A method for spectrum resource allocation

Abstract

The present invention discloses a spectrum resource allocation method, including: deploying multiple pairs of information transceivers, a passive backscatter tag group and an eavesdropping user in a backscatter communication system, where the information transceivers can simultaneously transmit radio frequency carriers and receive reflected signals, and each passive backscatter tag is equipped with an energy harvesting and conversion module and an information reflection module; constructing a resource allocation model that maximizes the sum rate of reflected signals for secure communication; constructing a directed hypergraph based on the backscatter system and coloring it; to solve the non-convexity problem of the resource optimization model, introducing auxiliary variables to reshape the resource allocation model and reducing the eavesdropping threat from a physical level. The method of the present invention can maximize the sum rate of reflected signals in the system on the premise of ensuring secure communication for each sub-channel, effectively reduce the interference between reflected signals by dividing spectrum resources and introducing artificial noise, and contain the impact of the eavesdropping user on the system security, meeting the requirements of users for service quality.

Description

Technical Field

[0001] The present invention relates to a method for allocating spectrum resources, belonging to the technical field of wireless communication. Background Art

[0002] As a product of the deep integration of new-generation information technology and manufacturing industry, the Industrial Internet of Things (IIoT) constructs an intelligent network system covering the entire chain of manufacturing, control, supervision, etc. by efficiently interconnecting key components such as industrial devices and sensors, which has inestimable value for improving the performance of future mobile communication systems and factory productivity. However, with the accelerating iteration of IoT technology, the application demand for ultra-dense device IoT has surged, which poses higher requirements for the flexible deployment of sensor nodes and the optimal allocation of limited communication resources.

[0003] In this context, the backscatter communication system has increasingly become the focus of research due to its unique advantages of low deployment cost and the use of passive reflection tags. In a reflection communication network, numerous information transceivers and reflection tags share limited sub-channel resources, which leads to complex interference phenomena among reflection signals and significantly affects the overall sum rate performance of the system. Although the current academic community has begun to explore optimizing frequency reuse strategies through graph theory tools to reduce interference, unfortunately, existing research often ignores the cumulative interference effect of multiple signals on a single reflection signal in dense scenarios, and the potential threat posed by this phenomenon to communication quality cannot be ignored.

[0004] In addition, the inherent broadcast characteristic of backscatter communication brings severe security challenges while enjoying the improvement of transmission efficiency, especially being vulnerable to eavesdropping attacks, resulting in a sharp increase in the risks of data leakage and privacy leakage. Although various security solutions based on lightweight cryptography have been proposed currently, due to the complexity of key generation and management, the effectiveness and feasibility of these solutions encounter bottlenecks in large-scale tag deployment scenarios. Therefore, exploring physical layer security mechanisms, such as introducing artificial noise and other strategies, has become a new way to ensure the security of communication information. However, there is a trade-off problem between pursuing system sum rate improvement and ensuring communication security. How to find the best balance between resource allocation and security protection, which can not only meet the needs of efficient data transmission but also ensure the confidentiality and integrity of information transmission, is the key challenge faced by current research. Summary of the Invention

[0005] The technical problem to be solved by the present invention is: to provide a method for allocating spectrum resources, which maximizes the sum rate of reflection signals in the system on the premise of ensuring secure communication on each sub-channel, effectively reduces the interference among reflection signals by dividing spectrum resources and introducing artificial noise, and curbs the impact of eavesdropping users on system security.

[0006] The present invention adopts the following technical solutions to solve the above technical problems:

[0007] A spectrum resource allocation method is applied to a backscatter system including eavesdropping users. The backscatter system includes an information transceiver, a passive reflection tag, and an eavesdropping user; there are available sub-channels in the backscatter system network; the method includes:

[0008] Step 1, according to the backscatter system, construct a resource allocation model that maximizes the sum rate of the reflected signal based on the channel security capability;

[0009] Step 2, construct a directed hypergraph based on the backscatter system, color the constructed directed hypergraph, and then allocate the reflected signals of each passive reflection tag to the corresponding available sub-channels;

[0010] Step 3, introduce a first auxiliary variable to reshape the security capability constraint of each available sub-channel and the objective function of the resource allocation model, use quadratic transformation to solve the non-convex problem, and optimize the artificial noise ratio coefficient introduced by each passive reflection tag when reflecting signals;

[0011] Step 4, introduce a second auxiliary variable to reshape the objective function of the resource allocation model, use quadratic transformation to solve the non-convex problem, and optimize the reflection coefficient of each passive reflection tag;

[0012] Step 5, use the cross-iteration method to repeat Steps 2 - 4 until the available sub-channel allocation results obtained in Step 2, the artificial noise ratio coefficients of each passive reflection tag obtained in Step 3, and the reflection coefficients of each passive reflection tag obtained in Step 4 remain unchanged in two adjacent iterations, then the iteration converges, and use the available sub-channel allocation results, the artificial noise ratio coefficients of each passive reflection tag, and the reflection coefficients obtained in the last iteration to achieve spectrum resource allocation that maximizes the sum rate of the reflected signal on the premise of ensuring the security capability of each available sub-channel.

