Frequency preference method and apparatus based on spectrum sensing

Abstract

The application discloses a frequency optimization method and device based on spectrum sensing, and belongs to the field of wireless communication, which comprises the following steps: firstly, starting the spectrum sensing function before the beginning of the current receiving time slot; continuously performing frequency configuration during the spectrum sensing process; after the frequency configuration, sampling and mixing the radio frequency signal corresponding to the current frequency, and performing low-pass filtering to output the baseband signal; calculating the average power of the baseband signal in the time domain, calculating the fast Fourier transform in the frequency domain, and then taking the modulus and searching the peak value to complete the spectrum sensing calculation in the time-frequency two dimensions; finally, according to the sensing calculation result of the time-frequency, configuring the subsequent frequency, and performing the frequency optimization according to the optimization strategy to output the final optimized frequency. The application does not occupy the system bandwidth, does not depend on the prediction and cooperation among nodes, and only needs the receiving node to complete the synchronous pulse spectrum sensing and frequency optimization with a low calculation amount, so that the frequency domain interference is avoided, and the synchronization capability is improved.

Description

Technical Field

[0001] This invention relates to the field of wireless communication, and more specifically, to a frequency optimization method and apparatus based on spectrum sensing. Background Technology

[0002] Frequency hopping technology is a technique that transmits signals on multiple predefined frequencies. Compared with fixed-frequency technology, it has stronger anti-interference capabilities, better spectrum utilization, and better resistance to multipath fading, so it is widely used in the field of wireless communication.

[0003] Traditional frequency-hopping communication systems typically configure multiple frequency-hopping synchronization pulses in the frame structure design to improve the anti-interference capability of the synchronization segment and the synchronization probability of the receiving node. When the transmitting node transmits synchronization information through a predefined frequency, traditional frequency-hopping receiving nodes cannot adjust their receiving frequency according to changes in channel quality or environment; they can only wait in the order of the frequency-hopping pattern, which has obvious limitations. Spectrum sensing technology, by detecting the current spectrum status in real time, can detect abnormal spectrum activity and acquire spectrum status, and can better adapt to the rapidly changing wireless environment. When applied to frequency-hopping synchronization pulse reception, spectrum sensing can help receiving nodes avoid interfering frequencies and complete the received signal synchronization at the preferred frequency, improving the node's synchronization capability. However, the architecture and processing logic of existing spectrum sensing technologies are often too complex in real-time operation, requiring the system to have core capabilities such as detection, classification, prediction, and collaboration. Real-time detection and classification consume significant computing resources, while prediction and collaboration require nodes to exchange sensing results, increasing communication overhead and processing latency. If complex algorithms such as deep learning are used for spectrum sensing, higher-performance processors or dedicated chips are needed to provide computing power, resulting in high hardware costs. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a frequency optimization method and apparatus based on spectrum sensing. This method does not occupy system bandwidth, does not rely on inter-node prediction and cooperation, and only requires the receiving node to complete the synchronization pulse spectrum sensing and frequency optimization with a low amount of computation, so as to avoid frequency domain interference and improve synchronization capability.

[0005] The objective of this invention is achieved through the following solution:

[0006] A frequency optimization device based on spectrum sensing includes a time synchronization acquisition module, a frequency configuration module, a frequency conversion sampling module, a spectrum sensing module, and a sensing decision module;

[0007] The time synchronization acquisition module is used to acquire system time information and start the spectrum sensing function before the current receiving time slot begins;

[0008] The frequency configuration module is used to configure the synchronization pulse frequency during the spectrum sensing process;

[0009] The frequency conversion sampling module is used to complete the sampling, mixing and low-pass filtering of the radio frequency signal corresponding to the current frequency after the frequency is configured, and output the baseband signal.

[0010] The spectrum sensing module is used to calculate the average power of the baseband signal in the time domain, calculate the modulus and retrieve the peak value after calculating the fast Fourier transform in the frequency domain, and complete the spectrum sensing calculation in both time and frequency dimensions.

[0011] The perception decision module is used to control the frequency configuration of the frequency configuration module based on the time-frequency perception calculation results, optimize the frequency according to the optimization strategy, and output the final optimized frequency.

[0012] A frequency optimization method based on spectrum sensing, using the apparatus described above, includes the following steps:

[0013] S1, activate the spectrum sensing function before the start of the current reception time slot;

[0014] S2 continuously configures frequencies during the spectrum sensing process;

[0015] S3, after the frequency is configured, performs sampling, mixing, and low-pass filtering on the RF signal corresponding to the current frequency, and outputs the baseband signal. ;

[0016] S4, for baseband signal The average power is calculated in the time domain, and the modulus and peak value are retrieved after the Fast Fourier Transform (FFT) is calculated in the frequency domain, thus completing the spectrum sensing calculation in both time and frequency dimensions.

