A network status-aware assisted grant-free multiple access method

Abstract

The application discloses a network state sensing assisted grant-free multiple access method and device and a storage medium. The method comprises the following steps: acquiring the usage of resource blocks in a grant-free multiple access system, and estimating the number of active unmanned aerial vehicle (UAV) users and ground users in the system in real time according to the usage of the resource blocks to obtain an estimated number; distributing the resource blocks by using a weighted dynamic resource distribution strategy based on the estimated number of active users and the weights of the users; and dynamically adjusting the access control parameters of the UAV and ground user equipment by using an access control parameter dynamic adjustment strategy based on the estimated number of active users and the number of resource blocks corresponding to the active users. The application estimates the number of UAV users and ground users in the grant-free multiple access system in real time, dynamically distributes resources and adjusts the access control parameters according to the estimated number and the weights of the users, improves the estimation accuracy, and thus meets the access requirements of the UAV and ground users.

Description

Technical Field

[0001] This disclosure relates to the field of wireless communication technology, and in particular to a network state-aware assisted unlicensed multiple access method, apparatus and storage medium. Background Technology

[0002] Random access is a key design element in the fifth-generation (B5G) wireless mobile communication technology framework, especially in emerging application scenarios for ultra-reliable low-latency communication, such as autonomous driving, remote medical surgery, and industrial IoT control. Traditional licensed access technologies are limited by the fact that users must endure at least 10 milliseconds of latency before uplinking data transmission, making it difficult to meet the extreme quality-of-service requirements of ultra-reliable low-latency communication services. Therefore, unlicensed access technology, as a potential solution, allows users to directly transmit data to the base station without authorization, and is thus considered a viable alternative.

[0003] Faced with the stringent random access requirements of high-reliability, low-latency services, effectively mitigating collisions during user access has become a critical challenge, especially in complex and dynamic wireless communication environments with limited resources and diverse user needs. Existing solutions primarily focus on optimizing resource management strategies, such as allocating dedicated resource blocks for homogeneous latency-tolerant users and dynamically adjusting shared resource pools. By dynamically adjusting access category constraint parameters and flexibly allocating resources, these strategies aim to balance overall system throughput with meeting the access needs of heterogeneous users. However, these strategies typically rely on the assumption that the number of active users is known during the random access phase. This assumption is difficult to maintain in self-organizing networks or dynamically changing scenarios. Therefore, accurately estimating the number of active users, especially user groups with different latency tolerances, and achieving efficient dynamic allocation of radio resources based on this estimation, has become a crucial problem to be solved.

[0004] In existing technologies, estimation methods based on Bayesian theory have attracted widespread attention due to their ability to handle uncertain information. Specifically, the Bayesian criterion effectively handles parameter uncertainty by iteratively updating the posterior probability estimate by combining prior knowledge with actual observation data, providing a stable and adaptable approach for estimating the number of active users, thereby improving the accuracy and flexibility of resource allocation decisions. However, the aforementioned existing technologies only utilize local information when estimating the number of active users, resulting in low estimation accuracy. Summary of the Invention

[0005] This disclosure provides a network state-aware assisted unlicensed multiple access method, apparatus, and storage medium. In an unlicensed multiple access system, the number of UAV users and ground users is estimated in real time. Based on the estimated number and the weight of each user, resources are dynamically allocated and access control parameters are adjusted, thereby improving the estimation accuracy and meeting the access needs of UAVs and ground users.

[0006] According to one aspect of this disclosure, a network state-aware assisted unlicensed multiple access method is provided, applied to an unlicensed multiple access system, the unlicensed multiple access system comprising a base station, N h A latency-sensitive drone user and N l A latency-tolerant ground user equipment, wherein the UAV and the ground user equipment access the base station through an unlicensed access mechanism, characterized in that the method includes:

[0007] The usage status of resource blocks in the unlicensed multiple access system is obtained, and the number of active UAV users and ground users in the system is estimated in real time based on the usage status of the resource blocks to obtain the estimated number;

[0008] Based on the estimated number of active users and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy.

