Method and apparatus for resource allocation in wireless networks

Abstract

The present invention relates to a method and apparatus for allocating resources in a wireless network. By limiting the resources allocated based on whether the IoT device satisfies the minimum data throughput when allocating resources, the invention prevents the phenomenon of resources being concentrated on some IoT devices, thereby enabling the allocation of resources so that multiple IoT devices satisfy QoS.

Description

Technology Field

[0001] The present invention relates to a resource allocation technology for wireless networks, and more specifically, to a technology for optimizing resource allocation in a wireless network composed of Access Points (APs) and Internet of Things (IoT) devices. Background Technology

[0002] As automation and real-time control technologies utilizing IoT devices advance, the number of IoT devices connected to wireless networks is increasing, and networks are becoming more complex. To ensure the Quality of Services (QoS) for each IoT device in a wireless network, it is necessary to satisfy the data throughput required by each IoT device.

[0003] Existing resource allocation technologies perform resource allocation by deriving optimal variables that maximize the network's total throughput while satisfying constraints. However, in situations where resources are limited and the number of IoT devices connected to each AP increases, it is difficult to derive optimal variables that satisfy all constraints.

[0004] Furthermore, existing resource allocation technologies focus on preventing interference, and as they prioritize allocating resources to IoT devices with high channel gain to maximize total throughput, there is a problem where the QoS of the remaining IoT devices degrades. Prior art literature

[0005] (Patent Document 0001) KR 10-2034571 B1(Patent Document 0002) KR 10-1372483 B1 The problem to be solved

[0006] The objective of the present invention is to solve the above problems and to provide a method and device for allocating resources in a wireless network such that the number of IoT devices satisfying the minimum data throughput is maximized in order to improve the total throughput of the network. means of solving the problem

[0007] A method for allocating resources in a wireless network according to one aspect of the present invention for achieving the above-mentioned purpose comprises: an initial resource allocation step of calculating an optimal variable such that the total throughput is maximized for each of a plurality of pre-configured IoT devices based on a connection variable and a transmission power variable according to whether the connection with a plurality of pre-configured APs is established; a step of dividing a plurality of IoT devices into a first set satisfying the individual data throughput and a second set not satisfying the individual data throughput, depending on whether the individual data throughput of each IoT device calculated from the optimal variable derived in the initial resource allocation step exceeds a pre-configured threshold value; and a step of updating the optimal variable by adjusting the transmission power variable so that the total throughput is maximized under the condition that the individual data throughput of the IoT devices included in the first set is limited to a pre-configured threshold value.

[0008] A resource allocation device for a wireless network according to another aspect of the present invention includes a communication unit, a memory in which computer-executable commands are stored, and a processor connected to the memory. The processor calculates an optimal variable that maximizes the total throughput according to a connection variable and a transmission power variable based on whether each of a plurality of pre-configured IoT devices is connected to a plurality of pre-configured APs, and classifies the plurality of IoT devices into a first set that satisfies the individual data throughput and a second set that does not satisfy the individual data throughput, depending on whether the individual data throughput of each IoT device calculated from the optimal variable exceeds a pre-configured threshold value. The processor updates the optimal variable by adjusting the transmission power variable to maximize the total throughput under the condition that the individual data throughput of the IoT devices included in the first set is limited to a pre-configured threshold value. Effects of the invention

[0009] According to the present invention, by performing resource allocation optimization of a network to maximize the number of IoT devices satisfying the minimum data throughput, there is an effect of guaranteeing the QoS of IoT devices in a network system.

[0010] In other words, by enabling services for more IoT devices within limited resources, it has the effect of improving the overall data throughput of the network.

[0011] The effects of the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description in the claims. Brief explanation of the drawing

[0012] FIG. 1 is a block diagram showing a wireless network system to which a resource allocation device of a wireless network according to an embodiment of the present invention is applied. FIG. 2 is a flowchart of a resource allocation method for a wireless network according to an embodiment of the present invention. FIG. 3 is a diagram showing a first algorithm for calculating the initial transmission power of an IoT device during the initial resource allocation process in embodiments of the present invention. FIG. 4 is a diagram showing a second algorithm for calculating the transmission power of an IoT device in the process of updating optimal variables in embodiments of the present invention. FIG. 5 is a diagram showing a third algorithm for calculating a linkage variable indicating whether an IoT device and an AP are linked during the process of updating optimal variables in embodiments of the present invention. FIG. 6 is a diagram showing a fourth algorithm for outputting the finally calculated optimal variable by repeating the process of updating the optimal variable until a predetermined condition is satisfied in embodiments of the present invention. Figure 7 is a graph showing the data throughput of each IoT device derived as a result of performing resource allocation optimization for IoT devices using the present invention and existing technology, respectively. Figure 8(a) is a graph showing the average number of IoT devices satisfying the requirements derived as a result of optimizing resource allocation for IoT devices using the present invention and existing technology, respectively, and (b) is a graph showing the probability that there are 5 and 7 or more serviceable IoT devices, respectively. Specific details for implementing the invention

