A cooperative resource allocation method and device in a hybrid NOMA-FDMA Internet of Things system

Abstract

The present invention discloses a cooperative resource allocation method and device in a hybrid NOMA-FDMA Internet of Things system, and the proposed method includes the following steps: Step 1: Establish an optimization problem model for cooperative resource allocation in a hybrid NOMA-FDMA Internet of Things system; Step 2: Convert the optimization problem established in Step 1 into a two-layer optimization problem nested inside and outside, wherein the outer optimization problem optimizes channel allocation, and the inner optimization problem optimizes time and power allocation; Step 3: Solve the inner optimization problem for all combinations of hybrid relays and channel allocations; Step 4: Based on the solution result of the inner optimization problem, solve the outer optimization problem by the Hungarian algorithm to obtain the channel allocation result; Step 5: Obtain time and power allocation according to the channel allocation result. The cooperative resource allocation method in a hybrid NOMA-FDMA Internet of Things system of the present invention maximizes the amount of transmitted data of all Internet of Things devices by optimizing various resources, and improves the overall transmission efficiency of the system.

Description

Technical Field

[0001] The present invention belongs to the field of wireless communications and relates to a cooperative resource allocation method and device in a hybrid NOMA-FDMA Internet of Things system. Background Art

[0002] Wireless communication technology has become a research focus in recent years, and wireless energy transmission in wireless communication is also a research hotspot, and radio frequency technology is one of the important ways of wireless energy transmission.

[0003] Since wireless energy transmission can free devices from dependence on power supply, and in today's energy shortage, the collection and utilization of wireless energy has very important research and application value. Relay technology is an important technology in wireless communication, which can effectively improve signal quality and expand the coverage area of ​​base stations to enable more devices to access. In the Internet of Things system, it may not be possible to continuously interact with the base station relying solely on the user's own energy, but when wireless communication is completed with the help of relays, it can not only increase the coverage area of ​​the base station, but also provide wireless energy to the terminal through the base station, so that the terminal can work longer and transmit more data. Multiple access technology is a technology used to distinguish different users in wireless communication.

[0004] The non-orthogonal multiple access technology that emerged with 5G technology is gradually being used in wireless communications, providing a foundation for the Internet of Things system to achieve ultra-large-scale connections. In practical applications, non-orthogonal multiple access is often used in combination with traditional orthogonal multiple access technology to meet different needs in different scenarios. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a cooperative resource allocation method and device in a hybrid NOMA-FDMA Internet of Things system. Wireless energy transmission and hybrid NOMA-FDMA multiple access technology are adopted to supply energy to the Internet of Things terminal and assist the terminal in communicating with the base station with the help of hybrid relay, so as to maximize the total amount of data transmitted by the system while meeting the energy consumption requirements of the system.

[0006] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0007] In a first aspect, the present invention provides a cooperative resource allocation method in a hybrid NOMA-FDMA Internet of Things system, based on the Internet of Things system;

[0008] The IoT system includes multiple IoT terminals, multiple hybrid relays and a base station; multiple hybrid relays are connected to the base station, and each hybrid relay serves a group of IoT terminals; all terminals served by each hybrid relay transmit their own data to the hybrid relay based on the NOMA multiple access mode, and then the hybrid relay communicates with the base station through FDMA;

[0009] The entire data transmission process is divided into three stages, namely, hybrid relay power supply, terminal data transmission to relay, and hybrid relay data transmission to base station.

[0010] The cooperative resource allocation method maximizes the amount of data transmitted by all IoT device terminals by optimizing time slots and power channel allocation, and specifically includes the following steps:

[0011] Step 1: Establish an optimization problem model for cooperative resource allocation in a hybrid NOMA-FDMA IoT system;

[0012] Step 2: Convert the established optimization problem into a two-layer optimization problem with inner and outer nesting, where the outer optimization problem is used to optimize channel allocation, and the inner optimization problem is used to optimize time and power allocation;

[0013] Step 3: Solve the inner optimization problem for all combinations of hybrid relays and channel allocations;

[0014] Step 4: Based on the solution of the inner optimization problem, the Hungarian algorithm is used to solve the outer optimization problem to obtain the channel allocation result;

[0015] Step 5: Obtain time and power allocation based on the channel allocation results.

