Predictive scheduling and reliable handover method for multi-channel communication of mobile terminals

Abstract

The application relates to the technical field of communication channel management of a mobile terminal, and discloses a prediction scheduling and reliable switching method for multi-channel communication of a mobile terminal, which comprises the following steps: collecting a communication index of a kth communication channel in a communication channel set according to a preset period to obtain a kth index set; determining a kth state probability distribution of the kth index set; predicting a kth channel risk based on a kth conditional entropy of the kth communication channel and the kth state probability distribution; determining a target channel from the communication channel set based on a channel risk set; and scheduling and switching a data transmission channel of the mobile terminal from a current channel to the target channel. The scheme can overcome the technical defects of channel switching hysteresis in related technologies.

Description

Technical Field

[0001] This application relates to the field of communication channel management technology for mobile terminals, specifically to, but not limited to, a predictive scheduling and reliable handover method for multi-channel communication of mobile terminals. Background Technology

[0002] In practical applications, mobile terminals are often in heterogeneous network environments, including Long-Term Evolution (LTE), 5G New Radio (5G NR), and Wi-Fi. The network conditions in these heterogeneous environments are often characterized by strong time-varying and abrupt changes. For example, these heterogeneous network environments are prone to hotspot congestion, sudden changes in base station load, sudden changes in interference, and mobility obstruction. These changes can easily lead to abnormal situations such as latency jitter, sudden changes in throughput, packet loss rate, surge in retransmission operations, and even short-term disconnections in communication channels or links.

[0003] Meanwhile, with the diversification of mobile terminal functions and the enhancement of data processing capabilities, in the aforementioned heterogeneous network environment, it has become a common and widespread application scenario for mobile terminals to simultaneously carry out multiple service operations, including real-time audio and video, interactive services, and background synchronization. Therefore, enabling mobile terminals to switch channels between LTE, 5G NR, and Wi-Fi has become a necessary technical means to improve the stability of these various service operations.

[0004] In related technologies, mobile terminals need to measure the communication indicators of various communication channels in real time and switch the mobile terminal's communication channel to the one with better communication indicators to maintain the mobile terminal's data transmission operation. However, the above-mentioned technical solutions have obvious lag and therefore cannot meet the actual needs of mobile terminals to continuously and stably perform data transmission operations. Summary of the Invention

[0005] Based on the above technical problems, this application provides a predictive scheduling and reliable switching method for multi-channel communication of mobile terminals, which can overcome the technical defects of channel switching lag in related technologies; by switching the data transmission channel of the mobile terminal from the current channel to the target channel, the actual needs of the mobile terminal to stably perform data transmission operations can be met.

[0006] The technical solution provided in this application is as follows: This application provides a predictive scheduling and reliable handover method for multi-channel communication in a mobile terminal, including: The communication indicators of the kth communication channel in the communication channel set are collected according to a preset period to obtain the kth indicator set; where k is any integer greater than or equal to 1 and less than or equal to K, and K is greater than 1 and is used to characterize the number of communication channels in the communication channel set; Determine the probability distribution of the k-th state of the k-th index set; Based on the k-th conditional entropy of the k-th communication channel and the k-th state probability distribution, predict the risk of the k-th channel; The target channel is determined from the communication channel set based on the channel risk set; wherein, the channel risk set includes the risks of the first channel to the Kth channel. The data transmission channel of the mobile terminal is switched from the current channel to the target channel.

[0007] The predictive scheduling and reliable handover method for multi-channel communication in mobile terminals provided in this application has at least the following beneficial effects: The predictive scheduling and reliable handover method for multi-channel communication in mobile terminals provided in this application collects communication indicators of the k-th communication channel in a set of communication channels according to a preset period, obtaining a set of k-th indicators, where k is any integer greater than or equal to 1 and less than or equal to K, and K is greater than 1 and used to characterize the number of communication channels in the set of communication channels. This achieves continuous and traversal collection of communication indicators for each communication channel in the set of communication channels, improving the continuity and completeness of the data in the set of k-th indicators. Furthermore, after determining the probability distribution of the k-th state in the set of k-th indicators, the risk of the k-th channel is predicted based on the k-th conditional entropy and the probability distribution of the k-th state of the k-th communication channel, improving the correlation between the risk of the k-th channel and the k-th conditional entropy and the probability distribution of the k-th state, and improving the accuracy of the risk of the k-th channel. Further, compared to... Compared with the static communication channel switching decisions at the indicator level that involve thresholding or weighting network indicators and then sorting and switching them, the embodiments of this application can also predictively interpret and quantify the mutation risks and volatility in the communication channel set. Based on this, a target channel is determined from the communication channel set based on the channel risk set, which includes the risks of the first channel to the Kth channel. In this way, targeted screening of communication channels in the communication channel set is achieved, thereby enabling the prediction of the channel risks of communication channels in advance and the pre-switching of the data transmission channel of the mobile terminal based on the channel risks. This overcomes the technical defects of channel switching lag in the related technologies. On the other hand, switching the data transmission channel of the mobile terminal from the current channel to the target channel can meet the actual needs of the mobile terminal to stably perform data transmission operations. Attached Figure Description

[0008] Figure 1This is a flowchart illustrating the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in an embodiment of this application. Detailed Implementation

[0009] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0010] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0011] In practical applications, mobile terminals are easily placed in heterogeneous network environments, including Long Term Evolution (LTE), 5G NR, and Wi-Fi. The network conditions of these heterogeneous network environments usually exhibit strong time-varying and abrupt characteristics. For example, these heterogeneous network environments may suddenly experience changes such as hotspot congestion, sudden changes in base station load, sudden changes in interference, and mobility obstruction. These changes can easily lead to abnormal situations such as latency jitter, sudden changes in throughput, packet loss rate, surge in retransmission operations, or even short-term disconnection in communication channels or links.