[0013] Compared with the prior art, the present invention adopts the above technical solutions and has the following technical effects:

[0014] 1. The present invention considers the system communication security and resource allocation problems in the presence of eavesdroppers. Taking the system security capability and rate as indicators, it solves the non-convex optimization problem by using quadratic transformation and performs spectrum resource allocation by using the directed hypergraph coloring algorithm, so as to maximize the system sum rate on the premise of meeting the minimum security capability index.

[0015] 2. The present invention uses hypergraph theory for modeling. This method can more effectively capture and manage the mutual interference in the network, and then significantly improve the user communication quality and enhance the network data throughput through a refined frequency reuse strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is the overall layout diagram of a backscatter communication system containing eavesdropping users;

[0017] Figure 2 It is an example diagram of various interference patterns that may exist in undirected hyperedges;

[0018] Figure 3 It is a comparison diagram of the security capabilities of the communication system before and after optimization;

[0019] Figure 4 It is a relationship diagram between the sum rate of the communication system and the number of available subchannels;

[0020] Figure 5 It is a relationship diagram between the sum rate of the communication system and the signal-to-noise ratio (SNR);

[0021] Figure 6 It is a relationship diagram between the sum rate of the communication system and the number of information transceiver - reflection tags. Specific implementation manners

[0022] The following details the implementation manners of the present invention, and examples of the implementation manners are shown in the accompanying drawings. The implementation manners described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as a limitation of the present invention.

[0023] The present invention provides a resource allocation method for a backscatter communication system containing eavesdropping users. The backscatter communication system containing eavesdropping users includes an information transceiver ( ) and a passive reflection tag ( ), and an eavesdropping user, as shown in Figure 1 . Each information transceiver contains two antennas, which are respectively used for transmitting radio frequency carrier signals and receiving the reflection signals of the tags. Each passive reflection tag includes three parts: an energy harvesting module, an information acquisition module, and a reflection module. Among them, the energy harvesting module can convert the received radio frequency carrier part into DC energy for activating the information acquisition module. The information acquisition module is used for collecting the information of the tag itself. The reflection module can directly reflect the received other part of the radio frequency carrier for transmitting its own information. The eavesdropping user does not emit active interference but passively eavesdrops on the broadcast reflection signals.

[0024] The specific steps are as follows:

[0025] Step 1: Construct a resource allocation mathematical model that maximizes the sum rate of the reflection signal based on the channel security capability;

[0026] Assume that there are There are available sub-channels, each of which is flat and static. Therefore, only the path loss of the signal is considered. The reflected signal received from can be expressed as , where is the channel gain, is the transmitted reflected signal, is Gaussian white noise. However, in a backscatter network with limited spectrum resources, multiple pairs of information transceivers and reflection tags share the same channel. Therefore, at , there will be interference from the reflected signals of other tags. The signal-to-interference-plus-noise ratio (SINR) of the th information transceiver receiving the reflected signal can be written as:

[0027] ,

[0028] where represents the reflection coefficient of the th reflection tag, represents the proportion coefficient of the artificial noise injected by the th reflection tag when backscattering the signal, represents the transmission power of the radio frequency carrier sent by the th information transceiver, represents the channel gain from the th information transceiver to the th reflection tag, represents the channel gain from the th reflection tag to the th information transceiver, then represents the channel gain between the th reflection tag and the th information transceiver, is the cancellation factor based on the prior knowledge of the artificial noise, is the power of Gaussian white noise in the channel.

[0029] In addition, it is assumed that the eavesdropper eavesdrops on all the reflected signals in the channel . Therefore, the secrecy capacity of the th sub-channel is expressed as:

[0030] ,

[0031] where , , is the signal-to-interference-plus-noise ratio (SINR) of the eavesdropping user receiving the reflected signal, is the The channel gain between the reflective tag and the eavesdropping user.

