An intelligent communication method and system integrating mobile communication and broadcast communication

Abstract

This invention belongs to the field of communication technology, specifically an intelligent communication method and system integrating mobile communication and broadcast communication, comprising the following steps: determining the activity time, dividing the activity time into at least two time periods, and dividing each time period into at least one communication cycle, denoted as cycle T. i Based on historical data analysis, a first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication is set for each period, denoted as A. Ti :B Ti :C; By setting a first spectrum resource allocation ratio for mobile communication, broadcast communication and reserved communication for each period, in any period, according to the corresponding first spectrum resource allocation ratio, it can be effectively ensured that the allocation of spectrum resources is relatively reasonable in any period, so as to meet the usage needs of mobile communication or broadcast communication.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, specifically an intelligent communication method and system that integrates mobile communication and broadcast communication. Background Technology

[0002] With the rapid development of technologies such as the Internet, the Internet of Things, and mobile communications, the number of mobile terminals on the network will increase, audiovisual media content will grow exponentially, and video services and network requirements will become increasingly diversified.

[0003] During large-scale events, the sheer number of users gathered and the limited local communication spectrum resources can lead to insufficient allocation of local communication spectrum resources to meet the needs of users' mobile and broadcast communications, resulting in a poor user experience. Furthermore, if an emergency occurs during the event, such as when weather deteriorates and an emergency evacuation of the audience is required, the large number of users may crowd out mobile communication spectrum resources, causing disruption to the audience's mobile communications. In addition, the unreasonable allocation of spectrum resources limits broadcast communication resources, hindering the rapid dissemination of notifications. Consequently, in the event of an emergency, spectrum resources cannot be effectively used for evacuation.

[0004] Therefore, the present invention provides an intelligent communication method and system that integrates mobile communication and broadcast communication. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by this invention to solve its technical problem is: an intelligent communication method integrating mobile communication and broadcast communication, comprising the following steps:

[0007] S1: Determine the activity time and divide the activity time into at least two time periods, and divide each time period into at least one communication cycle, denoted as cycle T. i , i = 1, 2, 3, ..., n;

[0008] S2: Based on historical data analysis, a first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication is set for each period, denoted as A. Ti :B Ti :C, and A Ti +B Ti +C = 1;

[0009] S3: Real-time monitoring and calculation of mobile communication demand R in each period A_Ti And based on the demand level R A_Ti Obtain the adjustment scaling factor α;

[0010] S4: Based on the adjustment scaling factor α, dynamically calculate the expected spectrum resource allocation ratio corresponding to mobile communication, and then determine the adjusted second spectrum resource allocation ratio, denoted as A. Ti_a :B Ti_a :C, and A Ti_a +B Ti_a +C = 1;

[0011] S5: When any period T i In the event of an emergency, the spectrum resource allocation ratio for reserved communication will be combined with the spectrum resource allocation ratio for broadcast communication, denoted as A. Ti_a :B Ti_a +C.

[0012] Preferably, the method for dividing each time period into at least one communication cycle is as follows:

[0013] Obtain a time period, divide the time period into segments based on a preset communication cycle length, and obtain at least one communication cycle corresponding to the time period;

[0014] Real-time monitoring of user numbers;

[0015] When the number of users exceeds the preset value, shorten the communication cycle length and increase the number of communication cycles;

[0016] When the number of users is lower than the preset value, the communication cycle length is extended and the number of communication cycles is reduced.

[0017] Preferably, the demand degree R of the mobile communication A_Ti The calculation method is as follows:

[0018] Get T i Total data volume D within the period t Total network capacity G t Actual network throughput N t Maximum network throughput N max Number of dropped calls (T) t Total number of sessions T t_a ;

[0019] According to the formula:

[0020]

[0021] T is calculated based on the formula. i Periodic mobile communication demand R A_Ti Among them, w1, w2, and w3 are weighting factors, and w1+w2+w3=1, which are allocated according to the importance of data traffic, user density, and service quality.

[0022] Preferably, the method for calculating the adjustment scaling factor α is as follows:

[0023] Demand R for mobile communication A_Ti ;

[0024] According to the formula:

[0025]

[0026] The adjustment scaling factor α is calculated according to the formula, where R A_max For T i Baseline demand level within the cycle.

