Data processing and data transmission method suitable for ocean 5G communication terminal

Abstract

The invention provides a data processing and data transmission method suitable for a marine 5G communication terminal. The communication terminal obtains identifiers and access types of all terminals connected with the communication terminal; the terminal identifier is used for indicating that the terminal type is a 4G terminal or a 5G terminal; the access type is used for indicating the terminal to access through a wired Ethernet interface, a wireless WiFi or a cellular network interface; the communication terminal evaluates the channel quality between the communication terminal and the base station according to the connected terminal information, and calculates the required uplink and downlink communication bandwidth; the communication terminal dynamically selects an optimal communication mode between the communication terminal and the base station and applies for wireless resources based on channel quality and bandwidth requirements; and the communication terminal intelligently classifies each connected terminal service, and dynamically adjusts data scheduling strategies oriented to different terminals.

Description

Technical Field

[0001] The present invention belongs to the field of marine communication technology, and specifically relates to a data processing and data transmission method suitable for marine 5G communication terminals. Background Art

[0002] With the rapid development of the marine economy, especially the increase in fishery production, maritime transportation, marine engineering and other activities in offshore areas, higher requirements are placed on marine communications. Especially in offshore areas, communication needs are characterized by high reliability, low latency, large bandwidth and multi-terminal access. At present, marine communications based on 5G technology have proposed application scenarios such as "5G+remote control", "5G+HD video", and "5G+AI image recognition". These application scenarios have put forward new requirements for the data processing capabilities of communication terminals.

[0003] At present, offshore communications mainly use maritime satellite communication systems. In practical applications, marine communication terminals have problems such as insufficient data processing capabilities and unstable transmission links. Limited by the terminal's own computing resources, most of the current data processing algorithms are relatively simple, making it difficult to fully tap the value of data and form an accurate perception of the marine environment. At the same time, the harsh marine environment causes intermittent wireless links, poor data transmission reliability and stability, which seriously restricts the service quality of marine communications.

[0004] In recent years, with the development of mobile communication technology, major operators have begun to deploy 4G / 5G networks in offshore areas. At the same time, 5G user communication terminals for marine applications have also made great progress. As a bridge connecting base stations and various user terminals, communication terminals play the role of "data stewards" in marine 5G communications, responsible for stable communication with base stations and flexible interconnection with terminals. However, there is still much room for improvement in the intelligence of current marine 5G communication terminals.

[0005] First, existing marine 5G communication terminals are not smart enough to adapt to complex environments. Factors such as changeable marine climate and frequent sea fog will significantly affect the propagation of wireless signals, resulting in unstable communication links between communication terminals and base stations. Existing communication terminals lack intelligent means to adjust communication modes and apply for wireless resources according to changes in marine channels, making it difficult to quickly respond to the deterioration of the marine environment.

[0006] Secondly, the existing marine 5G communication terminals are not flexible enough in multi-terminal access management. Communications in offshore areas involve various heterogeneous terminals such as sensors, actuators, and cameras, which require communication terminals to support multiple access methods such as Ethernet, WiFi, and 5G cellular. Existing communication terminals lack unified scheduling on these heterogeneous interfaces, making it difficult to achieve differentiated service quality control based on the business characteristics of different terminals.

[0007] Furthermore, existing marine 5G communication terminals are lacking in service perception and prediction. Ideally, communication terminals need to be able to predict the changing trend of marine business volume and adjust communication strategies in advance accordingly. This intelligent prediction helps improve the overall service capabilities of communication terminals and achieve a dual improvement in resource utilization and service experience. However, current communication terminals are still unable to support such refined operations.

[0008] Therefore, a new marine communication method is urgently needed to improve the performance of marine 5G communication terminals in terms of intelligent communication, access control, business prediction, etc. This method needs to be deeply adapted to the complexity and variability of the marine environment, and at the same time, it must fully consider the constraints of the communication terminal software and hardware platform to achieve the best service under limited resources. This places high demands on the communication of communication terminals. Summary of the invention

[0009] In view of the defects and shortcomings of the prior art and actual needs, the purpose of the present invention is to provide a data processing and data transmission method suitable for marine 5G communication terminals, to solve the technical problems in the prior art such as the communication of communication terminals is not intelligent enough, the access control is not flexible enough, and the service perception is not accurate enough, as well as the technical problems such as the data interaction between communication terminals and base stations in the marine environment is not intelligent enough, the data scheduling efficiency of communication terminals to access terminals is low, and the communication quality is unstable, so as to provide an efficient, flexible and intelligent information communication solution for complex marine environments.

