An adaptive signal waveform generation method and device for unmanned ad hoc networks

Abstract

The application discloses an adaptive signal waveform generation method and device for unmanned ad hoc networks, and the method comprises the following steps: acquiring total communication band information and communication device number information of the unmanned ad hoc networks; performing division processing on the total communication band information to obtain a communication band set and a synchronization coding frequency band; the communication band set comprises communication sub-frequency bands and center frequency information of each communication device; and based on the communication band set and the synchronization coding frequency band, the communication waveform of each communication device is designed to obtain the communication waveform of each communication device.

Description

Technical Field

[0001] This invention relates to the fields of unmanned ad hoc network communication, information transmission, and waveform design, specifically to an adaptive signal waveform generation method and apparatus for unmanned ad hoc networks. Background Technology

[0002] In recent years, unmanned ad hoc network (AAN) technology has seen rapid development and application in unmanned cluster communication scenarios, with an increasing number of devices connecting to AAN networks. These devices require efficient and reliable communication. However, existing communication waveform design methods have several problems in AAN network scenarios. On the one hand, traditional communication waveform designs often fail to fully consider the low-power consumption requirements of AAN network devices, leading to excessive power consumption during communication, thus shortening device lifespan and increasing maintenance costs and replacement frequency. On the other hand, in multi-user environments, existing communication waveform designs struggle to effectively resist mutual interference between multiple users, easily resulting in signal collisions and data loss, severely impacting the communication quality and reliability of AAN network systems. Furthermore, existing methods lack flexibility in frequency band allocation and waveform design, making it difficult to adaptively adjust based on the specific number of AAN network devices and communication frequency band information, failing to fully utilize frequency band resources and thus limiting the overall performance improvement of AAN network systems.

[0003] The problem that needs to be solved is how to design a low-power communication waveform that is resistant to multi-user interference for unmanned self-organizing network scenarios. Summary of the Invention

[0004] This invention primarily addresses the problem of designing low-power and multi-user interference-resistant communication waveforms for unmanned ad hoc network scenarios. This invention discloses an adaptive signal waveform generation method and apparatus for unmanned ad hoc networks.

[0005] In a first aspect, this invention discloses an adaptive signal waveform generation method for unmanned ad hoc networks, comprising:

[0006] S1, obtain the total communication frequency band information and the number of communication devices of the unmanned self-organizing network;

[0007] S2, the total communication frequency band information is divided to obtain a communication frequency band set and a synchronization coding frequency band; the communication frequency band set includes the communication sub-frequency band and center frequency information of each communication device in the unmanned ad hoc network;

[0008] S3, based on the communication frequency band set and synchronous coding frequency band, designs the communication waveform of each communication device to obtain the communication waveform of each communication device.

[0009] The process of dividing the total communication frequency band information to obtain a communication frequency band set and a synchronization coding frequency band includes:

[0010] S21, using a preset scaling factor, the total communication frequency band information is divided into a communication frequency band and a synchronization coding frequency band; the ratio of the bandwidth of the communication frequency band to the bandwidth of the synchronization coding frequency band is the scaling factor.

[0011] S22, the communication frequency band is evenly divided into N communication sub-bands. Each communication sub-band is the communication sub-band of each communication device in the unmanned self-organizing network. The center frequency of each sub-band is the center frequency information of each communication device.

[0012] The communication waveform of each communication device is designed based on the communication frequency band set and synchronous coding frequency band, resulting in the following:

[0013] S31, based on the communication frequency band set, design the data loading waveform for each communication device to obtain the data loading waveform and synchronization coding information for each communication device;

[0014] S32, based on the synchronization coding frequency band and the synchronization coding information of each communication device, the synchronization waveform of each communication device is designed to obtain the synchronization waveform of each communication device;

[0015] S33, the data loading waveform and synchronization waveform of each communication device are superimposed in the time domain to obtain the communication waveform of each communication device.

