Multi-communication module fusion transmission method

Abstract

The invention discloses a multi-communication module fusion transmission method, which comprises the following steps that: firstly, a main control module analyzes downlink data issued by an upper computer and determines a service type to which the downlink data belongs; meanwhile, the main control module can collect various transmission quality indexes of each communication module, so as to evaluate the signal quality score of each communication module. Then, the main control module can select a corresponding communication module and a corresponding transmission frequency band to transmit the received downlink data according to a set decision rule in combination with the service type of the downlink data and the signal quality score of each communication module. And finally, based on the selected transmission frequency band and the service type, through the constructed joint optimization model, distributing transmission power of each communication module used for transmitting downlink data. Therefore, the network coverage range is expanded, the coverage blind area is reduced, the repeated construction is reduced, the resource waste is avoided, and the seamless connection requirement of the mobile traffic of the terminal between the networks is met.

Description

Technical Field

[0001] The present invention relates to a technical field specifically applicable to wireless communication networks, and in particular to a multi-communication module fusion transmission method. Background Art

[0002] With the rapid development of communication technology, 5G and Wi-Fi 6, as the most advanced mobile communication technologies and wireless local area network technologies, each possesses significant advantages. However, when the two independently transmit signals, problems such as incomplete signal coverage, resource waste, and mutual interference may occur. Therefore, how to effectively integrate 5G and Wi-Fi 6 signals for communication transmission has become a technical challenge that needs to be solved. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention proposes a multi-communication module fusion transmission method that can integrate multiple different communication modules for communication transmission. The specific technical solution is as follows:

[0004] In a first aspect, a multi-communication module fusion transmission method is provided. In a first possible implementation of the first aspect, the method includes:

[0005] The main control module parses the received downlink data, determines the service type corresponding to the downlink data, and evaluates the signal quality score of each communication module based on the corresponding transmission quality index;

[0006] Determining the communication module and transmission frequency band corresponding to the downlink data according to a set decision rule based on the service type and the signal quality score of each communication module;

[0007] According to the transmission frequency band and service type corresponding to the downlink data, the transmission power of the downlink data is allocated through a joint optimization model.

[0008] In combination with the first implementable manner of the first aspect, in a second implementable manner of the first aspect, evaluating the signal quality score of the communication module according to the corresponding transmission quality indicator includes:

[0009] The transmission quality indicators corresponding to the communication module are obtained, and the signal quality score of the communication module is calculated by a weighted algorithm in combination with the indicator weights corresponding to the transmission quality indicators.

[0010] In combination with the first implementable manner of the first aspect, in a third implementable manner of the first aspect, determining the communication module and transmission frequency band corresponding to the downlink data according to a set decision rule includes:

[0011] Determine the score difference threshold of each communication module under different transmission frequency bands according to the service type;

[0012] The score difference of each communication module is calculated, and the score difference is compared with the score difference threshold, and the communication module and transmission frequency band corresponding to the downlink data are selected according to the comparison result.

[0013] In combination with the first implementable manner of the first aspect, in a fourth implementable manner of the first aspect, allocating the transmission power of the downlink data through a joint optimization model includes:

[0014] Determine the weight of each service quality indicator corresponding to the downlink data according to the service type;

[0015] Determining a total transmission power and a spectrum bandwidth by using a transmission frequency band corresponding to the downlink data, and determining an optimization constraint condition based on the total transmission power and the spectrum bandwidth;

[0016] Based on the weights of the various quality of service indicators and the optimization constraints, the transmission power of the downlink data is obtained by solving a set objective function.

[0017] In conjunction with the first possible implementation of the first aspect, a fifth possible implementation of the first aspect further includes:

[0018] The occupancy of the spectrum to which the transmission frequency band corresponding to the downlink data belongs is analyzed, and a subcarrier set corresponding to the downlink data is allocated using a greedy algorithm.