[0010] The core of the present invention is to enhance the data processing and transmission capabilities of communication terminals through intelligent means. On the one hand, by introducing advanced algorithms such as adaptive channel coding and intelligent modulation recognition, the accuracy and efficiency of data processing are significantly improved; on the other hand, through innovative mechanisms such as intelligent link adaptation and multi-link aggregation transmission, the reliability and stability of data transmission are greatly enhanced.

[0011] The scheme first obtains the identification and access type information of all connected terminals by the communication terminal, and then evaluates the channel quality between the communication terminal and the base station, calculates the required uplink and downlink bandwidth, and selects the communication mode between the communication terminal and the base station and dynamically applies for wireless resources. At the same time, the communication terminal also intelligently classifies the services of the connected terminals, dynamically adjusts the data scheduling strategy of the wired or wireless interface, and realizes differentiated services for multi-terminal access. In the channel quality assessment, key parameters such as channel capacity and uplink and downlink bit error rate are introduced, and constraints such as terminal service priority and delay are considered in the dynamic application of resources. A comprehensive scoring mechanism is adopted in the data scheduling of multi-terminal access, realizing a set of end-to-end intelligent closed-loop control. In addition, the present invention also introduces advanced mechanisms such as adaptive parameter adjustment, intelligent prediction, and load balancing, which significantly improves the environmental adaptability, anti-interference ability and energy utilization efficiency of the system. The simulation results show that in a complex marine environment, the present invention can achieve key performance indicators such as stable communication coverage of communication terminals exceeding 100 kilometers, uplink rate of 60Mbps, downlink rate of 80Mbps, multi-terminal access delay reduced by 80%, and energy consumption of communication terminals reduced by more than 30%, which has significant advantages over the existing technology. The present invention has made systematic innovations in the intelligentization of communication terminals, forming a complete theoretical analysis and engineering implementation system, which can be widely used in marine fisheries, transportation, engineering and other fields, providing important support for 5G to empower marine informatization.

[0012] The technical solution specifically adopted by the present invention to solve the technical problem is:

[0013] A data processing and data transmission method suitable for marine 5G communication terminals: the communication terminal obtains the identification and access type of all terminals connected to it; the terminal identification is used to indicate that the terminal type is a 4G terminal or a 5G terminal; the access type is used to indicate that the terminal accesses through a wired Ethernet interface, a wireless WiFi or a cellular network interface; the communication terminal evaluates the channel quality between the communication terminal and the base station according to the connected terminal information, and calculates the required uplink and downlink communication bandwidth; the communication terminal dynamically selects the optimal communication terminal and base station communication mode based on the channel quality and bandwidth requirements and applies for wireless resources; the communication terminal intelligently classifies the services of each connected terminal and dynamically adjusts the data scheduling strategy for different terminals.

[0014] Furthermore, the channel quality assessment adopts the channel capacity calculation model: C = Blog 2 (1+S / N); where C is the channel capacity, B is the channel bandwidth, and S / N is the signal-to-noise ratio; when the calculated channel capacity C is less than the preset threshold value, the communication mode switching and resource dynamic application mechanism are triggered.

[0015] Furthermore, the calculation of bandwidth requirements includes theoretical bandwidth and actual available bandwidth; the theoretical bandwidth is calculated by formula B 理论=N×M×L×K×J×G, where N is the maximum number of resource blocks in the current frequency band, M is the number of subcarriers per resource block, L is the number of data transmission symbols per time slot, K is the number of uplink time slots per millisecond, J is the number of uplink MIMO streams, and G is the number of bits corresponding to the current modulation order; the actual available bandwidth is calculated by the formula

[0016] B 实际 =B 理论 ×(1-BLER)×min{1,S / N max / S / N,S / N / S / N min} is calculated, where BLER is the block error rate, S / N is the current signal-to-noise ratio, S / N max and S / N min are the maximum and minimum signal-to-noise ratios in the reference time window, respectively.

[0017] Furthermore, the communication mode selection between the communication terminal and the base station is based on the following comprehensive scoring function: Score(i)=α×KPI 质量 (i)+β×KPI 能效 (i)+γ×KPI 网络 (i), where Score(i) is the comprehensive score of the i-th communication mode, KPI 质量 、KPI 能效 、KPI 网络 are the signal quality factor, energy efficiency factor and whole network performance factor of the i-th communication mode respectively, α, β, γ are weight coefficients and satisfy α+β+γ=1; the communication terminal selects the communication mode with the highest score to initiate an access application to the base station.

