. When the transmission performance falls below a preset threshold, a dynamic transmission group reconstruction process is triggered, re-executing the network-connected terminal screening and node role allocation to adapt to the current electromagnetic environment and task requirements. Furthermore, based on the communication records, when a network-connected terminal failure is detected within the dynamic transmission group (including communication interruption, capacity degradation, or inability to execute scheduling instructions on time), the system reconstructs the dynamic transmission group and reconfigures node roles using the remaining normal network-connected terminals as a baseline. The failed network-connected terminal can be configured as a source node, a cooperating node, or a sink node, thereby ensuring the continuity and robustness of task flow communication.

[0038] Furthermore, if the task flow received by the server is a multi-concurrent task flow, the distributed task queue is integrated and the task flow is pre-classified and split to determine the task flow cluster; dynamic transmission groups are constructed for each task flow cluster, and lightweight coroutine communication management for multi-task concurrency is performed. The task flow cluster and the dynamic transmission group correspond one-to-one. If there are terminals in the same network that are incorporated into at least two dynamic transmission groups, dynamic resource slicing configuration is performed on the terminals in the network.

[0039] When the server receives multiple concurrent task flows, it integrates these flows from different business sources or task requests, constructs a distributed task queue, and pre-classifies and distributes them based on task attributes such as priority, data size, timeliness requirements, and reliability level, forming multiple task flow clusters. Each task flow cluster corresponds to a set of tasks with similar or identical communication needs. The server executes a dynamic transport group construction process for each task flow cluster, generating a corresponding dynamic transport group for each cluster, thus establishing a one-to-one correspondence between task flow clusters and dynamic transport groups. During multi-task concurrent communication, the server or edge management terminal manages the communication process within the dynamic transport group using lightweight coroutines, allocating independent coroutine execution contexts to each task flow cluster to achieve parallel scheduling and communication control of multiple tasks. When the same network access terminal is detected to be incorporated into at least two dynamic transmission groups, the server or edge management terminal performs dynamic resource slicing configuration on the network access terminal, dividing the communication resources, computing resources and time slots of the network access terminal into multiple resource slices, and mapping them to the corresponding dynamic transmission groups respectively, so as to ensure the communication isolation and scheduling stability of each dynamic transmission group in the multi-task concurrent scenario.

[0040] In summary, the embodiments of this application have at least the following technical effects: Broadband cognitive radio front-ends are deployed at each network-accessible terminal to continuously scan the licensed frequency bands and adjacent frequency bands of the private network. The raw scan data is reported to the server to generate a four-dimensional spectrum map. The network-accessible terminals include private network base stations and key terminals. The server receives the task flow, performs data segmentation and multi-dimensional encoding, and determines the distributed coded data. Based on the task intent of the task flow, a dynamic transmission group is formed according to the network-accessible terminals in the electromagnetic environment based on the four-dimensional spectrum map. Absolute clock constraints are used at the edge management end, with the dynamic transmission group as the target communication network, to perform adaptive communication allocation management of the distributed coded data. This solves the technical problems of low spectrum utilization and fixed communication resource allocation methods in existing private network communication technologies, resulting in low communication efficiency. It achieves the technical effect of improving the efficiency and resource utilization of private network communication by dynamically forming transmission groups and performing adaptive communication allocation management.

[0041] Example 2, based on the same inventive concept as the private network-based intelligent communication method in the aforementioned examples, such as... Figure 2 As shown, this application provides an intelligent communication system based on a private network, wherein the system includes: Data acquisition module 11: Deploys broadband cognitive radio front-ends at each network access terminal, continuously scans the licensed frequency bands of the private network and adjacent frequency bands, reports the raw scan data to the server, and generates a four-dimensional spectrum map. The network access terminals include private network base stations and key terminals. Data processing module 12: The server receives the task flow, performs data segmentation and multi-dimensional encoding, and determines the distributed encoded data. Transmission group formation module 13: Based on the task intent of the task flow, in the electromagnetic environment based on the four-dimensional spectrum map, a dynamic transmission group is formed according to the network access terminals. Communication management module 14: At the edge management end, absolute clock constraints are used, and the dynamic transmission group is used as the target communication network to perform adaptive communication allocation management of the distributed encoded data.

[0042] Furthermore, the data processing module 12 is used to perform the following methods: The task flow is segmented into N data segments; each of the N data segments is encoded according to a predefined encoding dimension to determine N encoding vectors, wherein the encoding dimension includes frequency slices, time slots, spatial flow, and power weights; the N encoding vectors are integrated to determine distributed encoded data.

