Non-orthogonal multiple access technology enhanced full duplex unmanned aerial vehicle relay method and system

Abstract

The invention discloses a non-orthogonal multiple access technology enhanced full-duplex unmanned aerial vehicle relay method and system, and the method comprises the steps: precisely calibrating the spatial positions of a base station, an unmanned aerial vehicle and a ground user in a three-dimensional rectangular coordinate system, and constructing a geometric model which accords with an actual scene; and carrying out quantitative analysis on the channel capacity between the nodes based on the Shannon theorem. On the basis, a full-duplex relay transmission mechanism of time slot division is designed, the unmanned aerial vehicle applies a self-interference elimination technology in receiving and forwarding, and the maximum reachable transmission rate of a single user is deduced from the self-interference elimination technology. Furthermore, a power distribution constraint is introduced for each user, the balance between throughput improvement and energy consumption reduction is realized by optimizing the transmitting power of the unmanned aerial vehicle, and meanwhile, the network average rate is taken as a quantitative index of overall performance evaluation. With the continuous development of the unmanned aerial vehicle communication technology, the method of the invention can significantly improve the transmission rate and the coverage quality of the macro cell on the premise of not additionally occupying spectrum resources.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of wireless communication, and particularly relates to a non-orthogonal multiple access technology enhanced full-duplex unmanned aerial vehicle relay method and system. BACKGROUND

[0002] As an aerial relay node, the unmanned aerial vehicle can be flexibly deployed to expand the coverage of the cellular network. However, the existing scheme mostly adopts half-duplex relay, and needs to complete uplink and downlink forwarding in time or frequency, which limits the spectrum utilization rate. Full-duplex communication technology can realize simultaneous sending and receiving, and theoretically can double the spectrum efficiency. In addition, the non-orthogonal multiple access technology can further improve the spectrum utilization efficiency through power domain multiplexing. The existing unmanned aerial vehicle relay scheme mostly does not combine full-duplex and non-orthogonal multiple access, resulting in a low system transmission rate. When the transmission power of the unmanned aerial vehicle is fixed, high power can improve coverage but shorten the endurance, and low power can cause a sharp decrease in the rate of edge users. SUMMARY

[0003] The technical problem to be solved by the application is to provide a non-orthogonal multiple access technology enhanced full-duplex unmanned aerial vehicle relay method and system, which combines non-orthogonal multiple access and full-duplex communication technology, significantly improves the overall transmission rate of the cellular network without increasing additional spectrum resources, and solves the technical problems that the existing unmanned aerial vehicle relay mostly adopts half-duplex mode, the spectrum utilization rate is low, and full-duplex and non-orthogonal multiple access technology are not fully combined, resulting in a limited system transmission rate.

[0004] The application adopts the following technical scheme: The non-orthogonal multiple access technology enhanced full-duplex unmanned aerial vehicle relay method comprises the following steps: S1, a three-dimensional geometric model of a cellular communication network comprising a single base station, a full-duplex relay unmanned aerial vehicle and K ground users is constructed, and the spatial positions of the nodes are accurately calibrated; S2, based on the Shannon theorem, the channel capacity of the base station-unmanned aerial vehicle, base station-user and unmanned aerial vehicle-user links is quantitatively analyzed in combination with the line-of-sight and non-line-of-sight channel models; S3, a full-duplex relay transmission mechanism of time slot division is designed: In time slot t, the base station broadcasts signals to the unmanned aerial vehicle and the target user; In time slot t+1, the unmanned aerial vehicle synchronously receives the new signals of the base station and forwards the decoded signals of time slot t through self-interference cancellation technology, and the user end preferentially decodes the unmanned aerial vehicle forwarding signals through the serial interference cancellation technology; The user end performs maximum ratio combining on the direct link signals of time slot t and the relay link signals of time slot t+1, and improves the signal-to-noise ratio; S4. Introduce power allocation constraints for each user, optimize the drone's transmit power to balance throughput and energy consumption, and calculate the single-user achievable rate and the network average rate.

