Low-delay wireless screen projection method and device based on Polar code

Abstract

The invention relates to the technical field of wireless communication, in particular to a low-delay wireless screen projection method and device based on a Polar code, and the method comprises the following steps: based on a device connection record, through analyzing the connection time and frequency between devices, identifying a connection mode between the devices, including identifying a connection time period and a device combination preferred by a user, and performing automatic pairing and connection on the equipment to generate an automatic pairing record of the equipment. According to the invention, by analyzing the connection mode between the devices and the user preference, the process of connecting the devices by the user is simplified, the experience of wireless screen projection is optimized, the redundancy is automatically adjusted through the real-time evaluated signal error condition, the reliability of data transmission is improved, the quality of data transmission is optimized, and the real-time monitoring of the network environment is realized. According to the method, the load conditions of multiple frequency bands are evaluated, a data basis is provided for dynamically adjusting frequency band selection, the method is helpful to adapt to real-time changes of a wireless environment, and effective utilization of network bandwidth is maximized through real-time monitoring and transmission management of data streams.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular to a low-latency wireless screen projection method and device based on Polar codes. Background Art

[0002] The field of wireless communication technology focuses on transmitting information between multiple devices and exchanging data through radio waves and various wireless signals, including signal modulation and demodulation, channel coding and decoding, spectrum allocation and management, wireless network protocols and transmission standards. It aims to achieve in complex environments, including multiple devices concurrently, channel interference, and high data flow requirements, improve the rate, stability and reliability of data transmission, and is applied to data transmission between various types of devices, including mobile communications, satellite communications, and wireless local area networks. Various coding technologies, transmission protocols, frequency management strategies, and anti-interference technologies are all key components.

[0003] Among them, the wireless screen projection method refers to the technology of transmitting the images, audio and other contents of the display device to the receiving device through a wireless network. It aims to solve various problems such as delay control, data packet loss, transmission stability, and concurrent interference of multiple devices. By improving the stability and error correction capability of data transmission, it ensures low-latency transmission even in complex wireless environments. Combined with the priority scheduling mechanism and dynamic spectrum scheduling technology of the protocol layer, it optimizes the transmission path of the projection data stream, reduces the impact of network congestion and interference, and optimizes the performance and stability of wireless screen projection.

[0004] Traditional wireless screen projection methods lack the ability to control delays and correct signals when faced with multi-device concurrency, high data flow demands, and wireless interference in complex wireless environments. They rely on fixed frequency bands and fixed bandwidth allocation strategies in multi-device environments, and are unable to flexibly respond to changes in frequency band loads and fluctuations in channel quality. They are relatively slow in frequency band selection and switching, and frequency band congestion and interference often lead to transmission delays and data loss. In an environment with too many connected devices, bandwidth allocation cannot be adjusted in a timely manner, resulting in excessive network load and affecting transmission quality. There is a lack of a priority scheduling mechanism for different data stream types, and resources cannot be effectively allocated, resulting in waste of network bandwidth or delayed transmission of key data, resulting in the inability to meet low-latency, stable data transmission requirements in the case of poor signals. Summary of the invention

[0005] In order to solve the technical problems existing in the prior art, the embodiments of the present invention provide a low-latency wireless screen projection method and device based on Polar code. The technical solution is as follows:

[0006] On the one hand, a low-latency wireless screen projection method based on Polar code is provided, and the method includes:

[0007] S1: Based on the device connection records, the connection time and frequency between devices are analyzed to identify the connection mode between devices, including identifying the user's preferred connection time period and device combination, automatically pairing and connecting the devices, and generating device automatic pairing records;

[0008] S2: Based on the automatic pairing record of the device, decode the received Polar code signal, evaluate the error of the signal, adjust the redundancy, optimize the data transmission quality, and generate signal decoding and correction parameters;

[0009] S3: Based on the signal decoding and correction parameters, monitor the wireless network environment in real time, evaluate the load conditions and congestion levels of multiple frequency bands, and generate network status evaluation information;

[0010] S4: Based on the network status evaluation information, the signal strength and interference of the current frequency band are evaluated in real time, the adjustment requirement of the data transmission frequency band is evaluated, and the frequency band of data transmission is adjusted according to the load conditions of multiple channels to generate a transmission channel adjustment result;

[0011] S5: Based on the transmission channel adjustment result, the data flow is monitored in real time, the type of transmission data is analyzed, and the transmission list of the data packet is adjusted to generate data flow scheduling parameters.

[0012] As a further solution of the present invention, the device automatic pairing record includes the connection mode between devices, the device combination pairing record, and the user preference analysis result; the signal decoding and correction parameters include the signal error detection value, the decoding redundancy adjustment value, and the decoding accuracy analysis result; the network status evaluation information includes signal strength data, bandwidth usage, and frequency band load information; the transmission channel adjustment result includes the signal strength evaluation result of the current frequency band, the interference situation evaluation result, and the frequency band switching parameters; the data stream scheduling parameters include video data stream priority, audio data stream priority, and control signal priority.