[0009] Based on the estimated number of active users and the number of their corresponding resource blocks, the access control parameters of the UAV and ground user equipment are adaptively adjusted using a dynamic adjustment strategy for access control parameters.

[0010] Optionally, the resource block includes a successful resource block, an idle resource block, and a collision resource block, wherein,

[0011] The idle resource blocks include resource blocks that do not have user-transmitted data packets;

[0012] The successful resource block includes a resource block that has transmitted data packets on one and only one user.

[0013] The collision resource block includes resource blocks on which data packets are transmitted by at least two users.

[0014] Optionally, the step of estimating the number of active drone users and ground users in the system in real time based on the usage of the resource blocks to obtain the estimated number includes:

[0015] Determine whether the number of collision resource blocks is at a preset threshold;

[0016] If the number of collision resource blocks is equal to the preset threshold, then the estimated number is obtained based on the number of successful resource blocks and the access control parameters;

[0017] If the number of collision resource blocks is not equal to the preset threshold, then a first probability of the first condition is determined, and an estimated number is obtained based on the first probability, wherein the first condition is N. x There are n users x A user randomly selects M through access control. x Data packets are transmitted on each resource block, and s exists simultaneously. x One successful resource block, i x One free resource block and c x One collision resource block.

[0018] Optionally, determining the first probability of the first condition includes:

[0019] Determine the second probability of the second condition, where the second condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, with i x One resource block is an idle resource block;

[0020] Determine the third probability of the third condition, where the third condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x In the case of 1 free resource block, there are s x One resource block is a successful resource block;

[0021] Determine the fourth probability of the fourth condition, where the fourth condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x One free resource block and s x In the case of 1 successful resource block, there are c x Each resource block is a collision resource block;

[0022] Based on the second probability, the third probability, and the fourth probability, the first probability of the first condition is determined.

[0023] Optionally, obtaining the estimated quantity based on the first probability includes:

[0024] Based on the distribution of the first probability and the number of active users, a joint probability distribution is obtained;

[0025] Based on the joint probability distribution, the fifth probability is determined;

[0026] Based on the joint probability distribution and the fifth probability, the posterior estimate of the number of active users is determined.

[0027] The posterior estimation result is updated based on the offset to obtain the estimated quantity.

[0028] Optionally, the allocation of resource blocks based on the estimated number of active users and the weight of each user, using a weighted dynamic resource allocation strategy, includes:

[0029] Determine the target distribution that the users follow;

[0030] Based on the target distribution, the estimated number of active users, and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy, wherein the weighted resource allocation strategy is as follows:

[0031]

[0032] Wherein, the λ t t This indicates the estimated number of active users with priority x, where w is the value of the number of active users. x This represents the weight of user with priority x, where M represents the total number of time-frequency resource blocks. x This represents the time-frequency resource block allocated to user with priority x, where x∈{h,l}.

[0033] Optionally, the dynamic adjustment strategy for the access control parameters includes:

[0034]

[0035] Among them, the Indicates the access control parameters, the M x This represents the time-frequency resource block allocated to user x. This represents the estimated number of active users with priority x.

[0036] According to another aspect of this disclosure, a network state-aware assisted unlicensed multiple access device is provided, applied to an unlicensed multiple access system, the unlicensed multiple access system comprising a base station, N h A latency-sensitive drone user and N l A latency-tolerant ground user equipment, wherein the UAV and the ground user equipment access the base station through an unlicensed access mechanism, characterized in that the device comprises:

[0037] The estimation module is used to obtain the usage status of resource blocks in the unlicensed multiple access system, and to estimate the number of active UAV users and ground users in the system in real time based on the usage status of the resource blocks, so as to obtain the estimated number.

[0038] The resource allocation module is used to allocate resource blocks based on the estimated number of active users and the weight of each user, using a weighted dynamic resource allocation strategy.

[0039] The adjustment module is used to adaptively adjust the access control parameters of the UAV and ground user equipment based on the estimated number of active users and the number of their corresponding resource blocks using a dynamic adjustment strategy for access control parameters.

[0040] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0041] At least one processor; and

[0042] A memory communicatively connected to the at least one processor; wherein,

[0043] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in any one of the preceding aspects.