[0005] Preferably, in step S1, the position of the drone for:

[0006] The distances from the base station to the drone, the drone to the user, and the base station to the user are expressed in a three-dimensional coordinate system as follows:

[0007]

[0008]

[0009] in, are the horizontal and vertical positions of the UAV in the three-dimensional coordinate system, is the total number of transmission time slots, is the distance from the base station to the drone, is the base station location, is the drone location, is the distance from the drone to the user, is the user's location, is the distance from the base station to the user.

[0010] Preferably, step S2 is specifically: The free space path loss model is used to calculate the channel power gain of the base station to drone and drone to user links; According to Shannon's theorem, for k Data transmission of each user determines the channel capacity of the base station to drone link , the channel capacity of the UAV-to-user link ; and determine the signal-to-interference-and-noise ratio from the base station to the user .

[0011] Preferably, the channel capacity of the base station to drone link and the channel capacity of the drone-to-user link They are:

[0012]

[0013] in, Assigning base stations to users k The transmission power, is the power of Gaussian white noise, Assigning drones to usersk The transmission power, is the channel attenuation factor per unit distance, is the base station location, is the drone location, is the channel gain from the base station to the user, The user's location.

[0014] Preferably, the signal to interference and noise ratio for:

[0015] in, is the transmission power from the base station to the user, is the channel gain from the base station to the user, is the ambient white noise power.

[0016] Preferably, step S3 is specifically: The data transmission process is divided into multiple small time slots. In any time slot, the drone and the base station use the same frequency to forward data. t In the base station, the data D t Encode and send to the target k users; in time slots t+1 In the process, the drone receives the data D t Decode, re-encode, and forward to the k Users, using the serial interference cancellation technique, are given priority from the received time slots t+1 signal Y t+1 Decoding the data forwarded by the drone D t ; k Users pass through time slots t The received data signal of the direct link is delayed to the time slot t+1 and uses the maximum ratio combining technique to combine the signals for decoding.

[0017] Preferably, the data D t Transmission rate for:

[0018] in, is the transmission power from the base station to the user, is the channel gain from the base station to the drone, is the transmission power from the UAV to the user, is the channel gain from the UAV to the user, the environmental white noise power, the channel gain from the base station to the user.

[0019] Preferably, step S4 is specifically: When the transmission rate is expressed as , the signal-to-noise ratio satisfies ; When the constraint is introduced, and is adjusted to ensure satisfies the condition; By introducing the constraint , the is simplified; the average transmission rate of all users in the network .

[0020] Preferably, the average transmission rate is:

[0021] wherein, the signal-to-noise ratio from the UAV to the user, the signal-to-noise ratio from the base station to the user, the total number of users, the i-th user. k

[0022] In a second aspect, the embodiments of the present application provide a non-orthogonal multiple access technology enhanced full-duplex UAV relay system, comprising: a construction module, which constructs a three-dimensional geometric model of a cellular communication network containing a single base station, a full-duplex relay UAV, and K ground users, and accurately calibrates the spatial positions of each node; a quantitative module, which quantitatively analyzes the channel capacity of the base station-UAV, base station-user, and UAV-user links based on the Shannon theorem and in combination with the line-of-sight and non-line-of-sight channel models; a mechanism module, which designs a full-duplex relay transmission mechanism with time slot division At time slot t, the base station broadcasts signals to the UAV and the target user; At time slot t+1, the UAV synchronously receives the new signals from the base station and forwards the decoded signals of time slot t by using the self-interference cancellation technology, and the user end preferentially decodes the UAV forwarding signals by using the serial interference cancellation technology; The user end performs maximum ratio combining on the direct link signals of time slot t and the relay link signals of time slot t+1, and improves the signal-to-noise ratio; an output module, which introduces a power allocation constraint for each user, optimizes the UAV transmission power to balance the throughput and energy consumption, and calculates the single-user achievable rate and the network average rate.​

[0023] In a third aspect, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the non-orthogonal multiple access technology enhanced full-duplex UAV relay method when executing the computer program.