[0019] In combination with the first possible implementation of the first aspect, a sixth possible implementation of the first aspect further includes:

[0020] Evaluate the signal quality score of each communication module in real time based on the corresponding transmission quality indicators, and calculate the score difference between the communication module corresponding to the downlink data and other communication modules;

[0021] Count the average score differences between the communication module corresponding to the downlink data and other communication modules within the set time window, and compare the average score difference corresponding to each communication module with the trigger threshold;

[0022] In response to the average score difference being greater than a trigger threshold, the main control module is triggered to switch the transmission frequency band of the downlink data.

[0023] In combination with the sixth implementation manner of the first aspect, in a seventh implementation manner of the first aspect, the main control module switches the transmission frequency band of the downlink data, including:

[0024] Constructing a state space based on the signal quality score, interference intensity, and temperature state of the communication module corresponding to the downlink data, and constructing an action space based on the selectable frequency band corresponding to the communication module;

[0025] According to the state space and the action space, a Q learning algorithm is adopted based on a set reward function to adjust the transmission frequency band corresponding to the downlink data.

[0026] In a second aspect, a multi-communication module fusion transmission method is provided. In a first possible implementation of the second aspect, the method includes:

[0027] The main control module parses the received uplink data and determines the service type corresponding to the uplink data;

[0028] Obtain the operating parameters of different communication modules in real time, and evaluate the signal quality score of each communication module based on the corresponding operating parameters;

[0029] The transmission mode corresponding to the uplink data is determined according to the signal quality score of each communication module, and the corresponding fusion strategy is generated and sent to the mixer according to the transmission mode.

[0030] In conjunction with the first implementable manner of the second aspect, in a second implementable manner of the second aspect, evaluating the signal quality score of the communication module according to the corresponding operating condition parameters includes:

[0031] Normalizing each of the operating parameters, and setting parameter weights corresponding to each of the operating parameters according to the entropy weight method;

[0032] Combining the normalized processing results and parameter weights corresponding to the operating condition parameters, a weighted algorithm is used to calculate the signal quality score of the communication module.

[0033] In combination with the first possible implementation of the second aspect, a third possible implementation of the second aspect further includes:

[0034] When the fusion strategy is multi-mode concurrent transmission, the mixer encapsulates the uplink data uploaded by each communication module into the same coding format and fragments the uplink data after the unified coding format;

[0035] A hierarchical modulation method is used to map the sliced data corresponding to each communication module to the transmission frequency band corresponding to the issued fusion strategy;

[0036] Determine the link weight according to the real-time channel status of each communication module, and use the weighted polling method to allocate the corresponding data transmission volume of each communication module based on the link weight;

[0037] The protocol conversion is performed on the fragmented data corresponding to each communication module, and the fragmented data corresponding to each communication module is integrated into a unified data stream and uploaded to the host computer according to the allocated data transmission volume.

[0038] Beneficial effects: The multi-communication module fusion transmission method of the present invention can utilize various communication modules for fusion transmission, thereby expanding network coverage, reducing coverage blind spots, reducing duplicate construction and avoiding resource waste, and meeting the seamless connection requirements of terminals for moving traffic between networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the specific embodiments of the present invention, the following briefly introduces the drawings required for use in the specific embodiments. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0040] Figure 1 A flowchart of a multi-communication module integrated transmission method for downlink data provided by one embodiment of the present invention;

[0041] Figure 2 This is a flowchart of a multi-communication module fusion transmission method for uplink data provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are therefore only examples and are not intended to limit the scope of protection of the present invention.

[0043] like Figure 1 The flowchart of the multi-communication module fusion transmission method shown in FIG. 1 includes:

[0044] Step 1: The main control module parses the received downlink data, determines the service type corresponding to the downlink data, and evaluates the signal quality score of each communication module based on the corresponding transmission quality index;

[0045] Step 2: Determine the communication module and transmission frequency band corresponding to the downlink data based on the service type and the signal quality score of each communication module according to the set decision rules;

[0046] Step 3: Allocate the transmission power of the downlink data through a joint optimization model according to the transmission frequency band and service type corresponding to the downlink data.

