Electric power cognitive radio NC-OFDM pilot frequency design method and system
By introducing weighted cross-correlation and ant colony algorithm optimization into the pilot design in the NC-OFDM communication system, the problem of low channel estimation performance in the prior art is solved, and the channel estimation performance is improved.
Patent Information
- Application Number
- CN202511176885.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-21
- Publication Date
- 2025-11-11
AI Technical Summary
In existing NC-OFDM communication systems, pilot design focuses solely on minimizing cross-correlation, resulting in low channel estimation performance and impacting overall communication system performance.
We introduce weighted cross-correlation and combine it with ant colony algorithm to optimize pilot design. By iteratively optimizing pilot position and power through ant colony algorithm, we optimize the sampling matrix corresponding to the pilot and improve channel estimation performance.
This improves the channel estimation performance of the NC-OFDM system and enhances the accuracy of signal reconstruction.
Smart Images
Figure CN120934969A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of communication technology, and in particular relates to a pilot design method and system for electric cognitive radio (NC-OFDM). Background Technology
[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.
[0003] With the rapid development of smart grids, existing wireless network resources can no longer meet the diverse needs of communication services. Since cognitive radio (CR) technology can utilize idle licensed frequency bands to improve spectrum efficiency, communication systems based on non-continuous orthogonal frequency division multiplexing (NC-OFDM) technology have great application potential. The introduction of the cognitive wireless sensor network concept effectively solves the problems faced by smart grid wireless sensor networks, such as the coexistence of heterogeneous wireless networks, spectrum resource scarcity, and low spectrum resource utilization.
[0004] For coherent NC-OFDM communication systems, the receiver needs to accurately obtain channel state information through channel estimation methods during coherent demodulation. The accuracy of channel estimation determines the bit error rate of the communication, and thus the performance of the entire communication system. Currently, channel estimation techniques can be divided into blind channel estimation, semi-blind channel estimation, and pilot-based channel estimation. In pilot-based channel estimation, the transmitter needs to insert pilot symbols, and the receiver performs channel estimation using the received known pilot symbols. Since compressed sensing technology can accurately reconstruct the original high-dimensional signal with fewer sample values, and NC-OFDM channels are typically sparse, using sparse channel estimation based on compressed sensing can reduce the number of pilots used, thus achieving NC-OFDM channel estimation.
[0005] In NC-OFDM communication systems, pilots are selected from available subcarriers for channel estimation. Different pilot combinations correspond to a uniquely determined sampling matrix, and different sampling matrices have different reconstruction performance, thus affecting the NC-OFDM channel estimation performance. According to compressed sensing theory, the lower the correlation of the sampling matrix, the better the sparse reconstruction performance and signal reconstruction quality. Existing technologies often design pilots by minimizing the mutual coherence (MC) of the sampling matrix. However, the mutual coherence refers to the maximum value of the inner product of the normalized absolute values of the mutual coherence of any two columns of the matrix. It can only reflect the maximum value of the correlation values of any two possible columns of the matrix. That is, the mutual coherence can only reflect the upper bound of the correlation values of any two columns of the sampling matrix and cannot reflect the correlation values of other columns. This leads to low performance of signal estimation using pilots designed only with the minimum mutual coherence value, affecting the performance of the communication system. Summary of the Invention
[0006] To address the shortcomings of the existing technology, this invention provides a pilot design method and system for electric cognitive radio (NC-OFDM). By introducing weighted cross-correlation and combining it with ant colony optimization, the performance of the designed pilot corresponding sampling matrix is effectively improved, thereby enhancing the NC-OFDM channel estimation performance.
[0007] In a first aspect, the present invention provides a pilot design method for NC-OFDM power cognitive radio.
[0008] A method for designing pilot signals for NC-OFDM (Non-Cognitive Radio) power systems includes: Based on the available carrier set of the NC-OFDM communication system, M pilots are selected from the set, and each selection... The initial pilot vector is formed by the position indices of the pilot carriers. The ant colony algorithm parameters are initialized using the pilot vector as the ant matrix. Randomly generate the initial positions of the ants, and calculate the pheromone and state transition probability matrix for each ant; Based on pheromones and state transition probability matrices, outer and inner loops are iterated to optimize ant positions. During the iteration process, the optimal pilot position index is determined by minimizing the weighted cross-correlation of the sampling matrices corresponding to the pilot vectors. Based on the optimal pilot position index, the pilot power is determined using the minimum cross-correlation method, and the pilot design results of the NC-OFDM communication system are obtained.
