A multi-frequency transmission method and system for wireless signals based on a compression algorithm

Abstract

The present invention discloses a multi-frequency transmission method and system for wireless signals based on a compression algorithm, which relates to the field of wireless communication technologies. It includes dividing multi-frequency wireless signals into a high-frequency signal band and a low-frequency signal band according to frequency characteristics to obtain a signal group to be processed; performing signal amplitude analysis on the signal group to be processed by using adaptive threshold detection, generating an amplitude feature matrix, dividing compression levels, selecting a wavelet basis function, and performing wavelet transform on the high-frequency signal band and the low-frequency signal band respectively to obtain a set of transform coefficients; dividing the set of transform coefficients into data segments to be transmitted according to a preset length, and allocating channel identification codes and check codes to the data segments to be transmitted; allocating the data segments to be transmitted to different frequency bands according to the frequency division multiplexing rule, and setting a guard bandwidth between adjacent frequency bands to complete multi-frequency parallel transmission. Through the technical solution combining adaptive compression and intelligent transmission, the present invention not only improves the utilization efficiency of spectrum resources but also ensures the reliability of transmission quality.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and particularly to a multi-frequency wireless signal transmission method and system based on a compression algorithm. Background Art

[0002] Traditional wireless signal transmission methods mainly use fixed bandwidth allocation and a single compression algorithm for processing. This approach is difficult to adapt to complex and changing channel environments. In recent years, to improve spectrum utilization efficiency, researchers have proposed various signal compression methods based on wavelet transform, which achieve adaptive compression through the analysis of signal characteristics. However, existing compression transmission technologies often adopt a unified compression strategy and do not fully consider the characteristic differences of signals in different frequency bands. At the same time, during multi-frequency parallel transmission, due to the lack of an effective frequency band protection mechanism, the problem of inter-band crosstalk significantly affects the transmission quality, and existing channel allocation schemes lack the ability of dynamic optimization and are difficult to cope with the real-time changes of channel states.

[0003] Currently, multi-frequency wireless signal transmission technology still faces many challenges in practical applications. First, traditional signal compression algorithms often use fixed wavelet basis functions and cannot adaptively select according to signal characteristics, resulting in unsatisfactory compression effects. Second, existing signal characteristic analysis methods are mainly based on static thresholds and are difficult to adapt to the dynamic changes of signal strength and noise levels. Third, during multi-frequency parallel transmission, due to the lack of accurate channel quality assessment and dynamic scheduling mechanisms, the utilization efficiency of spectrum resources is low. Finally, existing frequency band protection schemes generally use fixed protection bandwidths, which can neither effectively suppress inter-band interference nor cause waste of spectrum resources.

[0004] To address the above problems, the present invention provides a multi-frequency wireless signal transmission method based on a compression algorithm, which belongs to the field of wireless communication technologies. The present invention effectively solves the technical problems in the prior art, such as low signal compression efficiency, low frequency band utilization rate, and poor anti-interference ability, through adaptive threshold detection and differential compression strategies, combined with dynamic frequency band allocation and protection mechanisms. Summary of the Invention

[0005] In view of the problems existing in the existing multi-frequency wireless signal transmission technology, such as poor adaptability of the compression algorithm, low utilization efficiency of frequency band resources, and insufficient anti-interference ability, the present invention is proposed.

[0006] Therefore, the problems to be solved by the present invention are how to achieve adaptive compression processing according to signal characteristics, how to improve the utilization efficiency of spectrum resources, and how to effectively suppress inter-band interference during multi-frequency parallel transmission.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a multi-frequency transmission method for wireless signals based on a compression algorithm, which includes dividing the acquired multi-frequency wireless signals into a high-frequency signal band and a low-frequency signal band according to frequency characteristics to obtain a signal group to be processed; performing signal amplitude analysis on the signal group to be processed by using adaptive threshold detection to generate an amplitude feature matrix, and dividing compression levels based on the amplitude feature matrix; selecting wavelet basis functions according to the compression levels, and performing wavelet transforms on the high-frequency signal band and the low-frequency signal band respectively to obtain a set of transform coefficients; dividing the set of transform coefficients into data segments to be transmitted according to a preset length, and allocating channel identification codes and check codes to the data segments to be transmitted; and allocating the data segments to be transmitted to different frequency bands according to frequency division multiplexing rules, and setting a protection bandwidth between adjacent frequency bands to complete multi-frequency parallel transmission.