[0047] Specifically, first, the main control module can parse the downlink data sent by the upper computer to determine the service type of the downlink data, such as voice service, video service or file transfer service. At the same time, the main control module can collect various transmission quality indicators of each communication module to evaluate the signal quality score of each communication module. Then, the main control module can combine the service type of the downlink data and the signal quality score of each communication module, and select the corresponding communication module and transmission frequency band to transmit the received downlink data according to the set decision rules. Finally, based on the selected transmission frequency band and service type, the transmission power of each communication module used to transmit downlink data is allocated through the constructed joint optimization model. This will expand the network coverage, reduce coverage blind spots, reduce duplicate construction and avoid waste of resources, and meet the seamless connection requirements of terminals moving traffic between networks.

[0048] The following will use 5G communication modules and WiFi6 communication modules as examples.

[0049] In this embodiment, optionally, in step 1, evaluating the signal quality score of the communication module according to the corresponding transmission quality indicator includes:

[0050] The transmission quality indicators corresponding to the communication module are obtained, and the signal quality score of the communication module is calculated by a weighted algorithm in combination with the indicator weights corresponding to the transmission quality indicators.

[0051] Specifically, taking the 5G communication module and WiFi6 communication module as examples, the main control module can evaluate the signal quality score of the 5G communication module based on transmission quality indicators such as signal-to-noise ratio, bit error rate, and spectrum efficiency. The specific calculation formula is as follows:

[0052]

[0053] Among them, SNR 5G BER 5G 、SE 5G They are the signal-to-noise ratio, bit error rate, spectrum efficiency, and SNR of the 5G communication module. max The maximum signal-to-noise ratio and BER of the 5G communication module max 、SE max are the maximum bit error rate and maximum spectrum efficiency of the 5G communication module, respectively. α1, α2, and α3 are the indicator weights corresponding to the signal-to-noise ratio, bit error rate, and spectrum efficiency of the 5G communication module, respectively.

[0054] The main control module can also evaluate the signal quality score of the WiFi6 communication module based on channel occupancy, signal reception strength, and multi-user efficiency. The specific calculation formula is as follows:

[0055]

[0056] Among them, COR, RSSI WiFi , MUE are the channel occupancy rate, signal reception strength and multi-user efficiency of the WiFi6 communication module respectively. RSSI max 、MUE max They are the maximum signal reception strength and multi-user efficiency upper limit of the WiFi6 communication module, respectively. β1, β2, and β3 are the indicator weights corresponding to the channel occupancy rate, signal reception strength, and multi-user efficiency of the WiFi6 communication module, respectively.

[0057] In this embodiment, optionally, in step 2, determining the communication module and transmission frequency band corresponding to the downlink data according to a set decision rule includes:

[0058] Determine the score difference threshold of each communication module under different transmission frequency bands according to the service type;

[0059] The score difference of each communication module is calculated, and the score difference is compared with the score difference threshold, and the communication module and transmission frequency band corresponding to the downlink data are selected according to the comparison result.

[0060] Specifically, different service types have different QoS requirements, that is, different service quality requirements, and different score difference thresholds need to be set for different service types. For example, for urgent low-latency services, such as VR services or AR services, the score difference threshold between the 5G communication module and the WiFi6 communication module can be set to 0.2. After calculating the signal quality scores of the 5G communication module and the WiFi6 communication module, the score difference between the 5G communication module and the WiFi6 communication module can be calculated. If the score difference between the 5G communication module and the WiFi6 communication module is greater than 0.2, that is, Q 5G -Q WiFi >Δ1, Δ1=0.2, the millimeter wave band of the 5G communication module is preferentially selected to transmit downlink data. Otherwise, the Sub-6GHz band of the 5G communication module and the 6GHz band of the WiFi6 communication module are selected to transmit urgent low-latency downlink data in a fusion manner.

