Design of win-win irs assisted opportunistic cognitive wireless network for primary and secondary users
Patent Information
- Application Number
- CN202310761309.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-06-26
- Publication Date
- 2026-09-08
- Estimated Expiration
- 2043-06-26
AI Technical Summary
然而，现有的技术没有考虑智能反射面辅助的频谱感知对主次用户传输性能产生的影响
本发明提供的一种主次用户双赢的IRS辅助机会型认知无线网络设计方法，相较于传统的认知无线电网络，本发明引入智能反射面辅助网络中的频谱感知和主次用户的数据传输，并设计相应的时隙结构，使得智能反射面在感知阶段能够辅助感知，在传输阶段能够根据不同的感知结果选择辅助主用户或次用户，充分利用智能反射面的潜力，实现了在不完美的频谱感知下同时改善认知无线电网络中频谱感知性能以及主次用户传输性能的目的，此外，本发明还提供了一种发射功率、智能反射面相移矩阵和频谱感知时长的联合优化方法，充分调动系统可利用资源，在保证频谱感知精度以及主用户平均可达速率的同时，最大化次用户的平均可达速率，提升网络的感知性能和传输性能。
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Figure CN116963079B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of radio cognitive transmission technology, and in particular to a design method for an IRS-assisted opportunistic cognitive wireless network that achieves a win-win situation for both primary and secondary users. Background Technology
[0002] The rapid development of wireless devices has brought convenience to human life, but it has also created a massive demand for wireless data transmission. Under a fixed spectrum allocation system, the increasing number of wireless devices leads to increasingly congested spectrum, posing a significant challenge to spectrum resources. Cognitive radio technology is one of the main solutions to the spectrum scarcity problem. It allows unlicensed users to access and use licensed spectrum while maintaining the quality of service for licensed users, thereby improving spectrum utilization. Unlicensed users are considered secondary users, while licensed users are considered primary users.
[0003] In opportunistic cognitive radio networks, spectrum sensing is a crucial technology. Its role is to enable secondary users to perceive the operational status of primary users, thus providing them with a basis for determining whether they can access the primary user's licensed spectrum. However, under low signal-to-noise ratio (SNR) conditions, the accuracy of spectrum sensing drops sharply, making it impossible to accurately determine the primary user's operational status. Furthermore, to reduce interference with the primary user, the transmit power of secondary users is often limited, leading to a decline in their transmission performance. Intelligent Reflecting Surfaces (IRS), as an emerging technology for reconfigurable wireless channel environments, consist of multiple independent passive reflective elements. Each reflective element can alter the amplitude and phase of the incident signal, causing the superimposed signals to be amplified or weakened in the desired direction, thereby generating passive beamforming to improve user transmission performance and significantly enhance spectral efficiency. Therefore, introducing intelligent reflectors into cognitive radio networks can improve the network's SNR and enhance the transmission performance of both primary and secondary users.
[0004] Existing technologies only consider using smart reflectors to improve the transmission performance of primary or secondary users in opportunistic cognitive networks, without considering using smart reflectors to simultaneously assist the transmission of both primary and secondary users. Furthermore, using smart reflectors to assist spectrum sensing is one method to address the performance degradation caused by low signal-to-noise ratios. However, existing technologies do not consider the impact of smart reflector-assisted spectrum sensing on the transmission performance of both primary and secondary users. Therefore, designing a transmission scheme that allows smart reflectors to improve both spectrum sensing performance and the transmission performance of both primary and secondary users is a pressing problem in this field. Summary of the Invention
[0005] Therefore, the purpose of this invention is to provide an opportunistic cognitive radio network design method that uses IRS to assist spectrum sensing and data transmission, and provides a joint optimization method to significantly improve the sensing and transmission performance of wireless networks.