[0024] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium including a computer program, wherein the computer program implements the steps of the non-orthogonal multiple access technology enhanced full-duplex UAV relay method when executed by a processor.

[0025] In a fifth aspect, a chip includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the non-orthogonal multiple access technology enhanced full-duplex UAV relay method when executing the computer program.

[0026] In a sixth aspect, an embodiment of the present application provides an electronic device including a computer program, wherein the computer program implements the steps of the non-orthogonal multiple access technology enhanced full-duplex UAV relay method when executed by the electronic device.

[0027] Compared with the prior art, the present application has at least the following beneficial effects: A non-orthogonal multiple access technology enhanced full-duplex UAV relay method integrates full-duplex relay and NOMA technology, and breaks through the half-duplex spectrum efficiency bottleneck. Full-duplex enables the UAV to simultaneously transmit and receive signals, and the theoretical spectrum efficiency is improved by 100%. NOMA supports multi-user parallel transmission through power domain multiplexing, further compressing resource occupation. The time slot mechanism ensures controllable signal timing, combined with self-interference cancellation to suppress self-interference at the same frequency, ensuring the feasibility of full-duplex. The user end uses serial interference cancellation to decouple the mixed signal, and then enhances the signal quality through maximum ratio combining, significantly improving the signal-to-noise ratio of the edge user. The power optimization module dynamically balances the throughput and energy consumption, prolonging the endurance of the UAV; fully utilizing the high-altitude line-of-sight link advantage of the UAV, using serial interference cancellation to separate and decode the mixed signal received by the user, and further using maximum ratio combining technology to superimpose power gain on the multipath signal, thereby significantly improving the signal-to-noise ratio and transmission rate.

[0028] Further, a three-dimensional rectangular coordinate system is constructed to accurately quantify the spatial positions of the base station, the UAV and the ground user: taking the projection point of the base station antenna on the ground as the origin, x 、 y the axis is horizontal on the ground, z the axis is vertically upward. Defining the coordinates of each node and the node connection distance provides an intuitive and implementable geometric basis for subsequent channel gain calculation.

[0029] Furthermore, based on the differences in propagation environments, channel models are established for line-of-sight and non-line-of-sight links. Combining Shannon's theorem, channel capacity expressions for the three links are given.

[0030] Furthermore, a full-duplex UAV relay transmission mechanism based on time slot division is designed to achieve time domain diversity gain between two time slots. The maximum transmission rate of a single user can be derived from the channel capacity of each link.

[0031] Furthermore, in order to balance throughput and energy consumption, power constraints are introduced for each user and the drone transmission power is optimized, the user's transmission rate is simplified, and the average network rate is given to provide a quantitative indicator for overall performance evaluation.

[0032] Furthermore, a three-dimensional geometric model converts actual deployment parameters into quantified channel gains, ensuring accurate path loss calculations. Line-of-sight links use a free-space model, while non-line-of-sight links incorporate a standard loss model to accommodate the complex macrocell environments. The channel capacity formula clearly defines the mathematical relationship between power and interference, providing theoretical constraints for power optimization and avoiding blind allocation.

[0033] Furthermore, the direct link and relay link signals complement each other in the time domain, and MRC weighted superposition can mitigate channel fading. Power constraints ensure the drone's power can be adjusted within a certain range, avoiding resource waste. The system adaptively switches to direct transmission mode to reduce energy consumption; otherwise, relay transmission is activated to enhance coverage.

[0034] It can be understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0035] In summary, the present invention provides higher link quality and throughput guarantees for cell users through precise three-dimensional geometric modeling, differentiated channel capacity analysis, time domain diversity non-orthogonal multiple access enhanced relay mechanism and adaptive power optimization.