[0009] As a preferred solution of the multi-frequency transmission method for wireless signals based on a compression algorithm according to the present invention, the steps of allocating the data segments to be transmitted to different frequency bands according to frequency division multiplexing rules, setting a protection bandwidth between adjacent frequency bands, and completing multi-frequency parallel transmission include: constructing a frequency band resource pool based on the data segments to be transmitted, where the frequency band resource pool includes the bandwidth, center frequency, and channel state information of available frequency bands; evaluating the transmission quality of frequency bands according to channel measurement data to generate a frequency band quality score table, and grading the frequency bands; calculating the mutual interference degree between adjacent frequency bands, and adaptively setting the width of the protection bandwidth according to the interference degree, where no data is transmitted within the protection bandwidth; establishing a frequency band scheduler according to the priority and delay requirements of the data segments to be transmitted, mapping the data segments to be transmitted to frequency bands, and monitoring the data transmission rate of the frequency bands; and when a decrease in transmission performance is detected, starting a frequency band switching mechanism to adjust the protection bandwidth and transmission parameters in real time through a feedback control mechanism.

[0010] As a preferred solution of the multi-frequency transmission method for wireless signals based on a compression algorithm according to the present invention, the method for obtaining the data segments to be transmitted is as follows: establishing a data segmentation buffer, where the data segmentation buffer includes a main data area and a frame header area; the main data area is used to store transform coefficients; the frame header area is used to store control information; determining an optimal segmentation length according to the channel bandwidth characteristics, and sequentially splitting the set of transform coefficients according to the optimal segmentation length to generate a number of data segments to be transmitted; constructing a channel identification code generator, where the channel identification code includes a frequency band index, a time slot number, and a priority flag, and allocating a unique channel identification code to each data segment to be transmitted according to transmission requirements; performing cyclic redundancy check coding on each data segment to be transmitted to generate a check code sequence; inserting the channel identification code and the check code sequence into the frame header area of the data segment to be transmitted; and establishing a data segment mapping table to record the numbers, lengths, and check information of the data segments to be transmitted.

[0011] As a preferred embodiment of the wireless signal multi-frequency transmission method based on a compression algorithm according to the present invention, wherein: the method for obtaining the set of transform coefficients includes: establishing a wavelet basis function library; the wavelet basis function library includes an orthogonal wavelet basis function group and a biorthogonal wavelet basis function group; the orthogonal wavelet basis function group is used to process the high-frequency signal band; the biorthogonal wavelet basis function group is used to process the low-frequency signal band; selecting corresponding decomposition levels according to different compression levels; selecting wavelet basis functions in the orthogonal wavelet basis function group to decompose the high-frequency signal band to generate high-frequency sub-band coefficients; selecting wavelet basis functions in the biorthogonal wavelet basis function group to decompose the low-frequency signal band to generate low-frequency sub-band coefficients; performing energy concentration analysis on the high-frequency sub-band coefficients and the low-frequency sub-band coefficients, screening and retaining the main coefficients; sorting and arranging the retained main coefficients to form a set of transform coefficients.

[0012] As a preferred embodiment of the wireless signal multi-frequency transmission method based on a compression algorithm according to the present invention, wherein: the method for dividing the compression level of the amplitude feature matrix is to establish a sliding sampling window for the signal group to be processed, wherein a main detection area and a secondary detection area are set in the sliding sampling window, and the main detection area is located at the center position of the sliding sampling window; establishing an amplitude cumulative histogram in the main detection area, and calculating the statistical distribution characteristics of the signal amplitude through the amplitude cumulative histogram; calculating the background noise level by using the signal data in the secondary detection area, and setting the background noise level as the initial threshold reference; dynamically adjusting the initial threshold reference according to the statistical distribution characteristics to obtain an adaptive detection threshold; using the adaptive detection threshold as a demarcation point to perform multi-level division on the amplitudes of the signal group to be processed to generate an amplitude feature matrix; based on the distribution density of the signal amplitude X in the amplitude feature matrix, dividing the signal into a first compression level, a second compression level, and a third compression level.

[0013] As a preferred embodiment of the multi-frequency wireless signal transmission method based on a compression algorithm according to the present invention, the method for obtaining the signal group to be processed is as follows: receiving multi-frequency wireless signals through an antenna array, where the antenna array includes a plurality of omnidirectional antenna units that are evenly distributed in a ring; amplifying and filtering the multi-frequency wireless signals through a radio frequency front-end circuit to obtain filtered signals; using a band-pass filter bank to divide the frequency bands of the filtered signals, where signals higher than the center frequency point are assigned to the high-frequency signal band, and signals lower than the center frequency point are assigned to the low-frequency signal band; sampling the high-frequency signal band and the low-frequency signal band respectively, and setting buffer register groups respectively, where the buffer register group includes a main buffer area and an auxiliary buffer area; setting a timestamp counter in the main buffer area, and the timestamp counter synchronously counts during the sampling processes of the high-frequency signal band and the low-frequency signal band; based on the count value of the timestamp counter, writing the sampling data of the high-frequency signal band and the sampling data of the low-frequency signal band into the corresponding main buffer areas respectively; calculating the phase difference between the high-frequency signal band and the low-frequency signal band through a phase correction module, and writing the phase difference as an offset into the auxiliary buffer area; performing interpolation compensation on the data in the main buffer area according to the offset in the auxiliary buffer area to generate a signal group to be processed with aligned time series.