[0061] For high-throughput services, such as 4K video, the score difference threshold is set to 0.15. WiFi -Q 5G > Δ2, Δ2 = 0.2, the 160MHz band of the WiFi6 communication module is preferred for downlink data transmission. Otherwise, the high-throughput downlink data transmission is combined with the C-band of the 5G communication module and the 80MHz band of the WiFi6 communication module. For ordinary services, the communication module with the highest score can be selected for downlink data transmission.

[0062] In this embodiment, optionally, in step 3, allocating the transmission power of the downlink data by using a joint optimization model includes:

[0063] Determine the weight of each service quality indicator corresponding to the downlink data according to the service type;

[0064] Determining a total transmission power and a spectrum bandwidth by using a transmission frequency band corresponding to the downlink data, and determining an optimization constraint condition based on the total transmission power and the spectrum bandwidth;

[0065] Based on the weights of the various quality of service indicators and the optimization constraints, the transmission power of the downlink data is obtained by solving a set objective function.

[0066] Specifically, since the service quality indicator weights for downlink data of different business types are also different, it is first necessary to determine the weights of the various service quality indicators corresponding to the downlink data based on the business type of the downlink data received by the main control module. In this embodiment, the weights of the various service quality indicators corresponding to the downlink data can be set according to the following table.

[0067] Business Type <![CDATA[Weight assignment (w delay , w throughput , w reliability ) <!-- 4 -->]]> Real-time voice (0.6,0.2,0.2) Video Stream (0.3,0.5,0.2) File Transfer (0.1,0.7,0.2)

[0068] Among them, w delay ,w throughput ,w reliability They represent delay weight, throughput weight and reliability weight respectively.

[0069] Then, the total transmission power and spectrum bandwidth can be determined based on the transmission frequency band corresponding to the downlink data, and optimization constraints can be set based on the total transmission power and spectrum bandwidth. In this embodiment, the constraints can be set as follows:

[0070]

[0071] Among them, P i 、P total are the transmission power and total transmission power corresponding to downlink data, B i 、B total They are the transmission spectrum bandwidth and total spectrum bandwidth corresponding to downlink data respectively.

[0072] Finally, based on the constructed objective function and the set constraints, the Lagrange multiplier method can be used to solve the constrained optimization problem. The objective function is specifically:

[0073]

[0074] Among them, D i 、T i and BER i are respectively the delay, throughput and bit error rate of the i-th service, Tmax is the maximum throughput, and M is the number of services in the system.

[0075] By solving the above objective function, we can obtain the transmission power and transmission frequency band corresponding to all downlink data received by the main control module under the condition of maximizing U. Then, we can determine the power allocation ratio of each downlink data according to the transmission power and transmission frequency band, and thus allocate the transmission power of each downlink data. The specific calculation formula of the power allocation ratio is as follows:

[0076]

[0077] Among them, P i 、P j is the optimal allocated power for the i-th and g-th services, N0 is the noise power spectrum density, h i is the channel gain of service i.

[0078] In this embodiment, optionally, the following is further included:

[0079] The occupancy of the spectrum to which the transmission frequency band corresponding to the downlink data belongs is analyzed, and a subcarrier set corresponding to the downlink data is allocated using a greedy algorithm.

[0080] Specifically, the communication module may be subject to other interference when transmitting data. Therefore, the main control module can also analyze the occupancy of the spectrum of the transmission frequency band corresponding to the downlink data through Fourier transform. The specific analysis formula is as follows:

[0081]

[0082] Among them, S(t0) is the time domain signal, and I(f) is the frequency domain interference energy distribution.

[0083] Then, a greedy algorithm can be used to allocate the subcarrier set corresponding to the downlink data. The specific allocation method is as follows:

[0084] First, the transmission frequency band corresponding to the downlink data is divided into N subcarriers, and the width of each subcarrier is Δf. Then, the subcarrier set S(u) with the least interference can be allocated to the downlink data. The subcarriers satisfy:

[0085]

[0086] Furthermore, the number of subcarriers in the subcarrier set needs to not exceed N.

