Internet of Things access control method and related equipment

Abstract

The invention provides an Internet of Things access control method and related equipment, and the method comprises the steps: carrying out the signal-to-interference ratio constraint of the throughput of a main communication channel in the Internet of Things through a main channel gain between a base station and user equipment in the Internet of Things, and obtaining a lower limit guarantee value of the throughput of the main communication channel in the Internet of Things; performing joint convex optimization on the access parameter of each candidate access terminal according to the channel interference feature between each candidate access terminal and the user equipment to obtain the interference coupling feature of the access parameter in each candidate access terminal; and performing constraint optimization on an access indication vector between the user and each candidate access terminal through each interference coupling feature and a lower limit guarantee value, and screening a target access terminal from the plurality of candidate access terminals by using the access indication vector after constraint optimization, and sending an access authorization of user access and a resource configuration instruction to the target access terminal. Based on the above scheme, the joint optimization switching of the access terminal can be realized when the Internet of Things is in the congestion state.

Description

Technical Field

[0001] This application relates to the field of Internet of Things (IoT) control technology, and more specifically, to an IoT access control method and related equipment. Background Technology

[0002] The Internet of Things (IoT) refers to connecting various physical devices, sensors, and smart terminals to the Internet through network technology, enabling information exchange and communication between devices. IoT devices can collect and transmit data in real time, allowing users to remotely monitor and manage device status, thereby improving the level of intelligence and operational efficiency. Common IoT access methods include wireless networks, Bluetooth, and cellular networks, and are widely used in fields such as smart homes, industrial automation, and smart cities.

[0003] When the main channel is busy, existing technologies employ passive waiting or simple retry mechanisms, which can easily lead to connection interruptions for user equipment due to channel contention failures or high latency introduced by multiple retransmissions, making it difficult to meet real-time service requirements. In scenarios with dense multi-terminal access, existing technologies lack global interference coordination capabilities. Each terminal often adjusts its transmission power independently based on local information, resulting in accumulated inter-channel interference and a sharp deterioration in the signal-to-noise ratio. If the power control algorithm only aims at single-link optimization, it may cause power ramp-up problems, where terminals continuously increase their transmission power to combat interference, which in turn exacerbates the overall system interference level and reduces spectral efficiency. At the same time, fixed access thresholds or static resource allocation strategies are difficult to adapt to dynamic load changes, further causing throughput fluctuations and energy waste. Therefore, how to achieve joint optimized switching of access terminals when the Internet of Things (IoT) is in a congested state has become a challenge for the industry. Summary of the Invention

[0004] This application provides an Internet of Things (IoT) access control method and related equipment, which can realize joint optimized switching of access terminals when the IoT is in a congested state.

[0005] In a first aspect, this application provides an Internet of Things (IoT) access control method, comprising: When the main communication channel in the Internet of Things (IoT) accessed by the user is in a busy state, multiple candidate access terminals are selected from the IoT based on the location and historical access information of the user equipment, and the channel status of each candidate access terminal is obtained. The main channel gain between the base station and user equipment in the Internet of Things (IoT) is determined. The throughput of the main communication channel in the IoT is constrained by the signal-to-dryness ratio (SDR) using the main channel gain and the noise power spectral density of the IoT, thereby obtaining the lower limit guaranteed value of the throughput of the main communication channel in the IoT. The channel interference characteristics between each candidate access terminal and user equipment are determined by the maximum transmit power constraint and available energy constraint in each channel state. Then, the access parameters of each candidate access terminal are jointly optimized based on the channel interference characteristics and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal. Initialize the access indication vector between the user and each candidate access terminal, constrain and optimize each access indication vector by various interference coupling characteristics and the lower limit guarantee value, use the constrained and optimized access indication vector to select the target access terminal from the multiple candidate access terminals, and send the user access authorization and resource configuration instructions to the target access terminal.

[0006] In some embodiments, determining the main channel gain between a base station and a user equipment in the Internet of Things specifically includes: The base station sends a known reference signal to the user equipment, and the user equipment measures the power information of the received reference signal; The path loss and channel response matrix of the reference signal are calculated using the power information and the transmit power of the reference signal. The main channel gain between the base station and user equipment in the Internet of Things is determined based on the path loss and the channel response matrix.

[0007] In some embodiments, the signal-to-dryness ratio constraint on the throughput of the main communication channel in the Internet of Things (IoT) is applied using the main channel gain and the noise power spectral density of the IoT to obtain the lower limit guaranteed value of the throughput of the main communication channel in the IoT. Specifically, this includes: Obtain noise power spectral density and system bandwidth information for the Internet of Things; The signal-to-dryness ratio of the main communication channel in the Internet of Things is determined by the main channel gain and the noise power spectral density. The lower limit of the guaranteed throughput of the main communication channel in the Internet of Things is determined based on the signal-to-dryness ratio and the system bandwidth information.

