Multi-band adaptive signal processing method and system, medium and program product

Abstract

The invention relates to the technical field of wireless communication, in particular to a multi-band adaptive signal processing method and system, a medium and a program product, and the method comprises the steps: obtaining signal transmission record data of each channel in a current band in a first preset time period, identifying a transmission service type proportion, a historical bit error rate and a channel expansion value contained in each signal transmission record data, and then determining a switching priority level of each channel; when it is detected that the frequency band load pressure value of the current frequency band is larger than a preset pressure threshold value, acquiring to-be-migrated transmission task data corresponding to the current frequency band in a second preset time period, and identifying to-be-migrated demand feature parameters; determining a target switching frequency band based on the to-be-migrated demand features; and formulating a signal transmission switching sequence based on the switching priority of each channel in the current frequency band, and carrying out adaptive migration switching on the to-be-migrated transmission task data to the target switching frequency band based on the signal transmission switching sequence. According to the invention, the signal processing efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a multi-band adaptive signal processing method, system, medium, and program product. Background Technology

[0002] With the large-scale commercialization of 5G communication technology and the forward-looking research and development of 6G communication technology, global communication networks are continuously evolving towards ultra-high speed, ultra-low latency, massive connectivity, and wide-area coverage. Cross-scenario and high-dimensional communication needs have become the core demands of the next generation of communication technologies. Against this backdrop, signal processing, as the central core of the communication process, directly determines the depth of spectrum resource utilization, the fidelity of signal transmission, and the overall operational efficiency of the network. It is also a key pillar supporting the implementation and empowerment of the next generation of communication technologies and meeting the diverse and high demands of multiple scenarios.

[0003] However, existing signal processing methods are mostly designed to adapt to narrow bandwidth and low concurrency scenarios. By adopting a serial processing architecture, they may be unable to cope with the exponentially increasing data volume, resulting in increased processing latency. In some cases, signal accuracy may have to be sacrificed for processing speed. In addition, the parameter configuration of existing signal processing methods is relatively fixed, which may not be able to dynamically adapt to multi-band switching. This may result in low efficiency of communication resource allocation, which may affect signal processing efficiency. Summary of the Invention

[0004] To improve signal processing efficiency, this application provides a multi-band adaptive signal processing method, system, medium, and program product.

[0005] Firstly, this application provides a multi-band adaptive signal processing method, which adopts the following technical solution: A multi-band adaptive signal processing method, comprising: Acquire signal transmission record data of each channel in the current frequency band within a first preset time period, and identify the proportion of transmission service types, historical bit error rate, and channel expansion value contained in each signal transmission record data; The handover priority level of each channel is determined by multi-dimensional weighting of the proportion of transmission service types, historical bit error rate, and channel expansion value. When the frequency band load pressure value of the current frequency band is detected to be greater than the preset pressure threshold, the data of the transmission task to be migrated corresponding to the current frequency band in the second preset time period is obtained, and the characteristics of the migration requirement are identified based on the data of the transmission task to be migrated. The target switching frequency band is determined from the candidate frequency bands based on the characteristics of the migration requirements. Based on the switching priority level of each channel in the current frequency band, a signal transmission switching sequence is formulated, and based on the signal transmission switching sequence, the signal transmission task to be migrated corresponding to the current frequency band is adaptively migrated and switched to the target switching frequency band.

[0006] By adopting the above technical solution, the transmission status of each signal in the current frequency band can be analyzed from multiple dimensions, and the switching priority of each channel can be intuitively evaluated after weighted calculation. In addition, by analyzing the characteristics of the data to be migrated, the target switching frequency band is selected from multiple candidate frequency bands, which facilitates the improvement of the compatibility between the data to be migrated and the target switching frequency band, and avoids transmission interruptions and data packet loss caused by blind frequency band switching. By formulating the signal transmission switching sequence according to the switching priority level of each channel, the simultaneous migration mode of multiple channels is abandoned, which helps to avoid the contention for target frequency band resources when multiple tasks switch concurrently, and at the same time helps to avoid the synchronization conflict between the release of resources in the current frequency band and the acquisition of resources in the target frequency band. This helps to ensure the continuity and stability of the transmission task in the entire adaptive frequency band switching process, and thus improves signal processing efficiency.

[0007] In one possible implementation, when the data to be migrated includes preset distribution characteristics, the method further includes: Identify the sending device and its corresponding location in the data of the task to be migrated and transmitted; and determine whether the sending device needs blind spot filling based on the occlusion status of the sending location. If so, the target missing frequency band is determined from the candidate missing frequency bands based on the characteristics of the missing frequency band to be migrated, and the missing frequency band is used to transmit the data of the transmission task to be migrated.

[0008] By adopting the above technical solution, the blind spot filling process is triggered by identifying the obstruction at the transmitter location, and the target blind spot filling frequency band is located based on the characteristics of the migration requirements. This makes it easier to compensate for the weak penetration of high-frequency signals. By quickly filling the coverage gaps in the obstructed area, the transmitter equipment can still obtain a stable signal link in complex obstruction environments.

[0009] In one possible implementation, determining whether the transmitting device needs blind spot compensation based on the occlusion situation at the transmitting end's location includes: The interference object identifier and other transmitting devices of the transmitting device are identified from the environmental image. A first interference value is determined by weighted calculation based on the interference object identifier and the interference interval between the transmitting device location and each interference object. A second interference value is determined based on the historical transmission record data of the other transmitting devices. The environmental image is an image of the area where the transmitting device is located. Obtain the receiving end location of the receiving end device corresponding to the sending end device, and determine the path complexity of the transmission path based on the environmental image, the sending end location, and the receiving end location; Based on the first interference value, the second interference value, and the path complexity, a blind spot compensation score is determined for the transmitting device. When the blind spot compensation score is higher than a preset score threshold, it is determined that the transmitting device needs to perform blind spot compensation processing.