[0016] Furthermore, the optimization problem model of cooperative resource allocation in the hybrid NOMA-FDMA IoT system is established including:

[0017] Establish the optimization problem model P1 solved by the cooperative resource allocation method in the hybrid NOMA-FDMA IoT system:

[0018] P1:

[0019] Constraint C1:

[0020] Constraint C2:

[0021] Constraint C3:

[0022] Constraint C4: τ 1，m +τ 2，m +τ 3，m ≤1

[0023] Constraint C5: τ 1，m ≥0,τ 2，m ≥0,τ 3，m ≥0

[0024] Constraint C6:

[0025] Constraint C7:

[0026] Constraint C8:

[0027] The goal of this problem is to maximize the total amount of data transmitted by the system. and are the set of hybrid relays, the set of IoT terminals served by the mth hybrid relay, and the set of channels;

[0028] and They respectively represent the maximum total amount of data transmitted from the IoT terminal responsible for the m-th hybrid relay to the hybrid relay and the maximum amount of data transmitted from the m-th hybrid relay to the base station;

[0029] τ 1，m , τ 2，m and τ 3，m They are respectively the time when the hybrid relay transmits wireless energy to the IoT terminal it is responsible for, the time when the IoT terminal sends information to the hybrid relay it belongs to, and the time when the hybrid relay sends data to the base station;

[0030] p m，n ,q m，n and b m，n，k They represent the power of each hybrid relay broadcasting energy to the terminal, the transmission power of the hybrid relay transmitting data to the base station, and the transmission power of the kth terminal on channel n that the mth hybrid relay is responsible for; α m，n is the channel allocation function, α m，n =1 means that channel n is allocated to hybrid relay m and its responsible IoT terminal, α m，n =0 means that channel n is not allocated to hybrid relay m and the IoT terminal it is responsible for;

[0031] g m，n，k 、h m，n，k and γ m，n They respectively represent the channel gain on channel n from the m-th hybrid relay to the k-th terminal it is responsible for, the channel gain on channel n between the k-th terminal and the hybrid relay m to which it belongs, and the channel gain on channel n between the m-th hybrid relay and the base station;

[0032] P m and E m They represent the peak transmit power limit on each channel and the total consumed energy limit of the hybrid relay m respectively;

[0033] Constraints C1 and C2 respectively indicate that each hybrid relay is assigned only one channel and each channel is assigned only one hybrid relay; Constraint C3 indicates that α m，n The value of can only be 0 or 1; Constraint C4 indicates that the sum of the lengths of the three transmission time slots does not exceed the normalized 1; The three transmission time slots are: the relay transmission wireless energy time slot, the terminal to the relay transmission data, the relay to the base station transmission data;

[0034] Constraint C5 indicates that the three transmission time slots are all non-negative; constraint C6 indicates that the energy consumed by the IoT terminal to transmit data to the hybrid relay in the second transmission time slot should not be greater than the wireless energy collected by the terminal in the first stage; constraint C7 indicates the total energy consumption constraint of the hybrid relay; constraint C8 indicates that the transmission power of the hybrid relay and the terminal is non-negative.

[0035] Furthermore, the established optimization problem is transformed into a two-layer optimization problem with inner and outer nesting, including:

[0036] Step 2-1: Let constraint C6 be true, and from constraint C1 we can get Let p m，n Its maximum value P m , that is, p m，n =P m .

[0037] Step 2-2: Rewrite constraint C7 as follows:

[0038] Constraint C9:

[0039] Step 2-3: Order and They represent the maximum total amount of data transmitted by the IoT terminal to the hybrid relay m and the maximum amount of data transmitted by the hybrid relay m to the base station when the channel n is allocated to the hybrid relay m. Problem P1 is reconstructed into two layers of inner and outer nested problems, where the outer optimization problem optimizes α to solve the channel allocation problem, which is modeled as:

[0040] P2:

[0041] Constraints C1, C2, and C3

[0042] in The objective function value obtained for the following inner optimization problem P3, where: is the total amount of data transmitted between the terminal and the hybrid relay m on channel n, is the total amount of data transmitted between hybrid relay m and the base station on channel n, and the smaller one of the two represents the maximum amount of data transmitted to the base station by all terminals that hybrid relay m is responsible for on channel n;

[0043] The inner optimization problem aims to optimize the maximum amount of data transmitted by each hybrid relay on each channel and is modeled as:

[0044] P3:

[0045] Constraint C9: τ 1，m P m +τ 3，m q m，n ≤E m

[0046] Constraint C10: 0 ≤ q m，n ≤P m

[0047] Constraint C4, Constraint C5

[0048] Furthermore, for all combinations of hybrid relays and channel allocations, the inner optimization problem is solved to obtain the corresponding time slot allocation τ 1，m，n , τ 2，m，n , τ 3，m，n and the transmission power q of the hybrid relay to transmit data to the base station m，n ,include:

[0049] Step 3-1: In order to solve the inner optimization problem P3, introduce the auxiliary variable η and rewrite the problem P3 as P4:

[0050] P4:

[0051] Constraint C11: R 1，m，n ≥η

[0052] Constraint C12: R 2，m，n ≥η

[0053] Constraints C4, C5, C9, and C10 remain unchanged.