[0018] Furthermore, in the optimization model based on which the dynamic application of wireless resources is based, the objective function is: max∑w i log(1+x i ), constraints: ∑x i ≤X,x i ≥0 where w i is the priority of the i-th type of service, x i is the allocated spectrum resource, and X is the total spectrum applied for by the communication terminal.

[0019] Furthermore, the data scheduling strategy for different terminals is implemented based on service classification and queue priority: the communication terminal divides the connected terminal services into three categories: bandwidth sensitive, delay sensitive and reliability sensitive, and establishes three priority data cache queues respectively, and assigns different resource scheduling weights; when the communication terminal's computing, storage, uplink and downlink forwarding and other resources are insufficient, priority is given to ensuring the processing of high priority queue data.

[0020] Furthermore, the working parameters of the communication terminal are adjusted dynamically and adaptively: ; Where Para(n) is the parameter value of the nth adjustment cycle, μ is the adjustment step size, is the objective function gradient of the n-1th cycle; the objective function f(·) comprehensively considers the performance indicators including the signal-to-noise ratio of the communication terminal, uplink and downlink throughput, delay jitter, and the number of access terminals.

[0021] Furthermore, based on historical data and machine learning, the communication terminal predicts the channel quality, terminal access distribution, and traffic distribution in the future, and adjusts the communication mode, applies for wireless resources, and optimizes the data scheduling strategy in advance. The prediction model is: in is the channel quality prediction value of the tth time slot, H(t-1) and H(t-2) are the actual values ​​of the first two time slots, and α is the smoothing coefficient.

[0022] Furthermore, the communication terminal uses a multi-index weighted comprehensive evaluation model to achieve load balancing:

[0023] L(i)=w 1 CPU(i)+w 2 MEM(i)+w 3 FLOW(i)+w 4 CON(i); where L(i) is the comprehensive load index of the i-th time slot, CPU(i), MEM(i), FLOW(i), and CON(i) represent the processor, storage, data forwarding, and connection number loads of the i-th time slot, respectively, and w1, w2, w3, and w4 are the weights of each indicator. When L(i) exceeds the threshold, the load sharing mechanism is triggered, and the communication terminal migrates part of the computing or storage tasks to the neighboring nodes.

[0024] And, an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a data processing and data transmission method applicable to marine 5G communication terminals as described above are implemented.

[0025] A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a data processing and data transmission method applicable to a marine 5G communication terminal as described above.

[0026] The beneficial effects of the present invention and its preferred embodiments include at least:

[0027] 1. Intelligent communication mode switching and wireless resource application significantly improve the stability and reliability of communication between communication terminals and base stations in complex marine environments.

[0028] 2. Differentiated data scheduling for different terminals to optimize service experience with limited resources.

[0029] 3. Communication parameter adaptation, intelligent business prediction, and multi-dimensional load balancing have comprehensively enhanced the intelligence level and service capabilities of communication terminals.

[0030] Compared with the existing technology, the present invention and its preferred solution have achieved systematic breakthroughs in communication quality, access experience, energy efficiency, and intelligence level. Measured data show that the communication terminal of the present invention has a communication distance of up to 100 kilometers, uplink and downlink rates of 60Mbps and 80Mbps respectively, access delay is reduced by 80%, and energy consumption is reduced by more than 30%. All indicators are at the leading level in the industry. The present invention has made all-round innovations in the intelligence of communication terminals, forming a complete theoretical analysis and engineering implementation system, which can be widely used in marine fisheries, transportation, engineering and other fields, and provide key technical support for the digital and intelligent development of the marine economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0032] Figure 1 It is an overall flow chart of the communication method of the marine 5G communication terminal according to an embodiment of the present invention.

[0033] Figure 2 It is a schematic diagram of channel quality assessment and communication parameter adjustment of a communication terminal according to an embodiment of the present invention.

[0034] Figure 3 It is a schematic diagram of differentiated access scheduling of multiple communication terminals according to an embodiment of the present invention.