[0013] Specific details regarding the problem to be solved, the means for solving the problem, and the effects of the invention as described above are included in the embodiments and drawings to be described below. The advantages and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described in detail below in conjunction with the accompanying drawings. Throughout the specification, the same reference numerals refer to the same components.

[0014] The present invention relates to a resource allocation technology for determining the connection between an IoT device and an AP and the transmission power of each IoT device so that the total throughput in a wireless network system is maximized.

[0015] In particular, the present invention is characterized by increasing the number of IoT devices satisfying minimum requirements during the optimization process of finding variables that maximize total throughput.

[0016] These features can be achieved by a configuration that determines whether the data throughput of each IoT device satisfies the minimum requirements and updates the optimal variables as a condition to limit the data throughput of the IoT device determined to satisfy the requirements.

[0017] Hereinafter, a method and apparatus for resource allocation of a wireless network according to embodiments of the present invention will be described in detail with reference to the attached drawings.

[0018] Referring to FIG. 1, a wireless network system to which a resource allocation device (100) according to the present invention is applied may include a server (10), K APs (20), and N IoT devices (30).

[0019] AP (20) can be managed by the server (10).

[0020] The IoT device (30) can perform downlink communication with any one AP (20) using a single antenna.

[0021] In downlink communication, one AP (20) can transmit data to multiple IoT devices (30) simultaneously, but each IoT device (30) can transmit data to one AP (20) due to hardware limitations.

[0022] A signal (y) received by the nth IoT device among N IoT devices (30). n ) can be represented as follows.

[0023]

[0024] Here, n={1, … , N} , k={1, … , K}, is a binary variable indicating whether the k-th AP and the n-th IoT device are associated, is a binary variable indicating whether the k-th AP and the n-th IoT device are a propagation channel, is the power allocated to the nth IoT device.

[0025] In Equation 1, the first term from the left of the right side represents the desired signal for the nth IoT device, the second term represents mutual interference due to frequency resource reuse, and the last term represents the additive white Gaussian noise (AWGN) of the nth IoT device.

[0026] Here, the AWGN for each IoT device has an average of 0, and the power spectral density of each noise ( ) and the power width of each IoT device ( Variance calculated by ) It may have a distribution that is ).

[0027] Considering that all APs (20) transmit signals to IoT devices (30) at the same frequency, the SINR (Signal to Interference plus Noise Ratio) ratio for the nth IoT device ( ) is calculated as shown in mathematical formula 2 below.

[0028]

[0029] Here, μ n are binary variables indicating the association between multiple APs and the nth IoT device ( It is a set of , k={1, … , K}), and h n are binary variables indicating whether multiple APs and the nth IoT device are on the propagation channel ( It is a set of , k={1, … , K}), and = , am.

[0030] Based on Equation 2, the data throughput of the nth IoT device can be summarized as follows:

[0031]

[0032] And, the total throughput of the network can be expressed as shown in the following mathematical formula.

[0033]

[0034] In existing technologies, the optimization of IoT networks was achieved by finding ψ and p that maximize the total network throughput shown in Equation 4 under the following constraints.

[0035] Constraint 1. Each IoT device can be connected to one AP.

[0036] Constraint 2. The sum of the transmission power provided to connected IoT devices from each AP must be less than or equal to the maximum transmission power of the AP.

[0037] Constraint 3. The data throughput of each IoT device must exceed the required threshold.

[0038] These existing resource allocation optimization techniques may face a problem where resource allocation becomes impossible because it is difficult to find an optimal variable that satisfies up to constraint 3 as the number of IoT devices included in the network increases in an environment with limited resources.

[0039] When performing optimization excluding constraint 3, most power resources are allocated to IoT devices with good channel gain to maximize total throughput, and there is a problem where the data throughput of the remaining IoT devices does not meet the minimum requirement threshold, resulting in a decrease in QoS.

