Symbiotic radio resource allocation method based on bounded CSI error and related device
By optimizing the resource allocation of symbiotic radio systems using a robust resource allocation method based on bounded CSI error, the problems of high system outage probability and poor information transmission security are solved, thereby improving spectral efficiency and transmission robustness.
Patent Information
- Application Number
- CN202511697013.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-19
- Publication Date
- 2026-01-09
AI Technical Summary
Existing co-existing radio systems rely on CSI for resource allocation, resulting in high system outage probability, low throughput, and poor information transmission security, especially under CSI disturbances and eavesdropping interference.
A robust resource allocation method based on bounded CSI error is adopted, combined with Tinkelbach and semidefinite relaxation methods, to optimize the resource allocation strategy, taking into account CSI uncertainty and eavesdropping interference, thereby improving system energy efficiency and transmission robustness.
It effectively reduces the probability of system outages, improves spectrum efficiency and information transmission security, and enhances the anti-interference capability of symbiotic radio systems.
Smart Images
Figure CN121310286A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the field of wireless communication, and relates to a symbiotic radio resource allocation method based on bounded CSI error and related devices. BACKGROUND
[0002] To improve spectrum efficiency and reduce system hardware overhead, symbiotic radio as a new generation of 6G communication key technology capable of sharing the spectrum resources and information receivers of the main system has attracted much attention. However, the system performance is heavily dependent on good information state information (CSI), and the resource allocation method based on outdated CSI will increase the system interruption probability and reduce the system throughput. At the same time, due to the openness of shared electromagnetic spectrum and reflected signals, information is easily eavesdropped, thereby affecting the information transmission security. Therefore, it is of great significance to develop a resource allocation method with anti-CSI disturbance and eavesdropping interference by comprehensively considering the influence of channel perturbation and eavesdroppers. SUMMARY
[0003] The application aims to overcome the shortcomings of the prior art and provide a symbiotic radio resource allocation method based on bounded CSI error and related devices, which can allocate resources with CSI disturbance and eavesdropping interference.
[0004] To achieve the above-mentioned purpose, the application discloses a symbiotic radio resource allocation method based on bounded CSI error, which comprises the following steps: Initializing the parameters of a multi-output single-output multi-user symbiotic radio system; Considering the basic QoS of users, limited power supply, and minimum energy demand guarantee of symbiotic devices, based on a bounded CSI error model, an energy efficiency maximization resource allocation problem is established; Solving the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and using the robust resource allocation strategy to allocate symbiotic radio resources.
[0005] The symbiotic radio resource allocation method based on bounded CSI error further improves in that: Further, the energy efficiency maximization resource allocation problem is solved based on the Dingkelbach and semi-definite relaxation method to obtain a robust resource allocation strategy.
[0006] Further, the bounded CSI error model is:
[0007] wherein, and is a set of CSI uncertainties; is a channel gain from BS to Eve; represents the i-th Channel gain from SN to Eve; and These are the channel gain estimates from BS to Eve and the channel gain estimates from SN to Eve, respectively. and These are the channel estimation error parameters from BS to Eve and from SN to Eve, respectively. and These represent the upper limits of the estimation error from BS to Eve and the upper limits of the estimation error from SN to Eve, respectively.
[0008] Furthermore, the energy efficiency maximization resource allocation problem is as follows:
[0009] Where max(0,x) represents taking values of 0 and x. x The larger of the two; The rate of SIR; For the first The transmission rate of each SN; and For the corresponding user rate QoS requirements; For Eve's rate; Represents the beam vector of BS. Its maximum transmission power; For the first k SN reflectance coefficient; Energy conversion efficiency; For BS to the number k Channel gain of each SN; This indicates that SIR is decoding the first... When the SN signal is received, the first The signal-to-noise ratio of each SN signal; Indicates the SIR decoding of the first The signal-to-noise ratio of each SN signal; This is the power amplification factor; For the first The mean and variance of each number are zero. Hardware damage factors; ; This indicates that the SIR means zero and the variance is... Hardware damage factors; ; This represents the imperfect serial interference cancellation factor; For the first Hardware damage factor of each SN; and These are the hardware impairment factor and noise variance of SIR, respectively; Let be the noise variance of Eve.
[0010] The application discloses a symbiotic radio resource allocation system based on bounded CSI error, comprising: An initialization module, configured to initialize parameters of a multi-output single-output multi-user symbiotic radio system; A building module, configured to build an energy efficiency maximization resource allocation problem based on a bounded CSI error model by considering user basic QoS, limited power supply and minimum energy requirement guarantee of symbiotic equipment; An allocation module, configured to solve the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and perform symbiotic radio resource allocation by using the robust resource allocation strategy.
