Equipment access control method and device, equipment, storage medium and program product
By acquiring MTC device status data and adjusting access control parameters, the problems of low success rate and long latency for large-scale device access were solved, enabling devices to successfully access at appropriate times and locations, thus improving the overall network performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-10
- Publication Date
- 2026-04-14
AI Technical Summary
In large-scale machine-type communication scenarios, the success rate of device access is low and the time delay is long. Existing technologies are difficult to effectively manage the access of a large number of devices, resulting in access conflicts and resource waste.
By acquiring the status data of MTC devices within the network coverage area, the device groups and backbone node devices are identified, and the access control parameters are adjusted based on network performance indicators using the access control network to optimize the device access process.
It improved the success rate of device access, reduced retries and resource waste, lowered access latency, and optimized network performance.
Smart Images
Figure CN121865373A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of Internet of Things (IoT) technology, and in particular to a device access control method, apparatus, device, storage medium, and program product. Background Technology
[0002] With the development of mobile wireless networks, Machine-Type Communication (MTC) faces the challenge of large-scale device access. To support connection densities of millions, large-scale MTC scenarios require efficient management of a large number of device accesses to enable information interaction between people and things, and between things themselves.
[0003] However, in large-scale machine and equipment access scenarios, when a large number of user devices send access requests to the base station almost simultaneously, the base station may face severe overload pressure, which will directly lead to a decrease in access success rate and an increase in terminal device power consumption. Summary of the Invention
[0004] This application provides a device access control method, apparatus, device, storage medium, and program product to at least solve the problems of low device access success rate and long access time when accessing a large number of devices.
[0005] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, embodiments of this application provide a device access control method, comprising: acquiring device status data of multiple machine-type communication (MTC) devices within a network coverage area; determining at least one MTC device group and backbone node devices in each MTC device group based on the device status data of the multiple MTC devices; inputting device access information and access control parameters of each MTC device group to an access control network, adjusting the access control parameters according to network performance indicators through the access control network to obtain target access control parameters for each MTC device group; and controlling the MTC devices in each MTC device group to access the backbone node devices according to the target access control parameters.
[0006] Secondly, embodiments of this application provide a device access control apparatus, comprising: a data acquisition module for acquiring device status data of multiple MTC devices within a network coverage area; an information acquisition module for determining at least one MTC device group and backbone node devices in each MTC device group based on the device status data of the multiple MTC devices; a parameter acquisition module for inputting device access information and access control parameters of each MTC device group to an access control network, and adjusting the access control parameters according to network performance indicators through the access control network to obtain target access control parameters for each MTC device group; and an access control module for controlling the MTC devices in each MTC device group to access the backbone node devices according to the target access control parameters.
[0007] Thirdly, embodiments of this application provide a network device, the network device including a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the steps of the method described in the first aspect above.
[0008] Fourthly, embodiments of this application provide a computer-readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect above.
[0009] Fifthly, embodiments of this application provide a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the steps of the method described in the first aspect above.
[0010] In this embodiment, device status data of multiple machine-type communication (MTC) devices within the network coverage area are acquired. Based on the device status data of the multiple MTC devices, at least one MTC device group and backbone node devices in each MTC device group are determined. The device access information and access control parameters of each MTC device group are input to the access control network. The access control network adjusts the access control parameters according to network performance indicators to obtain the target access control parameters for each MTC device group. Based on the target access control parameters, the MTC devices in each MTC device group are controlled to access the backbone node devices. In this way, by determining the MTC device group based on the device status data and adjusting the access control parameters for each MTC device group according to network performance indicators, it is possible to ensure that MTC devices successfully access the network at the appropriate time and location, reduce retries and resource waste caused by device access failures, improve the success rate of large-scale device access, reduce access latency, and thus optimize the overall network performance.
