User access method and system in a converged network, storage medium

Abstract

The application discloses a user access method and system in a communication and sensing calculation control fusion network, and a storage medium, comprising the following steps: collecting communication demands and sensing demands of a user; calculating uplink and downlink communication signal-to-interference-and-noise ratios and sensing signal-to-interference-and-noise ratios of each base station; calculating calculation load information of each base station; calculating priorities of each base station according to a utility function, and selecting a base station with the highest priority to access; performing constraint condition checking, if communication quality and calculation resource constraints are satisfied, the user accesses the base station, and the system state is updated. By evaluating the communication and sensing coverage capabilities of each base station and the current network communication and sensing calculation load, the base station most suitable for performing communication, sensing and calculation tasks is selected, so that the communication, sensing and calculation performance of the network can be effectively ensured, and network load balancing is realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of information processing, and particularly relates to a user access method and system in a sensing-computing integrated network and a storage medium. BACKGROUND

[0002] In the sensing-computing integrated network, users not only have traditional communication needs, but also need to perceive target information in the surrounding environment to support intelligent driving, augmented reality (AR), industrial automation and other application scenarios. Due to the limited computing resources of user equipment, directly performing a computing task locally may result in high energy consumption and delay. Therefore, users usually rely on a base station for computing offloading, offloading part or all of the computing task to the base station for processing, thereby improving the efficiency of task execution. The base station not only undertakes communication tasks, but also needs to perform sensing positioning, target detection, identification and other tasks, which puts higher requirements on its computing capability. Since task execution depends on low-latency, high-reliability transmission, high-precision sensing and real-time computing, the base station needs to have strong computing capability to simultaneously support communication and sensing tasks, thereby improving the sensing accuracy and real-time performance of task processing. With the growth of network size, a heterogeneous network architecture gradually emerges, and different base stations have different communication, sensing and computing capabilities. In this scenario, user equipment needs to select the optimal access point among multiple heterogeneous base stations to optimize communication latency, computing cost and sensing accuracy. Base station selection not only depends on communication link quality, but also is affected by computing resources and sensing capability. For example, a high-computing-capability base station is suitable for high-complexity tasks, and a high-sensing-accuracy base station is suitable for target detection tasks. In the sensing-computing integrated network, the base station can provide communication services for users while sensing targets around the users, and can process offloaded data of the users and sensed data, thereby generating and transmitting instructions in real time according to the obtained data. Most current access mechanisms mainly consider communication quality, ignoring the influence of sensing and computing capability, and are difficult to meet the needs of sensing-computing integration. However, in actual base station deployment scenarios, different base stations have different communication, sensing and computing capabilities, and there is a problem of unbalanced user access load, and users need to select the optimal access point according to the heterogeneous capabilities of base stations. SUMMARY

[0003] The technical problem to be solved by the application is to provide a user access method and system in a sensing-computing integrated network and a storage medium.

[0004] To achieve the above object, the application adopts the following technical scheme:

[0005] A user access method in a sensing-computing integrated network, comprising:

[0006] collecting communication needs and sensing needs of the user;

[0007] Based on the user's communication and perception requirements, calculate the uplink and downlink signal-to-interference-plus-noise ratio and the perception signal-to-interference-plus-noise ratio for each base station;

[0008] Calculate the computing load information of each base station based on the user's communication and perception needs;

[0009] The priority of each base station is calculated based on the utility function, and the base station with the highest priority is selected for access.

[0010] Perform a constraint check. If the communication quality and computing resource constraints are met, the user can access the base station, and the system status is updated.

[0011] As a preferred option, the utility function is:

[0012] ;

[0013] Where B is the user access load bias factor. , and These correspond to the uplink / downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR, respectively. and These correspond to the obtained communication computing load information and perception computing load information, respectively. , , , This represents the weighting factors of each parameter, and + + + .

[0014] The present invention also provides a user access system in a converged sensing, computing, and control network, comprising:

[0015] The first processing module is used to collect users' communication and perception requirements;

[0016] The second processing module is used to calculate the uplink and downlink signal-to-interference-plus-noise ratio and the sensing signal-to-interference-plus-noise ratio of each base station.