[0027] Preferably, the method for adjusting the second spectrum resource allocation ratio is as follows:

[0028] Obtain the adjustment scaling factor α;

[0029] According to the formula:

[0030] A Ti_a =A Ti ×α

[0031] B Ti_a =B Ti +A Ti ×(1-α)

[0032] The second spectrum resource allocation ratio A is calculated according to the formula. Ti_a :B Ti_a :C.

[0033] Preferably, the method for adjusting the second spectrum resource allocation ratio further includes:

[0034] Get T i Average video latency (VE) of broadcast communication within a period t_mean 1. Preset minimum video delay VE t_min 1. Preset maximum video delay VE t_max ;

[0035] According to the formula:

[0036]

[0037] Based on the formula, T is calculated. i The video latency index J of the period Ti ;

[0038] With video latency index J Ti Compare with the threshold θ:

[0039] When the video latency index J Ti If it is less than the threshold θ, then:

[0040] A Ti_a =ATi ×α

[0041] B Ti_a =B Ti +A Ti ×(1-α)

[0042] When the video latency index J Ti If it is greater than or equal to the threshold θ, then:

[0043] A Ti_a =min(A Ti ×α,A Ti )

[0044]

[0045] The video latency index J is calculated according to the formula. Ti Second spectrum resource allocation ratio A under the influence Ti_a :B Ti_a :C.

[0046] Preferably, S2 further includes:

[0047] To ensure that periods belonging to the same time period are matched with the same first spectrum resource allocation ratio;

[0048] The allocation ratio of the first spectrum resources in the next cycle will be determined at the end of the current cycle and will be automatically applied at the start of the next cycle.

[0049] Preferably, the method for setting the first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication for each period based on historical data analysis is as follows:

[0050] Collect historical activity data, including activity type, number of users, and activity duration;

[0051] The collected historical activity data is cleaned and preprocessed;

[0052] Machine learning algorithms are used to establish a model of the relationship between activity data and communication needs;

[0053] The model is trained using historical data, and the model parameters are adjusted to minimize the prediction error.

[0054] Based on activity data, communication demand is predicted using a relational model to determine the first spectrum resource allocation ratio.

[0055] Preferably, the machine learning algorithm includes one or more combinations of time series analysis, random forest algorithm, machine learning algorithm such as linear regression, neural network or support vector machine.

[0056] Preferably, an intelligent communication system integrating mobile communication and broadcast communication includes:

[0057] The dynamic spectrum adjustment module is used to monitor the spectrum usage of mobile and broadcast communications and dynamically adjust the spectrum allocation according to network traffic and user demand.

[0058] The spectrum sensing and allocation module, based on spectrum sensing technology, identifies spectrum resources below the utilization threshold and allocates them to services with high demand.

[0059] The emergency response coordination module identifies emergency situations and coordinates the allocation of spectrum resources for mobile and broadcast communications to ensure the efficient dissemination of critical information.

[0060] The beneficial effects of the present invention are as follows:

[0061] 1. The intelligent communication method and system integrating mobile communication and broadcast communication described in this invention sets a first spectrum resource allocation ratio for mobile communication, broadcast communication and reserved communication for each period. In any period, according to the corresponding first spectrum resource allocation ratio, the allocation of spectrum resources can be effectively guaranteed to be relatively reasonable in any period, meeting the usage needs of mobile communication or broadcast communication. Then, by obtaining the demand of mobile communication in any period, an adjustment ratio factor is calculated, and the spectrum resource allocation ratio is dynamically adjusted according to the adjustment ratio factor, so that the demand of mobile communication and broadcast communication can be met in any period, thereby improving the utilization rate of limited spectrum resources.

[0062] 2. The intelligent communication method and system integrating mobile communication and broadcast communication described in this invention calculates the demand degree R of mobile communication. A_Ti Then, use the demand degree R A_Ti The adjustment ratio α is calculated by comparing it with the baseline demand. Based on the ratio α, the updated second spectrum resource allocation ratio can be obtained. This allows for dynamic adjustment of the pre-set spectrum resource allocation ratio in each cycle to meet the needs of mobile communication and avoid affecting the user experience due to reduced service quality. Attached Figure Description

[0063] The invention will now be further described with reference to the accompanying drawings.

