Complex environment-oriented optical communication device dynamic interference compensation method and device

Abstract

The invention discloses a dynamic interference compensation method and device for an optical communication device in a complex environment, and relates to the technical field of optical communication, and the method comprises the steps: analyzing the interference parameters, the interference characteristics and the interference prediction range of the optical communication device in the complex environment; performing multi-level decomposition compensation from a hardware layer, a production process layer and a compensation algorithm layer according to the interference parameters, the interference characteristics and the interference prediction range, and establishing a multi-level compensation network; performing multi-layer cooperative compensation search based on the multi-layer compensation network to obtain a multi-layer compensation scheme; and extracting a static compensation result and a dynamic compensation relationship of the multi-level compensation scheme, and constructing a self-adaptive dynamic compensation strategy. The technical problem that in the prior art, multi-level cooperative compensation and self-adaptive adjustment of dynamic interference of an optical communication device in a complex environment are difficult to achieve is solved, and the technical effect that the anti-interference performance and the communication stability are improved through multi-level static and dynamic fusion compensation and a self-adaptive strategy is achieved.

Description

Technical Field

[0001] The present application relates to the field of optical communication technology, and in particular to a method and device for dynamic interference compensation of optical communication devices in complex environments. Background Art

[0002] As the core means of modern high-speed information transmission, optical communication is widely used in data centers, backbone networks, industrial Internet, aerospace and other fields. With the continuous expansion of application scenarios, optical communication systems have gradually migrated from ideal laboratory environments to a variety of complex and non-ideal environments, such as high temperature, strong electromagnetic interference, high vibration or strong light interference. Especially in scenarios such as industrial control, rail transportation, and long-distance communication, the variability and unpredictability of the environment place higher demands on the stability and communication quality of optical communication devices. However, most existing optical communication interference compensation technologies only optimize parameters under specific interference types or ideal experimental conditions, and often rely on a single compensation method, such as interference control based on hardware structure reinforcement, packaging material optimization, or bit error rate algorithm correction, and lack cross-layer collaboration and environmental perception capabilities.

[0003] In practical applications, interference sources in complex environments are often diverse and uncertain. Different interference types may overlap, couple, or even dynamically transform with each other. Existing compensation methods struggle to achieve coordinated identification and comprehensive responses to multiple interference factors. Furthermore, most current compensation schemes are highly static in design and fail to adapt adaptively to changing environmental conditions. This results in significant fluctuations in communication performance in dynamic and complex environments, significantly reducing device stability and anti-interference capabilities.

[0004] Therefore, there is an urgent need to propose an interference compensation scheme for optical communication devices that can integrate the characteristics of multiple interference factors, take into account hardware structure, process parameters and algorithm strategies, and support dynamic perception and adaptive adjustment, so as to achieve rapid modeling, accurate prediction and efficient compensation of interference effects in complex environments, thereby ensuring the long-term stable operation and communication reliability of optical communication systems. Summary of the Invention

[0005] This application solves the technical problem in the prior art that it is difficult to achieve multi-level collaborative compensation and adaptive adjustment of dynamic interference of optical communication devices in complex environments by providing a dynamic interference compensation method and device for optical communication devices in complex environments. It achieves the technical effect of improving anti-interference performance and communication stability through multi-level static and dynamic fusion compensation and adaptive strategies.

[0006] The present application provides a dynamic interference compensation method for optical communication devices in complex environments, and the method includes: analyzing the interference parameters, interference characteristics, and interference prediction range of optical communication devices in complex environments; performing multi-level decomposition compensation from the hardware layer, production process layer, and compensation algorithm layer according to the interference parameters, interference characteristics, and interference prediction range, and establishing a multi-level compensation network; performing multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation scheme; extracting the static compensation results and dynamic compensation relationships of the multi-level compensation scheme, and constructing an adaptive dynamic compensation strategy, wherein the static compensation result corresponds to the compensation fusion result of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation result is mapped and associated with the dynamic compensation relationship.

[0007] The present application also provides a dynamic interference compensation device for optical communication devices in complex environments, including: an environment analysis unit: analyzing the interference parameters, interference characteristics, and interference prediction range of optical communication devices in complex environments; a decomposition and compensation unit: performing multi-level decomposition and compensation from the hardware layer, production process layer, and compensation algorithm layer according to the interference parameters, interference characteristics, and interference prediction range, and establishing a multi-level compensation network; a compensation search unit: performing multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation scheme; a strategy construction unit: extracting the static compensation results and dynamic compensation relationships of the multi-level compensation scheme, and constructing an adaptive dynamic compensation strategy, wherein the static compensation result corresponds to the compensation fusion result of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation result is mapped and associated with the dynamic compensation relationship.

[0008] The present application proposes a method and apparatus for dynamic interference compensation of optical communication devices in complex environments to analyze interference parameters, interference characteristics, and interference prediction ranges of optical communication devices in complex environments; based on the interference parameters, interference characteristics, and interference prediction ranges, perform multi-level decomposition and compensation from the hardware layer, production process layer, and compensation algorithm layer to establish a multi-level compensation network; perform multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation scheme; extract the static compensation results and dynamic compensation relationships of the multi-level compensation scheme to construct an adaptive dynamic compensation strategy, wherein the static compensation results correspond to the compensation fusion results of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation results are mapped and associated with the dynamic compensation relationship. This solves the technical problem in the prior art that it is difficult to achieve multi-level collaborative compensation and adaptive adjustment of dynamic interference of optical communication devices in complex environments, and achieves the technical effect of improving anti-interference performance and communication stability through multi-level static and dynamic fusion compensation and adaptive strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the apparatus according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0010] Figure 1 A flow chart of a method for dynamic interference compensation of optical communication devices in complex environments provided in an embodiment of the present application.