[0040] The resource allocation device (100) according to the present invention uses mathematical formula 4 for the total network throughput, and in calculating the optimal variable, limits the data throughput of the IoT device to only the minimum requirement, thereby overcoming the problems of existing resource allocation optimization technology.

[0041] The resource allocation device (100) may include a communication unit (110), a memory (120), and a processor (130).

[0042] The communication unit (110) can perform communication with an external device including a server (10).

[0043] The memory (120) can store computer-executable instructions.

[0044] The processor (130) is connected to the communication unit (110) and the memory (120) and can calculate an optimal variable that maximizes the total network throughput by executing commands stored in the memory (120).

[0045] The steps of the resource allocation method according to another embodiment of the present invention illustrated in FIG. 2 can be implemented as computer instructions that perform specified functions and are loaded into the processor or memory of an electronic device capable of data processing (e.g., a general-purpose computer, a special-purpose computer, a portable notebook computer, a network computer) and can be performed by a processor (130).

[0046] Meanwhile, since the resource allocation method according to the present invention can be implemented as commands and stored in computer-readable memory, the server (10) may perform the resource allocation method according to the present invention without separately providing a resource allocation device (100) as in FIG. 1 according to an embodiment.

[0047] Hereinafter, for the convenience of explanation, the description will be based on a resource allocation device (100) independent of the server (10), and the content functionally corresponding to FIG. 2 will be described by matching the reference numerals.

[0048] The processor (130) can perform initial resource allocation to calculate an optimal variable that maximizes the total throughput for each of the configured multiple IoT devices based on a connection variable and a transmission power variable based on whether the device is connected to a configured multiple AP (S100).

[0049] Before performing initial resource allocation, the processor (130) can receive network information from the server (10) via the communication unit (110), including the number of APs included in the network, location information of each AP, maximum power that each AP can allocate, the number of IoT devices included in the network, location information of each IoT device, and bandwidth of each IoT device.

[0050] The processor (130) can pre-set the number of connection variables and transmission power variables for IoT devices based on whether multiple IoT devices and multiple APs included in the network are connected, based on the received network information, and then perform initial resource allocation (S100).

[0051] The processor (130) can perform initial resource allocation by determining values ​​for connection variables based on whether multiple IoT devices and multiple APs included in the network are connected based on large-scale fading, and by calculating transmission power variables such that the total network throughput is maximized under the constraint that the sum of transmission power variables representing the transmission power provided from each AP to the IoT device when the determined connection variables are substituted into a preset equation for the total network throughput does not exceed the maximum transmission power of each AP (S100).

[0052] The processor (130) can calculate initial transmission power variables from a convex objective function such as the following equation, which is derived by applying a logarithmic approximation to the total network throughput and constraint 2 on the transmission power of the AP presented in Equation 4.

[0053]

[0054] Here, is the bandwidth of each IoT device, and represents the SINR ratio of the nth IoT device.

[0055] and, and It can be expressed as shown in the following mathematical formula.

[0056]

[0057] The processor (130) uses the algorithm 1 shown in FIG. 3 to calculate a set of initial linkage variables based on large-scale fading ( The difference between the value of the most recently calculated transmission power variable and the value of the immediately preceding transmission power variable, based on ), is a preset threshold ( The process of calculating values ​​for transmission power variables for each IoT device satisfying Equation 5 is repeated until it becomes less than or equal to ), and the set of initial transmission power variables consisting of the last calculated values ​​for transmission power variables ( ) can be produced.

[0058] Subsequently, the processor (130) derives the optimal variable ( , Depending on whether the individual data throughput of each IoT device based on ) exceeds a preset threshold, it can be divided into a first set that satisfies the individual data throughput and a second set that does not satisfy the individual data throughput (S200).

[0059] Here, the optimal variable derived in the initial resource allocation stage ( , The first set distinguished based on ) can be represented as follows.

[0060]

[0061] Here, is a preset threshold for the nth IoT device, representing the minimum requirement for data throughput.

[0062] The processor (130) determines whether all IoT devices included in the network satisfy individual data throughput based on whether the number of IoT devices included in the first set, which is separated from the optimal variable derived in the initial resource allocation step, is equal to the total number of IoT devices included in the network (S300). If it is determined that all IoT devices do not satisfy individual data throughput because the number of IoT devices included in the first set is smaller than the total number of IoT devices included in the network, the processor can update the optimal variable by adjusting the transmission power variable so that the total throughput is maximized under the condition that the individual data throughput of the IoT devices included in the first set is limited to a preset threshold (S400).