[0064] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0065] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0066] like Figure 1As shown in the figure, an intelligent communication method integrating mobile communication and broadcast communication according to an embodiment of the present invention includes the following steps:

[0067] S1: Determine the activity time and divide the activity time into at least two time periods, and divide each time period into at least one communication cycle, denoted as cycle T. i , i = 1, 2, 3, ..., n;

[0068] S2: Based on historical data analysis, a first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication is set for each period, denoted as A. Ti :B Ti :C, and A Ti +B Ti +C = 1;

[0069] S3: Real-time monitoring and calculation of mobile communication demand R in each period A_Ti And based on the demand level R A_Ti Obtain the adjustment scaling factor α;

[0070] S4: Based on the adjustment scaling factor α, dynamically calculate the expected spectrum resource allocation ratio corresponding to mobile communication, and then determine the adjusted second spectrum resource allocation ratio, denoted as A. Ti_a :B Ti_a :C, and A Ti_a +B Ti_a +C = 1;

[0071] S5: When any period T i In the event of an emergency, the spectrum resource allocation ratio for reserved communication will be combined with the spectrum resource allocation ratio for broadcast communication, denoted as A. Ti_a :B Ti_a +C.

[0072] During large-scale events, the sheer number of users gathered and the limited local communication spectrum resources can lead to insufficient allocation of local communication spectrum resources to meet the needs of users' mobile and broadcast communications, resulting in a poor user experience. Furthermore, if an emergency occurs during the event, such as when weather deteriorates and an emergency evacuation of the audience is required, the large number of users may crowd out mobile communication spectrum resources, causing disruption to the audience's mobile communications. In addition, the unreasonable allocation of spectrum resources limits broadcast communication resources, making it difficult to quickly disseminate notifications. Consequently, in the event of an emergency, spectrum resources cannot be effectively used for evacuation.

[0073] Based on the above, in one embodiment of the present invention, mobile communication refers to networks that provide communication services to mobile devices, such as 2G, 3G, 4G, and 5G, supporting functions such as voice calls, SMS, and data transmission; broadcast communication refers to networks used by television stations or streaming media services for unidirectional transmission of video content to a large number of users, supporting live video streaming and on-demand video, characterized by broadcast transmission, that is, sending the same content from one source to multiple receivers; the activity time is divided into layers according to time period-cycle, and a first spectrum resource allocation ratio is set for each cycle for mobile communication, broadcast communication, and reserved communication. In any cycle, according to the corresponding first spectrum resource allocation ratio, it can be effectively ensured that the allocation of spectrum resources is relatively reasonable in any cycle, meeting the usage needs of mobile communication or broadcast communication. Furthermore, since mobile communication is more efficient in each cycle, the network provides more efficient communication services. The first spectrum resource allocation ratio for mobile communication and broadcast communication is a preset value, so it needs to be dynamically adjusted according to the real-time situation. That is, in one embodiment, the adjustment ratio factor is calculated by obtaining the demand of mobile communication in any period, and then the spectrum resource allocation ratio is dynamically adjusted according to the adjustment ratio factor so that the demand of mobile communication and broadcast communication in any period can be met, thereby improving the utilization rate of limited spectrum resources. In addition, it should be noted that in order to deal with the emergency situation and spread the emergency to all viewers as soon as possible, a reserved communication is also set in one embodiment of the present invention. When the existence of an emergency is detected, the spectrum resource allocation ratio of the reserved communication can be merged with the spectrum resource allocation ratio of the broadcast communication, thereby rapidly increasing the spectrum resources of the broadcast communication and ensuring that the emergency information can be quickly and widely conveyed to all viewers.

[0074] It is understandable that:

[0075] Taking large-scale sporting events as an example, the event preparation phase, the event itself, and the event conclusion phase are defined as time periods. Each time period is further divided into cycles. Based on historical data analysis, the spectrum resource allocation ratios for mobile communication, broadcast communication, and reserved communication are set as follows:

[0076] During the event preparation phase: the spectrum resource allocation ratio for mobile communication, broadcast communication, and reserved communication is 0.5:0.3:0.2;

[0077] During the competition phase: the spectrum resource allocation ratio for mobile communication, broadcast communication, and reserved communication is 0.3:0.5:0.2;

[0078] In the final stage of the competition: the spectrum resource allocation ratio for mobile communication, broadcast communication, and reserved communication is 0.5:0.3:0.2;

[0079] In the event of an unforeseen incident during the event preparation phase: the spectrum resource allocation ratio for mobile communication and broadcast communication is 0.5:0.5;

