A Multichannel Optical Receiver Switching Method and System Based on TDD State Awareness

Abstract

This application discloses a multi-channel optical receiver handover method and system based on TDD state awareness, relating to the field of multi-channel optical receiver technology. The method includes: fusing environmental awareness data, channel quality indicators, and TDD state information for monitoring; freezing quality samples in the uplink time slot; obtaining stable preprocessed channel quality characteristics by smoothing and normalizing only the effective downlink samples; calculating a comprehensive evaluation score for each candidate optical channel by combining environmental attenuation characteristics and uplink / downlink duty cycle matching characteristics; and performing relative threshold judgment at a predetermined decision time within the TDD frame; restricting the handover action to be performed at the boundary of adjacent time slots, ensuring that channel selection takes into account link quality, service duty cycle requirements, and handover timing. This improves system stability and service continuity under complex atmospheric environments and TDD systems.

Description

Technical Field

[0001] This application relates to the field of multi-channel optical receiver technology, and in particular to a multi-channel optical receiver switching method and system based on TDD state awareness. Background Technology

[0002] With the rapid development of new optical communication systems such as free-space optical communication and flexible optical networks, multi-channel optical receivers are widely used to carry high-bandwidth, low-latency service flows. In scenarios such as ground-to-air links and outdoor backhaul links, parallel transmission using multiple wavelengths, multiple beams, or multiple modes of optical channels can significantly improve system capacity and spectrum utilization. However, optical link quality is highly sensitive to the atmospheric environment. Factors such as haze, smoke, and atmospheric turbulence can cause link attenuation and flicker, making it difficult for a single channel to operate stably for a long time. Therefore, multi-channel or multi-link switching is necessary to ensure service continuity.

[0003] To improve availability in complex environments, some systems introduce hybrid or backup links, switching between different links or optical channels via hard or soft handover. Hard handover schemes are simple in structure and low in implementation cost, but the handover logic often relies solely on instantaneous signal-to-noise ratio or threshold decisions, making them prone to the "ping-pong effect" of frequent round-trip handovers when link quality fluctuates, resulting in latency jitter and data loss. Soft handover schemes can simultaneously utilize multiple links or channels for traffic splitting or redundant transmission, offering higher reliability, but require complex resource management and power budgeting, resulting in high system overhead and making them difficult to promote in large-scale multi-channel scenarios.

[0004] On the other hand, Time Division Duplex (TDD) is increasingly widely used in converged wireless and optical wireless systems. TDD achieves flexible uplink and downlink bandwidth configuration by alternately dividing uplink and downlink time slots within the same frequency band, making it suitable for scenarios with asymmetrical traffic and dynamic loads. However, current multi-channel optical receiver switching strategies are often decoupled from the TDD frame structure, with coarse timing selection, frequently triggered during service transmission, failing to fully utilize the TDD time structure and uplink / downlink duty cycle information, and easily introducing additional latency and packet loss. Summary of the Invention

[0005] This application provides a TDD-based state-aware multichannel optical receiver switching method, system, storage medium, computer program product, and electronic device, which at least solves the problem in current related technologies that multichannel optical communication systems in complex environments have difficulty balancing link stability and service continuity during link switching.

[0006] In a first aspect, embodiments of this application provide a multi-channel optical receiver switching method based on TDD state awareness. The method includes: acquiring multi-source monitoring data for each candidate optical channel, the multi-source monitoring data including environmental awareness data, channel quality indicators characterizing the reception quality of the candidate optical channels, and TDD state information characterizing the operating mode of the optical communication system; the TDD state information including a current time slot type identifier and a corresponding time slot duty cycle parameter; performing state-aware preprocessing on the channel quality indicators based on the TDD state information, freezing the update of channel quality indicator samples for each candidate optical channel during uplink time slots, ensuring that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot, using the channel quality indicator samples during downlink time slots as valid samples, and performing time smoothing and normalization processing on the valid samples to obtain preprocessed channel quality features for each candidate optical channel; and generating a characterizing the degree of environmental impact on optical link attenuation based on the environmental awareness data. The environmental attenuation characteristics are analyzed; based on the time slot type identifier and time slot duty cycle parameter in the TDD state information, combined with the expected duty cycle of the current service for uplink and downlink resource allocation, a duty cycle matching feature is generated to characterize the degree of matching between the TDD frame structure and service requirements; based on the preprocessed channel quality characteristics, the environmental attenuation characteristics, and the duty cycle matching feature, a comprehensive evaluation score is calculated for each candidate optical channel; in each continuously running TDD frame cycle, at a predetermined decision time in each TDD frame cycle, the comprehensive evaluation score of the current receiving optical channel is obtained, and the comprehensive evaluation scores of each candidate optical channel are compared with the comprehensive evaluation score of the current receiving optical channel and a preset handover decision threshold. When it is detected that the comprehensive evaluation score of a candidate optical channel exceeds the handover decision threshold relative to the comprehensive evaluation score of the current receiving optical channel, the candidate optical channel is determined as the target receiving optical channel; within the time slot boundary adjacent to the predetermined decision time, the multi-channel optical receiver is controlled to switch from the current receiving optical channel to the target receiving optical channel.

[0007] Secondly, embodiments of this application provide a TDD state-aware multi-channel optical receiver switching system. The system includes: a multi-source monitoring data acquisition unit, used to acquire multi-source monitoring data for each candidate optical channel. The multi-source monitoring data includes environmental perception data, channel quality indicators characterizing the reception quality of the candidate optical channels, and TDD state information characterizing the operating mode of the optical communication system. The TDD state information includes a current time slot type identifier and a corresponding time slot duty cycle parameter. A state-aware preprocessing unit, used to perform state-aware preprocessing on the channel quality indicators based on the TDD state information. During uplink time slots, the updates of channel quality indicator samples for each candidate optical channel are frozen, ensuring that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot. Channel quality indicator samples during downlink time slots are used as valid samples, and time smoothing and normalization are performed on the valid samples to obtain preprocessed channel quality features for each candidate optical channel. A candidate channel feature scoring unit, used to generate a feature characterizing the environment's influence on the optical receiver based on the environmental perception data. The system includes: environmental attenuation characteristics affecting the link attenuation level; time slot type identifier and time slot duty cycle parameter in the TDD state information, combined with the expected duty cycle of the current service for uplink and downlink resource allocation, generating a duty cycle matching feature to characterize the degree of matching between the TDD frame structure and service requirements; calculating a comprehensive evaluation score for each candidate optical channel based on the preprocessed channel quality characteristics, the environmental attenuation characteristics, and the duty cycle matching feature; a handover condition decision unit, used to obtain the comprehensive evaluation score of the current received optical channel at a predetermined decision time in each continuously running TDD frame period, comparing the comprehensive evaluation scores of each candidate optical channel with the comprehensive evaluation score of the current received optical channel and a preset handover decision threshold, and determining the candidate optical channel as the target received optical channel when the comprehensive evaluation score of a candidate optical channel exceeds the handover decision threshold relative to the comprehensive evaluation score of the current received optical channel; and a channel handover control unit, used to control the multi-channel optical receiver to switch from the current received optical channel to the target received optical channel within the time slot boundary adjacent to the predetermined decision time.

[0008] Thirdly, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the TDD state-aware multichannel optical receiver switching method of any embodiment of this application.

[0009] Fourthly, embodiments of this application provide a storage medium storing a computer program thereon, characterized in that, when the program is executed by a processor, it implements the steps of the TDD state-aware multi-channel optical receiver switching method of any embodiment of this application.

[0010] Fifthly, embodiments of this application provide a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the TDD state-aware multichannel optical receiver switching method of any embodiment of this application.

[0011] The TDD-based state-aware multichannel optical receiver switching method and system provided in this application can achieve at least the following technical effects:

[0012] (1) By introducing a TDD state-aware channel quality preprocessing mechanism, the channel quality characteristics on which the handover decision is based are tightly bound to the TDD frame structure. During the uplink time slot, the updates of the channel quality indicators of each candidate optical channel are frozen, and only the quality estimate of the most recent downlink time slot is retained. Time smoothing and normalization are performed on the effective samples in the downlink time slot. As a result, the handover criterion is no longer directly exposed to the short-period fluctuations caused by TDD alternation, but is evaluated based on the stable quality characteristics under the actual downlink service carrying conditions. This allows the comprehensive evaluation results to reflect the continuous evolution of link quality rather than instantaneous disturbances, thereby reducing false handovers and round-trip handovers and stabilizing the service carrying link.

[0013] (2) Based on the aforementioned TDD-sensing channel quality characteristics, environmental attenuation characteristics and duty cycle matching characteristics are introduced to construct a multi-dimensional comprehensive scoring and time slot boundary switching mechanism oriented towards service requirements. Environmental attenuation characteristics are used to characterize the attenuation impact of the current atmospheric environment on each optical link, so that the comprehensive evaluation score can reflect the availability of the link in advance for a period of time in the future; duty cycle matching characteristics are used to characterize the degree of matching between the TDD frame structure and the current uplink and downlink resource requirements of the service, so that the selected target receiving optical channel has good link quality and its uplink and downlink time slot ratio is more in line with the service traffic structure. On this basis, at the predetermined decision time of each TDD frame period, the comprehensive evaluation scores of each candidate channel and the current channel are compared. Switching is triggered only when the advantage of the candidate channel exceeds the preset switching decision threshold, and the actual switching action is constrained to be completed within the adjacent time slot boundary. Thus, on the one hand, it ensures that each switching has a clear comprehensive performance benefit and suppresses frequent switching caused by slight differences; on the other hand, by completing the switching at the time slot boundary, it reduces the interference to ongoing data transmission and reduces packet loss and delay jitter.

[0014] This technical solution constructs an integrated handover control mechanism based on the time structure and uplink / downlink duty cycle information of the TDD system. This mechanism possesses state-aware multi-dimensional feature evaluation capabilities, performs centralized decision-making within the TDD frame period, and completes the receive channel handover at the time slot boundary. By uniformly mapping TDD state-aware channel quality characteristics, environmental attenuation characteristics, and duty cycle matching characteristics to a comprehensive evaluation score of candidate channels, and implementing threshold-based differential decision-making and boundary-aligned handover under the constraints of the TDD frame structure, stable handover, continuous carrying capacity, and delay jitter suppression of multi-channel optical receivers under complex environments and dynamic service loads are achieved without significantly increasing system complexity. This improves the service quality and operational robustness of the entire optical communication system in TDD scenarios. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating an example of a TDD state-aware multichannel optical receiver switching method according to an embodiment of this application is shown.