[0008] In some embodiments, determining the channel interference characteristics between each candidate access terminal and user equipment by using the maximum transmit power constraint and available energy constraint in each channel state specifically includes: For each candidate access terminal, obtain the interference channel gain from the candidate access terminal to the user; The maximum interference power between the candidate access terminal and the user equipment is determined by the maximum transmit power constraint in the channel state of the candidate access terminal and the interference channel gain. Based on the maximum interference power and the available energy constraints in the channel state of the candidate access terminal, the channel interference characteristics between the candidate access terminal and the user equipment are determined, thereby obtaining the channel interference characteristics between each candidate access terminal and the user equipment.

[0009] In some embodiments, joint convex optimization is performed on the access parameters of each candidate access terminal based on the interference characteristics of each channel and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal. Specifically, this includes: For each candidate access terminal, obtain the channel interference characteristics between the candidate access terminal and the user equipment, as well as the target channel capacity for IoT access. The constraints for joint convex optimization are determined based on the channel interference characteristics. The optimization objective of joint convex optimization is determined by the target channel capacity of IoT access; Based on the constraints and the optimization objective, the access parameters of the candidate access terminals are solved by convex optimization to obtain the interference coupling characteristics of the access parameters in the candidate access terminals, and then the interference coupling characteristics of the access parameters in each candidate access terminal are obtained.

[0010] In some embodiments, initializing the access indication vector between the user and each candidate access terminal involves initializing all access indication vectors between the user and each candidate access terminal to 0.

[0011] In some embodiments, constraining and optimizing each access indication vector using various interference coupling characteristics and the lower limit guarantee value specifically includes: For each candidate access terminal, initialize a constraint optimization model based on bipartite graph matching; The interference coupling characteristics of the access parameters in the candidate access terminals are used as the constraint optimization model in the constraint optimization model; The lower limit guarantee value is used as a guarantee constraint term in the constraint optimization model; Constraint optimization models are used to constrain access indication vectors, thereby completing the constraint optimization of each access indication vector.

[0012] Secondly, this application provides an Internet of Things (IoT) access control system, comprising: The acquisition module is used to filter out multiple candidate access terminals from the Internet of Things based on the location and historical access information of the user equipment when the main communication channel of the Internet of Things accessed by the user is in a busy state, and to obtain the channel status of each candidate access terminal. The processing module is used to determine the main channel gain between the base station and the user equipment in the Internet of Things (IoT), and to apply a signal-to-dryness ratio constraint to the throughput of the main communication channel in the IoT using the main channel gain and the noise power spectral density of the IoT, thereby obtaining the lower limit guaranteed value of the throughput of the main communication channel in the IoT. The processing module is also used to determine the channel interference characteristics between each candidate access terminal and the user equipment through the maximum transmit power constraint and available energy constraint in each channel state, and then perform joint convex optimization on the access parameters of each candidate access terminal according to the channel interference characteristics and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal. The execution module is used to initialize the access indication vector between the user and each candidate access terminal, perform constraint optimization on each access indication vector through various interference coupling characteristics and the lower limit guarantee value, use the constraint-optimized access indication vector to select the target access terminal from the multiple candidate access terminals, and send the user access authorization and resource configuration instructions to the target access terminal.

[0013] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, so that the computer device performs the above-described Internet of Things access control method.

[0014] Fourthly, this application provides a computer-readable storage medium storing instructions or code that, when executed on a computer, cause the computer to implement the aforementioned Internet of Things access control method.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: In the IoT access control method and related equipment provided in this application, when the main communication channel of the IoT accessed by the user is in a busy state, multiple candidate access terminals are selected from the IoT based on the location and historical access information of the user equipment, and the channel state of each candidate access terminal is obtained; the main channel gain between the base station and the user equipment in the IoT is determined, and the throughput of the main communication channel in the IoT is constrained by the signal-to-dryness ratio using the main channel gain and the noise power spectral density of the IoT to obtain the lower limit guaranteed value of the throughput of the main communication channel in the IoT; the channel interference characteristics between each candidate access terminal and the user equipment are determined by the maximum transmit power constraint and available energy constraint in each channel state, and then the access parameters of each candidate access terminal are jointly convex optimized according to each channel interference characteristic and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal; the access indication vector between the user and each candidate access terminal is initialized, and each access indication vector is constrained and optimized by each interference coupling characteristic and the lower limit guaranteed value, and the target access terminal is selected from the multiple candidate access terminals using the constrained and optimized access indication vector, and the user access authorization and resource configuration instruction is sent to the target access terminal.