[0032] In summary, the mathematical model configuration of resource allocation based on the reflection signal and rate maximization of channel security capability is:

[0033] ,

[0034] in, is the total number of transceiver and passive reflective tag pairs in the system, For the The energy conversion power of the received RF carrier signal by a reflective tag is For the The minimum activation power required for a reflective tag, is the minimum confidentiality capability standard that needs to be met; constraint C1 represents the guarantee that each reflective tag can be successfully activated, constraint C2 represents the QoS guarantee that the reflected signal transmitted in each subchannel meets the security link; constraints C3 and C4 are non-negative restrictions on the reflection coefficient and artificial noise proportional factor respectively.

[0035] Step 2: construct a directed hypergraph based on the backscatter communication system;

[0036] Resource allocation using the directed hypergraph coloring algorithm can be divided into two stages: 1) constructing a directed hypergraph model based on the interference relationship between reflected signals; 2) coloring the constructed directed hypergraph to allocate the system's spectrum resources;

[0037] When constructing a directed hypergraph model, the reflected signals are regarded as nodes of the hypergraph, and then directed hyperedges are constructed based on the independent interference and cumulative interference between the reflected signals. The directed hypergraph model effectively distinguishes the relationship between interference and interference between reflected signals by introducing directed hyperedges, which can avoid the waste of resources caused by repeated retrieval. When constructing directed hyperedges, independent interference is first determined. When the reflected signal satisfies Time Build ;in, Indicates The transmission power of the radio frequency carrier sent by each information transceiver, Indicates The information transceiver and the The channel gain between reflective tags, It means the The reflective label and The channel gain between the information transceivers is is the Gaussian white noise power in the channel. Then judge the cumulative interference. When the reflected signal meets Time Build ; In judging by When a reflected signal is in the situation of an accumulated interference node, all nodes that have formed independent interference with the th reflected signal will be preferentially excluded.

[0038] As Figure 2 shown, in the traditional undirected hypergraph model, it is impossible to accurately distinguish the interference and being interfered relationships among the 4 nodes (①, ②, ③, and ④) in the hyperedge. For example, there may be a situation where the signals of nodes ①, ②, and ③ accumulate interference on the signal of node ④, or the signals of nodes ①, ②, and ④ accumulate interference on the signal of node ③, etc. The traditional undirected hypergraph interference model cannot accurately distinguish the interfered node and the interfering node, and there are multiple combinations possible. Therefore, the present invention introduces a directed hypergraph model. In the directed hypergraph model, the nodes in the directed hyperedge are divided into an interference set and an interfered set, as shown, where belongs to the interfered set, while belongs to the interference set, and the direction is defined as .

[0039] When coloring the constructed directed hypergraph, an improved coloring algorithm is used to solve the problem that the number of colors is not limited in traditional greedy coloring, and it can be better applied to a communication system with limited spectrum resources. The specific improved rules are: a. Each node corresponds to one color; b. A total of colors can be used, where is the number of available sub-channels; c. The nodes within the same hyperedge should be colored with different colors. When coloring, first color the vertex with the highest "degree", and then "delete" the colored node. Subsequently, other nodes are colored according to the interference relationship. Among them, the "degree" of a certain node refers to the number of reflected signals affected by the node as an interference signal; "deleting" a certain node means deleting all hyperedges containing the node from the hyperedge set, deleting the node from the node set, and updating the sub-hypergraph of the remaining nodes and hyperedges.

[0040] Step 3. Since each sub-channel is independent of each other and the introduced artificial noise does not interfere with the signals in other channels, the security capability problem of the system can be split into independent sub-problems, and artificial noise is introduced into independent sub-channels respectively to ensure the security capability of the system, and the quadratic transformation is used to solve the non-convex problem, that is, the proportional coefficient of the artificial noise introduced for the reflection label setting;

[0041] In the resource allocation mathematical model for maximizing the sum rate of reflected signals based on the channel security capability, since the numerator and denominator are linear polynomials, the objective function is a non-convex problem with respect to the variable . For this reason, an auxiliary variable Reshape the security capability constraint and the objective function expression. The changed expression can be written as:

[0042] ,

[0043] where, , .

[0044] Step 4: Similarly, since each sub-channel is independent of each other, when optimizing the reflection coefficient, it can be split into independent sub-problems, and the reflection tags in independent sub-channels are discussed separately. The quadratic transformation is used to solve the non-convex problem, and the reflection coefficient of each reflection tag is optimized;

[0045] Similarly, in the resource allocation mathematical model for maximizing the sum rate of the reflected signal based on the channel security capability, the objective function is also a non-convex problem with respect to the variable . By introducing the auxiliary variable , the objective function expression is reshaped and can be rewritten as:

[0046] ,

[0047] where, , .