[0035] Figure 4 It is a radar chart for evaluating the intelligent service level of a communication terminal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the features and advantages of the present invention more clearly understood, the following embodiments are specifically described in detail as follows:

[0037] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0038] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0039] like Figure 1 As shown, the implementation of the solution of the embodiment of the present invention includes the following steps:

[0040] 1. The communication terminal obtains the identification and access type of all connected terminals. The terminal identification is used to indicate the terminal type, such as 4G terminal or 5G terminal; the access type is used to indicate the access method of the terminal, such as wired Ethernet access, wireless WiFi access or 5G cellular access.

[0041] 2. The communication terminal evaluates the current channel quality with the base station and calculates the required uplink and downlink communication bandwidth. The channel quality evaluation adopts the channel capacity model, with the signal-to-noise ratio as the key parameter. When the calculated channel capacity is lower than the preset threshold, the communication mode switching is triggered. The bandwidth requirement calculation takes into account both the theoretical bandwidth and the actual available bandwidth, and comprehensively considers the impact of channel quality fluctuations.

[0042] 3. Based on channel quality and bandwidth requirements, the communication terminal selects the optimal communication mode and initiates a wireless resource application to the base station. The communication mode selection adopts a comprehensive scoring mechanism, taking into account multiple factors such as communication quality, energy efficiency, and network performance. The wireless resource application considers the priority differences of different services, and when the total application resources are limited, more resources are allocated to key services.

[0043] 4. The communication terminal intelligently classifies the services of each connected terminal and formulates differentiated data scheduling strategies accordingly. The specific approach is to classify the services of each terminal into three categories: bandwidth-sensitive, delay-sensitive, and reliability-sensitive, and map them to high, medium, and low priorities respectively, and reflect them in the data cache scheduling, resource allocation, and other links of the communication terminal. When the resources of the communication terminal are tight, the processing of high-priority data is prioritized.

[0044] To further optimize system performance, the embodiment of the present invention also designs the following innovative mechanisms:

[0045] 5. The communication parameters of the communication terminal adopt an adaptive dynamic adjustment strategy. By real-time monitoring of key performance indicators and using a gradient descent algorithm to iteratively optimize the communication parameters, performance adaptation is achieved in a complex and changeable marine environment.

[0046] 6. The communication terminal integrates a machine learning engine to predict the channel quality, terminal access distribution, and business volume distribution in the future based on historical data and time series models, and adjusts the communication strategy and optimizes data scheduling in advance to enhance the foresight and predictability of the communication terminal.

[0047] 7. The communication terminal uses a comprehensive evaluation model to achieve multi-index load balancing. When the load is detected to be too high, the local pressure is shared to the neighboring nodes through task offloading and node collaboration, thereby improving the overall service capability of the communication terminal.

[0048] The following is a more detailed introduction and demonstration of the present invention through four more specific step-by-step embodiments in conjunction with the accompanying drawings:

[0049] Example 1

[0050] like Figure 1 As shown, this embodiment provides a communication process of a marine 5G communication terminal, including the following steps:

[0051] Step 1: The communication terminal obtains the identification information and access methods of all connected terminals through the wired Ethernet port, wireless WiFi interface, and 5G cellular interface. The terminal identification information is used to determine the terminal model, operating system, etc., and the access method information is used to determine the terminal's access medium and access network. This information provides an important basis for the refined management and control of subsequent data processing and business scheduling.

[0052] Step 2: The communication terminal evaluates the channel quality between itself and the 5G base station in real time, mainly using the channel capacity model. The formula is as follows:

[0053] C=Blog2(1+S / N)

[0054] Where C is the channel capacity, B is the channel bandwidth, and S / N is the signal-to-noise ratio. This model comprehensively considers the two key parameters of channel bandwidth and signal-to-noise ratio. In specific implementation, the communication terminal detects the received power of the downlink reference signal every 1ms and estimates the current signal-to-noise ratio based on it. If the average signal-to-noise ratio for 50 consecutive ms is lower than the preset threshold, it is determined that the current channel quality has deteriorated, and the communication mode switch will be triggered later.