[0013] As a further solution of the present invention, based on the device connection record, by analyzing the connection time and frequency between devices, identifying the connection mode between devices, including identifying the connection time period and device combination preferred by the user, automatically pairing and connecting the devices, the steps of generating the device automatic pairing record are specifically as follows:

[0014] S101: extracting connection time, connection frequency, connection success rate, and transmission quality information between multiple devices based on device connection records, and generating connection data extraction results;

[0015] S102: Analyze and identify the connection mode between devices based on the connection data extraction result, including identifying the connection frequency and connection time period of multiple device combinations, and generate a connection mode recognition result;

[0016] S103: Based on the connection mode recognition result, the devices are automatically paired and connected according to the connection time period and device combination preferred by the user, and a device automatic pairing record is generated.

[0017] As a further solution of the present invention, based on the automatic pairing record of the device, the received Polar code signal is decoded, the error of the signal is evaluated, the redundancy is adjusted, and the data transmission quality is optimized. The steps of generating signal decoding and correction parameters are specifically as follows:

[0018] S201: decoding the received Polar code signal based on the automatic pairing record of the device, identifying and recording error events in the decoding process, and generating a signal decoding result;

[0019] S202: Based on the signal decoding result, evaluate the error type and bit error rate of the signal, identify the amount of correction data that needs to be adjusted, and generate a redundancy adjustment parameter;

[0020] S203: Based on the redundancy adjustment parameter, the redundancy is adjusted in consideration of transmission efficiency and data quality, and a signal decoding and correction parameter is generated.

[0021] As a further solution of the present invention, based on the signal decoding and correction parameters, the wireless network environment is monitored in real time, the load conditions and congestion levels of multiple frequency bands are evaluated, and the steps of generating network status evaluation information are specifically as follows:

[0022] S301: Based on the signal decoding and correction parameters, monitor the wireless network environment in real time, measure signal strength and bandwidth usage, and obtain signal quality data;

[0023] S302: Based on the signal quality data, evaluate the real-time usage of multiple frequency bands, analyze the bandwidth occupancy of the frequency bands, and generate frequency band load evaluation data;

[0024] S303: Analyze the wireless network environment in real time according to the frequency band load evaluation data, evaluate the congestion levels of multiple channels, and generate network status evaluation information.

[0025] As a further solution of the present invention, the specific formula for evaluating the congestion levels of multiple channels is:

[0026]

[0027] Among them, N is the current network congestion level assessment value, T is the real-time channel traffic load size, B is the channel bandwidth utilization, C is the maximum channel transmission capacity, P is the packet error rate, M is the maximum transmission unit size, Q is the current queue delay, D is the maximum allowed queue delay, α1 is the channel load weight coefficient, α2 is the transmission error weight coefficient, and α3 is the queue delay weight coefficient.

[0028] As a further solution of the present invention, based on the network status evaluation information, the signal strength and interference of the current frequency band are evaluated in real time, the adjustment demand of the data transmission frequency band is evaluated, and the frequency band of data transmission is adjusted according to the load conditions of multiple channels. The steps of generating the transmission channel adjustment result are specifically as follows:

[0029] S401: Based on the network status evaluation information, the signal strength and interference of the current frequency band are acquired in real time, and compared with the data transmission demand to generate a frequency band adaptability evaluation result;

[0030] S402: Based on the frequency band adaptability evaluation result, evaluating the adjustment requirement of the data transmission frequency band, and generating an adjustment requirement evaluation result;

[0031] S403: According to the adjustment demand evaluation result and the real-time load conditions of multiple channels, the frequency band of data transmission is adjusted to generate a transmission channel adjustment result.

[0032] As a further solution of the present invention, based on the transmission channel adjustment result, the data flow is monitored in real time, the type of transmission data is analyzed, and the transmission list of the data packet is adjusted. The steps of generating data flow scheduling parameters are specifically as follows:

[0033] S501: Based on the transmission channel adjustment result, the data stream is monitored in real time, and the data packets are classified according to the data type, including video stream, audio stream, and control signal, and the transmission bandwidth requirements of various data streams are evaluated to generate a bandwidth requirement list;

[0034] S502: Based on the bandwidth requirement list, analyze the current network bandwidth resources, evaluate the transmission priorities of multiple data packets in real time, and generate data packet priority data;

[0035] S503: Based on the data packet priority data, the transmission list of the data packet is adjusted in real time to generate data flow scheduling parameters.

[0036] As a further solution of the present invention, the specific formula for real-time evaluation of the transmission priority of multiple data packets is:

[0037]

[0038] Among them, B1 represents the bandwidth value required by the data packet, B2 represents the current available bandwidth value, T1 represents the data packet transmission delay requirement, Q1 represents the data packet service quality level, L1 represents the network load level, D1 represents the data packet transmission distance, w1 represents the service quality weight coefficient, w2 represents the network load weight coefficient, β2 represents the bandwidth difference adjustment coefficient, β1 represents the transmission distance adjustment coefficient, and P1 is the transmission priority score of the target data packet.