[0006] To achieve the above-mentioned objectives, this invention provides a win-win IRS-assisted opportunistic cognitive wireless network design method for primary and secondary users, comprising the following steps: S1. Establish an intelligent reflective surface-assisted cognitive wireless network model consisting of primary users, secondary users, and IRS intelligent reflective surfaces; S2. Design the transmission time slot structure of the intelligent reflector-assisted cognitive wireless network, dividing the transmission time slot structure into a sensing stage and a transmission stage. The intelligent reflector transforms different phase shift matrices in different time slots to assist spectrum sensing or user transmission; S3. Establish a spectrum channel model and a sensing model, and construct a secondary user transmission performance optimization problem, jointly optimizing the secondary user transmit power, sensing duration, and phase shift matrix of the intelligent reflector; S4. Solve the secondary user transmission performance optimization problem using an optimization algorithm based on the alternating iteration method; The optimization problem is a non-convex optimization problem; the optimization problem is constructed as how to maximize the average reachability of secondary users under the constraints of detection probability and average reachability of primary users, i.e.:
[0007]
[0008]
[0009]
[0010]
[0011]
[0012]
[0013] in, This is the minimum average achievable rate that the primary user must meet. This is the maximum transmit power for secondary users. This represents the minimum detection probability that must be met. The average reachable rate for this user This is represented as the phase shift matrix during the IRS-assisted secondary user communication phase. This is represented as the phase shift matrix during the IRS-assisted primary user communication phase. The total duration of a single timeslot. This refers to the duration of the spectrum sensing phase. Indicates the detection probability. The number of reflective units. This is represented as the phase shift matrix in the IRS-assisted spectrum sensing stage; The optimization algorithm decouples the optimization problem into five sub-convex optimization problems based on the alternating iteration method, and solves the five sub-problems alternately and iteratively until the objective function converges, thus obtaining the solution to the original problem. The specific steps of the optimization algorithm include: S401. Given the phase shift matrix , Transmission power and perception duration The original question Transformed into phase shift matrix Optimization issues:
[0014]
[0015] in This represents the direct channel between the primary user transmitter PT and the secondary user transmitter ST. This indicates the channel between the primary user transmitter and the IRS; This represents the maximum phase shift matrix during the IRS-assisted spectrum sensing phase. This indicates the channel between the IRS and the secondary user transmitter; This indicates the magnitude of each element in the IRS; The optimal solution to this problem is expressed in closed form as follows:
[0016] in, Represents the phase shift matrix Phase of each reflecting unit The optimal value; Given a phase shift matrix , Transmission power and perception duration The original question Convert to about Feasibility issues:
[0017]
[0018]
[0019] S402. Constraint (9b) is rewritten as follows regarding The constraints, namely:
[0020] in This indicates the probability that the primary user's spectrum usage will be correctly perceived by the next user. Indicates in The achievable rate for the primary user under these conditions This indicates the direct channel between the primary user transmitter and the primary user receiver (PU). This indicates the channel between the IRS and the primary user receiver (PU). , , This indicates the probability that the primary user will perceive an error in the next instance when the primary user occupies the spectrum. Indicates in Under the given condition, the achievable rate of the primary user needs to be maximized to satisfy this constraint, requiring the cascaded channels to be maximized. , The optimal value is obtained by finding its closed-form expression:
[0021] in, In the phase shift matrix Phase of each reflecting unit The optimal value; S403. For phase shift matrix The solution is obtained by fixing variables; given the phase shift matrix. , Transmission power and perception duration The original problem is transformed into a problem concerning the phase shift matrix. Subproblems:
[0022]
[0023]
[0024] in This indicates the probability that the user will perceive the correct signal the next time the primary user has not occupied the spectrum. This indicates the probability that the user will perceive an error next time the main user occupies the spectrum. This indicates the probability that the main user's spectrum usage will be correctly perceived by the next user. Indicates in Secondary user achievable rate under certain conditions; Indicates in Secondary user achievable rate under certain conditions; Indicates in The achievable rate for the primary user under these conditions; Indicates in The achievable rate for the primary user under these conditions; The objective function and constraints are transformed into expressions of the trace of a matrix, thus converting the subproblem into a semidefinite programming (SDP) problem for solution. The transformed subproblem is as follows:
[0025]
[0026]
[0027]
[0028]
[0029] in, It is a matrix with rank 1. , , ; S404. Using the SROCR method, relax the rank-1 constraint (13e) to ,in express The largest eigenvalue, For the first The relaxation coefficients of the next iteration; after relaxation, the problem is transformed into a convex optimization problem, and the final solution is obtained after iterative convergence. By Jolesky's decomposition method The result is obtained by decomposition; S405. Based on the given phase shift matrix , , and perception duration The original question This can be transformed into the following sub-problem concerning transmission power:
[0030]
[0031]
[0032] in, Indicates the secondary user transmit power. Indicates the maximum transmit power of the secondary user. in, , , , ;when At any time, regardless For any given value, this constraint can be satisfied; under this constraint, the transmit power... The optimal value is ;when Then, based on constraints (14b) and (14c), the optimal transmit power is derived. Closed expressions, i.e. ,in ; where C is an intermediate variable.