[0017] Figure 2 A flowchart illustrating an example of calculating the comprehensive evaluation score of each candidate optical channel according to an embodiment of this application is shown.

[0018] Figure 3 The diagram illustrates an example of the operation mechanism of a TDD state-aware multichannel optical receiver switching method according to an embodiment of this application.

[0019] Figure 4 This diagram illustrates a comparison of throughput over time using different methods.

[0020] Figure 5 A two-dimensional heatmap showing the overall evaluation score as a function of TDD duty cycle and optical channel SNR is presented.

[0021] Figure 6 A schematic diagram illustrating an example of the relationship between a handover decision and the SNR difference between a candidate channel and the current received channel, according to an embodiment of this application, is shown.

[0022] Figure 7 A structural block diagram of an example of a TDD state-aware multichannel optical receiver switching system according to an embodiment of this application is shown. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] It should be noted that among current related technologies, Free-Space Optical Communication (FSO) is widely used to build high-capacity, low-latency wireless backhaul and access links due to its near-optical fiber bandwidth and high security. Research indicates that FSO links are extremely sensitive to environmental conditions such as fog, smoke, precipitation, and atmospheric turbulence. Fog and smoke introduce additional attenuation primarily through scattering, while turbulence causes phase distortion and light flicker. A single FSO link is difficult to operate stably for extended periods under severe weather conditions. Therefore, some studies have proposed combining RF links with FSO links to form a hybrid RF / FSO system, improving overall availability by switching between FSO and RF links. A common approach is hard handover based on switch control, where only either the FSO or RF link is active at any given time. Other researchers have proposed soft handover, splitting or replicating service data between the two links to improve reliability, and attempting to combine channel state information or cognitive wireless technology to detect idle RF (Radio Frequency) resources. However, these solutions generally focus more on link-level redundancy between FSO and RF, and their utilization of the multi-wavelength, multi-beam, and other multi-channel access capabilities within the FSO remains limited.

[0025] In bidirectional transmission systems, TDD is widely used in various converged wireless and optical wireless systems because the transmitter and receiver share the same frequency band and can flexibly adjust the uplink and downlink bandwidth ratio. Some studies indicate that TDD requires strict alignment of transmit and receive handover within precisely aligned time slots; otherwise, mutual interference can easily occur in scenarios with multiple links or multiple cells deployed in parallel. Furthermore, the transmit / receive handover itself introduces inherent latency, which needs to be compensated for through frame structure design and guard slots. Although there is currently a large body of research on TDD frame structure design and adaptive configuration of uplink and downlink resources, this work is mostly focused on the radio frequency layer or macroscopic resource scheduling level. Relatively little attention has been paid to how multi-channel optical receivers select receiving channels within a TDD frame and how handover is organized at specific time slot boundaries. There is still a lack of handover control strategies deeply coupled with the characteristics of multiple optical channels.

[0026] At the level of multi-channel optical receiver devices, various tunable receiver structures have been proposed in some studies. For example, tunable receivers based on tunable optical filters or arrayed waveguide gratings can selectively receive signals across multiple wavelength channels. Other studies utilize rapidly tunable local oscillator lasers to construct heterodyne tunable receivers, reducing wavelength switching time to nanoseconds or even sub-nanoseconds, meeting the switching delay requirements in high-speed packet switching or flexible optical networks. On the other hand, multi-beam optical receivers and programmable silicon photonic mesh structures for spatial multiplexing have also been used to achieve adaptive separation and reception of multi-directional, multi-mode incident beams, improving link capacity and anti-interference capabilities. Meanwhile, extensive research has been conducted on issues such as flexible spectrum allocation and routing and spectrum assignment (RSA) in flexible optical networks, exploring how to achieve more refined resource utilization in the spectrum dimension. Overall, these works focus more on device-level fast tunability or network-layer spectrum / path allocation optimization, and still do not adequately consider the dynamic switching strategies of multi-channel optical receivers under specific TDD frame structures, or the joint consideration of atmospheric conditions and uplink / downlink service requirements.

[0027] In summary, current technologies still have certain shortcomings in the dynamic switching of multi-channel optical receivers: First, the utilization of TDD time structure and uplink / downlink duty cycle information is insufficient, making it difficult to schedule the receiving channel in a timely manner according to the role and resource allocation of different intra-frame time slots; Second, link selection and switching decisions often focus on instantaneous channel strength or simple threshold decisions, lacking a comprehensive characterization of atmospheric environmental changes, link flicker characteristics, and historical channel states; Third, the evaluation index system is relatively simple, making it difficult to establish a coordinated balance between channel quality, switching stability, and service carrying requirements; Fourth, the coupling between switching timing and service transmission process is not refined enough, easily triggering switching at unfavorable times, causing additional delays and data loss.

[0028] It should be understood that the above description of the relevant technologies is intended only to help the public better understand the inventive spirit and motivation of this application, and is not intended to limit this application. Furthermore, the technical solutions described in the above-mentioned relevant technologies are not prior art, and may also be undisclosed technical solutions, such as those under research or in the laboratory stage.

[0029] The technical solutions in this application, including the collection, storage, use, processing, transmission, provision, and disclosure of users' personal information, comply with relevant laws and regulations and do not violate public order and good morals.

[0030] Figure 1 A flowchart illustrating an example of a TDD state-aware multichannel optical receiver switching method according to an embodiment of this application is shown.

[0031] Regarding the execution subject of the method in the embodiments of this application, it can be any controller or processor with computing or processing capabilities, such as a digital signal processing board deployed in a centralized baseband unit, or an embedded control module integrated inside a multi-channel optical receiver; it can be a communication controller with a microprocessor and / or digital signal processor (DSP) as its core, which executes program instructions stored in a non-volatile storage medium to collect, buffer, and analyze multi-source monitoring data from the multi-channel optical receiver and external environmental sensors, completes the extraction and comprehensive scoring calculation of channel quality characteristics, environmental attenuation characteristics, and duty cycle matching characteristics, and generates a switching control command based on the switching decision threshold, and sends it to the optical selection switch, local oscillator tuning module, and gain control unit, thereby executing the switching control of the multi-channel optical receiver.

[0032] In some examples, it may be integrated into an electronic device or terminal through software, hardware, or a combination of both, and the type of terminal or electronic device may be diverse.

[0033] like Figure 1 As shown, in step S110, multi-source monitoring data for each candidate optical channel is acquired. The multi-source monitoring data includes environmental perception data, channel quality indicators used to characterize the reception quality of the candidate optical channel, and TDD status information used to characterize the operating mode of the optical communication system.

[0034] In some implementations, the multi-source monitoring data acquisition module can be deployed in the control unit of the multi-channel optical receiver and establish data interfaces with environmental sensors, the receiving front end, and the TDD scheduling control plane.

[0035] Specifically, environmental perception data can be provided by fog / smoke sensors, visibility sensors, temperature and humidity meteorological units, or camera image analysis modules to reflect current atmospheric transmittance, scattering intensity, and other environmental conditions. Channel quality indicators are collected by the receiver front-end corresponding to each candidate optical channel, including one or more indicators such as received optical power, signal-to-noise ratio, bit error rate, eye diagram opening, and forward error correction decoding margin, and uploaded to the control unit at a preset sampling period (e.g., according to the TDD frame period or an integer multiple of several frame periods). TDD status information is issued by the frame structure management module of the upper-layer wireless / optical wireless fusion system, including at least the current slot type identifier and the corresponding slot duty cycle parameters, such as the uplink / downlink type identifier of the current slot within the frame, the duration proportion of each type of slot in a TDD frame, and the current or soon-to-be-effective uplink / downlink duty cycle configuration. The control unit timestamps and caches various data according to a unified time base, enabling subsequent processing steps to be correlated and calculated within the same frame structure.

[0036] In step S120, state-aware preprocessing is performed on the channel quality index based on TDD state information. During the uplink time slot, the update of the channel quality index samples of each candidate optical channel is frozen, so that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot. The channel quality index samples during the downlink time slot are used as valid samples, and time smoothing and normalization processing is performed on the valid samples to obtain the preprocessed channel quality features for each candidate optical channel.

[0037] In some implementations, a time-slot state machine is constructed based on TDD state information to indicate whether the current time is in an uplink time slot, downlink time slot, or guard interval. Specifically, a channel quality sample buffer and a corresponding preprocessing feature register can be maintained for each candidate optical channel: when the state machine detects that the current time slot is downlink, it reads the latest channel quality index sample from the receiving front end, writes it into the buffer, and performs time smoothing operations within a preset sliding time window, such as using moving average, exponential weighted average, or median filtering to suppress instantaneous spikes; subsequently, based on the index range obtained from long-term statistics or a preset normalization coefficient, the smoothed channel quality index is normalized and mapped so that the preprocessed features of different channels fall within a unified numerical range, facilitating subsequent direct comparison and weighting. Conversely, when the state machine detects that the current time slot is uplink, the module no longer updates the channel quality sample of that channel from the receiving front end, but keeps the preprocessed channel quality features calculated in the most recent downlink time slot unchanged, only internally recording the current time slot state and frame number for subsequent association.

[0038] Through the above processing, the preprocessed channel quality characteristics are updated only in the downlink time slots based on the effective service carrying conditions, while remaining frozen during the uplink time slots. This avoids spurious fluctuations caused by uplink control signaling, noise measurements, or temporary probes interfering with handover decisions. Furthermore, time smoothing and normalization further ensure the continuity of channel quality characteristics in the time dimension and their comparability across channels. This allows subsequent comprehensive evaluation to no longer rely on single-point instantaneous indicators, but rather on a robust quality estimate under recent downlink service transmission conditions. This helps reduce the probability of misjudgments and ping-pong handovers, improving the stability of handover decisions.