[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0012] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0013] Figure 1 A flowchart illustrating a device access control method provided in some embodiments of this application is shown; Figure 2 A flowchart illustrating a device access control method provided in other embodiments of this application is shown; Figure 3 This application provides schematic diagrams of the A2C network training process in some embodiments; Figure 4 This application shows a schematic diagram of the structure of a device access control device provided in some embodiments; Figure 5 A schematic diagram of the structure of a network device provided in some embodiments of this application is shown. Detailed Implementation
[0014] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0015] In scenarios involving large-scale machine-type communication device access, the reasons for the decrease in device access success rate include: 1) The deployment density of MTC devices far exceeds that of general communication devices, making it easier for a large number of devices to cause access conflicts due to communication interference between MTC devices when accessing the network. 2) Due to the large number of MTC devices and the scarcity of access resources, when a large number of MTC devices simultaneously initiate access to the base station, some MTC devices will inevitably cause access conflicts due to selecting the same access resources. In severe cases, this can lead to network congestion and cause all MTC devices to fail to access.
[0016] Therefore, through optimized access control mechanisms and MTC device grouping, it is possible to quickly respond to and manage access requests from millions of low-power, low-cost devices, thereby ensuring the effective utilization of spectrum resources and maximizing data transmission efficiency.
[0017] Device grouping is currently the primary means of resolving access conflicts caused by the dense deployment of MTC devices. Device grouping simplifies the network structure of the cell access network by assigning MTC devices within a cell to different groups, thereby reducing the number of device access conflicts within the cell. Current grouping methods mainly include prioritizing devices based on their service load, allocating MTC devices with high service arrival rates to high-priority groups for priority network access; and classifying devices based on their service load, distinguishing between human-to-human (H2H) communication devices and machine-to-machine (M2M) communication devices, configuring different access resources to reduce interference between H2H and M2M devices and improve access success rates. However, as the number of access devices increases, the challenges faced by the access network become increasingly severe, with decreased device success rates and increased access latency. Regarding device grouping, as the number of MTC devices increases, assigning a single device to multiple groups can lead to MTC devices not finding access targets, increasing algorithm complexity. When grouping based on device service load, lower-priority devices experience higher access latency, and the reusability of access resources is lower during device grouping, resulting in lower access success rates for resource-constrained groups.
[0018] Large-scale device access control technologies primarily employ methods such as Access Control Barring (ACB), Backoff Indictor (BI), Dynamic ACB, and resource allocation. The ACB control scheme essentially assigns an ACB factor to both the MTC device and the base station. If the MTC device's ACB factor is less than the base station's ACB factor, the device is allowed to initiate access; otherwise, access is denied, thus reducing the number of devices initiating access per Random Access Opportunity (RAO). The Dynamic ACB scheme adjusts the ACB factor based on the predicted number of access devices. The BI algorithm assigns a BI value to a device that hasn't received a RAR after initiating an access request, allowing the device to re-initiate access after a waiting period to mitigate access conflicts. Resource allocation aims to subdivide or reuse access resources to improve resource utilization. For example, grouping terminal devices with different service types and allocating access resources accordingly can improve access success rates to some extent. The ACB scheme is only suitable for situations with a small number of devices; the dynamic ACB scheme estimates the ACB factor based on the number of active devices in each access slot, but the existing estimation algorithm is relatively simple and cannot optimize access throughput performance; the window control scheme improves access success rate and reduces average access latency by controlling the number of devices initiating access in each access slot, but does not consider the problem of insufficient access resources.
[0019] In summary, while the proposed solutions reduce the number of devices and access conflicts per access slot, they do not consider the impact of access resources and access latency. The high latency required for access makes it difficult to support the needs of large-scale machine-type communication random access.
[0020] To address the aforementioned problems in the device access control process, this application provides a device access control method. This method determines MTC device groups based on device status data and adjusts access control parameters for each MTC device group according to network performance indicators to ensure that MTC devices successfully access the network at the appropriate time and location, thereby reducing retries and resource waste caused by device access failures.
[0021] Please see Figure 1 , Figure 1 This document illustrates a flowchart of a device access control method provided in some embodiments of this application. The execution entity of this method can be a terminal device or a server. The terminal device can be a personal computer, a mobile terminal device such as a mobile phone or tablet, or a sampling terminal device used by a user. The server can be a standalone server or a server cluster composed of multiple servers. Furthermore, the server can be a backend server for a specific service or a backend server for a platform or application (e.g., an IoT platform, an edge computing platform, a large-scale sensor network, etc.). This embodiment uses a server as the execution entity for illustration. For the case of a terminal device, the following related content can be used for processing, which will not be repeated here. Figure 1 As shown, the method 100 may include the following steps: Step 101: Obtain device status data of multiple machine-type communication (MTC) devices within the network coverage area.