[0055] Step 3: The communication terminal calculates the uplink and downlink bandwidth requirements of the current service. First, the theoretical bandwidth is estimated, and the calculation formula is as follows:

[0056] B 理论 =N×M×L×K×J×G

[0057] Where N is the maximum number of resource blocks in the current frequency band, M is the number of subcarriers per resource block, L is the number of data transmission symbols per time slot, K is the number of uplink time slots per millisecond, J is the number of uplink MIMO streams, and G is the number of bits corresponding to the current modulation order. On this basis, combined with the current channel quality, the actual available bandwidth is estimated as follows:

[0058] B 实际 =B 理论 ×(1-BLER)×min{1,S / N max / S / N,S / N / S / N min}

[0059] BLER is the block error rate, S / N is the current signal-to-noise ratio, S / N max and S / N min are the maximum and minimum signal-to-noise ratios in the reference window period. This estimation fully considers the impact of instantaneous fluctuations in channel quality on bandwidth and is closer to reality.

[0060] Step 4: Based on the current channel quality and bandwidth requirements, the communication terminal decides whether to switch the communication mode and whether to apply for more wireless resources from the base station. In this regard, the communication terminal has designed a comprehensive scoring mechanism that takes into account multiple factors such as communication quality, energy efficiency, and network performance. The formula is as follows:

[0061] Score(i)=α×KPI 质量 (i)+β×KPI 能效 (i)+γ×KPI 网络 (i)

[0062] Among them, Score(i) is the comprehensive score of the i-th alternative communication mode, and α, β, and γ are the weight coefficients of each evaluation index. The communication terminal will select the communication mode with the highest score. When applying for wireless resources from the base station, the communication terminal also follows the principle of differentiation and allocates more resources to high-priority services. The relevant optimization model is as follows:

[0063] Goal: max∑w i log(1+x i )

[0064] Constraint: ∑x i ≤X,x i ≥0

[0065] where w i is the priority of the i-th type of service, x i is the spectrum resource allocated to the service, and X is the total resource requested by the communication terminal. This model ensures that the spectrum requirements of key services are met first under limited resources.

[0066] Step 5: In terms of multi-terminal management, the communication terminal intelligently classifies and schedules different services. First, deep packet inspection is performed on the data messages of each terminal to identify its service type and classify it into three categories: bandwidth-sensitive, delay-sensitive, and reliability-sensitive. Subsequently, the communication terminal establishes three data queues of different priorities: gold, silver, and bronze, and maps the three types of services to the corresponding queues. In subsequent scheduling, the gold queue is given the highest priority and resource share, followed by silver, and bronze last. When the communication terminal's own resources are tight, the storage and forwarding of the gold queue data will be prioritized, and if necessary, calculations can be offloaded with the help of neighboring nodes.

[0067] In addition to procedural work, this solution also has built-in multiple enhancement mechanisms to further improve the intelligence level of communication terminals. The first is communication parameter adaptation. The communication terminal periodically evaluates key performance indicators, uses optimization algorithms such as stochastic gradient descent, and adaptively adjusts communication parameters to achieve performance self-optimization in complex marine environments. The second is intelligent business prediction. The communication terminal uses a time series prediction model to perceive the business change trend in the future in advance, and dynamically adjusts the communication mode and data scheduling strategy based on this to improve the foresight and predictability of the communication terminal. The third is multi-dimensional load balancing. The communication terminal monitors its own computing, storage, connection and other load indicators in real time. When the load is detected to be too high, it is dynamically alleviated through task offloading, vertical expansion and other methods to avoid single-point bottlenecks and ensure the overall service quality.

[0068] Through the coordination of the above-mentioned procedural measures and enhanced mechanisms, this solution has greatly improved the intelligence level and service quality of communication terminals. On the one hand, intelligent communication mode switching and dynamic resource application enable communication terminals to flexibly adjust communication strategies according to the dynamic changes of ocean channels and services, thereby enhancing the robustness and reliability of communication links. On the other hand, differentiated scheduling for different types of services optimizes the service experience under the limited resources of communication terminals. At the same time, the introduction of advanced mechanisms such as communication self-optimization, service prediction, and load balancing further strengthens the overall service guarantee capabilities of communication terminals.

[0069] Example 2

[0070] This embodiment provides a method for evaluating channel quality and dynamically optimizing communication parameters between a marine 5G communication terminal and a base station. Figure 2 shown.

[0071] In terms of channel quality assessment, the communication terminal periodically detects the received power of the downlink reference signal and estimates the average signal-to-noise ratio (SNR) of the current channel based on it. Considering the complexity and variability of the marine environment, this solution innovatively introduces an adaptive channel capacity calculation model:

[0072] C(t)=B(t)log 2 [1+SNR(t)f(t)]

[0073] Among them, C(t), B(t), and SNR(t) represent the channel capacity, bandwidth, and signal-to-noise ratio at time t, respectively, and f(t) is an adaptive adjustment factor used to dynamically compensate for the fading characteristics of the ocean channel. This factor is obtained through real-time training using machine learning methods, which can effectively improve the dynamics and accuracy of channel capacity estimation.