[0011] Figure 2 A schematic structural diagram of a dynamic interference compensation device for optical communication devices in complex environments provided in an embodiment of the present application.

[0012] Explanation of the reference numerals: environment analysis unit 11 , decomposition and compensation unit 12 , compensation search unit 13 , strategy construction unit 14 . DETAILED DESCRIPTION

[0013] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0014] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0015] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0016] The embodiment of the present application provides a method for dynamic interference compensation of optical communication devices in complex environments, such as Figure 1 As shown, the method includes:

[0017] Analyze the interference parameters, interference characteristics, and interference prediction range of optical communication devices in complex environments.

[0018] In the embodiments of the present application, optical communication devices, also known as optical devices, are divided into optical active devices and optical passive devices. Optical active devices refer to key devices in optical communication systems that require power to drive and can realize the conversion or amplification function between electrical signals and optical signals. Typical representatives include lasers (such as DFB lasers), photodetectors, optical amplifiers, optocouplers, etc. Optical passive devices refer to devices that can work without external power supply and do not involve electro-optical or optoelectronic conversion. They mainly play the role of guiding, controlling, coupling or distributing optical signals. Typical examples include optical fibers, wavelength division multiplexers (WDM), optical isolators, optical splitters, optical modulators (certain types), etc. Both types of optical communication devices are affected by the external environment during use. For example, electromagnetic interference can interfere with their signal integrity, temperature fluctuations may cause thermal expansion of materials, optical path drift or wavelength drift, mechanical vibrations may damage the coupling structure of the device, and strong light exposure may cause optical saturation or damage. For each of these interference types, actual distribution data and temporal variation samples are collected within the target environment to identify possible interference types and obtain corresponding interference parameters, such as temperature, field strength, and vibration. Statistical analysis and pattern recognition are then performed on the collected data to extract the interference characteristics of each interference type. For example, for temperature interference, its daily variation range, peak frequency distribution, and system response hysteresis can be analyzed. For electromagnetic interference, its frequency band coverage, modulation characteristics, and coupling with the device transmission signal can be analyzed. This analysis establishes a feature set for each type of interference. After extracting interference parameters and features, the spatial and temporal information of the target environment is combined to further predict the impact range of the interference. Specifically, for environments with clear physical boundaries (visible range), the spatial distribution ratio can be used to predict regional expansion. For environments with uncertain boundaries or those significantly affected by dynamic factors (invisible range), the probability distribution of sample types is used to infer the interference expansion trend, thereby constructing a complete interference prediction range for subsequent multi-level compensation modeling.

[0019] Furthermore, the present application provides methods for analyzing interference parameters and interference characteristics of optical communication devices in complex environments, as well as interference prediction ranges, including:

[0020] Perform multi-dimensional analysis of electromagnetic interference, temperature environment changes, vibration mechanical interference, optical interference, and channel nonlinear changes in the target complex environment to obtain the type of interference. Determine the corresponding interference characteristics based on the sample data of the interference type. Collect sample data of the target complex environment to obtain the interference range. Perform an extended prediction of the environment proportion based on the time distribution and spatial distribution of the collected sample data to obtain the interference prediction range.

[0021] Preferably, a multi-dimensional interference analysis is performed on the target complex environment where the optical communication device is deployed to identify interference factors in the environment that may affect the performance of optical communication, including electromagnetic interference, temperature environment changes, vibration and mechanical interference, optical interference, and channel nonlinear changes. Taking optical interference as an example, in outdoor deployment or open optical channels, atmospheric turbulence often causes random light intensity fluctuations (flickering) and wavefront distortion, which are typical spatial optical interference. In order to determine whether such interference exists, a light intensity detector (such as a photodiode array) and a wavefront sensor (such as a Shack–Hartmann wavefront detector) can be deployed at the optical receiving end to collect the intensity change sequence and wavefront distortion of the incident light signal in real time. If the standard deviation of the light intensity per unit time exceeds the set threshold, or the wavefront distortion presents a non-Gaussian distribution and has non-stationary disturbance characteristics, it can be determined that there is atmospheric turbulence interference of medium or above intensity. Through similar methods as described above, the type of interference that may exist in the current target complex environment can be determined, providing direction for subsequent feature extraction, interference prediction, etc. Subsequently, the interference types identified above are compared with sample data in the interference sample library to extract the primary interference characteristics of each interference type. For example, for temperature environments, parameters such as the ambient temperature fluctuation frequency and thermal expansion-related curves can be extracted. For mechanical vibration, acceleration change frequency and resonant response frequency band can be used. For electromagnetic interference, the main frequency, modulation type, and field strength level can be extracted. The interference sample library is constructed based on historical data, experimental simulations, and other methods and includes typical characteristics of all interference types. Next, sample data from the target complex environment is collected. Based on the collected data, it is determined whether the interference range of the current optical communication device is within the visible or invisible range. Based on the determined interference range, the sample data is combined to perform a spatial and temporal range expansion prediction. For example, if a certain interference type occurs within a clearly bounded visible range, spatial expansion can be directly performed based on the existing distribution density to predict its interference impact range. If the interference type exists in an invisible range with blurred or irregular boundaries, a prediction is made based on the distribution probability of the interference samples. Ultimately, the interference prediction range is obtained, providing a basis for the subsequent compensation solution design to ensure communication stability.