[0080] In the event of an emergency during the competition: the spectrum resource allocation ratio for mobile communication and broadcast communication is 0.3:0.7;

[0081] In the event of an unforeseen incident at the end of the competition: the spectrum resource allocation ratio for mobile communication and broadcast communication is 0.5:0.5;

[0082] It can be observed that during the event preparation phase, broadcast communication does not require a large amount of spectrum resources for live streaming, so its proportion is relatively small. However, during the event itself, broadcast communication is required for live streaming, and to ensure the quality of the broadcast, its proportion is relatively high. Furthermore, in any stage, if an emergency occurs, the spectrum resources reserved for communication will be merged with those for broadcast communication immediately. The aim is to quickly increase the proportion of spectrum resources allocated to broadcast communication, thereby rapidly disseminating notifications to address the emergency and ensure that users can respond in an orderly manner.

[0083] Based on the above, the spectrum resource allocation ratio for mobile communication, broadcast communication, and reserved communication is defined as the first spectrum resource allocation ratio, which is a preset value obtained from historical data analysis. Since the actual spectrum resource allocation ratio actually occupied by broadcast communication may differ from the preset first spectrum resource allocation ratio during actual application, the first spectrum resource allocation ratio is dynamically adjusted by obtaining the real-time demand of mobile communication in actual application to improve the user experience and increase the utilization rate of limited spectrum resources.

[0084] In one embodiment, the method for dividing each time period into at least one communication cycle is as follows:

[0085] Obtain a time period, divide the time period into segments based on a preset communication cycle length, and obtain at least one communication cycle corresponding to the time period;

[0086] Real-time monitoring of user numbers;

[0087] When the number of users exceeds the preset value, shorten the communication cycle length and increase the number of communication cycles;

[0088] When the number of users is lower than the preset value, the communication cycle length is extended and the number of communication cycles is reduced.

[0089] By dynamically adjusting the number of communication cycles in each time period, the aim is to allocate spectrum resources more effectively to adapt to changes in the number of users during different time periods. Taking large-scale sporting events as an example, time periods can be divided into the event preparation phase, the event itself, and the event conclusion phase. Within each phase, further subdivisions can be made based on time. For instance, during the event itself, a preset communication cycle of 15 minutes can be used to ensure at least one communication cycle. This allows for providing more communication resources when user demand is high and conserving resources when demand is low. When the number of users exceeds a preset value, the communication cycle length can be shortened to increase the number of communication cycles, reducing the waiting time for each user's allocated communication resources, thereby improving communication service quality and reducing call drops or data transmission delays. When the number of users is below a preset value, the communication cycle length can be extended to reduce the number of communication cycles, reducing the frequency of network switching and management, lowering network operating costs, and maintaining network efficiency. Through real-time monitoring and dynamic adjustment, the goal is to quickly respond to changes in the number of users caused by unforeseen events (such as large-scale events or emergencies) and ensure the stable operation of the communication network.

[0090] In one embodiment, the demand degree R of the mobile communication A_Ti The calculation method is as follows:

[0091] Get T i Total data volume D within the period t Total network capacity G t Actual network throughput N t Maximum network throughput N max Number of dropped calls (T) t Total number of sessions T t_a ;

[0092] According to the formula:

[0093]

[0094] T is calculated based on the formula. i Periodic mobile communication demand R A_Ti Among them, w1, w2, and w3 are weighting factors, and w1+w2+w3=1, which are allocated according to the importance of data traffic, user density, and service quality.

[0095] To address the communication demands of large-scale sporting events, given the limited spectrum resources available, a pre-set spectrum allocation ratio may lead to a shortage or waste of spectrum resources for mobile or broadcast communication during actual application. Therefore, dynamic adjustments based on the actual situation are necessary. In one embodiment of this invention, taking the spectrum allocation ratio for mobile communication as an example, during practical application, data is acquired, and the demand level of a communication network is calculated based on the data. This demand level can be used to characterize the demand for T... i Does the proportion of spectrum resources for mobile communication need to be adjusted within the cycle? It is worth noting, in particular, the calculated demand level R. A_Ti It needs to be compared with the pre-set baseline demand level. If the real-time demand level R... A_Ti If the demand exceeds the baseline, then mobile communication in T should be increased. i The spectrum resource allocation ratio within a period is adjusted accordingly, and vice versa.