[0022] In one exemplary embodiment, the aforementioned machine-type communication (MTC) devices include water and electricity meter reading devices, smart home devices, remote monitoring devices, etc. These MTC devices connect to the base station and network using a contention-based access mechanism. Once an MTC device successfully accesses the network, they can communicate with each other. Device status data of multiple MTC devices within the network coverage area is acquired; this device status data includes parameters such as signal strength information and historical communication frequencies.
[0023] Step 102: Based on the device status data of multiple MTC devices, determine at least one MTC device group and the backbone node devices in each MTC device group.
[0024] Continuing with the above embodiments, based on the device status data in step 101, multiple MTC devices are grouped to obtain at least one MTC device group and backbone node devices within each MTC device group. For example, the channel quality score of the MTC devices can be determined based on parameters such as signal strength information and historical communication frequency. Multiple MTC devices are then clustered based on the channel quality score to obtain an MTC device group, and subsequently, the backbone node devices within the MTC device group are determined. These backbone node devices need to possess strong processing capabilities, stable connections, and the ability to cover members within the group.
[0025] Step 103: Input the device access information and access control parameters of each MTC device group into the access control network. The access control network adjusts the access control parameters according to the network performance indicators to obtain the target access control parameters for each MTC device group.
[0026] Continuing with the above embodiments, the device access information includes device identification information, device type, current connection status, access request time, signal strength information, device access information, and historical access control information. The access control parameters include the ACB factor and the size of the backoff window. The collected device access information and access control parameters are input to the access control network. The access control network dynamically adjusts the access control parameters of each MTC device group based on network performance indicators such as network load, latency, packet loss rate, and throughput. After calculation and optimization, the target access control parameters for each MTC device group are obtained.
[0027] Step 104: Based on the target access control parameters, control the MTC devices in each MTC device group to access the backbone node devices.
[0028] Continuing with the above embodiments, control commands are issued to each MTC device group according to the target access control parameters; after receiving the control commands, each MTC device attempts to access the backbone node device of its group according to the target access control parameters.
[0029] In some possible implementations, during the access process, the access success rate and network status can be monitored, and the access control parameters can be further fine-tuned based on the feedback information to achieve closed-loop optimization.
[0030] This application provides a device access control method. It acquires device status data of multiple machine-type communication (MTC) devices within a network coverage area; based on the device status data, it determines at least one MTC device group and backbone node devices within each MTC device group; it inputs the device access information and access control parameters of each MTC device group into an access control network; the access control network adjusts the access control parameters according to network performance indicators to obtain target access control parameters for each MTC device group; and based on the target access control parameters, it controls the MTC devices in each MTC device group to access the backbone node devices. By determining MTC device groups based on device status data and adjusting access control parameters for each MTC device group according to network performance indicators, it ensures that MTC devices successfully access the network at the appropriate time and location, reducing retries and resource waste caused by device access failures, improving the success rate of large-scale device access, reducing access latency, and thus optimizing the overall network performance.
[0031] In some embodiments, step 102 above, determining at least one MTC device group and backbone node devices in each MTC device group based on device status data of multiple MTC devices, includes: Based on the device status data of multiple MTC devices, the multiple MTC devices are grouped to obtain an initial MTC device group; based on the feature state vectors of multiple MTC devices and the first reward function, the initial MTC device group is adjusted to obtain at least one MTC device group, and the backbone node devices in each MTC device group are determined; wherein, the feature state vector is determined based on the device status data; the first reward function is determined based on the intra-group communication efficiency, resource utilization, and service quality within the MTC device group.