[0011] The application further improves the symbiotic radio resource allocation system based on bounded CSI error in that: Further, the energy efficiency maximization resource allocation problem is solved based on Dingkelbach and semi-definite relaxation method to obtain the robust resource allocation strategy.
[0012] Further, the bounded CSI error model is:
[0013] Wherein, and are a set of CSI uncertainties; is a channel gain from a BS to Eve; is a channel gain from the i-th SN to Eve; is a channel gain from the i-th SN to Eve; and are an estimated value of the channel gain from the BS to Eve and an estimated value of the channel gain from the SN to Eve respectively; and are an estimated error parameter of the channel from the BS to Eve and an estimated error parameter of the channel from the SN to Eve respectively; and represent an upper limit of the estimated error from the BS to Eve and an upper limit of the estimated error from the SN to Eve respectively.
[0014] Further, the energy efficiency maximization resource allocation problem is:
[0015] Wherein, max (0, x) represents a larger value between 0 and x; x is a rate of SIR; is a transmission rate of the i-th SN; is a transmission rate of the i-th SN; and are corresponding user rate QoS requirements; For Eve's rate; Represents the beam vector of BS. Its maximum transmission power; For the first k SN reflectance coefficient; Energy conversion efficiency; For BS to the number k Channel gain of each SN; This indicates that SIR is decoding the first... When the SN signal is received, the first The signal-to-noise ratio of each SN signal; Indicates the SIR decoding of the first The signal-to-noise ratio of each SN signal; This is the power amplification factor; For the first The mean and variance of each number are zero. Hardware damage factors; ; This indicates that the SIR means zero and the variance is... Hardware damage factors; ; This represents the imperfect serial interference cancellation factor; For the first Hardware damage factor of each SN; and These are the hardware impairment factor and noise variance of SIR, respectively; Let be the noise variance of Eve.
[0016] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the co-occurrence radio resource allocation method based on bounded CSI error.
[0017] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the co-occurring radio resource allocation method based on bounded CSI error.
[0018] The present invention has the following beneficial effects: The coexisting radio resource allocation method and related device based on bounded CSI error described in this invention, in specific operation, considers the influence of CSI error and eavesdroppers, and maximizes the energy efficiency of resource allocation. It uses the Tinkelbach and semi-Tinkelbach relaxation methods to solve the problem, and allocates resources based on the solution results, effectively improving the energy efficiency and transmission robustness of coexisting radio under the conditions of shared spectrum resources and information receivers. Attached Figure Description
[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the present application. Obviously, the drawings in the following description only some of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor under the premise of these drawings.
[0020] Figure 1 For the flow chart of the method of the present application; Figure 2 For the performance chart of the simulation experiment; Figure 3 For the system structure diagram of the present application. DETAILED DESCRIPTION
[0021] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.
[0022] In the description of the present application, it should be understood that the terms "include" and "contain" indicate the presence of described features, whole, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, whole, steps, operations, elements, components and / or their sets.
[0023] It should also be understood that the terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clear from the context, the singular form "a", "an" and "the" are intended to include the plural form.
[0024] It should be further understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations, for example, A and / or B can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.
[0025] It should be understood that, although the terms first, second, third, etc. can be adopted in the embodiments of the present application to describe the preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, the first preset range can also be referred to as the second preset range, and similarly, the second preset range can also be referred to as the first preset range without departing from the scope of the embodiments of the present application.
[0026] 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 "when it is determined" or "in response to determining" or "when (the stated condition or event) is detected" or "in response to detecting (the stated condition or event)".
[0027] To make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present application belong to the scope of protection of the present application.
[0028] Various structural schematic diagrams according to the disclosed embodiments of the present application are shown in the drawings. These diagrams are not drawn to scale, in which certain details are exaggerated for the purpose of clarity and certain details can be omitted. The shapes of various regions, layers and the relative size and positional relationship therebetween shown in the diagrams are only exemplary, and in actuality, there can be deviations due to manufacturing tolerances or technical limitations, and regions / layers with different shapes, sizes and relative positions can be additionally designed by those skilled in the art according to actual needs.