[0016] The design of the data loading waveform for each communication device based on the communication frequency band set yields the data loading waveform and synchronization coding information for each communication device, including:

[0017] S311, based on the number of communication sub-bands and the ratio of the highest center frequency of all communication sub-bands to the bandwidth of the communication sub-bands, the coefficient solution matrix X is constructed;

[0018] The expression for the non-zero elements in the coefficient solution matrix is ​​as follows:

[0019] ,

[0020] ,

[0021] ,

[0022] in, To find the elements in the i-th row and i-th column of the matrix for the coefficients, To find the elements in the i-th row and (i+2)-th column of the matrix for the coefficients, Find the (i+2)th row and i-th column element of the matrix X for the coefficients, where i = 1, 2, ..., N, and the remaining elements of matrix X are 0. It is the ratio of the highest center frequency of all communication sub-bands to the bandwidth of the communication sub-band;

[0023] S312, perform eigenvalue calculation on the coefficient solution matrix X to obtain the eigenvalue set and the eigenvector set;

[0024] S313, Based on the set of eigenvalues ​​and the set of eigenvectors, a set of eigenpulses is constructed;

[0025] S314: Using the sinusoidal carrier signal corresponding to the center frequency information of each communication device in the communication frequency band set, multiply it with the characteristic pulse group respectively to obtain the data loading waveform of each communication device;

[0026] S315, based on the set of feature vectors and the set of feature values, synchronous coding information is constructed.

[0027] The construction of the feature pulse group based on the feature value set and feature vector set includes:

[0028] S3131, Based on the bandwidth of the communication sub-band, a baseband pulse group is constructed; the baseband pulse group includes N orthogonal baseband pulses; the frequency domain bandwidth of the baseband pulse is the bandwidth of the communication sub-band.

[0029] S3132, using each feature vector of the feature vector set, the baseband pulse group is weighted and summed to obtain the corresponding initial pulse;

[0030] S3133, using all the initial pulses, constructs an initial pulse group;

[0031] S3134, Perform cross-correlation operation on the initial pulse group to obtain the cross-correlation matrix C;

[0032] S3135, Based on the cross-correlation matrix and the initial pulse group, an optimized model is constructed;

[0033] S3136, Solve the optimization model to obtain the coefficient matrix Y;

[0034] S3137, using each column vector of the coefficient matrix Y, the initial pulse group is weighted and summed to obtain the corresponding characteristic pulse;

[0035] S3138 uses all the characteristic pulses to construct a characteristic pulse group.

[0036] The expression for the optimization model is:

[0037]

[0038] ,

[0039] in, Let be the coefficient matrix to be solved. It is the identity matrix. This represents the value of the j-th initial pulse in the initial pulse group at time t. Let Y be the element in the i-th row and j-th column of matrix Y. , represents the j-th column vector of matrix Y.

[0040] The synchronous coding information constructed based on the feature vector set and the feature value set includes:

[0041] S3151, Perform feature calculations on the feature vector set and feature value set to obtain synchronous feature values ​​and synchronous feature sequences;

[0042] The expression for calculating the feature is:

[0043]

[0044]

[0045] in, Let be the synchronization characteristic value of the i-th communication device. Let j be the j-th element of the synchronization feature sequence of the i-th communication device. Let i be the i-th eigenvalue of the eigenvalue set. For the j-th element of the i-th feature vector in the feature vector set, The mean of the set of eigenvalues. Let M be the mean of the i-th feature vector in the feature vector set, and M be the length of the feature vector.

[0046] S3152, using the synchronization feature values ​​and synchronization feature sequences of all communication devices, the synchronization coding information is constructed.

[0047] According to a second aspect of the present invention, an adaptive signal waveform generation device for unmanned ad hoc networks is disclosed, the device comprising:

[0048] Memory containing executable program code;

[0049] A processor coupled to the memory;

[0050] The processor calls the executable program code stored in the memory to execute the adaptive signal waveform generation method for unmanned ad hoc networks.

[0051] In a third aspect, the present invention discloses a computer-storable medium storing computer instructions, which, when invoked by a computer, are used to execute the adaptive signal waveform generation method for unmanned ad hoc networks.

[0052] In a fourth aspect, the present invention discloses an information data processing terminal, which is used to implement the adaptive signal waveform generation method for unmanned ad hoc networks.