[0044] According to another aspect of this disclosure, a computer storage medium storing computer instructions is provided, wherein the computer storage medium stores computer-executable instructions; the computer-executable instructions, when executed by a processor, are capable of implementing the method described in any one of the preceding aspects.

[0045] The network state awareness-assisted unlicensed multiple access method and apparatus of this disclosure estimate the number of UAV users and ground users in real time in an unlicensed multiple access system, and dynamically allocate resources and adjust access control parameters based on the estimated number and the weight of each user, thereby improving the estimation accuracy and meeting the access needs of UAVs and ground users.

[0046] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0047] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:

[0048] Figure 1 This is a flowchart of a network state-aware assisted unlicensed multiple access method according to an embodiment of the present disclosure;

[0049] Figure 2 This is a model diagram of an unlicensed multiple access system according to an embodiment of the present disclosure;

[0050] Figure 3 This is a frame structure diagram of an unlicensed multiple access system according to an embodiment of the present disclosure;

[0051] Figure 4This is a flowchart of a dynamic resource allocation scheme according to an embodiment of the present disclosure;

[0052] Figure 5 This is a structural diagram of a network state awareness-assisted unlicensed multiple access device according to an embodiment of the present disclosure;

[0053] Figure 6 This is a block diagram of an electronic device used to implement the network state-aware assisted unlicensed multiple access method according to embodiments of the present disclosure. Detailed Implementation

[0054] It should be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0055] To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0056] The following description, with reference to the accompanying drawings, describes a network state-aware assisted unauthorized multiple access method and apparatus according to embodiments of the present disclosure.

[0057] Figure 1 This is a flowchart of a network state-aware assisted unauthorized multiple access method according to an embodiment of this disclosure.

[0058] like Figure 1 As shown, the network state-aware assisted unlicensed multiple access method includes:

[0059] S101, obtain the usage status of resource blocks in the unlicensed multiple access system, and estimate the number of active drone users and ground users in the system in real time based on the usage status of resource blocks to obtain the estimated number;

[0060] It should be noted that the execution subject of the above-mentioned network state-aware assisted unauthorized multiple access method is a network state-aware assisted unauthorized multiple access device. This network state-aware assisted unauthorized multiple access device can be implemented by software and / or hardware. In this embodiment, the network state-aware assisted unauthorized multiple access device can be configured in an electronic device.

[0061] In this example embodiment, the electronic device may include devices such as terminal devices and servers, and this embodiment does not limit the electronic device.

[0062] In one embodiment of this disclosure, the above-described unlicensed multiple access system includes a base station, N h A latency-sensitive drone and N l A ground user equipment that is tolerant of latency, wherein drones and ground user equipment can access the base station through an unauthorized access mechanism. Figure 2 This is a model diagram of an unlicensed multiple access system proposed in an embodiment of this disclosure. Figure 2 As shown, in this system model, both drone users and ground users simultaneously access the base station via uplink. The configuration in the unlicensed multiple access system is as follows: total number of resource blocks M = 40, number of drones N... h =40, Number of ground users N l =10, the arrival speed ratio of drones to ground users is 4:1, the length of the subframe is 1 millisecond, and 1 subframe contains 8 time slots.

[0063] In one embodiment of this disclosure, drone users are set as high-priority users and ground users are set as low-priority users to ensure safe and stable drone flight.

[0064] Furthermore, in one embodiment of this disclosure, the disclosure adopts the Orthogonal Frequency Division Multiplexing (ALOMA) time slot scheme, that is, one frame contains 10 subframes, one subframe lasts for 1 millisecond and contains 8 time slots. Figure 3 This is a frame structure diagram of an unlicensed multiple access system proposed in an embodiment of this disclosure. Figure 3 As shown, each frame contains 10 subframes, each subframe lasts for 1 millisecond and contains 8 time slots.