[0039] In step S130, environmental attenuation features are generated based on environmental perception data to characterize the degree of influence of the environment on optical link attenuation; based on the slot type identifier and slot duty cycle parameter in the TDD state information, and combined with the expected duty cycle of the current service for uplink and downlink resource allocation, duty cycle matching features are generated to characterize the degree of matching between the TDD frame structure and service requirements; based on the preprocessed channel quality features, environmental attenuation features, and duty cycle matching features, a comprehensive evaluation score is calculated for each candidate optical channel.

[0040] Here, environmental perception data can be used as input, and parameters such as haze concentration, smoke particle density, visibility, and air humidity can be converted into scalar or vector features that characterize the degree of environmental impact on optical link attenuation using a preset physical model or empirical mapping relationship.

[0041] In some implementations, for each candidate optical channel's transmission path, path-related mapping can be performed on environmental data based on its elevation angle, propagation distance, and wavelength to obtain the environmental attenuation coefficient or environmental risk level corresponding to each channel. This is used to characterize the trend of link attenuation of the channel under current atmospheric conditions over a future period. Simultaneously, the duty cycle matching feature generation module calculates the degree of matching between the TDD frame structure and service requirements based on the slot type identifier and duty cycle parameters in the TDD state information, combined with the uplink and downlink traffic statistics and desired duty cycle configuration output by the upper-layer service management module. For example, a matching degree index can be constructed based on the difference between the downlink proportion of the current TDD configuration and the downlink traffic proportion of the current service. A higher matching degree indicates that the frame structure is more suitable for carrying the current service load structure.

[0042] After obtaining the preprocessed channel quality characteristics, environmental attenuation characteristics, and duty cycle matching characteristics, the comprehensive evaluation module can establish a unified scoring model for each candidate optical channel, mapping the above three types of characteristics into a comprehensive evaluation score.

[0043] For example, a configurable weighted summation model, a piecewise function model, or a rule-based scoring table can be used to collaboratively measure channel quality stability, environmental attenuation risk, and duty cycle matching. This allows the comprehensive evaluation score to simultaneously reflect the channel's overall performance in terms of link reliability, future availability, and service adaptability. Through this multi-dimensional feature fusion-based comprehensive scoring method, the system no longer considers only the current physical layer quality when comparing candidate channels, but also takes into account atmospheric environment evolution and uplink / downlink resource structure. This facilitates the selection of target receiving channels with superior overall performance during the current and expected service operation cycles.

[0044] In step S140, during each continuously running TDD frame period, at a predetermined decision time in each TDD frame period, the comprehensive evaluation score of the current received optical channel is obtained. The comprehensive evaluation scores of each candidate optical channel are compared with the comprehensive evaluation score of the current received optical channel and a preset handover decision threshold. When it is detected that the comprehensive evaluation score of a candidate optical channel exceeds the handover decision threshold relative to the comprehensive evaluation score of the current received optical channel, the candidate optical channel is determined as the target received optical channel.

[0045] Specifically, centralized decision-making using TDD frames as the time unit can be achieved by setting a TDD frame period timer in the system. A fixed, predetermined decision time can be selected within each TDD frame, such as a specific time after the end of a fixed downlink time slot or within a guard interval. Upon reaching the predetermined decision time, the comprehensive evaluation scores of the currently received optical channel and all candidate optical channels updated in the previous frame period are read, and a differential comparison is performed based on a preset handover decision threshold: for each candidate optical channel, the difference between its comprehensive evaluation score and the comprehensive evaluation score of the currently received optical channel is calculated. Only when this difference exceeds the handover decision threshold is the candidate channel considered to have sufficient handover benefit. Furthermore, when multiple candidate channels meet the conditions, the channel with the highest comprehensive evaluation score can be selected as the target received optical channel.

[0046] In some implementations, a minimum dwell time or a handover suppression window may be introduced to keep the current channel unchanged when no obvious dominant channel is observed within multiple consecutive TDD frame periods, in order to further suppress frequent handovers.

[0047] By centrally executing the aforementioned decision logic within a frame period, the handover decision naturally aligns with the TDD frame structure, enabling the system to perform a comprehensive evaluation of the previous frame's overall operating status at the end of each frame period, rather than being triggered by instantaneous fluctuations at arbitrary times. Furthermore, decisions based on the difference in comprehensive evaluation scores and preset thresholds ensure that handover is only triggered when a candidate channel demonstrates a significant advantage over the current channel in terms of channel quality stability, environmental adaptability, and duty cycle matching. This improves handover benefits while avoiding round-trip handovers caused by minor fluctuations, enhancing the stability and predictability of multi-channel optical receiver handover control.

[0048] In step S150, within the time slot boundary adjacent to the predetermined decision time, the multi-channel optical receiver is controlled to switch from the current receiving optical channel to the target receiving optical channel.

[0049] Here, based on the target receiving optical channel and the time slot boundary information of the current TDD frame, one or more time slot boundaries adjacent to the predetermined decision time are selected as the actual switching window.

[0050] In some implementations, the multi-channel optical receiver can employ an optical switch array, a tunable optical coupler, or a multi-wavelength selection device to switch the receiving path. The control unit sends a switching control command to the corresponding hardware when approaching the selected time slot boundary, enabling it to complete optical path reconstruction within the guard interval or idle time slot. During the switching process, the baseband processing module and the upper-layer protocol stack can temporarily freeze or mark the receiving buffer state at the current frame boundary. After the switching is complete, the synchronization relationship with the new receiving optical channel is re-established, ensuring a smooth continuation of subsequent frame header detection, clock recovery, and data demodulation. Simultaneously, metadata such as the switching time and frame number can be recorded before and after the switching, providing a basis for subsequent statistical analysis and strategy optimization.

[0051] By strictly constraining handover execution within the time slot boundary adjacent to the predetermined decision time, on the one hand, physical layer handover can be avoided in time slots where service data is being transmitted, reducing the risk of carrier interruption and data frame truncation, and lowering packet loss rate and instantaneous latency jitter; on the other hand, the handover time point is naturally aligned with the TDD frame structure, making it easier for upper-layer scheduling and buffer management to predict and adapt to handover behavior, which is conducive to maintaining the timing consistency and service continuity of the entire link, thereby minimizing the disturbance to existing network services while realizing channel handover.

[0052] In some examples of embodiments of this application, the predetermined decision time is set at the boundary time between the downlink time slot and the uplink time slot in the TDD frame structure and / or the boundary time between the downlink time slot and the reserved gap, so that the determination of the target receiving optical channel is completed at the predetermined decision time and the handover decision is aligned with the downlink receiving time slot.

[0053] Specifically, the controller of the multi-channel optical receiver can maintain a clock and counter synchronized with the TDD frame locally based on the TDD frame structure parameters configured in the system (including frame period, start and end times of each time slot, uplink and downlink duty cycles, and reserved slot positions, etc.), and trigger a handover decision process at the boundary moment of the end of each downlink time slot. At this boundary moment, the controller calls the previously completed comprehensive evaluation calculation results, reads the latest comprehensive evaluation score of the current received optical channel and all candidate optical channels in this frame, and determines whether there is a target received optical channel according to a pre-set threshold and comparison rules. If it exists, the target received optical channel is marked and buffered at this moment.

[0054] Since the predetermined decision time is chosen at the moment when downlink reception has just been completed, the channel quality data, environmental characteristics, and duty cycle matching characteristics used at this time all correspond to the most recent downlink service carrying status. This allows the handover decision to be closely aligned with the actual performance of the downlink reception time slot. This avoids making hasty decisions based on "frozen" old data during uplink and also reserves sufficient time for subsequent handover using the following uplink time slot or reserved slots, thereby improving the rationality and controllability of the handover timing selection.

[0055] Then, when it is determined that a switch from the current receiving optical channel to the target receiving optical channel is required, the switching control command used to control the multi-channel optical receiver to perform hardware reconfiguration is scheduled to be issued and executed in the uplink time slot and / or reserved gap time immediately following the downlink time slot. This ensures that the actual switching process of the multi-channel optical receiver is completed in the uplink time slot and / or reserved gap time, thereby avoiding interruption of service data reception in the downlink time slot.

[0056] Here, when it is determined that a switch from the current receiving optical channel to the target receiving optical channel is required, the controller will not immediately trigger a physical layer switch within the downlink time slot. Instead, the switch control command used to control the multi-channel optical receiver to perform hardware reconfiguration will be issued and executed in the uplink time slot and / or the reserved time slot immediately following the downlink time slot.

[0057] Specifically, after determining the target receiving optical channel, the controller selects one or more consecutive uplink time slots and / or reserved gaps as "switching execution windows" based on the start time of the uplink time slot after the downlink ends in the current TDD frame structure and the position of the reserved gap. At the beginning of this window, the controller sends a switching control command to the optical front end and related adjustable modules (such as optical switches, adjustable filters, different frequency local oscillators, programmable photonic grids, etc.) to drive them to reconfigure the receiving path from the current receiving optical channel to the target receiving optical channel.

[0058] In terms of control strategy, the controller can reserve sufficient time margin for the handover execution window by considering the maximum latency required for hardware reconfiguration. This ensures that all reconfiguration actions are completed before the start of the next downlink time slot, and the success of the handover can be confirmed by status readback or calibration signal detection. As a result, the actual handover process of the multi-channel optical receiver is strictly limited to the uplink time slot and / or reserved gap time. The downlink time slot maintains a stable and continuous receiving link throughout, avoiding interruptions, frame truncation, or packet loss caused by port switching, filter frequency sweeping, or local oscillator frequency hopping during downlink service payload transmission. Therefore, without sacrificing handover flexibility, it effectively reduces service latency jitter and data loss risks, significantly improving the system's support capability for real-time and high-reliability services.

[0059] Figure 2A flowchart illustrating an example of calculating the comprehensive evaluation score of each candidate optical channel according to an embodiment of this application is shown.

[0060] like Figure 2 As shown, in step S210, the wavelength parameters and beam direction angle parameters corresponding to the current received optical channel and each candidate optical channel are obtained.

[0061] In some implementations, the system can assign a unique channel identifier to each optical channel during the initialization or configuration phase, and record the center operating wavelength, possible wavelength tuning range, and directional information such as azimuth and elevation angles of the corresponding transmit / receive beams in the configuration table. These parameters can be derived from the system's static configuration file, or they can be dynamically corrected by combining the real-time measurement results of the wavelength locking module, the spectrum monitoring module, or the pointing error monitoring module.