[0053] The beneficial effects of this invention are as follows:

[0054] This invention provides an adaptive signal waveform generation method for unmanned ad hoc networks, which has the following significant advantages:

[0055] 1. Low-power design: By adaptively dividing the communication frequency band and designing a dedicated communication waveform for each communication device, each device can communicate within a narrower frequency band, reducing energy loss during signal transmission. Simultaneously, the optimized waveform design further reduces the device's transmit power while maintaining communication quality, effectively extending the battery life of unmanned autonomous networking devices, reducing energy costs, and meeting the stringent low-power requirements of unmanned autonomous networking devices.

[0056] 2. Strong resistance to multi-user interference: This invention utilizes synchronization coding frequency bands and synchronization coding information to design a unique synchronization waveform for each communication device, and then superimposes it with the data loading waveform in the time domain to form a communication waveform with anti-interference capabilities. This design can effectively distinguish the signals of different devices in a multi-user environment, reduce mutual interference between signals, improve signal reception quality, and ensure that the unmanned ad hoc network system can maintain stable communication performance even when high-density devices are connected, greatly enhancing the reliability and availability of the system.

[0057] 3. High Frequency Band Resource Utilization Efficiency: This invention adaptively divides the communication frequency band set and synchronization coding frequency band based on the communication frequency band information and the number of communication devices in the unmanned ad hoc network, and allocates a communication sub-band and center frequency information to each communication device. This adaptive frequency band allocation method can flexibly adjust the frequency band allocation according to actual needs, making full use of limited frequency band resources, avoiding waste of frequency band resources, improving the overall utilization efficiency of frequency band resources, and thus enhancing the communication capacity and performance of the unmanned ad hoc network system. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention. Detailed Implementation

[0059] To better understand the content of this invention, an embodiment is provided here.

[0060] Figure 1 This is a flowchart illustrating the implementation of the method of the present invention.

[0061] In a first aspect, this invention discloses an adaptive signal waveform generation method for unmanned ad hoc networks, comprising:

[0062] S1, obtain the total communication frequency band information and the number of communication devices of the unmanned self-organizing network;

[0063] S2, the total communication frequency band information is divided to obtain a communication frequency band set and a synchronization coding frequency band; the communication frequency band set includes the communication sub-band and center frequency information of each communication device;

[0064] S3, based on the communication frequency band set and synchronous coding frequency band, designs the communication waveform of each communication device to obtain the communication waveform of each communication device.

[0065] The process of dividing the total communication frequency band information to obtain a communication frequency band set and a synchronization coding frequency band includes:

[0066] S21, using a preset scaling factor, the total communication frequency band information is divided into a communication frequency band and a synchronization coding frequency band; the ratio of the bandwidth of the communication frequency band to the bandwidth of the synchronization coding frequency band is the scaling factor.

[0067] Specifically, the total communication frequency band information is represented as [fl, fh], the range of the communication frequency band is [fl, fl + (fh - fl) × i1 / (i1 + 1)], the remaining frequency band is the synchronization coding frequency band, and i1 is the scaling factor;

[0068] S22, the communication frequency band is evenly divided into N communication sub-bands, each communication sub-band is the communication sub-band of each communication device, and the center frequency of each sub-band is the center frequency information of each communication device;

[0069] The communication waveform of each communication device is designed based on the communication frequency band set and synchronous coding frequency band, resulting in the following:

[0070] S31, based on the communication frequency band set, design the data loading waveform for each communication device to obtain the data loading waveform and synchronization coding information for each communication device;

[0071] S32, based on the synchronization coding frequency band and the synchronization coding information of each communication device, the synchronization waveform of each communication device is designed to obtain the synchronization waveform of each communication device;

[0072] S33, Time-domain superposition of the data loading waveform and synchronization waveform of each communication device to obtain the communication waveform of each communication device;

[0073] The design of the data loading waveform for each communication device based on the communication frequency band set yields the data loading waveform and synchronization coding information for each communication device, including:

[0074] S311, based on the number of communication sub-bands and the ratio of the highest center frequency of all communication sub-bands to the bandwidth of the communication sub-bands, the coefficient solution matrix X is constructed;