[0029] Embodiment One With reference to Figure 1 The symbiotic radio resource allocation method based on bounded CSI error according to the present application comprises the following steps: 1) initializing parameters of a multiple-output single-output multi-user symbiotic radio system; Specifically, the initialization of the parameters of the multiple-output single-output multi-user symbiotic radio system at least includes: M a primary user system base station (BS) of a root antenna,K A single-antenna co-occurring radio node (SN), a single-antenna co-occurring information receiver (SIR), and a single-antenna eavesdropping device (Eve); base station power threshold. Total system circuit power consumption SIR minimum rate , No. Minimum rate of each SN and minimum energy requirement threshold .
[0030] 2) Considering user basic QoS, limited power supply, and minimum energy demand guarantee for coexisting devices, a resource allocation problem for maximizing energy efficiency is established based on the bounded CSI error model. Specifically, the bounded CSI error model is as follows:
[0031] in, and For the CSI uncertainty set; The channel gain from BS to Eve; Indicates the first Channel gain from SN to Eve; and This is the corresponding channel gain estimate; and For the corresponding channel estimation error parameters; and These represent the corresponding upper limits of estimation error.
[0032] The energy efficiency maximization resource allocation problem is as follows:
[0033] Where max(0,x) represents taking values of 0 and x. x The larger of the two; The rate of SIR; For the first The transmission rate of each SN; and For the corresponding user rate QoS requirements; For Eve's rate; Represents the beam vector of BS. Its maximum transmission power; For the first k SN reflectance coefficient; Energy conversion efficiency; For BS to the number k Channel gain of each SN; This indicates that SIR is decoding the first... the SNR of the first the SNR of the first the SNR of the first the SNR of the first is the power amplification factor; the SNR of the first the hardware impairment factor for the first SNR with zero mean and variance ; the hardware impairment factor for the first SNR with zero mean and variance ; the imperfect SIC factor, i.e. and represent perfect SIC and no SIC, respectively; the hardware impairment factor for the first SNR; and are the hardware impairment factor for the SIR and the noise variance, respectively; is the noise variance of Eve.
[0034] 3) solving the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and using the robust resource allocation strategy for symbiotic radio resource allocation.
[0035] The specific process of step 3) is as follows: 31) to deal with the CSI uncertainty in , set and auxiliary variable , combine the S process theorem, C7 into C1, to obtain:
[0036] wherein, is a slack variable, since and are highly coupled, let , the above formula can be equivalent to:
[0037] Similarly, based on , using the worst-case method, we obtain:
[0038] Therefore, the problem P1 becomes:
[0039] 32) since and Still non-convex, based on the semidefinite relaxation method, auxiliary variables are introduced and , become:
[0040] where, , and are relaxation variables. Based on the exponential transformation method, the above formula can be further transformed into:
[0041] where, , and are relaxation variables; and respectively represent and the previous iteration values. Similarly, can be re-expressed as:
[0042] where, , and are relaxation variables, and similarly, the above formula can be transformed into:
[0043] where, , and are relaxation variables, and respectively represent and the previous iteration values. In addition, can be changed to:
[0044] Let , the P2 optimization problem can be equivalent to:
[0045] 33) and , based on the Dingkelbach method, the P3 optimization problem can be equivalent to:
[0046] Based on the alternating optimization theory, the solutions of the active beam vector and the reflection coefficient are obtained, and the optimal solution is brought into the objective function to obtain the final system energy efficiency value. In the above process, it is necessary to comprehensively judge If yes, the above solution is the optimal solution; otherwise, a suboptimal solution is obtained by using a Gauss optimization method.
[0047] Simulation experiment The experimental conditions are that a channel model is set as , indicates a fading coefficient, is a path loss index, is a distance between a transceiver, and other parameters are shown in Table 1.
[0048] Table 1
[0049] Figure 2 The actual outage probability of the receiver end under different schemes is given. The experimental results show that the present application has the lowest outage probability, which indicates that the present application has better transmission performance and more stable signal transmission quality; the traditional non-robust method and the non-ideal hardware damage method have higher outage probability, which indicates that the resource allocation of these schemes cannot match the perturbed channel and obtain the best performance. With the increase of the horizontal axis error, the outage probability of all methods increases, which indicates that the larger the CSI error value, the greater the deviation of the estimated channel from the true value, and thus the reliability of the optimization method is poor.
[0050] Embodiment two Referring to Figure 3 The symbiotic radio resource allocation system based on bounded CSI error comprises: An initialization module, configured to initialize parameters of a multi-output single-output multi-user symbiotic radio system; A building module, configured to consider user basic QoS, limited power supply and minimum energy demand guarantee of symbiotic equipment, and build an energy efficiency maximization resource allocation problem based on a bounded CSI error model; An allocation module, configured to solve the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and perform symbiotic radio resource allocation by using the robust resource allocation strategy.