[0063] The processor (130) can calculate a transmission power variable for each of the IoT devices included in the first set and the IoT devices included in the second set under conditions where the individual data throughput of the IoT devices included in the first set corresponds to a preset threshold, calculate a linkage variable based on the calculated transmission power variable to maximize the total throughput calculated from the linkage variable based on whether the IoT device and the AP are linked, and update the optimal variable (S400).

[0064] In updating the optimal variable, the processor (130) can first calculate the transmission power variable for each of the IoT devices included in the first set and the IoT devices included in the second set such that the sum of the individual data throughputs of the IoT devices not included in the first set (i.e., those in the second set) is maximized under the constraint that the individual data throughput of the IoT devices included in the first set must be equal to a preset threshold.

[0065] The processor (130) can calculate transmission power variables for each of the IoT devices included in the first set (Q) and the IoT devices included in the second set (N / Q) using the following mathematical formula.

[0066]

[0067] Here, is a binary variable indicating whether it corresponds to the power constraint of the k-th AP.

[0068] A set of transmission power variables for multiple IoT devices calculated by the processor (130) p ) can be represented as follows.

[0069]

[0070] Here, the right-hand side can be defined as shown in the mathematical formula below.

[0071]

[0072] Here, is defined by mathematical formula 8.

[0073] The processor (130) is a set of initial transmission power variables ( p After calculating (0)), the set of transmission power variables calculated immediately before ( p A new set of transmission power variables from (s) p (s+1)) can be updated.

[0074]

[0075] In this case, the Lagrangian multiplier can be updated as follows to impose a penalty for violating the limited power constraint.

[0076]

[0077] Here, means a sufficiently small preset step size.

[0078] The processor (130) calculates the set of transmission power variables and the Lagrangian multiplier by increasing the iteration exponent s using algorithm 2 shown in FIG. 4 until the set of transmission power variables and the Lagrangian multiplier reach convergence, and when convergence is reached, the previously calculated set of transmission power variables ( ) and the set of newly calculated transmission power variables that reach convergence ( The difference of ) is a preset threshold ( Determines whether it is less than or equal to ), and the preset threshold ( If it exceeds ), the process of calculating the set of transmission power variables and the Lagrangian multiplier is repeated until convergence, and the preset threshold ( When it becomes less than ), convergence is reached and the set of newly calculated transmission power variables ( By outputting ), the transmission power variable can be calculated.

[0079] After calculating the transmission power variable, the processor (130) replaces the connection variables for multiple APs of each IoT device calculated immediately prior to the current time point so that the AP associated with each IoT device is changed, and if the individual data throughput calculated from the replaced connection variable for the IoT device included in the first set of the calculated transmission power variable is greater than or equal to a preset threshold and the total throughput is greater than before the connection variables were replaced, the replaced connection variable can be output.

[0080] The processor (130) uses algorithm 3 shown in FIG. 5 to obtain a temporary set (F) satisfying the following objective function. temp ) can be produced.

[0081]

[0082] Specifically, the processor (130) has a current set (F) composed of pre-calculated linkage variables to indicate whether the IoT device and the AP are linked in correspondence with a plurality of IoT devices and a plurality of APs. curr A temporary set (F) in which the linkage variables for each IoT device and AP are changed by changing the position of the vector corresponding to each AP in ) temp Create ) and temporary set(F temp Satisfying the constraint that the data throughput of IoT devices belonging to the first set, calculated from the linkage variables of ), is greater than or equal to a preset threshold, and the temporary set (F temp The total throughput calculated from ) is the current set (F curr If it is greater than the total throughput calculated from ), the current set(F curr Temporary set(F) in ) temp The process of assigning ) is repeated until it is determined that there are no IoT devices to change the connection with the AP, and if it is determined that there are no IoT devices to change the connection with the AP, the current set (F at that time) curr By finally outputting ), the linked variable can be calculated.

[0083] After step S400 of updating the optimal variable, the processor (130) may add to the first set an IoT device among the IoT devices included in the second set whose individual data throughput calculated from the updated optimal variable exceeds a preset threshold (S500).