[0054] Step 3-2: To solve problem P4, use the binary search method to search for the optimal solution for η. Given the initial search interval [η min , η max ].

[0055] Step 3-3: Order

[0056] Step 3-4: Let u m，n =τ 3，m q m，n , and test the feasibility of problem P4 by modeling the following problem P5:

[0057] P5:

[0058] Constraint C13: 0 ≤ u m，n≤τ 3，m P m

[0059] Constraint C14:

[0060] Constraint C15:

[0061] and constraints C4 and C5

[0062] Let constraints C14 and C15 hold true, that is, the total amount of data transmitted between the terminal and the hybrid relay m on channel n is equal to the total amount of data transmitted between the hybrid relay m and the base station on channel n, simplifying problem P5 to problem P6:

[0063] P6:

[0064] Constraint C16:

[0065] Constraint C17:

[0066] Solve problem P6 using the Lagrange multiplier method;

[0067] Step 3-5: From the constraints C14 and C15 of the equation, we get When τ 1，m P m +u m，n ≤E m When η min =η; otherwise, let η max =η;

[0068] Step 3-6: If η has not converged, repeat steps 3-3 to 3-5; otherwise, proceed to the next step;

[0069] Step 3-7: Order R m，n =η. Let τ 1，m，n , τ 2，m，n , τ 3，m，n They represent the optimized time slot τ when hybrid relay m is assigned channel n. 1，m , τ 2，m , τ 3，m The value of τ 1，m，n =τ 1，m , τ 2，m，n =τ 2，m , τ 3，m，n =τ 3，m .

[0070] Further, the method for solving problem P6 using the Lagrange multiplier method includes: introducing a Lagrange factor λ, and repeatedly executing steps 3-4-1 to 3-4-4 until λ converges;

[0071] Step 3-4-1: Given the initial search interval of λ [λ min ,λ max ].

[0072] Step 3-4-2: Order

[0073] Step 3-4-3: By finding the Langrange function For τ 2，m and τ 3，m The partial derivative of , and set it to zero, we get τ 2，m and τ 3，m The expression is as follows:

[0074]

[0075]

[0076] Step 3-4-4: When τ 2，m and τ 3，m When constraint C16 is satisfied, let λ max =λ; otherwise, let λ min =λ.

[0077] Furthermore, based on the solution of the inner optimization problem, the Hungarian algorithm is used to solve the outer optimization problem to obtain the channel allocation result, including:

[0078] Use the Hungarian algorithm to solve problem P2 and obtain the value of the channel allocation result α. If α m，n =1, then channel n is allocated to hybrid relay m, if α m，n =0, it is not allocated to relay m.

[0079] Furthermore, a time and power allocation result is obtained according to the channel allocation result, wherein the time and power allocation result includes the optimal channel n * The time slot allocation value τ 1，m , τ 2，m , τ 3，m and the power P of each hybrid relay broadcasting energy to the terminal m，n , the transmission power b of the kth terminal on channel n that the mth hybrid relay is responsible for m，n，k , the specific methods include:

[0080] Step 5-1: Let n * represents the channel allocated to each hybrid relay m, that is, For each hybrid relay m, let

[0081] Step 5-2: For each hybrid relay m and channel n, if α m，n =1, then let p m，n =P m ; otherwise, let p m，n =0,q m，n =0.

[0082] Step 5-3: For each hybrid relay m and its responsible terminal k, and channel n, if α m，n =1, from the equality constraints C6 and C1, we can get Otherwise, let b m，n，k =0.

[0083] In a second aspect, the present invention provides a cooperative resource allocation device in a hybrid NOMA-FDMA Internet of Things system, based on the Internet of Things system;

[0084] The IoT system includes multiple IoT terminals, multiple hybrid relays and a base station; multiple hybrid relays are connected to the base station, and each hybrid relay serves a group of IoT terminals; all terminals served by each hybrid relay transmit their own data to the hybrid relay based on the NOMA multiple access mode, and then the hybrid relay communicates with the base station through FDMA;

[0085] The entire data transmission process is divided into three stages, namely, hybrid relay power supply, terminal data transmission to relay, and hybrid relay data transmission to base station.