[0016] Therefore, in this application, the access indication vector between the user and each candidate access terminal is initialized. Each access indication vector is then constrained and optimized using various interference coupling characteristics and the lower limit guarantee value. The optimized access indication vector is then used to select the target access terminal from the multiple candidate access terminals, and access authorization and resource configuration instructions for user access are sent to the target access terminal. Firstly, determining the lower limit guarantee value ensures the minimum throughput guarantee of the main channel, thereby maintaining core communication quality under congestion. When the main channel is busy, directly switching to a candidate terminal may further degrade the main channel performance due to excessive resource allocation, even affecting other high-priority services. By calculating the lower limit guarantee value of the main channel, the minimum available throughput between the base station and user equipment can be ensured, thus guaranteeing that the Internet of Things can consider the main channel during handover decisions. To ensure stability and avoid overall network performance degradation due to blind switching, this approach not only optimizes resource allocation but also implements tiered service protection, ensuring that core communication is unaffected by congestion-induced switching. Furthermore, by determining interference coupling characteristics, the dynamic interference relationship between candidate terminals can be obtained, thereby optimizing access selection and improving overall spectrum efficiency. In congested scenarios with multiple terminals competing for access, traditional methods often only consider the quality of a single link channel while ignoring mutual interference between terminals, leading to a decline in overall system performance after switching. By quantifying the potential interference impact on the main channel and other terminals after access, not only can the candidate terminal with the least interference be selected, but higher spectrum reuse efficiency can also be maintained after switching, significantly improving the overall communication quality of IoT in high-load scenarios. In summary, based on the above scheme, joint optimized switching of access terminals can be achieved when IoT is in a congested state. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is an exemplary flowchart of an IoT access control method according to some embodiments of this application; Figure 2 This is a flowchart of the IoT management protocol shown in some embodiments of this application; Figure 3 This is a flowchart illustrating the constraint optimization process according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of an Internet of Things access control system according to some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device implementing an Internet of Things access control method according to some embodiments of this application. Detailed Implementation

[0019] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] refer to Figure 1 The figure is an exemplary flowchart of an IoT access control method according to some embodiments of this application. The IoT access control method mainly includes the following steps: In step 101, when the main communication channel in the Internet of Things (IoT) accessed by the user is in a busy state, multiple candidate access terminals are selected from the IoT based on the location and historical access information of the user equipment, and the channel status of each candidate access terminal is obtained.

[0021] It should be noted that in this application, channel state refers to the set of physical layer parameters between the terminal device and the base station; main communication channel busy state refers to the state in which the load of the main communication link between the current base station and the user equipment has reached a preset threshold and cannot directly process new access requests; candidate access terminals are a set of IoT terminal devices within the communication range of the user equipment and that meet the basic access conditions.

[0022] In practical implementation, firstly, the base station in the Internet of Things (IoT) continuously monitors the resource occupancy rate of the main communication channel. A channel is considered busy when any of the following conditions are detected: channel utilization exceeds 80%, the length of the data queue to be transmitted exceeds 70% of the buffer capacity, or the number of current users reaches 90% of the system's maximum capacity. The IoT console periodically sends channel status indications to user equipment via physical layer control signaling. These indications contain bit-coded information about the current load level, which includes idle, lightly busy, and heavily busy. Before initiating an access request, user equipment must first decode the channel status indication. Once it confirms that the main communication channel is heavily busy, it triggers the candidate access terminal screening process. Then, the IoT console maintains a list of all terminal devices... Based on the location and historical access information of the equipment, when the candidate access terminal screening process is triggered, the real-time location coordinates of the user equipment are determined by the received signal strength indication triangulation method. Then, a circular area with a radius of 300 meters is delineated with the real-time location coordinates as the center. From the historical access information, the terminal devices with the top 50% of successful access times in the past 30 days in this area are selected as candidate access terminals, thus obtaining multiple candidate access terminals. Finally, for each candidate access terminal, the maximum transmit power, available energy, and thermal noise power spectral density of the candidate access terminal are obtained from the IoT control console. The set of maximum transmit power, available energy, and thermal noise power spectral density is used as the channel state of the candidate access terminal. The channel state of each candidate access terminal can be obtained in the above way.

[0023] In some embodiments, reference Figure 2 The figure described herein is a flowchart of the Internet of Things (IoT) management protocol according to some embodiments of this application. The figure illustrates the workflow of the Simple Network Management Protocol (SNMP) in the Internet of Things. In the figure, multiple agent programs (labeled A) run SNMP server programs, connect to the Internet, and communicate with a management program (labeled M) through network protocols. The management program is responsible for monitoring and managing these agent programs, while the network administrator controls and maintains the entire network through the management program. Dashed arrows indicate the communication paths of the network protocol, and solid arrows indicate the communication paths of the SNMP protocol.

[0024] In step 102, the main channel gain between the base station and user equipment in the Internet of Things (IoT) is determined. The throughput of the main communication channel in the IoT is constrained by the signal-to-dryness ratio (SDR) using the main channel gain and the noise power spectral density of the IoT, thereby obtaining the lower limit guaranteed value of the throughput of the main communication channel in the IoT.

[0025] In some embodiments, determining the main channel gain between a base station and a user equipment in an Internet of Things (IoT) can be achieved through the following steps: The base station sends a known reference signal to the user equipment, and the user equipment measures the power information of the received reference signal; The path loss and channel response matrix of the reference signal are calculated using the power information and the transmit power of the reference signal. The main channel gain between the base station and user equipment in the Internet of Things is determined based on the path loss and the channel response matrix.