[0009] Secondly, the present invention provides a pilot design system for electric cognitive radio (NC-OFDM).
[0010] A power cognitive radio NC-OFDM pilot design system includes: The initialization module is used to select M pilots from the available carrier set for an NC-OFDM communication system, and to select M pilots each time. The initial pilot vector is formed by the position indices of the pilot carriers. The ant colony algorithm parameters are initialized using the pilot vector as the ant matrix. The pilot position determination unit is used to randomly generate the initial position of the ants and calculate the pheromone and state transition probability matrix for each ant. Based on the pheromone and state transition probability matrix, it performs outer and inner loop iterations to optimize the ant position. During the iteration process, the optimal pilot position index is determined with the goal of minimizing the weighted cross-correlation of the sampling matrix corresponding to the pilot vector. The pilot power determination unit is used to determine the pilot power based on the optimal pilot position index and the minimum cross-correlation method, so as to obtain the pilot design results of the NC-OFDM communication system.
[0011] Thirdly, the present invention also provides an electronic device, comprising: a memory for storing executable instructions; and a processor for implementing the above-described power cognitive radio NC-OFDM pilot design method when executing the executable instructions stored in the memory.
[0012] Fourthly, the present invention also provides a computer-readable storage medium storing executable instructions for causing a processor to execute the executable instructions to implement the above-described power cognitive radio NC-OFDM pilot design method.
[0013] Fifthly, the present invention also provides a computer program product comprising executable instructions stored in a computer-readable storage medium; wherein, when the processor of an electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, the above-described power cognitive radio NC-OFDM pilot design method is implemented.
[0014] The above one or more technical solutions have the following beneficial effects: This invention provides a pilot design method and system for NC-OFDM (Cognitive Radio-to-Distributed) systems. It introduces weighted cross-correlation and combines it with an ant colony algorithm to optimize pilot design. The weighted cross-correlation considers the impact of sampling matrix cross-correlation and t-average mutual coherence (t-AMC) on sparse signal reconstruction performance. With the goal of minimizing weighted cross-correlation, the pilot position and power are iteratively optimized using the ant colony algorithm. This optimizes the design of the pilot-corresponding sampling matrix for NC-OFDM, improves the performance of the designed sampling matrix, enhances the accuracy of sparse signal reconstruction, and ultimately improves the channel estimation performance of the NC-OFDM system.
[0015] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0016] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.
[0017] Figure 1 This is a flowchart of the NC-OFDM pilot design method for electric cognitive radio as described in an embodiment of the present invention; Figure 2 This is a schematic diagram showing the result of determining pilot power based on pilot position index in an embodiment of the present invention. Detailed Implementation
[0018] It should be noted that the following detailed descriptions are exemplary and are intended only to describe specific embodiments and to provide further explanation of the invention, and are not intended to limit the scope of exemplary embodiments of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.
[0019] Example 1 This embodiment provides a method for designing pilot signals for NC-OFDM (Non-Cognitive Radio Digitization), such as... Figure 1 As shown, the specific steps include: Step S1: Based on the available carrier set of the NC-OFDM communication system, select M pilots from them, and select each time... The initial pilot vector is formed by the position indices of the pilot carriers. The ant colony algorithm parameters are initialized using the pilot vector as the ant matrix.
[0020] Step S2: Randomly generate the initial position of the ants and calculate the pheromone and state transition probability matrix for each ant.
[0021] Step S3: Based on the pheromone and the state transition probability matrix, perform outer and inner loop iterations to optimize the ant position; during the iteration process, the optimal pilot position index is determined with the goal of minimizing the weighted cross-correlation of the sampling matrix corresponding to the pilot vector.
[0022] Step S4: Based on the optimal pilot position index, determine the pilot power using the minimum cross-correlation method to obtain the pilot design results of the NC-OFDM communication system.
[0023] The following content provides a more detailed introduction to the NC-OFDM pilot design method for electric cognitive radio proposed in this embodiment.
[0024] In this embodiment, for ease of understanding, the corresponding parameter values are first set: Let Indicates the number of subcarriers in the NC-OFDM system. Indicates the number of pilot symbols in an NC-OFDM system. For the set of all available carriers; let Indicates a size of Extracted from the Fourier matrix Where line and front Composed of columns This matrix is the sampling matrix; Indicates the first l Pilot symbols on each carrier, For the first Pilot power on each carrier is ;use Representation matrix The column-normalized matrix, , Representation matrix The i Column and number j The inner product of the normalized absolute values of the columns.