[0062] Specifically, based on the current received optical channel ID and the candidate optical channel ID, the corresponding center wavelength value and beam pointing angle vector can be read from the configuration table or register, and these parameters can be cached locally for subsequent calculation of the differences between them and the resulting reconstruction overhead.

[0063] In step S220, based on the acquired wavelength parameters and beam direction angle parameters, the switching cost index of each candidate optical channel is calculated; the switching cost index is used to characterize the hardware reconfiguration overhead required by the multi-channel optical receiver when switching from the current receiving optical channel to each candidate optical channel.

[0064] Specifically, for systems employing tunable filters or tunable local oscillator lasers, the adjustment time, energy consumption, and potential transient instability duration required for wavelength switching can be estimated based on the difference between the current operating wavelength and the target channel's operating wavelength, combined with the pre-calibrated "tuning distance-tuning time" or "tuning distance-energy consumption" curves of the devices. For systems using MEMS mirrors, optical phased arrays, etc., for beam pointing control, the time required to complete the pointing reconfiguration and the control complexity can be estimated based on the angular difference between the current beam direction angle and the target direction angle, combined with the angular velocity, acceleration, and settling time characteristics of the actuator.

[0065] In some implementations, the physical quantities such as time, energy consumption, and number of control steps mentioned above can be normalized and mapped to a dimensionless switching cost index, for example, by taking a weighted sum and then scaling it to the [0,1] range, where a larger value indicates a higher switching cost.

[0066] For example, the normalized wavelength difference and normalized beam direction difference of each candidate optical channel relative to the current received optical channel are calculated, and the corresponding handover cost index is obtained by weighted fusion:

[0067] Equation (1)

[0068] Equation (2)

[0069] Equation (3)

[0070] In the formula, and They represent the first The candidate optical channels at time... Compared to the normalized wavelength difference and normalized beam direction difference of the current receiving optical channel, It is a time variable; Indicates the first The candidate optical channels at time... Switching cost metrics Indicates the current received optical channel at time [time]. wavelength parameters, Indicates the first The candidate optical channels at time... wavelength parameters, Indicates the current received optical channel at time [time]. The beam direction angle parameters, Indicates the first The candidate optical channels at time... The beam direction angle parameters, As a wavelength normalization reference, This serves as a reference value for the normalized orientation angle. and This is the switching cost weighting coefficient, used to adjust the weighting of the impact of wavelength switching and beam direction switching on the switching cost index.

[0071] In some implementations, the multichannel optical receiver maintains a channel configuration table to record the currently received optical channel and each candidate optical channel at time... wavelength parameters and beam direction angle parameters At the decision point of each TDD frame, the controller reads the above parameters from the configuration table, calculates the wavelength difference and beam direction difference of each candidate optical channel relative to the current received optical channel according to equations (1) and (2), and uses a pre-set normalized reference quantity. and Different physical quantities are uniformly mapped to dimensionless normalized wavelength differences. Normalized beam direction difference Subsequently, the switching cost index is obtained by weighting and merging the two normalized differences according to equation (3). The weighting coefficient and Calibration can be performed based on statistical data of wavelength tuning time and beam pointing adjustment time in a specific hardware platform, thereby increasing performance when wavelength adjustment overhead is high. Increase when beam pointing changes are more sensitive to the impact on the link. .

[0072] In this way, the switching cost index not only quantitatively reflects the wavelength and beam reconstruction amplitude required when switching from the current receiving optical channel to a candidate optical channel, but also imposes a stronger penalty on large adjustments by using the square term, prompting the subsequent decision-making process to avoid frequently selecting high-cost channels and reducing the switching delay and bit error risk caused by optical tuning and pointing calibration.

[0073] In step S230, a comprehensive evaluation score is calculated for each candidate optical channel based on preprocessed channel quality characteristics, environmental attenuation characteristics, duty cycle matching characteristics, and handover cost indicators.

[0074] In some implementations, various features can be normalized first to ensure they fall within the same or comparable numerical range. Then, a scoring function is constructed based on weight parameters preset by the system or adjusted during runtime. For example, a single score value can be obtained through weighted linear combination or nonlinear mapping in a multi-dimensional feature space. Different service types or service levels can be configured with different weights. For instance, for latency-sensitive services, the weight of handover costs can be increased to avoid frequent reconfiguration for limited quality improvements; for extremely high-reliability services, the weight of channel quality-related features can be increased. Thus, the system generates a unified comprehensive evaluation score for each candidate optical channel that reflects both link quality and environmental adaptability, as well as the degree of TDD duty cycle matching and handover hardware costs. This helps to suppress invalid handovers, reduce system reconfiguration overhead, and improve overall operational stability.

[0075] More specifically, the preprocessed channel quality characteristics, environmental attenuation characteristics, and duty cycle matching characteristics of each candidate optical channel are normalized to obtain normalized channel quality evaluation values, normalized environmental attenuation values, and normalized duty cycle matching values, thereby determining the intermediate quality utility values ​​of each candidate optical channel.

[0076] Equation (4)

[0077] In the formula, , and They represent the first The candidate optical channels at time... The normalized channel quality evaluation quantity, the normalized environmental attenuation quantity, and the normalized duty cycle matching quantity. For the first The candidate optical channels at time... The intermediate quality utility value, , and These represent the channel quality sensitivity coefficient, duty cycle matching sensitivity coefficient, and environmental attenuation sensitivity coefficient, respectively.

[0078] In some implementations, after obtaining the handover cost metric, the controller further normalizes the preprocessed channel quality characteristics, environmental attenuation characteristics, and duty cycle matching characteristics of each candidate optical channel, mapping them to normalized channel quality evaluation values ​​within the interval [0,1]. Normalized environmental degradation and normalized duty cycle matching quantity The larger ones The better the channel quality, the larger the value. This indicates that the more closely the uplink and downlink duty cycle allocation matches business needs, the better the allocation is to business requirements. This indicates that the environmental degradation is more severe.

[0079] Based on the above normalized values, the intermediate quality utility value is calculated according to equation (4). ,in , and The sensitivity coefficient is designed to be configurable or adaptively adjustable over time to determine the relative strength of the influence of three factors—channel quality, duty cycle matching, and environmental attenuation—on the overall utility.

[0080] By employing an exponential superposition of multiple factors, even a slight improvement in channel quality or duty cycle matching can be mitigated in highly sensitive scenarios. The above is manifested as exponential amplification, while the deterioration of environmental degradation exponentially suppresses the utility value through the negative coefficient, thereby achieving nonlinear fusion of multi-source features, which is more in line with the actual correspondence between channel quality and service experience in complex wireless fiber fronthaul and backhaul links, and improves the responsiveness of the comprehensive evaluation results to changes in edge conditions.

[0081] Furthermore, the intermediate quality utility value and switching cost index are used to determine the first The overall evaluation score of each candidate optical channel:

[0082] Equation (5)

[0083] In the formula, For the first The candidate optical channels at time... The overall evaluation score This is the switching cost sensitivity coefficient.

[0084] In equation (5), and Multiplication results in the exponential factor approaching 1 when the handover cost is low, and the overall evaluation score is mainly determined by positive factors such as channel quality and duty cycle matching. However, when the handover cost is high, the exponential factor decreases rapidly, effectively suppressing the selection of candidate optical channels as target optical channels even if they are superior in quality and utility but have excessive reconstruction costs.

[0085] Therefore, the comprehensive evaluation score simultaneously reflects the trade-off between channel quality benefits and handover costs on the same number axis, enabling more robust and efficient utilization of multi-channel resources and reducing the risk of ping-pong effect and sudden increase in instantaneous bit error rate caused by blind and frequent handover.

[0086] Regarding the implementation details of preprocessing channel quality characteristics for generating candidate optical channels, in some examples of embodiments of this application, for each candidate optical channel... The raw signal-to-noise ratio measurement value is obtained at the moment when the TDD state is the downlink time slot. The smoothed signal-to-noise ratio estimate is updated based on an exponential smoothing strategy. It satisfies:

[0087] Equation (6)

[0088] In the formula, As a smoothing factor, This is the smoothed signal-to-noise ratio estimate from the previous sampling time.

[0089] At the moment when the TDD state is the uplink time slot, the smoothed signal-to-noise ratio estimate remains unchanged, satisfying the following conditions: This freezes the channel quality index sample updates for each candidate optical channel during the uplink time slot.

[0090] In some implementations, the multichannel optical receiver checks each candidate optical channel when each downlink time slot arrives. Collect a raw signal-to-noise ratio measurement. Because the downlink is susceptible to short-term fast fading, random noise, and receiver gain fluctuations, directly using instantaneous measurement results will lead to unstable channel quality assessment.

[0091] Therefore, in this embodiment, the smoothed signal-to-noise ratio estimate is updated using an exponential smoothing strategy according to equation (6). Smoothing factor Used to adjust the weights of the current measurement and historical estimates, when When the value is larger, the focus is more on tracking the current channel changes. When the value is smaller, the focus is more on suppressing random noise. During the TDD state in the uplink time slot, no new downlink measurements are collected; instead, [the following is set]. This means freezing the update of the smooth signal-to-noise ratio estimate, thereby avoiding misinterpreting uplink self-interference or invalid measurements as changes in downlink channel quality.

[0092] Through the above processing, time-domain filtering of the original signal-to-noise ratio sequence can be achieved without increasing hardware complexity, making the obtained smooth signal-to-noise ratio estimate more stable and reliable.

[0093] Based on the smoothed signal-to-noise ratio estimates of each candidate optical channel at each time step A first-order state-space model is established, using the smoothed signal-to-noise ratio estimate as the observation, to model the true channel gain state, thus making the true channel gain state... The observed output satisfies:

[0094] Equation (7)

[0095] In the formula, These are the state transition coefficients. and These are process noise and measurement noise, respectively.

[0096] To obtain a smoothed signal-to-noise ratio estimate updated by time slot. Then, a first-order state-space model is established based on the time-series behavior of each candidate optical channel, as shown in equation (7), to represent the actual channel gain state. Considered as a stochastic process with inertia, the state transition coefficients Describe the correlation of channel gain between adjacent sampling times, process noise. This characterizes the slow channel drift caused by factors such as user movement and changes in obstructions; simultaneously, it smooths the signal-to-noise ratio estimate. As an observation output, noise is measured. This reflects the remaining measurement and modeling errors. Using this state-space model, the controller can adjust the state variables at each sampling time using the current observations. By performing corrections, the main trend of channel evolution over time can be preserved while filtering out measurement noise. Compared with directly extrapolating and predicting the smooth signal-to-noise ratio, this is more in line with the physical characteristics of the slow change of channel gain over time in wireless fiber optic links, and can provide a more accurate basis for channel state decisions in the next frame.