[0051] In this embodiment, the energy efficiency maximization resource allocation problem is solved based on Dingkelbach and semi-definite relaxation method to obtain the robust resource allocation strategy.
[0052] In this embodiment, the bounded CSI error model is:
[0053] wherein, and are a CSI uncertainty set; is a channel gain from a BS to Eve; indicates the first Channel gain from SN to Eve; and These are the channel gain estimates from BS to Eve and the channel gain estimates from SN to Eve, respectively. and These are the channel estimation error parameters from BS to Eve and from SN to Eve, respectively. and represents the upper limit of the estimation error from BS to Eve and the upper limit of the estimation error from SN to Eve, respectively.
[0054] In this embodiment, the energy efficiency maximization resource allocation problem is:
[0055] Where max(0,x) represents taking values of 0 and x. x The larger of the two; For the rate of SIR; For the first The transmission rate of each SN; and For the corresponding user rate QoS requirements; For Eve's rate; Represents the beam vector of BS. Its maximum transmission power; For the first k SN reflectance coefficient; Energy conversion efficiency; For BS to the number k Channel gain of each SN; This indicates that SIR is decoding the first... When the SN signal is received, the first The signal-to-noise ratio of each SN signal; Indicates the SIR decoding of the first The signal-to-noise ratio of each SN signal; This is the power amplification factor; For the first The mean and variance of each number are zero. Hardware damage factors; ; This indicates that the SIR means zero and the variance is... Hardware damage factors; ; This represents the imperfect serial interference cancellation factor; For the first Hardware damage factor of each SN; and These are the hardware impairment factor and noise variance of SIR, respectively; Let be the noise variance of Eve.
[0056] The division of the modules in the embodiments of the present application is illustrative, and is only a logical function division. In actual implementation, another division manner can be used. In addition, each function module in each embodiment of the present application can be integrated in one processor, or can be physically separated, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module.
[0057] Embodiment three A computer device includes 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 method for allocating symbiotic radio resources based on a bounded CSI error are implemented, for example, including: initializing parameters of a multi-output single-output multi-user symbiotic radio system; considering user basic QoS, limited power supply, and minimum energy requirement guarantee of a symbiotic device, establishing an energy efficiency maximization resource allocation problem based on a bounded CSI error model; solving the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and using the robust resource allocation strategy to allocate symbiotic radio resources. The memory can include an internal memory, for example, a high-speed random access memory, and can also include a non-volatile memory, for example, at least one disk memory. The processor, network interface, and memory are connected to each other through an internal bus, which can be an industry standard architecture bus, a peripheral component interconnect standard bus, an extended industry standard architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provides instructions and data to the processor.
[0058] Embodiment four A computer readable storage medium stores a computer program, which, when executed by a processor, implements steps of the method for co-spectrum radio resource allocation based on bounded CSI error, for example, including: initializing parameters of a multi-output single-output multi-user co-spectrum radio system; considering user basic QoS, limited power supply, and co-spectrum device minimum energy requirement guarantee, establishing an energy efficiency maximization resource allocation problem based on a bounded CSI error model; solving the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and performing co-spectrum radio resource allocation by using the robust resource allocation strategy. Specifically, the computer readable storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. The volatile memory can include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory can include read-only memory (ROM), hard disk, flash memory, optical disc, magnetic disc, etc.
[0059] Those skilled in the art will appreciate that embodiments of the application can be supplied as a method, a system, or a computer program product. Therefore, the application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) having computer usable program code embodied thereon.
[0060] The application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, 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 apparatus to produce a machine, so that the instructions, which are executed via the processor of the computer or other programmable data processing apparatus, generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in a flow or multiple flows and / or blocks Figure 1 The functions specified in a flow or multiple flows and / or blocks
[0061] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including instruction means, which implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in a flow or multiple flows and / or blocks Figure 1 The functions specified in a flow or multiple flows and / or blocks
[0062] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks
[0063] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.
[0064] It is to be understood that the application is not limited to the specific structures described herein and illustrated in the accompanying drawings, which represent only preferred embodiments. The scope of the application is limited only by the claims.
[0065] The above description is only preferred embodiments of the present application, not any limitation thereto, any simple modification, change and equivalent structural change made according to the technical essence of the present application to the above embodiments shall still fall within the protection scope of the technical scheme of the present application.