[0014] As a preferred embodiment of the multi-frequency wireless signal transmission method based on a compression algorithm according to the present invention, the specific formula for the adaptive detection threshold T is as follows:

[0015] T = T0 × (1 + α × V) × (1 + β × S) × γ;

[0016] Where, T0 is the initial threshold reference, α is the adjustment factor of the coefficient of variation, V is the coefficient of variation of the signal amplitude in the main detection area, reflecting the degree of signal fluctuation, β is the adjustment factor of the skewness coefficient, S is the skewness coefficient of the cumulative histogram of the amplitudes in the main detection area, and γ is the safety margin coefficient.

[0017] Second aspect, an embodiment of the present invention provides a multi-frequency wireless signal transmission system based on a compression algorithm, which includes: an acquisition module, configured to divide the acquired multi-frequency wireless signal into a high-frequency signal band and a low-frequency signal band according to frequency characteristics to obtain a signal group to be processed; a division module, configured to perform signal amplitude analysis on the signal group to be processed by using adaptive threshold detection, generate an amplitude feature matrix, and divide compression levels based on the amplitude feature matrix; a transformation module, configured to select a wavelet basis function according to the compression level, and perform wavelet transformation on the high-frequency signal band and the low-frequency signal band respectively to obtain a set of transformation coefficients; an allocation module, configured to divide the set of transformation coefficients into data segments to be transmitted according to a preset length, and allocate a channel identification code and a check code to the data segments to be transmitted; a transmission module, configured to allocate the data segments to be transmitted to different frequency bands according to the frequency division multiplexing rule, and set a protection bandwidth between adjacent frequency bands to complete multi-frequency parallel transmission.

[0018] Third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and: when the computer program instructions are executed by the processor, the steps of the multi-frequency wireless signal transmission method based on the compression algorithm as described in the first aspect of the present invention are implemented.

[0019] Fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and: when the computer program instructions are executed by the processor, the steps of the multi-frequency wireless signal transmission method based on the compression algorithm as described in the first aspect of the present invention are implemented.

[0020] The beneficial effects of the present invention are as follows: By dividing the multi-frequency wireless signal into high and low frequency bands, and combining the adaptive threshold detection technology, the present invention realizes the accurate extraction of signal features and compression grading, and then adopts a differential wavelet transformation processing strategy to perform targeted compression on signals in different frequency bands. In the data transmission link, through channel coding and dynamic protection bandwidth mechanism, anti-interference and error control in the multi-frequency parallel transmission process are realized. This technical solution combining adaptive compression and intelligent transmission not only improves the utilization efficiency of spectrum resources, but also ensures the reliability of transmission quality. Description of the Drawings

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts. Among them:

[0022] Figure 1 It is a flowchart of the multi-frequency wireless signal transmission method based on the compression algorithm for Embodiment 1.

[0023] Figure 2 This is a simulation result diagram of the wireless signal multi-frequency transmission method based on the compression algorithm in Example 2. DETAILED DESCRIPTION

[0024] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0025] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0027] Example 1

[0028] Reference Figure 1 , which is the first embodiment of the present invention, and provides a wireless signal multi-frequency transmission method based on a compression algorithm, comprising:

[0029] S1: Divide the acquired multi-frequency wireless signal into a high-frequency signal band and a low-frequency signal band according to the frequency characteristics to obtain a signal group to be processed.

[0030] Specifically, the method for obtaining the signal group to be processed is to receive multi-frequency wireless signals through an antenna array, the antenna array includes a number of omnidirectional antenna units, and the antenna units are evenly distributed in a ring shape; the multi-frequency wireless signals are amplified and filtered by a radio frequency front-end circuit to obtain filtered signals; and the filtered signals are divided into frequency bands using a bandpass filter group, wherein signals higher than the center frequency are divided into a high-frequency signal band, and signals lower than the center frequency are divided into a low-frequency signal band.

[0031] Furthermore, the high-frequency signal band and the low-frequency signal band are sampled respectively, and cache register groups are set respectively, wherein the cache register groups include a main cache area and an auxiliary cache area; a timestamp counter is set in the main cache area, and the timestamp counter counts synchronously with the sampling process of the high-frequency signal band and the low-frequency signal band.