[0033] S406. Given a phase shift matrix , , and transmission power The original question Transformed into perception duration Subproblems:
[0034]
[0035] For discussion The unevenness, for about Taking the second derivative, we get:
[0036] S407. Using the golden ratio to determine the duration of perception. The optimal value; S408. The original problem is obtained by iteratively solving all subproblems using the alternating iteration method. The final solution.
[0037] Preferably, the primary user consists of a primary user transmitter and a primary user receiver, and the secondary user consists of a secondary user transmitter and a secondary user receiver; both the primary and secondary user transmitters and receivers are equipped with a single antenna; the number of reflective elements of the intelligent reflector is... Represented by sets The reflective units are arranged in a uniform array.
[0038] Preferably, in step S2, the total duration of a single time slot is The duration of the spectrum sensing phase is The duration of the data transmission phase is During the spectrum sensing phase, the intelligent reflector assists the secondary user in performing spectrum sensing on the primary user, detecting the presence of the primary user's signal. In this phase, the phase shift matrix of the intelligent reflector is... ,in If the primary user is detected to be inactive during the spectrum sensing phase, the secondary user will transmit data during the data transmission phase. In this case, the intelligent reflector assists the secondary user in transmission, and the phase shift matrix is... ,in If the primary user is detected to be active during the spectrum sensing phase, the secondary user will not transmit data. In this case, the intelligent reflector assists the primary user in transmission, and the phase shift matrix is... ,in .
[0039] Preferably, in step S3, the line-of-sight link between the primary user transmitter PT and the primary user receiver PR of the primary and secondary users is represented by a Rayleigh channel:
[0040] in, Path loss for reference distance, The distance between the primary user transmitter and the primary user receiver. The path loss index, It is a complex Gaussian random variable; The link between the primary and secondary users and the intelligent reflector is represented by a Ricean channel:
[0041] in, The distance between the transmitter and the smart reflector. Represents Rice factor, The non-line-of-sight component consists of independent and identically distributed complex Gaussian random variables. The line-of-sight component is composed of the array response of the planar array antenna; Furthermore, given the target detection probability Under these conditions, the false alarm probability of spectrum sensing is expressed as:
[0042] in, Represents the complementary cumulative distribution function. Indicates the sampling frequency. The received signal-to-noise ratio of the secondary user transmitter is denoted as , where The transmit power for primary users, For the channel from the smart reflector to the secondary user transmitter, The channel from the primary user transmitter to the smart reflector. This represents noise power.
[0043] Preferably, the intelligent reflector assists the secondary user in performing spectrum sensing for the primary user. If the sensing result indicates that the primary user is not operating, the secondary user accesses the licensed spectrum for its own data transmission, while the intelligent reflector assists the secondary user in transmission. In this case, the average achievable rate of the secondary user is:
[0044] in The rate at which a secondary user can reach the target assuming the perception result is correct. For the rate achievable by the secondary user in the case of an error in the perceived result, and They are respectively and The probabilities of these two scenarios; When the sensing results indicate that the primary user is active, the secondary user does not access the licensed spectrum, and the intelligent reflector assists the primary user's transmission. In this case, the average achievable rate of the primary user is:
[0045] in The achievable rate for the primary user assuming the perception result is correct. For the rate achievable by the secondary user in the case of an error in the perceived result, and They are respectively and The probabilities corresponding to these two scenarios.