[0012] Meanwhile, with the diversification of mobile terminal functions and the enhancement of data processing capabilities, in the aforementioned heterogeneous network environment, it has become a common and widespread application scenario for mobile terminals to simultaneously carry out multiple service operations, including real-time audio and video, interactive services, and background synchronization. Therefore, enabling mobile terminals to switch channels between LTE, 5G NR, and Wi-Fi has become a necessary technical means to improve the stability of these various service operations.

[0013] In related technologies, mobile terminals need to measure the communication indicators of various communication channels in real time and switch the mobile terminal's communication channel to the one with better indicators to maintain data transmission operations. In other words, these technologies follow a "use when the signal is good, switch again if the connection drops" strategy when switching communication channels. However, the above-mentioned technical solutions have significant lag and easily lead to frequent ping-pong switching by the mobile terminal, resulting in fluctuations in data transmission. Therefore, they cannot meet the actual need for mobile terminals to continuously and stably perform data transmission operations.

[0014] Based on the above technical problems, this application provides a predictive scheduling and reliable handover method for multi-channel communication of mobile terminals. Figure 1 This is a flowchart illustrating the predictive scheduling and reliable handover method for multi-channel communication in mobile terminals provided in an embodiment of this application. Figure 1 As shown, the method may include the following steps: Step 101: Collect the communication indicators of the kth communication channel in the communication channel set according to the preset period to obtain the kth indicator set.

[0015] Where k is any integer greater than or equal to 1 and less than or equal to K, and K is greater than 1 and is used to characterize the number of communication channels in the communication channel set.

[0016] In some embodiments, the preset period can be predetermined or adjusted; for example, the preset period may include the collection period for collecting communication indicators; for example, the value range of the collection period may be 100ms to 500ms, for example, the collection period may be 200ms by default.

[0017] In some embodiments, the number and type of metrics in the communication metrics can be preset or adjusted; for example, the communication metrics may include transmission latency (RTT_ms), throughput (Throughput_bps), and number of packet loss or retransmissions (loss_or_retrans).

[0018] For example, the transmission latency (RTT_ms) can be obtained by probes at the application layer or transport layer; for instance, it can be obtained by Quick User Datagram Protocol Internet Connections (QUIC) ping or HTTP HEAD; if QUIC ping or HTTP HEAD is unavailable, TCPconnect and TLS handshake times can be used to approximate the time.

[0019] For example, throughput (Throughput_bps) can be obtained by statistically analyzing the difference between the number of inbound bytes and the number of outbound bytes (bytes_in / out) per unit time.

[0020] For example, the number of packet loss or retransmissions (loss_or_retrans) can be obtained by counting the number of Transmission Control Protocol retransmissions (TCP retrans) or QUIC loss events. If the above two methods are not feasible, the failure rate can be used as an alternative.

[0021] In some embodiments, after acquiring communication metrics, a collection timestamp and a k-th channel identifier can be configured for the communication metrics to obtain a set of k-th metrics; wherein, the k-th channel identifier may include the number and / or name of the k-th communication channel.

[0022] Step 102: Determine the probability distribution of the k-th state in the k-th index set.

[0023] In some embodiments, the probability distribution of the k-th state can characterize the change state of various indicators in the set of k-th indicators within the time period corresponding to the time window; for example, the time window can be preset, and a single time window can be greater than or equal to 30 seconds and less than or equal to 60 seconds. In this case, the number of indicators for calculating the probability distribution of the k-th state can be determined according to the time window and the sampling interval.

[0024] For example, the state probability distribution of the i-th type of indicator in the k-th indicator set can be calculated as follows: According to the indicator threshold set, the indicator data of the i-th type in the k-th indicator set is discretized to obtain the channel state represented by the indicator data of the i-th type. Then, the above channel states are stored in a circular buffer, and the number of states of the above channel states is incremented. At the same time, the earliest time channel state is removed from the circular buffer, and the number of states corresponding to the removed channel state is decremented. Then, the channel states corresponding to the i-th type of indicator data in the circular buffer are statistically averaged to obtain the state probability distribution of the i-th type of indicator data. Specifically, the above state probability distribution can be calculated by equation (1): (1); in, Let i be the state probability distribution of the index data of the i-th type. For the state corresponding to the i-th type of indicator data, Let represent the number of index data of the i-th type in the k-th index set, where i is an integer greater than or equal to 1. The first expression in equation (1) can be used directly, and the second expression in equation (1) can be the implementation method of the probability smoothing of the first expression. The value can be , It can be a joint discrete state. The value of can be 27.

[0025] For example, the various types of indicators in the k-th indicator set can be traversed in the above manner to obtain the state probability distributions corresponding to each type of indicator, and then the various state probability distributions can be integrated according to the indicator type to obtain the k-th state probability distribution.