[0017] S5 configures subsequent frequencies based on the time-frequency sensing calculation results, performs frequency optimization according to the optimization strategy, and outputs the final optimized frequency.

[0018] Furthermore, the continuous frequency configuration during the spectrum sensing process specifically includes the following sub-steps:

[0019] Suppose that a burst frame contains N synchronization pulses. The spectrum sensing of this node begins before the start of the current time slot. At the end of the propagation protection segment of the previous frame, the frequency of synchronization pulse 1 is configured.

[0020] Furthermore, the step of sampling, mixing, and low-pass filtering the radio frequency signal corresponding to the current frequency to output a baseband signal specifically includes the following sub-steps:

[0021] Sampling is performed at the current frequency, and the sampled signal is down-mixed and filtered to obtain L I and Q baseband signals. The complex form of the baseband signal is expressed as follows: , Represents the imaginary unit. This represents the l-th I-band signal. This represents the l-th Q-band signal, where I indicates in-phase and Q indicates quadrature.

[0022] Furthermore, the baseband signal The process involves calculating the average power in the time domain, performing a Fast Fourier Transform (FFT) in the frequency domain, determining the modulus, and retrieving the peak value. This process includes the following sub-steps:

[0023] The average power of L complex baseband signals is calculated in the time domain to obtain the average power value. Calculate the FFT in the frequency domain for L I and Q baseband signals to obtain an L-point complex signal in the frequency domain. , For natural index, Continue to calculate the modulus of L frequency domain complex signals to obtain For L frequency domain modulus signals Perform a score search to find the maximum peak value. .

[0024] Furthermore, the step of configuring subsequent frequencies based on the time-frequency sensing calculation results, performing frequency optimization according to the optimization strategy, and outputting the final optimized frequency specifically includes the following sub-steps:

[0025] Average power value Maximum peak value in frequency domain Each with the set power threshold Frequency domain peak threshold Compare, if and If the frequency is considered to be free of interference, then frequency optimization ends, and the current frequency is output as the interference-free frequency. Otherwise, if interference is considered to exist at the current frequency, the average power value of the current frequency is stored. With the maximum peak value in the frequency domain At the same time, the frequency control switches to the next frequency point, and steps S3, S4 and S5 are repeated.

[0026] Furthermore, if no interference-free frequency is found even after all N synchronization pulse frequencies have been switched, then the average power value of the remaining frequencies (excluding the first frequency) is fused with the square of the frequency domain peak value to obtain the fusion parameter. Then apply all fusion parameters The frequency optimization process is then completed by comparing and selecting the frequency output with the smallest fusion parameters.

[0027] The beneficial effects of this invention include:

[0028] (1) This invention does not occupy additional system bandwidth. Specifically, this invention utilizes the propagation protection period at the end of the previous frame time slot in the frequency hopping system to control the frequency of the first synchronization pulse. After entering the current time slot, it determines whether to control the subsequent frequencies for spectrum sensing based on the result of each sensing decision. This fully utilizes the quiet period of the propagation protection segment and the differences in the frequencies of the synchronization pulses. Without the system having to separately divide the spectrum sensing period, a spectrum environment free from system node emission pollution can be obtained, saving system bandwidth.

[0029] (2) This invention does not rely on inter-node prediction, cooperation, or upper-layer protocol assistance. Specifically, this invention only requires a single node to perform unidirectional sampling calculation at the receiving time slot signal processing level to complete the synchronization pulse spectrum sensing and frequency optimization. It does not require the transmission of sensing information between nodes, the coordination of other nodes, or the participation of upper-layer protocols, which can greatly simplify the system complexity.

[0030] (3) The present invention has low computational complexity, fast processing speed, and good real-time performance. Specifically, the present invention only needs to perform basic power calculation, FFT calculation and peak retrieval calculation on a small number of sampled signals in the time and frequency domains when sensing the spectrum. It does not rely on complex algorithms such as deep learning and has low computational requirements for the system. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 A diagram of the frame format for a frequency hopping system with multiple synchronization pulses;

[0033] Figure 2 This is a structural block diagram of the device according to an embodiment of the present invention;

[0034] Figure 3 This is a flowchart of the method according to an embodiment of the present invention;

[0035] Figure 4 This is a timing diagram of frequency control in the method of this embodiment of the invention;

[0036] In the diagram, there are: synchronization segment 101, data segment 102, propagation protection segment 103, time synchronization acquisition module 201, frequency configuration module 202, frequency conversion sampling module 203, spectrum sensing module 204, and sensing decision module 205. Detailed Implementation

[0037] All features disclosed in all embodiments of this specification, or steps in all methods or processes implied in the disclosure, may be combined and / or extended or replaced in any way, except for mutually exclusive features and / or steps.