[0032] Further, based on the count value of the timestamp counter, the sampled data of the high-frequency signal band and the sampled data of the low-frequency signal band are respectively written into the corresponding main buffer; the phase difference between the high-frequency signal band and the low-frequency signal band is calculated by the phase correction module, and the phase difference is written into the auxiliary buffer as an offset; the specific formula for the phase difference is as follows:

[0033] ΔΦ=arctan(Q H / I H )-arctan(Q L / I L );

[0034] Where, ΔΦ is the phase difference between the high-frequency signal band and the low-frequency signal band, Q H and I H are respectively the quadrature component and the in-phase component of the high-frequency signal, Q L and I L are respectively the quadrature component and the in-phase component of the low-frequency signal.

[0035] Specifically, interpolation compensation is performed on the data in the main buffer according to the offset in the auxiliary buffer to generate a group of signals to be processed after timing alignment.

[0036] S2: Perform signal amplitude analysis on the group of signals to be processed by using adaptive threshold detection, generate an amplitude feature matrix, and divide the compression level based on the amplitude feature matrix.

[0037] Specifically, the method for dividing the compression level of the amplitude feature matrix is to establish a sliding sampling window for the group of signals to be processed; establish an amplitude cumulative histogram in the main detection area, and calculate the statistical distribution characteristics of the signal amplitude through the amplitude cumulative histogram; calculate the background noise level by using the signal data in the secondary detection area, and set the background noise level as the initial threshold reference.

[0038] It should be noted that a main detection area and a secondary detection area are set in the sliding sampling window, and the main detection area is located at the center position of the sliding sampling window.

[0039] Further, the initial threshold reference is dynamically adjusted according to the statistical distribution characteristics to obtain an adaptive detection threshold, and the specific formula is as follows:

[0040] T=T0×(1+α×V)×(1+β×S)×γ;

[0041] Where, T0 is the initial threshold reference, α is the adjustment factor of the coefficient of variation, V is the coefficient of variation of the signal amplitude in the main detection area, reflecting the signal fluctuation degree, β is the adjustment factor of the skewness coefficient, S is the skewness coefficient of the amplitude cumulative histogram in the main detection area, and γ is the safety margin coefficient.

[0042] Further, when the signal amplitude X > 2T, the signal is classified into the first compression level; when T < signal amplitude X ≤ 2T, the signal is classified into the second compression level; when 0.5T < signal amplitude X ≤ T, the signal is classified into the third compression level; when the signal amplitude X ≤ 0.5T, the signal is regarded as noise component and can be directly ignored in the compression process.

[0043] Specifically, using the adaptive detection threshold as the demarcation point, the amplitudes of the signal group to be processed are divided into multiple levels to generate an amplitude feature matrix; based on the distribution density of the signal amplitude X in the amplitude feature matrix, the signal is divided into the first compression level, the second compression level, and the third compression level.

[0044] S3: Select wavelet basis functions according to the compression level, and perform wavelet transforms on the high-frequency signal band and the low-frequency signal band respectively to obtain a set of transform coefficients.

[0045] Further, the method for obtaining the set of transform coefficients includes: establishing a wavelet basis function library; the wavelet basis function library includes an orthogonal wavelet basis function group and a biorthogonal wavelet basis function group; the orthogonal wavelet basis function group is used to process the high-frequency signal band; the biorthogonal wavelet basis function group is used to process the low-frequency signal band; the specific formulas of the orthogonal wavelet basis function group are as follows:

[0046] Ψ H (t) = {Ψ H,j,k (t) = 2j / 2Ψ H (2jt - k)};

[0047] φ H (t) = {φ H,j,k (t) = 2j / 2φ H (2jt - k)}

[0048] Among them, Ψ H (t) is the mother wavelet function for high-frequency signal processing, φ H (t) is the scaling function for high-frequency signal processing, Ψ H,j,k (t) is the wavelet function at the j-scale and k-displacement, φ H,j,k (t) is the scaling function at the j-scale and k-displacement, t is the time variable, j is the scale parameter representing the stretching degree of the wavelet function, and k is the translation parameter representing the displacement amount of the wavelet function.

[0049] Even further, the specific formulas of the biorthogonal wavelet basis function group are as follows:

[0050]

[0051] Among them, Ψ L (t) is the mother wavelet function for low-frequency signal processing, φ L$(t)$ is a scaling function for low-frequency signal processing. is the analysis wavelet function at scale $j$ and displacement $k$. is the analysis scaling function at scale $j$ and displacement $k$, $\Psi$ L,j,k $(t)$ is the wavelet function at scale $j$ and displacement $k$, $\varphi$ L,j,k $(t)$ is the scaling function at scale $j$ and displacement $k$.