[0097] Using a state-space model, the smoothed signal-to-noise ratio estimate at each time step is obtained. As input observations, the true channel gain state By performing recursive estimation, the downlink time slot time in the next frame can be obtained. Predicted state The predicted state is used as the predicted signal-to-noise ratio for the next downlink time slot, satisfying:

[0098] Equation (8)

[0099] In the formula, This represents the time interval from the current moment to the next downlink time slot;

[0100] Predict signal-to-noise ratio Perform a normalization mapping to obtain the representation of the first... The candidate optical channels at time... Normalized channel quality evaluation metric .

[0101] More specifically, after completing the state-space modeling, the controller employs a recursive estimation algorithm (such as Kalman filtering or a simplified version) to utilize the smoothed signal-to-noise ratio estimate at the current time step. Continuously update the estimate of the true channel gain state. And based on the time interval between the next downlink time slot and the current time. The predicted state of the next frame downlink time slot is derived according to equation (8). It is regarded as the predicted signal-to-noise ratio. .

[0102] Subsequently, the system operates according to the pre-calibrated signal-to-noise ratio range. right Perform linear or nonlinear normalization mapping to compress it to the [0,1] interval, thereby obtaining the value used to characterize the candidate optical channel at time [0,1]. Normalized channel quality evaluation metric .

[0103] By using state-space-based forward prediction, instead of simply relying on the measurement results at the current moment, the channel quality of the next downlink time slot is directly estimated. This enables the comprehensive scoring and handover decision to respond in advance to upcoming channel changes. In scenarios with user movement or rapid environmental changes, it effectively reduces the probability of misjudgment caused by channel lag estimation and improves the timeliness and stability of multi-channel optical receiver handover.

[0104] Regarding the implementation details of generating environmental degradation characteristics, in some examples of embodiments of this application, the haze concentration index corresponding to the environmental perception data is analyzed. and rainfall intensity The normalized haze concentration index was obtained after normalization. and normalized rainfall intensity And construct an environmental perception data function through weighted fusion. :

[0105] Equation (9)

[0106] In the formula, ,and , used to characterize the relative weights of the effects of haze and rainfall on optical link attenuation.

[0107] Based on environmental perception data functions An exponential decay model was constructed to obtain the environmental decay factor. It satisfies:

[0108] Equation (10)

[0109] In the formula, The environmental sensitivity coefficient; As each candidate optical channel at time Normalized environmental degradation To characterize at time The more severe the environmental degradation, the more The larger the characteristic.

[0110] In some implementations, the multi-channel optical receiver periodically acquires the haze concentration index covering the current optical link area. With rainfall intensity Because different sensors have different dimensions and value ranges, the first step is to... and Normalization was performed to obtain the normalized haze concentration index. and normalized rainfall intensity This maps both types of indicators to the interval ([0,1]). Then, according to equation (9), a weighted summation method is used to construct the environmental perception data function. The weight and This reflects the relative importance of haze and rainfall in link attenuation; for example, in haze-dominated atmospheric scattering scenarios, a setting can be made. Larger The smaller the value, the less the impact of the haze index on the overall environmental quality.

[0111] Based on the obtained An exponential environmental degradation model is constructed according to equation (10), and the environmental sensitivity coefficient is used to determine the degradation rate. The strength of the impact of environmental changes on link transmittance: when When the value is large, even a small increase in the environmental indicator can lead to The signal decreases rapidly, reflecting the physical characteristic of rapidly increasing signal attenuation under severe weather conditions; conversely, when... When the value is small, It is more adaptable to environmental changes. Furthermore, it will... As a normalized environmental attenuation value for each candidate optical channel, it is used to characterize the degree of optical power loss caused by the environment at the current moment. The larger the value, the more severe the atmospheric absorption and scattering. Through the above modeling process, the originally heterogeneous environmental perception data is uniformly transformed into scalar environmental attenuation features that can be directly used in the scoring model. This achieves a quantitative mapping of environmental state to the impact on link quality, which is beneficial for proactively avoiding degraded optical channels in areas with severe fog or heavy rainfall when making handover decisions.

[0112] Regarding the implementation details of generating duty cycle matching features, in some examples of embodiments of this application, the downlink slot duration in the current TDD frame structure is monitored. With uplink time slot duration Calculate the current duty cycle :

[0113] Equation (11)

[0114] The expected duty cycle related to the current traffic is obtained based on the traffic load. and with the current duty cycle Compared with expected duty cycle Based on the deviation between them, the normalized duty cycle matching amount of the candidate optical channel is determined. :

[0115] Equation (12)

[0116] In the formula, This is a reference value for duty cycle normalization, used to limit... The scale makes The larger the value, the better the TDD frame structure matches the service requirements.

[0117] In TDD (Time Diversion) mode, the allocation of downlink and uplink time slot durations directly determines the available time-frequency resources for services in different directions. This embodiment detects the downlink time slot duration in the current TDD frame structure. With uplink time slot duration The current duty cycle is calculated according to equation (11) and is used to characterize the proportion of resources allocated to the downlink direction within a frame. On the other hand, the expected duty cycle related to the current service traffic status can be obtained based on the service statistics of the access layer or core network. For example, improving performance in scenarios with high downlink traffic load. Reduced in scenarios where upstream business is dominant .

[0118] In equation (12), the absolute deviation between the current duty cycle and the desired duty cycle is used. Based on this, and combined with the duty cycle normalization reference value To constrain the deviation by scale, a normalized duty cycle matching quantity is constructed. , making The closer to the expected duty cycle , The closer the value is to 1, the higher the degree of matching between the TDD frame structure and service requirements; as the difference between the two increases, Gradually decrease the duty cycle setting to penalize situations where the duty cycle setting does not match the business direction.

[0119] By introducing duty cycle matching features, not only is the physical quality of the optical channel itself considered, but the adaptability of the TDD frame structure to the uplink and downlink service carrying capacity is also included in the comprehensive score. In scenarios where different candidate optical channels correspond to different TDD configurations or service binding relationships, optical channels with good channel quality and resource allocation that better meet the current service requirements can be selected first, thereby balancing link performance and system capacity utilization.

[0120] In some examples of embodiments of this application, the channel quality sensitivity coefficient Duty cycle matching sensitivity coefficient Environmental degradation sensitivity coefficient and switching cost sensitivity coefficient It is designed to dynamically adjust over time to adapt to different business loads and environmental conditions.

[0121] More specifically, based on the time of each candidate optical channel Normalized channel quality evaluation metric Calculate the optimal channel quality value and the average channel quality value, and adaptively update the channel quality sensitivity coefficient. :

[0122] Equation (13)

[0123] Equation (14)

[0124] Equation (15)

[0125] In the formula, This represents the optimal value for channel quality. This represents the average channel quality. Indicates the total number of channels; To update the quality sensitivity step size, the channel quality sensitivity coefficient is increased when the channel with the best quality is significantly better than the average level, so as to strengthen the weight of channel quality factors in the overall evaluation score.

[0126] On the one hand, the optimal quality value at the current moment is calculated using equation (13). This is used to reflect the channel with the best quality among the currently available channels; on the other hand, the average quality is calculated using equation (14). This is used to characterize the overall channel quality level. Then, using equation (15) according to... and The difference between them affects the channel quality sensitivity coefficient. Perform incremental updates: when Significantly higher than hour, If the value is positive and relatively large, then... This will affect the subsequent comprehensive evaluation score. In the calculation, the weight of the channel quality factor is increased; conversely, when all channel qualities are similar and the overall quality is poor, the difference tends to zero or even becomes negative, making... The value will not be increased further and may even be moderately decreased. Through an adaptive adjustment mechanism based on the difference between the optimal and average values, the preference for channel quality can be strengthened when there are clearly superior channels, avoiding the weakening of the superior channel score advantage due to fixed weights.

[0127] Then, based on the deviation between the current duty cycle and the expected duty cycle, the duty cycle matching sensitivity coefficient is adaptively updated:

[0128] Equation (16)

[0129] In the formula, To update the step size for duty cycle sensitivity, As a reference value for duty cycle deviation, the more obvious the imbalance between upstream and downstream business, the stronger the influence of duty cycle matching factor on the overall evaluation score.

[0130] In (16), Duty cycle deviation reference value The comparison is made when the deviation between the current duty cycle and the expected duty cycle exceeds [a certain threshold]. When the term inside the parentheses is positive, then... This amplifies the duty cycle matching feature in the overall evaluation score. The impact; when the deviation does not exceed At that time, the update increment approaches zero or even becomes negative, making Keep it unchanged or reduce it moderately.

[0131] By using an adaptive adjustment method triggered by "duty cycle deviation exceeding the threshold", the weight of the duty cycle matching factor can be automatically increased when the uplink and downlink services are extremely unbalanced and a TDD frame structure with a more matching duty cycle needs to be selected first. In scenarios where the services are relatively balanced or the duty cycle is not sensitive, this factor is prevented from overly dominating the comprehensive evaluation result, thereby achieving reasonable resource adaptation capability between different service load modes.

[0132] The average environmental attenuation is calculated based on the normalized environmental attenuation of each candidate optical channel, and the environmental attenuation sensitivity coefficient is adaptively updated.

[0133] Equation (16)

[0134] Equation (17)

[0135] In the formula, Update the step size for environmental sensitivity. This serves as a reference level for environmental degradation, ensuring that the more severe the overall environment, the stronger the inhibitory effect on environmental degradation factors.