[0010] By adopting the above technical solution, the identification of interference objects from environmental images and the weighted calculation of the interference interval between the transmitting device and each interference object are combined to overcome the limitations of traditional single-dimensional judgment of interference. This facilitates the improvement of the accuracy in determining the first interference value. The second interference value is determined by analyzing historical transmission record data, which facilitates the quantification of concurrent interference from multiple transmitting devices. Finally, by integrating the first interference value, the second interference value, and the path complexity quantification blind spot filling score, the dual pain points of interference and occlusion are considered in a coordinated manner. Compared with single-factor judgment, this avoids transmission lag after blind spot filling due to focusing only on occlusion and ignoring dense interference from devices. It also avoids misjudging the blind spot filling needs in occlusion scenarios due to considering only interference. This significantly improves the accuracy of blind spot filling triggering and reduces invalid or missed blind spot filling.

[0011] In one possible implementation, determining the second interference value based on historical transmission record data of the other transmitting devices includes: Based on the historical transmission record data of each other transmitting device, the proportion of high-frequency transmission of each other transmitting device during data transmission within the preset observation period is determined. Based on the transmission path corresponding to the transmitting device, the transmitting end examination area corresponding to the transmitting device is divided into multiple examination partitions. Different examination partitions have different influence weights. The transmitting end examination area is the examination area determined with the transmitting device as the center and a preset distance as the radius. The second interference value is determined based on the influence weight of each examination partition, the number of other transmitting devices in each examination partition, and the proportion of high-frequency transmission of other transmitting devices in each examination partition.

[0012] By adopting the above technical solution, and by analyzing the proportion of high-frequency transmission of each other transmitting device during the preset observation period, it is convenient to assess the parallel interference caused by each other transmitting device to the transmitting device. The transmitting device's transmission path is used to divide the transmitting device's observation area into regions, and the influence weight of each observation region is allocated differently. This makes it easier to accurately distinguish the interference contribution of different other transmitting devices to the transmitting device, thereby improving the accuracy of determining the second interference value.

[0013] In one possible implementation, transmitting the data of the transmission task to be migrated based on the current frequency band and the gap-filling frequency band includes: Identify the data features contained in the data to be migrated and transmitted, and divide the data to be migrated and transmitted based on the feature priority of the data features to obtain a first partitioned data and a second partitioned data, wherein the feature priority of the first partitioned data is higher than the feature priority of the second partitioned data. The first partitioned data is transmitted based on the current frequency band, and the second partitioned data is transmitted based on the blind spot filler frequency band; Identify the frequency interval between the current frequency band and the gap fill frequency band, and determine whether retransmission is needed based on the frequency interval and the data characteristics; If so, then supplementary data is generated based on the first partitioned data, and the supplementary data is transmitted based on the current frequency band.

[0014] By adopting the above technical solution, the data characteristics of the data to be migrated and transmitted are analyzed, and the transmission tasks are split based on feature priority. This allows for differentiated transmission of the data to be migrated and transmitted according to feature priority, preventing data with different feature priorities from competing for transmission resources. This fundamentally ensures the real-time performance and integrity of core data during transmission. In addition, the probability of leakage during parallel transmission is determined by analyzing the frequency interval between the current frequency band and the blind spot band. Furthermore, the importance of the data to be migrated and transmitted is understood by analyzing data characteristics. Supplementary data is generated based on the probability of possible leakage and the importance of the data. By sending supplementary data while transmitting the data to be migrated and transmitted, the integrity of core data during transmission is further improved.

[0015] In one possible implementation, generating resend data based on the first partitioned data includes: Based on the historical transmission logs of the current frequency band during the historical analysis period, the historical packet loss rate and historical packet loss type of the current frequency band during the historical analysis period are determined based on the historical transmission logs. The retransmission method is determined based on the historical packet loss rate and the historical packet loss type. The retransmission method includes overall retransmission and segmented retransmission. Based on the feature priority corresponding to the first segmentation data, the overlap of resending is determined; Retransmission data is generated based on the retransmission overlap and the first partition data, and transmitted in the current frequency band based on the retransmission format.

[0016] By adopting the above technical solution, based on the historical transmission logs of the current frequency band, the historical packet loss rate and historical packet loss type are extracted and the retransmission method is determined, which helps to reduce the probability of packet loss in the retransmitted data. The retransmission overlap is determined by the feature priority corresponding to the first partition data, rather than random retransmission or overall retransmission of the first partition data, which helps to avoid insufficient or excessive retransmission, thereby improving the effectiveness of retransmission.

[0017] Secondly, this application provides a processing system, which adopts the following technical solution: A processing system comprising: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the above-described multi-band adaptive signal processing method.

[0018] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and executed by the multi-band adaptive signal processing method described above.

[0019] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the above-described multi-band adaptive signal processing method.