[0022] Furthermore, the present application provides an extended prediction of the environmental proportion based on the temporal and spatial distribution of the collected sample data to obtain the interference prediction range, including:

[0023] Analyze the range type of the target complex environment, including a visible range and an invisible range. The visible range is an environment type with a clear range boundary, and the invisible range is an environment type without a clear range boundary. When the environment type is a visible range, perform an extended prediction based on the proportion of the spatial range of the spatial distribution to obtain an interference prediction range. When the environment type is an invisible range, perform an extended prediction based on the proportion of the spatial sample type of the spatial distribution to obtain an interference prediction range.

[0024] Optionally, when performing an expanded prediction of the environmental proportion, it is first necessary to analyze the scope type of the target complex environment and clarify the spatial boundaries of the interference source. To facilitate the controllability and scalability of interference prediction, the environment type is divided into visible and invisible scopes. The visible scope refers to an environmental area with physical or logical boundaries that clearly defines the spatial boundaries of the interference. For example, the service radius of a 5G communication base station, the interior of an optical communication equipment cabinet, or the isolated area of an industrial plant. The invisible scope refers to scenarios where the interference area has uncertain boundaries and shifts with equipment movement or environmental dynamics. For example, the spatial area where an on-board optical communication system operates in different terrains such as urban, mountainous, and grassland environments cannot be accurately demarcated by fixed boundaries. When the scope type of the target complex environment is visible, the prediction expansion can be directly based on the scope proportion of the interference source in the spatial distribution. Specifically, based on the data of each sub-area in the target complex environment recorded in the sample data, the number of interference events in each sub-area is counted, the total number of interference events is counted, and the interference spatial proportion of each sub-area is calculated, which is the ratio of the number of interference events in the sub-area to the total number of interference events. Subsequently, the interference space proportion is screened based on a spatial expansion threshold, obtaining multiple subregions greater than or equal to the threshold. The average interference strength of these subregions (e.g., electric field strength for electromagnetic interference, temperature fluctuation for temperature interference, and vibration intensity for mechanical vibration interference) is normalized, and the results are weighted to obtain the interference prediction range. When the target environment type is an invisible range, due to the lack of boundary information, statistics are required based on environmental sample classification and scenario type. Specifically, in a vehicle operation scenario, different geographical environment samples are collected during the vehicle's operation path, such as urban areas, plains, plateau environments, grasslands, forests, or mountainous areas, to form a set of spatial sample types. By analyzing the proportion of each geographical sample type in the overall operation trajectory, the spatial sample type proportion is constructed. The average interference strength of each spatial sample type is then determined based on historical data. The average interference strength is then weighted using the spatial sample type proportion as a weight to obtain the interference prediction range. In summary, the above-mentioned visible and invisible range distinction mechanism and corresponding prediction strategy can comprehensively construct the interference prediction range under current environmental conditions, providing a distribution basis for subsequent compensation network structural modeling and control strategy.

[0025] According to the interference parameters, interference characteristics and interference prediction range, multi-level decomposition and compensation are performed from the hardware layer, production process layer and compensation algorithm layer to establish a multi-level compensation network.

[0026] In one embodiment, after identifying and predicting complex environmental interference, hierarchical modeling and compensation design are performed at the hardware, production process, and compensation algorithm levels, focusing on the different source paths of interference affecting optical communication devices. This creates a well-structured, well-coupled, and multi-level compensation network. Specifically, at the hardware level, interference mechanisms that directly impact the physical structure of the device are identified based on the interference characteristics and distribution range. For example, to address thermal expansion issues caused by temperature fluctuations, packaging materials with matching thermal expansion coefficients can be designed to physically mitigate thermal stress. Compensation at the hardware level is achieved by establishing static physical compensation mechanisms corresponding to the interference type in the device structure and material selection. Subsequently, at the production process level, process flows most affected by interference are optimized based on the interference characteristics and distribution range. For example, to address the stress accumulation problem at the packaging interface caused by multiple thermal cycles, the stress distribution of the PLC chip can be adjusted to reduce the refractive index change caused by environmental stress. By constructing process-adjustable compensation relationships for different interference scenarios, a control compensation relationship at this level is formed, forming the foundational support for compensation integration with the hardware level. Finally, at the compensation algorithm layer, a mapping relationship between interference parameters and control compensation is established based on the interference characteristics and predicted range. This layer, primarily designed for programmable controllers, embedded control chips, or FPGA systems, rapidly corrects residual interference that the hardware and process layers fail to fully offset by implementing dynamic compensation mechanisms (such as PID control and model predictive control (MPC)). It also dynamically adapts to environmental changes, enabling real-time adjustment of control variables in response to interference inputs. To achieve an organic integration of these three layers, the compensation relationships of these layers are networked and integrated to construct a multi-level compensation network. In this network, the hardware and process layers serve as static top-level structures, forming a stable structural compensation framework for the device itself. The compensation algorithm layer, as a dynamic layer, forms a control-execution synergy with the upper static structure. Data linkage and feedback channels are established through interface protocols or control mapping tables, enabling response coupling, parameter coordination, and adaptive compensation across multiple levels, improving the interference resistance and communication stability of optical communication devices.

[0027] Furthermore, the present application provides multi-level decomposition compensation from the hardware layer, production process layer, and compensation algorithm layer, including:

[0028] According to the interference characteristics and interference prediction range, the compensation relationship of the hardware layer is established from the stress compensation of the silicon-based waveguide, the thermal expansion compensation of the packaging material, and the optical fiber array coupling optimization; according to the interference characteristics and interference prediction range, the compensation relationship of the production process layer is established from the stress process optimization and the packaging process optimization; according to the interference characteristics and interference prediction range, the dynamic compensation control parameters are analyzed, and the compensation relationship between the dynamic compensation control parameters and the characteristic compensation amount is established to obtain the dynamic control relationship of the compensation algorithm layer.