[0039] On the other hand, a low-latency wireless screen projection device based on Polar code is provided, and the device is applied to a low-latency wireless screen projection method based on Polar code, and the device includes:

[0040] The device automatic pairing module analyzes the connection time, frequency, and pairing status data between devices based on the device connection records, identifies the connection mode between devices, automatically pairs and connects according to the user's preferred connection time period and device combination, and generates device automatic pairing records;

[0041] The transmission signal processing module decodes the received Polar code signal based on the automatic pairing record of the device, evaluates the error of the signal, adjusts the redundancy according to the error analysis, optimizes the data transmission quality, and generates signal decoding and correction parameters;

[0042] The network status monitoring module monitors the wireless network environment in real time based on the signal decoding and correction parameters, including signal strength, bandwidth occupancy, interference, evaluates the load and congestion level of multiple frequency bands, and generates network status evaluation information;

[0043] The network frequency band adjustment module evaluates the signal strength and interference of the current frequency band in real time based on the network status evaluation information, analyzes the adjustment requirements of the data transmission frequency band, and adjusts the data transmission frequency band according to the load conditions of multiple channels to generate a transmission channel adjustment result;

[0044] Based on the transmission channel adjustment result, the transmission queue management module monitors the data flow in real time, classifies and analyzes the data, evaluates the transmission priority of video, audio data, and control signals, adjusts the transmission list of data packets, and generates data flow scheduling parameters.

[0045] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0046] By analyzing the connection modes and user preferences between devices, the process of users connecting devices is simplified, the wireless screen projection experience is optimized, and the redundancy is automatically adjusted through real-time evaluation of signal errors, which improves the reliability of data transmission and optimizes the quality of data transmission. Real-time monitoring of the network environment enables evaluation of the load conditions of multiple frequency bands, providing a data basis for dynamically adjusting frequency band selection, helping to adapt to real-time changes in the wireless environment, and maximizing the effective use of network bandwidth through real-time monitoring and transmission management of data streams. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0049] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0050] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0051] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0052] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0053] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0054] Figure 7 It is a flow chart of the device of the present invention. DETAILED DESCRIPTION

[0055] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0056] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0057] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0058] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0059] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0060] The embodiment of the present invention provides a low-latency wireless screen projection method based on Polar code, such as Figure 1 The flowchart of the low-latency wireless screen projection method based on Polar code is shown. The processing flow of the method may include the following steps:

[0061] S1: Based on the device connection records, the connection time and frequency between devices are analyzed to identify the connection mode between devices, including identifying the user's preferred connection time period and device combination, automatically pairing and connecting the devices, and generating device automatic pairing records;

[0062] S2: Decode the received Polar code signal based on the device automatic pairing record, evaluate the signal error, adjust the redundancy, optimize the data transmission quality, and generate signal decoding and correction parameters;

[0063] S3: Based on signal decoding and correction parameters, it monitors the wireless network environment in real time, evaluates the load and congestion level of multiple frequency bands, and generates network status evaluation information;

[0064] S4: Based on the network status evaluation information, the signal strength and interference of the current frequency band are evaluated in real time, the adjustment requirements of the data transmission frequency band are evaluated, and the data transmission frequency band is adjusted according to the load conditions of multiple channels to generate the transmission channel adjustment results;

[0065] S5: Based on the transmission channel adjustment result, the data flow is monitored in real time, the type of transmitted data is analyzed, and the transmission list of the data packet is adjusted to generate data flow scheduling parameters.

[0066] The device automatic pairing records include the connection mode between devices, device combination pairing records, and user preference analysis results. The signal decoding and correction parameters include signal error detection value, decoding redundancy adjustment value, and decoding accuracy analysis results. The network status assessment information includes signal strength data, bandwidth usage, and frequency band load information. The transmission channel adjustment results include the signal strength assessment results of the current frequency band, interference situation assessment results, and frequency band switching parameters. The data stream scheduling parameters include video data stream priority, audio data stream priority, and control signal priority.

[0067] See also Figure 2 Based on the device connection records, the connection time and frequency between devices are analyzed to identify the connection mode between devices, including identifying the user's preferred connection time period and device combination, and automatically pairing and connecting the devices. The specific steps for generating the device automatic pairing record are as follows:

[0068] S101: extracting connection time, connection frequency, connection success rate, and transmission quality information between multiple devices based on device connection records, and generating connection data extraction results;

[0069] In sub-step S101, data is extracted from the device connection record. The target data includes device ID, connection start time, connection end time, connection frequency, success or failure of each connection, quality of transmitted data, etc. The connection time, connection frequency and other data are sorted and clustered using time series analysis methods to generate a connection history for each device combination. Network quality data such as signal strength and packet loss rate are used in combination with latency analysis to analyze the average connection duration and transmission quality of each pair of devices. Through data aggregation technology, indicators such as connection frequency and success rate are summarized to generate connection data extraction results. The target data will provide a basis for subsequent device pairing and connection mode analysis.