[0020] In summary, this application includes at least one of the following beneficial technical effects: By analyzing the transmission status of various signals within the current frequency band from multiple dimensions and performing weighted calculations, the switching priority of each channel can be intuitively evaluated. In addition, by analyzing the characteristics of the data to be migrated, the target switching frequency band is selected from multiple candidate frequency bands, which helps to improve the compatibility between the data to be migrated and the target switching frequency band and avoid transmission interruptions and data packet loss caused by blind frequency band switching. By formulating the signal transmission switching sequence according to the switching priority of each channel, the simultaneous migration mode of multiple channels is abandoned, which helps to avoid contention for target frequency band resources when multiple tasks switch concurrently, and also helps to avoid synchronization conflicts between the release of resources in the current frequency band and the acquisition of resources in the target frequency band. This helps to ensure the continuity and stability of the transmission task in the entire adaptive frequency band switching process, and thus helps to improve signal processing efficiency. By analyzing the proportion of high-frequency transmissions of other transmitting devices during the preset observation period, it is easier to assess the parallel interference caused by other transmitting devices to the transmitting device. The transmitting device observation area is divided into regions according to the transmission path of the transmitting device, and the influence weight of each observation region is allocated differently. This makes it easier to accurately distinguish the interference contribution of different other transmitting devices to the transmitting device, thereby improving the accuracy of determining the second interference value. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a multi-band adaptive signal processing method according to an embodiment of this application; Figure 2 This is a schematic diagram of an interference value determination process in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a processing system according to an embodiment of this application. Detailed Implementation

[0022] The following is in conjunction with the appendix Figures 1 to 3 This application will be described in further detail.

[0023] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0024] 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.

[0025] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0026] Specifically, this application provides a multi-band adaptive signal processing method executed by a processing system. This processing system can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet computer, laptop computer, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this connection.

[0027] refer to Figure 1 , Figure 1 This is a flowchart illustrating a multi-band adaptive signal processing method according to an embodiment of this application. The method includes steps S110-S150, wherein: Step S110: Obtain signal transmission record data of each channel in the current frequency band within the first preset time period, and identify the proportion of transmission service types, historical bit error rate and channel expansion value contained in each signal transmission record data.

[0028] Specifically, the current frequency band can be any frequency band that requires multi-band adaptive signal processing. The current frequency band contains multiple channels. The signal transmission record data corresponding to each channel can be obtained from the processing system through the channel number of each channel. For the signal transmission record data corresponding to any channel, the transmission count corresponding to each transmission service type can be identified from the signal transmission record data according to a preset feature recognition algorithm. The transmission service types include, but are not limited to, video, audio, image, and text. Since different transmission service types correspond to different type identifiers, for example, MP4, AVI, and MOV correspond to video, TXT, JSON, and XML correspond to text, and MP3, WAV, and AAC correspond to audio, feature recognition can be used to identify them from the signal transmission record data. Finally, by comparing the transmission counts corresponding to each transmission service type, the proportion of the transmission service type corresponding to the channel in the first preset time period can be determined. The specific preset feature recognition algorithm is not specifically limited in this embodiment. The first preset time period is a period of time before the current time. The duration of the first preset time period can be 20 minutes or 30 minutes. The specific duration is not specifically limited in this embodiment.

[0029] The historical bit error rate is used to characterize the packet loss situation when the channel performs a transmission task within a first preset time period. It can be extracted from the signal transmission record data of the channel within the first preset time period based on a preset feature recognition algorithm. The total number of symbols and the number of erroneous symbols within the first preset time period are the total number of bits of binary data transmitted by the channel within the first preset time period, and the number of erroneous symbols is the total number of symbols that are judged to be erroneous during transmission. The historical bit error rate is determined according to the preset historical bit error rate calculation formula, i.e., historical bit error rate = number of erroneous symbols / total number of symbols. The preset feature recognition algorithm is not specifically limited in this embodiment of the application.

[0030] The channel expansion value is used to characterize the remaining carrying capacity of the channel within a first preset time period. The larger the value, the stronger the expansion potential; the smaller the value or the negative value, the more overloaded the channel is. Based on a preset feature recognition algorithm, the actual amount of data transmitted by all transmission tasks within the first preset time period can be identified from the signal transmission record data. Then, based on the preset channel expansion value calculation formula, i.e., channel expansion value = maximum carrying capacity - actual transmission data amount, the channel expansion value is determined. The maximum carrying capacity of the channel is related to the hardware specification parameters and protocol configuration parameters of the channel.

[0031] Based on the above method, the proportion of transmission service types, historical bit error rate, and channel expansion value of each channel in the first preset time period can be determined.

[0032] Step S120: Perform multi-dimensional weighted processing on the proportion of transmission service types, historical bit error rate, and channel expansion value corresponding to each channel to determine the handover priority level of each channel.