[0084] The processor (130) determines whether the number of IoT devices included in the first set is the same as before updating the optimal variable and whether the improvement rate of the total throughput is below a preset threshold value (S600), and if the number of IoT devices included in the first set is not the same as before updating the optimal variable or if the improvement rate of the total throughput exceeds the preset threshold value, the step S400 of updating the optimal variable may be performed again.

[0085] The processor (130) can repeat step S400 of updating the optimal variable and step S500 of adding to the first set until the number of IoT devices included in the first set is the same as before the most recent optimal variable update and the improvement rate of the total throughput is less than or equal to a preset threshold value.

[0086] Referring to Algorithm 4 of FIG. 6, the processor (130) can repeat the process of updating the optimal variable by obtaining a new transmission power variable that satisfies the condition of limiting the data throughput of the IoT device in the first set to a threshold value from the previously calculated linkage variables until the improvement rate according to the difference value calculated by subtracting the second total throughput based on the optimal variable calculated at the second time point (t-1), which is immediately before the first time point, from the first total throughput based on the optimal variable calculated at the first time point (t), which is most recently updated, is less than or equal to a preset threshold value, and until the number of IoT devices in the first set classified based on the optimal variable calculated at the first time point (t) becomes equal to the number of IoT devices in the first set classified based on the optimal variable calculated at the second time point (t-1), and obtaining a new linkage variable from the obtained new transmission power variable under the condition that the data throughput of the IoT device in the first set becomes greater than or equal to the threshold value.

[0087] The processor (130) can finally output the updated optimal variable when the improvement rate based on the difference value calculated by subtracting the second total throughput based on the optimal variable calculated at the second time point (t-1), which was updated immediately before the first time point, from the first total throughput based on the optimal variable calculated at the first time point (t), which was updated most recently, is less than or equal to a preset reference value, and the number of IoT devices belonging to the first set classified based on the optimal variable calculated at the first time point (t) becomes equal to the number of IoT devices belonging to the first set classified based on the optimal variable calculated at the second time point (t-1).

[0088] According to the above configuration, the number of IoT devices satisfying minimum requirements can be increased during the process of allocating resources to maximize the total throughput of the network.

[0089] In other words, it is possible to prevent the problem of overall QoS degrading due to resources being concentrated on some IoT devices during the resource optimization process.

[0090] Below, an experiment was conducted to confirm that performance is improved compared to existing technology when resource allocation is performed according to an embodiment of the present invention.

[0091] Existing technologies utilized Nearest AP association (Nearest-APA), which selects the AP closest in terms of geometry, and Equal power allocation (Equal-PA), which allocates a fixed transmission power equally to all IoT devices.

[0092] The experiment was conducted under experimental conditions assuming a network environment including 8 IoT devices and 3 APs.

[0093] Referring to Fig. 7, when the present invention is used (Proposed DIF-PA+Proposed CG-APA), it can be seen that the data throughput of IoT devices 1, 2, 3, 4, 6, and 7 satisfies the threshold value, and that 6 out of 8 IoT devices satisfy the minimum requirements.

[0094] In contrast, in the case of existing technologies using Nearest-APA and Equal-PA, it can be seen that there are only 3 IoT devices satisfying the threshold, namely devices 2, 6, and 7, due to the skewed data throughput of IoT device 2.

[0095] Referring to Fig. 8(a), in the case of the present invention (Proposed DIF-PA+Proposed CG-APA), there are an average of 6.3 IoT devices satisfying the minimum data throughput requirement (0.5 (bits / s / Hz)), whereas in the case of the existing technology (Nearest-APA+Equal-PA), there are an average of 2.5 IoT devices satisfying the minimum data throughput requirement, which can be confirmed once again that resources are concentrated on a small number of IoT devices.

[0096] In addition, referring to FIG. 8(b), in the case of the existing technology, the probability of having 5 or more serviceable IoT devices is less than 10% and the probability of having 7 or more is less than 1%, whereas in the present invention, the probability of having 5 or more is more than 60% and the probability of having 7 or more is more than 10%.

[0097] In other words, when allocating resources according to the present invention, there is an advantage in that limited resources are evenly distributed compared to existing technologies, allowing multiple IoT devices to satisfy QoS.