[0096] In addition, it should be noted that w1, w2, and w3 are weighting factors, and are allocated according to the importance of data traffic, user density, and service quality. The weighting factors are based on a hierarchical model, and the relative importance of data traffic, user density, and service quality is determined by pairwise comparisons, and the weights are obtained accordingly.

[0097] In one embodiment, the method for calculating the adjustment scaling factor α is as follows:

[0098] Demand R for mobile communication A_Ti ;

[0099] According to the formula:

[0100]

[0101] The adjustment scaling factor α is calculated according to the formula, where R A_max For T i Baseline demand level within the cycle.

[0102] Based on the above, since the pre-set spectrum resource allocation ratio for each cycle may not meet the demand in practical applications, leading to a decrease in the quality of service for mobile communication, it is also necessary to acquire real-time data and obtain the corresponding demand level R for mobile communication based on the real-time data. A_Ti In one embodiment of the present invention, the demand level R corresponding to mobile communication is calculated based on the real-time data obtained above. A_Ti Then, use the demand degree R A_TiThe adjustment ratio α is calculated by comparing it with the baseline demand. Based on the ratio α, the updated second spectrum resource allocation ratio can be obtained. This allows for dynamic adjustment of the pre-set spectrum resource allocation ratio in each period to meet the needs of mobile communication, avoid service quality degradation, experience loss, and waste of spectrum resources.

[0103] The baseline demand level is derived from historical data. By acquiring historical data and analyzing the demand for mobile communications within that data, the average value is calculated and used as the baseline demand level.

[0104] In one embodiment, the method for adjusting the second spectrum resource allocation ratio is as follows:

[0105] Obtain the adjustment scaling factor α;

[0106] According to the formula:

[0107] A Ti_a =A Ti ×α

[0108] B Ti_a =B Ti +A Ti ×(1-α)

[0109] The second spectrum resource allocation ratio A is calculated according to the formula. Ti_a :B Ti_a :C.

[0110] Since spectrum resources are preset values ​​for each period, but in actual applications, the allocation ratio will not be exactly the same as the preset ratio. There may be times when mobile communication requires a larger proportion of spectrum resources, meaning that in any period T... i Within, the demand for mobile communication R A_Ti Greater than in the period T i Based on the baseline demand level, in one embodiment of the present invention, it is also necessary to dynamically adjust the spectrum resource allocation ratio by combining the adjustment ratio factor α calculated from real-time data to meet the demand; exemplary:

[0111] For example, in any period T i The first spectrum resource allocation ratio is: 0.5:0.3:0.2;

[0112] The calculated adjustment factor α = 0.8 means that the demand for mobile communication R... A_Ti Less than the preset baseline demand level R in this cycle A_max Therefore, it can be understood that there is a waste of spectrum resources for mobile communication during this period;

[0113] Based on the above, the following can be calculated using the formula:

[0114] A Ti_a =0.5 × 0.8 = 0.4

[0115] B Ti_a =0.3 + 0.5 × (1 - 0.8) = 0.4

[0116] Based on the above, since mobile communication in any period T i Within this context, there is a waste of spectrum resources. Therefore, the second spectrum resource allocation ratio calculated according to the above formula can realize the dynamic adjustment of spectrum resources, so that the spectrum resource allocation ratio is updated from 0.5:0.3:0.2 to 0.4:0.4:0.2.

[0117] It is worth noting that since reserved communication is for emergency situations, it generally remains unchanged, with adjustments only made between the spectrum resources corresponding to mobile communication and broadcast communication; when the adjustment ratio factor α < 1, the demand degree R of mobile communication... A_Ti Less than the preset baseline demand level R in this cycle A_max This suggests that there is a waste of spectrum resources for mobile communication during this period. Based on this, the additional spectrum resources for mobile communication can be allocated to broadcast communication to expand the audience and reduce live broadcast latency. Conversely, when the scaling factor α > 1, the demand for mobile communication R... A_Ti Greater than the preset baseline demand level R in this period A_max Therefore, it can be understood that if the spectrum resources of mobile communication do not meet the demand during this period, then some spectrum resources of broadcast communication need to be allocated to mobile communication in order to meet the spectrum resource demand of mobile communication.