[0033] Specifically, due to the significant differences in the physical meaning and numerical range of the three indicators mentioned above—for example, the historical bit error rate might be a decimal on the order of 1e-6, the channel expansion value might be on the order of GB, and the proportion might be a percentage—it is necessary to convert the three indicators into standardized scores directly related to the handover priority level before determining the handover priority level for a channel. For any given channel: regarding the preprocessing of the proportion of transmission service types, a comprehensive value for the proportion of high-priority services can be determined based on preset service type priority weights. These preset service type priority weights can be set by relevant technical personnel according to actual needs; for example, video weight 0.4, audio weight 0.3, image weight 0.2, and text weight 0.1. Then, a weighted calculation is performed based on each transmission service type and its corresponding preset service type priority weight to obtain the total value of the proportion of high-priority services. Finally, the service type proportion score corresponding to the total value of the proportion of high-priority services is determined based on the first preset mapping relationship. The higher the total value of the proportion of high-priority services, the higher the corresponding service type proportion score. The first preset mapping relationship is the total value of the proportion of high-priority services... The correspondence between the service type percentage score and the service type proportion score is not specifically limited in this embodiment. Regarding the historical bit error rate (BER), the BER score corresponding to the historical BER can be determined based on a second preset mapping relationship; a higher historical BER corresponds to a higher BER score. The second preset mapping relationship is the correspondence between the historical BER and the BER score, and its specific details are not specifically limited in this embodiment. Regarding the channel expansion value, the expansion score corresponding to the channel expansion value can be determined based on a third preset mapping relationship; a higher channel expansion value corresponds to a lower expansion score. The third preset mapping relationship is the correspondence between the channel expansion value and the expansion score, and its specific details are not specifically limited in this embodiment. Finally, the service type proportion score, BER score, and expansion score are summed to obtain a total score. Then, the handover priority level corresponding to the total score is determined based on a preset priority mapping relationship, which is the correspondence between the total score and the handover priority level, and its specific details are not specifically limited in this embodiment. The handover priority level for each channel can be determined using the above method.

[0034] Step S130: When the frequency band load pressure value of the current frequency band is detected to be greater than the preset pressure threshold, the data of the transmission task to be migrated corresponding to the current frequency band in the second preset time period is obtained, and the characteristic parameters of the migration requirement are identified based on the data of the transmission task to be migrated.

[0035] Specifically, the band load pressure value of the current frequency band refers to the overall resource occupancy status of all channels within the current frequency band. It primarily characterizes the degree of strain on key resources such as channel bandwidth, concurrent connections, and transmission rate due to the occupation of transmission tasks. A higher band load pressure value indicates that channel resources within the current frequency band are more fully utilized, with fewer remaining available resources, and a higher risk of stuttering and packet loss during the execution of related transmission tasks. When the band load pressure value exceeds a preset pressure threshold, it may be necessary to initiate transmission task migration and traffic diversion to avoid overloading the current frequency band. The specific preset pressure threshold is not specifically limited in this embodiment. The band load pressure value of the current frequency band can be determined by weighted summation of the bandwidth occupancy rate, concurrent connection ratio, and transmission rate ratio of the current frequency band. The specific determination method is not elaborated in this embodiment.

[0036] The second preset time period is a period of time after the current moment. The duration of the second preset time period can be 20 minutes or 30 minutes, and the specific duration can be set by relevant technical personnel according to actual needs. In this embodiment, no specific limitation is made. The transmission task data to be migrated corresponding to the second preset time period are the transmission tasks that may need to be executed in the current frequency band within the second preset time period. The transmission task data to be migrated corresponding to the second preset time period can be predicted from historical transmission task data and determined together with the scheduled transmission tasks. The scheduled transmission tasks are transmission tasks that have been initiated in advance by the user or the system and explicitly specified to be executed within the second preset time period. They can be directly extracted from the corresponding task reservation module of the processing system without prediction. For example, tasks such as "automatically download high-definition video in 20 minutes" or "schedule to upload files to the cloud in 30 minutes" manually set by the user are stored in the task reservation module of the processing system. The migration requirement features in the transmission task data to be migrated can be identified based on a preset feature recognition algorithm. The migration requirement feature parameters include, but are not limited to, the maximum tolerable latency threshold, the minimum required transmission rate threshold, the maximum tolerable bit error rate threshold, and the minimum required bandwidth threshold, which facilitates the improvement of adaptability during the frequency band switching process.

[0037] Step S140: Determine the target switching frequency band from the candidate frequency bands based on the characteristics of the migration requirements.

[0038] Specifically, candidate frequency bands are idle frequency bands that meet preset conditions. These preset conditions may include: idle bandwidth percentage ≥ preset broadband threshold, current number of access devices ≤ preset device limit, bandwidth utilization rate ≤ preset ratio, and remaining bearer capacity ≥ preset capacity value. The preset broadband threshold, preset device limit, preset ratio, and preset capacity value are not specifically limited in this embodiment. Then, based on the characteristics of the migration requirement, the candidate frequency bands are filtered to obtain the corresponding target switching frequency band. Specifically, a preset feature recognition algorithm can be used to identify the candidate feature parameters corresponding to each candidate frequency band. By matching the candidate feature parameters of each candidate frequency band with the migration requirement feature parameters, a candidate matching score is determined for each candidate frequency band. The candidate frequency band with the highest candidate matching score is determined as the target switching frequency band. The candidate feature parameters include a candidate latency threshold, a candidate transmission rate threshold, a candidate bit error rate threshold, and a candidate bandwidth threshold. The specific preset feature recognition algorithm is not specifically limited in this embodiment.

[0039] Step S150: Based on the switching priority level of each channel in the current frequency band, formulate a signal transmission switching sequence, and based on the signal transmission switching sequence, adaptively migrate and switch the data to be migrated from the current frequency band to the target switching frequency band.

[0040] Specifically, all channels in the current frequency band are sorted according to their switching priority to obtain a signal transmission switching sequence. The switching priority of each channel in this signal transmission switching requirement can be from high to low or from low to high. The specific sorting method is not specifically limited in this embodiment, as long as the switching is performed in descending order of switching priority during adaptive migration to the target switching frequency band. That is, the transmission tasks corresponding to channels with higher switching priority are first migrated to idle channels in the target switching frequency band to avoid service interruption due to overload of the current frequency band. The transmission tasks corresponding to channels with moderate switching priority can be migrated sequentially according to plan, while the transmission tasks corresponding to channels with lower switching priority can be migrated with a delay. Since the target switching frequency band is determined by matching candidate delay thresholds, candidate transmission rate thresholds, candidate bit error rate thresholds, and candidate bandwidth thresholds, any channel in the target switching frequency band can meet the migration requirements. Therefore, when transmission tasks corresponding to channels with different switching priority levels migrate to the target switching frequency band, they can migrate to any idle channel in the target switching frequency band.