[0087] In this embodiment, optionally, the following is further included:

[0088] Evaluate the signal quality score of each communication module in real time based on the corresponding transmission quality indicators, and calculate the score difference between the communication module corresponding to the downlink data and other communication modules;

[0089] Count the average score differences between the communication module corresponding to the downlink data and other communication modules within the set time window, and compare the average score difference corresponding to each communication module with the trigger threshold;

[0090] In response to the average score difference being greater than a trigger threshold, the main control module is triggered to switch the transmission frequency band of the downlink data.

[0091] Specifically, during the data transmission process of the communication module, the main control module can monitor the various transmission quality indicators of each communication module in real time, and use this to evaluate the signal quality score of each communication module in real time. The main control module can calculate the score difference between the communication module currently transmitting data and other communication modules in real time, and calculate the average score difference in a specified time window. Taking the 5G communication module and the WiFi6 communication module as an example, the specific calculation formula for the average score difference is as follows:

[0092]

[0093] E is the number of sampling points in the time window.

[0094] The average score difference is compared with the set trigger threshold. If it exceeds the trigger threshold, the main control module is triggered to switch the transmission frequency band corresponding to the downlink data.

[0095] Band switching allows users to select higher-scoring bands to improve the system's signal-to-noise ratio and bit error rate, ensuring data transmission stability. It also helps mitigate interference and improve transmission efficiency. Some services can also be migrated to less-loaded bands, dynamically allocating bandwidth resources and avoiding network congestion. While meeting service needs, it switches to highly energy-efficient bands to extend device battery life, and adaptively selects the optimal band in the current environment to ensure seamless connectivity.

[0096] In this embodiment, optionally, the main control module switches the transmission frequency band of the downlink data, including:

[0097] Constructing a state space based on the signal quality score, interference intensity, and temperature state of the communication module corresponding to the downlink data, and constructing an action space based on the selectable frequency band corresponding to the communication module;

[0098] According to the state space and the action space, a Q learning algorithm is adopted based on a set reward function to adjust the transmission frequency band corresponding to the downlink data.

[0099] Specifically, when a frequency band switch is triggered, the main control module can construct a state space based on the signal quality score, interference intensity, and temperature status of the communication module corresponding to the downlink data, and construct an action space based on the selectable frequency band corresponding to the transmission module. Finally, based on the state space and action space, the Q learning algorithm is used to adjust the transmission frequency band corresponding to the downlink data based on the set reward function. The reward function is specifically:

[0100] R=α·S norm -β·I-γ·T norm ;

[0101] Among them, S norm and T norm are the normalized signal quality score and device temperature status, respectively. I is α, β, and γ are the corresponding adjustment coefficients.

[0102] like Figure 2 The flowchart of the multi-communication module fusion transmission method shown in FIG. 1 includes:

[0103] Step S1: The main control module parses the received uplink data and determines the service type corresponding to the uplink data;

[0104] Step S2: Acquire the operating parameters of different communication modules in real time, and evaluate the signal quality score of each communication module based on the corresponding operating parameters;

[0105] Step S3: Determine the transmission mode corresponding to the uplink data according to the signal quality score of each communication module, and generate a corresponding fusion strategy according to the transmission mode and send it to the mixer.

[0106] Specifically, first, the main control module parses the received uplink data to determine the service type corresponding to the uplink data. Then, the main control module obtains the real-time operating parameters of the 5G communication module and WiFi6 communication module, such as temperature, voltage, bit error rate, channel occupancy rate, etc., and scores the signal quality of the 5G communication module and WiFi6 communication module based on all the acquired operating parameters to obtain the corresponding signal quality scores of the 5G communication module and WiFi6 communication module. Finally, the main control module determines whether to activate the dual-mode concurrent transmission mode based on the signal quality scores of the 5G communication module and WiFi6 communication module. If activated, the corresponding fusion strategy is sent to the mixer, and the uplink data received by the 5G communication module and WiFi6 communication module are integrated into a unified data stream through the mixer, and transmitted to the host computer through the PHY module.