[0070] S102: Analyze and identify the connection mode between devices based on the connection data extraction result, including identifying the connection frequency and connection time period of multiple device combinations, and generate a connection mode recognition result;

[0071] In sub-step S102, the connection data extraction results are classified and summarized according to the connection frequency and time period of the device combination. In order to identify the connection mode of the device combination, the K-means clustering algorithm is used to classify the device combination, and the devices are grouped according to the connection frequency and connection time period. The device combination in each group is analyzed according to the connection duration, success rate, connection frequency and other characteristics to identify the user's preferred device combination. Cluster analysis helps to discover high-frequency connected device pairs and commonly used connection time periods, and further obtains the connection mode recognition results, including information such as the connection frequency of the device combination, common connection time periods and average connection duration. The process provides a basis for automatic pairing and optimization of connection solutions.

[0072] S103: Based on the connection mode recognition result, automatically pair and connect the devices according to the connection time period and device combination preferred by the user, and generate a device automatic pairing record;

[0073] In sub-step S103, high-frequency connection combinations and common connection periods are extracted from the connection pattern recognition results, and the devices are automatically paired in combination with the connection success rate and transmission quality of the devices. In order to ensure the stability and efficiency of the device pairing, a weighted sorting algorithm is used to prioritize the devices according to the connection success rate, transmission quality and user preference period of each pair of devices, and select the most suitable device for pairing. After pairing is completed, the connection process is automatically started. The automated pairing mechanism reduces manual intervention, and the pairing results and connection period are recorded in the device automatic pairing record. The process improves the automation level of the device pairing and ensures fast and stable connection of the devices during the screen projection process.

[0074] See also Figure 3 , based on the device automatic pairing record, decode the received Polar code signal, evaluate the signal error, adjust the redundancy, optimize the data transmission quality, and generate the signal decoding and correction parameters. The specific steps are:

[0075] S201: Based on the device automatic pairing record, decode the received Polar code signal, identify and record error events in the decoding process, and generate a signal decoding result;

[0076] In sub-step S201, polarization layered decoding is used to extract valid data by analyzing the data state of each bit in the signal. During the decoding process, error events in the signal are identified and recorded, including lost bits, bit errors, and delay fluctuations. The process uses bit error rate calculation to quantify the frequency of error events and generate signal decoding results. The signal decoding results include error information during the transmission process, including the position of the error bit, the bit error rate, the packet loss position, and the state of the recovery bit, to ensure accurate decoding of the Polar code signal and provide necessary error analysis data for subsequent redundancy adjustment.

[0077] S202: Based on the signal decoding result, evaluate the error type and bit error rate of the signal, identify the amount of correction data that needs to be adjusted, and generate redundancy adjustment parameters;

[0078] In sub-step S202, the error type of each bit is classified, including packet loss error, bit flip error, signal attenuation, etc. The error type after decoding is evaluated using the bit error rate calculation formula, and the size of the error is quantified. By analyzing the bit error rate, it is identified which data bits need to adjust the redundancy to improve the transmission quality, including generating a corresponding amount of correction data when a high bit error rate area is identified. The amount of correction data is calculated based on the bit error rate. It is further determined whether redundancy needs to be increased, the error correction capability is optimized, and redundancy adjustment parameters are generated. The target parameters define how to adjust the signal redundancy according to the error size to improve the robustness of data transmission.

[0079] S203: Based on the redundancy adjustment parameter, the redundancy is adjusted in consideration of transmission efficiency and data quality, and a signal decoding and correction parameter is generated;

[0080] In sub-step S203, the transmission bandwidth, transmission delay and bit error rate of the current signal are evaluated in combination with the transmission efficiency requirements and data quality to determine whether the current redundancy meets the requirements. When considering the transmission efficiency, the channel capacity model is used to calculate the maximum transmission capacity of the current channel to ensure that the increase in redundancy does not lead to excessive delay or bandwidth waste. If the redundancy of the current signal is low and the bit error rate is high, the redundancy will be increased to enhance the error correction capability and avoid data loss. During the redundancy adjustment process, a dynamic redundancy adjustment algorithm is used to dynamically adjust the redundancy according to the real-time evaluated bit error rate and channel quality, and generate signal decoding and correction parameters. The target parameters include new redundancy values ​​and correction strategies to ensure that signal transmission achieves the best balance in terms of stability and delay.

[0081] See also Figure 4 Based on signal decoding and correction parameters, the wireless network environment is monitored in real time, the load and congestion levels of multiple frequency bands are evaluated, and the steps for generating network status evaluation information are as follows:

[0082] S301: Based on signal decoding and correction parameters, monitor the wireless network environment in real time, measure signal strength and bandwidth usage, and obtain signal quality data;

[0083] In sub-step S301, the wireless signal strength measurement technology is used to determine the strength of the current wireless signal by receiving the RSSI value of the wireless signal, and the signal quality is inferred based on this data. By monitoring the bandwidth usage and analyzing the bandwidth occupancy rate of each frequency band, the bandwidth resource allocation of the current network is calculated. The bandwidth monitoring module can track the bandwidth usage of the device and network connection in real time, determine whether there is excessive bandwidth occupancy, and comprehensively consider the signal strength and bandwidth occupancy to obtain signal quality data, including signal strength, bandwidth utilization, transmission delay and other parameters, to provide the basic data required for evaluating the status of the wireless network.