[0043] Furthermore, the transmission group assembly module 13 is used to perform the following method: Each network access terminal reports its network access capabilities, which are defined jointly based on communication, computing, mobility, and energy. Based on the network access capabilities and the task flow, an adaptive terminal node group is established under the constraints of interference behavior patterns to determine the dynamic transmission group.

[0044] Furthermore, the transmission group assembly module 13 is used to perform the following method: The dynamic transmission group consists of source nodes, cooperating nodes, and sink nodes. The construction of the dynamic transmission group includes: in a terminal cluster composed of network-connected terminals, screening network-connected terminals according to preset conditions to determine task flow terminals, wherein spatial avoidance, capability matching, and topology optimization are used as screening constraints; in the task flow terminals, execution is performed based on the arrangement of source nodes, cooperating nodes, and sink nodes and the establishment of temporary communication to form the dynamic transmission group.

[0045] Furthermore, the transmission group assembly module 13 is used to perform the following method: Based on the four-dimensional spectrum map, interference behavior patterns are determined, wherein the interference behavior patterns are determined based on the dynamic propagation and spatiotemporal distribution patterns of interference; the available bandwidth of the private network is virtualized with high granularity in the frequency-time domain to determine the smallest resource unit; the task intent based on the task flow is determined, and combined with the interference behavior patterns, the dynamic transmission group is actively woven into a multi-dimensional resource pattern based on the smallest resource unit to determine the resource weaving pattern, wherein the resource weaving pattern defines the frequency selection, time slots, spatial paths, and power allocation of each network-connected terminal covered by the dynamic transmission group in the next communication cycle.

[0046] Furthermore, the transmission group assembly module 13 is used to perform the following method: The resource weaving pattern is compiled into binary control instructions and sent to each network terminal in the dynamic transmission group via the communication bus to perform communication resource initialization.

[0047] Furthermore, the communication management module 14 is used to perform the following methods: The server encapsulates the distributed encoded data and sends it to the edge management terminal of the dynamic transmission group. The edge management terminal receives the distributed encoded data and, based on the timestamp constraint issued by the absolute clock of the edge management terminal, performs communication allocation drive management based on the dynamic transmission group.

[0048] Furthermore, the communication management module 14 is used to perform the following methods: Based on the communication records of the dynamic transmission group, the transmission performance is determined by mining the group signal-to-noise ratio and service completion rate; if the transmission performance does not meet the preset threshold, the dynamic transmission group is reconstructed; based on the communication records, if there is a failed network access terminal in the dynamic transmission group, the dynamic transmission group is reconstructed based on the remaining network access terminals, wherein the failed network access terminal is any one of the source node, cooperating node or sink node configured.

[0049] Furthermore, the communication management module 14 is used to perform the following methods: If the task flow received by the server is a multi-concurrent task flow, the distributed task queue is integrated and the task flow is pre-classified and split to determine the task flow cluster. Dynamic transmission groups are constructed for each task flow cluster, and lightweight coroutine communication management for multi-task concurrency is performed. The task flow cluster and the dynamic transmission group correspond one-to-one. If there are terminals in the same network, they are incorporated into at least two dynamic transmission groups, and dynamic resource slicing configuration is performed on the terminals.

[0050] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method of intelligent communication based on a private network, characterized by, The method includes: Broadband cognitive radio front-ends are deployed in each network access terminal to continuously scan the licensed frequency bands of the private network and adjacent frequency bands, and the original scan data is reported to the server to generate a four-dimensional spectrum map. The network access terminals include private network base stations and key terminals. The server receives the task stream, performs data segmentation and multidimensional encoding, and determines the distributed encoded data. Based on the task intent of the task flow, in the electromagnetic environment based on the four-dimensional spectrum map, a dynamic transmission group is formed according to the network-connected terminals. Absolute clock constraints are used at the edge management end, and the dynamic transmission group is used as the target communication network to perform adaptive communication allocation management of the distributed coded data.

2. The intelligent communication method based on a private network as described in claim 1, characterized in that, Data segmentation and multidimensional encoding are performed to determine distributed encoded data, including: The task flow is segmented into N data segments; According to the predefined encoding dimension, each data segment in the N data segments is encoded to determine N encoding vectors, wherein the encoding dimension includes frequency slices, time slots, spatial flow and power weights. By integrating the N encoded vectors, the distributed encoded data is determined.