[0032] In an exemplary embodiment, multiple MTC devices can be grouped based on device status data such as signal strength and communication frequency to obtain an initial MTC device group. A feature state vector is determined based on the device status data. This feature state vector includes signal strength, device priority, etc., where the device priority indicates the priority level of the MTC device sending a connection request. For example, assuming there are N MTC devices, the feature state vector can be represented as: ; in, The values can be categorized into three levels: high, medium, and low, represented by the numerical values H, M, and L, as follows: ; Device priority is defined based on Quality of Service (QoS) requirements, taking into account three aspects: latency sensitivity, reliability requirements, and data volume. The device priority calculation formula is as follows: ; in, , and It is a weighting factor. It is a normalization function. This indicates the maximum allowable delay; the smaller the value, the higher the priority. This indicates the minimum probability of successful transmission; the higher the probability, the greater the priority. This represents the average data packet size; a larger value indicates a higher priority.
[0033] Furthermore, based on the characteristic state vectors of multiple MTC devices and the first reward function, the initial MTC device group is adjusted, for example, by merging, splitting, or moving devices, to obtain at least one MTC device group, and the backbone node devices in each MTC device group are determined; wherein, the first reward function is determined based on the intra-group communication efficiency, resource utilization, and service quality within the MTC device group.
[0034] In some possible implementations, a packet network model can be constructed based on neural networks, reinforcement learning, etc. This model identifies at least one MTC device group and the backbone node devices within each MTC device group. For example, a packet network model can be built based on an A2C network, which can be placed inside the base station. After receiving synchronization signaling from the base station, the MTC devices feed back their signal strength information to the base station. This packet network model includes an Actor network and a Critic network. The Actor network evaluates priorities based on the feedback information and groups devices according to their priorities, ensuring that the grouping results improve network access performance. In the MTC device grouping scenario, two variables are defined: state s and action a. State s can be represented as a vector, namely the aforementioned device state vector, which includes characteristics of all MTC devices, such as signal strength and device priority.
[0035] action This represents the strategy for grouping devices. It can be defined as a combination of dividing devices into K groups. For example, an action can be represented as a grouping scheme. The action space includes the following actions: Initial grouping The grouping state at the start of A2C model training; Combination Select two existing groups and merge them into a new group with a new number; Group splitting Based on the signal strength of the devices, the selected devices are reassigned to two or more groups; Equipment movement : Specify device Move to the target group; remain unchanged : Does not change the current group status.
[0036] Grouping schemes can be used express, The entire action space A can be represented as a set of operations that modify the current grouping scheme G: ; Each action a∈A causes a change in the grouping scheme G. The Actor network selects the optimal action based on the current state s. ,in It is the action value function evaluated by the Critic network.
[0037] To guide the A2C algorithm's learning, a first reward function is defined. The expression for the first reward function is as follows: ; in, , , It is a weighting factor. To improve intra-group communication efficiency, For resource utilization, For service quality.
[0038] When the A2C network performs an action, it monitors the effect of the new grouping and determines the reward function accordingly. Calculate scores. A positive reward is given if the new grouping leads to better network performance (e.g., lower average latency, higher success rate); conversely, a negative penalty is given. Finally, periodically evaluate whether the model performance has stabilized and decide whether to continue or terminate training.
[0039] After the Actor network completes its action, the system updates the Critic network using its current state and reward. The advantage function is then calculated. : ; in, This is the current reward. It is a discount factor. It is the Critic network's value estimate of the current state. It is the new state obtained after performing an action.
[0040] After evaluating the current action, the Critic network updates its parameters using mean squared error and the Actor network's parameters using the advantage function, as follows: ; ; in, It is the learning rate.
[0041] After updating the network parameters, repeat the steps of adjusting the MTC device group and updating the A2C network parameters until convergence or the predetermined number of iterations is reached to ensure optimal grouping results and the minimum number of overlapping devices, thereby reducing access interference between devices and enabling devices within the group to have sufficient access resources to initiate access to the backbone node device.
[0042] In some possible implementations, the above-mentioned grouping of multiple MTC devices to obtain an initial MTC device group includes: Select a predetermined number of initial backbone node devices from multiple MTC devices; determine the channel quality score of each MTC device based on its signal strength and communication frequency; group the multiple MTC devices according to the channel quality score to obtain the initial MTC device group.