Claims
1. A method for coexistence radio resource allocation based on bounded CSI error, characterized in that, The method comprises: initializing parameters of a multi-output single-output multi-user coexisting radio system; considering user basic QoS, limited power supply, and minimum energy requirement guarantee of coexisting devices, establishing an energy efficiency maximization resource allocation problem based on a bounded CSI error model; solving the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and performing coexisting radio resource allocation by using the robust resource allocation strategy.
2. The method of claim 1, wherein, The energy efficiency maximization resource allocation problem is solved based on the Dingkelbach and semi-definite relaxation method to obtain the robust resource allocation strategy.
3. The method of claim 1, wherein, The bounded CSI error model is: wherein, and are sets of CSI uncertainties; is a channel gain from the BS to Eve; denotes the channel gain from the th SN to Eve; and are an estimated channel gain from the BS to Eve and an estimated channel gain from the SN to Eve, respectively; and are a channel estimation error parameter from the BS to Eve and a channel estimation error parameter from the SN to Eve, respectively; and denote an upper bound of the estimation error from the BS to Eve and an upper bound of the estimation error from the SN to Eve, respectively.
4. The method of claim 1, wherein, The energy efficiency maximization resource allocation problem is: Where max(0,x) represents taking values of 0 and x. x The larger of the two; The rate of SIR; For the first The transmission rate of each SN; and For the corresponding user rate QoS requirements; For Eve's rate; Represents the beam vector of BS. Its maximum transmission power; For the first k SN reflectance coefficient; Energy conversion efficiency; For BS to the number k Channel gain of each SN; This indicates that SIR is decoding the first... When the SN signal is received, the first The signal-to-noise ratio of each SN signal; Indicates the SIR decoding of the first The signal-to-noise ratio of each SN signal; This is the power amplification factor; For the first The mean and variance of each number are zero. Hardware damage factors; ; This indicates that the SIR means zero and the variance is... Hardware damage factors; ; This represents the imperfect serial interference cancellation factor; For the first Hardware damage factor of each SN; and These are the hardware impairment factor and noise variance of SIR, respectively; Let be the noise variance of Eve.
5. A coexistence radio resource allocation system based on bounded CSI error, characterized by, The method comprises: an initialization module configured to initialize parameters of a multi-output single-output multi-user coexisting radio system; an establishment module configured to consider user basic QoS, limited power supply, and minimum energy requirement guarantee of coexisting devices, and establish an energy efficiency maximization resource allocation problem based on a bounded CSI error model; an allocation module configured to solve the energy efficiency maximization resource allocation problem to obtain a robust resource allocation strategy, and perform coexisting radio resource allocation by using the robust resource allocation strategy.
6. The bounded CSI error based coexistence radio resource allocation system of claim 5, wherein, The energy efficiency maximization resource allocation problem is solved based on the Dingkelbach and semi-definite relaxation method to obtain the robust resource allocation strategy.
7. The bounded CSI error based coexistence radio resource allocation system of claim 5, wherein, The bounded CSI error model is: wherein, and are sets of CSI uncertainties; is a channel gain from the BS to Eve; denotes the channel gain from the th SN to Eve; and are an estimated channel gain from the BS to Eve and an estimated channel gain from the SN to Eve, respectively; and are a channel estimation error parameter from the BS to Eve and a channel estimation error parameter from the SN to Eve, respectively; and denote an upper bound of the estimation error from the BS to Eve and an upper bound of the estimation error from the SN to Eve, respectively.
8. The bounded CSI error based coexistence radio resource allocation system of claim 5, wherein, The energy efficiency maximization resource allocation problem is: where max(0, x) denotes the larger value of 0 and x; x is the rate of SIR; is the transmission rate of the th SN; is the corresponding user rate QoS requirement; is the rate of Eve; is the beam vector of the BS, is the maximum transmit power thereof; is the reflection coefficient of the k th SN; is the energy conversion efficiency; is the channel gain from the BS to the k th SN; is the signal-to-noise ratio of the th SN signal when decoding the th SN signal; is the signal-to-noise ratio of the th SN signal when decoding the th SN signal; is the power amplification coefficient; is the hardware impairment factor with mean zero and variance for the th SN; is the hardware impairment factor with mean zero and variance for SIR; ; is the imperfect successive interference cancellation factor; is the hardware impairment factor for the th SN; are the hardware impairment factor and the noise variance for SIR, respectively; is the noise variance for Eve. 9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the coexisting radio resource allocation method based on the bounded CSI error according to any one of claims 1-4.
10. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to implement the steps of the coexisting radio resource allocation method based on the bounded CSI error according to any one of claims 1-4.