[0086] The cooperative resource allocation device maximizes the amount of data transmitted by all IoT device terminals by optimizing time slots and power channel allocation, specifically including:

[0087] Modeling module: used to establish the optimization problem model of cooperative resource allocation in hybrid NOMA-FDMA IoT system;

[0088] Problem conversion module: used to convert the established optimization problem into a two-layer optimization problem with inner and outer nesting, where the outer optimization problem is used to optimize channel allocation, and the inner optimization problem is used to optimize time and power allocation;

[0089] Inner layer solving module: used to solve the inner layer optimization problem for all combinations of hybrid relays and channel allocations;

[0090] Outer layer solution module: used to solve the outer layer optimization problem based on the inner layer optimization problem solution result, and obtain the channel allocation result by solving the outer layer optimization problem through the Hungarian algorithm;

[0091] Output module: used to obtain time and power allocation according to channel allocation results.

[0092] Compared with the prior art, the present invention has the following beneficial effects:

[0093] (1) The present invention proposes a cooperative resource allocation method in a hybrid NOMA-FDMA IoT system, which maximizes the amount of data delivered by all IoT devices by allocating channels to the hybrid relay and optimizing the transmission time slots of the system, thereby improving the overall transmission efficiency of the system.

[0094] The present invention proposes a cooperative resource allocation method in a hybrid NOMA-FDMA Internet of Things system, and proposes a new resource allocation method, that is, the terminal uses the energy provided by the relay to communicate with the base station, which reduces the energy consumption of the terminal and reduces the total energy consumption of the Internet of Things system.

[0095] (2) The present invention realizes large-scale access of IoT terminals and improves system transmission efficiency through hybrid multiple access technology. The terminals communicate with the relays through NOMA technology, and the relays communicate with the base stations through FDMA technology, which reduces the system transmission delay and increases the system's transmission data volume. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 A system model diagram of the Internet of Things system for cooperative resource allocation;

[0097] Figure 2 Slot allocation graph for cooperative resource allocation in hybrid NOMA-FDMA IoT system;

[0098] Figure 3 Flowchart of the cooperative resource allocation algorithm in hybrid NOMA-FDMA IoT system. DETAILED DESCRIPTION

[0099] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0100] Embodiment 1:

[0101] A method for cooperative resource allocation in a hybrid NOMA-FDMA Internet of Things system, characterized in that the hybrid relay uses wireless energy transmission to power the Internet of Things terminal and uses the hybrid multiple access technology NOMA-FDMA to assist the terminal in communicating with the base station. The Internet of Things system includes multiple Internet of Things terminals, M hybrid relays and a base station, and each hybrid relay serves a group of Internet of Things terminals. All terminals served by each hybrid relay transmit their own data to the hybrid relay based on the NOMA technology, and then the hybrid relay transmits the received signal from the terminal to the base station through the FDMA technology. The entire data transmission process is divided into three stages, namely, the hybrid relay supplies power, the terminal transmits data to the relay, and the relay transmits data to the base station. By optimizing the time slot, power and channel allocation scheme, the amount of transmitted data of all Internet of Things terminals is maximized, which specifically includes the following steps:

[0102] Step 1: Establish the optimization problem model solved by the cooperative resource allocation method in the hybrid NOMA-FDMA IoT system;

[0103] Establish the optimization problem model P1 solved by the cooperative resource allocation method in the hybrid NOMA-FDMA IoT system:

[0104] P1:

[0105] Constraint C1:

[0106] Constraint C2:

[0107] Constraint C3:

[0108] Constraint C4: τ 1，m +τ 2，m +τ 3，m ≤1

[0109] Constraint C5: τ 1，m ≥0,τ 2，m ≥0,τ 3，m ≥0

[0110] Constraint C6:

[0111] Constraint C7:

[0112] Constraint C8:

[0113] The goal of this problem is to maximize the total amount of data transmitted by the system. and are the set of hybrid relays, the set of IoT terminals served by the mth hybrid relay, and the set of channels; and They represent the maximum total amount of data transmitted from the IoT terminal to the hybrid relay and the maximum amount of data transmitted from the m-th hybrid relay to the base station; τ 1，m , τ 2，m and τ 3，m They are the time when the hybrid relay transmits wireless energy to the IoT terminal it is responsible for, the time when the IoT terminal sends information to the hybrid relay it belongs to, and the time when the hybrid relay sends data to the base station; m，n ,q m，n and b m，n，k They represent the power of each hybrid relay broadcasting energy to the terminal, the transmission power of the hybrid relay transmitting data to the base station, and the transmission power of the kth terminal on channel n that the mth hybrid relay is responsible for; α m，n is the channel allocation function, α m，n =1 means that channel n is allocated to hybrid relay m and its responsible IoT terminal, α m，n = 0 means that channel n is not allocated to hybrid relay m and its responsible IoT terminal; g m，n，k 、h m，n，k and γ m，n represent the channel gain on channel n from the mth hybrid relay to the kth terminal it is responsible for, the channel gain on channel n between the kth terminal and its hybrid relay m, and the channel gain on channel n between the mth hybrid relay and the base station; P m and E m They represent the peak transmit power limit on each channel and the total consumed energy limit of the hybrid relay m respectively;