[0084] S302: Based on the signal quality data, evaluate the real-time usage of multiple frequency bands, analyze the bandwidth occupancy of the frequency bands, and generate frequency band load evaluation data;

[0085] In sub-step S302, spectrum analysis technology is used to measure the real-time data traffic of different frequency bands to evaluate the bandwidth occupancy of each frequency band. The frequency band monitor will calculate the bandwidth utilization of each frequency band based on the real-time traffic data to obtain the load level of each frequency band. By comparing the frequency band usage with the predetermined frequency band bandwidth upper limit, it is identified which frequency bands are close to saturation and which frequency bands have idle resources. In the process, the bandwidth allocation algorithm is used to automatically calculate the optimal bandwidth allocation plan for each frequency band to maximize resource utilization. The generated frequency band load assessment data provides real-time usage of each frequency band, reflecting the current status of the network environment and the available bandwidth of each frequency band.

[0086] S303: Analyze the wireless network environment in real time according to the frequency band load evaluation data, evaluate the congestion levels of multiple channels, and generate network status evaluation information;

[0087] The specific formula for evaluating the congestion level of multiple channels is:

[0088]

[0089] Among them, N is the current network congestion level assessment value, T is the real-time channel traffic load size, B is the channel bandwidth utilization, C is the maximum channel transmission capacity, P is the packet error rate, M is the maximum transmission unit size, Q is the current queue delay, D is the maximum allowed queue delay, α1 is the channel load weight coefficient, α2 is the transmission error weight coefficient, and α3 is the queue delay weight coefficient.

[0090] formula:

[0091]

[0092] Detailed explanation of the formula and the process of formula calculation and derivation:

[0093] The formula is used to calculate the network congestion level assessment value and comprehensively evaluate the network status;

[0094] Parameter meaning and setting value:

[0095] T is the real-time channel traffic load size, assumed to be 750Mbps, reflecting the current channel transmission load;

[0096] B is the channel bandwidth utilization, assumed to be 0.85, indicating the degree of channel resource occupancy;

[0097] C is the maximum transmission capacity of the channel, assumed to be 1000Mbps;

[0098] P is the packet error rate, assumed to be 0.02, indicating the transmission quality status;

[0099] M is the maximum transmission unit size, which is assumed to be 1500 bytes;

[0100] Q is the current queue delay, assumed to be 25ms;

[0101] D is the maximum allowed queue delay, assumed to be 50ms;

[0102] α1 is the channel load weight coefficient, assumed to be 0.4;

[0103] α2 is the transmission error weight coefficient, assumed to be 0.3;

[0104] α3 is the queue delay weight coefficient, assumed to be 0.3;

[0105] Substitute the parameters into the formula for calculation:

[0106]

[0107] N = 0.4 × 0.799 + 0.3 × 1.33 × 10 ―5 +0.3×0.707;

[0108] N = 0.320 + 0.000004 + 0.212;

[0109] N = 0.532;

[0110] The result 0.532 indicates that the current network congestion level is at a medium level, and the network status is assessed as light congestion, requiring appropriate flow control and resource scheduling optimization.

[0111] See also Figure 5 Based on the network status evaluation information, the signal strength and interference of the current frequency band are evaluated in real time, the adjustment requirements of the data transmission frequency band are evaluated, and the data transmission frequency band is adjusted according to the load conditions of multiple channels. The specific steps of generating the transmission channel adjustment result are as follows:

[0112] S401: Based on the network status evaluation information, the signal strength and interference of the current frequency band are obtained in real time, and compared with the data transmission requirements to generate a frequency band adaptability evaluation result;

[0113] In sub-step S401, the signal strength of the current frequency band is measured in real time by a wireless spectrum analyzer, and the interference situation of the frequency band is detected using interference source monitoring technology. By comparing the current signal strength and interference level, it is evaluated whether the frequency band meets the requirements of data transmission. Combined with the data flow demand analysis, the requirements of data transmission on bandwidth, latency, data packet size and transmission priority are obtained to ensure that the frequency band can carry the required transmission load. Using the spectrum adaptability evaluation model, the measured signal strength and interference level are compared with the data transmission requirements to generate a frequency band adaptability evaluation result, which provides a basis for subsequent frequency band adjustments.