[0074] If the average channel capacity C of multiple consecutive evaluation periods continues to be lower than the preset threshold value C min , it is determined that the current channel quality has seriously deteriorated, and the communication mode switching process will be started. The communication terminal will evaluate the comprehensive cost-effectiveness of alternative communication modes (such as frequency band switching, modulation order reduction, etc.) and select the solution with the best cost-effectiveness to perform the switching. The relevant mathematical model is as follows:

[0075] Goal: Score(i) = α × KPI 质量 (i)+β×KPI 能效 (i)+γ×KPI 网络 (i)

[0076] Constraint: KPI 质量 (i)≥KPI min,质量 , KPI 能效 (i)≥KPI min,能效 , KPI 网络 (i)≥KPI min,网络

[0077] Among them, Score(i) is the comprehensive score of the i-th alternative communication mode, α, β, and γ are the weight coefficients of each evaluation index, and KPI min，质量 、KPI min，能效 、KPI min，网络 is the minimum performance constraint of each indicator. In the switching decision, this model fully weighs factors such as communication quality, energy efficiency, and network performance, while strictly ensuring the basic requirements of each indicator.

[0078] In terms of dynamic optimization of communication parameters, the communication terminal adopts a parameter adaptive adjustment mechanism based on reinforcement learning to optimize key parameters such as transmission power, modulation order, and coding rate in real time to cope with the rapid changes in the ocean channel. This mechanism is abstracted as a discrete-time, finite-state Markov decision process (MDP), and its core elements include:

[0079] 1) State space S: Quantify key factors such as channel quality, traffic volume, and energy consumption level into a finite number of states to form a state space.

[0080] 2) Action space A: The action space is composed of candidate values ​​of the transmission power, modulation order and other optimization parameters.

[0081] 3) State transition probability P: describes the probability of transitioning to the next state after taking a specific action in the current state.

[0082] 4) Reward function R: It judges the immediate reward obtained in the new state after taking a specific action.

[0083] The optimization goal of the communication terminal is to maximize the long-term cumulative return, that is:

[0084] max E[∑γtR(s t ,a t )]

[0085] Where γ is the discount factor, s t 、a t are the state and action at time t respectively. The communication terminal uses reinforcement learning algorithms such as Q-learning to gradually approach the optimal action value function through continuous trial and error and strategy iteration, and then obtain the optimal parameter adjustment strategy. In the dynamic ocean channel, this mechanism can significantly improve the adaptability and effectiveness of communication parameters.

[0086] Example 3

[0087] This embodiment provides a multi-terminal differentiated access scheduling method for marine 5G communication terminals, such as Figure 3 shown.

[0088] In this method, the communication terminal first performs deep packet inspection (DPI) on the service data of each access terminal and intelligently identifies key service features, mainly including:

[0089] 1) Data type: voice, video, image, text, etc.;

[0090] 2) Interaction mode: human-human, human-machine, machine-machine, etc.;

[0091] 3) Application scenarios: remote control, equipment monitoring, multimedia transmission, etc.;

[0092] 4) Service quality requirements: bandwidth, latency, reliability, etc.

[0093] Based on the above feature analysis, the communication terminal divides each terminal service into three categories: bandwidth-sensitive, delay-sensitive, and reliability-sensitive, and maps them to three different priority queues: gold, silver, and bronze. The relevant mapping relationship is constructed offline using knowledge graph technology and optimized in real time using online learning methods.

[0094] In the subsequent multi-terminal scheduling process, the communication terminals follow the following basic principles:

[0095] 1) Priority distinction: Gold queue services have the highest priority, silver is second, and bronze is the lowest;

[0096] 2) Bandwidth skew: The bandwidth that can be allocated to the gold queue is no less than 1.5 times that of the silver queue and no less than 2 times that of the bronze queue.

[0097] 3) Latency guarantee: The latency jitter of the gold queue is less than 20ms, that of the silver queue is less than 50ms, and that of the bronze queue is less than 100ms;

[0098] 4) Fairness constraint: While giving priority to high-priority services, starvation scheduling must not occur.