[0029] Preferably, based on interference characteristics and interference prediction ranges, a structured, multi-level compensation relationship is gradually established at the hardware, production process, and compensation algorithm levels, focusing on the anti-interference capabilities of optical communication devices in complex environments. At the hardware level, compensation design prioritizes the device structure for major interference sources such as temperature change and mechanical vibration. For temperature drift compensation, for example, an Athermal AWG module with self-stress compensation is employed. By optimizing the stress distribution in the silicon-based waveguide, the coupled offsetting of temperature-induced waveguide refractive index changes and thermal expansion effects is achieved. At the packaging level, a low coefficient of thermal expansion (CTE) packaging material is introduced to effectively control the linear expansion rate of the device structure within the -40°C to 85°C range, reducing wavelength drift to less than 0.02nm. This eliminates the need for active temperature control circuitry and improves system integration and reliability. For vibration interference, a precision coupling structure with a FA fiber array (supporting XYZ translation and angular rotation) with six-degree-of-freedom adjustment is employed, combined with a MEMS micromirror module to achieve dynamic, real-time compensation for small coupling offsets. This design leverages 83 existing high-precision coupling platforms to ensure optical path stability under interference frequencies below 10kHz, keeping coupling loss below 0.3dB. Ultimately, by summarizing the results of stress compensation, thermal expansion compensation, and coupling optimization, a compensation relationship between the silicon-based waveguide stress parameters, the packaging material thermal expansion parameters, and the fiber coupling adjustment parameters, and the corresponding interference characteristics, i.e., the hardware-level compensation relationship, was established. At the production level, process control was used to further enhance the device's tolerance to environmental fluctuations. To address stress sensitivity, ion implantation and annealing processes were used to precisely adjust the stress distribution in the PLC chip, reducing the impact of environmental stress on optical performance. This achieved a target refractive index fluctuation of less than 1×10⁻4, improving the long-term stability of the core structure. For EMI-sensitive components, such as WDM wavelength division multiplexers, a metallization packaging process combined with electromagnetic shielding materials such as nanosilver paste creates a complete EMI suppression layer. This ensures sealing performance while enhancing the device's shielding against external electromagnetic fields. Measured EMI attenuation exceeds 40dB, and the design is compatible with existing packaging production lines, keeping manufacturing costs manageable. Ultimately, a process compensation relationship was established between interference characteristics (such as temperature gradients and electromagnetic field strength) and the implantation process parameters and package shielding layer structure—in other words, a compensation relationship at the production process level. At the compensation algorithm level, a lightweight machine learning model based on historical data—interference characteristics, control parameters, and target compensation amounts—was established to address residual dynamic disturbances after hardware and process compensation, such as sudden temperature gradient changes, superimposed vibration interference, or composite optical path mismatches. This dynamic compensation control relationship was then formed.The lightweight machine learning model can be a neural network-based model, trained using forward propagation, loss calculation (such as mean squared error), backpropagation, and parameter optimization (such as the Adam optimizer). The dynamic compensation control relationship is decoupled and mapped with hardware layer structural parameters and process control settings through a standard interface to ensure data consistency and a closed-loop control between the dynamic and static layers. Ultimately, through the step-by-step modeling and linkage configuration of the three-layer compensation relationship, a complete multi-level compensation network is constructed, providing support for subsequent collaborative search and adaptive strategy control.

[0030] Furthermore, the present application provides for establishing a multi-level compensation network, including:

[0031] The hardware layer and the production process layer are used as the static top-level structure, wherein the nodes of the hardware layer and the production process layer are connected in series; the compensation algorithm layer is used as the dynamic top-level structure, and the static top-level structure and the dynamic top-level structure are connected in series as connecting nodes to construct a top-level structure; according to the compensation methods and compensation relationships of the hardware layer, the production process layer, and the compensation algorithm layer, the middle-level structure data relationship of each node in the top-level structure is established; based on the top-level structure and the middle-level structure data relationship, the multi-level compensation network is constructed.

[0032] Alternatively, the hardware layer and the production process layer can be connected in series as a static top-level structure to form a static compensation foundation covering the device's physical structure and manufacturing process, known as a dynamic top-level structure. In this structure, the hardware layer is responsible for resisting physical disturbances in complex environments through device design and material selection (such as silicon-based waveguide structures, low-thermal expansion packaging materials, and precision fiber-coupled components). The production process layer embeds compensation mechanisms during the device manufacturing process through stress and packaging process optimization, improving device stability from the source. The two layers work together to establish a static compensation strategy to maintain the basic operating performance and anti-interference capabilities of optical communication devices without control algorithm intervention. On this basis, the compensation algorithm layer is further connected to the static top-level structure as a dynamic top-level structure. Unlike the fixed compensation mechanism of the aforementioned static structure during design, the compensation algorithm layer, based on the basic compensation capabilities provided by the hardware and process, further addresses the dynamic changes in environmental interference during actual operation, accessing parameters in real time, executing control instructions, and assisting in adjusting the device's operating state. Specifically, the compensation algorithm layer establishes a correlation between interference signatures and dynamic compensation control parameters based on the parameter framework output by the static compensation strategy. During actual operation, it continuously monitors environmental changes such as sudden temperature changes, vibration interference, and electromagnetic wave variations, and performs real-time compensation adjustments to optical path coupling, operating wavelength, and power supply, thereby achieving adaptive tracking and response to complex interference. Based on this hierarchical configuration between the static and dynamic structures, a top-level structure is constructed, based on static physical optimization and supplemented by dynamic control response. In this result, the static top-level structure outputs various material selection parameters, structural alignment parameters, and process settings, while the dynamic top-level structure modifies input signals and fine-tunes execution instructions based on operating conditions. The two interact through pre-set interfaces and parameter transfer links, forming a joint static-dynamic compensation architecture. Subsequently, a middle-level structure data relationship is established based on data dependencies and logical mappings between the three layers. The middle-level structure is primarily responsible for transferring and mapping the compensation structure parameters generated by the static top-level structure to the real-time control parameters required by the dynamic top-level structure. For example, it can bind the waveguide length compensation structure in the static design to the wavelength offset control in the dynamic top-level structure, or map the package stress shield parameters to dynamic thermal drift compensation instructions. By establishing these intermediate data nodes, the entire compensation process ensures logical consistency, closed-loop control, and coordinated compensation across multiple layers. Finally, based on the linkage mechanism between the static top-level structure, dynamic top-level structure, and middle-level data relationships, a complete multi-level compensation network is constructed. This network features top-down coordination, closed-loop parameters, and a clear structural response. It can deploy compensation strategies at different levels based on the interference prediction range and current operating status, ensuring stable operation and continuous control of optical communication devices in complex environments.