[0114] Constraints C1 and C2 respectively indicate that each hybrid relay is assigned only one channel and each channel is assigned only one hybrid relay; Constraint C3 indicates that α m，n The value of can only be 0 or 1; constraint C4 indicates that the sum of the lengths of the three transmission time slots (relay transmission wireless energy time slot, terminal to relay transmission data, relay to base station transmission data) does not exceed the normalized 1; constraint C5 indicates that the three transmission time slots are all non-negative; constraint C6 indicates that the energy consumed by the IoT terminal to transmit data to the hybrid relay in the second transmission time slot should not be greater than the wireless energy collected by the terminal in the first stage; constraint C7 indicates the total energy consumption constraint of the hybrid relay; constraint C8 indicates that the transmission power of the hybrid relay and the terminal is non-negative.

[0115] Step 2: Convert the optimization problem established in step 1 into a two-layer optimization problem nested inside and outside, where the outer optimization problem optimizes channel allocation and the inner optimization problem optimizes time and power allocation;

[0116] Step 2-1: Let constraint C6 be true, and from constraint C1 we can get Let p m，n Its maximum value P m , that is, p m，n =P m .

[0117] Step 2-2: Rewrite constraint C7 as follows:

[0118] Constraint C9:

[0119] Step 2-3: Order and They represent the maximum total amount of data transmitted by the IoT terminal to the hybrid relay m and the maximum amount of data transmitted by the hybrid relay m to the base station when the channel n is allocated to the hybrid relay m. Problem P1 is reconstructed into two layers of inner and outer nested problems, where the outer optimization problem optimizes α to solve the channel allocation problem, which is modeled as:

[0120] P2:

[0121] Constraints C1, C2, and C3

[0122] in The objective function value obtained for the following inner optimization problem P3, where: is the total amount of data transmitted between the terminal and the hybrid relay m on channel n, is the total amount of data transmitted between hybrid relay m and the base station on channel n. The smaller of the two represents the maximum amount of data transmitted to the base station by all terminals that hybrid relay m is responsible for on channel n. The inner optimization problem aims to optimize the maximum amount of data transmitted by each hybrid relay on each channel and is modeled as:

[0123] P3:

[0124] Constraint C9: τ 1，m P m +τ 3，m q m，n ≤E m

[0125] Constraint C10: 0 ≤ q m，n ≤P m

[0126] Constraint C4, Constraint C5

[0127] Step 3: Solve the inner optimization problem for all combinations of hybrid relays and channel allocations;

[0128] Step 3-1: In order to solve the inner optimization problem P3, introduce the auxiliary variable η and rewrite the problem P3 as P4:

[0129] P4:

[0130] Constraint C11: R 1，m，n ≥η

[0131] Constraint C12: R 2，m，n ≥η

[0132] Constraints C4, C5, C9, and C10 remain unchanged.

[0133] Step 3-2: To solve problem P4, use the binary search method to search for the optimal solution for η. Given the initial search interval [η min , η max ].

[0134] Step 3-3: Order

[0135] Step 3-4: Let u m，n =τ 3，m q m，n , and test the feasibility of problem P4 by modeling the following problem P5:

[0136] P5:

[0137] Constraint C13: 0 ≤ u m，n ≤τ 3，m P m

[0138] Constraint C14:

[0139] Constraint C15:

[0140] and constraints C4 and C5

[0141] Let constraints C14 and C15 hold true, that is, the total amount of data transmitted between the terminal and the hybrid relay m on channel n is equal to the total amount of data transmitted between the hybrid relay m and the base station on channel n, simplifying problem P5 to problem P6:

[0142] P6:

[0143] Constraint C16:

[0144] Constraint C17:

[0145] Use the Lagrange multiplier method to solve problem P6. Specifically, introduce the Lagrange factor λ and repeat steps 3-4-1 to 3-4-4 until λ converges.

[0146] Step 3-4-1: Given the initial search interval of λ [λ min ,λ max ].

[0147] Step 3-4-2: Order

[0148] Step 3-4-3: By finding the Langrange function For τ 2，m and τ 3，m The partial derivative of , and set it to zero, we get τ 2，m and τ 3，m The expression is as follows:

[0149]

[0150]

[0151] Step 3-4-4: When τ 2，m and τ 3，m When constraint C16 is satisfied, let λ max =λ; otherwise, let λ min =λ.