[0046] Compared with the prior art, the beneficial effects of the present invention are: This invention provides a win-win IRS-assisted opportunistic cognitive radio network design method for primary and secondary users. Compared with traditional cognitive radio networks, this invention introduces spectrum sensing and data transmission between primary and secondary users in a smart reflector-assisted network, and designs a corresponding time slot structure. This allows the smart reflector to assist sensing during the sensing phase and select to assist primary or secondary users based on different sensing results during the transmission phase. This fully utilizes the potential of the smart reflector and achieves the goal of simultaneously improving the spectrum sensing performance and the transmission performance of primary and secondary users in the cognitive radio network under imperfect spectrum sensing conditions. In addition, this invention also provides a joint optimization method for transmit power, smart reflector phase shift matrix, and spectrum sensing duration, which fully mobilizes the available resources of the system. While ensuring the accuracy of spectrum sensing and the average reachability rate of primary users, it maximizes the average reachability rate of secondary users, thereby improving the network's sensing and transmission performance. Attached Figure Description
[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0048] Figure 1 This invention provides a model for a win-win IRS-assisted opportunistic cognitive wireless network for both primary and secondary users. Figure 2 This is a transmission time slot structure diagram of a win-win IRS-assisted opportunistic cognitive wireless network provided by an embodiment of the present invention.
[0049] Figure 3 This is a graph showing the relationship between the false alarm probability and the sensing duration under a win-win IRS-assisted opportunistic cognitive wireless network design method for primary and secondary users, provided by an embodiment of the present invention.
[0050] Figure 4 This is a graph showing the relationship between the average reachable rate of secondary users and the minimum average reachable rate required by primary users under a win-win IRS-assisted opportunistic cognitive wireless network design method provided by an embodiment of the present invention. Detailed Implementation
[0051] The principles and features of the present invention are described below with reference to the accompanying drawings. The listed embodiments are only used to explain the present invention and are not intended to limit the scope of the present invention.
[0052] This embodiment provides a win-win IRS-assisted opportunistic cognitive wireless network design method for primary and secondary users. The specific steps are as follows: S1. As Figure 1 As shown, a smart reflector-assisted cognitive wireless network model is established, consisting of a primary user, a secondary user, and an IRS smart reflector. The transmitters and receivers of both the primary and secondary users are equipped with a single antenna, and the number of reflector elements on the smart reflector is [number missing]. Represented by sets The reflective elements are arranged in a uniform array. S2. For example Figure 2 As shown, a transmission time slot structure for an intelligent reflective surface-assisted cognitive wireless network is designed, dividing the transmission time slot structure into a sensing phase and a transmission phase. The total duration of a single time slot in the time slot structure is set to... The duration of the spectrum sensing phase is The duration of the data transmission phase is The intelligent reflector uses different phase shift matrices in different time slots to assist in spectrum sensing or user transmission. During the spectrum sensing phase, the intelligent reflector assists the secondary user in performing spectrum sensing on the primary user, detecting the presence of the primary user's signal. In this phase, the phase shift matrix of the intelligent reflector is... ,in If the primary user is detected to be inactive during the spectrum sensing phase, the secondary user will transmit data during the data transmission phase. In this case, the intelligent reflector assists the secondary user in transmission, and the phase shift matrix is... ,in If the primary user is detected to be active during the spectrum sensing phase, the secondary user will not transmit data. In this case, the intelligent reflector assists the primary user in transmission, and the phase shift matrix is... ,in ; S3. Establish a spectrum channel model and a sensing model, and construct a secondary user transmission performance optimization problem, jointly optimizing the secondary user transmit power, sensing duration, and phase shift matrix of the intelligent reflector; It should be noted that the line-of-sight link between the primary user transmitter (PT) and the primary user receiver (PR) of the primary and secondary users is represented by a Rayleigh channel:
[0053] in, Path loss for reference distance, The distance between the primary user transmitter and the primary user receiver. The path loss index, It is a complex Gaussian random variable; The link between the primary and secondary users and the intelligent reflector is represented by a Ricean channel:
[0054] in, The distance between the transmitter and the smart reflector. Represents Rice factor, The non-line-of-sight component consists of independent and identically distributed complex Gaussian random variables. The line-of-sight component is composed of the array response of the planar array antenna; Furthermore, given the target detection probability Under these conditions, the false alarm probability of spectrum sensing is expressed as:
[0055] in, Represents the complementary cumulative distribution function. Indicates the sampling frequency. The received signal-to-noise ratio of the secondary user transmitter is denoted as , where The transmit power for primary users, For the channel from the smart reflector to the secondary user transmitter, The channel from the primary user transmitter to the smart reflector. For noise power, H As an operator, it is used to perform conjugate transpose on variables.