[0033] A multi-level collaborative compensation search is performed based on the multi-level compensation network to obtain a multi-level compensation solution.

[0034] In one embodiment, after constructing a multi-layer compensation network encompassing hardware, production process, and compensation algorithm layers, a multi-layer collaborative compensation search is conducted within the network structure to determine an optimal, cross-layer coordinated compensation parameter combination based on identified interference characteristics and interference prediction ranges, thereby forming a multi-layer compensation solution adapted to the current complex environmental conditions. Specifically, the compensation search process first analyzes compensation parameters at each layer within the compensation network. For example, hardware-layer compensation parameters include waveguide stress design parameters, packaging material thermal expansion coefficients, and fiber coupling displacement adjustment ranges. By summarizing the compensation methods and compensation relationships at each layer, with the goal of satisfying the interference characteristics and their predicted ranges, and using maximizing compensation stability and minimizing compensation cost as evaluation parameters, feasible compensation parameter combinations within the current constraints are retrieved layer by layer. During the compensation search process, coordinated adjustments are made using data relationships within the compensation network. For example, when a stress compensation structure is selected at the hardware layer, matching annealing process conditions are automatically retrieved, and the ranges of certain sensitive parameters in the dynamic compensation are simultaneously restricted to avoid compensation redundancy or conflicts. This search process will be iterated repeatedly until it gradually converges to the optimal solution, thereby obtaining a multi-level compensation scheme to guide the actual deployment and operation of optical communication devices in complex environments.

[0035] Furthermore, the present application provides a multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation solution, including:

[0036] According to the multi-level compensation network, the compensation promotion relationship and the compensation consumption relationship of the compensation parameters at each level are analyzed according to the compensation relationship; with the goal of meeting the interference characteristics and the interference prediction range, maximizing the compensation stability and minimizing the compensation consumption are used as evaluation parameters, and according to the compensation promotion relationship and the compensation consumption relationship of the multi-level compensation network, each layer scheme is searched until the search stop condition is reached, and the compensation parameters of each level with the best evaluation results are combined to obtain the multi-level compensation scheme.

[0037] Optionally, after completing the construction of the multi-level compensation network, in order to obtain the optimal compensation strategy combination under the current interference characteristics and its prediction range, a multi-level collaborative compensation solution search is conducted based on the intrinsic relationship between the compensation parameters at each level in the hardware layer, production process layer, and compensation algorithm layer, based on the compensation promotion relationship and compensation consumption relationship. Specifically, the various compensation parameters in the multi-level compensation network are first analyzed to identify the action path and coupling influence of each parameter in the actual compensation process. The compensation promotion relationship refers to the fact that the adjustment of one compensation parameter can promote or enhance the synergistic effect of the compensation effects at other levels. For example, using an AthermalAWG component with excellent temperature drift compensation in the hardware layer can significantly reduce the real-time adjustment burden required by the compensation algorithm layer when the temperature changes drastically, thereby promoting the stability of dynamic compensation. The compensation consumption relationship refers to the resource consumption or system burden generated during the compensation process. For example, while high-precision alignment of the FA fiber array in the hardware layer improves compensation accuracy, it correspondingly increases the processing requirements in the packaging accuracy and coupling calibration process of the production process layer, thereby increasing manufacturing consumption. Based on an understanding of the promotion and consumption relationships between compensation parameters at each layer, with the core goal of satisfying the target interference characteristics and their predicted range, a multi-dimensional compensation search and evaluation parameter set is established. This involves maximizing compensation stability (i.e., the robustness and tolerance of the interference response) and minimizing compensation consumption (i.e., minimizing the cost of materials, energy, time, or system complexity). The search process begins with the hardware layer as a static starting point, first screening available physical compensation methods, such as the alignment capability of fiber optic arrays (FAs), the temperature drift tolerance of Athermal AWGs (Athermal AWGs), and the equalization capability of PLC splitters under multi-channel regulation. Subsequently, at the production process layer, based on the selected physical foundation, an adapted electronic signal compensation mechanism is implemented, such as a frequency-domain signal separation strategy based on a WDM wavelength division multiplexer (WDM) or an embedded LMS / RLS adaptive equalization module, to achieve dynamic compensation of nonlinear interference and signal degradation at the mid-layer. Subsequently, combined with historical operational data feedback and real-time monitoring results from the compensation algorithm layer, a built-in lightweight machine learning module or control logic unit further adjusts the operating parameters of the optical communication device, such as the temperature fine-tuning amplitude and electrical signal equalization parameters, to keep the dynamic disturbance within the compensation capability range. Then, through iterative convergence, each possible combination of three-level compensation parameters is evaluated. If the current combination reaches the set threshold in terms of compensation stability and the compensation consumption is within an acceptable range, it is retained as a candidate solution. When the search reaches the stopping condition (such as the target interference prediction interval is fully covered, or there is no new optimization space), the best one among all candidate solutions is output as the final multi-level compensation solution. This compensation solution integrates static structural design, manufacturing process configuration and dynamic control logic to achieve full-link coordination from the physical bottom layer to the control layer. It has good robustness and environmental adaptability, enabling optical communication devices to operate stably under multi-source disturbance conditions.

