5G communication module and 5G communication system

Abstract

The invention relates to the technical field of communication, in particular to a 5G communication module which comprises a radio frequency front end module, an antenna system, a processor and an interface. Wherein the radio frequency front-end module comprises a radio frequency amplifier, a filter, a frequency mixer and a power amplifier; wherein the antenna system comprises a multi-band antenna supporting Sub-6GHz and millimeter waves under a 5G band, and a beam forming technology is adopted under the millimeter wave band; the base band processor supports the 3GPP 5G NR standard, and comprises a frequency division duplex mode, a time division duplex mode, carrier aggregation and dual connectivity. The design of the 5G communication module and system combines efficient hardware integration, intelligent scheduling, dynamic resource management and a security mechanism, and provides powerful technical support for high-speed, low-delay and wide-connection 5G network requirements. Through supporting advanced technologies such as multi-band communication, carrier aggregation, network slicing and the like, the system has a wide application prospect, and can meet the requirements under various scenes such as the Internet of Things, the smart city, the Internet of Vehicles, industrial control and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of communication technologies, and in particular to a 5G communication module and a 5G communication system. Background Art

[0002] With the rapid development of 5G technology, the design of communication modules and systems has become critical. 5G communication modules and systems must not only have high transmission rates, but also support low latency, large bandwidth, and wide connectivity to meet the needs of different application scenarios. The following is a detailed design of 5G communication modules and systems, which aims to meet the needs of various scenarios such as the Internet of Things (IoT), smart manufacturing, unmanned driving, augmented reality (AR), and virtual reality (VR);

[0003] The 5G communication module is an embedded module that is mainly used to integrate 5G network functions into devices. It achieves high-speed communication with the 5G network through multiple components such as antennas, baseband processing, RF front-end and digital interfaces. The module design needs to have wide adaptability, support multiple frequency bands, transmission modes and power control, and is suitable for applications such as the Internet of Things, smart terminals, and industrial control.

[0004] However, the existing 5G communication modules and 5G communication systems are affected by environmental and network fluctuations during application, resulting in high data transmission delays. In multi-unit application scenarios, the module's port connection cannot meet user needs well.

[0005] To this end, a 5G communication module and a 5G communication system are proposed. Summary of the invention

[0006] The object of the present invention is to provide a 5G communication module and a 5G communication system to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions: a 5G communication module, including a radio frequency front-end module, an antenna system, a processor and an interface;

[0008] The RF front-end module includes RF amplifier, filter, mixer and power amplifier;

[0009] The antenna system includes a multi-band antenna that supports Sub-6GHz and millimeter wave in the 5G frequency band, and uses beamforming technology in the millimeter wave band;

[0010] Supports 3GPP 5G NR standards, including frequency division duplex and time division duplex modes, as well as carrier aggregation and dual-connectivity baseband processors. The baseband processor is responsible for processing 5G signals, including modulation and demodulation, encoding and decoding, and protocol processing;

[0011] A 5G communication system of a 5G communication module, the 5G communication system mainly consists of a 5G base station, a 5G core network, a user terminal, including a 5G communication module and an edge computing node.

[0012] Preferably, the 5G base station includes the collaboration of a macro base station and a small base station. The macro base station and the small base station are connected to each other through a backhaul network to achieve collaborative work. The millimeter wave and the Sub-6GHz collaborate. The base station supports millimeter wave and Sub-6GHz frequency bands, uses the Sub-6GHz frequency band to provide wide coverage, and uses millimeter wave to provide ultra-high transmission rate and capacity.

[0013] Preferably, the 5G core network includes a cloud core network. The 5G core network uses virtualization technology to virtualize network functions, and implements flexible scheduling and resource management of network functions through software-defined networking. Slicing technology divides different network slices according to different application scenarios. Edge computing introduces edge computing nodes to delegate some computing tasks to the edge of the network.

[0014] Preferably, the user terminal includes 5G communication module access, and the user terminal communicates with the 5G network through the integrated 5G module. The system can intelligently schedule communication resources according to the mobile speed, application type and network environment of the terminal device. Through AI algorithms, the system can predict user needs and adjust resource allocation in advance.