[0041] In this embodiment of the application, by analyzing the transmission status of each signal in the current frequency band from multiple dimensions and performing weighted calculations, the switching priority of each channel can be intuitively evaluated. In addition, by analyzing the characteristics of the data to be migrated, the target switching frequency band is selected from multiple candidate frequency bands, which facilitates the improvement of the compatibility between the data to be migrated and the target switching frequency band, and avoids transmission interruptions and data packet loss caused by blind frequency band switching. By formulating a signal transmission switching sequence according to the switching priority level of each channel, the simultaneous migration mode of multiple channels is abandoned, which facilitates the avoidance of contention for target frequency band resources when multiple tasks are switched concurrently, and at the same time, it facilitates the avoidance of synchronization conflicts between the release of resources in the current frequency band and the acquisition of resources in the target frequency band. This facilitates the guarantee of the continuity and stability of the transmission task in the entire adaptive frequency band switching process, and thus facilitates the improvement of signal processing efficiency.

[0042] Furthermore, when the data to be migrated and transmitted includes preset distribution characteristics, the method provided in this application embodiment further includes: Identify the sending device and its corresponding location in the data to be migrated and transmitted. Based on the occlusion status of the sending device, determine whether the sending device needs blind spot filling processing. If so, determine the target blind spot filling frequency band from the candidate blind spot filling frequency bands based on the characteristics of the migration requirement, and transmit the data to be migrated and transmitted based on the current frequency band and the blind spot filling frequency band.

[0043] Specifically, the preset distribution characteristics refer to preset attributes used to characterize the spatial distribution of the data of the transmission task to be migrated in the sending device and the intensity of task concurrency. Specifically, this can be the density of sending devices exceeding a preset density threshold and the concurrency rate of transmission tasks exceeding a preset concurrency threshold, indicating that the sending device may be located at a large event venue, such as a concert or other large-scale event. The preset density threshold and preset concurrency threshold are not specifically limited in this embodiment. The degree of obstruction of the sending device can be quantified from two aspects: physical obstruction and signal interference. Based on the degree of obstruction, it is determined whether blind spot compensation processing is needed to ensure the transmission quality requirements of the sending device for the transmission task, thereby improving the smoothness after the transmission task migration. Furthermore, to improve the accuracy of blind spot compensation triggering, determining whether the sending device needs blind spot compensation processing based on the obstruction situation at the sending location can specifically include: The process involves identifying interference targets and other transmitting devices from an environmental image. A first interference value is determined by weighted calculation based on the interference targets and the interference interval between the transmitting device's location and each interference target. A second interference value is determined based on historical transmission records of other transmitting devices. The environmental image is an image of the area where the transmitting device is located. The receiving device's location is obtained, and the path complexity of the transmission path is determined based on the environmental image, the transmitting device's location, and the receiving device's location. A blind spot compensation score is determined based on the first interference value, the second interference value, and the path complexity. If the blind spot compensation score is higher than a preset threshold, the transmitting device is deemed to need to perform blind spot compensation processing.

[0044] Specifically, the system acquires images of the area where the transmitting device is located and identifies interfering devices that may interfere with the transmitting device from the environmental images based on a preset feature recognition algorithm. Interfering devices generally meet the characteristics of generating electromagnetic interference, occupying wireless frequency band resources, or affecting signal propagation. Different interfering devices have different interfering object identifiers. When the transmitting device is a mobile terminal, the interfering device can be a speaker, microphone, walkie-talkie, display screen, etc. Other transmitting devices can be other mobile terminals.

[0045] While identifying the interference object identifiers of various interference target devices from the environmental image based on a preset feature recognition algorithm, it is also necessary to identify the interference location of each interference target device. Based on the interference location and the transmitter location, the interference interval between each interference target device and the transmitter device is determined. Different interference object identifiers correspond to different interference impact values, and different interference intervals correspond to different interference weights. The interference impact value of each interference target device can be extracted from the processing system based on its identifier, and then a weighted calculation can be performed based on the corresponding interference weight to determine the first interference value. The smaller the interference interval, the higher the interference weight. The interference impact value of each interference target device can be determined based on a preset interference weight mapping relationship, which is the correspondence between interference intervals and interference weights. The specific details are not limited in this embodiment and can be determined by relevant personnel based on historical experimental data and then uploaded to the processing system.

[0046] By analyzing the historical transmission records of other transmitting devices within a historical time period, and identifying the number of times and duration that other transmitting devices used high-frequency bands for data transmission within that historical time period, the quality requirements of other transmitting devices for transmission tasks can be quantified. This facilitates the acquisition of a second interference value that can quantify the interference that other transmitting devices may cause to the transmitting device.