[0114] S402: Based on the frequency band adaptability evaluation result, evaluating the adjustment requirement of the data transmission frequency band, and generating an adjustment requirement evaluation result;

[0115] In sub-step S402, it is analyzed whether the current frequency band can meet the requirements of data transmission. If the evaluation result shows that the signal strength or interference level of the current frequency band does not meet the requirements, it will be evaluated whether it is necessary to switch to other frequency bands. The frequency band load prediction model is used to predict the signal quality, interference situation and bandwidth availability of each backup frequency band. By calculating the load and adaptability of each frequency band, the best time and frequency band for frequency switching are identified, and the adjustment demand assessment results are generated to ensure the reliability and efficiency of data transmission.

[0116] S403: adjusting the frequency band of data transmission according to the adjustment demand evaluation result and the real-time load conditions of the multiple channels, and generating a transmission channel adjustment result;

[0117] In sub-step S403, combined with real-time channel load monitoring, the current load status of each channel is obtained, and each frequency band is dynamically selected. When it is detected that the load of a certain frequency band has reached the upper limit or the signal quality cannot meet the transmission requirements, another channel will be selected for data transmission. In the process, the channel selection algorithm is used to evaluate the bandwidth utilization, signal strength and interference level of each channel to calculate the optimal frequency band. The frequency band will be adjusted according to the real-time load situation to reduce network congestion and interference, ensure smooth data transmission, generate the transmission channel adjustment result, and record the frequency band information after switching to ensure that the data stream is smoothly transmitted in a more optimal transmission channel.

[0118] See also Figure 6 ,Based on the transmission channel adjustment results, the data flow is monitored in real time, the type of transmitted data is analyzed, and the transmission list of the data packet is adjusted. The steps for generating data flow scheduling parameters are as follows:

[0119] S501: Based on the transmission channel adjustment result, the data stream is monitored in real time, and the data packets are classified according to the data type, including video stream, audio stream, and control signal, and the transmission bandwidth requirements of various data streams are evaluated to generate a bandwidth requirement list;

[0120] In sub-step S501, data packets are classified according to the characteristics of each data packet using data stream identification technology. Video streams, audio streams, and control signals are distinguished according to their different transmission requirements to determine the bandwidth requirements of each data stream. The bandwidth resources required for each data stream are calculated using a bandwidth estimation model in combination with the data packet size, data stream transmission delay requirements, and bandwidth allocation strategy. The bandwidth requirements of each type of data stream are summarized and a bandwidth requirement list is generated. The list records the bandwidth required for data streams of different data types under current network conditions, providing a basis for subsequent bandwidth allocation and priority scheduling.

[0121] S502: Analyze current network bandwidth resources based on the bandwidth demand list, evaluate transmission priorities of multiple data packets in real time, and generate data packet priority data;

[0122] The specific formula for evaluating the transmission priority of multiple data packets in real time is:

[0123]

[0124] Among them, B1 represents the bandwidth value required by the data packet, B2 represents the current available bandwidth value, T1 represents the data packet transmission delay requirement, Q1 represents the data packet service quality level, L1 represents the network load level, D1 represents the data packet transmission distance, w1 represents the service quality weight coefficient, w2 represents the network load weight coefficient, β2 represents the bandwidth difference adjustment coefficient, β1 represents the transmission distance adjustment coefficient, and P1 is the transmission priority score of the target data packet.

[0125] formula:

[0126]

[0127] Detailed explanation of the formula and the process of formula calculation and derivation:

[0128] The formula is used to calculate the data packet transmission priority value, and the result is used to determine the data packet transmission priority ranking; parameter meaning and setting value:

[0129] B1 represents the bandwidth required by the data packet, assuming it is 50Mbps;

[0130] B2 represents the current available bandwidth value, assuming it is 30Mbps;

[0131] T1 represents the data packet transmission delay requirement, which is assumed to be 20ms;

[0132] Q1 represents the data packet service quality level, which is assumed to be 0.8;

[0133] L1 represents the network load level, which is assumed to be 0.6;

[0134] D1 represents the data packet transmission distance, assuming it is 100m;

[0135] w1 represents the service quality weight coefficient, which is assumed to be 0.7;

[0136] w2 represents the network load weight coefficient, which is assumed to be 0.3;

[0137] β2 represents the bandwidth difference adjustment coefficient, which is assumed to be 0.8;

[0138] β1 represents the transmission distance adjustment coefficient, which is assumed to be 0.9;

[0139] Substitute the parameters into the formula for calculation:

[0140]

[0141] The result 0.00735 indicates that the data packet obtains a lower transmission priority value. The data packets are sorted in descending order according to the priority value, and the data transmission list is adjusted and managed to optimize bandwidth utilization and user experience.

[0142] S503: Based on the data packet priority data, the transmission list of the data packet is adjusted in real time to generate data flow scheduling parameters;

[0143] In sub-step S503, the data packets in the transmission list are sorted to ensure that high-priority data packets are given priority transmission when network bandwidth resources are insufficient. A dynamic priority scheduling algorithm is used to make real-time adjustments based on bandwidth requirements, data packet priority, and network conditions. For lower-priority data packets, their transmission will be postponed or a lower bandwidth will be selected for transmission to ensure efficient use of the network and avoid data packet loss. Data flow scheduling parameters are generated based on the real-time adjusted transmission order. The parameters include the priority of each data packet and the corresponding transmission path, which are used to optimize the transmission efficiency of the data flow and ensure that network resources are optimally allocated.