[0052] Specifically, the corresponding decomposition level is selected according to the compression level; for the high-frequency signal band, the wavelet basis function in the orthogonal wavelet basis function group is selected for decomposition to generate high-frequency sub-band coefficients; for the low-frequency signal band, the wavelet basis function in the biorthogonal wavelet basis function group is selected for decomposition to generate low-frequency sub-band coefficients; the energy concentration degree of the high-frequency sub-band coefficients and the low-frequency sub-band coefficients is analyzed, and the main coefficients are screened and retained.

[0053] Further, the retained main coefficients are sorted and organized to form a set of transform coefficients.

[0054] S4: The set of transform coefficients is divided into data segments to be transmitted according to a preset length, and a channel identification code and a check code are assigned to the data segments to be transmitted.

[0055] Specifically, the method for obtaining the data segments to be transmitted is to establish a data segmentation buffer, where the data segmentation buffer includes a main data area and a frame header area; the main data area is used to store the transform coefficients; the frame header area is used to store control information.

[0056] Further, the optimal segmentation length is determined according to the channel bandwidth characteristics, and the set of transform coefficients is segmented in the order of the optimal segmentation length to generate several data segments to be transmitted; a channel identification code generator is constructed, and the channel identification code includes a frequency band index, a time slot number, and a priority flag, and a unique channel identification code is assigned to each data segment to be transmitted according to the transmission requirements; a cyclic redundancy check coding is performed on each data segment to be transmitted to generate a check code sequence; the channel identification code and the check code sequence are inserted into the frame header area of the data segment to be transmitted; a data segment mapping table is established to record the number, length, and check information of the data segments to be transmitted.

[0057] Even further, the specific application scenarios of the data segment mapping table are as follows: in the pre-transmission retrieval scenario, the storage location and attribute information of each data segment are quickly located through the data segment mapping table for transmission scheduling optimization; when transmission congestion occurs, the data segments are dynamically scheduled and the transmission order is rearranged according to the priority information recorded in the data segment mapping table; in the transmission process monitoring scenario, the transmission status flags in the data segment mapping table are updated in real time, including statuses such as to be sent, already sent, and already confirmed; the transmission delay and the number of retransmissions of each data segment are tracked through the data segment mapping table for evaluating the link quality.

[0058] Specifically, in the error handling scenario, when the receiving end detects a data verification error, it quickly locates the error data segment according to the verification information in the data segment mapping table; and uses the original coding information recorded in the data segment mapping table to achieve selective retransmission or data recovery.

[0059] Furthermore, in the recombination and recovery scenario, the receiving end correctly recombines the scattered received data segments according to the sequence information and association relationship provided by the data segment mapping table; and verifies the data integrity through the data segment mapping table to ensure that all data segments are correctly received.

[0060] S5: Allocate the to-be-transmitted data segments to different frequency bands according to the frequency division multiplexing rule, and set a guard bandwidth between adjacent frequency bands to complete multi-frequency parallel transmission.

[0061] Specifically, based on the to-be-transmitted data segments, a frequency band resource pool is constructed, where the frequency band resource pool contains the bandwidth, center frequency, and channel state information of available frequency bands; evaluate the transmission quality of the frequency bands according to the channel measurement data, generate a frequency band quality score table, and classify these frequency bands; calculate the mutual interference degree between adjacent frequency bands, and adaptively set the width of the guard bandwidth according to the interference degree, where no data is transmitted within the guard bandwidth.

[0062] Furthermore, a frequency band scheduler is established according to the priority and delay requirements of the to-be-transmitted data segments, map the to-be-transmitted data segments to the frequency bands, and monitor the data transmission rate of the frequency bands.

[0063] Even further, when a decrease in transmission performance is detected, a frequency band switching mechanism is started, and the guard bandwidth and transmission parameters are adjusted in real time through a feedback control mechanism.

[0064] Furthermore, this embodiment also provides a multi-frequency transmission system for wireless signals based on a compression algorithm, including: an acquisition module for dividing the acquired multi-frequency wireless signals into high-frequency signal bands and low-frequency signal bands according to frequency characteristics to obtain a to-be-processed signal group; a division module for performing signal amplitude analysis on the to-be-processed signal group by using adaptive threshold detection to generate an amplitude feature matrix, and dividing the compression level based on the amplitude feature matrix; a transformation module for selecting wavelet basis functions according to the compression level, and performing wavelet transformation on the high-frequency signal band and the low-frequency signal band respectively to obtain a set of transformation coefficients; an allocation module for dividing the set of transformation coefficients into to-be-transmitted data segments according to a preset length, and allocating channel identification codes and check codes to the to-be-transmitted data segments; a transmission module for allocating the to-be-transmitted data segments to different frequency bands according to the frequency division multiplexing rule, and setting a guard bandwidth between adjacent frequency bands to complete multi-frequency parallel transmission.