[0048] Step 5: In a cross-iterative manner, repeat Step 2 to Step 4 until the channel allocation results in Step 2, the artificial noise ratio coefficient results of each reflection tag in Step 3, and the reflection coefficient results of each reflection tag in Step 4 remain unchanged in two adjacent iterations, then the optimization result converges. At this time, the backscatter communication system achieves the maximization of the sum rate of the reflected signal while ensuring the security capability of each sub-channel.

[0049] As Figure 3 shows, by introducing artificial noise, the security capability of each sub-channel in the communication system can reach the minimum security standard, effectively curbing the threat to the system security from eavesdropping users and meeting the user's requirements for service quality.

[0050] As Figure 4 , 5 and 6 show, simulations are respectively carried out on the relationship between the system sum rate and the number of available sub-channels, SNR, and the number of information transceiver-reflection tags. The results show that compared with the graph coloring algorithm, the directed hypergraph coloring algorithm has a significant improvement. Especially in the case of denser device deployment, higher SNR, and limited spectrum resources, the directed hypergraph coloring algorithm can bring a sum rate increase of nearly .

[0051] Based on the same inventive concept, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the foregoing spectrum resource allocation method are implemented.

[0052] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the foregoing spectrum resource allocation method are implemented.

[0053] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0054] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0055] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means realizes the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide means for realizing the functions specified in one Figure 1 one flow or multiple flows and / or blocksFigure 1 Steps of functions specified in one or more boxes.

[0057] The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention cannot be limited thereby. Any modification made on the basis of the technical solution according to the technical idea proposed by the present invention falls within the protection scope of the present invention.

Claims

1. A spectrum resource allocation method, applied to a backscatter system with a wiretapping user, the backscatter system including an information transceiver and a passive reflection tag, and a wiretapping user; there are available sub-channels in the backscatter system network; characterized in that The method includes the following steps: Step 1: According to the backscatter system, construct a resource allocation model that maximizes the sum rate of reflected signals based on channel security capabilities. Step 2: Construct a directed hypergraph based on the backscatter system, color the constructed directed hypergraph, and then allocate the reflected signals of each passive reflection tag to the corresponding available subchannels. Step 3: Introduce a first auxiliary variable to reshape the security capability constraints of each available subchannel and the objective function of the resource allocation model, use quadratic transformation to solve the non-convex problem, and optimize the artificial noise ratio coefficient introduced by each passive reflection tag when reflecting signals. Step 4: Introduce a second auxiliary variable to reshape the objective function of the resource allocation model, use quadratic transformation to solve the non-convex problem, and optimize the reflection coefficient of each passive reflection tag. Step 5: Use the cross-iteration method to repeat Steps 2 - 4 until the available subchannel allocation results obtained in Step 2, the artificial noise ratio coefficients of each passive reflection tag obtained in Step 3, and the reflection coefficients of each passive reflection tag obtained in Step 4 remain unchanged in two adjacent iterations, then the iteration converges. Use the available subchannel allocation results, the artificial noise ratio coefficients of each passive reflection tag, and the reflection coefficients obtained in the last iteration to achieve spectrum resource allocation that maximizes the sum rate of reflected signals while ensuring the security capabilities of each available subchannel.

2. The spectrum resource allocation method according to claim 1, wherein In the backscatter system, each information transceiver includes two antennas respectively used for transmitting radio frequency carrier signals and receiving the reflected signals of the passive reflection tag corresponding to the information transceiver; each passive reflection tag includes an energy harvesting module, an information acquisition module, and a reflection module. Among them, the energy harvesting module is used to convert a part of the received radio frequency carrier signal into DC energy and activate the information acquisition module using the DC energy; the information acquisition module is used to collect the information of the passive reflection tag itself; the reflection module is used to transmit the information of the passive reflection tag itself by reflecting the other part of the received radio frequency carrier signal to the information transceiver.