[0025] Preferably, according to compressed sensing theory, ideally, the smaller the inner product of the normalized absolute values of any two columns of the sampling matrix (i.e., the correlation value of any two columns), the better the reconstruction performance. However, existing technologies mostly design pilots based on minimizing the cross-correlation of the sampling matrix. Cross-correlation only reflects the maximum value of the correlation values of any two columns, which is only an extreme case of correlation. That is, cross-correlation reflects the upper bound of the correlation values of any two columns, and it cannot guarantee that the correlation values between columns other than the two least correlated columns in the sampling matrix are minimized. Research shows that the correlation values of any two columns of the sampling matrix should be as small as possible, thus it cannot guarantee that the final designed pilot will have optimal channel estimation performance. Therefore, this embodiment considers both the cross-correlation of the sampling matrix and the t-average cross-correlation, and defines the weighted cross-correlation in the compressed sensing algorithm. , The smaller the value, the smaller the correlation between the two least correlated columns in the sampling matrix. While minimizing this maximum correlation value, the t-mean cross-correlation also minimizes the correlation between any two other columns, thus minimizing the correlation between any two columns in the sampling matrix and achieving optimal pilot index position performance. Among these, weighted cross-correlation... It can be represented as: , (1) in, , They are respectively: (2) (3) in, , For the preset value, To meet of The number of and The ratio of .
[0026] Based on the above, utilizing the available carrier set and compressed sensing algorithm principles in the NC-OFDM communication system, and aiming to minimize weighted cross-correlation, the ant colony algorithm is employed to determine the pilot symbol position index, including: In step S1, a carrier is selected from the available carrier set of the NC-OFDM communication system. Secondary pilot, and each time selected The indices form the initial pilot vector, and this pilot vector forms the ant matrix. Initialize the ant colony algorithm parameters, including: initializing the number of ants. Maximum number of iterations pheromone volatile factors Search step size , ,and Step size transition probability constant , M A pheromone matrix (or pheromone vector) with 1 row and 1 column. , OK M Transition probability matrix of columns Ant matrix ,vector All available carriers pilot number Available carrier index set The number of available carriers is .
[0027] In step S2, random generation The initial position of the ants , Each line represents one ant. The i Random behavior from Selected Count the number of ants and calculate the pheromones of each ant. , among which, the ant pheromones The calculation is shown in the following formula (4): (4) Furthermore, calculation For weighted cross-correlation, i.e., equation (5): (5) in, ; ; , Represents the sampling matrix The i Column and number j The inner product of normalized absolute values of columns, For a pre-set value, it means Sort all items on the diagonal of the matrix in descending order. Number, To meet of The number of and The ratio, .
[0028] Then, based on the aforementioned pheromone matrix, the corresponding state transition probability matrix is calculated. . In step S3, outer and inner loops are iterated continuously until the weighted cross-correlation of the sampling matrix corresponding to the ant position is minimized, thus obtaining the optimal ant position, which is the optimal pilot position index.
[0029] Within the outer loop of the iteration, the state transition probability of each ant is calculated based on its pheromones. Specifically, for the ... Secondary external circulation Calculate the maximum pheromone value And then calculate The state transition probability of an ant. The probability of a single ant's transition for: (6) Furthermore, within the inner loop of the iteration, a portion of the ant's index value is randomly updated, i.e., randomly selected from the set of available carriers. Replace the original ant with an index. Each index forms a new ant, and the weighted cross-correlation value of the sampling matrix corresponding to the new ant (i.e., the new pilot vector) is calculated. If the newly generated ant (i.e. the new pilot) has a smaller weighted cross-correlation, the ant is updated; otherwise, the ant remains unchanged.
[0030] Specifically, in the inner loop of the iteration, the items to be replaced for the ants are determined based on the state transition probability, the ant positions are updated, and the calculation is performed based on the updated ants. The pheromones of the first ant. Specifically, for the first... The inner loop makes , From Remove from middle In A vector consisting of terms. From Remove from middle The vector consisting of all its terms 1 row A vector of columns; if ,make ,like ,make Randomly generated arrive Between A set of random numbers That is, equation (7), randomly generated arrive Between A set of random numbers That is, equation (8), using vectors exist Item replacement in position In vectors The position term, i.e., equation (9), refers to the ant. exist Place the item in the location of The position, i.e., equation (10), is expressed as follows: (7) (8) (9) (10) Furthermore, if If the corresponding perception matrix has a smaller weighted cross-correlation, then update the first... One ant, that is And thus update the first The pheromone of an ant, expressed as formula (11), is: (11) Through the iterative process of the ant colony algorithm described above, the position of the ant with the minimum weighted cross-correlation of the sampling matrix corresponding to the pilot vector is determined, and this position is the optimal pilot index position.