[0038] As a first aspect of the present invention, a frequency optimization device based on spectrum sensing is provided, such as... Figure 2 As shown, it includes: a time synchronization acquisition module 201, which acquires system time information and starts the spectrum sensing function before the current receiving time slot begins; a frequency configuration module 202, which completes the configuration of the synchronization pulse frequency during the spectrum sensing process; and a frequency conversion sampling module 203, which, after the frequency is configured, completes the sampling, mixing, and low-pass filtering of the radio frequency signal corresponding to the current frequency, and outputs the baseband signal. ; Spectrum sensing module 204, for baseband signals The average power is calculated in the time domain, and the modulus and peak value are obtained after FFT calculation in the frequency domain to complete the spectrum perception calculation in both time and frequency dimensions. The perception decision module 205 controls the frequency configuration module 202 to configure the frequency according to the perception calculation results of time and frequency, performs frequency optimization according to the optimization strategy, and outputs the final optimized frequency.

[0039] As a second aspect of the present invention, a frequency selection method based on spectrum sensing is provided, particularly relating to a method for frequency selection using spectrum sensing in a frequency hopping communication system, specifically including the following steps:

[0040] First, the spectrum sensing function is activated before the start of the current receiving time slot; frequency configuration is continuously performed during the spectrum sensing process; once the frequency is configured, the RF signal corresponding to the current frequency is sampled, mixed, and low-pass filtered to output the baseband signal. For baseband signals The average power is calculated in the time domain, and the modulus and peak value are obtained after FFT calculation in the frequency domain to complete the spectrum sensing calculation in both time and frequency dimensions. Finally, based on the sensing calculation results of time and frequency, the subsequent frequencies are configured, and the frequency is optimized according to the optimization strategy to output the final optimized frequency.

[0041] In other embodiments, based on the methods of the above embodiments, a frequency optimization method based on spectrum sensing is also provided, including the following:

[0042] exist Figure 1 In the burst frequency hopping system data frame format shown, to improve the anti-interference performance of synchronization segment 101, the burst frame contains N synchronization pulses, each with a different frequency, predetermined by the frequency hopping pattern. The receiver selects one of the synchronization pulses to complete signal acquisition, timing synchronization, and frequency and phase offset estimation. Then, it demodulates and decodes the signal in data segment 102 to recover the source data. 103 is the propagation protection segment. (See reference...) Figure 3 and Figure 4This embodiment specifically proposes a frequency optimization method based on spectrum sensing, which is implemented through the following steps:

[0043] Step A: The spectrum sensing of this node begins before the start of the current time slot, at the end of the propagation protection of the previous frame, and the frequency of synchronization pulse 1 is configured.

[0044] Step B: After configuration, sample at the current frequency and down-mix and filter the sampled signal to obtain L I and Q baseband signals. The complex form of the baseband signal can be expressed as: , Represents the imaginary unit. This represents the l-th I-band signal. This represents the l-th Q-baseband signal, where I indicates in-phase and Q indicates quadrature.

[0045] Step C: Calculate the average power of the L complex baseband signals in the time domain to obtain the average power value. Calculate the FFT in the frequency domain for L I and Q baseband signals to obtain an L-point complex signal in the frequency domain. In the above formula For natural index, Continue to calculate the modulus of L frequency domain complex signals to obtain For L frequency domain modulus signals Perform a score search to find the maximum peak value. ;

[0046] Step D: Average power value Maximum peak value in frequency domain Each with the set power threshold Frequency domain peak threshold Compare, if and If the frequency selection is successful, then the frequency optimization is considered to be free of interference, the frequency selection process ends, and the current frequency is output. Otherwise, if interference is found at the current frequency, the average power value of the current frequency is stored. With the maximum peak value in the frequency domain Meanwhile, the frequency configuration module 202 switches to the next frequency point and repeats the above steps B, C and D.

[0047] Step E: If no interference-free frequency is found after all N synchronization pulse frequencies have been switched, then the average power value of the remaining frequencies (excluding the first frequency) is fused with the square of the frequency domain peak value to obtain the fusion parameter. Then apply all fusion parameters The frequency optimization process is then completed by comparing and selecting the frequency output with the smallest fusion parameters.

[0048] The units described in the embodiments of the present invention can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0049] According to one aspect of the present invention, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described above.