[0026] It should be noted that, in this application, the main channel gain represents the signal transmission efficiency of the main propagation path between the base station and the user equipment; the reference signal is a pilot signal with fixed power and a specific waveform transmitted by the base station, used for channel characteristic measurement; path loss characterizes the degree of power attenuation of the signal during propagation; and the channel response matrix describes the amplitude and phase changes of the signal after passing through the multipath channel.

[0027] In specific implementation, firstly, the base station sends a known reference signal to the user equipment. The user equipment measures the power information of the received reference signal, which can be achieved as follows: the base station sends the known reference signal to the user equipment, and the user equipment measures all received power values ​​of the reference signal, thus using the set of all received power measurements as the power information of the reference signal. Then, the path loss and channel response matrix of the reference signal can be calculated using the power information and the transmit power of the reference signal, which can be achieved as follows: the transmit power of the reference signal is obtained from the base station, and the sum of the differences between each received power measurement value and the transmit power in the power information is used as... In other embodiments, to improve the accuracy of the path loss calculation, an antenna gain correction factor can be considered during the calculation of the reference signal path loss. This antenna gain correction factor includes compensation values ​​for the transmit antenna gain and the user equipment receive antenna gain obtained from the base station's control console; this is not limited here. The user equipment performs a sliding cross-correlation operation on each received reference signal and a standard received signal stored locally as the reference signal. The peak point in the cross-correlation result is taken as the detection correlation peak, thus obtaining multiple detection correlation peaks. The time delay position corresponding to each detection correlation peak is taken as the arrival time of the corresponding multipath component, and the magnitude of the complex amplitude of each detection correlation peak is taken as the reference value. Due to the amplitude attenuation of the path, the phase angle of each detected correlation peak corresponds to the phase shift of the carrier. By statistically averaging the arrival time, amplitude attenuation, and phase shift over multiple consecutive symbol periods, the arrival time, amplitude, and phase information of each multipath component can be obtained. Matrix filling techniques are used to reconstruct the parameters of each discrete multipath component into a complete channel response matrix, where the number of rows and columns of the channel response matrix corresponds to the number of transmit and receive antennas, respectively. During the calculation, invalid multipath components with delays exceeding the cyclic prefix length are automatically filtered out. Finally, based on the path loss and the channel response matrix, the main channel gain between the base station and user equipment in the Internet of Things is determined. The gain can be achieved in the following way: perform multipath analysis on the channel response matrix, search for the amplitude values ​​of all path components in the channel response matrix, and determine the path component with the largest magnitude as the main path component. Use the complex form of the main path component as the channel coefficient, and then use the calculation result of 10^(path loss value / 10) as the compensation factor. The product of the magnitude of the channel coefficient and the compensation factor is used as the main channel gain between the base station and the user equipment in the Internet of Things. In other embodiments, to ensure reliability, the system will synchronously monitor the phase stability of the main path component. When a phase jump is detected to exceed the threshold, the re-measurement process will be automatically triggered. This is not limited here.

[0028] In some embodiments, the lower limit guaranteed value of the throughput of the main communication channel in the Internet of Things (IoT) can be obtained by constraining the signal-to-dryness ratio (SDR) of the main communication channel through the main channel gain and the noise power spectral density of the IoT using the following steps: Obtain noise power spectral density and system bandwidth information for the Internet of Things; The signal-to-dryness ratio of the main communication channel in the Internet of Things is determined by the main channel gain and the noise power spectral density. The lower limit of the guaranteed throughput of the main communication channel in the Internet of Things is determined based on the signal-to-dryness ratio and the system bandwidth information.

[0029] It should be noted that in this application, the lower limit guarantee value is the minimum effective data transmission rate that the main communication channel must maintain; noise power spectral density refers to the noise power per unit bandwidth; system bandwidth information refers to the effective frequency range allocated to the main communication channel; signal-to-interference-plus-noise ratio is the ratio of the main channel signal power to the interference noise power, reflecting the signal transmission quality.