[0015] Preferably, in scenarios where multiple users and devices communicate simultaneously, a spectrum resource scheduler is introduced to dynamically adjust spectrum allocation based on device usage, bandwidth requirements, and network load using a machine learning algorithm.

[0016] Preferably, the spectrum efficiency η is defined as the number of bits transmitted within a unit bandwidth, and the optimized spectrum efficiency can be expressed as:

[0017]

[0018] Where: η is the spectrum efficiency, unit: bps / Hz, C is the channel capacity bps, and B is the bandwidth Hz.

[0019] Preferably, in high-density user scenarios, in order to further optimize spectrum utilization, the system combines channel selection and beamforming technology to dynamically select the optimal channel and enhance coverage and communication performance by directional transmission of signals; the channel capacity formula can be expressed by Shannon's theorem as:

[0020]

[0021] Where: C is the channel capacity in bps, B is the bandwidth in Hz, P is the signal power, and N0 is the noise power spectral density in W / Hz.

[0022] Preferably, in the edge computing, the system sinks the computing tasks to the node closest to the user, dynamically allocates computing resources to the edge nodes, adjusts the computing power according to the real-time needs of the user, introduces AI optimization algorithms, and determines which computing tasks can be sunk to the edge computing nodes;

[0023] Total delay T total It can be decomposed into three parts: data transmission delay, edge computing processing delay and core network processing delay. After more tasks are transferred to edge computing nodes, the total delay of the system can be reduced:

[0024]

[0025] After optimization: By reducing T core , the system latency is significantly reduced.

[0026] Preferably, the system dynamically adjusts queue length, bandwidth allocation, and task priority through an adaptive queue management strategy. The queue delay can be approximately calculated using a small M / M / 1 queue model:

[0027]

[0028] Where: μ is the service rate, the number of tasks served per second; λ is the task arrival rate. The intelligent scheduling algorithm is used to optimize queue management to ensure that μ is greater than λ, thereby reducing the queuing delay T queue .

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The design of the 5G communication module and system combines efficient hardware integration, intelligent scheduling, dynamic resource management and security mechanisms, providing strong technical support for the high-speed, low-latency and wide-connected 5G network requirements. By supporting advanced technologies such as multi-band communication, carrier aggregation, and network slicing, the system has broad application prospects and can meet the needs of various scenarios such as the Internet of Things, smart cities, Internet of Vehicles, and industrial control. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 The 5G communication module of the present invention;

[0033] Figure 2 This is the 5G communication system of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] See also Figure 1 to Figure 2 , the present invention provides a technical solution:

[0036] A 5G communication module, including a radio frequency (RF) front-end module: used to receive and send 5G signals, supporting FR1 (Sub-6GHz) and FR2 (millimeter wave) frequency bands. The RF front-end includes components such as RF amplifiers, filters, mixers, and power amplifiers, which must meet the high frequency and broadband requirements of the 5G network.

[0037] Antenna system:

[0038] Multi-band antenna: The module design uses a multi-band antenna to support Sub-6GHz and millimeter wave in the 5G band. The communication efficiency of the antenna is improved through MIMO (multiple input multiple output) technology.

[0039] Beamforming technology: Beamforming technology is used to improve signal strength and transmission stability, especially in the millimeter wave frequency band, to achieve high-speed, low-latency data transmission.

[0040] Baseband processor: The core of the module, responsible for processing 5G signals, including modulation and demodulation, encoding and decoding, and protocol processing.

[0041] 5G NR (New Radio) standard support: The baseband processor must support the 3GPP 5G NR standard, including frequency division duplex (FDD) and time division duplex (TDD) modes, as well as enhanced technologies such as carrier aggregation (CA) and dual connectivity (DC).

[0042] Protocol stack support: It is necessary to implement the 5G protocol stack, including the physical layer, MAC layer, RLC layer and PDCP layer, to ensure that the module can communicate smoothly with the 5G core network. Both NSA (non-standalone networking) and SA (standalone networking) modes are supported.

[0043] Processor and interface:

[0044] High-performance processor: Multi-core processor is used to handle high-bandwidth data streams, ensuring efficient data processing.