[0043] In one exemplary embodiment, after the terminal device is powered on, when the base station groups multiple MTC devices within a cell, it first creates a network topology map of the cell access network based on the communication range and location of the MTC devices, thus identifying multiple MTC devices located within the same communication range. After obtaining the network topology map, the signal strength of the MTC devices is used... Communication frequency of MTC devices Grouping, the specific grouping process is as follows: 1) Computing devices and The calculation formula is as follows: ; ; 2) Calculate the channel quality score for the MTC device. : ; in, and It is a weighting factor used to balance the effects of signal strength and communication frequency.
[0044] 3) Select the number of clusters and randomly select One MTC device serves as the backbone node device, and then the remaining devices are calculated. Based on the distance to all backbone node devices, the device is assigned to the group containing the nearest backbone node. The nearest group can be represented as: ; For each device Indicates a group, It is a group The backbone node equipment.
[0045] 4) After all devices are assigned, the backbone node devices in each group are recalculated. The comprehensive score of the new backbone node is the one that is closest to the average comprehensive score of the devices in that group.
[0046] In some embodiments, the access control network described above includes an action network and an evaluation network; in step 103, the device access information and access control parameters of each MTC device group are input to the access control network, and the access control network adjusts the access control parameters according to network performance indicators to obtain the target access control parameters for each MTC device group, including: Step 1031: Obtain the access status vector, which includes the device access information and historical access control information of the MTC device group.
[0047] In an exemplary embodiment, after grouping multiple MTC devices, an access state vector is obtained. This access state vector includes device access information and historical access control information for the MTC device group. The device access information includes the number of currently connected devices, the type and number of currently active devices, etc., and the historical access control information includes historical access control parameters and network performance metrics. Exemplarily, an access state vector is defined. as follows: ; in, Indicates the number of currently connected devices. This indicates the type and number of currently active devices. This indicates past access control parameters and network performance metrics (such as packet loss rate, latency, etc.).
[0048] Step 1032: By inputting the access state vector into the action network, the adjustment action of the access control parameters is obtained, and the network performance index of the adjustment action is determined by the evaluation network.
[0049] Continuing with the above embodiments, the A2C algorithm can be used to control the access of each group of devices. A Critic network evaluates the network performance for different access control parameters, and an Actor network dynamically adjusts and optimizes these parameters. The Actor and Critic networks can be structured using a Deep Neural Network (DNN), with the input layer being a state vector. The network has two fully connected hidden layers with ReLU activation function; the Actor network output layer is a Softmax layer that outputs the action probability distribution; the Critic network output layer is a single neuron that outputs the state value.
[0050] action The adjustment of the access control parameters can be represented as follows: ; in, Indicates the current ACB factor. This indicates the size of the current backoff window.
[0051] Step 1033: Determine the second reward function based on the network performance indicators, and adjust the parameters of the action network and the evaluation network according to the second reward function until the access control network meets the preset convergence conditions, and obtain the target access control parameters.
[0052] Continuing with the above embodiments, the reward function can enhance the A2C algorithm learning and can be designed based on the effect of access control. Specifically, the second reward function is expressed as follows: ; in, It is in time network throughput, It is in time packet loss rate, It is in time The average delay.
[0053] In some possible implementations, the above convergence conditions include the number of iterations of the access control network reaching a preset threshold; or the function value of the second reward function converging to the target reward value.
[0054] Continuing with the above embodiments, the parameters of the Actor and Critic networks are set. and Initialize access state And access control parameters. Based on the current access state vector. The reward value of the second reward function is calculated, and the Critic network calculates the advantage function. .
[0055] ; Based on the current state, the Critic network awards rewards and updates both the Critic network and the Actor network accordingly, as follows: ; ; This continues until convergence or the predetermined number of iterations is reached. During training, the convergence of the A2C algorithm needs to be checked periodically. This can be done through the second reward function. The trend of the reward function's change can be used to determine whether the algorithm has converged. Generally, when the average value of the reward function fluctuates within a certain range and no longer increases significantly, the algorithm can be considered to have converged.
[0056] In some embodiments, step 104 above, controlling the MTC devices in each MTC device group to access the backbone node device, includes: The system controls MTC devices in each MTC device group to use the same number of preambles to access the backbone node device, and achieves MTC device access by matching the device identification information of the backbone node device with the group identification information of the MTC device that initiated the access request.