[0030] In specific implementation, firstly, obtaining the noise power spectral density and system bandwidth information of the Internet of Things (IoT) can be achieved as follows: the base station samples environmental noise during idle periods of the receiver front-end circuit, uses Fast Fourier Transform to convert the time-domain noise signal into a frequency-domain power spectrum, performs statistical analysis on the power spectrum of 100 consecutive sampling periods, removes outliers, and takes the 95th percentile as a stable estimate of the noise power spectral density; the system bandwidth information parameter is directly obtained from the base station's resource management module, and this value is determined during the network planning stage, including channel bandwidth information such as the protection bandwidth; then, determining the signal-to-dryness ratio (SDR) of the main communication channel in the IoT through the main channel gain and the noise power spectral density can be achieved as follows: the product of the main channel gain and the base station's current actual transmit power is taken as the theoretical receive power of the main channel, thereby scanning the phase... The interference signal strength in adjacent frequency bands is measured, and the result of integrating and summing the measured interference signal strength and noise power spectral density is taken as the total interference noise power. The logarithm of the theoretical received power of the main channel divided by the total interference noise power is taken as the signal-to-interference-plus-noise ratio (SIR / NNR) of the main communication channel in the Internet of Things (IoT). Finally, the lower limit guarantee value of the throughput of the main communication channel in the IoT can be determined based on the SIR / NNR and the system bandwidth information in the following way: obtain the correspondence table between SIR / NNR and spectral efficiency from the modulation and coding scheme of the base station's communication protocol, input the measured SIR / NNR into the correspondence table, obtain the theoretical spectral efficiency under the current channel conditions through linear interpolation, multiply the spectral efficiency by the system bandwidth as the theoretical maximum throughput, and then take 60% of the theoretical maximum throughput as the lower limit guarantee value of the throughput of the main communication channel in the IoT.

[0031] In step 103, the channel interference characteristics between each candidate access terminal and the user equipment are determined by the maximum transmit power constraint and available energy constraint in each channel state. Then, based on the channel interference characteristics and the target channel capacity of IoT access, the access parameters of each candidate access terminal are jointly convex optimized to obtain the interference coupling characteristics of the access parameters in each candidate access terminal.

[0032] In some embodiments, determining the channel interference characteristics between each candidate access terminal and user equipment by means of the maximum transmit power constraint and available energy constraint in each channel state can be achieved by the following steps: For each candidate access terminal, obtain the interference channel gain from the candidate access terminal to the user; The maximum interference power between the candidate access terminal and the user equipment is determined by the maximum transmit power constraint in the channel state of the candidate access terminal and the interference channel gain. Based on the maximum interference power and the available energy constraints in the channel state of the candidate access terminal, the channel interference characteristics between the candidate access terminal and the user equipment are determined, thereby obtaining the channel interference characteristics between each candidate access terminal and the user equipment.

[0033] It should be noted that, in this application, the channel interference characteristic is a quantitative indicator that comprehensively reflects the terminal's interference capability and availability; the interference channel gain represents the signal transmission loss characteristics from the candidate access terminal to the user equipment, reflecting the degree of attenuation of the interference signal; and the maximum interference power is the theoretical interference intensity generated at the user equipment when the candidate terminal operates at its maximum transmit power.

[0034] In specific implementation, firstly, for each candidate access terminal, the interference channel gain from the candidate access terminal to the user can be obtained in the following way: for each candidate access terminal, the interference channel gain from the IoT central control station is obtained; then, the maximum interference power between the candidate access terminal and the user equipment can be determined by the maximum transmit power constraint in the channel state of the candidate access terminal and the interference channel gain in the following way: the maximum transmit power is obtained from the channel state of the candidate access terminal as the maximum transmit power constraint in the channel state of the candidate access terminal, and the result of multiplying the maximum transmit power constraint by the square of the modulus of the interference channel gain is taken as the theoretical maximum interference power. During the calculation, antenna pattern correction needs to be considered, that is, according to the relative azimuth angle between the terminal and the user, the horizontal and vertical plane patterns of the terminal antenna are queried, and the corresponding gain adjustment factor is introduced. To cope with emergencies, the IoT central control station adds a 3dB emergency margin to the calculation result to ensure that even in the most unfavorable scenario... The system can accurately assess the impact of interference, thus using the product of the theoretical maximum interference power and the gain adjustment factor as the maximum interference power between the candidate access terminal and the user equipment. Finally, based on the maximum interference power and the available energy constraints in the channel state of the candidate access terminal, the channel interference characteristics between the candidate access terminal and the user equipment are determined, thereby obtaining the channel interference characteristics between each candidate access terminal and the user equipment. This can be achieved by: normalizing the maximum interference power according to the sensitivity range of the user equipment receiver and mapping it to a scoring range of 0-100 as the interference intensity score; obtaining the available energy from the channel state of the candidate access terminal as the available energy constraint in the channel state of the candidate access terminal, and mapping this available energy constraint to a rating range of 0-10 as the energy sustainability rating; thus, the set of the interference intensity score and the energy sustainability rating is used as the channel interference characteristics between the candidate access terminal and the user equipment. The channel interference characteristics between each candidate access terminal and the user equipment can be obtained in the above manner.

[0035] In some embodiments, the interference coupling characteristics of the access parameters of each candidate access terminal are obtained by performing joint convex optimization on the access parameters of each candidate access terminal based on the interference characteristics of each channel and the target channel capacity of IoT access. This can be achieved by the following steps: For each candidate access terminal, obtain the channel interference characteristics between the candidate access terminal and the user equipment, as well as the target channel capacity for IoT access. The constraints for joint convex optimization are determined based on the channel interference characteristics. The optimization objective of joint convex optimization is determined by the target channel capacity of IoT access; Based on the constraints and the optimization objective, the access parameters of the candidate access terminals are solved by convex optimization to obtain the interference coupling characteristics of the access parameters in the candidate access terminals, and then the interference coupling characteristics of the access parameters in each candidate access terminal are obtained.