[0056] like Figure 3 As shown, the false alarm probability of spectrum sensing varies with the sensing duration under different numbers of intelligent reflector units. The "no intelligent reflector" scheme indicates spectrum sensing without the introduction of an intelligent reflector to assist the network. Figure 3 It can be seen that the false alarm probability gradually decreases with the increase of sensing time. In addition, compared with the "no intelligent reflector" scheme, the introduction of intelligent reflector to assist spectrum sensing can greatly reduce the false alarm probability, which confirms the performance gain of intelligent reflector to spectrum sensing under the proposed scheme. Furthermore, it can also be seen from the figure that the magnitude of the false alarm probability is affected by the number of reflector units of the intelligent reflector. Specifically, the more reflector units there are, the smaller the false alarm probability.
[0057] It should be noted that the intelligent reflector assists the secondary user in performing spectrum sensing of the primary user. If the sensing result indicates that the primary user is not operating, the secondary user accesses the licensed spectrum for its own data transmission, while the intelligent reflector assists the secondary user in transmission. In this case, the average achievable rate of the secondary user is:
[0058] in The rate at which a secondary user can reach the target assuming the perception result is correct. For the rate achievable by the secondary user in the case of an error in the perceived result, and They are respectively and The probabilities of these two scenarios; When the sensing results indicate that the primary user is active, the secondary user does not access the licensed spectrum, and the intelligent reflector assists the primary user's transmission. In this case, the average achievable rate of the primary user is:
[0059] in The achievable rate for the primary user assuming the perception result is correct. For the rate achievable by the secondary user in the case of an error in the perceived result, and They are respectively and The probabilities corresponding to these two scenarios.
[0060] It should be noted that the optimization problem is a non-convex optimization problem; the optimization problem is constructed as how to maximize the average reachability of secondary users under the constraints of detection probability and the average reachability rate of primary users, that is:
[0061]
[0062]
[0063]
[0064]
[0065]
[0066]
[0067] in, This is the minimum average achievable rate that the primary user must meet. This is the maximum transmit power for secondary users. This represents the minimum detection probability that must be met. The average reachable rate for this user This is represented as the phase shift matrix during the IRS-assisted secondary user communication phase. This is represented as the phase shift matrix during the IRS-assisted primary user communication phase. The total duration of a single timeslot. This refers to the duration of the spectrum sensing phase. Indicates the detection probability. The number of reflective units. This is represented as the phase shift matrix in the IRS-assisted spectrum sensing stage; S4. Solve the secondary user transmission performance optimization problem using an optimization algorithm based on the alternating iteration method; the optimization algorithm decouples the optimization problem into five sub-convex optimization problems based on the alternating iteration method, and performs alternating iteration on each of the five sub-problems until the objective function converges, thus obtaining the solution to the original problem.