[0045] Interface support: Design multiple interfaces, such as USB 3.0, PCIe, Ethernet, etc., to communicate with other devices or systems. In particular, industrial interfaces (such as UART, SPI, I2C) need to be supported to adapt to industrial IoT applications.

[0046] Power consumption control:

[0047] Low power mode: The module needs to be designed with low power consumption mechanisms (such as DRX, PSM, etc.) to meet the long-term operation requirements of IoT devices, especially for battery-powered terminals.

[0048] Power amplifier design: supports adjustable power output and reduces power consumption at different transmission distances.

[0049] 5G communication module features

[0050] High transmission rate: Supports download speeds of more than 1Gbps and upload speeds of 200Mbps, meeting the needs of high-speed applications such as HD video, AR / VR, etc.

[0051] Low latency: Low latency requirements must be considered when designing the module to ensure millisecond-level response in key application scenarios (such as unmanned driving and industrial automation).

[0052] Extensive connectivity: The module supports the simultaneous access of massive devices, meeting the needs of connecting millions of devices in the Internet of Things and smart cities.

[0053] Security encryption: Supports 5G network security protocols such as IPsec, TLS, etc. to ensure the encryption and security of communication data.

[0054] A 5G communication system based on 5G communication modules, mainly composed of 5G base stations, 5G core networks, user terminals (including 5G communication modules) and edge computing nodes. The system supports large-scale IoT device access, high-speed data transmission, low latency and wide coverage.

[0055] 5G base station (gNodeB):

[0056] Collaboration between macro base stations and small base stations: In 5G communication systems, macro base stations provide wide-area network coverage, and small base stations are used to enhance signal strength and network capacity in densely populated areas. Macro base stations and small base stations are connected through a backhaul network to achieve collaborative work.

[0057] Collaboration between millimeter wave and Sub-6GHz: The base station supports millimeter wave and Sub-6GHz frequency bands, using the Sub-6GHz frequency band to provide wide coverage and using millimeter wave to provide ultra-high transmission rate and capacity.

[0058] 5G Core Network (5GC):

[0059] Cloud Core Network: The 5G core network uses virtualization technology to virtualize network functions (NFV) and implement flexible scheduling and resource management of network functions through software-defined networking (SDN). This design can dynamically adjust network resources according to actual needs to ensure flexibility and scalability.

[0060] Network Slicing: The core network supports network slicing technology, which divides different network slices according to different application scenarios (such as the Internet of Things, high-definition video, AR / VR, etc.) to ensure the service quality of each application.

[0061] MEC (Edge Computing): Introducing edge computing (MEC) nodes to delegate some computing tasks to the edge of the network, improve response speed and reduce latency. It is particularly suitable for scenarios that are sensitive to latency, such as unmanned driving and industrial control.

[0062] User Terminal (UE):

[0063] 5G communication module access: User terminals communicate with 5G networks through integrated 5G modules to achieve high-speed data upload and download. User terminals can be smartphones, IoT devices, industrial control equipment, and other types.

[0064] Terminal perception and intelligent scheduling: The system can intelligently schedule communication resources based on the mobile speed, application type and network environment of the terminal device. Through AI algorithms, the system can predict user needs and adjust resource allocation in advance.

[0065] Transmission network:

[0066] High-speed fiber optic backhaul network: The base station and the core network are connected via high-speed fiber optic cables to achieve large data volume transmission and low-latency communication.

[0067] Transmission path optimization: Use the SDN control plane to dynamically optimize the transmission path to avoid congestion and ensure efficient transmission.

[0068] System features

[0069] Multi-connection support:

[0070] Multi-connection technology: The system supports multi-connection technology, allowing terminal devices to connect to multiple base stations at the same time, achieving seamless switching and load balancing. Especially in high-speed mobile scenarios (such as high-speed railways, unmanned driving, etc.), it ensures the continuity of communication.

[0071] Carrier aggregation: Through carrier aggregation technology, the system can combine multiple frequency bands to provide higher transmission bandwidth and improve the overall communication rate.