[0136] Environmental attenuation sensitivity coefficient Regarding adaptive updates, at each decision time, the normalized environmental attenuation of each candidate optical channel is considered. The average level of current environmental degradation can be calculated using equation (16). Compare it with the preset environmental attenuation reference level. Compare and apply according to equation (17). Perform incremental updates. When Higher than This indicates that the overall network environment (including the combined effects of smog, rainfall, etc.) is relatively more severe. In the comprehensive evaluation score, The suppression effect is enhanced, further penalizing channels with significant environmental attenuation; when Below At that time, the overall environmental conditions were relatively good. The update increment can be zero or negative, thus reducing the constraint of environmental factors on the overall score. This allows the system to dynamically adjust its sensitivity to environmental degradation based on the overall environmental conditions, prioritizing candidate optical channels with lower environmental degradation and more reliable link quality under adverse weather conditions, while avoiding over-reliance on environmental factors and narrowing the selection space when the environment is favorable.

[0137] Based on the number of channel switching observed within a preset time window Update switching cost sensitivity coefficient:

[0138] Equation (18)

[0139] In the formula, To switch to cost-sensitive update step size, This serves as a reference value for the desired number of handovers, allowing for a higher weighting of handover cost when the number of handovers is excessive.

[0140] Switching cost sensitivity coefficient Regarding adaptive updates, the actual number of channel switching events occurring at the multi-channel optical receiver is counted within a preset time window. and compared with the expected number of switching reference values. Compare according to equation (18) Make dynamic adjustments. When Greater than This indicates that the switching behavior is relatively frequent within a certain period of time, posing a risk of ping-pong switching. In the comprehensive evaluation score China's switching cost indicators The penalty weight is increased, thereby raising the margin required to trigger a switch and suppressing unnecessary frequent switches in the future; when Below This indicates that the system has been staying on the same channel for an extended period or has had infrequent switching, which is permissible. The size should be reduced appropriately so that handover can be triggered more aggressively when a significantly better candidate channel appears.

[0141] In some implementations, to avoid frequent handovers or prolonged lingering on degraded channels caused by using only a fixed handover threshold, a dynamic threshold update strategy based on stability penalty suppression is adopted for the handover decision threshold.

[0142] Specifically, it records the stable duration for which the multi-channel optical receiver remains in the current receiving optical channel since the last optical channel switch. And calculate the stability penalty factor based on the stable duration:

[0143] Equation (19)

[0144] In the formula, This is a stability penalty coefficient. The larger the value, the greater the stability penalty factor. The rate at which the value approaches 1 increases with increasing stability duration; when the stability duration is short... A value close to 0 is used to suppress the threshold from decreasing too quickly in scenarios with frequent switching.

[0145] along with The increase, A value monotonically approaching 1 indicates that the current channel has been operating stably for a relatively long time; when When smaller, It is close to 0, thus suppressing a large drop in the subsequent threshold during frequent switching phases.

[0146] Based on time Comprehensive evaluation score of each candidate optical channel The comprehensive evaluation score of the optimal candidate optical channel is obtained as follows:

[0147] Equation (20)

[0148] The switching decision threshold function is updated according to the following formula:

[0149] Equation (21)

[0150] In the formula, For a moment The switching decision threshold, For the current received optical channel at time The overall evaluation score The threshold update step size is positive. When the optimal candidate optical channel is significantly better than the current received optical channel and the stable duration exceeds the preset stable duration threshold, the step size is reduced. Lowering the switching threshold encourages switching; when the stable duration does not exceed the stable duration threshold, a stability penalty factor is applied. Approaching 0, making and The threshold variation between them is reduced, thereby limiting the handover decision threshold from falling too quickly to suppress ping-pong handover.

[0151] Specifically, when Significantly greater than ,and When the preset stable duration threshold is exceeded, Approaching 1, making Significantly smaller than This is equivalent to lowering the advantage threshold required to trigger a handover, thereby enabling a proactive handover decision on a significantly better candidate optical channel after the current channel has been operating stably for a period of time; while... If the threshold is not reached, Approaching 0, making and The difference between them is compressed, and the handover decision threshold will not drop rapidly in a short period of time, thereby suppressing ping-pong handover between several close channels by multi-channel optical receivers and improving link stability and service transmission continuity.

[0152] Figure 3 A schematic diagram illustrating the operational mechanism of an example of a TDD state-aware multichannel optical receiver switching method according to an embodiment of this application is shown.

[0153] like Figure 3As shown, the overall mechanism of the TDD state-aware multi-channel optical receiver handover method includes three levels: channel state awareness, scoring calculation, and resource scheduling. The TDD state detection module and the optical channel sensor output TDD frame structure information and physical layer measurement results such as the signal-to-noise ratio of each candidate optical channel, respectively, which are input to the upper-layer scoring calculation module to jointly weight and evaluate the SNR and TDD duty cycle. The environmental sensor collects external environmental data such as haze and rainfall, which are dynamically weighted and sent to the lower-layer scoring calculation module. In this module, the SNR and trigger threshold are combined for scoring, and frequent handover is suppressed through a hysteresis mechanism. The scoring calculation results of the upper and lower levels are aligned on the time axis and then uniformly sent to the decision logic unit on the multi-channel optical receiver side. The decision logic unit determines the target receiving optical channel under the dynamic weighting rules and hands over the handover decision to the scheduler for execution. The scheduler then combines the dynamic alignment information to drive the dynamic resource scheduling module to coordinate the receiving resources and TDD time slots of the multi-channel optical receiver.

[0154] To verify the effectiveness of the proposed TDD state-aware multi-channel optical receiver handover method, an offline simulation platform was constructed to compare the performance differences between the proposed algorithm and traditional hard handover schemes in typical scenarios. The simulation platform uniformly models factors such as TDD frame structure, optical link attenuation, random weather evolution, and receiver hardware handover delay, and generates multiple sets of test trajectories under the same random seed to ensure the repeatability of the comparison results.

[0155] Regarding the channel model, it is assumed that the system has Four candidate optical channels, each with a fixed center wavelength, differ only in attenuation and noise levels. The average received signal-to-noise ratios (SNRs) of the four channels under no-attenuation conditions are set to 10 dB, 8 dB, 6 dB, and 5 dB, respectively, and are superimposed with Rayleigh small-scale fading and slowly varying shadow fading. A random weather generator, based on the characteristics of the optical link being affected by haze, smoke, and turbulence, generates time-evolving haze concentration and rainfall intensity processes, and calculates the additional atmospheric attenuation coefficient accordingly. This coefficient is then input into the environmental attenuation feature extraction module of this paper as environmental perception data.

[0156] In the TDD frame structure settings, the frame length is fixed at 1 ms, and the uplink and downlink time slots are dynamically adjusted according to the system service load. The initial downlink duty cycle is set to... TDD transmit / receive handover is completed at frame boundaries, with a 50 µs guard interval reserved for hardware handover and locking time of the multi-channel optical receiver. The service generation process employs a Poisson arrival and random packet length model, constructing various load scenarios by adjusting uplink and downlink service arrival rates to match the characteristics. It exhibits obvious dynamic changes during the simulation process.

[0157] The algorithms compared in the experiment included two categories:

[0158] The baseline algorithm is a traditional SNR threshold-driven hard handover strategy: when the instantaneous SNR measured by the current received optical channel in the downlink time slot is lower than a fixed threshold for several consecutive frames, it immediately switches to a pre-set alternative optical channel. Throughout the process, TDD uplink and downlink status, environmental attenuation information, and hysteresis or stability constraints are not considered.

[0159] The algorithm in this paper adopts the TDD state-aware comprehensive evaluation model proposed above: at each downlink time slot boundary, based on the smoothed and predicted signal-to-noise ratio... Environmental degradation data obtained from smog and rainfall data Matching quantity obtained from the deviation between the actual duty cycle and the expected duty cycle And the switching cost derived from wavelength difference and beam direction difference. Calculate the overall evaluation score Then, combining the stability penalty factor and the dynamic threshold update strategy, it is determined whether to trigger channel switching. The sensitivity coefficient is initially set to... , , , The adaptive update formula is adjusted over time to reflect the relative importance of channel quality, duty cycle matching, environmental attenuation, and handover overhead in different operational phases.

[0160] Figure 4 This diagram illustrates a comparison of throughput over time using different methods.

[0161] like Figure 4 As shown, under the same channel attenuation and service load conditions, the hard handover scheme immediately triggers channel handover when channel quality fluctuates or suddenly deteriorates, causing the system to frequently travel between different optical channels, resulting in a significant "ping-pong handover" phenomenon. This leads to large fluctuations in the throughput curve and a low minimum value. In contrast, the proposed method determines whether to handover based on a comprehensive evaluation score at each downlink time slot boundary, and adds a handover cost and stability penalty mechanism. Handover is only triggered when the candidate channel is significantly better than the current channel and meets stability constraints. Therefore, the overall number of handovers is reduced, the link maintains a stable transmission range for a longer period, the throughput curve is smoother, and it remains at a high level for most of the time. Statistical results show that, under this experimental configuration, the average throughput of the TDD state-aware method is about 20% higher than that of the hard handover scheme, verifying the effectiveness of the proposed method in ensuring transmission stability and improving effective throughput.

[0162] Figure 5A two-dimensional heatmap showing the overall evaluation score as a function of TDD duty cycle and optical channel SNR is presented. The horizontal axis represents the downlink duty cycle, and the vertical axis represents the optical SNR (dB). The color bars on the right represent the magnitude of the overall evaluation score, with the colors from blue to red indicating scores from low to high. The superimposed black contour lines in the figure represent contour lines of different evaluation scores.

[0163] like Figure 5 As shown, when the optical SNR is high and the TDD duty cycle is close to the desired duty cycle (approximately 0.5), the evaluation score region exhibits a distinct peak shape, indicating that the algorithm tends to prioritize the corresponding channel within this region. In regions with high SNR but a duty cycle deviating from the desired value, the contour lines shift downwards to both sides, suggesting that a decrease in duty cycle matching characteristics will gradually reduce the overall evaluation score. Under a fixed duty cycle, as the SNR decreases, the color gradually changes from red to blue, and the evaluation score decreases approximately monotonically. When the score falls below a preset threshold, the corresponding channel will not be used as a handover target. Furthermore, in low SNR regions, even if the duty cycle is highly matched with service requirements, the heatmap still shows a low score band due to the suppressive effect of the environmental attenuation factor on the evaluation function. This demonstrates that the proposed method can avoid misselecting poor-quality channels based solely on duty cycle factors in adverse environmental scenarios such as fog and haze, and more comprehensively balances the combined impact of channel quality and TDD frame structure matching degree on handover decisions.