[0144] See also Figure 7 , a low-latency wireless screen projection device based on Polar code, the low-latency wireless screen projection device based on Polar code is used to execute the above-mentioned low-latency wireless screen projection method based on Polar code, and the device includes:

[0145] The device automatic pairing module analyzes the connection time, frequency, and pairing status data between devices based on the device connection records, identifies the connection mode between devices, automatically pairs and connects according to the user's preferred connection time period and device combination, and generates device automatic pairing records;

[0146] The transmission signal processing module decodes the received Polar code signal based on the device automatic pairing record, evaluates the signal error, adjusts the redundancy according to the error analysis, optimizes the data transmission quality, and generates signal decoding and correction parameters;

[0147] The network status monitoring module monitors the wireless network environment in real time based on signal decoding and correction parameters, including signal strength, bandwidth occupancy, interference, evaluates the load and congestion level of multiple frequency bands, and generates network status evaluation information;

[0148] The network frequency band adjustment module evaluates the signal strength and interference of the current frequency band in real time based on the network status evaluation information, analyzes the adjustment requirements of the data transmission frequency band, and adjusts the data transmission frequency band according to the load conditions of multiple channels to generate the transmission channel adjustment results;

[0149] Based on the transmission channel adjustment results, the transmission queue management module monitors the data flow in real time, classifies and analyzes the data, evaluates the transmission priority of video, audio data, and control signals, adjusts the transmission list of data packets, and generates data flow scheduling parameters.

[0150] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0151] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0152] In the present invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0153] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0154] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0155] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0156] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0157] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0158] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0159] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0160] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A low-latency wireless screen projection method based on Polar code, characterized in that: The method comprises: S1: Based on the device connection records, the connection time and frequency between devices are analyzed to identify the connection mode between devices, including identifying the user's preferred connection time period and device combination, automatically pairing and connecting the devices, and generating device automatic pairing records; S2: Based on the automatic pairing record of the device, decode the received Polar code signal, evaluate the error of the signal, adjust the redundancy, optimize the data transmission quality, and generate signal decoding and correction parameters; S3: Based on the signal decoding and correction parameters, monitor the wireless network environment in real time, evaluate the load conditions and congestion levels of multiple frequency bands, and generate network status evaluation information; S4: Based on the network status evaluation information, the signal strength and interference of the current frequency band are evaluated in real time, the adjustment requirement of the data transmission frequency band is evaluated, and the frequency band of data transmission is adjusted according to the load conditions of multiple channels to generate a transmission channel adjustment result; S5: Based on the transmission channel adjustment result, the data flow is monitored in real time, the type of transmission data is analyzed, and the transmission list of the data packet is adjusted to generate data flow scheduling parameters.

2. According to claim 1, the low-latency wireless screen projection method based on Polar code is characterized in that: The device automatic pairing record includes the connection mode between devices, device combination pairing record, and user preference analysis results; the signal decoding and correction parameters include signal error detection value, decoding redundancy adjustment value, and decoding accuracy analysis results; the network status evaluation information includes signal strength data, bandwidth usage, and frequency band load information; the transmission channel adjustment result includes the signal strength evaluation result of the current frequency band, the interference situation evaluation result, and the frequency band switching parameters; the data stream scheduling parameters include video data stream priority, audio data stream priority, and control signal priority.

3. The low-latency wireless screen projection method based on Polar code according to claim 1, characterized in that: Based on the device connection records, by analyzing the connection time and frequency between devices, the connection mode between devices is identified, including identifying the user's preferred connection time period and device combination, and the devices are automatically paired and connected. The specific steps for generating the device automatic pairing record are as follows: S101: extracting connection time, connection frequency, connection success rate, and transmission quality information between multiple devices based on device connection records, and generating connection data extraction results; S102: Analyze and identify the connection mode between devices based on the connection data extraction result, including identifying the connection frequency and connection time period of multiple device combinations, and generate a connection mode recognition result; S103: Based on the connection mode recognition result, the devices are automatically paired and connected according to the connection time period and device combination preferred by the user, and a device automatic pairing record is generated.

4. The low-latency wireless screen projection method based on Polar code according to claim 1, characterized in that: Based on the automatic pairing record of the device, the received Polar code signal is decoded, the error of the signal is evaluated, the redundancy is adjusted, the data transmission quality is optimized, and the steps of generating signal decoding and correction parameters are specifically as follows: S201: decoding the received Polar code signal based on the automatic pairing record of the device, identifying and recording error events in the decoding process, and generating a signal decoding result; S202: Based on the signal decoding result, evaluate the error type and bit error rate of the signal, identify the amount of correction data that needs to be adjusted, and generate a redundancy adjustment parameter; S203: Based on the redundancy adjustment parameter, the redundancy is adjusted in consideration of transmission efficiency and data quality, and a signal decoding and correction parameter is generated.