[0047] Different transmitting devices may correspond to different receiving devices. The transmission path between the transmitting and receiving devices can be determined based on the locations of the transmitting and receiving devices, combined with the environmental image. The transmission path is not a straight-line distance between the transmitting and receiving devices, but needs to be determined by combining the locations of the two ends, obstructions / interference devices in the environmental image, and following the principles of bypassing obstacles, avoiding strong interference, and adapting to signal propagation characteristics. Specifically, the key elements affecting the signal propagation of the transmitting device can be identified from the environmental image based on a preset feature recognition algorithm, and their positions and attributes can be marked as constraints for path planning. Key elements include, but are not limited to, obstruction marks, such as buildings, crowds, and displays; and interference device marks, including but not limited to speakers and microphones. Following the physical laws of signal diffraction, reflection, and scattering, and combining environmental constraints with preset path planning principles, a feasible path is planned. The transmission path can be a broken line or a curve. The preset path planning principles can include prioritizing bypassing completely obstructive objects and areas with strong interference, and selecting the edges of obstructive objects and areas with weak interference as path nodes. Specific details are not limited in this embodiment. For example, if the transmitting device is a viewer's mobile phone and the receiving device is a live streaming server on the stage, the straight path might be mobile phone - stage backdrop - server. However, the actual transmission path might be: mobile phone (viewer area) - bypassing densely populated areas (partial obstruction) - rear outer wall of the stage (reflected signal) - avoiding areas with strong interference from wireless microphones - server. The path complexity can be determined by identifying the number of nodes, path length, number of bends, and average bend angle in the transmission path using a preset feature recognition algorithm. Higher path complexity corresponds to a greater number of nodes, a longer path length, more bends, and a larger average bend angle.

[0048] Finally, the first interference value, the second interference value, and the path complexity are normalized. The blind spot compensation score is obtained by summing the normalization results. When the blind spot compensation score is higher than a preset threshold, it indicates a higher probability of transmission interruption or data loss during the transmission task of the sending device. Therefore, blind spot compensation is required when executing the transmission task of the sending device. That is, after determining the target switching frequency band corresponding to the data to be migrated, a lower frequency band is still needed to transmit part or all of the data to be migrated to avoid affecting user experience due to transmission interruption or packet loss. The specific preset threshold is not specifically limited in this embodiment and can be set by relevant technical personnel according to actual needs.

[0049] Furthermore, to improve the accuracy of determining the second interference value, the determination of the second interference value based on historical transmission record data from other transmitting devices may specifically include steps S210-S230, such as... Figure 2 As shown, where: Step S210: Based on the historical transmission record data corresponding to each other transmitting end device, determine the proportion of high-frequency band transmission when each other transmitting end device transmits data within a preset observation period.

[0050] Specifically, the preset observation period is a period of time prior to the current moment. The duration of the preset observation period can be 1 hour or 2 hours, and the specific duration is not specifically limited in this embodiment. For any transmitting device, the historical frequency bands used at each historical moment can be identified from the historical transmission record data corresponding to other transmitting devices according to a preset feature recognition algorithm. Historical frequency bands higher than a preset frequency band threshold are identified as high-frequency bands, and the historical usage duration corresponding to the high-frequency bands is determined. By comparing the historical usage duration with the duration corresponding to the preset observation period, the transmission ratio of the high-frequency band can be determined.

[0051] Step S220: Based on the transmission path corresponding to the sending device, the sending end examination area corresponding to the sending device is divided into multiple examination partitions. Different examination partitions have different influence weights. The sending end examination area is the examination area determined with the sending device as the center and a preset distance as the radius.

[0052] Specifically, the observation area of ​​the transmitting device is first determined with the transmitting device as the center and a preset distance as the radius. Then, the observation area is unevenly divided according to the path direction of the transmission path, resulting in multiple observation partitions. The center points of all observation partitions are different and all follow the path direction. The partition influence weight corresponding to different observation partitions can be determined based on the partition interval between the center of each region and the center of the observation area. The larger the partition interval, the higher the partition influence weight. The specific weight mapping relationship can be determined according to a preset weight mapping relationship, which is the correspondence between partition interval and partition influence weight. The specific content can be determined by relevant personnel based on historical experimental data and then uploaded to the processing system.

[0053] Step S230: Determine the second interference value based on the influence weight of each test partition, the number of other transmitting devices in each test partition, and the proportion of high-frequency transmission of other transmitting devices in each test partition.

[0054] Specifically, the number of other transmitting devices falling within each observation zone is determined based on the device location of each other transmitting device. Then, the average high-frequency band ratio is determined based on the high-frequency band transmission ratio of other transmitting devices in each observation zone. The number of other transmitting devices and the average high-frequency band ratio in each observation zone are normalized. Finally, the second interference value is obtained by weighted calculation based on the normalization result and the influence weight of the observation zone. The more other transmitting devices in each observation zone, the higher the average high-frequency band ratio, and the larger the corresponding second interference value.

[0055] In the embodiments of this application, by analyzing the proportion of high-frequency transmission of each other transmitting device during data transmission within a preset observation period, it is convenient to assess the parallel interference caused by each other transmitting device to the transmitting device. The transmitting end observation area is divided into regions by the transmission path of the transmitting end device, and the partition influence weight of each observation region is allocated differently, which is convenient to accurately distinguish the interference contribution of different other transmitting devices to the transmitting device, thereby improving the accuracy of determining the second interference value.

[0056] When the gap-filling score is higher than the preset score threshold, it is determined that the transmitting device needs to perform gap-filling processing. At this time, it is necessary to determine the target gap-filling frequency band from the candidate gap-filling frequency bands based on the characteristics of the migration requirement. The method for determining the target gap-filling frequency band can refer to the method for determining the target switching frequency band mentioned above, and will not be repeated here. Before the data to be migrated is switched to the target switching frequency band, the data to be migrated is transmitted based on the current frequency band and the gap-filling frequency band, wherein the frequency of the gap-filling frequency band is lower than that of the current frequency band. After the data to be migrated is switched to the target switching frequency band, the data to be migrated is transmitted based on the target switching frequency band and the gap-filling frequency band, wherein the frequency of the gap-filling frequency band is lower than that of the target switching frequency band.