[0164] Figure 6 This diagram illustrates an example of the relationship between a handover decision and the SNR difference between a candidate channel and the current received channel, according to an embodiment of this application. The horizontal axis represents the SNR difference between the candidate optical channel and the current received optical channel (in dB, with the candidate channel having a higher SNR to the right), and the vertical axis represents the decision event index numbered chronologically. The scatter plot colors are indicated by the color scale on the right, where red scatter plots with a value of 1 indicate that a channel handover decision was made in the corresponding decision event, and blue scatter plots with a value of 0 indicate that the current channel was kept unchanged. The vertical dashed line corresponds to the boundary where the SNR difference is 0.

[0165] like Figure 6 As shown, when the candidate channel's SNR has a significant advantage over the current channel (e.g., an SNR difference greater than approximately 1 dB, located in the segment to the right of the dashed line), the scatter points are mainly red, indicating a significant improvement in the overall evaluation score and a tendency for the algorithm to perform a handover. Conversely, in areas where the SNR difference is close to 0 or the candidate channel's SNR is not advantageous, the scatter points are mainly blue, indicating that the algorithm maintains the current channel when there are small fluctuations or when the candidate channel's quality is insufficient to bring significant benefits. Therefore, this application effectively suppresses unnecessary handovers caused by small SNR fluctuations through lag mechanisms such as the overall evaluation function and stability penalty, triggering handover only when the channel quality improvement reaches the expected threshold, thereby reducing the handover frequency and mitigating the ping-pong effect.

[0166] Experimental results demonstrate that this method has significant advantages in multi-channel optical communication scenarios. Firstly, by utilizing TDD state awareness, handover decisions are made only at downlink time slot boundaries. This avoids potential self-interference during uplink and allows for hardware reconfiguration of local oscillator wavelength and beam direction during the uplink / downlink handover interval, thus reducing the impact on service data interruption. Secondly, the constructed comprehensive evaluation function, based on channel quality, incorporates multiple dimensions such as duty cycle matching, environmental attenuation, handover cost, and historical stability. A dynamic weight update mechanism adaptively adjusts the influence weights of each factor according to changes in service load and environment. This ensures that handover decisions prioritize high-quality channels while suppressing frequent handovers under small fluctuations, effectively reducing performance loss caused by the ping-pong effect.

[0167] In summary, this application, based on an analysis of the shortcomings of existing dynamic handover schemes for multi-channel optical receivers, proposes a TDD-based state-aware multi-channel optical receiver handover method. Addressing issues such as the ping-pong effect inherent in traditional hard handover, the complexity of soft handover implementation, the lack of system-level scheduling in tunable receivers, and the lack of consideration for TDD frame structure in multi-beam receivers, this application constructs an integrated technical framework from state awareness to decision control. This method collects TDD state information, channel quality indicators, and environmental awareness data. It uses Kalman filtering to predict the channel quality of future downlink time slots. A comprehensive evaluation function is designed with channel quality, duty cycle matching, environmental attenuation, handover cost, and stability penalty as core elements. Combined with dynamic weight updates and a threshold adaptive mechanism based on stability penalty, it achieves refined handover decisions and rapid reconfiguration at TDD frame boundaries. Simulation results show that compared with traditional hard handover schemes, this method improves the average throughput by approximately 20% under typical operating conditions while significantly suppressing the ping-pong handover phenomenon, verifying the effectiveness and engineering application value of the proposed method in improving the stability and effective throughput of multi-channel optical communication systems.

[0168] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of combined actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Secondly, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application. In the above embodiments, the descriptions of each embodiment have their own emphasis; for parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0169] Figure 7A structural block diagram of an example of a TDD state-aware multichannel optical receiver switching system according to an embodiment of this application is shown, the system being deployed at a remote wireless node.

[0170] like Figure 7 As shown, the TDD state-aware multi-channel optical receiver switching system 700 includes a multi-source monitoring data acquisition unit 710, a state-aware preprocessing unit 720, a candidate channel feature scoring unit 730, a switching condition decision unit 740, and a channel switching control unit 750.

[0171] The multi-source monitoring data acquisition unit 710 is used to acquire multi-source monitoring data for each candidate optical channel. The multi-source monitoring data includes environmental perception data, channel quality indicators used to characterize the reception quality of the candidate optical channel, and TDD status information used to characterize the operating mode of the optical communication system. The TDD status information includes the current time slot type identifier and the corresponding time slot duty cycle parameter.

[0172] The state-aware preprocessing unit 720 is used to perform state-aware preprocessing on the channel quality indicators based on the TDD state information. During the uplink time slot, the update of the channel quality indicator samples of each candidate optical channel is frozen, so that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot. The channel quality indicator samples during the downlink time slot are used as valid samples, and the valid samples are subjected to time smoothing and normalization processing to obtain the preprocessed channel quality features for each candidate optical channel.

[0173] The candidate channel feature scoring unit 730 is used to generate environmental attenuation features to characterize the degree of influence of the environment on optical link attenuation based on the environmental perception data; based on the slot type identifier and slot duty cycle parameter in the TDD state information, combined with the expected duty cycle of the current service for uplink and downlink resource allocation, it generates duty cycle matching features to characterize the degree of matching between the TDD frame structure and service requirements; and calculates a comprehensive evaluation score for each candidate optical channel based on the preprocessed channel quality features, the environmental attenuation features, and the duty cycle matching features.

[0174] The handover condition decision unit 740 is used to obtain the comprehensive evaluation score of the current received optical channel at a predetermined decision time in each TDD frame period during continuous operation, compare the comprehensive evaluation score of each candidate optical channel with the comprehensive evaluation score of the current received optical channel and a preset handover decision threshold, and when it is detected that the comprehensive evaluation score of a candidate optical channel exceeds the handover decision threshold relative to the comprehensive evaluation score of the current received optical channel, determine the candidate optical channel as the target received optical channel.

[0175] The channel switching control unit 750 is used to control the multi-channel optical receiver to switch from the current receiving optical channel to the target receiving optical channel within the time slot boundary adjacent to the predetermined decision time.

[0176] In some embodiments, this application provides a non-volatile computer-readable storage medium storing one or more programs including execution instructions. The execution instructions can be read and executed by an electronic device (including but not limited to a computer, server, or network device) to perform the steps of any of the TDD state-aware multichannel optical receiver switching methods described above.

[0177] In some embodiments, this application also provides a computer program product, the computer program product including a computer program stored on a non-volatile computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the steps of any of the above-described TDD state-aware multichannel optical receiver switching methods.

[0178] In some embodiments, this application also provides an electronic device, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform steps of a TDD state-aware multichannel optical receiver switching method.

[0179] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0180] The electronic devices in this application can exist in various forms, including but not limited to: mobile communication devices, ultra-mobile personal computer devices, portable entertainment devices, or other airborne electronic devices with data interaction functions.

[0181] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0182] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0183] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A multi-channel optical receiver switching method based on TDD state awareness, characterized in that, The method includes: Acquire multi-source monitoring data for each candidate optical channel. The multi-source monitoring data includes environmental perception data, channel quality indicators used to characterize the reception quality of the candidate optical channel, and TDD status information used to characterize the operating mode of the optical communication system. The TDD status information includes the current time slot type identifier and the corresponding time slot duty cycle parameter. Based on the TDD state information, state-aware preprocessing is performed on the channel quality index. During the uplink time slot, the update of the channel quality index samples of each candidate optical channel is frozen, so that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot. The channel quality index samples during the downlink time slot are used as valid samples, and the valid samples are subjected to time smoothing and normalization to obtain the preprocessed channel quality features for each candidate optical channel. An environmental attenuation feature is generated based on the environmental perception data to characterize the degree of environmental impact on optical link attenuation; based on the slot type identifier and slot duty cycle parameter in the TDD state information, and combined with the expected duty cycle of the current service for uplink and downlink resource allocation, a duty cycle matching feature is generated to characterize the degree of matching between the TDD frame structure and service requirements; based on the preprocessed channel quality feature, the environmental attenuation feature, and the duty cycle matching feature, a comprehensive evaluation score is calculated for each candidate optical channel. In each continuously running TDD frame cycle, at a predetermined decision time in each TDD frame cycle, the comprehensive evaluation score of the current received optical channel is obtained. The comprehensive evaluation scores of each candidate optical channel are compared with the comprehensive evaluation score of the current received optical channel and a preset handover decision threshold. When it is detected that the comprehensive evaluation score of a candidate optical channel exceeds the handover decision threshold relative to the comprehensive evaluation score of the current received optical channel, the candidate optical channel is determined as the target received optical channel. The predetermined decision time is set as the boundary time between the downlink time slot and the uplink time slot in the TDD frame structure and / or the boundary time between the downlink time slot and the reserved gap, so that the determination of the target received optical channel is completed at the predetermined decision time, and the handover decision is aligned with the downlink received time slot. Within the time slot boundary adjacent to the predetermined decision time, controlling the multi-channel optical receiver to switch from the current receiving optical channel to the target receiving optical channel specifically includes: The handover control command for controlling the multi-channel optical receiver to perform hardware reconfiguration is scheduled to be issued and executed in the uplink time slot and / or the reserved gap time immediately following the downlink time slot, so that the actual handover process of the multi-channel optical receiver is completed in the uplink time slot and / or the reserved gap time, thereby avoiding interruption of service data reception in the downlink time slot.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the wavelength parameters and beam direction angle parameters corresponding to the current received optical channel and each candidate optical channel; Based on the obtained wavelength parameters and beam direction angle parameters, the switching cost index of each candidate optical channel is calculated; the switching cost index is used to characterize the hardware reconfiguration overhead required by the multi-channel optical receiver when switching from the current receiving optical channel to each candidate optical channel. The step of calculating a comprehensive evaluation score for each candidate optical channel based on the preprocessed channel quality characteristics, the environmental attenuation characteristics, and the duty cycle matching characteristics includes: Based on the preprocessed channel quality characteristics, the environmental attenuation characteristics, the duty cycle matching characteristics, and the switching cost index, a comprehensive evaluation score is calculated for each candidate optical channel.