[0057] In some exemplary embodiments, a pre-amble (PA) scheme is introduced, enabling MTC devices within each MTC device group to use the same number of pre-ambles to access the backbone node device (i.e., cluster head device), thereby improving the utilization rate of the pre-amble. To ensure that the backbone node device accurately identifies the access device, each MTC device carries packet identification information, such as a packet identifier number, when initiating an access request. When a backbone node device receives an access request from an MTC device, it matches its own device identification information with the packet identification information of the MTC device that initiated the access request. The matching result is as follows: ; in: This refers to the equipment identification information of backbone node devices; This indicates whether the device identifier information of the MTC device initiating the access request is the same as that of the backbone node device. If they are the same, it means that the MTC device initiating the access request and the backbone node device are in the same group, and the device is allowed to request access from the backbone node device with the same device identifier information. The backbone node device initiates an access request.
[0058] In an exemplary embodiment, taking the base station as the executing entity of the above-described device access control method as an example, such as... Figure 2 As shown, the device access control method may include the following steps: Step 201: The terminal is powered on, and the base station starts the A2C training mode; Step 202: Obtain device status data of multiple machine-type communication (MTC) devices within the network coverage area; based on the device status data of multiple MTC devices, determine at least one MTC device group and the backbone node devices in each MTC device group; specifically, the Actor network executes a grouping strategy, and the Critic network evaluates the strategy; update parameters until the grouping training time is reached, and obtain at least one MTC device group and the backbone node devices in each MTC device group. Step 203: Input the device access information and access control parameters of each MTC device group into the access control network. The access control network adjusts the access control parameters according to network performance indicators to obtain the target access control parameters for each MTC device group. Specifically, the access control network can be constructed based on the A2C network. The A2C network includes an Actor network and a Critic network. The Actor network executes the grouping strategy, and the Critic network evaluates the strategy. Update the parameters until the grouping training time is reached to obtain the target access control parameters for each MTC device group. Step 204: The base station broadcasts an access control command to each MTC device in each MTC device group. The access control command includes the target access control parameters. Step 205: The MTC device initiates an access request to connect to the backbone node device in its group; the process ends.
[0059] These include the aforementioned MTC devices for water and electricity meter reading, smart home devices, and remote monitoring devices. The training process for the A2C network is as follows: Figure 3 As shown in the image.
[0060] Please refer to Figure 4. Figure 4 This application provides a schematic diagram of the structure of a device access control device according to some embodiments. This device access control device can achieve the following: Figure 1 or Figure 2 All or part of the contents of the illustrated embodiment, the device is connected to the control device 400, including: Data acquisition module 410 is used to acquire device status data of multiple MTC devices within the network coverage area; The device grouping module 420 is used to determine at least one MTC device group and backbone node devices in each MTC device group based on the device status data of the plurality of MTC devices. The parameter adjustment module 430 is used to input the device access information and access control parameters of each MTC device group to the access control network, and adjust the access control parameters according to the network performance indicators through the access control network to obtain the target access control parameters of each MTC device group. The access control module 440 is used to control the MTC devices in each of the MTC device groups to access the backbone node device according to the target access control parameters.
[0061] In some embodiments, the device grouping module 420, when determining at least one MTC device group and backbone node devices in each MTC device group based on the device status data of the plurality of MTC devices, is specifically configured to: Based on the device status data of the multiple MTC devices, the multiple MTC devices are grouped to obtain an initial MTC device group; Based on the feature state vectors of the multiple MTC devices and the first reward function, the initial MTC device group is adjusted to obtain at least one MTC device group, and the backbone node devices in each MTC device group are determined; wherein, the feature state vectors are determined based on the device state data; the first reward function is determined based on the intra-group communication efficiency, resource utilization, and service quality within the MTC device group.
[0062] In some possible implementations, the device status data includes signal strength and communication frequency; the device grouping module 420, when grouping the multiple MTC devices according to their device status data to obtain an initial MTC device group, is specifically used for: Select a predetermined number of initial backbone node devices from the plurality of MTC devices; The channel quality score for each MTC device is determined based on its signal strength and communication frequency. The multiple MTC devices are grouped according to the channel quality score to obtain an initial MTC device group.