[0068] It should be further explained that the specific steps of the optimization algorithm include: S401. Given the phase shift matrix , Transmission power and perception duration The original question Transformed into phase shift matrix Optimization issues:
[0069]
[0070] in This represents the direct channel between the primary user transmitter PT and the secondary user transmitter ST. This indicates the channel between the primary user transmitter and the IRS; This represents the maximum phase shift matrix during the IRS-assisted spectrum sensing phase. This indicates the channel between the IRS and the secondary user transmitter; This indicates the magnitude of each element in the IRS; The optimal solution to this problem is expressed in closed form as follows:
[0071] in, Represents the phase shift matrix Phase of each reflecting unit The optimal value; Given a phase shift matrix , Transmission power and perception duration The original question Convert to about Feasibility issues:
[0072]
[0073]
[0074] S402. Constraint (9b) is rewritten as follows regarding The constraints, namely:
[0075] in This indicates the probability that the primary user's spectrum usage will be correctly perceived by the next user. Indicates in The achievable rate for the primary user under these conditions This indicates the direct channel between the primary user transmitter and the primary user receiver (PU). This indicates the channel between the IRS and the primary user receiver (PU). , , This indicates the probability that the primary user will perceive an error in the next instance when the primary user occupies the spectrum. Indicates in Under the given condition, the achievable rate of the primary user needs to be maximized to satisfy this constraint, requiring the cascaded channels to be maximized. , The optimal value is obtained by finding its closed-form expression:
[0076] in, In the phase shift matrix Phase of each reflecting unit The optimal value; S403. For phase shift matrix The solution is obtained by fixing variables; given the phase shift matrix. , Transmission power and perception duration The original problem is transformed into a problem concerning the phase shift matrix. Subproblems:
[0077]
[0078]
[0079] in This indicates the probability that the user will perceive the correct signal the next time the primary user has not occupied the spectrum. This indicates the probability that the user will perceive an error next time the main user occupies the spectrum. This indicates the probability that the main user's spectrum usage will be correctly perceived by the next user. Indicates in Secondary user achievable rate under certain conditions; Indicates in Secondary user achievable rate under certain conditions; Indicates in The achievable rate for the primary user under these conditions; Indicates in The achievable rate for the primary user under these conditions; The objective function and constraints are transformed into expressions of the trace of a matrix, thus converting the subproblem into a semidefinite programming (SDP) problem for solution. The transformed subproblem is as follows:
[0080]
[0081]
[0082]
[0083]
[0084] in, It is a matrix with rank 1. , , ; S404. Using the SROCR method, relax the rank-1 constraint (13e) to ,in express The largest eigenvalue, For the first The relaxation coefficients of the next iteration; after relaxation, the problem is transformed into a convex optimization problem, and the final solution is obtained after iterative convergence. By Jolesky's decomposition method The result is obtained by decomposition; S405. Based on the given phase shift matrix , , and perception duration The original question This can be transformed into the following sub-problem concerning transmission power:
[0085]
[0086]
[0087] in, Indicates the secondary user transmit power. Indicates the maximum transmit power of the secondary user. in, , , , ;when At any time, regardless For any given value, this constraint can be satisfied; under this constraint, the transmit power... The optimal value is ;when Then, based on constraints (14b) and (14c), the optimal transmit power is derived. Closed expressions, i.e. ,in ; where C is an intermediate variable.
[0088] S406. Given a phase shift matrix , , and transmission power The original question Transformed into perception duration Subproblems:
[0089]
[0090] For discussion The unevenness, for about Taking the second derivative, we get:
[0091] S407. Using the golden ratio to determine the duration of perception. The optimal value; S408. The original problem is obtained by iteratively solving all subproblems using the alternating iteration method. The final solution.