[0038] The static compensation results and dynamic compensation relationships of the multi-level compensation scheme are extracted to construct an adaptive dynamic compensation strategy, wherein the static compensation results correspond to the compensation fusion results of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation results are mapped and associated with the dynamic compensation relationship.

[0039] In one embodiment, after obtaining a multi-level compensation scheme, in order to achieve continuous and stable operation of optical communication devices in complex environments, it is necessary to extract and integrate the compensation elements of each layer in the scheme to construct a set of dynamic compensation strategies with environmental adaptability. The core of this strategy is to clarify the responsibility boundaries and response mechanisms between static and dynamic compensation, and to achieve collaborative operation through parameter mapping relationships. Specifically, the compensation configurations of the hardware layer and the production process layer are first extracted from the multi-level compensation scheme to form a static compensation result. The result covers the physical structure compensation means in the hardware layer (such as temperature drift adaptive waveguide structure, fiber coupling array, etc.) and the signal conditioning components in the production process layer (such as WDM multiplexer, embedded equalization module, etc.). These static compensation configurations jointly determine the range of environmental disturbances that the device can cover without relying on external control and adjustment, that is, the static tolerance band of the optical communication device. On this basis, the control parameter configuration and adjustment mechanism in the compensation algorithm layer are further extracted to form a dynamic compensation relationship, which corresponds to the real-time response process after the interference occurs. For example, for residual temperature drift, coupling error or signal nonlinear distortion, the wavelength fine-tuning step size, electrical signal gain compensation value, etc. are set to quickly complete the fine-tuning of the device working state. To achieve synergistic effects between static and dynamic compensation, the optimized hardware structure and process configuration define the environmental interference boundaries that the static combination can cover. Fluctuations outside these boundaries are then analyzed to identify the compensation dimensions and control amplitudes that require dynamic algorithmic control. Specifically, for a given interference variable, dynamic adjustment will not be triggered if it is within the static structural support range. Once it deviates from the static tolerance range, the corresponding dynamic control strategy will be invoked for compensation. For example, if the Athermal AWG module can control temperature drift within ±0.02nm, the dynamic algorithm layer will only invoke wavelength control fine-tuning instructions when the temperature drift exceeds this range, thus achieving a closed-loop compensation loop. If the embedded equalization module can pre-process signal distortion within a specific frequency band, the dynamic algorithm will only perform adaptive gain adjustment or reconstruction instructions for band-edge or out-of-band interference. This response mapping based on structural capabilities and disturbance characteristics logically binds static compensation results to dynamic compensation relationships, constructing an adaptive dynamic compensation strategy that intelligently switches compensation mechanisms based on interference conditions in complex environments, ensuring the long-term stability and responsiveness of optical communication devices.

[0040] Furthermore, the present application provides a method for constructing an adaptive dynamic compensation strategy, which further includes:

[0041] Detect environmental interference characteristics; perform compensation difference calculation on the environmental interference characteristics according to the static compensation result to obtain interference compensation parameters and compensation difference; use the interference compensation parameters and compensation difference as input variables, perform compensation analysis through dynamic compensation relationship to obtain dynamic compensation parameters, and perform adaptive control of optical communication device operating parameters according to the dynamic compensation parameters.

[0042] Preferably, after the adaptive dynamic compensation strategy is established, in order to achieve real-time response and compensation adjustment to environmental changes, it is necessary to dynamically execute the interference detection and parameter control process during the operation phase of the optical communication device to build a complete adaptive closed loop. First, through environmental sensors or operating status acquisition modules deployed inside and outside the optical communication device, the interference characteristics of the optical communication device's environment are detected in real time. These interference characteristics include but are not limited to the current ambient temperature, temperature change rate, mechanical vibration amplitude, vibration frequency, etc. The above interference parameters can be obtained by a thermistor, accelerometer, field strength probe, or signal analysis module. After detecting the current interference characteristics, the measured data is compared with the previously established static compensation results, and a compensation difference calculation is performed. That is, it is determined whether the current interference has been covered by the static compensation capabilities of the hardware layer and the production process layer. If the interference intensity or change trend exceeds the static tolerance range, the interference compensation parameters and compensation difference corresponding to the excess portion are calculated. This difference is the compensation content that needs to be intervened and processed by the dynamic algorithm layer. Subsequently, the interference compensation parameters and compensation difference are passed as input variables to the established dynamic compensation relationship to perform compensation analysis driven by the difference. A lightweight machine learning model analyzes the mapping relationship between the current difference and the control strategy, outputting corresponding dynamic compensation parameters. These include control instructions such as adjusting the optical device coupling position, fine-tuning the center wavelength, and adjusting the electronic equalization coefficient or gain value. Finally, based on these dynamic compensation parameters, the operating state of the optical communication device is adjusted in real time to achieve a rapid response to environmental disturbances. This adaptive control process requires no human intervention and can adjust the operating state immediately upon the occurrence of interference changes, maximizing the stability and reliability of communication performance and ensuring that optical communication devices can maintain high-reliability operation in complex and dynamic environments.