[0026] For example, in this embodiment, the quantile thresholds corresponding to the indicators of the communication channel during the stable period are used to discretize the corresponding type of indicator data. For instance, when the communication channel is in a stable period, the transmission delay, throughput, and number of packet loss or retransmissions of the communication channel can be statistically analyzed to determine the delay thresholds corresponding to the round-trip delay, including T_low=P30(T) and T_high=P60(T), the throughput thresholds corresponding to the throughput, including R_fast=P33(R) and R_slow=P66(R), and the bucket thresholds for determining the packet loss / retransmission rate P, which can be P_low=P50(P) and P_high=P80(P). For example, by combining the above thresholds, a joint discrete state can be obtained. Where T_bin∈{TL,TM,TH}, R_bin∈{F,N,S}, P_bin∈{L,M,H}, the number of states of the above joint discrete states is 27.

[0027] For example, the set of metric thresholds may include latency thresholds, throughput thresholds, and bucketing thresholds.

[0028] Specifically, for transmission delay T, if T is less than T_low, the discrete state corresponding to the transmission delay is TL; if T is greater than or equal to T_low and less than or equal to T_high, the discrete state corresponding to it is TM; if T is greater than or equal to T_high, the discrete state corresponding to it is TH. Meanwhile, for throughput R, if R is less than R_fast, the discrete state corresponding to it can be F; if R is greater than or equal to R_fast and less than R_slow, the discrete state corresponding to it can be N; if R is greater than or equal to R_slow, the discrete state corresponding to it can be S. For packet loss / retransmission P, if P is less than P < P_low, the discrete state corresponding to it can be L; if P is greater than or equal to P_low and less than P_high, the discrete state corresponding to it can be M; and if P is greater than or equal to P_high, the discrete state corresponding to it can be H.

[0029] Step 103: Based on the conditional entropy of the kth communication channel and the probability distribution of the kth state, predict the risk of the kth channel.

[0030] In some embodiments, the k-th conditional entropy can characterize the uncertainty or volatility of the communication state of the k-th communication channel.

[0031] Accordingly, the k-th conditional entropy can be determined as follows: establish the first-order state transition probability corresponding to the probability distribution of the k-th state, and then calculate the k-th conditional entropy by calculating the first-order state transition probability. Specifically, a state transition counter can be maintained. For example, whenever a new state is detected in the circular buffer, an increment operation is performed on the state transition counter corresponding to the new state. At the same time, in order to reduce the computational complexity, the exponential decay approximation can be used to calculate the k-th conditional entropy. That is, the count result of the state transition counter can be multiplied by 0.98, and then the new transition count can be added.

[0032] In some embodiments, the risk of the k-th channel can characterize the risk that the communication state of the k-th communication channel is in an unstable state for at least one future time period; for example, the risk of the k-th channel can be determined in the following manner: Based on the probability distribution of the k-th state, the k-th Jensen-Shannon Divergence (JSD) of the k-th communication channel is calculated. Then, the k-th JSD and the k-th conditional entropy are weighted and summed to obtain the channel risk of the k-th communication channel at the current time. The historical channel risk set corresponding to the k-th communication channel at at least one historical time is obtained. Then, in the time dimension, the changing trend of the historical channel risk set of the k-th communication channel and the k-th channel risk of the k-th communication channel at the current time is predicted to obtain the k-th channel risk.

[0033] Step 104: Determine the target channel from the communication channel set based on the channel risk set.

[0034] The channel risk set includes the risks of the first channel to the Kth channel.

[0035] In some embodiments, the number of communication channels in the target channel can be at least one; for example, if the mobile terminal supports split transmission or multipath transmission of its data transmission process, the number of communication channels in the target channel can be at least two. In this case, at least two communication channels can be selected as target channels in order of channel risk from low to high; for example, if the mobile terminal does not support split transmission or multipath transmission of its data transmission process, the number of communication channels in the target channel can be one. In this case, the target channel can be the communication channel with the lowest channel risk in the set of communication channels.

[0036] Step 105: Switch the data transmission channel of the mobile terminal from the current channel to the target channel.

[0037] As can be seen from the above, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application collects the communication indicators of the k-th communication channel in the communication channel set according to a preset period to obtain the k-th indicator set, where k is any integer greater than or equal to 1 and less than or equal to K, and K is greater than 1 and used to characterize the number of communication channels in the communication channel set. This achieves continuous and traversal collection of the communication indicators of each communication channel in the communication channel set, improving the continuity and completeness of the data in the k-th indicator set. Furthermore, after determining the k-th state probability distribution of the k-th indicator set, the risk of the k-th channel is predicted based on the k-th conditional entropy and the k-th state probability distribution of the k-th communication channel, improving the correlation between the risk of the k-th channel and the k-th conditional entropy and the k-th state probability distribution, and improving the accuracy of the risk of the k-th channel. Further, Compared to the static communication channel switching decisions at the indicator level in related technologies, which involve thresholding or weighting network indicators and then sorting and switching them, the embodiments of this application can also predictively interpret and quantify the mutation risks and volatility in the communication channel set. Based on this, a target channel is determined from the communication channel set based on a channel risk set, which includes risks from the first channel to the Kth channel. This achieves targeted screening of communication channels in the communication channel set, enabling the prediction of channel risks in advance and the pre-switching of the mobile terminal's data transmission channel based on these risks. This overcomes the technical defects of channel switching lag in related technologies. Furthermore, switching the mobile terminal's data transmission channel from the current channel to the target channel meets the actual needs of the mobile terminal for stable data transmission operations.