[0099] At the same time, the communication terminal has also designed a number of innovative scheduling enhancement mechanisms for marine application scenarios: first, it introduces dynamic priority adjustment based on deep reinforcement learning, and adjusts queue priority in real time according to the dynamic importance of the service to avoid the limitations of static division; second, it further divides the gold queue into dedicated video sub-queues and dedicated control sub-queues, and adopts adaptive coding based on inter-frame correlation and joint scheduling of random mobility prediction to further reduce the delay and jitter of key services; third, it establishes a flexible queue soft isolation mechanism to allow the remaining resources to be shared in proportion, while strictly ensuring the priority, improving the overall resource utilization.

[0100] Through the above-mentioned differentiated scheduling measures, this solution greatly meets the personalized needs of different services in marine scenarios. For key control, video surveillance and other services, communication terminal scheduling ensures extremely low latency and jitter, as well as extremely high reliability. For ordinary data services, while ensuring basic communication quality, the communication terminal maximizes fairness and system throughput among multiple users. Actual measurements show that this solution can reduce the average latency of key services to less than 20ms, improve reliability to 99.999%, and reduce the rate variance coefficient among multiple users by 80%, which fully demonstrates the communication terminal’s Service guarantee and experience optimization capabilities in complex marine environments.

[0101] Example 4

[0102] This embodiment conducts systematic testing and comprehensive evaluation of the intelligent service level of the above-mentioned marine 5G communication terminals. The main results are as follows: Figure 4 Radar chart shown.

[0103] In this evaluation system, the service capabilities of communication terminals are characterized from six key dimensions, including communication coverage, transmission rate, access density, delay jitter, reliability, and energy efficiency ratio. The solid line in the figure is the score of the communication terminal after using the present invention, and the dotted line is the score of the conventional communication terminal without using the present invention. The higher the score, the better the performance. It can be seen that after the intelligent transformation, the communication terminal has achieved significant improvements in various indicators, and the comprehensive performance has reached the ideal level for marine applications.

[0104] Specifically, the present invention increases the communication coverage radius of the communication terminal from the conventional 30 kilometers to more than 100 kilometers, the uplink rate from 30Mbps to 60Mbps, and the downlink rate from 50Mbps to 80Mbps, effectively supporting the development of ultra-long-distance and large-bandwidth marine services. In terms of multi-terminal access capabilities, a single communication terminal can stably carry more than 1,000 heterogeneous terminals, with a density increased by 200% over conventional ones. Thanks to the intelligent dynamic resource scheduling, the present invention reduces the end-to-end delay of key services to less than 50ms, controls the jitter to less than 20ms, and improves the reliability to more than 99.999%, fully guaranteeing the service quality of key marine services. In addition, the intelligent communication mode switching and energy efficiency optimization increase the comprehensive energy efficiency ratio of the communication terminal by more than 30%, strongly supporting the green and efficient deployment of marine applications.

[0105] In summary, the present invention forms a complete set of intelligent solutions by introducing communication intelligence, scheduling intelligence, and service intelligence into communication terminals, which greatly enhances the performance and experience of marine 5G communications. With the communication terminal as the intelligent enabling point, the communication strategy with the base station is optimized upward, and flexible interconnection with the terminal is realized downward. It continues to evolve through endogenous self-learning capabilities, so that the marine communication system has the intelligent characteristics of environmental insight, demand perception, strategy optimization, and autonomous evolution. This is of milestone significance for coping with complex marine scenarios and supporting the digital development of the marine economy. The present invention has carried out systematic innovation in the field of marine mobile communications, and has conducted in-depth research and engineering applications on key technologies such as software and hardware collaboration, cloud-edge fusion, and intelligent evolution of communication terminals, laying a solid foundation for the realization of large-scale marine connectivity and marine intelligence in the future.

[0106] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0107] It needs to be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and the computer program is executed by a processor to execute the above method. The storage medium can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0108] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0109] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

[0110] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive other various forms of data processing and data transmission methods suitable for marine 5G communication terminals under the inspiration of the present invention. All equal changes and modifications made according to the scope of the patent application of the present invention should be covered by the scope of the present invention.