[0065] In this disclosure, drone users and ground users can access the base station through an unauthorized access mechanism, meaning that drone and ground users can directly transmit messages to the base station without waiting. Furthermore, this disclosure employs a hybrid automatic repeat request mechanism, whereby drone and ground users wait for confirmation from the base station after sending data packets. If the base station fails to receive the data packets, the drone and ground user equipment will continue to retransmit the data packets until the base station confirms successful reception. Further, in one embodiment of this disclosure, the condition for a user to successfully access the base station is defined as follows: successful access is considered achieved if and only if the user exclusively occupies a time-frequency resource block for data transmission.

[0066] Furthermore, in one embodiment of this disclosure, the resource block may include a successful resource block, an idle resource block, and a collision resource block, wherein the idle resource block includes a resource block with no user uploading data packets; the successful resource block includes a resource block with one and only one user uploading data packets; and the collision resource block includes a resource block with at least two user uploading data packets.

[0067] Furthermore, in one embodiment of this disclosure, the method for obtaining the estimated number of active drone users and ground users in the system in real time based on the usage of resource blocks may include the following steps:

[0068] S1011, Determine whether the number of collision resource blocks is at a preset threshold;

[0069] S1012, If the number of collision resource blocks is equal to the preset threshold, then the estimated number is obtained based on the number of successful resource blocks and the access control parameters;

[0070] S1013, if the number of collision resource blocks is not equal to the preset threshold, then determine the first probability of the first condition, and obtain the estimated number based on the first probability, where the first condition is N. x There are n users x A user randomly selects M through access control. x Data packets are transmitted on each resource block, and s exists simultaneously. x One successful resource block, i x One free resource block and c x One collision resource block.

[0071] In one embodiment of this disclosure, the preset threshold can be set as needed; for example, the preset threshold is 0.

[0072] Furthermore, in one embodiment of this disclosure, the number c of collision resource blocks mentioned above... x When = 0, the number of successful resource blocks s can be used as a reference. x The number of actual active users is obtained from the access control parameters.

[0073]

[0074] Among them, E(N) x |s x i x ,c x ) represents the posterior estimate of the number of active users, i x Indicates the number of free resource blocks. This indicates the access control parameters.

[0075] Furthermore, in one embodiment of this disclosure, the method for determining the first probability of the first condition may include the following steps:

[0076] Step 1: Determine the second probability of the second condition, where the second condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, with i x One resource block is an idle resource block;

[0077] Step 2: Determine the third probability of the third condition, where the third condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x In the case of 1 free resource block, there are s x One resource block is a successful resource block;

[0078] Step 3: Determine the fourth probability of the fourth condition, where the fourth condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x One free resource block and s x In the case of 1 successful resource block, there are c x Each resource block is a collision resource block;

[0079] Step 4: Based on the second probability, the third probability, and the fourth probability, determine the first probability of the first condition.

[0080] In one embodiment of this disclosure, the second condition n is described above. x A user randomly selects M x Data packets are transmitted on resource blocks, with i x The second probability that a resource block is an idle resource block is P(i x |n x ),in,

[0081]

[0082] Furthermore, in one embodiment of this disclosure, the aforementioned third condition n x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x In the case of 1 free resource block, there are s x The third probability that a resource block is a successful resource block is P(s). x |i x ,n x ),in,

[0083]

[0084] Furthermore, in one embodiment of this disclosure, the fourth condition n x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x One free resource block and s x In the case of 1 successful resource block, there are c x The fourth probability that a resource block is a colliding resource block is P(c x |s xi x ,n x ),in,

[0085]

[0086] Furthermore, in one embodiment of this disclosure, after obtaining the second probability, the third probability, and the fourth probability through the above steps, the first probability of the first condition can be determined based on the second probability, the third probability, and the fourth probability. In one embodiment of this disclosure, the method for determining the first probability of the first condition based on the second probability, the third probability, and the fourth probability may include: determining the first probability of the first condition based on a probability formula, wherein the probability formula is:

[0087]

[0088] Furthermore, in one embodiment of this disclosure, the method for obtaining an estimated quantity based on the first probability obtained through the above steps may include the following steps:

[0089] Step a: Based on the distribution of the first probability and the number of active users, obtain the joint probability distribution;

[0090] Step b: Determine the fifth probability based on the joint probability distribution;

[0091] Step c: Based on the joint probability distribution and the fifth probability, determine the posterior estimate of the number of active users;

[0092] Step d: Update the posterior estimation results based on the offset to obtain the estimated quantity.