[0063] In some embodiments, the access control network includes an action network and an evaluation network; the parameter adjustment module 430, when inputting device access information and access control parameters of each MTC device group to the access control network, and adjusting the access control parameters according to network performance indicators through the access control network to obtain target access control parameters for each MTC device group, is specifically used for: Obtain the access status vector, which includes the device access information and historical access control information of the MTC device group; By inputting the access state vector into the action network, the adjustment action of the access control parameters is obtained, and the network performance index of the adjustment action is determined by the evaluation network. A second reward function is determined based on the network performance indicators. The parameters of the action network and the evaluation network are adjusted according to the second reward function until the access control network meets the preset convergence conditions, and the target access control parameters are obtained.
[0064] In some possible implementations, the above convergence conditions include the number of iterations of the access control network reaching a preset threshold; or, the function value of the second reward function converges to the target reward value.
[0065] In some embodiments, when the access control module 440 controls the MTC devices in each of the MTC device groups to access the backbone node device according to the target access control parameters, it is specifically used for: The system controls the MTC devices in each MTC device group to use the same number of preambles to access the backbone node device, and achieves the access of the MTC devices by matching the device identification information of the backbone node device with the group identification information of the MTC device that initiated the access request.
[0066] This application provides a device access control apparatus, including a data acquisition module, a device grouping module, a parameter adjustment module, and an access control module. The data acquisition module acquires device status data of multiple MTC devices within the network coverage area. The device grouping module determines at least one MTC device group and backbone node devices in each MTC device group based on the device status data. The parameter adjustment module inputs the device access information and access control parameters of each MTC device group to the access control network, and adjusts the access control parameters according to network performance indicators through the access control network to obtain the target access control parameters for each MTC device group. The access control module controls the MTC devices in each MTC device group to access the backbone node devices according to the target access control parameters. In this way, by determining the MTC device group based on the device status data and adjusting the access control parameters for each MTC device group according to network performance indicators, it is possible to ensure that MTC devices successfully access the network at the appropriate time and location, reduce retries and resource waste caused by device access failures, improve the success rate of large-scale device access, reduce access latency, and thus optimize the overall network performance.
[0067] Figure 5The diagram illustrates the structure of a network device according to some embodiments of this application. Referring to the diagram, at the hardware level, the network device 500 includes a processor 510, and optionally includes an internal bus 520, a network interface 530, and a memory. The memory may include RAM 541, such as high-speed random-access memory (RAM), and may also include non-volatile memory 542, such as at least one disk storage device. Of course, the network device may also include other hardware required for other services.
[0068] The processor 510, network interface 530, and memory can be interconnected via an internal bus 520. This internal bus 520 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be categorized as an address bus, data bus, control bus, etc. For ease of illustration, only a single bidirectional arrow is used in this diagram, but this does not imply that there is only one bus or one type of bus.
[0069] The memory stores programs. Specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory 541 and non-volatile memory 542, and provides instructions and data to the processor 510.
[0070] Processor 510 reads the corresponding computer program from non-volatile memory 542 into memory and then runs it, forming a device for locating the target user at the logical level. Processor 510 executes the program stored in memory and specifically performs the following: Figure 1 or Figure 2 The methods disclosed in the embodiments shown achieve the functions and beneficial effects of the methods described in the preceding method embodiments, and will not be repeated here.
[0071] The above is as stated in this application. Figure 1 or Figure 2The methods disclosed in the illustrated embodiments can be applied to or implemented by processor 510. Processor 510 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the hardware of processor 510 or by instructions in software form. The processor 510 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.
[0072] The computer device can also execute the methods described in the preceding method embodiments and achieve the functions and beneficial effects of the methods described in the preceding method embodiments, which will not be repeated here.
[0073] Of course, in addition to software implementation, the network device of this application does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.
[0074] This application also proposes a computer-readable storage medium that stores one or more programs, which, when executed by a network device including multiple applications, cause the network device to perform... Figure 1 or Figure 2 The methods disclosed in the embodiments shown achieve the functions and beneficial effects of the methods described in the preceding method embodiments, and will not be repeated here.
[0075] The computer-readable storage medium mentioned above includes read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc.