[0036] It should be noted that, in this application, interference coupling characteristics are a set of parameters in the optimization results that reflect the interference relationship between terminals; the target channel capacity is the minimum data transmission rate required by IoT services; the constraint condition is a mathematical inequality that restricts the solution space of the optimization problem to ensure that the solution meets the actual system requirements; the optimization objective is a performance index that a convex optimization problem needs to maximize or minimize.

[0037] In specific implementation, firstly, for each candidate access terminal, obtaining the channel interference characteristics between the candidate access terminal and the user equipment, as well as the target channel capacity for IoT access, can be achieved in the following way: for each candidate access terminal, obtain the channel interference characteristics between the candidate access terminal and the user equipment, and obtain the target channel capacity for IoT access from the IoT control center; secondly, determining the constraints of joint convex optimization through the channel interference characteristics can be achieved in the following way: using the channel interference characteristics as the constraints of joint convex optimization; then, determining the optimization objective of joint convex optimization through the target channel capacity for IoT access can be achieved in the following way: using the target channel capacity for IoT access as the optimization objective of joint convex optimization; finally, performing convex optimization on the access parameters of the candidate access terminals according to the constraints and the optimization objective, to obtain the target channel capacity for IoT access terminals. The interference coupling characteristics of access parameters, and thus the interference coupling characteristics of access parameters in each candidate access terminal, can be obtained in the following way: The primal-dual interior-point method is used for optimization. This algorithm iteratively approximates the optimal solution. In each iteration: first, the dual gap of the current point is calculated; then, the search direction is determined; and finally, the step size is selected. The system sets three convergence conditions: the rate of change of the objective function, the rate of change of variables, and the degree of constraint violation. The iteration terminates when any one of these conditions is met. After the solution is obtained, the interference coupling characteristics are extracted from the Lagrange multipliers of the optimal solution. These include: the marginal contribution of each terminal's power adjustment to the system capacity, the interference sensitivity coefficient between terminals, and the correlation gradient between power and interference. After normalization, these characteristics are used as the interference coupling characteristics of access parameters in the candidate access terminals. The interference coupling characteristics of access parameters in each candidate access terminal can then be obtained in this way.

[0038] It should be noted that, in this application, joint convex optimization is a mathematical optimization method used to find the optimal solution of a convex objective function under convex constraints. In this IoT access control scenario, the access control problem of multiple candidate terminals is modeled as a unified convex optimization problem. The optimization objective is to maximize the total channel capacity of the system while meeting the target capacity requirements. The constraints include the maximum transmit power limit of each terminal, energy constraints, and interference constraints on the main channel. The interference constraint is quantified by the channel interference characteristics. Through convex optimization theories such as Lagrange duality, the original problem is transformed into a dual problem that can be solved efficiently. The solution is iteratively obtained using algorithms such as the interior point method or gradient projection method, and finally the optimal power allocation scheme of each terminal is output. The interference coupling characteristics are the set of parameters reflecting the mutual interference relationship between terminals in the optimization results. Its mathematical essence is the correlation gradient between the optimization variables and the interference constraints. This method can guarantee the global optimal solution and the computational complexity is controllable.

[0039] In step 104, the access indication vector between the user and each candidate access terminal is initialized. Each access indication vector is constrained and optimized using various interference coupling characteristics and the lower limit guarantee value. The optimized access indication vector is used to select the target access terminal from the multiple candidate access terminals, and the user access authorization and resource configuration instructions are sent to the target access terminal.

[0040] In practice, the access indication vector between the user and each candidate access terminal is initialized to 0.

[0041] In some embodiments, each access indication vector is constrained and optimized using various interference coupling characteristics and the lower limit guarantee value, with reference to... Figure 3 The figure is a schematic diagram of the process of implementing constraint optimization in some embodiments of this application. The constraint optimization in this embodiment can be implemented by the following steps: In step 1041, for each candidate access terminal, a constraint optimization model based on bipartite graph matching is initialized; In step 1042, the interference coupling characteristics of the access parameters in the candidate access terminal are used as the constraint optimization model in the constraint optimization model; In step 1043, the lower limit guarantee value is used as a guarantee constraint term in the constraint optimization model; In step 1044, the access indication vector is constrained using a constraint optimization model, thereby completing the constraint optimization of each access indication vector.