[0093] In one embodiment of this disclosure, based on the first probability P(s) x i x ,c x |N x ) and number of active users N x From the distribution of these distributions, we can obtain the joint probability distribution P(s). x i x ,c x N x ),

[0094]

[0095] Furthermore, in one embodiment of this disclosure, the joint probability distribution P(s) is... x i x ,c x N x The total number of possible active users N in ) xAdding them together, we can further obtain the fifth probability P(s). x i x ,c x ),

[0096]

[0097] Furthermore, in one embodiment of this disclosure, based on the joint probability distribution P(s) obtained above... x i x ,c x N x ) and the fifth probability P(s) x i x ,c x The posterior estimate of the number of active users, E(N), is determined. x |s x i x ,c x ) can be represented as,

[0098]

[0099] Furthermore, in one embodiment of this disclosure, taking into account the above-described posterior estimation result E(N) x |s x i x ,c x Since updates are needed in every subframe, and the number of newly arriving users in each subframe is unknown, this disclosure introduces an offset Δλ. x ,Δλ x This represents the posterior estimation result E(N). x |s x i x ,c x The estimated number of users in the previous subframe is compared with the above-mentioned number of users. The difference,

[0100]

[0101] Based on this, an estimate of the number of active users in the current subframe can be obtained.

[0102]

[0103] S102, Based on the estimated number of active users and the weight of each user, allocate resource blocks using a weighted dynamic resource allocation strategy;

[0104] In one embodiment of this disclosure, after obtaining the estimated number of active users and the weight of each user through the above steps, resource blocks can be allocated using a weighted dynamic resource allocation strategy.

[0105] Specifically, in one embodiment of this disclosure, the method for allocating resource blocks using a weighted dynamic resource allocation strategy based on the estimated number of active users and the weight of each user may include the following steps:

[0106] S1021, Determine the target distribution that the user follows;

[0107] S1022, based on the target distribution, the estimated number of active users, and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy. The weighted resource allocation strategy is as follows:

[0108]

[0109] in, This indicates the estimated number of active users with priority x, and w. x This represents the weight of user with priority x, and M represents the total number of time-frequency resource blocks. x This represents the time-frequency resource block allocated to user with priority x, where x∈{h,l}.

[0110] In one embodiment of this disclosure, the number of active high-priority users and low-priority users both follow a mean of λ. x The Poisson distribution of x∈(h,l)

[0111]

[0112] Furthermore, in one embodiment of this disclosure, the number of time-frequency resource blocks in the above system is M. x The access control parameters are The probability that a user connects to the base station via access control is p. x ,but,

[0113]

[0114] Furthermore, in one embodiment of this disclosure, the number of subframes a user waits from the start of an access attempt to successfully access the base station is defined as the access delay D. x The number of users who successfully access the base station in the same subframe is defined as the throughput R. x ,but,

[0115]

[0116] Where T represents the duration of a unit subframe.

[0117] S103, based on the estimated number of active users and the number of their corresponding resource blocks, adaptively adjusts the access control parameters of UAVs and ground user equipment using a dynamic adjustment strategy for access control parameters.

[0118] In one embodiment of this disclosure, in order to avoid network congestion caused by a large number of users accessing the base station at the same time, a dynamic adjustment strategy for access control parameters is designed. Based on the number of UAV users and ground users and the number of their corresponding time-frequency resource blocks, the access control parameters of UAVs and ground user equipment are adaptively adjusted.

[0119] In one embodiment of this disclosure, the aforementioned dynamic adjustment strategy for access control parameters includes:

[0120]

[0121] in, Indicates the access control parameters, M x This represents the time-frequency resource block allocated to user x. This represents an estimated number of active users.

[0122] In one embodiment of this disclosure, Figure 4 This is a flowchart illustrating a dynamic resource allocation scheme proposed in an embodiment of this disclosure. Figure 4 As shown, at the beginning of each subframe, after the UAV and ground users complete uplink transmission, the base station estimates the number of active UAV and ground users; and determines the number of resource blocks allocated to UAV and ground users based on the estimated number and weight of active users; and adjusts the access control parameters based on the estimated number of active users and the number of resource blocks. Finally, the resource allocation results and access control parameters are sent to the UAV and ground user equipment.