[0075] The expression for the non-zero elements in the coefficient solution matrix is ​​as follows:

[0076] ,

[0077] ,

[0078] ,

[0079] in, To find the elements in the i-th row and i-th column of the matrix for the coefficients, To find the elements in the i-th row and (i+2)-th column of the matrix for the coefficients, Find the (i+2)th row and i-th column element of the matrix X for the coefficients, where i = 1, 2, ..., N, and the remaining elements of matrix X are 0. It is the ratio of the highest center frequency of all communication sub-bands to the bandwidth of the communication sub-band;

[0080] S312, perform eigenvalue calculation on the coefficient solution matrix X to obtain the eigenvalue set and the eigenvector set;

[0081] S313, Based on the set of eigenvalues ​​and the set of eigenvectors, a set of eigenpulses is constructed;

[0082] S314: Using the sinusoidal carrier signal corresponding to the center frequency information of each communication device in the communication frequency band set, multiply it with the characteristic pulse group respectively to obtain the data loading waveform of each communication device;

[0083] S315, Based on the set of feature vectors and the set of feature values, synchronous coding information is constructed;

[0084] The construction of the feature pulse group based on the feature value set and feature vector set includes:

[0085] S3131, Based on the bandwidth of the communication sub-band, a baseband pulse group is constructed; the baseband pulse group includes N orthogonal baseband pulses; the frequency domain bandwidth of the baseband pulse is the bandwidth of the communication sub-band.

[0086] The baseband pulse group can be an Nth-order Gaussian pulse, Hermite pulse, or wavelet pulse, or any orthogonal function system.

[0087] S3132, using each feature vector of the feature vector set, the baseband pulse group is weighted and summed to obtain the corresponding initial pulse;

[0088] S3133, using all the initial pulses, constructs an initial pulse group;

[0089] S3134, Perform cross-correlation operation on the initial pulse group to obtain the cross-correlation matrix C;

[0090] S3135, Based on the cross-correlation matrix and the initial pulse group, an optimized model is constructed;

[0091] S3136, Solve the optimization model to obtain the coefficient matrix Y;

[0092] S3137, using each column vector of the coefficient matrix Y, the initial pulse group is weighted and summed to obtain the corresponding characteristic pulse;

[0093] S3138 uses all the characteristic pulses to construct a characteristic pulse group.

[0094] This invention provides a wealth of choices and flexible adjustment space for communication waveform design by constructing mathematical models such as coefficient solution matrices and characteristic pulse groups, and by employing various baseband pulse forms such as Gaussian pulses, Hermite pulses, or wavelet pulses. It allows for optimization of waveform design parameters based on different unmanned ad hoc network application scenarios and device characteristics, generating the most suitable communication waveform and further improving the performance and adaptability of unmanned ad hoc network communication systems.

[0095] The elements in the i-th row and j-th column of the cross-correlation matrix C are the cross-correlation values ​​of the i-th and j-th initial pulses in the initial pulse group.

[0096] The expression for the optimization model is:

[0097]

[0098] ,

[0099] in, Let be the coefficient matrix to be solved. It is the identity matrix. This represents the value of the j-th initial pulse in the initial pulse group at time t. Let Y be the element in the i-th row and j-th column of matrix Y. , represents the j-th column vector of matrix Y.

[0100] The synchronous coding information constructed based on the feature vector set and the feature value set includes:

[0101] S3151, Perform feature calculations on the feature vector set and feature value set to obtain synchronous feature values ​​and synchronous feature sequences;

[0102] The expression for calculating the feature is:

[0103]

[0104]

[0105] in, Let be the synchronization characteristic value of the i-th communication device. Let j be the j-th element of the synchronization feature sequence of the i-th communication device. Let i be the i-th eigenvalue of the eigenvalue set. For the j-th element of the i-th feature vector in the feature vector set, The mean of the set of eigenvalues. Let M be the mean of the i-th feature vector in the feature vector set, and M be the length of the feature vector.

[0106] S3152, using the synchronization feature values ​​and synchronization feature sequences of all communication devices, the synchronization coding information is constructed.