[0107] In this embodiment, optionally, evaluating the signal quality score of the communication module according to corresponding operating condition parameters includes:

[0108] Normalizing each of the operating parameters, and setting parameter weights corresponding to each of the operating parameters according to the entropy weight method;

[0109] Combining the normalized processing results and parameter weights corresponding to the operating condition parameters, a weighted algorithm is used to calculate the signal quality score of the communication module.

[0110] Specifically, by perceiving environmental status and business needs in real time and dynamically adjusting the parameter weights of various working conditions, precise resource allocation can be achieved to match the dynamic environment with diverse business needs, achieve a balance between performance and stability, and improve the robustness of the system and service continuity in complex scenarios.

[0111] Specifically, since the dimensions of different operating parameters are different, the main control module needs to normalize the various operating parameters after receiving them from each communication module. The specific calculation formula is as follows:

[0112]

[0113] Where T is the temperature of the communication module, T min 、T max are the minimum and maximum temperatures of the communication module, σ v is the standard deviation of voltage fluctuation in the last 10 seconds.

[0114] At the same time, the main control module uses the entropy weight method to dynamically assign parameter weights to various working condition parameters based on the information entropy of the collected working condition parameters. The specific calculation formula is as follows:

[0115]

[0116] Among them, x ij is the signal quality score of service i on frequency band J, and n is the number of data points in the sampling window

[0117] Finally, the comprehensive signal quality scores of the 5G communication module and the WiFi6 communication module can be calculated based on the normalized results and parameter weights corresponding to each working condition parameter. The specific calculation formula is as follows:

[0118] S score =w T ·T norm +w v ·V score +w s ·S norm ;

[0119] Among them, T norm 、V score They are the normalized results corresponding to temperature and voltage, S normis the signal quality of the communication module, w T 、w v and w s The parameter weights corresponding to temperature, voltage, and signal quality are as follows:

[0120]

[0121] In this embodiment, optionally, the following is further included:

[0122] When the fusion strategy is multi-mode concurrent transmission, the mixer encapsulates the uplink data uploaded by each communication module into the same coding format and fragments the uplink data after the unified coding format;

[0123] A hierarchical modulation method is used to map the sliced data corresponding to each communication module to the transmission frequency band corresponding to the issued fusion strategy;

[0124] Determine the link weight according to the real-time channel status of each communication module, and use the weighted polling method to allocate the corresponding data transmission volume of each communication module based on the link weight;

[0125] The protocol conversion is performed on the fragmented data corresponding to each communication module, and the fragmented data corresponding to each communication module is integrated into a unified data stream and uploaded to the host computer according to the allocated data transmission volume.

[0126] Specifically, after the main control module calculates the signal quality scores of the 5G communication module and the WiFi6 communication module, it can determine whether to start the dual-mode concurrent transmission mode based on the signal quality scores of the 5G communication module and the WiFi6 communication module. Specifically, when |S score 95G)-S score When (WiFi)|≤Δ, Δ is the set threshold, generally set to 0.2, and the dual-mode concurrent transmission mode is started to upload uplink data.

[0127] When using dual-mode concurrent transmission mode, first, the mixer can encapsulate the 5GNR protocol data unit (PDU) in the uplink data uploaded by the 5G communication module into a unified transmission frame (UTF). The specific encapsulation method is as follows:

[0128] UTE 5G =[Header(4B)]+[Payload(L 5G )]+[FCS(2B)].

[0129] Among them, Header (4B) represents the header of the data frame, Payload (L 5G) represents the effective load, that is, the data content actually transmitted, FCS (2B) represents the frame check sequence, which is used to detect errors in data transmission, L 5G 5G MAC layer data packet length.