[0123] In one or more embodiments of this disclosure, the usage of resource blocks in an unlicensed multiple access system is obtained, and the number of active UAV users and ground users in the system is estimated in real time based on the resource block usage. Based on the estimated number of active users and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy. Based on the estimated number of active users and the corresponding number of resource blocks, the access control parameters of UAV and ground user equipment are adaptively adjusted using a dynamic adjustment strategy for access control parameters. Therefore, this disclosure provides real-time estimation of the number of UAV users and ground users in an unlicensed multiple access system, and dynamically allocates resources and adjusts access control parameters based on the obtained estimated number and the weight of each user, improving estimation accuracy and thus meeting the access needs of UAV and ground users.

[0124] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0125] Please see Figure 5This illustration shows a schematic diagram of a network state-aware assisted unlicensed multiple access device according to an embodiment of the present disclosure. This network state-aware assisted unlicensed multiple access device is applied to an unlicensed multiple access system, which includes a base station, N g A latency-sensitive drone user and N l A latency-tolerant ground user equipment, wherein the UAV and the ground user equipment access the base station through an unauthorized access mechanism, the device 10 includes an estimation module 100, a resource allocation module 200, and an adjustment module 300, wherein:

[0126] The estimation module 100 is used to obtain the usage status of resource blocks in the unlicensed multiple access system, and to estimate the number of active UAV users and ground users in the system in real time based on the usage status of resource blocks, so as to obtain the estimated number.

[0127] Resource allocation module 200 is used to allocate resource blocks based on the estimated number of active users and the weight of each user using a weighted dynamic resource allocation strategy.

[0128] The adjustment module 300 is used to adaptively adjust the access control parameters of UAV users and ground users based on the estimated number of active users and the number of their corresponding resource blocks using a dynamic adjustment strategy of access control parameters.

[0129] Optionally, in one practical example of this disclosure, the aforementioned resource blocks include successful resource blocks, idle resource blocks, and collision resource blocks, wherein,

[0130] Free resource blocks include resource blocks that do not have user-transmitted data packets;

[0131] A successful resource block includes a resource block on which a data packet was transmitted by one and only one user.

[0132] A collision resource block includes a resource block on which data packets are transmitted by at least two users.

[0133] Optionally, in one practical example of this disclosure, the above estimation module is specifically used for:

[0134] Determine whether the number of collision resource blocks is at a preset threshold;

[0135] If the number of collision resource blocks is equal to the preset threshold, then the estimated number is obtained based on the number of successful resource blocks and the access control parameters;

[0136] If the number of collision resource blocks is not equal to the preset threshold, then a first probability of the first condition is determined, and an estimated number is obtained based on the first probability, wherein the first condition is N. x There are n users xA user randomly selects M through access control. x Data packets are transmitted on each resource block, and s exists simultaneously. x One successful resource block, i x One free resource block and c x One collision resource block.

[0137] Optionally, in one embodiment of this disclosure, the estimation module is further configured to:

[0138] Determine the second probability of the second condition, where the second condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, with i x One resource block is an idle resource block;

[0139] Determine the third probability of the third condition, where the third condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x In the case of 1 free resource block, there are s x One resource block is a successful resource block;

[0140] Determine the fourth probability of the fourth condition, where the fourth condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x One free resource block and s x In the case of 1 successful resource block, there are c x Each resource block is a collision resource block;

[0141] Based on the second, third, and fourth probabilities, determine the first probability of the first condition.

[0142] Optionally, in one embodiment of this disclosure, the estimation module is further configured to:

[0143] Based on the distribution of the first probability and the number of active users, a joint probability distribution is obtained;

[0144] The fifth probability is determined based on the joint probability distribution;

[0145] Based on the joint probability distribution and the fifth probability, the posterior estimate of the number of active users is determined.

[0146] The posterior estimation results are updated based on the offset to obtain the estimated quantity.