[0017] The third processing module is used to calculate the computing load information of each base station;

[0018] The fourth processing module is used to calculate the priority of each base station based on the utility function and select the base station with the highest priority for access.

[0019] The fifth processing module is used to check the constraints. If the communication quality and computing resource constraints are met, the user can access the base station and the system status is updated.

[0020] As a preferred option, the utility function is:

[0021] ;

[0022] Where B is the user access load bias factor. , and These correspond to the uplink / downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR, respectively. and These correspond to the obtained communication computing load information and perception computing load information, respectively. , , , This represents the weighting factors of each parameter, and + + + .

[0023] The present invention also provides a storage medium storing a computer program, which executes a user access method in a converged sensing, computing, and control network during runtime.

[0024] This invention calculates the SINR of communication and sensing data through an information acquisition and processing module, and obtains the corresponding computational load by acquiring communication and sensing data information from the received signals. A decision module inputs the acquired information into a utility function and selects the base station with the highest utility function value. An access module controls user access; the user sends an access request to the target base station, and the base station receives the request and establishes a connection. This invention has the following technical effects:

[0025] This invention evaluates the sensing coverage capability of each base station and the current network sensing computing load, and selects the base station most suitable for performing communication, sensing and computing tasks. This can effectively guarantee the network's communication, sensing and computing performance and achieve network load balancing.

[0026] 2. Based on the signal-to-interference-plus-noise ratio of the communication and sensing received signals, as well as the sensing computing load, this invention establishes a multi-objective utility function using a weighted summation method for different network environments, thereby realizing the modeling of user access in heterogeneous sensing and computing-control converged networks. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0028] Figure 1 This is a flowchart of the user access method in the converged sensing, computing, and control network according to an embodiment of the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0031] Example 1:

[0032] like Figure 1 As shown, this embodiment of the invention provides a user access method in a converged sensing, computing, and control network, comprising:

[0033] Collect users' communication and perception needs;

[0034] Calculate the uplink and downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR for each base station;

[0035] Calculate the computational load information for each base station;

[0036] The priority of each base station is calculated based on the utility function, and the base station with the highest priority is selected for access.

[0037] Perform a constraint check. If the communication quality and computing resource constraints are met, the user can access the base station, and the system status is updated.

[0038] As one embodiment of the present invention, the utility function includes: uplink and downlink communication signal-to-interference-plus-noise ratio, perceived signal-to-interference-plus-noise ratio, calculated load information, and base station load balancing factor.

[0039] As one embodiment of the present invention, a target access base station is selected based on the SINR of the bias received communication sensing signal and the computational load of the corresponding communication and sensing tasks.

[0040] Example 2:

[0041] like Figure 1 As shown, this embodiment of the invention also provides a user access method in a converged sensing, computing, and control network, including:

[0042] Step 1: Initialize base station parameter configuration and user information. Base station parameter configuration includes: transmit power. Calculation speed User information includes: user location information, location information of targets perceived around the user, and user transmission power. .

[0043] Step 2: When a user has communication and sensing needs, they send a task request to the base station. Communication needs involve data uploading and computation offloading; that is, the user wants the base station to help handle computational tasks and to send back control commands generated after the base station has processed the data. Sensing needs require the base station to perceive the user's surrounding environment, such as locating and identifying nearby objects or obstacles. After receiving the user's request, the base station needs to assess whether it can meet the user's needs, including whether the channel quality is good and whether the computing resources are sufficient.

[0044] Step 3: The base station receives the user's communication and sensing requests, assesses whether it can meet the user's needs, and calculates the quality of the user's communication signal and the quality of the sensing echo signal. Simultaneously, the base station calculates the computational load based on the received data volume and computation rate. Specifically, this includes:

[0045] Step 3.1: The base station receives data from the user. The system requests communication services, simultaneously senses the user's surrounding environment to acquire sensing information, and transmits control commands back in real time. Given a channel environment, it calculates the SINR of the uplink and downlink received signals, as well as the SINR of the sensed echo signal. The SINR expression for the uplink and downlink received signals is:

[0046] ;

[0047] ;

[0048] in, and These are the user's transmit beam gain and receive beam gain, respectively. and These are the transmit beam gain and receive beam gain of the base station, respectively. The channel's small-scale fading factor. This is the path loss factor. , and These represent the distance from the user to the base station, the uplink interference distance from the user to the base station, and the downlink interference distance from the base station to the user. This represents the noise interference power experienced by the communication signal.