[0118] In one embodiment, the method for adjusting the second spectrum resource allocation ratio further includes:

[0119] Get T i Average video latency (VE) of broadcast communication within a period t_mean 1. Preset minimum video delay VE t_min 1. Preset maximum video delay VE t_max ;

[0120] According to the formula:

[0121]

[0122] Based on the formula, T is calculated. i The video latency index J of the period Ti ;

[0123] With video latency index J Ti Compare with the threshold θ:

[0124] When the video latency index J Ti If it is less than the threshold θ, then:

[0125] A Ti_a =A Ti ×α

[0126] B Ti_a =B Ti +A Ti ×(1-α)

[0127] When the video latency index J Ti If it is greater than or equal to the threshold θ, then:

[0128] A Ti_a =min(A Ti ×α,A Ti )

[0129]

[0130] The video latency index J is calculated according to the formula. Ti Second spectrum resource allocation ratio A under the influence Ti_a :B Ti_a :C.

[0131] In practical applications, if the scaling factor α > 1, it indicates that the demand level R corresponding to mobile communication, calculated based on real-time data, is increasing. A_Ti Greater than the period T i The baseline demand level R within A_max That is, in the period T i Within the country, mobile communication spectrum resources need to account for a larger proportion. Based on the above, if the scaling factor α is adjusted to 1.2;

[0132] Then, according to the formula, we can calculate:

[0133] A Ti_a =0.5 × 1.2 = 0.6

[0134] B Ti_a =0.3 + 0.5 × (1 - 1.2) = 0.2

[0135] Based on the calculation results of the above formula, the second spectrum resource allocation ratio can be expressed as: 0.6:0.2:0.2;

[0136] However, in practical applications, although each cycle T iWithin the spectrum resource allocation system, the allocation ratio can be dynamically adjusted. However, if the spectrum resource allocation ratio for mobile communication continuously increases, it will inevitably lead to a continuous decrease in the spectrum resources for broadcast communication, thereby affecting the live broadcast content, such as causing stuttering or latency. Therefore, in one embodiment of this invention, the adjustment ratio factor α for mobile communication cannot be directly calculated using a formula to prevent the continuous decrease in the spectrum resource ratio for broadcast communication from causing stuttering in live broadcast content. In one embodiment, it is also necessary to calculate the video latency index J for broadcast communication. Ti Based on the video latency index J Ti The expression can determine whether broadcast communication has been affected by mobile communication; the threshold θ is obtained based on historical data, specifically, the threshold θ for real-time activities is determined based on similar activity types, activity levels and the number of users;

[0137] Exemplary, when the video latency index J Ti If the value is less than the threshold θ, it indicates that there is still room for adjustment of the spectrum resources for broadcast communication, which can be calculated using the following formula;

[0138] A Ti_a =0.5 × 1.2 = 0.6

[0139] B Ti_a =0.3 + 0.5 × (1 - 1.2) = 0.2

[0140] When the video latency index J Ti If the value is greater than or equal to the threshold θ, it indicates that the spectrum resources for broadcast communication are already relatively scarce. Based on this, the following formula is used for calculation:

[0141] A Ti_a =min(0.5×1.2,0.5)=0.5

[0142] B Ti_a =max(0.3+0.5×(1-1.2)×0.05,0.3)=max(0.295,0.3)

[0143] Based on the above calculations, we obtain A. Ti_a =0.5, while B Ti_a =0.3;

[0144] In other words, in this period T i Inside, although the demand for mobile communication R A_Ti Greater than the period T i The baseline demand level R within A_maxHowever, increasing the proportion of spectrum resources allocated to mobile communications would affect broadcast communications, specifically causing live video buffering and noticeable delays, thus impacting the viewing experience for live audiences. Therefore, based on the formula above, maintaining the spectrum allocation within this period T... i The allocation ratio of spectrum resources within the region remains unchanged; furthermore, it is worth noting that... A value less than 1 is used to reduce the impact on the proportion of spectrum resources corresponding to broadcast communications, in any period T. i If an emergency occurs, the demand for mobile communication will inevitably increase. Therefore, if no control measures are taken, the spectrum resources of broadcast communication will be occupied, causing the broadcast communication channels to be blocked, which will lead to video stuttering or high latency. Based on the above formula, even if an emergency occurs, the spectrum resources of broadcast communication will not be occupied. In the event of an emergency, the service quality of broadcast communication can be effectively guaranteed, thereby ensuring that the emergency can be responded to in an orderly manner.