[0065] This embodiment also provides a computer device, which is applicable to the case of the multi-frequency transmission method of wireless signals based on a compression algorithm, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the multi-frequency transmission method of wireless signals based on the compression algorithm proposed in the above embodiment.

[0066] The computer device may be a terminal. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be achieved through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device may be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the outer shell of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0067] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by a processor, the following steps are implemented: dividing the acquired multi-frequency wireless signal into a high-frequency signal band and a low-frequency signal band according to the frequency characteristics to obtain a signal group to be processed; performing signal amplitude analysis on the signal group to be processed by using adaptive threshold detection to generate an amplitude feature matrix, and dividing the compression level based on the amplitude feature matrix; selecting a wavelet basis function according to the compression level, and performing wavelet transform on the high-frequency signal band and the low-frequency signal band respectively to obtain a set of transform coefficients; dividing the set of transform coefficients into data segments to be transmitted according to a preset length, and allocating a channel identification code and a check code to the data segments to be transmitted; allocating the data segments to be transmitted to different frequency bands according to the frequency division multiplexing rule, and setting a protection bandwidth between adjacent frequency bands to complete multi-frequency parallel transmission.

[0068] In summary, the present invention divides the multi-frequency wireless signal into high and low frequency bands, combines the adaptive threshold detection technology to accurately extract the signal features and compress the levels, and then adopts a differential wavelet transform processing strategy to perform targeted compression on signals in different frequency bands. In the data transmission link, through the channel coding and dynamic protection bandwidth mechanism, anti-interference and error control in the multi-frequency parallel transmission process are realized. This technical solution combining adaptive compression and intelligent transmission not only improves the utilization efficiency of spectrum resources but also ensures the reliability of transmission quality.

[0069] Embodiment 2

[0070] Referring to Figure 2 , which is the second embodiment of the present invention. This embodiment provides a multi-frequency wireless signal transmission method based on a compression algorithm. To verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0071] Specifically, in this experiment, an experimental system constructed by the USRP X310 software radio platform is selected. This platform is equipped with a dual-channel transceiver, and the sampling rate is set to 100 MHz. The antenna array uses 8 omnidirectional antenna elements, which are evenly distributed in a circle with a radius of 25 cm. The experiment is carried out in an anechoic chamber, and the ambient temperature is maintained at 23±2°C, and the relative humidity is controlled at 45%±5%.

[0072] Furthermore, the signal source uses an R&S SMW200A vector signal generator to generate multi-frequency test signals, and the frequency range covers 700 MHz - 6 GHz. The test signals include 15 groups of sinusoidal modulation signals with different bandwidths, and the signal-to-noise ratio ranges from -5 dB to 15 dB. The RF front-end uses an AD9361 RF transceiver, configured with a low-noise amplifier AD8347, and the gain is set to 20 dB. The bandpass filter bank uses an 8th-order Butterworth filter, and the cut-off frequencies are located at 2.4 GHz and 5.8 GHz respectively.

[0073] Even further, in the signal processing section, adaptive threshold detection is performed on the received signal; the window length of the main detection area is set to 1024 points, the secondary detection area is set to 256 points, and the sliding step is 128 points; real-time amplitude cumulative histogram calculation is implemented through FPGA, and 256 quantization levels are used.

[0074] Specifically, in the wavelet basis function library, the db4 wavelet basis function is selected for the high-frequency signal band, and the sym5 wavelet basis function is selected for the low-frequency signal band. According to different compression levels, the decomposition levels are set to 3 layers, 4 layers, and 5 layers respectively. The amplitude threshold of the first compression level is set to 0.8 Vpp, the second compression level is 0.5 Vpp, and the third compression level is 0.3 Vpp. The energy concentration threshold of the transform coefficients is set to 95%.

[0075] Furthermore, the data segmentation buffer is configured with 4MB of SDRAM, including a main data area of 3.5MB and a frame header area of 0.5MB. According to the channel characteristics, the optimal segmentation length is determined to be 2048 bytes. The channel identification code adopts a 12-bit coding scheme, including a 4-bit band index, a 6-bit time slot number, and a 2-bit priority flag. The check code adopts the CRC-16 algorithm. The band resource pool covers the available frequency bands in the range of 2.4GHz - 5.8GHz and is divided into 24 sub-bands. The guard bandwidth is adaptively adjusted according to the interference level, with an initial value set to 10% of the sub-band bandwidth and a maximum of 25%. The band quality score uses a 100-point system, comprehensively considering three indicators: signal-to-noise ratio, bit error rate, and delay jitter.