[0036] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Flowchart of the present invention; Figure 2 A scene graph provided by the present invention; Figure 3Performance comparison chart of the method provided by the present invention (DF NOMA Scheme) with the full-duplex UAV relay method using orthogonal multiple access technology (DF OMA Scheme), the half-duplex UAV relay method using non-orthogonal multiple access technology (HF NOMA Scheme), and the half-duplex UAV relay method using orthogonal multiple access technology (HF OMA Scheme) under different user number conditions; Figure 4 This is a performance comparison chart of the method provided by the present invention, DF NOMA Scheme, DF OMA Scheme, HF NOMA Scheme, and HFOMA Scheme under different maximum transmission power conditions; Figure 5 A schematic diagram of a computer device provided in accordance with an embodiment of the present invention; Figure 6 The block diagram of a chip provided according to one embodiment of the present invention is shown.

[0038] Among them, 60. Computer device; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / Utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0040] In the description of the present invention, it is to be understood that the terms “include” and “comprise” indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0041] It should also be understood that the terms used in the present specification are only for the purpose of describing particular embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0042] It should be further understood that the term "and / or" as used in the specification and in the claims, if any, means any of the conjunctive or disjunctive sense and / or all possible combinations of the conjunctive or disjunctive sense, i.e., A and / or B can mean A alone, A and B together, B alone, or any combination of A and B.

[0043] It should be understood that, although the terms first, second, third, etc. can be used herein to describe various ranges, etc., these ranges should not be limited to these terms. These terms are only used to distinguish one range from another. For example, a first range could be termed a second range without departing from the scope of the embodiments.

[0044] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if [a stated condition or event] is detected" can be interpreted to mean "upon determining" or "in response to determining" or "upon detecting [the stated condition or event]" or "in response to detecting [the stated condition or event]."

[0045] Various structural diagrams according to the disclosed embodiments of the present application are shown in the accompanying drawings. These diagrams are not drawn to scale, in which certain details are shown in a somewhat exaggerated manner for the purpose of clarity and understanding, and certain details can be omitted. The shapes of various regions, layers, and the relative size and positional relationship between them shown in the drawings are only exemplary, and in actuality, they can be deviated due to manufacturing tolerances or technical limitations, and a person skilled in the art can additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0046] The present application provides a non-orthogonal multiple access technology enhanced full-duplex unmanned aerial vehicle relay method, which synchronously receives and forwards base station signals under the same frequency resource by combining non-orthogonal multiple access and full-duplex communication technology, so as to realize relay enhanced transmission; the user end separates and decodes the mixed signal through serial interference cancellation technology, and then uses maximum ratio combining technology to weight and superimpose the multiple received signals, so as to significantly improve the signal-to-noise ratio and effectively improve the average transmission rate of the cell users; through the three-dimensional cooperation of full-duplex relay+NOMA+power optimization, the problem of low spectrum efficiency and insufficient transmission rate in the unmanned aerial vehicle relay scene is solved without increasing the spectrum resource.

[0047] Please refer to Figure 1The present invention provides a full-duplex UAV relay method enhanced by non-orthogonal multiple access technology, comprising the following steps: S1, build a system including a single base station, a full-duplex relay drone and K Cellular communication network model for users in each cell; See also Figure 2 , including 1 base station, 1 full-duplex drone and K The cellular communication network scenario model of users in each cell is constructed as follows: S101. Construct a three-dimensional rectangular coordinate system with the projection point of the base station antenna relative to the ground as the origin. O . x Axis and y The axis is horizontal (ground plane), z The axis points vertically upward; S102, let the installation height of the base station antenna be H b , its position in the coordinate system is:

[0048] No. k The position of a ground user in the coordinate system is:

[0049] The drone's location is:

[0050] The distances from the base station to the drone, the drone to the user, and the base station to the user are expressed in a three-dimensional coordinate system as follows:

[0051]

[0052]

[0053] S2. Based on the cellular communication network model constructed in step S1, clarify the channel conditions and establish the channel capacities between the base station and the drone, between the base station and the user, and between the drone and the user; Establish the channel capacity between each node, specifically: S201. Since the drone hovers at high altitude, the links between it and the base station and the terminal are mainly line-of-sight transmission. Therefore, the free space path loss model is used to calculate the channel power gain of the base station-to-drone and drone-to-user links:

[0054] in, is the received power at the reference distance (usually 1m).