[0038] Based on the foregoing embodiments, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application, which predicts the risk of the k-th channel based on the k-th conditional entropy and the k-th state probability distribution of the k-th communication channel, can be achieved through the following steps: Step A1: Based on the k-th baseline distribution corresponding to the k-th state probability distribution, determine the k-th distribution drift index of the k-th communication channel.

[0039] In some embodiments, the k-th baseline distribution can be characterized by tracking and detecting various types of communication indicators of the k-th communication channel during the stable period, and by statistical averaging.

[0040] In some embodiments, the k-th distribution drift index can be the k-th JSD in the foregoing embodiments; for example, the k-th JSD It can be calculated using equation (2): (2); in, Let k be the probability distribution of the k-th state. , Let k be the k-th baseline distribution corresponding to the probability distribution of the k-th state.

[0041] Step A2: Process the k-th distribution drift index and the k-th conditional entropy to obtain the risk of the k-th channel.

[0042] In some embodiments, the risk of the k-th channel can be obtained in the following way: The risk of the k-th channel is obtained by weighted summation of the k-th distribution drift index and the k-th conditional entropy.

[0043] As can be seen from the above, in the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application embodiment, the k-th distribution drift index of the k-th communication channel is determined based on the k-th reference distribution corresponding to the k-th state probability distribution. In this way, the k-th distribution drift index can characterize the similarity between the k-th state probability distribution and the k-th reference distribution, thereby realizing the targeted quantification of the fluctuation state of the k-th communication channel characterized by the k-th state probability distribution. Furthermore, by processing the k-th distribution drift index and the k-th conditional entropy, the risk of the k-th channel is obtained, so that the risk of the k-th channel can comprehensively and accurately reflect the communication risk of the k-th communication channel from the dimensions of the fluctuation state and interference state of the k-th communication channel.

[0044] Based on the foregoing embodiments, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application, which processes the k-th distribution drift index and the k-th conditional entropy to obtain the k-th channel risk, can be achieved in the following way: Determine the k-th rate of change of the k-th distribution drift index; then, perform a weighted summation of the k-th distribution drift index, the k-th conditional entropy, and the k-th rate of change to obtain the risk of the k-th channel.

[0045] In some embodiments, the k-th rate of change may include the magnitude change of the k-th distribution drift index in the time dimension; for example, the k-th rate of change may include the difference between the k-th distribution drift index at time j and the distribution drift index at time j-1; where j is an integer greater than or equal to 1.

[0046] In some embodiments, the risk of the k-th channel can be calculated using equation (3): (3); in, For the risk of the k-th channel, Let k be the conditional entropy. Let be the k-th rate of change.

[0047] As can be seen from the above, in the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application embodiment, the k-th rate of change of the k-th distribution drift index is determined. Thus, the k-th rate of change can be used to finely characterize the magnitude and speed of change of the k-th distribution drift index. Furthermore, the k-th distribution drift index, the k-th conditional entropy, and the k-th rate of change are weighted and summed to obtain the k-th channel risk, which improves the comprehensiveness of the factors associated with the k-th channel risk, thereby improving the accuracy and comprehensiveness of the k-th channel risk.

[0048] Based on the foregoing embodiments, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application can also perform the following operations: If the kth communication channel is in the cold start period, or the kth communication channel is in the state of switching from the cold start period to the stable period, or the data volume of the kth indicator set is less than or equal to the quantity threshold, the kth baseline distribution is determined as the kth state probability distribution; If the k-th communication channel is in a stable period, the k-th baseline distribution and the k-th state probability distribution at the historical time are weighted and summed to obtain the k-th baseline distribution at the current time.

[0049] In some embodiments, the quantity threshold can be preset or adjusted, and this application embodiment does not limit this.

[0050] In some embodiments, when the k-th communication channel is in a cold start period, the mobile terminal may be prohibited from switching to the k-th communication channel if the k-th confidence level of the k-th communication channel is less than the confidence level threshold; for example, the confidence level threshold may be 0.6.

[0051] In some embodiments, after the k-th communication channel switches to the stable period, the index data of the k-th communication channel can be collected and statistically analyzed to obtain P_stable, which is then determined as the initial baseline distribution after the k-th communication channel switches to the stable period.

[0052] In some embodiments, the historical time can be the time before the current time, and may also include the time after the last channel switching was performed for the k-th communication channel; correspondingly, if the k-th communication channel is in a stable period, the k-th baseline distribution at the current time can be calculated by equation (4): (4); Where t is an integer greater than 1, used to represent the current time. Let k be the baseline distribution at the current time. , ) is the weight, It can be greater than or equal to 0.7 and less than or equal to 0.9; for example, its value can be 0.8. Let k be the baseline distribution at a historical moment.

[0053] As can be seen from the above, the predictive scheduling and reliable switching method for multi-channel communication of mobile terminals provided in this application provides multiple ways to determine the k-th benchmark distribution based on whether the k-th communication channel is in the cold start period and the size of the k-th index set. In this way, not only is the flexibility and robustness of the operation of determining the k-th benchmark distribution improved, but also the closed-loop update of the k-th benchmark distribution is realized.

[0054] Based on the foregoing embodiments, in the predictive scheduling and reliable switching method for multi-channel communication of mobile terminals provided in this application, the communication channel set includes the current channel.