[0107] The synchronization waveform of each communication device is designed based on the synchronization coding frequency band and the synchronization coding information of each communication device, resulting in the synchronization waveform of each communication device, including:

[0108] Based on the synchronization coding frequency band and the synchronization characteristic value of each communication device, the initial synchronization waveform of each communication device is obtained.

[0109] By using the synchronization characteristic sequence of each communication device, the initial synchronization waveform of each communication device is amplitude modulated to obtain the synchronization waveform of each communication device.

[0110] The initial synchronization waveform of each communication device is obtained by solving based on the synchronization coding frequency band and the synchronization characteristic value of each communication device, including:

[0111] The synchronization waveform solution model for each communication device is constructed, and its expression is as follows:

[0112] ,

[0113] ,

[0114] Where t is the time variable, For time-shifted variables, The duration of the initial synchronization waveform. Let be the synchronization waveform of the i-th communication device to be solved. It is a bandpass waveform. For synchronous coding frequency bands;

[0115] The synchronization waveform solution model is solved to obtain the initial synchronization waveform of each communication device; the synchronization waveform solution model can be solved by discretizing the model and using numerical methods.

[0116] The synchronization characteristic sequence of each communication device is used to perform amplitude modulation on the initial synchronization waveform of each communication device to obtain the synchronization waveform of each communication device, the expression of which is:

[0117]

[0118] in, Let be the synchronization waveform of the i-th communication device.

[0119]

[0120] The data loading waveform and synchronization waveform of each communication device are superimposed in the time domain to obtain the communication waveform of each communication device within one symbol time. Represented as:

[0121]

[0122]

[0123] in, For the modulation data on the i-th pulse, For the i-th characteristic pulse group of the communication device, For the center frequency information of the communication equipment, data loading waveform With synchronous waveform It is time-domain parallel and frequency-domain separated. This is the time sequence number.

[0124] According to a second aspect of the present invention, an adaptive signal waveform generation device for unmanned ad hoc networks is disclosed, the device comprising:

[0125] Memory containing executable program code;

[0126] A processor coupled to the memory;

[0127] The processor calls the executable program code stored in the memory to execute the adaptive signal waveform generation method for unmanned ad hoc networks.

[0128] In a third aspect, the present invention discloses a computer-storable medium storing computer instructions, which, when invoked by a computer, are used to execute the adaptive signal waveform generation method for unmanned ad hoc networks.

[0129] In a fourth aspect, the present invention discloses an information data processing terminal, which is used to implement the adaptive signal waveform generation method for unmanned ad hoc networks.

[0130] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. An adaptive signal waveform generation method for unmanned ad hoc networks, characterized in that, include: S1, obtain the total communication frequency band information and the number of communication devices of the unmanned self-organizing network; S2, the total communication frequency band information is divided to obtain a communication frequency band set and a synchronization coding frequency band; the communication frequency band set includes the communication sub-frequency band and center frequency information of each communication device in the unmanned ad hoc network; S3, based on the communication frequency band set and synchronization coding frequency band, designs the communication waveform for each communication device, resulting in the communication waveform for each device, including: S31, based on the communication frequency band set, designs the data loading waveform for each communication device to obtain the data loading waveform and synchronization coding information for each communication device, including: S311, based on the number of communication sub-bands and the ratio of the highest center frequency of all communication sub-bands to the bandwidth of the communication sub-bands, the coefficient solution matrix X is constructed; The expression for the non-zero elements in the coefficient solution matrix is ​​as follows: ， ， ， in, To find the elements in the i-th row and i-th column of the matrix for the coefficients, To find the elements in the i-th row and (i+2)-th column of the matrix for the coefficients, Find the (i+2)th row and i-th column element of the matrix X for the coefficients, where i = 1, 2, ..., N, and the remaining elements of matrix X are 0. It is the ratio of the highest center frequency of all communication sub-bands to the bandwidth of the communication sub-band; S312, perform eigenvalue calculation on the coefficient solution matrix X to obtain the eigenvalue set and the eigenvector set; S313, Based on the set of eigenvalues ​​and the set of eigenvectors, a set of eigenpulses is constructed; S314: Using the sinusoidal carrier signal corresponding to the center frequency information of each communication device in the communication frequency band set, multiply it with the characteristic pulse group respectively to obtain the data loading waveform of each communication device; S315, Based on the set of feature vectors and the set of feature values, synchronous coding information is constructed; S32, based on the synchronization coding frequency band and the synchronization coding information of each communication device, the synchronization waveform of each communication device is designed to obtain the synchronization waveform of each communication device; S33, the data loading waveform and synchronization waveform of each communication device are superimposed in the time domain to obtain the communication waveform of each communication device.