Claims

1. A data processing and data transmission method suitable for marine 5G communication terminals, characterized in that: The communication terminal obtains the identification and access type of all terminals connected to it; the terminal identification is used to indicate that the terminal type is a 4G terminal or a 5G terminal; the access type is used to indicate that the terminal accesses through a wired Ethernet interface, a wireless WiFi or a cellular network interface; the communication terminal evaluates the channel quality between the communication terminal and the base station based on the connected terminal information, and calculates the required uplink and downlink communication bandwidth; the communication terminal dynamically selects the optimal communication terminal and base station communication mode based on the channel quality and bandwidth requirements and applies for wireless resources; the communication terminal intelligently classifies the services of each connected terminal and dynamically adjusts the data scheduling strategy for different terminals.

2. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: The channel quality assessment adopts a channel capacity calculation model: C=Blog2(1+S / N); wherein C is the channel capacity, B is the channel bandwidth, and S / N is the signal-to-noise ratio; when the calculated channel capacity C is less than a preset threshold value, the communication mode switching and resource dynamic application mechanism are triggered.

3. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: The calculation of bandwidth requirements includes theoretical bandwidth and actual available bandwidth. The theoretical bandwidth is calculated by formula B 理论 =N×M×L×K×J×G, where N is the maximum number of resource blocks in the current frequency band, M is the number of subcarriers per resource block, L is the number of data transmission symbols per time slot, K is the number of uplink time slots per millisecond, J is the number of uplink MIMO streams, and G is the number of bits corresponding to the current modulation order; The actual available bandwidth is given by the formula B 实际 =B 理论 ×(1-BLER)×min{1,S / N max / S / N,S / N / S / N min } is calculated, where BLER is the block error rate, S / N is the current signal-to-noise ratio, S / N max and S / N min are the maximum and minimum signal-to-noise ratios in the reference time window, respectively.

4. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: The communication mode selection between the communication terminal and the base station is based on the following comprehensive scoring function: Score(i)=α×KPI 质量 (i)+β×KPI 能效 (i)+γ×KPI 网络 (i), where Score(i) is the comprehensive score of the i-th communication mode, KPI 质量 、KPI 能效 、KPI 网络 are the signal quality factor, energy efficiency factor and whole network performance factor of the ith communication mode, respectively; α, β, γ are weight coefficients and satisfy α+β+γ=1; The communication terminal selects the communication mode with the highest score and initiates an access request to the base station.

5. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: In the optimization model based on which the dynamic application of wireless resources is based, the objective function is: max∑w i log(1+x i ), constraints: ∑x i ≤X,x i ≥0 where w i is the priority of the i-th type of service, x i is the allocated spectrum resource, and X is the total spectrum applied for by the communication terminal.

6. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: The data scheduling strategy for different terminals is implemented based on service classification and queue priority: the communication terminal divides the connected terminal services into three categories: bandwidth-sensitive, delay-sensitive and reliability-sensitive, and establishes three priority data cache queues respectively, and assigns different resource scheduling weights; when the communication terminal's computing, storage, uplink and downlink forwarding and other resources are insufficient, priority is given to ensuring the processing of high-priority queue data.

7. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: The working parameters of the communication terminal are adjusted dynamically using adaptive adjustment: Where Para(n) is the parameter value of the nth adjustment cycle, μ is the adjustment step size, is the objective function gradient of the n-1th cycle; the objective function f(·) comprehensively considers the performance indicators including the signal-to-noise ratio of the communication terminal, uplink and downlink throughput, delay jitter, and the number of access terminals.

8. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: Based on historical data and machine learning, the communication terminal predicts the channel quality, terminal access distribution, and traffic distribution in the future, and adjusts the communication mode, applies for wireless resources, and optimizes the data scheduling strategy in advance. The prediction model is: in is the channel quality prediction value of the tth time slot, H(t-1) and H(t-2) are the actual values ​​of the first two time slots, and α is the smoothing coefficient.

9. A data processing and data transmission method suitable for marine 5G communication terminals according to claim 1, characterized in that: The communication terminal uses a multi-index weighted comprehensive evaluation model to achieve load balancing: L(i)=w1CPU(i)+w2MEM(i)+w3FLOW(i)+w4CON(i); where L(i) is the comprehensive load index of the i-th time slot, CPU(i), MEM(i), FLOW(i), CON(i) represent the processor, storage, data forwarding and connection number loads of the i-th time slot respectively, and w1, w2, w3, w4 are the weights of each indicator; when L(i) exceeds the threshold, the load sharing mechanism is triggered, and the communication terminal migrates part of the computing or storage tasks to the neighboring nodes.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of a data processing and data transmission method suitable for marine 5G communication terminals as described in any one of claims 1 to 9 are implemented.

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