3. The spectrum resource allocation method according to claim 1, wherein The resource allocation model that maximizes the sum rate of reflected signals based on channel security capabilities is specifically as follows: The information transceiver receives the reflected signal from the passive reflection tag and is interfered by the reflected signals from other passive reflection tags. The signal-to-interference-plus-noise ratio (SINR) for receiving the reflected signal is expressed as: ， Among them, respectively represent the th reflection coefficient of the passive reflection tag, represents the th artificial noise proportion coefficient injected by the passive reflection tag when backhauling the signal, respectively represent the th transmission power of the radio frequency carrier signal sent by the information transceiver, represents the th channel gain from the th information transceiver to the th passive reflection tag, represents the th channel gain from the th passive reflection tag to the th information transceiver, represents the th channel gain from the th passive reflection tag to the th information transceiver, is the cancellation factor according to the prior knowledge of the artificial noise, is the Gaussian white noise power in the channel; Set the eavesdropping user to eavesdrop on all the reflected signals in the th sub-channel , then the secrecy capacity of the th sub-channel is expressed as: ， Among them, , , denotes the th passive reflection tag whose reflected signal is allocated to the th sub-channel, is the signal-to-interference-plus-noise ratio for the eavesdropping user to receive the reflected signal, , is the channel gain between the th passive reflection tag and the eavesdropping user; The resource allocation model that maximizes the sum rate of reflected signals based on channel security capabilities is as follows: ， Among them, is the rate of the reflected signal in the backscatter system, is the rate of the reflected signal of the th passive reflection tag, is the energy conversion power of the th passive reflection tag for the received RF carrier signal, is the minimum activation power required for the th passive reflection tag; is the minimum secrecy capability standard that needs to be satisfied; Constraint C1 is the guarantee for each passive reflection tag to be successfully activated, Constraint C2 is the QoS guarantee for the reflected signal transmitted in each available sub-channel to meet the secure link, and Constraints C3 and C4 are the non-negativity restrictions on the reflection coefficient and the artificial noise ratio coefficient respectively.​​ 4. The spectrum resource allocation method according to claim 3, wherein The construction process of the directed hypergraph is as follows: Take the reflected signals of the passive reflection tags as the nodes of the directed hypergraph, and construct directed hyperedges according to the independent interference and cumulative interference between the reflected signals. When constructing a directed hyperedge, first determine the independent interference between any two nodes, that is, when the reflection signal of the th passive reflection tag satisfies , construct a directed hyperedge , where represents the reflection coefficient of the th passive reflection tag, represents the artificial noise ratio coefficient injected by the th passive reflection tag when transmitting the feedback signal, represents the transmission power of the th information transceiver for sending a radio frequency carrier signal, represents the channel gain from the th information transceiver to the th passive reflection tag, represents the channel gain from the th passive reflection tag to the th information transceiver, represents the channel gain between the th passive reflection tag and the th information transceiver, is the signal-to-interference-plus-noise ratio threshold for independent interference; Then, judge the cumulative interference between nodes, that is, when the reflection signal of the th passive reflection tag satisfies , construct a directed hyperedge , where represents the channel gain between the th passive reflection tag and the th information transceiver, and is the signal-to-interference-plus-noise ratio threshold of cumulative interference; When determining that the reflected signal of the th passive reflection tag is a node with accumulated interference, exclude all nodes that have formed independent interference with the reflected signal of the th passive reflection tag.

5. The spectrum resource allocation method according to claim 4, characterized in that The coloring of the constructed directed hypergraph is specifically as follows: Use an improved greedy coloring algorithm to color the constructed directed hypergraph, and the coloring rule is as follows: a. Each node corresponds to one color; b. The available colors are types; c. The nodes within the same directed hyperedge are colored with different colors. Each time of coloring, obtain the degrees of all nodes in the current node set, color the node with the highest degree, and after deleting the colored nodes, enter the next coloring. The degree of a node refers to the number of reflected signals affected by the node as an interference signal. Deleting the colored nodes means deleting the colored nodes from the node set and deleting all directed hyperedges containing the colored nodes from the directed hyperedge set.

6. The spectrum resource allocation method according to claim 5, wherein, The specific process of Step 3 is as follows: The objective function of the resource allocation model with respect to is a non-convex problem. By introducing auxiliary variables the security capacity constraints of each available sub-channel and the objective function of the resource allocation model are reshaped, and the expressions are as follows: ， Among them, is the sum rate of the reflected signals in the th sub-channel. ， 。 7. The spectrum resource allocation method according to claim 6, characterized in that The specific process of Step 4 is as follows: The objective function of the resource allocation model with respect to is a non-convex problem. By introducing an auxiliary variable the objective function of the resource allocation model is reshaped and the expression is as follows: ， Among them, , 。 8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the spectrum resource allocation method according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the spectrum resource allocation method according to any one of claims 1 to 7.

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