[0076] Furthermore, the simulation experiment results of the multi-frequency wireless signal transmission method based on the compression algorithm are as Figure 2 shown. Figure 2 The solid line in the figure represents the performance curve of the method of the present invention, and the dashed line represents the performance curve of the prior art. The abscissa represents the signal load, with the unit of Mbps; the ordinate represents the transmission performance index, expressed as a percentage. It can be seen from the simulation results that in the low-load range (0 - 50Mbps), the performance of the method of the present invention is comparable to that of the prior art, and the trends of the two curves are close. As the load increases, the advantages of the method of the present invention gradually emerge. In the medium-load range (50 - 100Mbps), the performance curve of the method of the present invention maintains a steady upward trend, while the performance of the prior art begins to decline significantly. When the system enters the high-load range (100 - 150Mbps), the method of the present invention can still maintain a high transmission performance, and the transmission performance index remains above 75%; in contrast, the performance of the prior art drops sharply, and the transmission performance index drops below 50%.

[0077] Specifically, at a maximum load of 150Mbps, the transmission performance index of the method of the present invention is approximately 80%, while that of the prior art is only 40%. This indicates that the method of the present invention has improved the transmission efficiency by approximately 100% compared to the prior art. This significant performance improvement is mainly due to the adaptive compression algorithm and the optimized frequency division multiplexing mechanism adopted by the present invention, effectively solving the performance bottleneck problem of traditional methods in high-load situations. The experimental results show that the method of the present invention not only significantly improves the transmission efficiency of the system but also ensures the stability of the transmission performance. This has important practical value for actual application scenarios that require processing large-capacity data transmission.

[0078] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A wireless signal multi-frequency transmission method based on a compression algorithm, characterized in that: include, Dividing the acquired multi-frequency wireless signals into a high-frequency signal band and a low-frequency signal band according to the frequency characteristics to obtain a signal group to be processed; Performing signal amplitude analysis on the signal group to be processed by using adaptive threshold detection to generate an amplitude feature matrix, and dividing the compression level based on the amplitude feature matrix; Selecting a wavelet basis function according to the compression level, performing wavelet transform on the high-frequency signal band and the low-frequency signal band respectively, to obtain a transform coefficient set; Dividing the transform coefficient set into data segments to be transmitted according to a preset length, and allocating a channel identification code and a check code to the data segments to be transmitted; Allocating the data segments to be transmitted to different frequency bands according to frequency division multiplexing rules, setting a protection bandwidth between adjacent frequency bands, and completing multi-frequency parallel transmission; The method for obtaining the data segment to be transmitted is: Establishing a data segmentation buffer, wherein the data segmentation buffer includes a main data area and a frame header area; the main data area is used to store transformation coefficients; and the frame header area is used to store control information; Determine an optimal segment length according to the channel bandwidth characteristics, divide the transform coefficient set in order according to the optimal segment length, and generate a plurality of data segments to be transmitted; Constructing a channel identification code generator, wherein the channel identification code includes a frequency band index, a time slot number and a priority tag, and assigning a unique channel identification code to each of the data segments to be transmitted according to transmission requirements; Performing cyclic redundancy check encoding on each of the data segments to be transmitted to generate a check code sequence; Inserting the channel identification code and the check code sequence into the frame header area of ​​the data segment to be transmitted; Establish a data segment mapping table to record the number, length and check information of the data segment to be transmitted; The method for obtaining a transform coefficient set comprises: Establishing a wavelet basis function library; the wavelet basis function library includes an orthogonal wavelet basis function group and a biorthogonal wavelet basis function group; the orthogonal wavelet basis function group is used to process the high-frequency signal band; the biorthogonal wavelet basis function group is used to process the low-frequency signal band; Select the corresponding number of decomposition layers according to the compression level; Decomposing the high-frequency signal band by selecting a wavelet basis function from the orthogonal wavelet basis function group to generate high-frequency sub-band coefficients; Decomposing the low-frequency signal band by selecting a wavelet basis function from the biorthogonal wavelet basis function group to generate low-frequency sub-band coefficients; Performing energy concentration analysis on the high-frequency sub-band coefficients and the low-frequency sub-band coefficients, and screening and retaining main coefficients; The retained main coefficients are sorted and organized to form a transformation coefficient set.

