Batch scattering parameter compression method and batch scattering parameter decompression method

Abstract

This application provides a batch scattering parameter compression method and a batch scattering parameter decompression method. The method includes: parsing the original scattering parameter file to extract the N-port scattering matrix and structural parameters for each frequency point; determining first frequency domain coefficients based on the N-port scattering matrix; dividing the first frequency domain coefficients by order to determine first template coefficients and first residual coefficients; quantizing the first template coefficients and first residual coefficients using a quantization function to obtain scattering quantization parameters; and packaging the scattering quantization parameters and the structural parameters to obtain a compressed file corresponding to the original scattering parameter file. Through the above implementation, the scattering file can be compressed into a smaller file while better protecting its physical consistency and batch consistency.

Description

Technical Field

[0001] This application relates to the field of data processing, and more specifically, to a method for batch scattering parameter compression and a method for batch scattering parameter decompression. Background Technology

[0002] In wafer-level production testing, if batch wafer testing is required, the following technical problems arise: the amount of data to be processed is enormous, such as the numerous measurement points per chip, resulting in large files of raw scattering parameters. This leads to a large data processing load for the testing system. Traditional file compression algorithms (such as ZIP and RAR) are insufficient in compression efficiency. Summary of the Invention

[0003] The purpose of this application is to provide a batch scattering parameter compression method and a batch scattering parameter decompression method, which can compress scattering files into smaller files while better protecting their physical consistency and batch consistency.

[0004] In a first aspect, the present invention provides a batch scattering parameter compression method, comprising: parsing an original scattering parameter file to extract an N-port scattering matrix and structural parameters for each frequency point; determining a first frequency domain coefficient based on the N-port scattering matrix; dividing the first frequency domain coefficient into orders to determine a first template coefficient and a first residual coefficient; quantizing the first template coefficient and the first residual coefficient using a quantization function to obtain scattering quantization parameters; and packaging the scattering quantization parameters and the structural parameters to obtain a compressed file corresponding to the original scattering parameter file.

[0005] In the above implementation, by parsing the frequency domain coefficients in the original scattering parameter file and using quantization-based processing, the overall data length can be reduced. Furthermore, the quantized data obtained through quantization processing can better preserve the important information in the original scattering parameters, ensuring that the errors in data compression and the scattering parameters obtained after recovery from the compressed file are within a controllable range.

[0006] In an optional implementation, the parameters in the N-port scattering matrix include amplitude parameters and phase parameters; determining the first frequency domain coefficients based on the N-port scattering matrix includes: converting the amplitude parameters and phase parameters in the N-port scattering matrix into complex numbers to obtain a complex scattering matrix; and converting the real part and imaginary part of the complex scattering matrix respectively to determine the first frequency domain coefficients.

[0007] In an optional implementation, the step of transforming the real and imaginary parts of the complex scattering matrix to determine the first frequency domain coefficients includes: performing discrete cosine transform on the real and imaginary parts of the complex scattering matrix to determine the first frequency domain coefficients.

[0008] In the above implementation method, it can be converted into frequency domain coefficients based on conventional matrix operations such as discrete cosine transform. It does not require difficult and complex calculation logic, which makes its implementation relatively easy. The calculation logic can be embedded into other simulation or testing software.

[0009] In an optional implementation, the step of dividing the first frequency domain coefficients by order to determine the first template coefficients and the first residual coefficients includes: dividing the first frequency domain coefficients according to a specified order coefficient, wherein the coefficients in the first frequency domain coefficients at or before the specified order coefficients are determined as the first template coefficients, and the remaining coefficients are determined as the first residual coefficients.

[0010] In the above implementation, the first frequency domain coefficients can be divided into template coefficients and residual coefficients. Different quantization standards can be used for different coefficient parts, which can better preserve the required accuracy of the frequency domain coefficients.