[0145] In one embodiment, S2 further includes:

[0146] To ensure that periods belonging to the same time period are matched with the same first spectrum resource allocation ratio;

[0147] The allocation ratio of the first spectrum resources in the next cycle will be determined at the end of the current cycle and will be automatically applied at the start of the next cycle.

[0148] In one embodiment, the method for setting the first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication for each period based on historical data analysis is as follows:

[0149] Collect historical activity data, including activity type, number of users, and activity duration;

[0150] The collected historical activity data is cleaned and preprocessed;

[0151] Machine learning algorithms are used to establish a model of the relationship between activity data and communication needs;

[0152] The model is trained using historical data, and the model parameters are adjusted to minimize the prediction error.

[0153] Based on activity data, communication demand is predicted using a relational model to determine the first spectrum resource allocation ratio.

[0154] In one embodiment of the present invention, historical activity data, including activity type, activity level, number of users, and activity time, is acquired. Based on this historical activity data, a relationship model between activity data and communication demand is constructed. The activity type can be understood as sports, public welfare, performing arts, etc., while the activity level is determined according to the popularity of the specific activity. The number of users and the activity time are obtained statistically. Based on the relationship model established above, communication demand can be predicted for real-time activities, and then the corresponding first spectrum resource allocation ratio can be output. The first spectrum resource allocation ratio is expressed differently according to different periods. Therefore, the relationship model can also output the first spectrum resource allocation ratio corresponding to different time periods based on the input activity type, activity level, and real-time number of users and activity time.

[0155] Exemplary:

[0156] Data was collected from 100 events of different types and levels over the past year, including: event type (sports, charity, performing arts), number of users (number of users participating in the event), and event time (date and time).

[0157] Clean the data, remove invalid and erroneous data, and perform one-hot encoding on activity types, for example:

[0158] Sports: [1,0,0]

[0159] Public Welfare: [0,1,0]

[0160] Entertainment: [0,0,1]

[0161] Standardize the number of users and the duration of the event.

[0162] The Random Forest algorithm was chosen as the prediction model, with features including one-hot encoding of activity type, number of users, and activity time. The dataset was divided into a training set (80%) and a validation set (20%). The Random Forest parameters were set as follows: number of trees: 100, tree depth: unlimited, minimum number of samples per leaf node: 10, and mean squared error (MSE) was used as the loss function. The optimal parameter combination was found through grid search. The model performance was evaluated on the validation set, and the parameter combination with the smallest MSE was selected.

[0163] Predict the communication needs of upcoming events using optimal models;

[0164] For example: There is an upcoming large-scale sporting event with an event type of [1,0,0], an estimated number of users of 10,000, and an event duration of 3 hours;

[0165] Input features into the model to predict communication needs;

[0166] Assuming historical data shows that the baseline spectrum resource allocation ratio for similar activity types is 0.5 for mobile communications, 0.4 for broadcast communications, and 0.1 for reserved communications.

[0167] The model predicts that the communication demand for real-time activities is 20% higher than the baseline demand.

[0168] Calculate the adjusted initial allocation ratio: mobile communication is adjusted to 0.5*(1-0.2)=0.4, broadcast communication is adjusted to 0.4(1+0.2)=0.5, and reserved communication is 0.1.

[0169] In one embodiment, the machine learning algorithm includes time series analysis, random forest algorithm, machine learning algorithms such as linear regression, neural network or support vector machine, or one or more combinations thereof.

[0170] In one embodiment, an intelligent communication system integrating mobile communication and broadcast communication includes:

[0171] The dynamic spectrum adjustment module is used to monitor the spectrum usage of mobile and broadcast communications and dynamically adjust the spectrum allocation according to network traffic and user demand.

[0172] The spectrum sensing and allocation module, based on spectrum sensing technology, identifies spectrum resources below the utilization threshold and allocates them to services with high demand.

[0173] The emergency response coordination module identifies emergency situations and coordinates the allocation of spectrum resources for mobile and broadcast communications to ensure the efficient dissemination of critical information.