[0050] In another aspect, embodiments of the present invention also provide a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

Claims

1. A frequency optimization device based on spectrum sensing, characterized in that, It includes a time synchronization acquisition module, a frequency configuration module, a frequency conversion sampling module, a spectrum sensing module, and a sensing decision module; The time synchronization acquisition module is used to acquire system time information and start the spectrum sensing function before the current receiving time slot begins; The frequency configuration module is used to configure the synchronization pulse frequency during the spectrum sensing process; The frequency conversion sampling module is used to complete the sampling, mixing and low-pass filtering of the radio frequency signal corresponding to the current frequency after the frequency is configured, and output the baseband signal. The spectrum sensing module is used to calculate the average power of the baseband signal in the time domain, calculate the modulus and retrieve the peak value after calculating the fast Fourier transform in the frequency domain, and complete the spectrum sensing calculation in both time and frequency dimensions. The perception decision module is used to control the frequency configuration of the frequency configuration module based on the time-frequency perception calculation results, perform frequency optimization according to the optimization strategy, and output the final optimized frequency; and to set the average power value Maximum peak value in frequency domain Each with the set power threshold Frequency domain peak threshold Compare, if and If the frequency is considered to be free of interference, then frequency optimization ends, and the current frequency is output as the interference-free frequency. Otherwise, if interference is considered to exist at the current frequency, the average power value of the current frequency is stored. With the maximum peak value in the frequency domain Simultaneously, the frequency control switches to the next frequency point, and the frequency conversion sampling module, spectrum sensing module, and sensing decision module are repeatedly executed.

2. A frequency optimization method based on spectrum sensing, characterized in that, The frequency optimization device based on spectrum sensing as described in claim 1 includes the following steps: S1, activate the spectrum sensing function before the start of the current reception time slot; S2 continuously configures frequencies during the spectrum sensing process; S3, after the frequency is configured, performs sampling, mixing, and low-pass filtering on the RF signal corresponding to the current frequency, and outputs the baseband signal. ; S4, for baseband signals The average power is calculated in the time domain, and the modulus and peak value are retrieved after calculating the Fast Fourier Transform (FFT) in the frequency domain, thus completing the spectrum sensing calculation in both time and frequency dimensions. S5, based on the time-frequency sensing calculation results, configures subsequent frequencies, performs frequency optimization according to the optimization strategy, and outputs the final optimized frequency; the average power value is... Maximum peak value in frequency domain Each with the set power threshold Frequency domain peak threshold Compare, if and If the frequency is considered to be free of interference, then frequency optimization ends, and the current frequency is output as the interference-free frequency. Otherwise, if interference is considered to exist at the current frequency, the average power value of the current frequency is stored. With the maximum peak value in the frequency domain At the same time, the frequency control switches to the next frequency point, and steps S3, S4 and S5 are repeated.

3. The frequency optimization method based on spectrum sensing according to claim 2, characterized in that, The continuous frequency configuration during spectrum sensing specifically includes the following sub-steps: Suppose that a burst frame contains N synchronization pulses. The spectrum sensing of this node begins before the start of the current time slot. At the end of the propagation protection segment of the previous frame, the frequency of synchronization pulse 1 is configured.

4. The frequency optimization method based on spectrum sensing according to claim 3, characterized in that, The step of sampling, mixing, and low-pass filtering the radio frequency signal corresponding to the current frequency to output a baseband signal specifically includes the following sub-steps: Sampling is performed at the current frequency, and the sampled signal is down-mixed and filtered to obtain L I and Q baseband signals. The complex form of the baseband signal is expressed as follows: , Represents the imaginary unit. This represents the l-th I-band signal. This represents the l-th Q-band signal, where I indicates in-phase and Q indicates quadrature.

5. The frequency optimization method based on spectrum sensing according to claim 4, characterized in that, The baseband signal The process involves calculating the average power in the time domain, performing a Fast Fourier Transform (FFT) in the frequency domain, determining the modulus, and retrieving the peak value. This process includes the following sub-steps: The average power of L complex baseband signals is calculated in the time domain to obtain the average power value. Calculate the FFT in the frequency domain for L I and Q baseband signals to obtain an L-point complex signal in the frequency domain. , For the natural index Continue to calculate the modulus of L complex signals in the frequency domain to obtain... For L frequency domain modulus signals Perform a score search to find the maximum peak value. .

6. The frequency optimization method based on spectrum sensing according to claim 2, characterized in that, If no interference-free frequency is found after all N synchronization pulse frequencies have been switched, then the average power value of the remaining frequencies (excluding the first frequency) is fused with the square of the frequency domain peak value to obtain the fusion parameter. Then apply all fusion parameters The frequency optimization process is then completed by comparing and selecting the frequency output with the smallest fusion parameters.

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