[0092] like Figure 4 As shown, the average reachability rate of secondary users varies with the minimum average reachability rate required by primary users, from... Figure 3 It can be seen that the optimization algorithm achieves higher primary user and secondary user rates compared to other schemes, demonstrating its superiority. As the minimum average rate required by primary users increases, the average rate of secondary users under all algorithms eventually becomes zero. This is because when the primary user rate requirement is too high, the entire network cannot meet the rate requirement of the primary user with limited resources, thus making the original problem infeasible. Furthermore, compared to other schemes, the proposed scheme simultaneously optimizes the phase shift matrices of spectrum sensing, primary user transmission, and secondary user transmission, fully exploring the potential of the intelligent reflector and achieving better performance. The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A win-win IRS-assisted opportunistic cognitive wireless network design method for primary and secondary users, characterized in that, Includes the following steps: S1. Establish an intelligent reflective surface-assisted cognitive wireless network model consisting of primary users, secondary users, and IRS intelligent reflective surfaces; S2. Design the transmission time slot structure of the intelligent reflector-assisted cognitive wireless network, dividing the transmission time slot structure into a sensing stage and a transmission stage. The intelligent reflector changes different phase shift matrices in different time slots to assist spectrum sensing or user transmission; S3. Establish a spectrum channel model and a sensing model, and construct a secondary user transmission performance optimization problem, jointly optimizing the secondary user transmit power, sensing duration, and phase shift matrix of the intelligent reflector; S4. Solve the secondary user transmission performance optimization problem using an optimization algorithm based on the alternating iteration method; The optimization problem is a non-convex optimization problem; it is constructed as how to maximize the average reachability of secondary users under the constraints of detection probability and average reachability of primary users, i.e.: in, This is the minimum average achievable rate that the primary user must meet. This is the maximum transmit power for secondary users. The minimum detection probability that needs to be met. The average reachable rate for this user This is represented as the phase shift matrix during the IRS-assisted secondary user communication phase. This is represented as the phase shift matrix during the IRS-assisted primary user communication phase. The total duration of a single timeslot. This refers to the duration of the spectrum sensing phase. Indicates the secondary user transmit power. Indicates the maximum transmit power of the secondary user. Indicates the detection probability. The number of reflective units. This is represented as the phase shift matrix in the IRS-assisted spectrum sensing stage; The optimization algorithm decouples the optimization problem into five sub-convex optimization problems based on the alternating iteration method, and solves the five sub-problems alternately and iteratively until the objective function converges, thus obtaining the solution to the original problem. The specific steps of the optimization algorithm include: S401. Given the phase shift matrix , Transmission power and perception duration The original question Transformed into phase shift matrix Optimization issues: in This represents the direct channel between the primary user transmitter PT and the secondary user transmitter ST. This indicates the channel between the primary user transmitter and the IRS; This represents the maximum phase shift matrix during the IRS-assisted spectrum sensing phase. This indicates the channel between the IRS and the secondary user transmitter; This indicates the magnitude of each element in the IRS; The optimal solution to this problem is expressed in closed form as follows: in, Represents the phase shift matrix Phase of each reflecting unit The optimal value; Given a phase shift matrix , Transmission power and perception duration The original question Convert to about Feasibility issues: S402. Constraint (9b) is rewritten as follows regarding The constraints, namely: in This indicates the probability that the primary user's spectrum usage will be correctly perceived by the next user. Indicates in The achievable rate for the primary user under these conditions, This indicates the direct channel between the primary user transmitter and the primary user receiver (PU). This indicates the channel between the IRS and the primary user receiver (PU). , , This indicates the probability that the primary user will perceive an error in the next instance when the primary user occupies the spectrum. Indicates in Under the given condition, the achievable rate of the primary user needs to be maximized to satisfy this constraint, requiring the cascaded channels to be maximized. , The optimal value is obtained by finding its closed-form expression: in, In the phase shift matrix Phase of each reflecting unit The optimal value; S403. For phase shift matrix The solution is obtained by fixing variables; given the phase shift matrix. , Transmission power and perception duration The original problem is transformed into a problem concerning the phase shift matrix. Subproblems: in This indicates the probability that the user will perceive the correct signal the next time the primary user has not occupied the spectrum. This indicates the probability that the user will perceive an error next time the main user occupies the spectrum. This indicates the probability that the main user's spectrum usage will be correctly perceived by the next user. Indicates in Secondary user achievable rate under certain conditions; Indicates in Secondary user achievable rate under certain conditions; Indicates in The achievable rate for the primary user under these conditions; Indicates in The achievable rate for the primary user under these conditions; The objective function and constraints are transformed into expressions of the trace of a matrix, thus converting the subproblem into a semidefinite programming (SDP) problem for solution. The transformed subproblem is as follows: in, It is a matrix with rank 1. , , ; S404. Using the SROCR method, relax the rank-1 constraint (13e) to ,in express The largest eigenvalue, For the first The relaxation coefficients of the next iteration; after relaxation, the problem is transformed into a convex optimization problem, and the final solution is obtained after iterative convergence. By Jolesky's decomposition method The result is obtained by decomposition; S405. Based on the given phase shift matrix , , and perception duration The original question This can be transformed into the following sub-problem concerning transmission power: in, Indicates the secondary user transmit power. Indicates the maximum transmit power of the secondary user. in, , , , ;when At any time, regardless For any given value, this constraint can be satisfied; under this constraint, the transmit power... The optimal value is ;when Then, based on constraints (14b) and (14c), the optimal transmit power is derived. Closed expressions, i.e. ,in ; where C is an intermediate variable. S406. Given a phase shift matrix , , and transmission power The original question Transformed into perception duration Subproblems: For discussion The unevenness, for about Taking the second derivative, we get: S407. Using the golden ratio to determine the duration of perception. The optimal value; S408. The original problem is obtained by iteratively solving all subproblems using the alternating iteration method. The final solution.