[0031] Specifically, in After the second iteration, the pheromone is obtained. The maximum value, assuming the maximum value is Then the optimal pilot position is The position matrix is as follows: (12) in, .
[0032] In step S4, based on the optimal ant position found, i.e. the pilot index position, and combined with the cross-correlation principle of the compressed sensing algorithm, the power value of the pilot symbol at each pilot carrier position is determined by minimizing the cross-correlation method, i.e., the pilot power at the pilot index position is determined.
[0033] Specifically, such as Figure 2 As shown, based on the obtained optimal pilot position index, let Combined with the preset lower and upper limits of pilot power and the total power of all pilot symbols Solve for the given command. The minimum power value, i.e., the pilot power calculated according to the following formula (13), can be expressed as: (13) in, for: (14) Where z represents the equivalent cross-correlation value, and equation (13) minimizes the equivalent cross-correlation; F represents the Frobenius norm; express The real part, express The imaginary part, This indicates the search for the infinite norm of a vector, which is the maximum value of the vector.
[0034] Finally, the output pilot symbol position index is used. and the power value of the pilot symbol This is the final result of the pilot design for the NC-OFDM communication system.
[0035] The pilot design method for the NC-OFDM system proposed in this embodiment can minimize the weighted cross-correlation, improve the accuracy of sparse signal reconstruction from the sampling matrix, and thus improve the channel estimation performance of the OFDM system.
[0036] Example 2 This embodiment provides a pilot design system for NC-OFDM (Cognitive Electric Wire) radio, the system comprising: The initialization module is used to select M pilots from the available carrier set for an NC-OFDM communication system, and to select M pilots each time. The initial pilot vector is formed by the position indices of the pilot carriers. The ant colony algorithm parameters are initialized using the pilot vector as the ant matrix. The pilot position determination unit is used to randomly generate the initial position of the ants and calculate the pheromone and state transition probability matrix for each ant. Based on the pheromone and state transition probability matrix, it performs outer and inner loop iterations to optimize the ant position. During the iteration process, the optimal pilot position index is determined with the goal of minimizing the weighted cross-correlation of the sampling matrix corresponding to the pilot vector. The pilot power determination unit is used to determine the pilot power based on the optimal pilot position index and the minimum cross-correlation method, so as to obtain the pilot design results of the NC-OFDM communication system.
[0037] Example 3 This embodiment provides an electronic device, including: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement the method provided in this embodiment.
[0038] Example 4 This embodiment also provides a computer-readable storage medium storing executable instructions, which, when executed by a processor, will cause the processor to execute the method described above in this embodiment.
[0039] Example 5 This embodiment provides a computer program product including executable instructions, which are computer instructions; the executable instructions are stored in a computer-readable storage medium. When the processor of an electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, the electronic device performs the method described in this embodiment.
[0040] The steps and methods involved in Embodiments 2 to 5 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.
[0041] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.
[0042] The above description is only a preferred embodiment of the present invention. Although the specific implementation of the present invention has been described in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that, based on the technical solution of the present invention, various modifications or variations that can be made by those skilled in the art without creative effort are still within the scope of protection of the present invention.
Claims
1. A pilot design method for NC-OFDM electric cognitive radio, characterized in that, include: Based on the available carrier set of the NC-OFDM communication system, M pilots are selected from the set, and each selection... The initial pilot vector is formed by the position indices of the pilot carriers. The ant colony algorithm parameters are initialized using the pilot vector as the ant matrix. Randomly generate the initial positions of the ants, and calculate the pheromone and state transition probability matrix for each ant; Based on pheromones and the state transition probability matrix, outer and inner loop iterations are performed to optimize the ant position; During the iteration process, the optimal pilot position index is determined with the goal of minimizing the weighted cross-correlation of the sampling matrix corresponding to the pilot vector. Based on the optimal pilot position index, the pilot power is determined using the minimum cross-correlation method, and the pilot design results of the NC-OFDM communication system are obtained.