[0011] In an optional implementation, the scattering quantization parameters include template quantization coefficients and residual quantization coefficients; the step of performing quantization processing on the first template coefficients and the first residual coefficients using a quantization function to obtain the scattering quantization parameters includes: applying a first quantization step size to the first template coefficients to perform quantization step size processing on the first template coefficients to obtain template quantization coefficients; and applying a second quantization step size to the first residual coefficients to perform quantization step size processing on the first residual coefficients to obtain residual quantization coefficients.

[0012] In the above implementation, the template coefficients are quantized using the first quantization step size and dead zone coefficient. This allows for a relatively smaller amount of scattering parameter data. While sacrificing a small amount of precision, the key information of the template coefficients and residual coefficients can be well preserved.

[0013] In an optional implementation, the step of using a first quantization step size to process the first template coefficients and obtain template quantization coefficients includes: processing the first template coefficients based on dead zone coefficients to obtain preprocessed template coefficients; and using the first quantization step size to process the preprocessed template coefficients and obtain template quantization coefficients.

[0014] In the above implementation, the residual coefficients are quantized using the second quantization step size and dead zone coefficient. This allows for a relatively smaller amount of scattering parameter data. While sacrificing a small amount of precision, the key information of the template coefficients and residual coefficients can be well preserved.

[0015] In an optional implementation, the step of using a second quantization step size to process the first residual coefficient to obtain a residual quantization coefficient includes: processing the first residual coefficient based on the dead zone coefficient to obtain a preprocessed residual coefficient; and using the second quantization step size to process the preprocessed residual coefficient to obtain a residual quantization coefficient.

[0016] Secondly, the present invention provides a batch scattering parameter decompression method, the batch scattering parameter decompression method comprising: parsing a compressed file to be processed to obtain quantization coefficients and structural parameters; wherein the compressed file to be processed is a file obtained by processing using any one of the batch scattering parameter compression methods described in the foregoing embodiments; performing inverse quantization processing on the quantization coefficients using an inverse quantization function to obtain second template coefficients and second residual coefficients; merging the second template coefficients and the second residual coefficients to obtain second frequency domain coefficients; performing reset processing based on the second frequency domain coefficients to obtain a reset scattering matrix; and regenerating the scattering parameter file based on the reset scattering matrix.

[0017] In an optional implementation, the step of performing reset processing based on the second frequency domain coefficients to obtain a reset scattering matrix includes: performing a discrete cosine inverse transform on the second frequency domain coefficients to obtain a complex scattering sequence; and obtaining a reset scattering matrix based on the complex scattering sequence.

[0018] In an optional implementation, obtaining the reset scattering matrix based on the complex scattering sequence includes: recombining the complex scattering sequence into a set of complex matrices in terms of frequency points; performing reciprocity correction on the complex matrix at each frequency point to obtain a corrected complex matrix; and obtaining the reset scattering matrix by performing singular value decomposition on the corrected complex matrix to constrain all singular values ​​to be less than or equal to a set value.

[0019] In the above implementation, each complex matrix in the complex matrix set is processed using reciprocity correction and singular value decomposition, which can better ensure the physical consistency of the recovered data.

[0020] Thirdly, the present invention provides a testing system, comprising: a probe station and a vector network analyzer; the probe station is used to connect to a device under test; the vector network analyzer is used to apply a high-frequency signal to the device under test and measure the response of the device under test, and to perform the steps in the batch scattering parameter compression method of any one of the foregoing embodiments, or to perform the steps in the batch scattering parameter decompression method of any one of the foregoing embodiments.

[0021] Fourthly, the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the machine-readable instructions are executed by the processor to perform the steps in the batch scattering parameter compression method described in any of the foregoing embodiments, or to perform the steps in the batch scattering parameter decompression method described in any of the foregoing embodiments.

[0022] Fifthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the batch scattering parameter compression method described in any one of the foregoing embodiments, or performs the steps of the batch scattering parameter decompression method described in any one of the foregoing embodiments.