[0055] Accordingly, determining the target channel from the communication channel set based on the channel risk set can be achieved through the following steps: Step B1: If the current channel meets the first condition, determine the candidate channel set from the communication channel set based on the penalty coefficient set and the cooldown period set of the communication channel set.

[0056] The first condition includes either the second or the third condition; The second condition includes: the current channel is in a high-risk state; the duration of the current channel being in a high-risk state is greater than or equal to the high-risk period threshold; the channel confidence level of the current channel is greater than or equal to the confidence threshold; and the current channel is not in a cooling-off period. The high-risk state is associated with the channel risk of the current channel. The third condition includes: the rate of change of the channel risk of the current channel is greater than or equal to the rate of change threshold, the average value of the channel risk of the current channel is greater than or equal to the channel risk threshold, the channel confidence level of the current channel is greater than or equal to the confidence level threshold, and the current channel is not in a cooling-off period.

[0057] Accordingly, if the current channel does not meet the first condition, the operation of determining the candidate channel set from the communication channel set can be skipped.

[0058] In some embodiments, the penalty coefficient Penalty in the penalty coefficient set can characterize the penalty value imposed on the channel quality of the corresponding communication channel; for example, the penalty coefficient can be preset or can vary with fluctuations in the channel quality or channel state of the communication channel.

[0059] In some embodiments, the cooldown corresponding to a cooldown period in the set of cooldown periods can characterize a period of time that the corresponding communication channel must wait after the last execution of a related channel operation; for example, the cooldown can be preset or can vary with the frequency of channel operations performed by the communication channel; for example, channel operations can include commit, rollback, and ping-pong for channel switching.

[0060] In some embodiments, the number of communication channels in the candidate channel set may be less than the number of communication channels in the communication channel set, and the candidate channel set may not include the current channel.

[0061] In some embodiments, a high-risk status may include any of the following: During the specified time period, the channel risk of the current channel remains greater than or equal to the high-risk threshold. Within a specified time period, the channel risk of the current channel is statistically averaged to obtain the risk statistics result, and the risk statistics result is greater than or equal to the high risk threshold.

[0062] In some embodiments, the high-risk threshold can be 0.65; the high-risk period threshold can be 5 seconds.

[0063] In some embodiments, the high-risk period threshold can be preset; correspondingly, the duration of the high-risk state is greater than or equal to the high-risk period threshold, which may include a specified period that is greater than or equal to the high-risk period threshold.

[0064] In some embodiments, channel confidence can be a quantitative score characterizing the reliability, trustworthiness, and stability of the current channel's communication status.

[0065] In some embodiments, the rate of change of channel risk may include the difference in channel risk between adjacent time points for the current channel.

[0066] In some embodiments, the rate of change threshold can be preset or adjusted.

[0067] In some embodiments, the average channel risk of the current channel is greater than or equal to the channel risk threshold, which may include a risk statistics result greater than or equal to the channel risk threshold; for example, the channel risk threshold may be 0.6.

[0068] In some embodiments, the candidate channel set can be determined in the following ways: The set of communication channels whose penalty coefficients are less than or equal to the penalty threshold and whose cooldown periods are less than or equal to the time period threshold are identified as the candidate channel set.

[0069] Step B2: Determine the channel score set of the candidate channel set.

[0070] Among them, the channel scores in the channel score set are used to characterize the communication stability of candidate channels.

[0071] In some embodiments, the score of the m-th channel in the candidate channel set can be determined in the following way: The m-th penalty coefficient and the m-th cooldown of the m-th channel are weighted and summed to obtain the score of the m-th channel. The scores of the first channel to the m-th channel are integrated according to the channel identifier to obtain the channel score set; where m is every integer greater than or equal to 1 and less than K; the channel identifier may include the number or name of the communication channel.

[0072] Step B3: Based on the channel score set, determine the target channel from the candidate channel set.

[0073] In some embodiments, at least one communication channel in the channel score set that is greater than or equal to a score threshold can be identified as the target channel.

[0074] As can be seen from the above, in the predictive scheduling and reliable switching method for multi-channel communication of mobile terminals provided in this application embodiment, if the current channel meets the second condition or the third condition, a candidate channel set is determined from the communication channel set. In this way, strict control is achieved over the operation of determining the candidate channel set. Furthermore, by means of the second condition or the third condition, a comprehensive judgment of multiple dimensions of the current channel is achieved. At the same time, determining the candidate channel set from the communication channel set based on the penalty coefficient set and the cooldown period set of the communication channel set can improve the reliability and switchability probability of the communication channels in the candidate channel set, thereby reducing the probability of rollback and ping-pong operations. On this basis, the target channel is determined from the candidate channel set based on the channel score set, narrowing the communication channel screening range of the target channel, thereby improving the screening efficiency of the target channel.

[0075] Based on the foregoing embodiments, in the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application, the channel score set for determining the candidate channel set can be achieved in the following way: Obtain the m-th candidate state; based on the m-th candidate state, the m-th penalty coefficient, and the m-th channel risk, determine the m-th channel score of the m-th candidate channel in the candidate channel set.

[0076] Wherein, the m-th candidate state includes the m-th stability score, the m-th capacity score, and the m-th penalty coefficient associated with the m-th candidate channel in the candidate channel set; the m-th stability score is associated with at least the transmission delay of the m-th candidate channel; the m-th capacity score is associated with the throughput of the m-th candidate channel; m is any integer greater than or equal to 1 and less than K.