[0147] Optionally, in one embodiment of this disclosure, the resource allocation module is specifically used for:

[0148] Determine the target distribution that users should follow;

[0149] Based on the target distribution, the estimated number of active users, and the weight of each user, a weighted dynamic resource allocation strategy is used to allocate resource blocks. The weighted resource allocation strategy is as follows:

[0150]

[0151] in, This indicates the estimated number of active users with priority x, and w. x This represents the weight of user with priority x, and M represents the total number of time-frequency resource blocks. x This represents the time-frequency resource block allocated to user with priority x, where x∈{h,l}.

[0152] Optionally, in one embodiment of this disclosure, the above-mentioned dynamic adjustment strategy for access control parameters includes:

[0153]

[0154] in, Indicates the access control parameters, the M x This represents the time-frequency resource block allocated to user x. This represents the estimated number of active users with priority x.

[0155] In one or more embodiments of this disclosure, the usage of resource blocks in an unlicensed multiple access system is obtained, and the number of active UAV users and ground users in the system is estimated in real time based on the resource block usage. Based on the estimated number of active users and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy. Based on the estimated number of active users and the corresponding number of resource blocks, the access control parameters of UAV and ground user equipment are adaptively adjusted using a dynamic adjustment strategy for access control parameters. Therefore, this disclosure provides real-time estimation of the number of UAV users and ground users in an unlicensed multiple access system, and dynamically allocates resources and adjusts access control parameters based on the obtained estimated number and the weight of each user, improving estimation accuracy and thus meeting the access needs of UAV and ground users.

[0156] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0157] According to embodiments of this disclosure, this disclosure also provides an electronic device and a computer storage medium.

[0158] Figure 6A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable electronic devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0159] like Figure 6 As shown, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 606. The RAM 603 may also store various programs and data required for the operation of the electronic device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0160] Multiple components in electronic device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of displays, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows electronic device 600 to exchange information / data with other electronic devices through computer networks such as the Internet and / or various telecommunications networks.

[0161] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the network state-aware assisted unauthorized multiple access method. For example, in some embodiments, the network state-aware assisted unauthorized multiple access method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the network state-aware assisted unauthorized multiple access method described above can be performed. Alternatively, in other embodiments, computing unit 601 may be configured by any other suitable means (e.g., by means of firmware) to perform a network state-aware assisted unlicensed multiple access method.

[0162] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic electronic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0163] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0164] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or electronic device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or electronic devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage electronics, magnetic storage electronics, or any suitable combination of the foregoing.

[0165] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0166] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.

[0167] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0168] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0169] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A network state-aware assisted unlicensed multiple access method, applied to an unlicensed multiple access system, wherein the unlicensed multiple access system includes a base station, N h A latency-sensitive drone user and N l A ground user equipment unit that is tolerant of latency, among which, The UAV and ground user equipment access the base station through an unauthorized access mechanism, characterized in that the method includes: The usage status of resource blocks in the unlicensed multiple access system is obtained, and the number of active UAV users and ground users in the system is estimated in real time based on the usage status of the resource blocks to obtain the estimated number; Based on the estimated number of active users and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy. Based on the estimated number of active users and the number of their corresponding resource blocks, the access control parameters of the UAV and ground user equipment are adaptively adjusted using a dynamic adjustment strategy for access control parameters. The allocation of resource blocks based on the estimated number of active users and the weight of each user, using a weighted dynamic resource allocation strategy, includes: Determine the target distribution that the users follow; Based on the target distribution, the estimated number of active users, and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy, wherein the weighted resource allocation strategy is as follows: Among them, the This indicates the estimated number of active users with priority x, where w is the value of the number of active users. x This represents the weight of user with priority x, where M represents the total number of time-frequency resource blocks. x This represents the time-frequency resource block allocated to user with priority x, where x ∈ {h, l}. The w represents the estimated number of active users with priority h. h This represents the weight of user with priority h. This indicates the estimated number of active users with priority level l, where w is the value of the number of active users. l This represents the weight of the user with priority level l. The dynamic adjustment strategy for access control parameters includes: Among them, the Indicates the access control parameters, the M x This represents the time-frequency resource block allocated to user with priority x. This represents the estimated number of active users with priority x.