2. The adaptive signal waveform generation method for unmanned ad hoc networks as described in claim 1, characterized in that, The process of dividing the total communication frequency band information to obtain a communication frequency band set and a synchronization coding frequency band includes: S21, using a preset scaling factor, the total communication frequency band information is divided into a communication frequency band and a synchronization coding frequency band; the ratio of the bandwidth of the communication frequency band to the bandwidth of the synchronization coding frequency band is the scaling factor. S22, the communication frequency band is evenly divided into N communication sub-bands. Each communication sub-band is the communication sub-band of each communication device in the unmanned self-organizing network. The center frequency of each sub-band is the center frequency information of each communication device.

3. The adaptive signal waveform generation method for unmanned ad hoc networks as described in claim 1, characterized in that, The construction of the feature pulse group based on the feature value set and feature vector set includes: S3131, Based on the bandwidth of the communication sub-band, a baseband pulse group is constructed; the baseband pulse group includes N orthogonal baseband pulses; the frequency domain bandwidth of the baseband pulse is the bandwidth of the communication sub-band. S3132, using each feature vector of the feature vector set, the baseband pulse group is weighted and summed to obtain the corresponding initial pulse; S3133, using all the initial pulses, constructs an initial pulse group; S3134, Perform cross-correlation operation on the initial pulse group to obtain the cross-correlation matrix. C ; S3135, Based on the cross-correlation matrix and the initial pulse group, an optimized model is constructed; S3136, Solve the optimization model to obtain the coefficient matrix Y; S3137, using each column vector of the coefficient matrix Y, the initial pulse group is weighted and summed to obtain the corresponding characteristic pulse; S3138 uses all the characteristic pulses to construct a characteristic pulse group.

4. The adaptive signal waveform generation method for unmanned ad hoc networks as described in claim 3, characterized in that, The expression for the optimization model is: ， , in, Y Let be the coefficient matrix to be solved. E It is the identity matrix. This represents the value of the j-th initial pulse in the initial pulse group at time t. Let Y be the element in the i-th row and j-th column of matrix Y. , represents the j-th column vector of matrix Y.

5. The adaptive signal waveform generation method for unmanned ad hoc networks as described in claim 3, characterized in that, The synchronous coding information constructed based on the feature vector set and the feature value set includes: S3151, Perform feature calculations on the feature vector set and feature value set to obtain synchronous feature values ​​and synchronous feature sequences; The expression for calculating the feature is: , , in, Let be the synchronization characteristic value of the i-th communication device. Let j be the j-th element of the synchronization feature sequence of the i-th communication device. Let i be the i-th eigenvalue of the eigenvalue set. For the j-th element of the i-th feature vector in the feature vector set, The mean of the set of eigenvalues. Let M be the mean of the i-th feature vector in the feature vector set, and M be the length of the feature vector. S3152, using the synchronization feature values ​​and synchronization feature sequences of all communication devices, the synchronization coding information is constructed.

6. An adaptive signal waveform generation device for unmanned ad hoc networks, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the adaptive signal waveform generation method for unmanned ad hoc networks as described in any one of claims 1 to 5.

7. A computer-storable medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked by the computer, are used to execute the adaptive signal waveform generation method for unmanned ad hoc networks as described in any one of claims 1 to 5.

8. An information data processing terminal, characterized in that, The information data processing terminal is used to implement the adaptive signal waveform generation method for unmanned self-organizing networks as described in any one of claims 1 to 5.

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