[0077] In some embodiments, the m-th stability score may include the fluctuation state of the transmission delay of the m-th candidate channel within a specified time period; for example, the m-th stability score may be determined in any of the following ways: If the delay variation coefficient of the transmission delay of the m-th candidate channel cannot be obtained, then the m-th stability score is calculated using equation (5). : (5); in, This represents the standard deviation of the transmission delay.

[0078] If the time delay variation coefficient of the m-th candidate channel can be obtained, the m-th stability score can be calculated using equation (6): (6); in, Let be the time delay variation coefficient of the m-th candidate channel.

[0079] In some embodiments, the m-th capacity score can be calculated based on the throughput of the m-th candidate channel, as shown in equation (7): (7); in, For the m-th capacity score, The median throughput of the m-th candidate channel. Let m be the reference throughput of the m-th candidate channel.

[0080] In some embodiments, the score of the m-th channel can be determined in the following way: The m-th penalty coefficient is corrected to obtain the m-th corrected penalty value. Then, the m-th candidate state, the m-th corrected penalty value, and the m-th channel risk of the m-th candidate channel are weighted and summed to obtain the m-th channel score. Specifically, it can be shown in Equation (8): (8); in, For the m-th channel score, The m-th correction penalty value can be calculated using equation (9): (9); in, Let be the penalty coefficient for the m-th term.

[0081] As can be seen from the above, in the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application embodiment, the m-th stability score, m-th capacity score, and m-th penalty coefficient associated with the m-th candidate channel in the candidate channel set are obtained. The m-th stability score is at least associated with the transmission delay of the m-th candidate channel, and the m-th capacity score is associated with the throughput of the m-th candidate channel. Thus, through the m-th stability score, m-th capacity score, and m-th penalty coefficient, the characteristics of the m-th candidate channel can be comprehensively characterized from the dimensions of transmission delay, throughput, and penalty coefficient. On this basis, based on the m-th candidate state, m-th penalty coefficient, and m-th channel risk, including the m-th stability score, m-th capacity score, and m-th penalty coefficient, the m-th channel score is determined, which improves the correlation between the m-th channel score and the m-th candidate state, m-th penalty coefficient, and m-th channel risk, and improves the comprehensiveness and integration of the m-th channel score, thereby improving the accuracy of the m-th channel score.

[0082] Based on the foregoing embodiments, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application can also perform the following operations: Obtain the channel switching results for the target channel; If the channel switching result includes a commit, reduce the historical penalty coefficient to obtain the penalty coefficient for the target channel; If the channel switching result includes a rollback, or if the historical switching result indicates that at least two ping-pongs occurred within the target time period, the historical penalty coefficient is increased to obtain the penalty coefficient for the target channel.

[0083] In some embodiments, the channel switching result may include a successful switch (commit), a failed switch / rollback, and a ping-pong operation.

[0084] In some embodiments, the penalty coefficient of the target channel can be obtained in the following way: If the channel switching result is commit, the historical penalty coefficient of the target channel can be reduced using equation (10) to obtain the penalty coefficient of the target channel at the current moment: (10); Where t represents the current time, t-1 represents a historical time, and t is an integer greater than 1. The historical penalty coefficient, This represents the penalty coefficient for the target channel at the current moment.

[0085] If the channel switching result is a rollback, the historical penalty coefficient of the target channel can be increased using equation (11) to obtain the penalty coefficient of the target channel at the current moment: (11); For example, if the channel switching result is that at least two ping-pongs occur within the target time period, the historical penalty coefficient of the target channel can be increased using equation (12) to obtain the penalty coefficient of the target channel at the current time: (12); In some embodiments, the length of the target time period can be predetermined or adjusted; for example, the target time period can be 60 seconds.

[0086] In the embodiments of this application, after the channel switching operation for any communication channel in the communication channel set is completed, the historical penalty coefficient of any communication channel can be updated by the above method to obtain the penalty coefficient of any communication channel at the current moment.

[0087] As can be seen from the above, in the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application embodiment, the channel handover result of the target channel is obtained, and the historical penalty coefficient of the target channel is updated based on different channel handover results to obtain the penalty coefficient of the target channel. In this way, a targeted closed-loop update of the historical penalty coefficient of the target channel is realized, thereby improving the dynamics and accuracy of the penalty coefficient of the target channel, and also realizing diversified updates of the historical penalty coefficient of the target channel.

[0088] Based on the foregoing embodiments, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application, which determines the candidate channel set from the communication channel set based on the penalty coefficient set and the cooldown period set of the communication channel set, can be implemented in the following way: If the success rate of the linkup of the k-th communication channel is greater than or equal to the probability threshold, the current time is not in the k-th cooldown period corresponding to the k-th communication channel, and the k-th penalty coefficient is less than the penalty threshold, the k-th communication channel is determined as a candidate channel.

[0089] The set of penalty coefficients includes the kth penalty coefficient; the set of cooldown periods includes the kth cooldown period.

[0090] Accordingly, if the success rate of linkup for the k-th communication channel is less than the probability threshold, or the current time is not in the k-th cooldown period, or the k-th penalty coefficient is greater than or equal to the penalty coefficient, then the operation of identifying the k-th communication channel as a candidate channel can be omitted.

[0091] In some embodiments, the probability threshold can be predetermined or adjusted, and this application embodiment does not limit this; for example, the probability threshold can be 2 / 3.