[0055] In contrast, in macro cell scenarios, there is usually non-line-of-sight transmission between the base station and the ground user. According to the standard path loss model, the path loss (unit: dB) is expressed as

[0056] in, f c is the carrier frequency (GHz), and the corresponding linear channel power gain is:

[0057] S202. According to Shannon's theorem, for k For data transmission of a user, the channel capacity of the base station to drone link is:

[0058] in, Indicates that the base station is assigned to the user k The transmission power, The power of Gaussian white noise, often used to describe background noise in communication systems.

[0059] Considering that the communication from the drone to the user link is interfered by the base station to the user link, its channel capacity is:

[0060] in, Indicates that the drone is assigned to the user k transmission power.

[0061] The transmission from the base station to the user is processed by the user end, so its signal-to-interference-and-noise ratio is expressed as:

[0062] S3. Based on the cellular communication network model constructed in step S1 and the channel capacity between each node constructed in step S2, further construct a data transmission mechanism for communication data between each node, and clarify the data exchange process and decoding process between each node; Establish a data transmission mechanism, specifically: S301, the data transmission process is divided into multiple small slots; In any time slot, the drone and the base station use the same frequency to forward data; In the time gap t In the base station, the data D t Encode and send it to the target kSince the base station sends the signal in the form of broadcast, the drone will also receive the signal; In the subsequent time slot t+1 In the process, the drone receives the data D t Decode, re-encode, and forward it to the k For individual users, it is important to note that while receiving signals, full-duplex drones effectively suppress interference from their own transmitted signals through self-interference cancellation technology.

[0063] Note that in the time slot t+1 In addition to the data forwarded by the drone D t In addition, the base station will also send new data D t+1 Since the UAV’s air-to-ground link has a low path loss, resulting in a significant power difference between the two signals, the serial interference cancellation technology is used to prioritize the received time slot. t+1 signal Y t+1 Decoding the data forwarded by the drone D t Therefore, the transmission rate of the UAV relay link can be expressed as

[0064] S302, due to k Users pass through time slots t Direct link and time slot t+1 The relay link receives data D t , so the former signal is delayed to the time slot t+1 The two signals are combined and decoded using the maximum ratio combining technique. This full-duplex UAV-based approach enables the system to achieve time-domain diversity gain, which is beneficial for D t Transmission rate Expressed as

[0065] S4. Based on the data transmission mechanism established in step S3, further establish the drone energy-saving mechanism, calculate the transmission rate of a single user and the average transmission rate of all users in the network, and then reflect the overall communication efficiency of the network.

[0066] Establish the average transmission rate for a single user and for all users of the network, specifically: S401. Furthermore, considering that drones are high-energy-consuming devices, it is necessary to optimize their transmission power to reduce communication power consumption.

[0067] Note that when When the transmission rate It can be directly expressed as , which is the most direct case, where the signal-to-interference-noise ratio satisfies ;when When the transmission power of the UAV Can be adjusted to 0, so constraints can be introduced and by adjusting Thus ensuring

[0068] S402. In summary, by introducing constraints in these two cases , without reducing the transmission rate, Simplified to:

[0069] The average transmission rate of all users in the network is expressed as:

[0070] In another embodiment of the present invention, a full-duplex UAV relay system enhanced by non-orthogonal multiple access technology is provided. The system can be used to implement the above-mentioned full-duplex UAV relay method enhanced by non-orthogonal multiple access technology. Specifically, the full-duplex UAV relay system enhanced by non-orthogonal multiple access technology includes a construction module, a quantitative module, a mechanism module and an output module.