[0072] Smart Resource Management:

[0073] Dynamic spectrum sharing: Based on 5G spectrum sharing technology, the system can dynamically allocate spectrum resources and improve spectrum utilization according to network traffic and terminal device requirements.

[0074] AI-driven network optimization: By introducing AI algorithms, the system can monitor network status in real time, automatically adjust resource allocation and transmission paths according to traffic changes, device load, etc., to ensure service quality.

[0075] Security and Privacy Protection:

[0076] End-to-end encryption: Data transmission between terminals, base stations, and core networks is end-to-end encrypted to ensure user data security.

[0077] Network access control: The system uses strong authentication and network access control to prevent unauthorized device access.

[0078] 5G communication system application scenarios

[0079] Smart Manufacturing: In factories, 5G communication modules support real-time control, remote monitoring, data analysis, etc. of industrial equipment through high-speed connections and low latency, realizing smart manufacturing and industrial automation.

[0080] Internet of Vehicles and Autonomous Driving: 5G modules and systems support high-speed mobile Internet of Vehicles environments, providing low-latency road safety information, autonomous driving control command transmission, in-car entertainment and other functions.

[0081] Internet of Things (IoT): 5G communication systems can connect a large number of IoT devices, such as smart homes, urban sensing devices, environmental monitoring, etc., to ensure high-speed interconnection between devices.

[0082] Augmented reality / virtual reality (AR / VR): Through 5G modules and systems, AR / VR devices can achieve ultra-low latency interactive experience and are widely used in games, education, telemedicine and other fields.

[0083] The design of the 5G communication module and system combines efficient hardware integration, intelligent scheduling, dynamic resource management and security mechanisms, providing strong technical support for the high-speed, low-latency and wide-connected 5G network requirements. By supporting advanced technologies such as multi-band communication, carrier aggregation, and network slicing, the system has broad application prospects and can meet the needs of various scenarios such as the Internet of Things, smart cities, Internet of Vehicles, and industrial control.

[0084] To further optimize and improve the design of 5G communication modules and systems, and enhance their performance and adaptability.

[0085] Spectrum efficiency optimization

[0086] Dynamic spectrum allocation and carrier aggregation optimization

[0087] In 5G systems, multiple frequency bands can be used simultaneously through carrier aggregation (CA), which can improve overall bandwidth and data rate. However, spectrum resources are limited and must be managed efficiently. By introducing dynamic spectrum sharing technology, spectrum resources can be allocated according to real-time demand.

[0088] Optimization and improvements:

[0089] In scenarios where multiple users and devices communicate simultaneously, a spectrum resource scheduler is introduced to dynamically adjust spectrum allocation based on device usage, bandwidth requirements, and network load using machine learning algorithms.

[0090] Spectral efficiency formula:

[0091] The spectrum efficiency η is defined as the number of bits transmitted within a unit bandwidth. The optimized spectrum efficiency can be expressed as:

[0092]

[0093] Where: η is the spectrum efficiency (unit: bps / Hz); C is the channel capacity (bps); B is the bandwidth (Hz).

[0094] Dynamic spectrum allocation and carrier aggregation can maximize the utilization of B, thereby improving η. Intelligent scheduling of bandwidth resources can avoid spectrum waste and conflicts.

[0095] Dynamic channel selection and signal enhancement

[0096] In high-density user scenarios (such as stadiums, city squares, etc.), in order to further optimize spectrum utilization, the system can combine channel selection and beamforming technology to dynamically select the optimal channel and enhance coverage and communication performance through directional transmission signals.

[0097] The channel capacity formula can be expressed by Shannon's theorem as:

[0098]

[0099] Where C is the channel capacity (bps); B is the bandwidth (Hz); P is the signal power; and N0 is the noise power spectral density (W / Hz).

[0100] Through beamforming technology, the system can increase the signal power P, thereby increasing the channel capacity C and enhancing communication performance.

[0101] Low latency and edge computing optimization

[0102] Edge computing and data processing sinking

[0103] In order to reduce end-to-end latency, 5G systems can introduce edge computing (MEC) to move computing tasks to the nodes closest to users, which can reduce the path and time of data transmission and improve the response speed of the system.