[0076] Furthermore, embodiments of this application also provide a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, implement the following process: Figure 1 or Figure 2 The methods disclosed in the embodiments shown achieve the functions and beneficial effects of the methods described in the preceding method embodiments, and will not be repeated here.
[0077] This application's embodiments can be applied to various network device collaboration or interconnection scenarios, including: collaboration and interconnection between mobile phones and laptops / tablets; collaboration and interconnection between mobile sampling terminals and smart TVs / monitors; collaboration and interconnection between mobile phones or tablets and in-vehicle entertainment systems; collaboration and interconnection between mobile sampling terminals and smart conferencing systems, etc. This satisfies users' diverse needs in smart home, smart office, and smart travel scenarios.
[0078] In summary, the above description is merely a preferred embodiment of this application and does not limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.
[0079] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.
[0080] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.
[0081] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0082] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.
Claims
1. A device access control method, characterized in that, include: Acquire device status data of multiple machine-type communication (MTC) devices within the network coverage area; Based on the device status data of the plurality of MTC devices, at least one MTC device group and the backbone node devices in each MTC device group are determined. The device access information and access control parameters of each MTC device group are input to the access control network. The access control network adjusts the access control parameters according to network performance indicators to obtain the target access control parameters for each MTC device group. Based on the target access control parameters, control the MTC devices in each of the MTC device groups to access the backbone node devices.
2. The method according to claim 1, characterized in that, The step of determining at least one MTC device group and backbone node devices in each MTC device group based on the device status data of the plurality of MTC devices includes: Based on the device status data of the multiple MTC devices, the multiple MTC devices are grouped to obtain an initial MTC device group; Based on the feature state vectors of the multiple MTC devices and the first reward function, the initial MTC device group is adjusted to obtain at least one MTC device group, and the backbone node devices in each MTC device group are determined; wherein, the feature state vectors are determined based on the device state data; the first reward function is determined based on the intra-group communication efficiency, resource utilization, and service quality within the MTC device group.
3. The method according to claim 2, characterized in that, The device status data includes signal strength and communication frequency; the step of grouping the multiple MTC devices according to their device status data to obtain an initial MTC device group includes: Select a predetermined number of initial backbone node devices from the plurality of MTC devices; The channel quality score for each MTC device is determined based on its signal strength and communication frequency. The multiple MTC devices are grouped according to the channel quality score to obtain an initial MTC device group.
4. The method according to claim 1, characterized in that, The access control network includes an action network and an evaluation network; the step of inputting the device access information and access control parameters of each MTC device group into the access control network, and adjusting the access control parameters according to network performance indicators through the access control network to obtain the target access control parameters for each MTC device group includes: Obtain the access status vector, which includes the device access information and historical access control information of the MTC device group; By inputting the access state vector into the action network, the adjustment action of the access control parameters is obtained, and the network performance index of the adjustment action is determined by the evaluation network. A second reward function is determined based on the network performance indicators. The parameters of the action network and the evaluation network are adjusted according to the second reward function until the access control network meets the preset convergence conditions, and the target access control parameters are obtained.
5. The method according to claim 4, characterized in that, The convergence condition includes the number of iterations of the access control network reaching a preset threshold; or, the function value of the second reward function converges to the target reward value.
6. The method according to any one of claims 1 to 5, characterized in that, The control of MTC devices in each of the MTC device groups to access the backbone node device includes: The system controls the MTC devices in each MTC device group to use the same number of preambles to access the backbone node device, and achieves the access of the MTC devices by matching the device identification information of the backbone node device with the group identification information of the MTC device that initiated the access request.
7. A device access control device, characterized in that, include: The data acquisition module is used to acquire device status data of multiple MTC devices within the network coverage area; The device grouping module is used to determine at least one MTC device group and backbone node devices in each MTC device group based on the device status data of the multiple MTC devices. The parameter adjustment module is used to input the device access information and access control parameters of each MTC device group to the access control network, and adjust the access control parameters according to the network performance indicators through the access control network to obtain the target access control parameters of each MTC device group. The access control module is used to control the MTC devices in each of the MTC device groups to access the backbone node device according to the target access control parameters.
8. A network device, characterized in that, The network device includes a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the steps of the method as described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 6.
10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to perform the steps of the method as described in any one of claims 1 to 6.