2. The method according to claim 1, characterized in that, The resource blocks include successful resource blocks, idle resource blocks, and collision resource blocks, wherein... The idle resource blocks include resource blocks that do not have user-transmitted data packets; The successful resource block includes a resource block that has transmitted data packets on one and only one user. The collision resource block includes resource blocks on which data packets are transmitted by at least two users.

3. The method according to claim 2, characterized in that, The step of estimating the active number of drone users and ground users in the system in real time based on the usage of the resource blocks to obtain the estimated number includes: Determine whether the number of collision resource blocks is at a preset threshold; If the number of collision resource blocks is equal to the preset threshold, then the estimated number is obtained based on the number of successful resource blocks and the access control parameters; If the number of collision resource blocks is not equal to the preset threshold, then a first probability of the first condition is determined, and an estimated number is obtained based on the first probability, wherein the first condition is N. x There are n users x A user randomly selects M through access control. x Data packets are transmitted on each resource block, and s exists simultaneously. x One successful resource block, i x One free resource block and c x One collision resource block.

4. The method according to claim 3, characterized in that, The determination of the first probability of the first condition includes: Determine the second probability of the second condition, where the second condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, with i x One resource block is an idle resource block; Determine the third probability of the third condition, where the third condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x In the case of 1 free resource block, there are s x One resource block is a successful resource block; Determine the fourth probability of the fourth condition, where the fourth condition is n. x A user randomly selects M x Data packets are transmitted on resource blocks, and i exists. x One free resource block and s x In the case of 1 successful resource block, there are c x Each resource block is a collision resource block; Based on the second probability, the third probability, and the fourth probability, the first probability of the first condition is determined.

5. The method according to claim 3, characterized in that, The process of obtaining the estimated quantity based on the first probability includes: Based on the distribution of the first probability and the number of active users, a joint probability distribution is obtained; Based on the joint probability distribution, the fifth probability is determined; Based on the joint probability distribution and the fifth probability, the posterior estimate of the number of active users is determined. The posterior estimation result is updated based on the offset to obtain the estimated quantity.

6. A network state-aware assisted unlicensed multiple access device, applied to an unlicensed multiple access system, the unlicensed multiple access system comprising a base station, N h A latency-sensitive drone user and N l A ground user equipment unit that is tolerant of latency, among which, The UAV and ground user equipment access the base station through an unauthorized access mechanism, characterized in that the device includes: The estimation module is used to obtain the usage status of resource blocks in the unlicensed multiple access system, and to estimate the number of active UAV users and ground users in the system in real time based on the usage status of the resource blocks, so as to obtain the estimated number. The resource allocation module is used to allocate resource blocks based on the estimated number of active users and the weight of each user, using a weighted dynamic resource allocation strategy. The adjustment module is used to adaptively adjust the access control parameters of the UAV and ground user equipment based on the estimated number of active users and the number of their corresponding resource blocks using a dynamic adjustment strategy for access control parameters. The resource allocation module is specifically used for: Determine the target distribution that the users follow; Based on the target distribution, the estimated number of active users, and the weight of each user, resource blocks are allocated using a weighted dynamic resource allocation strategy, wherein the weighted resource allocation strategy is as follows: Among them, the This indicates the estimated number of active users with priority x, where w is the value of the number of active users. x This represents the weight of user with priority x, where M represents the total number of time-frequency resource blocks. x This represents the time-frequency resource block allocated to user with priority x, where x ∈ {h, l}. The w represents the estimated number of active users with priority h. h This represents the weight of user with priority h. This indicates the estimated number of active users with priority level l, where w is the value of the number of active users. l This represents the weight of the user with priority level l. The dynamic adjustment strategy for access control parameters includes: Among them, the Indicates the access control parameters, the M x This represents the time-frequency resource block allocated to user with priority x. This represents the estimated number of active users with priority x.

7. An electronic device, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

8. A computer storage medium, wherein, The computer storage medium stores computer-executable instructions; when executed by a processor, the computer-executable instructions can implement the method described in any one of claims 1-5.

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