5. The low-latency wireless screen projection method based on Polar code according to claim 1, characterized in that: Based on the signal decoding and correction parameters, the wireless network environment is monitored in real time, the load conditions and congestion levels of multiple frequency bands are evaluated, and the steps of generating network status evaluation information are specifically as follows: S301: Based on the signal decoding and correction parameters, monitor the wireless network environment in real time, measure signal strength and bandwidth usage, and obtain signal quality data; S302: Based on the signal quality data, evaluate the real-time usage of multiple frequency bands, analyze the bandwidth occupancy of the frequency bands, and generate frequency band load evaluation data; S303: Analyze the wireless network environment in real time according to the frequency band load evaluation data, evaluate the congestion levels of multiple channels, and generate network status evaluation information.

6. The low-latency wireless screen projection method based on Polar code according to claim 5, characterized in that: The specific formula for evaluating the congestion levels of multiple channels is: Among them, N is the current network congestion level assessment value, T is the real-time channel traffic load size, B is the channel bandwidth utilization, C is the maximum channel transmission capacity, P is the packet error rate, M is the maximum transmission unit size, Q is the current queue delay, D is the maximum allowed queue delay, α1 is the channel load weight coefficient, α2 is the transmission error weight coefficient, and α3 is the queue delay weight coefficient.

7. The low-latency wireless screen projection method based on Polar code according to claim 1, characterized in that: Based on the network status evaluation information, the signal strength and interference of the current frequency band are evaluated in real time, the adjustment requirement of the data transmission frequency band is evaluated, and the frequency band of data transmission is adjusted according to the load conditions of multiple channels. The steps of generating the transmission channel adjustment result are specifically as follows: S401: Based on the network status evaluation information, the signal strength and interference of the current frequency band are acquired in real time, and compared with the data transmission demand to generate a frequency band adaptability evaluation result; S402: Based on the frequency band adaptability evaluation result, evaluating the adjustment requirement of the data transmission frequency band, and generating an adjustment requirement evaluation result; S403: According to the adjustment demand evaluation result and the real-time load conditions of multiple channels, the frequency band of data transmission is adjusted to generate a transmission channel adjustment result.

8. The low-latency wireless screen projection method based on Polar code according to claim 1, characterized in that: Based on the transmission channel adjustment result, the data flow is monitored in real time, the type of transmission data is analyzed, and the transmission list of the data packet is adjusted. The steps of generating the data flow scheduling parameters are specifically as follows: S501: Based on the transmission channel adjustment result, the data stream is monitored in real time, and the data packets are classified according to the data type, including video stream, audio stream, and control signal, and the transmission bandwidth requirements of various data streams are evaluated to generate a bandwidth requirement list; S502: Based on the bandwidth requirement list, analyze the current network bandwidth resources, evaluate the transmission priorities of multiple data packets in real time, and generate data packet priority data; S503: Based on the data packet priority data, the transmission list of the data packet is adjusted in real time to generate data flow scheduling parameters.

9. The low-latency wireless screen projection method based on Polar code according to claim 8, characterized in that: The specific formula for real-time evaluation of the transmission priority of multiple data packets is: Among them, B1 represents the bandwidth value required by the data packet, B2 represents the current available bandwidth value, T1 represents the data packet transmission delay requirement, Q1 represents the data packet service quality level, L1 represents the network load level, D1 represents the data packet transmission distance, w1 represents the service quality weight coefficient, w2 represents the network load weight coefficient, β2 represents the bandwidth difference adjustment coefficient, β1 represents the transmission distance adjustment coefficient, and P1 is the transmission priority score of the target data packet.

10. A low-latency wireless screen projection device based on Polar code, characterized in that: According to the low-latency wireless screen projection method based on Polar code according to any one of claims 1 to 9, the device comprises: The device automatic pairing module analyzes the connection time, frequency, and pairing status data between devices based on the device connection records, identifies the connection mode between devices, automatically pairs and connects according to the user's preferred connection time period and device combination, and generates device automatic pairing records; The transmission signal processing module decodes the received Polar code signal based on the automatic pairing record of the device, evaluates the error of the signal, adjusts the redundancy according to the error analysis, optimizes the data transmission quality, and generates signal decoding and correction parameters; The network status monitoring module monitors the wireless network environment in real time based on the signal decoding and correction parameters, including signal strength, bandwidth occupancy, interference, evaluates the load and congestion level of multiple frequency bands, and generates network status evaluation information; The network frequency band adjustment module evaluates the signal strength and interference of the current frequency band in real time based on the network status evaluation information, analyzes the adjustment requirements of the data transmission frequency band, and adjusts the data transmission frequency band according to the load conditions of multiple channels to generate a transmission channel adjustment result; Based on the transmission channel adjustment result, the transmission queue management module monitors the data flow in real time, classifies and analyzes the data, evaluates the transmission priority of video, audio data, and control signals, adjusts the transmission list of data packets, and generates data flow scheduling parameters.

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