2. The method for multi-frequency transmission of wireless signals based on a compression algorithm as claimed in claim 1, characterized in that: Allocating the data segments to be transmitted to different frequency bands according to the frequency division multiplexing rule, setting a protection bandwidth between adjacent frequency bands, and completing multi-frequency parallel transmission, including: Based on the data segment to be transmitted, a frequency band resource pool is constructed, wherein the frequency band resource pool contains bandwidth, center frequency and channel state information of an available frequency band; Evaluate the transmission quality of the frequency band according to the channel measurement data, generate a frequency band quality score table, and grade the frequency band; Calculating the mutual interference degree between adjacent frequency bands, and adaptively setting the width of the protection bandwidth according to the interference degree, wherein no data is transmitted within the protection bandwidth; Establishing a frequency band scheduler according to the priority and delay requirements of the data segments to be transmitted, mapping the data segments to be transmitted to the frequency bands, and monitoring the data transmission rate of the frequency bands; When a degradation in transmission performance is detected, the frequency band switching mechanism is activated, and the protection bandwidth and transmission parameters are adjusted in real time through a feedback control mechanism.

3. The method for multi-frequency transmission of wireless signals based on a compression algorithm as claimed in claim 1, characterized in that: The method of dividing the compression level by the amplitude characteristic matrix is: Establishing a sliding sampling window for the signal group to be processed, wherein a main detection area and a secondary detection area are set in the sliding sampling window, and the main detection area is located at the center of the sliding sampling window; Establishing an amplitude accumulation histogram in the main detection area, and calculating the statistical distribution characteristics of the signal amplitude through the amplitude accumulation histogram; Calculating a background noise level using the signal data of the secondary detection area, and setting the background noise level as an initial threshold reference; Dynamically adjust the initial threshold reference according to the statistical distribution characteristics to obtain an adaptive detection threshold; Using the adaptive detection threshold as a dividing point, dividing the amplitude of the signal group to be processed into multiple levels to generate an amplitude feature matrix; Based on the distribution density of the signal amplitude X in the amplitude feature matrix, the signal is divided into a first compression level, a second compression level and a third compression level.

4. The method for multi-frequency transmission of wireless signals based on a compression algorithm as claimed in claim 3, characterized in that: The method for obtaining the signal group to be processed is: Receiving multi-frequency wireless signals through an antenna array, wherein the antenna array includes a plurality of omnidirectional antenna units, and the antenna units are evenly distributed in a ring shape; Amplifying and filtering the multi-frequency wireless signal through a radio frequency front-end circuit to obtain a filtered signal; Using a bandpass filter group to divide the filtered signal into frequency bands, wherein signals higher than the center frequency point are divided into a high-frequency signal band, and signals lower than the center frequency point are divided into a low-frequency signal band; The high-frequency signal band and the low-frequency signal band are sampled respectively, and cache register groups are set respectively, wherein the cache register groups include a main cache area and an auxiliary cache area; A timestamp counter is set in the main buffer area, and the timestamp counter counts synchronously with the sampling process of the high-frequency signal band and the low-frequency signal band; Based on the count value of the timestamp counter, the sampled data of the high-frequency signal band and the sampled data of the low-frequency signal band are respectively written into the corresponding main buffer area; Calculating a phase difference between the high-frequency signal band and the low-frequency signal band through a phase correction module, and writing the phase difference as an offset into the auxiliary buffer area; Interpolation compensation is performed on the data in the main buffer area according to the offset in the auxiliary buffer area to generate a signal group to be processed after timing alignment.

5. The method for multi-frequency transmission of wireless signals based on compression algorithm as claimed in claim 3, characterized in that: The adaptive detection threshold The specific formula is as follows: ； in, is the initial threshold reference, is the adjustment factor of the coefficient of variation, The coefficient of variation of the signal amplitude in the main detection area reflects the degree of signal fluctuation. is the adjustment factor of the skewness coefficient, is the skewness coefficient of the amplitude cumulative histogram of the main detection area, is the safety margin factor.

6. A wireless signal multi-frequency transmission system based on a compression algorithm, based on the wireless signal multi-frequency transmission method based on a compression algorithm according to any one of claims 1 to 5, characterized in that: include, An acquisition module, used to divide the acquired multi-frequency wireless signal into a high-frequency signal band and a low-frequency signal band according to the frequency characteristics, to obtain a signal group to be processed; A division module, used for performing signal amplitude analysis on the signal group to be processed by using adaptive threshold detection, generating an amplitude feature matrix, and dividing the compression level based on the amplitude feature matrix; A transformation module, configured to select a wavelet basis function according to the compression level, and perform wavelet transformation on the high-frequency signal band and the low-frequency signal band respectively to obtain a transformation coefficient set; an allocation module, configured to divide the transform coefficient set into data segments to be transmitted according to a preset length, and allocate a channel identification code and a check code to the data segments to be transmitted; The transmission module is used to distribute the data segments to be transmitted to different frequency bands according to the frequency division multiplexing rules, set the protection bandwidth between adjacent frequency bands, and complete multi-frequency parallel transmission.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the wireless signal multi-frequency transmission method based on compression algorithm described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the wireless signal multi-frequency transmission method based on a compression algorithm described in any one of claims 1 to 5 are implemented.

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