2. The power cognitive radio NC-OFDM pilot design method as described in claim 1, characterized in that, The ant colony algorithm is used to continuously optimize and iteratively calculate the optimal pilot position index, which is: Initialize the ant colony algorithm parameters, including: initial number of ants M, maximum number of iterations, pheromone evaporation factor, search step size, transition probability constant, pheromone matrix, and state transition probability matrix P; Randomly generate the initial positions of M ants, calculate the pheromone of each ant, and then calculate the state transition probability matrix P; where the pheromone is the reciprocal of the weighted cross-correlation of the sampling matrix, and the sampling matrix is the matrix formed by the ant positions; The outer loop iterates continuously, calculating the state transition probability of each ant based on its pheromones; the inner loop iterates continuously, determining the items to replace the ants based on the state transition probabilities, updating the ant positions, and updating the ant pheromones. Through continuous iteration, the optimal ant position is obtained when the weighted cross-correlation of the sampling matrix corresponding to the ant position is minimized, which is the optimal pilot position index.
3. The power cognitive radio NC-OFDM pilot design method as described in claim 2, characterized in that, The formula for calculating the pheromone is: ； in, Indicates weighted cross-correlation. , Indicates weight; ; ; , Represents the sampling matrix The i Column and number j The inner product of normalized absolute values of columns, For a pre-set value, it means Sort all items on the diagonal of the matrix in descending order. Number, To meet of The number of and The ratio, .
4. The power cognitive radio NC-OFDM pilot design method as described in claim 2, characterized in that, During the inner loop, the items to be replaced for the ant are determined based on the state transition probability, the ant's position is updated, and the ant's pheromone is updated, including: In the In the next inner loop, let , From Remove from middle In A vector consisting of terms. From Remove from middle The vector consisting of all its terms 1 row A vector of columns; When the state transition probability , make step length When the state transition probability , make step length Randomly generated arrive Between A set of random numbers Randomly generated arrive Between A set of random numbers , will vector exist Replace the position item with In vectors The item of position will be the ant exist Place the item in the location of Location, if If the corresponding perception matrix has a smaller weighted cross-correlation, then update the first... The location of each ant, that is .
5. The power cognitive radio NC-OFDM pilot design method as described in claim 4, characterized in that, Also includes: Based on the updated ant positions, update the... The pheromone of an ant is represented as: ； in, This refers to the pheromone volatile factor.
6. The power cognitive radio NC-OFDM pilot design method as described in claim 1, characterized in that, Based on the optimal pilot position index, the pilot power is determined using the minimum cross-correlation method, as follows: Based on the obtained optimal pilot position index, and the preset lower and upper limits of pilot power and the total power of all pilot symbols, the solution is obtained for... The pilot power is obtained by taking the minimum power value, which is expressed as: ； Among them, the position matrix ; ; , These represent the lower limit, upper limit, and total power of all pilot symbols, respectively. The power is represented by F, which represents the Frobenius norm. express The real part, express The imaginary part.
7. A pilot design system for electric cognitive radio (NC-OFDM), characterized in that, include: The initialization module is used to select M pilots from the available carrier set for an NC-OFDM communication system, and to select M pilots each time. The initial pilot vector is formed by the position indices of the pilot carriers. The ant colony algorithm parameters are initialized using the pilot vector as the ant matrix. The pilot position determination unit is used to randomly generate the initial position of the ants and calculate the pheromone and state transition probability matrix for each ant. Based on pheromones and the state transition probability matrix, outer and inner loop iterations are performed to optimize the ant position; During the iteration process, the optimal pilot position index is determined with the goal of minimizing the weighted cross-correlation of the sampling matrix corresponding to the pilot vector. The pilot power determination unit is used to determine the pilot power based on the optimal pilot position index and the minimum cross-correlation method, so as to obtain the pilot design results of the NC-OFDM communication system.
8. An electronic device, characterized in that, include: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the NC-OFDM pilot design method of any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The device stores executable instructions that, when executed by a processor, implement the NC-OFDM pilot design method for electric cognitive radio as described in any one of claims 1-6.
10. A computer program product, characterized in that, The computer program product includes executable instructions stored in a computer-readable storage medium; When the processor of the electronic device reads the executable instructions from the computer-readable storage medium and executes the executable instructions, it implements the NC-OFDM pilot design method of any one of claims 1-6.