[0049] The SINR expression for the sensed echo signal is:

[0050] ;

[0051] in, To sense the scattering cross-section parameters of the target, and These represent the distance from the target to the base station and the distance from other interfering base stations to each other. This represents the noise interference power experienced by the echo signal.

[0052] Therefore, communication SINR depends on the user's transmit power and receive capability, the base station's transmit power and receive capability, and channel conditions; while sensing SINR is related to factors such as the base station's sensing capability and environmental interference.

[0053] Step 3.2: The information processing module at the base station will process the received communication signals and sensing signals to obtain the amount of sensing data per unit processing time, i.e. and The corresponding computational load information is obtained based on the allocated synergistic computing resources. The computational load sizes for communication and sensing are respectively...

[0054] ;

[0055] Step 4: Calculate the utility function L of each base station and sort them. Select the base station with the highest access utility function. Specifically, this includes:

[0056] Step 4.1, the utility function is defined as:

[0057] ;

[0058] Where B is the user access load bias factor. For the purpose of load balancing, micro base stations can be prioritized for access when user needs can be met. Therefore, the bias factor of micro base stations is greater than that of macro base stations. , and These correspond to the uplink / downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR, respectively. and These correspond to the obtained communication computing load information and perception computing load information, respectively. The larger the computing load information, the longer the processing time. Therefore, users choose to access base stations with smaller computing loads. , , , This represents the weighting factors of each parameter, satisfying the following conditions: + + + .

[0059] Step 4.2: Starting with the first user, each user calculates the utility function of each base station and sorts them in descending order. The base station with the largest utility function value is then selected for access.

[0060] Step 5 determines whether the constraints are met under the current access status, specifically including:

[0061] Step 5.1: Determine whether the SINR of the received signal is greater than a preset threshold to ensure the minimum service quality for the user. If it is greater than the threshold, proceed to the next step; if it is less than the threshold, determine whether to traverse all base stations in the system.

[0062] Step 5.2: Due to limited base station computing resources, it is necessary to determine whether the sensor computing load information is greater than the base station computing load threshold. If it is less, the user selects that base station for access; if it is greater, it is necessary to determine whether to traverse all base stations in the system.

[0063] Step 5.3: When the SINR of the received sensor signal is less than the threshold or the amount of sensor data exceeds the computational load threshold, other base stations need to be selected in conjunction with the utility function to determine the connection. If the constraints are not met after traversing all base stations, the user enters a blocking phase and cannot receive communication, sensing, or computation services.

[0064] When the above constraints are met in step 6, the user successfully connects to the base station. The system will update the base station's computing resource usage and the user's access status, and recalculate the base station utility function to inform subsequent user access decisions. This process continues until all users have successfully connected, or until insufficient system resources prevent some users from connecting.

[0065] Example 3:

[0066] This invention also provides a user access system in a converged sensing, computing, and control network, comprising:

[0067] The first processing module is used to collect users' communication and perception requirements;

[0068] The second processing module is used to calculate the uplink and downlink signal-to-interference-plus-noise ratio and the sensing signal-to-interference-plus-noise ratio of each base station.

[0069] The third processing module is used to calculate the computing load information of each base station;

[0070] The fourth processing module is used to calculate the priority of each base station based on the utility function and select the base station with the highest priority for access.

[0071] The fifth processing module is used to check the constraints. If the communication quality and computing resource constraints are met, the user can access the base station and the system status is updated.

[0072] As one embodiment of the present invention, the utility function is:

[0073] ;

[0074] Where B is the user access load bias factor. , and These correspond to the uplink / downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR, respectively. and These correspond to the obtained communication computing load information and perception computing load information, respectively. , , , This represents the weighting factors of each parameter, and + + + .

[0075] Example 4:

[0076] This invention also provides a storage medium storing a computer program, which executes a user access method in a converged sensing, computing, and control network during runtime.