[0057] By identifying the obstruction at the transmitter location, blind spot filling processing is triggered, and the target blind spot filling frequency band is located based on the characteristics of the migration requirements. This facilitates targeted compensation for the weak penetration of high-frequency signals. By quickly filling the coverage gaps in the obstructed areas, it ensures that the transmitter equipment can still obtain a stable signal link in complex obstruction environments.

[0058] Furthermore, to improve the integrity of the transmission process, the method provided in this application embodiment, when transmitting data of the migration task based on the current frequency band and the blind spot fill frequency band, is specifically used for: The system identifies data features contained in the data to be migrated and transmits, and divides the data based on the feature priority of the data features to obtain first partitioned data and second partitioned data, wherein the feature priority of the first partitioned data is higher than that of the second partitioned data; the first partitioned data is transmitted based on the current frequency band, and the second partitioned data is transmitted based on the blind spot filler frequency band; the frequency interval between the current frequency band and the blind spot filler frequency band is identified, and it is determined whether retransmission is required based on the frequency interval and data features; if so, retransmission data is generated based on the first partitioned data, and the retransmission data is transmitted based on the current frequency band.

[0059] Specifically, taking the transmission of data for the task to be migrated in the current frequency band and the gap-filling frequency band as an example, the data features contained in the data to be migrated can be identified based on a preset feature recognition algorithm. The feature priority of each data feature is determined according to a preset feature priority mapping relationship. This preset feature priority mapping relationship includes the feature priorities corresponding to different data features. The data to be migrated can be divided equally or unequally based on the data feature priorities to obtain a first partition and a second partition. The amount of data corresponding to the first partition is greater than or equal to the amount of data corresponding to the second partition, and the feature priority of the first partition is higher than that of the second partition. The first partition is transmitted using the current frequency band with a higher frequency, and the second partition is transmitted using the gap-filling frequency band with a lower frequency, in order to fundamentally ensure the real-time performance and integrity of the core data during transmission.

[0060] Because frequency bands with similar frequencies are prone to interference during parallel transmission, leading to misidentification of signal attribution by the receiver—that is, misidentifying data transmitted in band A as data in band B, or causing indistinguishable data from both bands—it is necessary to analyze the frequency interval between the current band and the gap-filling band after transmitting the first partitioned data based on the current band and the second partitioned data based on the gap-filling band. This analysis aims to determine whether data leakage will occur during parallel transmission of the first and second partitioned data. If the frequency interval between the current band and the gap-filling band is lower than a preset interval threshold, it indicates a high probability of data leakage during parallel transmission. In this case, to further ensure the real-time performance and integrity of core data during transmission, supplementary data needs to be generated based on the first partitioned data and then transmitted using the current band. If the target switching band and the gap-filling band are used to transmit the data for the migration task, the specific process can be found in the above embodiment, where the specific operation process for transmitting the data for the migration task using the current band and the gap-filling band is described, and will not be repeated here.

[0061] Furthermore, to avoid the problems of insufficient or excessive resending, the method provided in this application embodiment, when generating resending data based on the first partitioned data, may specifically include: Based on the historical transmission logs of the current frequency band within the historical analysis period, the historical packet loss rate and historical packet loss type of the current frequency band within the historical analysis period are determined; the retransmission method is determined based on the historical packet loss rate and historical packet loss type, including overall retransmission and segmented retransmission; the retransmission overlap is determined based on the feature priority corresponding to the first segmentation data; retransmission data is generated based on the retransmission overlap and the first segmentation data, and transmitted in the current frequency band based on the retransmission method.

[0062] Specifically, the historical analysis period is a time period preceding the current moment. The duration of the historical analysis period can be 5 days or 7 days, and the specific duration is not specifically limited in this embodiment. Based on a preset feature recognition algorithm, the historical packet loss rate and historical packet loss type corresponding to the current frequency band within the historical analysis period can be identified from the historical transmission log. The retransmission method is determined based on the historical packet loss type with the lowest historical packet loss rate. Historical packet loss types include continuous packet loss and random packet loss. When the historical packet loss type with the lowest historical packet loss rate is continuous packet loss, the probability of overall data packet loss is relatively low. Retransmission is performed as a whole to avoid the probability of packet loss during retransmission, thus ensuring the continuity and integrity of the retransmission data. When the historical packet loss type with the lowest historical packet loss rate is random packet loss, the probability of fragmented data loss is relatively low. Retransmission is performed by segmentation to accurately locate and retransmit the smallest fragmented lost data units, further reducing the probability of packet loss during retransmission.

[0063] The retransmission data can be the first segment data or a portion of the first segment data. The retransmission overlap degree corresponding to the feature priority of the first segment data can be determined according to the preset overlap degree mapping relationship. Different feature priorities represent different levels of importance of the first segment data. The higher the importance, the higher the retransmission overlap degree. Determining the retransmission data based on the retransmission overlap degree helps to further ensure the integrity of core data during transmission.

[0064] This application provides a processing system, such as... Figure 3 As shown, Figure 3 The processing system 300 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the processing system 300 may also include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one type, and the structure of this processing system 300 does not constitute a limitation on the embodiments of this application.