2. The IRS-assisted opportunistic cognitive wireless network design method for a win-win situation for primary and secondary users as described in claim 1, characterized in that, The primary user consists of one primary user transmitter and one primary user receiver, and the secondary user consists of one secondary user transmitter and one secondary user receiver; both the primary and secondary user transmitters and receivers are equipped with a single antenna; the number of reflective elements in the intelligent reflector is... Represented by sets The reflective units are arranged in a uniform array.
3. The IRS-assisted opportunistic cognitive wireless network design method for a win-win situation for primary and secondary users as described in claim 1, characterized in that, In step S2, the total duration of a single time slot is The duration of the spectrum sensing phase is The duration of the data transmission phase is During the spectrum sensing phase, the intelligent reflector assists the secondary user in performing spectrum sensing on the primary user, detecting the presence of the primary user's signal. In this phase, the phase shift matrix of the intelligent reflector is... ,in ; If the primary user is detected to be inactive during the spectrum sensing phase, the secondary user will transmit data during the data transmission phase. In this case, the intelligent reflector assists the secondary user in transmission, and the phase shift matrix is... ,in ; If the primary user is detected to be active during the spectrum sensing phase, the secondary user will not transmit data. In this case, the intelligent reflector assists the primary user in transmission, and the phase shift matrix is... ,in .
4. The IRS-assisted opportunistic cognitive wireless network design method for a win-win situation for primary and secondary users as described in claim 1, characterized in that, In step S3, the line-of-sight link between the primary user transmitter PT and the primary user receiver PR of the primary and secondary users is represented by a Rayleigh channel: in, Path loss for reference distance, The distance between the primary user transmitter and the primary user receiver. The path loss index, It is a complex Gaussian random variable; The link between the primary and secondary users and the intelligent reflector is represented by a Ricean channel: in, The distance between the transmitter and the smart reflector. Represents Rice factor, The non-line-of-sight component consists of independent and identically distributed complex Gaussian random variables. The line-of-sight component is composed of the array response of the planar array antenna; Furthermore, given the target detection probability Under these conditions, the false alarm probability of spectrum sensing is expressed as: in, Represents the complementary cumulative distribution function. Indicates the sampling frequency. The received signal-to-noise ratio of the secondary user transmitter is denoted as , where The transmit power for primary users, For the channel from the smart reflector to the secondary user transmitter, The channel from the primary user transmitter to the smart reflector. This represents noise power.
5. The IRS-assisted opportunistic cognitive wireless network design method for a win-win situation for primary and secondary users as described in claim 1, characterized in that, The intelligent reflector assists the secondary user in performing spectrum sensing of the primary user. If the sensing result indicates that the primary user is not operating, the secondary user accesses the licensed spectrum for its own data transmission, while the intelligent reflector assists the secondary user in transmission. In this case, the average achievable rate of the secondary user is: in The rate at which a secondary user can reach the target assuming the perception result is correct. For the rate achievable by the secondary user in the case of an error in the perceived result, and They are respectively and The probabilities of these two scenarios; When the sensing results indicate that the primary user is active, the secondary user does not access the licensed spectrum, and the intelligent reflector assists the primary user's transmission. In this case, the average achievable rate of the primary user is: in The achievable rate for the primary user assuming the perception result is correct. For the rate achievable by the secondary user in the case of an error in the perceived result, and They are respectively and The probabilities corresponding to these two scenarios.