[0152] Step 3-5: From the constraints C14 and C15 of the equation, we get When τ 1，m P m +u m，n ≤E m When η min =η; otherwise, let η max =η.

[0153] Step 3-6: If η has not converged, repeat steps 3-3 to 3-5; otherwise, proceed to the next step.

[0154] Step 3-7: Order R m，n =η. Let τ 1，m，n , τ 2，m，n , τ 3，m，n They represent the optimized time slot τ when hybrid relay m is assigned channel n. 1，m , τ 2，m , τ 3，m The value of τ 1，m，n =τ 1，m , τ 2，m，n =τ 2，m , τ3，m，n =τ 3，m .

[0155] Step 4: Based on the solution of the inner optimization problem, the Hungarian algorithm is used to solve the outer optimization problem to obtain the channel allocation result;

[0156] Solve problem P2 using the Hungarian algorithm and obtain the value of α.

[0157] Step 5: Obtain time and power allocation based on the channel allocation results.

[0158] Step 5-1: Let n * represents the channel allocated to each hybrid relay m, that is, For each hybrid relay m, let

[0159] Step 5-2: For each hybrid relay m and channel n, if α m，n =1, then let p m，n =P m ; otherwise, let p m，n =0,q m，n =0.

[0160] Step 5-3: For each hybrid relay m and its responsible terminal k, and channel n, if α m，n =1, from the equality constraints C6 and C1, we can get Otherwise, let b m，n，k =0.

[0161] Embodiment 2:

[0162] This embodiment provides a cooperative resource allocation device in a hybrid NOMA-FDMA Internet of Things system, based on the Internet of Things system;

[0163] The IoT system includes multiple IoT terminals, multiple hybrid relays and a base station; multiple hybrid relays are connected to the base station, and each hybrid relay serves a group of IoT terminals; all terminals served by each hybrid relay transmit their own data to the hybrid relay based on the NOMA multiple access mode, and then the hybrid relay communicates with the base station through FDMA;

[0164] The entire data transmission process is divided into three stages, namely, hybrid relay power supply, terminal data transmission to relay, and hybrid relay data transmission to base station.

[0165] The cooperative resource allocation device maximizes the amount of data transmitted by all IoT device terminals by optimizing time slots and power channel allocation, specifically including:

[0166] Modeling module: used to establish the optimization problem model of cooperative resource allocation in hybrid NOMA-FDMA IoT system;

[0167] Problem conversion module: used to convert the established optimization problem into a two-layer optimization problem with inner and outer nesting, where the outer optimization problem is used to optimize channel allocation, and the inner optimization problem is used to optimize time and power allocation;

[0168] Inner layer solving module: used to solve the inner layer optimization problem for all combinations of hybrid relays and channel allocations;

[0169] Outer layer solution module: used to solve the outer layer optimization problem based on the inner layer optimization problem solution result, and obtain the channel allocation result by solving the outer layer optimization problem through the Hungarian algorithm;

[0170] Output module: used to obtain time and power allocation according to channel allocation results.

[0171] The device of this embodiment can be used to implement the method described in the first embodiment.