[0104] Optimization and improvements:

[0105] In the 5G system, computing resources are dynamically allocated to edge nodes to adjust computing power according to real-time user needs. AI optimization algorithms are introduced to determine which computing tasks can be transferred to edge computing nodes.

[0106] Delay formula:

[0107] Total delay T total It can be decomposed into three parts: data transmission delay, edge computing processing delay and core network processing delay. After sinking more tasks to edge computing nodes, the total delay of the system can be reduced:

[0108]

[0109] After optimization:

[0110] (Reduces or avoids core network latency)

[0111] By reducing T core , the system latency is significantly reduced.

[0112] Adaptive queue management

[0113] In communication systems, queue delay is also an important factor. To reduce the delay caused by queue congestion, the system can dynamically adjust queue length, bandwidth allocation and task priority through adaptive queue management strategies.

[0114] Queuing delay formula:

[0115] The queue delay can be approximated by the small M / M / 1 queue model:

[0116]

[0117] Where: μ is the service rate (the number of tasks served per second), λ is the task arrival rate, and the intelligent scheduling algorithm optimizes queue management to ensure that μ is greater than λ, thereby reducing the queuing delay T queue .

[0118] Multi-user massive MIMO and network slicing optimization:

[0119] Improvements in Multi-User Massive MIMO:

[0120] Multi-user massive MIMO technology allows 5G base stations to serve multiple users simultaneously on the same frequency resources. This greatly improves spectrum utilization, but if not handled properly, it may cause interference. Therefore, by introducing adaptive beamforming and user scheduling strategies, interference between users can be minimized.

[0121] Optimization and improvements:

[0122] Intelligent algorithms are used to optimize beamforming for each user, dynamically adjusting beam direction and power. Multi-user scheduling algorithms are used to ensure that each user can transmit data in the best channel state.

[0123] SINR formula (Signal-to-Noise Ratio and Interference Ratio):

[0124]

[0125] Where: P s is the signal power; P i is the interference power; N0 is the noise power. Through intelligent beamforming, the system can effectively improve P s and reduce P i , thereby improving the SINR value of each user and ensuring high-quality communication.

[0126] Dynamic management of network slices

[0127] 5G network slicing technology allows dedicated network slices to be provided for different application scenarios (such as IoT, AR / VR, and Internet of Vehicles). By dynamically adjusting slice resources, system resources can be maximized and overall system performance can be improved.

[0128] Optimization and improvements:

[0129] Use AI algorithms to dynamically schedule slice resources and adjust slice bandwidth, latency and other resource allocation in real time based on network load and device connection status.

[0130] Network slicing resource allocation model:

[0131] Slicing resources can be achieved by optimizing the objective function:

[0132]

[0133] Where: Ri is the amount of resources allocated to slice i; URi is the utility function of slice i, which is usually related to parameters such as bandwidth and delay; R total is the total resource limit.

[0134] By dynamically allocating resources through optimization algorithms, the system can balance the needs between different slices in real time and ensure the service quality of each application scenario.

[0135] Security and encryption optimization

[0136] Layered encryption and lightweight encryption algorithms

[0137] Although existing encryption algorithms are secure, they increase the computational burden of the communication system. In order to optimize the security of the 5G system, a layered encryption strategy is used to select different encryption levels based on the sensitivity of the data and the communication scenario. At the same time, lightweight encryption algorithms (such as elliptic curve encryption ECC) are introduced for resource-constrained devices (such as IoT terminals).

[0138] Optimization and improvements:

[0139] End-to-end encryption and layered encryption: Use different levels of encryption in different communication links (terminal to base station, base station to core network). Use strong encryption for low-latency, high-security scenarios, and use lightweight encryption for resource-constrained devices.