[0098] A person skilled in the art to which the present invention pertains will understand that the present invention may be implemented in other specific forms without altering its technical concept or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims set forth below rather than by the detailed description above, and all modifications or variations derived from the claims and their equivalents should be interpreted as being included within the scope of the present invention. Explanation of the symbols

[0099] 10 : Server 20 : AP 30: IoT devices 100: Resource allocation unit 110 : Communications Department 120 : Memory 130 : Processor

Claims

Claim 1 A method for allocating resources in a wireless network, performed by a resource allocation device comprising: a communication unit for performing communication with an external device; a memory for storing computer-executable commands; and a processor connected to the communication unit and the memory for executing commands stored in the memory. The method comprises: an initial resource allocation step of calculating an optimal variable such that the total throughput is maximized for each of a plurality of pre-configured IoT devices based on a connection variable and a transmission power variable according to whether the individual data throughput of each of the IoT devices calculated from the optimal variable derived in the initial resource allocation step exceeds a pre-configured threshold value; a step of dividing the plurality of IoT devices into a first set satisfying the individual data throughput and a second set not satisfying the individual data throughput; and a step of updating the optimal variable by adjusting the transmission power variable so that the total throughput is maximized under the condition that the individual data throughput of the IoT devices included in the first set is limited to a pre-configured threshold value. Claim 2 A method for allocating resources in a wireless network according to claim 1, wherein the step of updating the optimal variable comprises: a step of calculating a transmission power variable for each of the IoT devices included in the first set and the IoT devices included in the second set under conditions where the individual data throughput of the IoT devices included in the first set corresponds to a preset threshold value; and a step of calculating a linkage variable such that the total throughput calculated from a linkage variable based on the calculated transmission power variable is maximized according to whether the IoT devices and the AP are linked. Claim 3 A method for allocating resources in a wireless network according to paragraph 2, wherein the step of calculating the linkage variable involves swapping the linkage variables for a plurality of APs of each IoT device calculated immediately prior to the current time point so that the AP linked to each IoT device is changed, and outputting the swapped linkage variable when the individual data throughput calculated from the calculated transmission power variable and the linked variable for the IoT device included in the first set is greater than or equal to a preset threshold and the total throughput is greater than before the linkage variables were swapped. Claim 4 A method for allocating resources in a wireless network according to claim 1, further comprising, after the step of updating the optimal variable, a step of adding to the first set an IoT device among the IoT devices included in the second set whose individual data throughput calculated from the updated optimal variable exceeds a preset threshold; and repeating the step of updating the optimal variable and the step of adding to the first set until the number of IoT devices included in the first set is the same as before updating the optimal variable and the improvement rate of the total throughput is less than or equal to a preset reference value. Claim 5 A wireless network resource allocation device comprising: a communication unit; a memory in which computer-executable commands are stored; and a processor connected to said memory; wherein the processor, by executing commands stored in said memory, calculates an optimal variable that maximizes the total throughput according to a connection variable and a transmission power variable based on whether each of a preset plurality of IoT devices is connected to a preset plurality of APs, and classifies the preset plurality of IoT devices into a first set satisfying the individual data throughput and a second set not satisfying the individual data throughput, depending on whether the individual data throughput of each IoT device calculated from the calculated optimal variable exceeds a preset threshold, and updates the optimal variable by adjusting the transmission power variable to maximize the total throughput under the condition that the individual data throughput of the IoT devices included in the first set is limited to a preset threshold. Claim 6 A resource allocation device for a wireless network, wherein, in updating the optimal variable, the processor calculates a transmission power variable for each of the IoT devices included in the first set and the IoT devices included in the second set under conditions where the individual data throughput of the IoT devices included in the first set corresponds to a preset threshold, and calculates a linkage variable based on the calculated transmission power variable such that the total throughput calculated from the linkage variable according to whether the IoT device and the AP are linked is maximized. Claim 7 A resource allocation device for a wireless network according to claim 6, wherein the processor, in calculating the linkage variable, swaps the linkage variables for a plurality of APs of each IoT device calculated immediately prior to the current time point so that the AP linked to each IoT device is changed, and outputs the swapped linkage variable when the individual data throughput calculated from the calculated transmission power variable and the swapped linkage variable for the IoT device included in the first set is greater than or equal to a preset threshold and the total throughput is greater than before the linkage variables were swapped. Claim 8 A resource allocation device for a wireless network according to claim 5, wherein the processor, after updating the optimal variable, reclassifies among the IoT devices included in the second set whose individual data throughput calculated from the updated optimal variable exceeds a preset threshold value into the first set, and repeats the steps of updating the optimal variable and adding to the first set until the number of IoT devices included in the first set is the same as before updating the optimal variable and the improvement rate of the total throughput is less than or equal to a preset reference value.

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