[0130] At the same time, the 802.11ax MAC frame in the uplink data uploaded by the WiFi6 communication module is converted into UTF format. The specific conversion relationship is as follows:

[0131] UTE WiFi =[Header(4B)]+[Payload(L WiFi )]+[QoS label (1B)]+[FCS (2B)];

[0132] Among them, Payload(L WiFi ) indicates that L WiFi It is WiFi6MTU.

[0133] The mixer slices the uplink data after unified coding format. WiFi ≠L 5G When the mixer performs dynamic slicing, the slicing size is set to L WiFi , L 5G and S max The minimum value in S max This is the Ethernet MTU limit. The fragment numbering rules are as follows:

[0134]

[0135] Wherein, NB is the original data packet sequence number corresponding to the fragment data, and ΔF is the fragment offset.

[0136] Then, the mixer uses a hierarchical modulation method to map the sliced data corresponding to each communication module to the communication frequency band included in the issued fusion strategy. Specifically, the delay error between the OFDM symbols of the sliced data corresponding to the 5G communication module and the OFDMA symbols of the sliced data corresponding to the WiFi6 communication module is first calculated, and the delay error is compensated by the interpolation filter. The specific calculation formula for the delay error is as follows:

[0137]

[0138] in, is the symbol time of the 5G communication module, that is, the duration of a single OFDM symbol in the 5G signal. It is the symbol time of the WiFi communication module, that is, the duration of a single OFDM symbol in the WiFi signal.

[0139] Then, for high-priority fragmented data, such as control signaling, QPSK is used to map it to the 5G band included in the fusion strategy, and low-priority data, such as background traffic, is mapped to the WiFi6 band using 256-QAM.

[0140] Afterwards, the mixer can determine the link weight based on the real-time channel status of each communication module, and use a weighted polling method to allocate the corresponding data transmission volume of each communication module based on the link weight. Specifically, the mixer first calculates the link weight based on the real-time channel status of the 5G communication module and the WiFi6 communication module. The specific calculation formula is as follows:

[0141]

[0142] Among them, B k 、D k 、J k and SNR k are the available bandwidth, current link delay, interference intensity and signal-to-noise ratio of communication module k respectively.

[0143] The mixer then uses a weighted round-robin method to allocate the amount of data transmitted per cycle between the 5G communication module and the WiFi6 communication module. The data allocation ratio is:

[0144]

[0145] The amount of data allocated by the communication module per cycle is:

[0146]

[0147] Among them, ρ k , Q total is the data allocation ratio corresponding to the communication module and the length of the queue for uplink data to be sent, τ is the time decay constant, T cuur The current time is used to mark the moment of resource allocation, scheduling or status update, and calculate the time interval. The time of the last operation of service k, used to record the historical interaction time of service k and to calculate waiting time or priority. In fair scheduling, users who have not been scheduled for a long time will be given priority in allocating resources.

[0148] Finally, the mixer can perform protocol conversion on the fragmented data corresponding to each communication module, and integrate the fragmented data corresponding to each communication module into a unified data stream and upload it to the host computer according to the allocated data transmission volume. The protocol mapping table between 5G and WiFi6 is as follows:

[0149]

[0150] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A multi-communication module fusion transmission method, characterized in that: include: The main control module parses the received downlink data, determines the service type corresponding to the downlink data, and evaluates the signal quality score of each communication module based on the corresponding transmission quality index; Determining the communication module and transmission frequency band corresponding to the downlink data according to a set decision rule based on the service type and the signal quality score of each communication module; According to the transmission frequency band and service type corresponding to the downlink data, the transmission power of the downlink data is allocated through a joint optimization model.