[0043] In the above, refer to Figure 1 The dynamic interference compensation method for optical communication devices in complex environments according to an embodiment of the present invention is described in detail. Figure 2 A dynamic interference compensation device for an optical communication device in a complex environment according to an embodiment of the present invention is described.

[0044] The dynamic interference compensation device for optical communication devices in complex environments according to an embodiment of the present invention is designed to address the technical problem in the prior art of difficulty in implementing multi-level coordinated compensation and adaptive adjustment for dynamic interference of optical communication devices in complex environments. This device achieves the technical effect of improving anti-interference performance and communication stability through multi-level static and dynamic fusion compensation and adaptive strategies. The dynamic interference compensation device for optical communication devices in complex environments includes: an environment analysis unit 11, a decomposition and compensation unit 12, a compensation search unit 13, and a strategy construction unit 14.

[0045] An environmental analysis unit 11 analyzes interference parameters, interference characteristics, and interference prediction ranges of optical communication devices in a complex environment; a decomposition and compensation unit 12 performs multi-level decomposition and compensation from the hardware layer, production process layer, and compensation algorithm layer according to the interference parameters, interference characteristics, and interference prediction range, and establishes a multi-level compensation network; a compensation search unit 13 performs multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation scheme; a strategy construction unit 14 extracts the static compensation results and dynamic compensation relationships of the multi-level compensation scheme, and constructs an adaptive dynamic compensation strategy, wherein the static compensation result corresponds to the compensation fusion result of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation result is mapped and associated with the dynamic compensation relationship.

[0046] Furthermore, the environment analysis unit 11 further includes:

[0047] Perform multi-dimensional analysis of electromagnetic interference, temperature environment changes, vibration mechanical interference, optical interference, and channel nonlinear changes in the target complex environment to obtain the type of interference. Determine the corresponding interference characteristics based on the sample data of the interference type. Collect sample data of the target complex environment to obtain the interference range. Perform an extended prediction of the environment proportion based on the time distribution and spatial distribution of the collected sample data to obtain the interference prediction range.

[0048] Furthermore, the environment analysis unit 11 further includes:

[0049] Analyze the range type of the target complex environment, including a visible range and an invisible range. The visible range is an environment type with a clear range boundary, and the invisible range is an environment type without a clear range boundary. When the environment type is a visible range, perform an extended prediction based on the proportion of the spatial range of the spatial distribution to obtain an interference prediction range. When the environment type is an invisible range, perform an extended prediction based on the proportion of the spatial sample type of the spatial distribution to obtain an interference prediction range.

[0050] Furthermore, the decomposition compensation unit 12 further includes:

[0051] According to the interference characteristics and interference prediction range, the compensation relationship of the hardware layer is established from the stress compensation of the silicon-based waveguide, the thermal expansion compensation of the packaging material, and the optical fiber array coupling optimization; according to the interference characteristics and interference prediction range, the compensation relationship of the production process layer is established from the stress process optimization and the packaging process optimization; according to the interference characteristics and interference prediction range, the dynamic compensation control parameters are analyzed, and the compensation relationship between the dynamic compensation control parameters and the characteristic compensation amount is established to obtain the dynamic control relationship of the compensation algorithm layer.

[0052] Furthermore, the decomposition compensation unit 12 further includes:

[0053] The hardware layer and the production process layer are used as the static top-level structure, wherein the nodes of the hardware layer and the production process layer are connected in series; the compensation algorithm layer is used as the dynamic top-level structure, and the static top-level structure and the dynamic top-level structure are connected in series as connecting nodes to construct a top-level structure; according to the compensation methods and compensation relationships of the hardware layer, the production process layer, and the compensation algorithm layer, the middle-level structure data relationship of each node in the top-level structure is established; based on the top-level structure and the middle-level structure data relationship, the multi-level compensation network is constructed.

[0054] Furthermore, the compensation search unit 13 further includes:

[0055] According to the multi-level compensation network, the compensation promotion relationship and the compensation consumption relationship of the compensation parameters at each level are analyzed according to the compensation relationship; with the goal of meeting the interference characteristics and the interference prediction range, maximizing the compensation stability and minimizing the compensation consumption are used as evaluation parameters, and according to the compensation promotion relationship and the compensation consumption relationship of the multi-level compensation network, each layer scheme is searched until the search stop condition is reached, and the compensation parameters of each level with the best evaluation results are combined to obtain the multi-level compensation scheme.

[0056] Furthermore, the strategy building unit 14 further includes:

[0057] Detect environmental interference characteristics; perform compensation difference calculation on the environmental interference characteristics according to the static compensation result to obtain interference compensation parameters and compensation difference; use the interference compensation parameters and compensation difference as input variables, perform compensation analysis through dynamic compensation relationship to obtain dynamic compensation parameters, and perform adaptive control of optical communication device operating parameters according to the dynamic compensation parameters.