[0092] In some embodiments, the penalty threshold can be predetermined or adjusted; for example, the penalty threshold can be 5.

[0093] In some embodiments, the k-th communication channel can be determined as a candidate channel in the following manner: If the success rate of linkup in the k-th communication channel is greater than or equal to the probability threshold, the current time is not in the k-th cooldown period corresponding to the k-th communication channel, and the k-th penalty coefficient is less than the penalty threshold, and the confidence level of the k-th communication channel is greater than or equal to 0.6, then the k-th communication channel can be identified as a candidate channel.

[0094] As can be seen from the above, in the predictive scheduling and reliable switching method for multi-channel communication of mobile terminals provided in this application embodiment, if the success rate of the linkup of the k-th communication channel is greater than or equal to the probability threshold, the current time is not in the k-th cooling period corresponding to the k-th communication channel, and the k-th penalty coefficient is less than the penalty threshold, the k-th communication channel is determined as a candidate channel. In this way, strict screening of the k-th communication channel is achieved, thereby increasing the probability that the communication status of the candidate channel can meet the data transmission requirements of the mobile terminal.

[0095] Based on the foregoing embodiments, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application can also perform the following operations: Obtain the channel switching result of the target channel; if the channel switching result indicates that the number of times the target channel was rolled back within the first time period is greater than or equal to the number threshold, determine the cooling period of the target channel as the minimum between twice the first cooling period and the second cooling period; if the channel switching result indicates that no rollback was executed within the second time period, determine the cooling period of the target channel based on the first cooling period and the third cooling period.

[0096] The first cooling period includes the historical cooling period of the target channel.

[0097] In some embodiments, the first cooling period may include the cooling period of the previous moment before the current moment, or the first cooling period may include the cooling period of the target channel after the previous channel operation ended.

[0098] In some embodiments, the second and third cooling periods can be predetermined or adjusted.

[0099] In some embodiments, the first time period and the second time period may be predetermined or adjusted.

[0100] Specifically, if the channel switching result indicates that the number of times the target channel rollback occurs within the first time period is greater than or equal to the number threshold, the cooling period of the target channel can be calculated using equation (13): (13); in, For the target channel's cooldown period, This is the first cooling-off period. This is the second cooling period, measured in seconds; correspondingly, the first period can be 60 seconds.

[0101] If the channel switching result indicates that no rollback was executed during the second time period, the cooldown period of the target channel can be determined using equation (14): (14); The third cooling period can be 15 seconds, and the second period can be 10 minutes.

[0102] It should be noted that the target channel can be any communication channel in the communication channel set. In this way, the cooldown of each communication channel in the communication channel set can be updated using the above method.

[0103] In summary, in the embodiments of this application, the mobile terminal can use a state machine to perform transactional switching of the communication channel; for example, the above state machine may include PRECHECK, PREWARM, MIGRATE, VERIFY, and COMMIT / ROLLBACK; wherein, PRECHECK is used to perform threshold and conflict checks, PREWARM is used to establish a linkup in the candidate channel entropy, MIGRATE is used to perform full migration or gradual migration, VERIFY is used to verify the linkup results, and is also used to determine the relationship between transmission delay and throughput and relevant thresholds, and COMMIT is used to perform communication channel switching. If the communication channel switching fails, ROLLBACK is performed to the original channel or the suboptimal channel, and the penalty coefficient and the cool-off period are recorded and updated.

[0104] For example, if the mobile terminal supports the function of splitting or multi-path transmission of data transmission services, it can select multiple communication channels as target channels from the candidate channel set according to the channel score, and adopt a progressive data transmission process migration according to the channel score. After each migration action, VERIFY is performed. If VERIFY fails, it will either rollback or degrade to the suboptimal channel to improve the handover success rate and reduce instantaneous jitter.

[0105] For example, a suboptimal channel may include at least one communication channel in the candidate channel set whose channel score is less than the highest channel score.

[0106] As can be seen from the above, the predictive scheduling and reliable handover method for multi-channel communication of mobile terminals provided in this application obtains the channel handover result of the target channel and determines how to update the cooldown period of the target channel based on the channel handover result. In this way, not only is a closed-loop update of the cooldown period of the target channel realized, improving the dynamism and accuracy of the cooldown period of the target channel; but also, targeted and diversified updates of the cooldown period of the target channel are realized, thereby improving the robustness of the cooldown period update operation.

[0107] In related technologies, the switching of communication channels of mobile terminals usually relies on pre-set static rules or priorities to make threshold judgments on the indicators of each communication channel. However, the technical solution provided in this application, after collecting the indicator sets of each communication channel in the communication channel set, discretizes and processes the indicator sets to obtain channel risk and channel score that can more accurately characterize the communication channel, realizing multi-dimensional and high-precision judgment of the communication status of the communication channel. At the same time, in related technologies, mobile terminals usually need to perform passive detection after the current communication channel is disconnected, or trigger the switching of the communication channel through timeout. However, this application can pre-execute the indicator collection, candidate channel selection and target channel determination operations of other communication channels when the current channel cannot meet the data transmission needs of the mobile terminal, thereby improving the stability of mobile terminal data transmission. On the other hand, in the embodiments of this application, by updating the penalty coefficient and cool-off period of each communication channel in a closed loop, the stability of the communication channel can be fully quantified.

[0108] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0109] The methods disclosed in the various method embodiments provided in this application can be arbitrarily combined to obtain new method embodiments without conflict.