[0065] Processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0066] Bus 302 may include a pathway for transmitting information between the aforementioned components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 302 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by only one line, but this does not mean that there is only one bus or one type of bus.

[0067] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0068] The memory 303 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0069] The processing system includes, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. It can also include servers. Figure 3 The processing system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0070] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0071] This application provides a computer program product including a computer program that, when executed by a processor, implements the methods described in any of the above embodiments.

[0072] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0073] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A multi-band adaptive signal processing method, characterized by, The method comprises the following steps: acquiring signal transmission record data of each channel in the current frequency band within a first preset time period, and identifying the transmission service type proportion, historical error rate and channel expansion value contained in each signal transmission record data; performing multi-dimensional weighted processing on the transmission service type proportion, historical error rate and channel expansion value corresponding to each channel to determine the switching priority level of each channel; when it is detected that the frequency band load pressure value of the current frequency band is greater than a preset pressure threshold, acquiring the to-be-migrated transmission task data corresponding to the current frequency band within a second preset time period, and identifying the to-be-migrated demand feature parameters based on the to-be-migrated transmission task data; determining a target switching frequency band from the candidate frequency bands based on the to-be-migrated demand features; formulating a signal transmission switching sequence based on the switching priority level of each channel in the current frequency band, and adaptively migrating the to-be-migrated transmission task data corresponding to the current frequency band to the target switching frequency band based on the signal transmission switching sequence.

2. The method of claim 1, wherein, When the to-be-migrated transmission task data includes a preset distribution feature, the method further comprises the following steps: identifying the sending end device and the corresponding sending end location in the to-be-migrated transmission task data, and judging whether the sending end device needs to be subjected to blind filling processing based on the blocking condition of the sending end location; if yes, determining a target blind filling frequency band from the candidate blind filling frequency bands based on the to-be-migrated demand features, and performing transmission on the to-be-migrated transmission task data based on the current frequency band and the blind filling frequency band.

3. The method of claim 2, wherein, The step of judging whether the sending end device needs to be subjected to blind filling processing based on the blocking condition of the sending end location comprises the following steps: identifying the interference object identifier and other sending end devices of the sending end device from an environment image, and determining a first interference value through weighted calculation based on the interference object identifier and the interference interval between the sending end location and each interference object, and determining a second interference value based on the historical transmission record data of the other sending end devices, wherein the environment image is an image of the area where the sending end device is located; acquiring the receiving end location of the receiving end device corresponding to the sending end device, and determining the path complexity of the transmission path based on the environment image, the sending end location and the receiving end location; determining the blind filling score of the sending end device based on the first interference value, the second interference value and the path complexity, and determining that the sending end device needs to perform blind filling processing when the blind filling score is higher than a preset score threshold.

4. The method of claim 3, wherein, The step of determining the second interference value based on the historical transmission record data of the other sending end devices comprises the following steps: determining the high-frequency band transmission proportion of each other sending end device when performing data transmission within a preset observation time period based on the historical transmission record data corresponding to each other sending end device; performing regional division on the sending end investigation area corresponding to the sending end device based on the transmission path of the sending end device to obtain a plurality of investigation sub-regions, wherein different investigation sub-regions correspond to different sub-region influence weights, and the sending end investigation area is an investigation area determined with the sending end device as the center and a preset distance as the radius. According to the influence weight of each investigation subarea, the number of other sending end devices in each investigation subarea, and the high frequency band transmission proportion of other sending end devices in each investigation subarea, the second interference value is determined.

5. The method of claim 2, wherein the step of determining the frequency band of the received signal comprises the steps of: determining the frequency band of the received signal based on the received signal strength of the received signal. The transmission of the to-be-migrated transmission task data based on the current frequency band and the blind frequency band includes: Data features contained in the to-be-migrated transmission task data are identified, and the to-be-migrated transmission task data are divided based on the feature priority of the data features, to obtain first divided data and second divided data, wherein the feature priority of the first divided data is higher than the feature priority of the second divided data; The first divided data are transmitted based on the current frequency band, and the second divided data are transmitted based on the blind frequency band; A frequency interval between the current frequency band and the blind frequency band is identified, and whether retransmission is needed is determined based on the frequency interval and the data features; If so, retransmission data are generated based on the first divided data, and the retransmission data are transmitted based on the current frequency band.

6. The method of claim 5, wherein, The generation of the retransmission data based on the first divided data includes: Based on the historical transmission log of the current frequency band in a historical analysis time period, and based on the historical transmission log, a historical packet loss rate and a historical packet loss type corresponding to the current frequency band in the historical analysis time period are determined; Based on the historical packet loss rate and the historical packet loss type, a retransmission form is determined, and the retransmission form includes whole retransmission and split retransmission; Based on the feature priority corresponding to the first divided data, a retransmission coincidence degree is determined; The retransmission data are generated based on the retransmission coincidence degree and the first divided data, and transmission is performed in the current frequency band based on the retransmission form.

7. A processing system, characterized by The processing system includes: at least one processor; a memory; at least one application program, wherein the at least one application program is stored in the memory and is configured to be executed by the at least one processor, and the at least one application program is configured to perform the multi-frequency band adaptive signal processing method of any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, including: a computer program stored in the memory and capable of being loaded and executed by the processor to perform the multi-frequency band adaptive signal processing method of any one of claims 1-6.

9. A computer program product, characterised in that, including a computer program, which, when executed by the processor, implements the steps of the multi-frequency band adaptive signal processing method of any one of claims 1-6.

Images