[0140] Encryption algorithm complexity optimization formula:

[0141] For lightweight encryption algorithms, the complexity can be expressed as:

[0142] C ECC =O(n 3 )

[0143] Where n is the key length. Compared with traditional RSA encryption (complexity O(n 4 ), ECC encryption significantly reduces the computational complexity and resource consumption while maintaining the same security level.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. 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 replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A 5G communication module, characterized in that: Includes RF front-end module, antenna system, processor and interface; The RF front-end module includes RF amplifier, filter, mixer and power amplifier; The antenna system includes a multi-band antenna that supports Sub-6GHz and millimeter wave in the 5G frequency band, and uses beamforming technology in the millimeter wave band; Supports 3GPP 5G NR standards, including frequency division duplex and time division duplex modes, as well as carrier aggregation and dual-connectivity baseband processors. The baseband processor is responsible for processing 5G signals, including modulation and demodulation, encoding and decoding, and protocol processing; 2. A 5G communication system applicable to a 5G communication module according to claim 1, characterized in that: The 5G communication system is mainly composed of 5G base stations, 5G core network, user terminals, including 5G communication modules and edge computing nodes.

3. The 5G communication system of the 5G communication module according to claim 2, characterized in that: The 5G base station includes the collaboration of macro base stations and small base stations. The macro base stations and small base stations are connected through a backhaul network to achieve collaborative work. Millimeter waves and Sub-6GHz collaborate. The base stations support millimeter wave and Sub-6GHz frequency bands, using the Sub-6GHz frequency band to provide wide coverage and millimeter waves to provide ultra-high transmission rates and capacities.

4. The 5G communication system of the 5G communication module according to claim 2, characterized in that: The 5G core network includes a cloud core network. The 5G core network uses virtualization technology to virtualize network functions, and implements flexible scheduling and resource management of network functions through software-defined networking. The slicing technology divides different network slices according to different application scenarios, and edge computing introduces edge computing nodes to delegate some computing tasks to the edge of the network.

5. The 5G communication system of the 5G communication module according to claim 2, characterized in that: The user terminal includes 5G communication module access. The user terminal communicates with the 5G network through an integrated 5G module. The system can intelligently schedule communication resources based on the mobile speed, application type and network environment of the terminal device. Through AI algorithms, the system can predict user needs and adjust resource allocation in advance.

6. The 5G communication system of the 5G communication module according to claim 2, characterized in that: In scenarios where multiple users and devices communicate simultaneously, a spectrum resource scheduler is introduced to dynamically adjust spectrum allocation based on device usage, bandwidth requirements, and network load using machine learning algorithms.

7. The 5G communication system of the 5G communication module according to claim 2, characterized in that: The spectrum efficiency η is defined as the number of bits transmitted within a unit bandwidth. The optimized spectrum efficiency can be expressed as: Where: η is the spectrum efficiency, unit: bps / Hz, C is the channel capacity bps, and B is the bandwidth Hz.

8. The 5G communication system of the 5G communication module according to claim 2, characterized in that: In high-density user scenarios, in order to further optimize spectrum utilization, the system combines channel selection and beamforming technology to dynamically select the optimal channel and enhance coverage and communication performance through directional transmission signals; the channel capacity formula can be expressed by Shannon's theorem as follows: Where: C is the channel capacity in bps, B is the bandwidth in Hz, P is the signal power, and N0 is the noise power spectral density in W / Hz.

9. The 5G communication system of the 5G communication module according to claim 2, characterized in that: In the edge computing, the system sinks the computing tasks to the node closest to the user, dynamically allocates computing resources to the edge nodes, adjusts the computing power according to the real-time needs of the user, and introduces AI optimization algorithms to determine which computing tasks can be sunk to the edge computing nodes; Total delay T total It can be decomposed into three parts: data transmission delay, edge computing processing delay and core network processing delay. After more tasks are transferred to edge computing nodes, the total delay of the system can be reduced: After optimization: By reducing T core , the system latency is significantly reduced.

10. The 5G communication system of the 5G communication module according to claim 2, characterized in that: The system dynamically adjusts queue length, bandwidth allocation, and task priority through an adaptive queue management strategy. The queue delay can be approximately calculated using a small M / M / 1 queue model: Where: μ is the service rate, the number of tasks served per second; λ is the task arrival rate. The intelligent scheduling algorithm is used to optimize queue management to ensure that μ is greater than λ, thereby reducing the queuing delay T queue .

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