[0172] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0173] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0174] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0175] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0176] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A cooperative resource allocation method in a hybrid NOMA-FDMA Internet of Things system, characterized in that: Based on the Internet of Things system; The IoT system includes multiple IoT terminals, multiple hybrid relays and a base station; multiple hybrid relays are connected to the base station, and each hybrid relay serves a group of IoT terminals; all terminals served by each hybrid relay transmit their own data to the hybrid relay based on the NOMA multiple access mode, and then the hybrid relay communicates with the base station through FDMA; The cooperative resource allocation method comprises the following steps: Step 1: Establish an optimization problem model for cooperative resource allocation in a hybrid NOMA-FDMA IoT system; Step 2: Convert the established optimization problem into a two-layer optimization problem with inner and outer nesting, where the outer optimization problem is used to optimize channel allocation, and the inner optimization problem is used to optimize time and power allocation; Step 3: For all combinations of hybrid relays and channel allocations, solve the inner optimization problem and obtain the corresponding time slot allocation τ 1,m,n , τ 2,m,n , τ 3,m,n and the transmission power q of the hybrid relay to transmit data to the base station m,n ; Step 4: Based on the solution of the inner optimization problem, the outer optimization problem is solved by the Hungarian algorithm to obtain the channel allocation result; Step 5: Obtain time and power allocation results based on the channel allocation results, wherein the time and power allocation results include the optimal channel n * The time slot allocation value τ 1,m , τ 2,m , τ 3,m and the power p of each hybrid relay broadcasting energy to the terminal m,n , the transmission power b of the kth terminal on channel n that the mth hybrid relay is responsible for m,n,k ; The optimization problem model for cooperative resource allocation in a hybrid NOMA-FDMA IoT system includes: Establish the optimization problem model P1 solved by the cooperative resource allocation method in the hybrid NOMA-FDMA IoT system: P1： Constraint C1: Constraint C2: Constraint C3: constraintC4:t 1,m +t 2,m +t 3,m ≤1 constraintC5:t 1,m ≥0,τ 2,m ≥0,τ 3,m ≥0 Constraint C6: Constraint C7: Constraint C8: The goal of this problem is to maximize the total amount of data transmitted by the system. and are the set of hybrid relays, the set of IoT terminals served by the mth hybrid relay, and the set of channels; and They respectively represent the maximum total amount of data transmitted from the IoT terminal responsible for the m-th hybrid relay to the hybrid relay and the maximum amount of data transmitted from the m-th hybrid relay to the base station; τ 1,m , τ 2,m and τ 3,m They are respectively the time when the hybrid relay transmits wireless energy to the IoT terminal it is responsible for, the time when the IoT terminal sends information to the hybrid relay it belongs to, and the time when the hybrid relay sends data to the base station; p m,n ,q m,n and b m,n,k They represent the power of each hybrid relay broadcasting energy to the terminal, the transmission power of the hybrid relay transmitting data to the base station, and the transmission power of the kth terminal on channel n that the mth hybrid relay is responsible for; α m,n is the channel allocation function, α m,n =1 means that channel n is allocated to hybrid relay m and its responsible IoT terminal, α m,n =0 means that channel n is not allocated to hybrid relay m and the IoT terminal it is responsible for; g m,n,k 、h m,n,k and γ m,n They respectively represent the channel gain on channel n from the m-th hybrid relay to the k-th terminal it is responsible for, the channel gain on channel n between the k-th terminal and the hybrid relay m to which it belongs, and the channel gain on channel n between the m-th hybrid relay and the base station; P m and E m They represent the peak transmit power limit on each channel and the total consumed energy limit of the hybrid relay m respectively; Constraints C1 and C2 respectively indicate that each hybrid relay is assigned only one channel and each channel is assigned only one hybrid relay; Constraint C3 indicates that α m,n The value of can only be 0 or 1; Constraint C4 indicates that the sum of the lengths of the three transmission time slots does not exceed the normalized 1; The three transmission time slots are: the relay transmission wireless energy time slot, the terminal to the relay transmission data, the relay to the base station transmission data; Constraint C5 indicates that the three transmission time slots are all non-negative; constraint C6 indicates that the energy consumed by the IoT terminal to transmit data to the hybrid relay in the second transmission time slot should not be greater than the wireless energy collected by the terminal in the first stage; constraint C7 indicates the total energy consumption constraint of the hybrid relay; constraint C8 indicates that the transmission power of the hybrid relay and the terminal is non-negative.

2. The cooperative resource allocation method according to claim 1, characterized in that: The established optimization problem is transformed into a two-layer optimization problem with inner and outer nesting, including: Step 2-1: Let constraint C6 be true, and from constraint C1 we can get Let p m,n Its maximum value P m , that is, p m,n =P m ; Step 2-2: Rewrite constraint C7 as follows: Constraint C9: Step 2-3: Order and They represent the maximum total amount of data transmitted from the IoT terminal to the hybrid relay m and the maximum amount of data transmitted from the hybrid relay m to the base station when the channel n is allocated to the hybrid relay m. Problem P1 is reconstructed into two-layer problems nested inside and outside, where the outer optimization problem optimizes α to solve the channel allocation problem, which is modeled as: P2： Constraints C1, C2, and C3 in The objective function value obtained for the following inner optimization problem P3, where: is the total amount of data transmitted between the terminal and the hybrid relay m on channel n, is the total amount of data transmitted between hybrid relay m and the base station on channel n, and the smaller one of the two represents the maximum amount of data transmitted to the base station by all terminals that hybrid relay m is responsible for on channel n; The inner optimization problem aims to optimize the maximum amount of data transmitted by each hybrid relay on each channel and is modeled as: P3： Constraint C9: τ 1,m P m +τ 3,m q m,n ≤E m Constraint C10: 0 ≤ q m,n ≤P m Constraint C4, Constraint C5.