[0071] Among them, the construction module constructs a three-dimensional geometric model of the cellular communication network including a single base station, a full-duplex relay drone and K ground users, and accurately calibrates the spatial position of each node; The quantitative module, based on Shannon's theorem and combining line-of-sight and non-line-of-sight channel models, quantitatively analyzes the channel capacity of base station-drone, base station-user, and drone-user links; Mechanism module, design of full-duplex relay transmission mechanism with time slot division At time slot t, the base station broadcasts the signal to the UAV and the target user; At time slot t+1, the drone synchronously receives the new signal from the base station through self-interference cancellation technology and forwards the decoded signal of time slot t. The user end uses serial interference cancellation technology to preferentially decode the signal forwarded by the drone; The user end performs maximum ratio combining on the direct link signal at time slot t and the relay link signal at time slot t+1 to improve the signal-to-noise ratio. The output module introduces power allocation constraints for each user, optimizes the UAV transmission power to balance throughput and energy consumption, and calculates the single-user achievable rate and the network average rate.

[0072] The present invention provides a terminal device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the full-duplex unmanned aerial vehicle relay method enhanced by non-orthogonal multiple access technology, including: A three-dimensional geometric model of a cellular communication network consisting of a single base station, a full-duplex relay drone, and K ground users is constructed to accurately calibrate the spatial position of each node. Based on Shannon's theorem, combined with line-of-sight and non-line-of-sight channel models, the channel capacity of the base station-drone, base station-user, and drone-user links is quantitatively analyzed. A full-duplex relay transmission mechanism with time slot division is designed: in time slot t, the base station broadcasts the signal to the drone and the target user. In time slot t+1, the drone synchronously receives the new signal from the base station through self-interference cancellation technology and forwards the decoded signal of time slot t. The user end uses serial interference cancellation technology to preferentially decode the drone forwarded signal. The user end performs maximum ratio combining on the direct link signal of time slot t and the relay link signal of time slot t+1 to improve the signal-to-noise ratio. A power allocation constraint is introduced for each user, and the drone's transmit power is optimized to balance throughput and energy consumption. The single-user achievable rate and the network average rate are calculated.

[0073] See also Figure 5The terminal device is a computer device. Computer device 60 in this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in memory 62 and executable by processor 61. When executed by processor 61, computer program 63 implements the method for estimating the concentration of radioactive iodine species in a post-accident containment vessel described in this embodiment. To avoid repetition, this description is omitted here. Alternatively, when executed by processor 61, computer program 63 implements the functions of various models / units in the full-duplex UAV relay system enhanced by non-orthogonal multiple access technology in this embodiment. To avoid repetition, this description is omitted here.

[0074] The computer device 60 may be a desktop computer, a notebook computer, a PDA, a cloud server, or other computing devices. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. It will be understood by those skilled in the art that Figure 5 This is merely an example of the computer device 60 and does not constitute a limitation of the computer device 60 . The computer device 60 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0075] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, a graphics processing unit (GPU), a tensor processing unit (TPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0076] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 60.

[0077] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is about to be output.

[0078] See also Figure 6 The terminal device is an electronic device 600, which is implemented as a general-purpose computing device. The components of the electronic device may include, but are not limited to, at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), and a display unit 640.

[0079] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 can perform the following steps: Figure 1 Follow the steps shown in .

[0080] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0081] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0082] Bus 630 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0083] The electronic device 600 may also communicate with one or more external devices 700 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and / or any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., a router, a modem). Such communication may occur via an input / output interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network, a wide area network, and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0084] Example 4 The present invention also provides a storage medium, specifically a computer-readable storage medium. The computer-readable storage medium is a memory device in a terminal device, used to store programs and data. It is understood that the computer-readable storage medium herein may include both the built-in storage medium in the terminal device and, of course, the extended storage medium supported by the terminal device. It may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for being loaded and executed by a processor. These instructions may be one or more computer programs (including program code). It should be noted that more specific examples of the computer-readable storage medium herein include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0085] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program code. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, radio frequency, etc., or any suitable combination of the above.