3. The intelligent communication method based on a private network as described in claim 1, characterized in that, Establishing a dynamic transport group includes: Each network access terminal reports its network access capabilities, which are based on a joint definition of communication, computing, mobility, and energy. Based on the network access capability and the task flow, adaptive terminal node grouping is performed under the constraint of interference behavior mode to determine the dynamic transmission group.

4. The intelligent communication method based on a private network as described in claim 3, characterized in that, The dynamic transmission group consists of a source node, a cooperating node, and a sink node; The construction of the dynamic transmission group includes: In the terminal cluster composed of network access terminals, network access terminals are screened according to preset conditions to determine task flow terminals, among which spatial avoidance, capability matching and topology optimization are used as screening constraints. In the task flow terminal, the dynamic transmission group is formed by the arrangement of source nodes, cooperating nodes and sink nodes and the establishment of temporary communication.

5. The intelligent communication method based on a private network as described in claim 4, characterized in that, After constituting the dynamic transmission group, it includes: Based on the four-dimensional spectrum map, the interference behavior pattern is determined, wherein the interference behavior pattern is determined based on the dynamic propagation and spatiotemporal distribution law of interference. The available bandwidth of the private network is virtualized in a high-granularity manner in the frequency domain and time domain to determine the smallest resource unit; Based on the task intent determined by the task flow and combined with the interference behavior pattern, the dynamic transmission group is subjected to active multidimensional resource weaving based on the minimum resource unit to determine the resource weaving pattern. The resource weaving pattern defines the frequency selection, time slots, spatial paths and power allocation of each network-connected terminal covered by the dynamic transmission group in the next communication cycle.

6. The intelligent communication method based on a private network as described in claim 5, characterized in that, The resource weaving pattern is compiled into binary control instructions and sent to each network terminal in the dynamic transmission group via the communication bus to perform communication resource initialization.

7. The intelligent communication method based on a private network as described in claim 1, characterized in that, Using the dynamic transmission group as the target communication network, adaptive communication allocation management is performed on the distributed coded data, including: The server encapsulates the distributed encoded data and sends it to the edge management terminal of the dynamic transmission group; The edge management terminal receives the distributed encoded data and, based on the timestamp constraint issued by the absolute clock of the edge management terminal, performs communication allocation drive management based on the dynamic transmission group.

8. The intelligent communication method based on a private network as described in claim 1, characterized in that, After performing adaptive communication allocation management on the distributed encoded data, the process includes: Based on the communication records of the dynamic transmission group, the transmission performance is determined by mining the group signal-to-noise ratio and service completion rate; If the transmission performance does not meet the preset threshold, dynamic transmission group reconstruction is triggered. According to the communication records, if a network-entry terminal fails within the dynamic transmission group, the dynamic transmission group is reorganized based on the remaining network-entry terminals, wherein the failed network-entry terminal is any one of the source node, cooperating node, or sink node configured.

9. The intelligent communication method based on a private network as described in claim 1, characterized in that, If the task flow received by the server is a multi-concurrent task flow, integrate the distributed task queue and perform task flow pre-classification and diversion to determine the task flow cluster; Dynamic transmission groups are constructed for each task flow cluster, and lightweight coroutine communication management for multi-task concurrency is performed. The task flow clusters and dynamic transmission groups correspond one-to-one. If there are terminals in the same network that are incorporated into at least two dynamic transmission groups, dynamic resource slicing configuration is performed on the terminals.

10. An intelligent communication system based on a private network, characterized in that: The system is used to implement the intelligent communication method based on a private network according to any one of claims 1-9, the system comprising: Data acquisition module: Deploy broadband cognitive radio front-ends in each network access terminal, continuously scan the licensed frequency bands of the private network and adjacent frequency bands, report the raw scan data to the server, and generate a four-dimensional spectrum map. The network access terminal includes private network base stations and key terminals. Data processing module: The server receives the task stream, performs data segmentation and multidimensional encoding, and determines the distributed encoded data; Transmission group formation module: Based on the task intent of the task flow, in an electromagnetic environment based on the four-dimensional spectrum map, a dynamic transmission group is formed according to the network-connected terminals. Communication management module: At the edge management end, an absolute clock constraint is adopted, and the dynamic transmission group is used as the target communication network to perform adaptive communication allocation management of the distributed coded data.

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