3. The cooperative resource allocation method according to claim 1, characterized in that: For all combinations of hybrid relays and channel allocations, solve the inner optimization problem to obtain the corresponding time slot allocation τ 1,m,n , τ 2,m,n , τ 3,m,n and the transmission power q of the hybrid relay to transmit data to the base station m,n ,include: Step 3-1: In order to solve the inner optimization problem P3, introduce the auxiliary variable η and rewrite the problem P3 as P4: P4： Constraint C11: R 1,m,n ≥η Constraint C12: R 2,m,n ≥η Constraints C4, C5, C9, and C10 remain unchanged; Step 3-2: To solve problem P4, use the binary search method to search for the optimal solution for η. Given the initial search interval [η min ,η max ]; Step 3-3: Order Step 3-4: Let u m,n =τ 3,m q m,n , and test the feasibility of problem P4 by modeling the following problem P5: P5： Constraint C13: 0 ≤ u m,n ≤τ 3,m P m Constraint C14: Constraint C15: and constraints C4 and C5 Let constraints C14 and C15 hold true, that is, the total amount of data transmitted between the terminal and the hybrid relay m on channel n is equal to the total amount of data transmitted between the hybrid relay m and the base station on channel n, simplifying problem P5 to problem P6: P6： Constraint C16: Constraint C17: Solve problem P6 using the Lagrange multiplier method; Step 3-5: From the constraints C14 and C15 of the equation, we get When τ 1,m P m +u m,n ≤E m When η min =η; otherwise, let η max =η; Step 3-6: If η has not converged, repeat steps 3-3 to 3-5; otherwise, proceed to the next step; Step 3-7: Order R m,n =η; let τ 1,m,n , τ 2,m,n , τ 3,m,n They represent the optimized time slot τ when hybrid relay m is assigned channel n. 1,m , τ 2,m , τ 3,m The value of τ 1,m,n =τ 1,m , τ 2,m,n =τ 2,m , τ 3,m,n =τ 3,m .

4. The cooperative resource allocation method according to claim 3, characterized in that: The method for solving problem P6 using the Lagrange multiplier method includes: introducing a Lagrange factor λ, and repeatedly executing steps 3-4-1 to 3-4-4 until λ converges; Step 3-4-1: Given the initial search interval of λ [λ min ,λ max ]; Step 3-4-2: Order Step 3-4-3: By finding the Langrange function For τ 2,m and τ 3,m The partial derivative of , and set it to zero, we get τ 2,m and τ 3,m The expression is as follows: Step 3-4-4: When τ 2,m and τ 3,m When constraint C16 is satisfied, let λ max =λ; otherwise, let λ min =λ.

5. The cooperative resource allocation method according to claim 1, characterized in that: Based on the solution of the inner optimization problem, the Hungarian algorithm is used to solve the outer optimization problem to obtain the channel allocation results, including: Use the Hungarian algorithm to solve problem P2 and obtain the value of the channel allocation result α. If α m,n =1, then channel n is allocated to hybrid relay m, if α m,n =0, it is not allocated to relay m.

6. The cooperative resource allocation method according to claim 1, characterized in that: The time and power allocation results are obtained based on the channel allocation results, including: Step 5-1: Let n * represents the channel allocated to each hybrid relay m, that is, For each hybrid relay m, let Step 5-2: For each hybrid relay m and channel n, if α m,n =1, then let p m,n =P m ; otherwise, let p m,n =0,q m,n =0; Step 5-3: For each hybrid relay m and its responsible terminal k, and channel n, if α m,n =1, from the equality constraints C6 and C1, we can get Otherwise, let b m,n,k =0.

7. A cooperative resource allocation device in a hybrid NOMA-FDMA Internet of Things system for executing the method as claimed in claim 1, characterized in that: Based on the Internet of Things system; The IoT system includes multiple IoT terminals, multiple hybrid relays and a base station; multiple hybrid relays are connected to the base station, and each hybrid relay serves a group of IoT terminals; all terminals served by each hybrid relay transmit their own data to the hybrid relay based on the NOMA multiple access mode, and then the hybrid relay communicates with the base station through FDMA; The cooperative resource allocation device maximizes the amount of data transmitted by all IoT device terminals by optimizing time slots and power channel allocation, specifically including: Modeling module: used to establish the optimization problem model of cooperative resource allocation in hybrid NOMA-FDMA IoT system; Problem conversion module: used to convert the established optimization problem into a two-layer optimization problem with inner and outer nesting, where the outer optimization problem is used to optimize channel allocation, and the inner optimization problem is used to optimize time and power allocation; Inner layer solving module: used to solve the inner layer optimization problem for all combinations of hybrid relays and channel allocations; Outer layer solution module: used to solve the outer layer optimization problem based on the inner layer optimization problem solution result, and obtain the channel allocation result by solving the outer layer optimization problem through the Hungarian algorithm; Output module: used to obtain time and power allocation according to channel allocation results.

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