[0058] The dynamic interference compensation device for optical communication devices in complex environments provided by an embodiment of the present invention can execute the dynamic interference compensation method for optical communication devices in complex environments provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0059] Although the present application makes various references to certain modules in the apparatus according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0060] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A dynamic interference compensation method for optical communication devices in complex environments, characterized in that: include: Analyze the interference parameters, interference characteristics, and interference prediction range of optical communication devices in complex environments; According to the interference parameters, their interference characteristics, and interference prediction range, multi-level decomposition and compensation are performed from the hardware layer, production process layer, and compensation algorithm layer to establish a multi-level compensation network; Performing a multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation solution; The static compensation results and dynamic compensation relationships of the multi-level compensation scheme are extracted to construct an adaptive dynamic compensation strategy, wherein the static compensation results correspond to the compensation fusion results of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation results are mapped and associated with the dynamic compensation relationship.

2. The method for dynamic interference compensation of optical communication devices in complex environments according to claim 1, characterized in that: Analyze the interference parameters and interference characteristics of optical communication devices in complex environments, as well as the interference prediction range, including: Conduct multi-dimensional analysis of electromagnetic interference, temperature environment changes, vibration mechanical interference, optical interference, and channel nonlinear changes in the target complex environment to obtain the type of interference. Determining corresponding interference features according to sample data of the interference type; Collect sample data of the target complex environment to obtain the interference range, and make an environmental proportion expansion prediction based on the time distribution and spatial distribution of the collected sample data to obtain the interference prediction range.

3. The method for dynamic interference compensation of optical communication devices in complex environments according to claim 2, characterized in that: Based on the temporal and spatial distribution of the collected sample data, an environmental proportion expansion prediction is performed to obtain the interference prediction range, including: Analyze the range type of the target complex environment, including a visible range and an invisible range. The visible range is an environment type with a clear range boundary, and the invisible range is an environment type without a clear range boundary; When the environment type is a visible range, an extended prediction is performed according to the spatial range proportion of the spatial distribution to obtain an interference prediction range; When the environment type is an invisible range, an extended prediction is performed according to the proportion of spatial sample types in the spatial distribution to obtain an interference prediction range.

4. The method for dynamic interference compensation of optical communication devices in complex environments according to claim 1, characterized in that: Multi-level decomposition and compensation are carried out from the hardware layer, production process layer, and compensation algorithm layer, including: Based on the interference characteristics and interference prediction range, a compensation relationship at the hardware layer is established from the perspectives of stress compensation of silicon-based waveguides, thermal expansion compensation of packaging materials, and optical fiber array coupling optimization; Based on the interference characteristics and interference prediction range, a compensation relationship of the production process layer is established from the perspective of stress process optimization and packaging process optimization; The dynamic compensation control parameters are analyzed according to the interference characteristics and interference prediction range, and the compensation relationship between the dynamic compensation control parameters and the characteristic compensation amount is established to obtain the dynamic control relationship of the compensation algorithm layer.

5. The method for dynamic interference compensation of optical communication devices in complex environments according to claim 4, characterized in that: Establish a multi-level compensation network, including: The hardware layer and the production process layer are used as the static top-level structure, wherein the nodes of the hardware layer and the production process layer are connected in series, and the compensation algorithm layer is used as the dynamic top-level structure, wherein the static top-level structure and the dynamic top-level structure are connected in series as connection nodes to construct the top-level structure; Establishing a middle-level structure data relationship of each node in the top-level structure according to the compensation methods and compensation relationships of the hardware layer, production process layer, and compensation algorithm layer; The multi-level compensation network is constructed according to the data relationship between the top-level structure and the middle-level structure.

6. The method for dynamic interference compensation of optical communication devices in complex environments according to claim 5, characterized in that: A multi-level collaborative compensation search is performed based on the multi-level compensation network to obtain a multi-level compensation solution, including: According to the multi-level compensation network, the compensation promotion relationship and the compensation consumption relationship of the compensation parameters at each level are analyzed according to the compensation relationship; With the goal of meeting the interference characteristics and its interference prediction range, maximizing compensation stability and minimizing compensation consumption are used as evaluation parameters. According to the compensation promotion relationship and compensation consumption relationship of the multi-level compensation network, each layer scheme is searched until the search stop condition is reached. The compensation parameter combination of each layer with the best evaluation result is obtained to obtain the multi-level compensation scheme.

7. The method for dynamic interference compensation of optical communication devices in complex environments according to claim 1, characterized in that: Build an adaptive dynamic compensation strategy, which also includes: Detect environmental interference characteristics; Performing compensation difference calculation on the environmental interference feature according to the static compensation result to obtain interference compensation parameters and compensation difference; The interference compensation parameter and the compensation difference are used as input variables, compensation analysis is performed through a dynamic compensation relationship to obtain dynamic compensation parameters, and adaptive control of optical communication device operating parameters is performed based on the dynamic compensation parameters.

8. A dynamic interference compensation device for optical communication devices in complex environments, characterized in that: The device is used to execute the method for dynamic interference compensation of optical communication devices in complex environments according to any one of claims 1 to 7, comprising: Environmental analysis unit: Analyzes interference parameters and interference characteristics of optical communication devices in complex environments, as well as interference prediction range; Decomposition and compensation unit: Based on the interference parameters, interference characteristics, and interference prediction range, multi-level decomposition and compensation are performed from the hardware layer, production process layer, and compensation algorithm layer to establish a multi-level compensation network; Compensation search unit: performs multi-level collaborative compensation search based on the multi-level compensation network to obtain a multi-level compensation solution; Strategy construction unit: extract the static compensation results and dynamic compensation relationships of the multi-level compensation scheme, and construct an adaptive dynamic compensation strategy, wherein the static compensation results correspond to the compensation fusion results of the hardware layer and the production process layer, the dynamic compensation relationship corresponds to the compensation scheme of the compensation algorithm layer, and the static compensation results are mapped and associated with the dynamic compensation relationship.

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