3. The method according to claim 2, characterized in that, The calculation of the switching cost index for each candidate optical channel based on the acquired wavelength parameters and beam direction angle parameters includes: Calculate the normalized wavelength difference and normalized beam direction difference of each candidate optical channel relative to the current received optical channel, and obtain the corresponding handover cost index through weighted fusion: ， ， ， In the formula, and They represent the first The candidate optical channels at time... Compared to the normalized wavelength difference and normalized beam direction difference of the current receiving optical channel, It is a time variable; Indicates the first The candidate optical channels at time... Switching cost metrics Indicates the current received optical channel at time [time]. wavelength parameters, Indicates the first The candidate optical channels at time... wavelength parameters, Indicates the current received optical channel at time [time]. The beam direction angle parameters, Indicates the first The candidate optical channels at time... The beam direction angle parameters, As a wavelength normalization reference, This serves as a reference value for the normalized orientation angle. and This is the switching cost weighting coefficient, used to adjust the weighting of the impact of wavelength switching and beam direction switching on the switching cost index. The step of calculating a comprehensive evaluation score for each candidate optical channel based on the preprocessed channel quality characteristics, the environmental attenuation characteristics, the duty cycle matching characteristics, and the handover cost index includes: The preprocessed channel quality characteristics, environmental attenuation characteristics, and duty cycle matching characteristics of each candidate optical channel are normalized to obtain normalized channel quality evaluation values, normalized environmental attenuation values, and normalized duty cycle matching values, thereby determining the intermediate quality utility values ​​of each candidate optical channel. ， In the formula, , and They represent the first The candidate optical channels at time... The normalized channel quality evaluation quantity, the normalized environmental attenuation quantity, and the normalized duty cycle matching quantity; For the first The candidate optical channels at time... The intermediate quality utility value, , and These represent the channel quality sensitivity coefficient, duty cycle matching sensitivity coefficient, and environmental attenuation sensitivity coefficient, respectively. Based on the intermediate quality utility value and the switching cost index, determine the first... The overall evaluation score of each candidate optical channel: ， In the formula, For the first The candidate optical channels at time... The overall evaluation score This is the switching cost sensitivity coefficient.

4. The method according to claim 3, characterized in that, The process involves performing state-aware preprocessing on the channel quality indicators based on the TDD state information. During uplink time slots, the updates of channel quality indicator samples for each candidate optical channel are frozen, ensuring that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot. Channel quality indicator samples during downlink time slots are used as valid samples, and these valid samples undergo time smoothing and normalization to obtain preprocessed channel quality features for each candidate optical channel. This includes: For each candidate optical channel The raw signal-to-noise ratio measurement value is obtained at the moment when the TDD state is the downlink time slot. The smoothed signal-to-noise ratio estimate is updated based on an exponential smoothing strategy. It satisfies: ， In the formula, As a smoothing factor, This is the smoothed signal-to-noise ratio estimate from the previous sampling time. At the moment when the TDD state is the uplink time slot, the smoothed signal-to-noise ratio estimate remains unchanged, satisfying the following conditions: This freezes the channel quality index sample update for each candidate optical channel during the uplink time slot. Based on the smoothed signal-to-noise ratio estimates of each candidate optical channel at each time step A first-order state-space model is established, using the smoothed signal-to-noise ratio estimate as an observation, to model the true channel gain state, thus making the true channel gain state... The observed output satisfies: ， In the formula, These are the state transition coefficients. and These are process noise and measurement noise, respectively. Using a state-space model, the smoothed signal-to-noise ratio estimate at each time step is obtained. As input observations, the true channel gain state By performing recursive estimation, the downlink time slot time in the next frame can be obtained. Predicted state The predicted state is used as the predicted signal-to-noise ratio for the next downlink time slot, satisfying: ， In the formula, This represents the time interval from the current moment to the next downlink time slot; Predict signal-to-noise ratio Perform a normalization mapping to obtain the representation of the first... The candidate optical channels at time... Normalized channel quality evaluation metric .

5. The method according to claim 3, characterized in that, The step of generating environmental attenuation features based on the environmental perception data to characterize the degree of environmental impact on optical link attenuation includes: Analyzing the haze concentration index corresponding to environmental perception data and rainfall intensity The normalized haze concentration index was obtained after normalization. and normalized rainfall intensity And construct an environmental perception data function through weighted fusion. : ， In the formula, ,and , used to characterize the relative weights of the effects of haze and rainfall on optical link attenuation; Based on the environmental perception data function An exponential decay model was constructed to obtain the environmental decay factor. It satisfies: ， In the formula, The environmental sensitivity coefficient; As each candidate optical channel at time Normalized environmental degradation To characterize at time The more severe the environmental degradation, the more The larger the characteristic; The step of generating a duty cycle matching feature based on the slot type identifier and slot duty cycle parameter in the TDD state information, combined with the expected duty cycle of the current service's allocation of uplink and downlink resources, to characterize the degree of matching between the TDD frame structure and service requirements includes: Monitor downlink slot duration in the current TDD frame structure With uplink time slot duration Calculate the current duty cycle : ， The expected duty cycle related to the current traffic is obtained based on the traffic load. and with the current duty cycle Compared with expected duty cycle Based on the deviation between them, the normalized duty cycle matching amount of the candidate optical channel is determined. : ， In the formula, This is a reference value for duty cycle normalization, used to limit... The scale makes The larger the value, the better the TDD frame structure matches the service requirements.

6. The method according to claim 5, characterized in that, The channel quality sensitivity coefficient Duty cycle matching sensitivity coefficient Environmental degradation sensitivity coefficient and switching cost sensitivity coefficient Designed to dynamically adjust over time to adapt to different business loads and environmental conditions: Based on the time of each candidate optical channel Normalized channel quality evaluation metric Calculate the optimal channel quality value and the average channel quality value, and adaptively update the channel quality sensitivity coefficient. : ， ， ， In the formula, This represents the optimal value for channel quality. This represents the average channel quality. Indicates the total number of channels; To update the quality sensitivity step size, the channel quality sensitivity coefficient is increased when the channel with the best quality is significantly better than the average level, so as to strengthen the weight of channel quality factors in the overall evaluation score. Based on the deviation between the current duty cycle and the expected duty cycle, the duty cycle matching sensitivity coefficient is adaptively updated: ， In the formula, To update the step size for duty cycle sensitivity, As a reference value for duty cycle deviation, the more obvious the imbalance between upstream and downstream business, the stronger the influence of duty cycle matching factor on the overall evaluation score. The average environmental attenuation is calculated based on the normalized environmental attenuation of each candidate optical channel, and the environmental attenuation sensitivity coefficient is adaptively updated. ， ， In the formula, Update the step size for environmental sensitivity. As a reference level for environmental degradation, the more severe the overall environment, the stronger the inhibitory effect on environmental degradation factors; Based on the number of channel switching observed within a preset time window Update switching cost sensitivity coefficient: ， In the formula, To switch to cost-sensitive update step size, This serves as a reference value for the desired number of handovers, allowing for a higher weighting of handover cost when the number of handovers is excessive.

7. The method according to claim 3, characterized in that, The switching decision threshold adopts a dynamic threshold update strategy based on stability penalty suppression, specifically including: Record the stable duration for which the multi-channel optical receiver remains in the current receiving optical channel since the last optical channel switch. And calculate the stability penalty factor based on the stability duration: ， In the formula, This is a stability penalty coefficient. The larger the value, the greater the stability penalty factor. The rate at which the value approaches 1 increases with increasing stability duration; when the stability duration is short... A value close to 0 is used to suppress the threshold from decreasing too quickly in scenarios with frequent switching. Based on time Comprehensive evaluation score of each candidate optical channel The comprehensive evaluation score of the optimal candidate optical channel is obtained as follows: ， The switching decision threshold function is updated according to the following formula: ， In the formula, For a moment The switching decision threshold, For the current received optical channel at time The overall evaluation score The threshold update step size is positive. When the optimal candidate optical channel is significantly better than the current received optical channel and the stable duration exceeds the preset stable duration threshold, the step size is reduced. Lowering the switching threshold encourages switching; when the stable duration does not exceed the stable duration threshold, a stability penalty factor is applied. Approaching 0, making and The threshold variation between them is reduced, thereby limiting the handover decision threshold from falling too quickly to suppress ping-pong handover.

8. A multi-channel optical receiver switching system based on TDD state awareness, characterized in that, The system is used to implement the method as described in any one of claims 1-7; the system comprises: The multi-source monitoring data acquisition unit is used to acquire multi-source monitoring data for each candidate optical channel. The multi-source monitoring data includes environmental perception data, channel quality indicators used to characterize the reception quality of the candidate optical channel, and TDD status information used to characterize the operating mode of the optical communication system. The TDD status information includes the current time slot type identifier and the corresponding time slot duty cycle parameter. A state-aware preprocessing unit is used to perform state-aware preprocessing on the channel quality indicators based on the TDD state information. During the uplink time slot, the update of the channel quality indicator samples of each candidate optical channel is frozen, so that the preprocessed channel quality features maintain the channel quality estimate corresponding to the most recent downlink time slot during the uplink time slot. The channel quality indicator samples during the downlink time slot are used as valid samples, and the valid samples are subjected to time smoothing and normalization processing to obtain the preprocessed channel quality features for each candidate optical channel. The candidate channel feature scoring unit is used to generate environmental attenuation features to characterize the degree of influence of the environment on optical link attenuation based on the environmental perception data; to generate duty cycle matching features to characterize the degree of matching between TDD frame structure and service requirements based on the slot type identifier and slot duty cycle parameter in the TDD state information, combined with the expected duty cycle of the current service for uplink and downlink resource allocation; and to calculate a comprehensive evaluation score for each candidate optical channel based on the preprocessed channel quality features, the environmental attenuation features, and the duty cycle matching features. The handover condition decision unit is used to obtain the comprehensive evaluation score of the current received optical channel at a predetermined decision time in each TDD frame period during continuous operation, compare the comprehensive evaluation score of each candidate optical channel with the comprehensive evaluation score of the current received optical channel and a preset handover decision threshold, and when it is detected that the comprehensive evaluation score of a candidate optical channel exceeds the handover decision threshold relative to the comprehensive evaluation score of the current received optical channel, determine the candidate optical channel as the target received optical channel. The channel switching control unit is used to control the multi-channel optical receiver to switch from the current receiving optical channel to the target receiving optical channel within the time slot boundary adjacent to the predetermined decision time.

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