[0042] It should be noted that in this application, the constrained optimization model in the context of IoT communication specifically refers to a mathematical programming model based on bipartite graph matching. This constrained optimization model abstracts candidate terminals and communication resources into two types of vertices in a bipartite graph. It solves for the optimal matching scheme by defining constraints and optimization objectives. The left vertex set represents candidate terminals, and the right vertex set represents available communication resources. The edge weights are determined by interference coupling characteristics. The lower bound guarantee value is transformed into vertex capacity constraints to ensure the quality of service of the main channel. The optimization objective is to maximize resource utilization while satisfying interference constraints. This constrained optimization model transforms the discrete matching problem into a continuous convex optimization problem by introducing slack variables, uses the Lagrange multiplier method to handle complex constraints, and finally outputs the access decision (access indication vector) for each terminal. It can guarantee the lower bound of system performance and effectively coordinate the interference coupling relationship between terminals. Compared with traditional methods, it has higher solution efficiency and better scalability.

[0043] Furthermore, in another aspect of this application, in some embodiments, this application provides an Internet of Things (IoT) access control system, with reference to... Figure 4 The figure is a schematic diagram of the structure of an Internet of Things (IoT) access control system according to some embodiments of this application. The IoT access control system includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described below: The acquisition module 201 in this application is mainly used to filter out multiple candidate access terminals from the Internet of Things based on the location and historical access information of the user equipment when the main communication channel in the Internet of Things accessed by the user is in a busy state, and to obtain the channel status of each candidate access terminal. Processing module 202, in this application, is used to determine the main channel gain between the base station and the user equipment in the Internet of Things (IoT), and to constrain the throughput of the main communication channel in the IoT by the main channel gain and the noise power spectral density of the IoT, so as to obtain the lower limit guaranteed value of the throughput of the main communication channel in the IoT. It should be noted that the processing module 202 is also used to determine the channel interference characteristics between each candidate access terminal and the user equipment through the maximum transmit power constraint and available energy constraint in each channel state, and then perform joint convex optimization on the access parameters of each candidate access terminal according to the channel interference characteristics and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal. The execution module 203 in this application is mainly used to initialize the access indication vector between the user and each candidate access terminal, optimize each access indication vector by means of various interference coupling characteristics and the lower limit guarantee value, use the optimized access indication vector to select the target access terminal from the multiple candidate access terminals, and send the user access authorization and resource configuration instructions to the target access terminal.

[0044] The foregoing has detailed examples of the IoT access control method and related devices provided in the embodiments of this application. It is understood that, in order to achieve the above functions, the corresponding devices include hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0045] In some embodiments, this application also provides a computer device, the computer device including a memory and a processor, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, so that the computer device performs the above-described Internet of Things access control method.

[0046] In some embodiments, reference Figure 5 The dashed lines in the figure indicate that the unit or module is optional. This figure is a structural schematic diagram of a computer device implementing an IoT access control method according to an embodiment of this application. The IoT access control method described in the above embodiments can... Figure 5 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device may be a terminal device, a server or a chip.

[0047] Processor 301 can be a general-purpose processor or a special-purpose processor. For example, processor 301 can be a central processing unit (CPU), which can be used to control computer devices, execute software programs, and process data from software programs. The computer device may also include a communication unit 305 for inputting (receiving) and outputting (transmitting) signals.

[0048] For example, the computer device may be a chip, and the communication unit 305 may be the input and / or output circuit of the chip, or the communication unit 305 may be the communication interface of the chip, which may be a component of a terminal device, network device or other device.

[0049] For example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0050] The computer device may include one or more memories 302 storing a program 304. The program 304 can be executed by a processor 301 to generate instructions 303, causing the processor 301 to execute the method described in the above method embodiments according to the instructions 303. Optionally, the memory 302 may also store data (such as a target audit model). Optionally, the processor 301 may also read data stored in the memory 302, which may be stored at the same storage address as the program 304, or it may be stored at a different storage address than the program 304.

[0051] The processor 301 and memory 302 can be configured separately or integrated together, for example, integrated on the system on chip (SOC) of the terminal device.

[0052] It should be understood that each step of the above method embodiment can be completed by hardware logic circuits or software instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0053] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0054] For example, in some embodiments, this application also provides a computer-readable storage medium storing instructions or code that, when executed on a computer, cause the computer to implement the above-described IoT access control method.

[0055] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0056] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. An Internet of Things (IoT) access control method, characterized in that, Includes the following steps: When the main communication channel in the Internet of Things (IoT) accessed by the user is in a busy state, multiple candidate access terminals are selected from the IoT based on the location and historical access information of the user equipment, and the channel status of each candidate access terminal is obtained. The main channel gain between the base station and user equipment in the Internet of Things (IoT) is determined. The throughput of the main communication channel in the IoT is constrained by the signal-to-dryness ratio (SDR) using the main channel gain and the noise power spectral density of the IoT, thereby obtaining the lower limit guaranteed value of the throughput of the main communication channel in the IoT. The channel interference characteristics between each candidate access terminal and user equipment are determined by the maximum transmit power constraint and available energy constraint in each channel state. Then, the access parameters of each candidate access terminal are jointly optimized based on the channel interference characteristics and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal. Initialize the access indication vector between the user and each candidate access terminal, constrain and optimize each access indication vector by various interference coupling characteristics and the lower limit guarantee value, use the constrained and optimized access indication vector to select the target access terminal from the multiple candidate access terminals, and send the user access authorization and resource configuration instructions to the target access terminal.