2. The multi-communication module fusion transmission method according to claim 1, characterized in that: Evaluate the signal quality score of the communication module based on the corresponding transmission quality indicators, including: The transmission quality indicators corresponding to the communication module are obtained, and the signal quality score of the communication module is calculated by a weighted algorithm in combination with the indicator weights corresponding to the transmission quality indicators.

3. The multi-communication module fusion transmission method according to claim 1, characterized in that: Determining the communication module and transmission frequency band corresponding to the downlink data according to a set decision rule includes: Determine the score difference threshold of each communication module under different transmission frequency bands according to the service type; The score difference of each communication module is calculated, and the score difference is compared with the score difference threshold, and the communication module and transmission frequency band corresponding to the downlink data are selected according to the comparison result.

4. The multi-communication module fusion transmission method according to claim 1, characterized in that: Allocating the transmission power of the downlink data through a joint optimization model includes: Determine the weight of each service quality indicator corresponding to the downlink data according to the service type; Determining a total transmission power and a spectrum bandwidth by using a transmission frequency band corresponding to the downlink data, and determining an optimization constraint condition based on the total transmission power and the spectrum bandwidth; Based on the weights of the various quality of service indicators and the optimization constraints, the transmission power of the downlink data is obtained by solving a set objective function.

5. The multi-communication module fusion transmission method according to claim 1, characterized in that: Also includes: The occupancy of the spectrum to which the transmission frequency band corresponding to the downlink data belongs is analyzed, and a subcarrier set corresponding to the downlink data is allocated using a greedy algorithm.

6. The multi-communication module fusion transmission method according to claim 1, characterized in that: Also includes: Evaluate the signal quality score of each communication module in real time based on the corresponding transmission quality indicators, and calculate the score difference between the communication module corresponding to the downlink data and other communication modules; Count the average score differences between the communication module corresponding to the downlink data and other communication modules within the set time window, and compare the average score difference corresponding to each communication module with the trigger threshold; In response to the average score difference being greater than a trigger threshold, the main control module is triggered to switch the transmission frequency band of the downlink data.

7. The multi-communication module fusion transmission method according to claim 6, characterized in that: The main control module switches the transmission frequency band of the downlink data, including: Constructing a state space based on the signal quality score, interference intensity, and temperature state of the communication module corresponding to the downlink data, and constructing an action space based on the selectable frequency band corresponding to the communication module; According to the state space and the action space, a Q learning algorithm is adopted based on a set reward function to adjust the transmission frequency band corresponding to the downlink data.

8. A multi-communication module fusion transmission method, characterized in that: include: The main control module parses the received uplink data and determines the service type corresponding to the uplink data; Obtain the operating parameters of different communication modules in real time, and evaluate the signal quality score of each communication module based on the corresponding operating parameters; The transmission mode corresponding to the uplink data is determined according to the signal quality score of each communication module, and the corresponding fusion strategy is generated and sent to the mixer according to the transmission mode.

9. The multi-communication module fusion transmission method according to claim 8, characterized in that: Evaluate the signal quality score of the communication module based on the corresponding operating parameters, including: Normalizing each of the operating parameters, and setting parameter weights corresponding to each of the operating parameters according to the entropy weight method; Combining the normalized processing results and parameter weights corresponding to the operating condition parameters, a weighted algorithm is used to calculate the signal quality score of the communication module.

10. The multi-communication module fusion transmission method according to claim 8, characterized in that: Also includes: When the fusion strategy is multi-mode concurrent transmission, the mixer encapsulates the uplink data uploaded by each communication module into the same coding format and fragments the uplink data after the unified coding format; A hierarchical modulation method is used to map the sliced data corresponding to each communication module to the transmission frequency band corresponding to the issued fusion strategy; Determine the link weight according to the real-time channel status of each communication module, and use the weighted polling method to allocate the corresponding data transmission volume of each communication module based on the link weight; The protocol conversion is performed on the fragmented data corresponding to each communication module, and the fragmented data corresponding to each communication module is integrated into a unified data stream and uploaded to the host computer according to the allocated data transmission volume.

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