[0086] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network or a wide area network, or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0087] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the non-orthogonal multiple access technology enhanced full-duplex UAV relay method in the above embodiment; the processor may load and execute the following steps: A three-dimensional geometric model of a cellular communication network consisting of a single base station, a full-duplex relay drone, and K ground users is constructed to accurately calibrate the spatial position of each node. Based on Shannon's theorem, combined with line-of-sight and non-line-of-sight channel models, the channel capacity of the base station-drone, base station-user, and drone-user links is quantitatively analyzed. A full-duplex relay transmission mechanism with time slot division is designed: in time slot t, the base station broadcasts the signal to the drone and the target user. In time slot t+1, the drone synchronously receives the new signal from the base station through self-interference cancellation technology and forwards the decoded signal of time slot t. The user end uses serial interference cancellation technology to preferentially decode the drone forwarded signal. The user end performs maximum ratio combining on the direct link signal of time slot t and the relay link signal of time slot t+1 to improve the signal-to-noise ratio. A power allocation constraint is introduced for each user, and the drone's transmit power is optimized to balance throughput and energy consumption. The single-user achievable rate and the network average rate are calculated.

[0088] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0089] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0090] This experiment simulates a full-duplex drone relay method enhanced with non-orthogonal multiple access (NOMA) and an existing mechanism based on the same network parameters to verify the superiority of the proposed method. The specific steps are as follows: the same network parameters are: base station height 35m, user height 1.5m, drone height 50m, carrier frequency 2.4GHz, noise level -100dBm, and reference channel gain -40dB. See also Figure 3 For any number of users, the full-duplex UAV relay method enhanced by non-orthogonal multiple access is superior to other schemes in terms of system transmission rate. Figure 4 , for any maximum transmission power, in terms of total throughput, the non-orthogonal multiple access enhanced full-duplex UAV relay method adopted in the present invention is superior to other schemes.

[0091] In summary, the present invention provides a full-duplex UAV relay method and system enhanced by non-orthogonal multiple access technology, which constructs a three-dimensional rectangular coordinate system to accurately quantify the spatial positions of base stations, UAVs, and ground users. The channel capacity of each link under this transmission scheme is analyzed using the Shannon formula. A full-duplex UAV relay transmission mechanism based on time slot division is designed to derive the maximum transmission rate of a single user. Power constraints are introduced for each user and the UAV transmission power is optimized to balance throughput and energy consumption. The average network rate is given to provide a quantitative indicator for overall performance evaluation. With the development of UAV communication technology, the full-duplex UAV relay method enhanced by non-orthogonal multiple access technology can effectively improve the transmission rate of the cell.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0093] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0094] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0095] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, and can be electrical, mechanical, or other forms.

[0096] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0097] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0098] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above-mentioned various method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0099] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks 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 produce 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.

[0100] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0102] The above content is only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A full-duplex UAV relay method enhanced by non-orthogonal multiple access technology, characterized in that: The following steps are involved: S1. Construct a 3D geometric model of a cellular communication network consisting of a single base station, a full-duplex relay drone, and K ground users, and accurately calibrate the spatial position of each node. S2. Based on Shannon's theorem, combined with line-of-sight and non-line-of-sight channel models, quantitatively analyze the channel capacity of base station-UAV, base station-user, and UAV-user links; S3. Design a full-duplex relay transmission mechanism with time slot division: At time slot t, the base station broadcasts the signal to the UAV and the target user; At time slot t+1, the drone synchronously receives the new signal from the base station through self-interference cancellation technology and forwards the decoded signal of time slot t. The user end uses serial interference cancellation technology to preferentially decode the signal forwarded by the drone; The user end performs maximum ratio combining on the direct link signal at time slot t and the relay link signal at time slot t+1 to improve the signal-to-noise ratio. S4. Introduce power allocation constraints for each user, optimize the drone's transmit power to balance throughput and energy consumption, and calculate the single-user achievable rate and the network average rate.

2. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 1 is characterized in that: In step S1, the position of the drone for: The distances from the base station to the drone, the drone to the user, and the base station to the user are expressed in a three-dimensional coordinate system as follows: in, are the horizontal and vertical positions of the UAV in the three-dimensional coordinate system, is the total number of transmission time slots, is the distance from the base station to the drone, is the base station location, is the drone location, is the distance from the drone to the user, is the user's location, is the distance from the base station to the user.

3. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 1 is characterized in that: Step S2 is specifically as follows: The free space path loss model is used to calculate the channel power gain of the base station to drone and drone to user links; According to Shannon's theorem, for k Data transmission of each user determines the channel capacity of the base station to drone link , the channel capacity of the UAV-to-user link ; And determine the signal-to-interference-and-noise ratio from the base station to the user .

4. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 3 is characterized in that: Channel capacity of the base station to drone link and the channel capacity of the drone-to-user link They are: in, Assigning base stations to users k The transmission power, is the power of Gaussian white noise, Assigning drones to users k The transmission power, is the channel attenuation factor per unit distance, is the base station location, is the drone location, is the channel gain from the base station to the user, The user's location.

5. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 3 is characterized in that: Signal-to-noise ratio for: in, is the transmission power from the base station to the user, is the channel gain from the base station to the user, is the ambient white noise power.

6. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 1, characterized in that: Step S3 is specifically as follows: The data transmission process is divided into multiple small time slots. In any time slot, the drone and the base station use the same frequency to forward data. t In the base station, the data D t Encode and send to the target k users; in time slots t+ 1 In the process, the drone receives the data D t Decode, re-encode, and forward to the k Users, using the serial interference cancellation technique, are given priority from the received time slots t+1 signal Y t+1 Decoding the data forwarded by the drone D t ; k Users pass through time slots t The received data signal of the direct link is delayed to the time slot t+1 and uses the maximum ratio combining technique to combine the signals for decoding.

7. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 6, characterized in that: data D t Transmission rate for: in, is the transmission power from the base station to the user, is the channel gain from the base station to the drone, is the transmission power from the UAV to the user, is the channel gain from the drone to the user, is the ambient white noise power, is the channel gain from the base station to the user.

8. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 1, characterized in that: Step S4 is specifically as follows: when When the transmission rate Expressed as , the signal-to-interference-noise ratio satisfies ; when When the constraint and by adjusting make sure meet the conditions; By introducing constraints ,Will simplify; Get the average transmission rate of all users on the network .

9. The full-duplex UAV relay method enhanced by non-orthogonal multiple access technology according to claim 8, characterized in that: Average transmission rate for: in, is the signal-to-noise ratio from the drone to the user, is the signal-to-noise ratio from the base station to the user, is the total number of users, Specifically refers to k users.

10. A full-duplex UAV relay system enhanced by non-orthogonal multiple access technology, characterized in that: include: The construction module constructs a 3D geometric model of the cellular communication network consisting of a single base station, a full-duplex relay drone, and K ground users, and accurately calibrates the spatial position of each node; The quantitative module, based on Shannon's theorem and combining line-of-sight and non-line-of-sight channel models, quantitatively analyzes the channel capacity of base station-drone, base station-user, and drone-user links; Mechanism module, designing a full-duplex relay transmission mechanism with time slot division: At time slot t, the base station broadcasts the signal to the UAV and the target user; At time slot t+1, the drone synchronously receives the new signal from the base station through self-interference cancellation technology and forwards the decoded signal of time slot t. The user end uses serial interference cancellation technology to preferentially decode the signal forwarded by the drone; The user end performs maximum ratio combining on the direct link signal at time slot t and the relay link signal at time slot t+1 to improve the signal-to-noise ratio. The output module introduces power allocation constraints for each user, optimizes the UAV transmission power to balance throughput and energy consumption, and calculates the single-user achievable rate and the network average rate.

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