[0077] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A user access method in a converged sensing, computing, and control network, characterized in that, include: Collect users' communication and perception needs, including: When a user has communication and sensing needs, they send a task request to the base station. Communication needs involve data uploading and computation offloading, meaning the user wants the base station to help process computational tasks and send back control commands generated after the base station has processed the data. Sensing needs require the base station to sense the user's surrounding environment. After receiving the user's request, the base station assesses whether it can meet the user's needs, including whether the channel quality is good and whether the computing resources are sufficient. Based on the user's communication and perception requirements, the uplink and downlink signal-to-interference-plus-noise ratio (SIR) and the perceived SIR of each base station are calculated, including: Base station receives data from users The system requests communication services, simultaneously senses the user's surrounding environment to acquire sensing information, and transmits control commands back in real time. Given a channel environment, it calculates the SINR of the uplink and downlink received signals, as well as the SINR of the sensed echo signal. The SINR expression for the uplink and downlink received signals is: ； ； in, and These are the user's transmit beam gain and receive beam gain, respectively. and These are the transmit beam gain and receive beam gain of the base station, respectively. The channel's small-scale fading factor. This is the path loss factor. , and These represent the distance from the user to the base station, the uplink interference distance from the user to the base station, and the downlink interference distance from the base station to the user. The noise interference power received by the communication signal; The SINR expression for the sensed echo signal is: ； in, To sense the scattering cross-section parameters of the target, and These represent the distance from the target to the base station and the distance from other interfering base stations to each other. This represents the noise interference power experienced by the echo signal. Based on users' communication and perception requirements, the computational load information of each base station is calculated, including: The information processing module at the base station will process the received communication and sensing signals to obtain the amount of sensor data per unit processing time, i.e. and Based on the allocated synesthetic computing resources, the corresponding computational load information is obtained. The computational load sizes for communication and sensing are as follows: ； The priority of each base station is calculated based on the utility function, and the base station with the highest priority is selected for access, including: Utility function for: ； Where B is the user access load bias factor. , and These correspond to the uplink / downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR, respectively. and These correspond to the obtained communication computing load information and perception computing load information, respectively. , , , This represents the weighting factors of each parameter, and + + + ; Starting with the first user, each user calculates the utility function of each base station and sorts them in descending order, then finds the base station with the largest utility function value to be connected to. Perform constraint checks. If the communication quality and computing resource constraints are met, the user connects to the base station, and the system status is updated, including: Determine whether the SINR of the received signal is greater than a preset threshold to ensure the minimum service quality for users. If it is greater than the threshold, proceed to the next step; if it is less than the threshold, determine whether to traverse all base stations in the system. Determine if the sensory computing load information is greater than the base station computing load threshold. If it is greater, the user selects that base station for access; if it is less, determine whether to traverse all base stations in the system. When the SINR of the sensory received signal is less than the threshold or the amount of sensory data exceeds the computing load threshold, other base stations are selected in combination with the utility function to determine the connection; if the constraints are not met after traversing all base stations, the user enters a blocking phase and cannot receive communication, sensing, or computing services. When the above constraints are met, the user successfully accesses the base station. The system will update the base station's computing resource usage and the user's access status, and recalculate the base station utility function so that subsequent users can make access decisions. The entire process continues until all users have completed access, or until system resources are insufficient and some users cannot access.

2. A user access system in a converged sensing, computing, and control network, used to implement the method as described in claim 1, characterized in that, include: The first processing module is used to collect users' communication and perception requirements; The second processing module is used to calculate the uplink and downlink signal-to-interference-plus-noise ratio and the sensing signal-to-interference-plus-noise ratio of each base station. The third processing module is used to calculate the computing load information of each base station; The fourth processing module is used to calculate the priority of each base station based on the utility function and select the base station with the highest priority for access. The fifth processing module is used to check the constraints. If the communication quality and computing resource constraints are met, the user can access the base station and the system status is updated. The utility function is: ； Where B is the user access load bias factor. , and These correspond to the uplink / downlink signal-to-interference-plus-noise ratio (SIR) and the sensing SIR, respectively. and These correspond to the obtained communication computing load information and perception computing load information, respectively. , , , This represents the weighting factors of each parameter, and + + + .

3. A storage medium, characterized in that, The storage medium stores a computer program, which executes the user access method in the converged sensing, computing, and control network as described in claim 1 when it runs.

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