[0174] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart communication method integrating mobile communication and broadcast communication, characterized in that, Includes the following steps: S1: Determine the activity time and divide the activity time into at least two time periods, and divide each time period into at least one communication cycle, denoted as cycle T. i , i = 1, 2, 3, ..., n; S2: Based on historical data analysis, a first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication is set for each period, denoted as A. Ti :B Ti :C, and A Ti +B Ti +C = 1; S3: Real-time monitoring and calculation of mobile communication demand R in each period A_Ti And based on the demand level R A_Ti Obtain the adjustment scaling factor α; S4: Based on the adjustment scaling factor α, dynamically calculate the expected spectrum resource allocation ratio corresponding to mobile communication, and then determine the adjusted second spectrum resource allocation ratio, denoted as A. Ti_a :B Ti_a :C, and A Ti_a +B Ti_a +C = 1; S5: When any period T i In the event of an emergency, the spectrum resource allocation ratio for reserved communication will be combined with the spectrum resource allocation ratio for broadcast communication, denoted as A. Ti_a :B Ti_a +C; The demand for mobile communication R A_Ti The calculation method is as follows: Get T i Total data volume D within the period t Total network capacity G t Actual network throughput N t Maximum network throughput N max Number of dropped calls (T) t Total number of sessions T t_a ; According to the formula: T is calculated based on the formula. i Periodic mobile communication demand R A_Ti Among them, w1, w2, and w3 are weighting factors, and w1+w2+w3=1, which are allocated according to the importance of data traffic, user density, and service quality. The method for calculating the adjustment scaling factor α is as follows: Demand R for mobile communication A_Ti ; According to the formula: The adjustment scaling factor α is calculated according to the formula, where R A_max For T i Baseline demand level within the cycle; The method for adjusting the second spectrum resource allocation ratio is as follows: Obtain the adjustment scaling factor α; According to the formula: A Ti_a =A Ti ×α B Ti_a =B Ti +A Ti ×(1-a) The second spectrum resource allocation ratio A is calculated according to the formula. Ti_a :B Ti_a :C; The method for adjusting the second spectrum resource allocation ratio also includes: Get T i Average video latency (VE) of broadcast communication within a period t_mean 1. Preset minimum video delay VE t_min 1. Preset maximum video delay VE t_max ; According to the formula: Based on the formula, T is calculated. i The video latency index J of the period Ti ; With video latency index J Ti Compare with the threshold θ: When the video latency index J Ti If it is less than the threshold θ, then: A Ti_a =A Ti ×α B Ti_a =B Ti +A Ti ×(1-a) When the video latency index J Ti If it is greater than or equal to the threshold θ, then: IN Ti_a =min(A Ti ×α,A Ti ) The video latency index J is calculated according to the formula. Ti Second spectrum resource allocation ratio A under the influence Ti_a :B Ti_a :C.

2. The intelligent communication method integrating mobile communication and broadcast communication according to claim 1, characterized in that: The method for dividing each time period into at least one communication cycle is as follows: Obtain a time period, divide the time period into segments based on a preset communication cycle length, and obtain at least one communication cycle corresponding to the time period; Real-time monitoring of user numbers; When the number of users exceeds the preset value, shorten the communication cycle length and increase the number of communication cycles; When the number of users is lower than the preset value, the communication cycle length is extended and the number of communication cycles is reduced.

3. The intelligent communication method integrating mobile communication and broadcast communication according to claim 1, characterized in that: S2 further includes: To ensure that periods belonging to the same time period are matched with the same first spectrum resource allocation ratio; The allocation ratio of the first spectrum resources in the next cycle will be determined at the end of the current cycle and will be automatically applied at the start of the next cycle.

4. The intelligent communication method integrating mobile communication and broadcast communication according to claim 1, characterized in that: The method for setting the first spectrum resource allocation ratio corresponding to mobile communication, broadcast communication, and reserved communication for each period based on historical data analysis is as follows: Collect historical activity data, including activity type, number of users, and activity duration; The collected historical activity data is cleaned and preprocessed; Machine learning algorithms are used to establish a model of the relationship between activity data and communication needs; The model is trained using historical data, and the model parameters are adjusted to minimize the prediction error. Based on activity data, communication demand is predicted using a relational model to determine the first spectrum resource allocation ratio.

5. The intelligent communication method integrating mobile communication and broadcast communication according to claim 4, characterized in that: The machine learning algorithms include one or more combinations of time series analysis, random forest algorithm, machine learning algorithms such as linear regression, neural network or support vector machine.

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