2. The method as described in claim 1, characterized in that, Determining the main channel gain between the base station and user equipment in the Internet of Things (IoT) specifically includes: The base station sends a known reference signal to the user equipment, and the user equipment measures the power information of the received reference signal; The path loss and channel response matrix of the reference signal are calculated using the power information and the transmit power of the reference signal. The main channel gain between the base station and user equipment in the Internet of Things is determined based on the path loss and the channel response matrix.

3. The method as described in claim 1, characterized in that, By applying a signal-to-dryness ratio constraint to the throughput of the main communication channel in the Internet of Things (IoT) using the main channel gain and the noise power spectral density of the IoT, the lower limit guaranteed value of the throughput of the main communication channel in the IoT is obtained, specifically including: Obtain noise power spectral density and system bandwidth information for the Internet of Things; The signal-to-dryness ratio of the main communication channel in the Internet of Things is determined by the main channel gain and the noise power spectral density. The lower limit of the guaranteed throughput of the main communication channel in the Internet of Things is determined based on the signal-to-dryness ratio and the system bandwidth information.

4. The method as described in claim 1, characterized in that, The channel interference characteristics between each candidate access terminal and user equipment are determined by the maximum transmit power constraint and available energy constraint in each channel state, specifically including: For each candidate access terminal, obtain the interference channel gain from the candidate access terminal to the user; The maximum interference power between the candidate access terminal and the user equipment is determined by the maximum transmit power constraint in the channel state of the candidate access terminal and the interference channel gain. Based on the maximum interference power and the available energy constraints in the channel state of the candidate access terminal, the channel interference characteristics between the candidate access terminal and the user equipment are determined, thereby obtaining the channel interference characteristics between each candidate access terminal and the user equipment.

5. The method as described in claim 1, characterized in that, Based on the interference characteristics of each channel and the target channel capacity for IoT access, joint convex optimization is performed on the access parameters of each candidate access terminal to obtain the interference coupling characteristics of the access parameters in each candidate access terminal, specifically including: For each candidate access terminal, obtain the channel interference characteristics between the candidate access terminal and the user equipment, as well as the target channel capacity for IoT access. The constraints for joint convex optimization are determined based on the channel interference characteristics. The optimization objective of joint convex optimization is determined by the target channel capacity of IoT access; Based on the constraints and the optimization objective, the access parameters of the candidate access terminals are solved by convex optimization to obtain the interference coupling characteristics of the access parameters in the candidate access terminals, and then the interference coupling characteristics of the access parameters in each candidate access terminal are obtained.

6. The method as described in claim 1, characterized in that, The access indication vector between the user and each candidate access terminal is initialized to 0.

7. The method as described in claim 1, characterized in that, The constraint optimization of each access indication vector based on various interference coupling characteristics and the lower limit guarantee value specifically includes: For each candidate access terminal, initialize a constraint optimization model based on bipartite graph matching; The interference coupling characteristics of the access parameters in the candidate access terminals are used as the constraint optimization model in the constraint optimization model; The lower limit guarantee value is used as a guarantee constraint term in the constraint optimization model; Constraint optimization models are used to constrain access indication vectors, thereby completing the constraint optimization of each access indication vector.

8. An Internet of Things (IoT) access control system, characterized in that, include: The acquisition module is used to filter out multiple candidate access terminals from the Internet of Things based on the location and historical access information of the user equipment when the main communication channel of the Internet of Things accessed by the user is in a busy state, and to obtain the channel status of each candidate access terminal. The processing module is used to determine the main channel gain between the base station and the user equipment in the Internet of Things (IoT), and to apply a signal-to-dryness ratio constraint to the throughput of the main communication channel in the IoT using the main channel gain and the noise power spectral density of the IoT, thereby obtaining the lower limit guaranteed value of the throughput of the main communication channel in the IoT. The processing module is also used to determine the channel interference characteristics between each candidate access terminal and the user equipment through the maximum transmit power constraint and available energy constraint in each channel state, and then perform joint convex optimization on the access parameters of each candidate access terminal according to the channel interference characteristics and the target channel capacity of IoT access to obtain the interference coupling characteristics of the access parameters in each candidate access terminal. The execution module is used to initialize the access indication vector between the user and each candidate access terminal, perform constraint optimization on each access indication vector through various interference coupling characteristics and the lower limit guarantee value, use the constraint-optimized access indication vector to select the target access terminal from the multiple candidate access terminals, and send the user access authorization and resource configuration instructions to the target access terminal.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory is used to store computer programs, and the processor is used to call and run the computer programs from the memory, causing the computer device to perform the Internet of Things access control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions or code that, when executed on a computer, cause the computer to implement the IoT access control method as described in any one of claims 1 to 7.

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