[0110] The features disclosed in the various product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0111] The features disclosed in the various method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0112] It should be noted that the aforementioned computer-readable storage media can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM), etc.; or it can be various electronic devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0113] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0114] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0115] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware nodes. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0116] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0117] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0118] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0119] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A predictive scheduling and reliable handover method for multi-channel communication in a mobile terminal, characterized in that, include: The communication indicators of the kth communication channel in the communication channel set are collected according to a preset period to obtain the kth indicator set; where k is any integer greater than or equal to 1 and less than or equal to K, and K is greater than 1 and is used to characterize the number of communication channels in the communication channel set; Determine the probability distribution of the k-th state of the k-th index set; Based on the k-th conditional entropy of the k-th communication channel and the k-th state probability distribution, predict the risk of the k-th channel; The target channel is determined from the communication channel set based on the channel risk set; wherein, the channel risk set includes the risks of the first channel to the Kth channel. The data transmission channel of the mobile terminal is switched from the current channel to the target channel.

2. The method according to claim 1, characterized in that, The prediction of the risk of the k-th channel based on the k-th conditional entropy of the k-th communication channel and the k-th state probability distribution includes: Based on the k-th baseline distribution corresponding to the k-th state probability distribution, the k-th distribution drift index of the k-th communication channel is determined; The risk of the k-th channel is obtained by processing the k-th distribution drift index and the k-th conditional entropy.

3. The method according to claim 2, characterized in that, The process of processing the k-th distribution drift index and the k-th conditional entropy to obtain the k-th channel risk includes: Determine the k-th rate of change of the k-th distribution drift index; The risk of the k-th channel is obtained by weighted summation of the k-th distribution drift index, the k-th conditional entropy, and the k-th rate of change.

4. The method according to claim 2, characterized in that, The method further includes: If the kth communication channel is in the cold start period, or the kth communication channel is in the state of switching from the cold start period to the stable period, or the data volume of the kth indicator set is less than or equal to the quantity threshold, the kth baseline distribution is determined to be the kth state probability distribution; If the k-th communication channel remains in the stable period, the k-th baseline distribution and the k-th state probability distribution at the historical time are weighted and summed to obtain the k-th baseline distribution at the current time.

5. The method according to claim 1, characterized in that, The communication channel set includes the current channel; determining the target channel from the communication channel set based on the channel risk set includes: If the current channel satisfies the first condition, a candidate channel set is determined from the communication channel set based on the penalty coefficient set and the cooldown period set of the communication channel set; wherein, the first condition includes a second condition or a third condition; the second condition includes: The current channel is in a high-risk state, the duration of the current channel being in the high-risk state is greater than or equal to the high-risk period, the channel confidence level of the current channel is greater than or equal to the confidence level threshold, and the current channel is not in a cooling-off period; the high-risk state is associated with the channel risk of the current channel; The third condition includes: The current channel's channel risk change rate is greater than or equal to the change rate threshold, the current channel's channel risk average value is greater than or equal to the channel risk threshold, the current channel's channel confidence level is greater than or equal to the confidence threshold, and the current channel is not in the cooling-off period; Determine the channel score set of the candidate channel set; wherein the channel scores in the channel score set are used to characterize the communication stability of the candidate channels in the candidate channel set; The target channel is determined from the candidate channel set based on the channel score set.

6. The method according to claim 5, characterized in that, The set of channel scores for determining the candidate channel set includes: Obtain the m-th candidate state; wherein the m-th candidate state includes the m-th stability score, the m-th capacity score, and the m-th penalty coefficient associated with the m-th candidate channel in the candidate channel set; the m-th stability score is at least associated with the transmission delay of the m-th candidate channel; the m-th capacity score is associated with the throughput of the m-th candidate channel; m is any integer greater than or equal to 1 and less than K; Based on the m-th candidate state, the m-th penalty coefficient, and the m-th channel risk of the m-th candidate channel, the m-th channel score of the m-th candidate channel is determined.

7. The method according to claim 1 or 5, characterized in that, The method further includes: Obtain the channel switching result of the target channel; If the channel switching result includes commit, the historical penalty coefficient is reduced to obtain the penalty coefficient of the target channel; If the channel switching result includes a rollback, or the historical switching result indicates that at least two ping-pongs occurred within the target time period, the historical penalty coefficient is increased to obtain the penalty coefficient of the target channel.

8. The method according to claim 5, characterized in that, The process of determining a candidate channel set from the communication channel set based on the penalty coefficient set and the cooldown period set includes: If the success rate of the linkup of the k-th communication channel is greater than or equal to the probability threshold, the current time is not in the k-th cooldown period corresponding to the k-th communication channel, and the k-th penalty coefficient is less than the penalty threshold, the k-th communication channel is determined as a candidate channel; wherein, the penalty coefficient set includes the k-th penalty coefficient; and the cooldown period set includes the k-th cooldown period.

9. The method according to claim 5, characterized in that, The method further includes: Obtain the channel switching result of the target channel; If the channel switching result indicates that the number of times the target channel rollback occurs within the first time period is greater than or equal to the number threshold, the cooling period of the target channel is determined to be the minimum value between twice the first cooling period and the second cooling period; wherein, the first cooling period includes the historical cooling period of the target channel; If the channel switching result indicates that the rollback was not executed during the second time period, the cooling period of the target channel is determined based on the first cooling period and the third cooling period.

Images