[0023] In a sixth aspect, the present invention provides a computer program product comprising a computer program that, when executed by a processor, implements the batch scattering parameter compression method described in any one of the foregoing embodiments, or implements the batch scattering parameter decompression method described in any one of the foregoing embodiments. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A schematic diagram of the testing system provided in the embodiments of this application;

[0026] Figure 2 A block diagram illustrating an electronic device provided in an embodiment of this application;

[0027] Figure 3 A flowchart of the batch scattering parameter compression method provided in the embodiments of this application;

[0028] Figure 4 A flowchart of a batch scattering parameter decompression method provided in an embodiment of this application. Detailed Implementation

[0029] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0030] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] In wafer-level production testing of silicon photonics and high-speed radio frequency chips, it is necessary to measure the scattering parameters (also known as S-parameters) of multiple ports of silicon photonics and high-speed radio frequency chips over a wide frequency range. Common test systems for S-parameter measurement include probe stations and vector network analyzers. This test system can achieve high-precision, wide-bandwidth S-parameter measurement, but in batch wafer testing, there are the following problems: (1) Each chip has a large number of measurement points, resulting in a large size of the original S-parameter file. Taking a 4-port S-parameter file as an example, using a 67 GHz vector network analyzer, the total size of the original S-parameter file for each wafer is more than 5 GB. (2) The S-parameter similarity between chips within the same wafer is high, and there is a large amount of compressible redundant information. Traditional file compression algorithms (such as ZIP and RAR) cannot fully utilize the physical characteristics of S-parameters, resulting in limited compression efficiency. Therefore, there is currently a lack of an efficient compression coding method that can significantly reduce data volume while ensuring physical consistency and batch consistency of S-parameters.

[0032] Based on the above research, the embodiments of this application can provide a batch scattering parameter compression method, a batch scattering parameter decompression method, and a testing system, which can compress scattering files into smaller files while better protecting their physical consistency and batch consistency.

[0033] To facilitate understanding of this embodiment, the test system for performing the batch scattering parameter compression method and batch scattering parameter decompression method disclosed in this application embodiment will first be introduced.

[0034] like Figure 1 As shown, the test system may include: a probe station 110 and a vector network analyzer 120.

[0035] The probe station 110 is used to connect to the device under test (DUT). The vector network analyzer 120 is used to apply a high-frequency signal to the DUT and measure the response of the DUT.

[0036] The vector network analyzer 120 can be used to perform steps in the batch scattering parameter compression method and the batch scattering parameter decompression method.

[0037] Optionally, the vector network analyzer 120 may include a memory and a processor. The memory may store code required for the tests to be performed by the vector network analyzer 120, and may also store code for implementing a batch scattering parameter compression method and a batch scattering parameter decompression method. The processor may run the code in the memory to perform tests, batch scattering parameter compression methods, and batch scattering parameter decompression methods.

[0038] The batch scattering parameter compression method and batch scattering parameter decompression method disclosed in the embodiments of this application can also be applied to electronic devices with memory and processor for execution.

[0039] like Figure 2 The diagram shown is a block illustration of an electronic device. The electronic device 200 may include a memory 211 and a processor 213. Those skilled in the art will understand that... Figure 2 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device 200. For example, the electronic device 200 may also include components that are more... Figure 2 The more or fewer components shown, or having the same Figure 2 The different configurations shown.

[0040] The memory 211 and processor 213 described above are electrically connected to each other directly or indirectly to enable data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The processor 213 described above is used to execute executable modules stored in the memory.

[0041] The memory 211 can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 211 stores programs, and the processor 213 executes these programs upon receiving execution instructions. The methods executed by the electronic device 200, as defined in any embodiment of this application, can be applied to or implemented by the processor 213.

[0042] The aforementioned processor 213 may be an integrated circuit chip with signal processing capabilities. The processor 213 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a digital signal processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor.

[0043] In this embodiment, the electronic device 200 may run simulation software. This simulation software can obtain scattering parameter files through simulation and can compress the scattering parameter files based on a batch scattering parameter compression method.

[0044] The electronic device 200 in this embodiment can be used to execute various steps in the various methods provided in the embodiments of this application. The implementation process of the batch scattering parameter compression method and the batch scattering parameter decompression method is described in detail below through several embodiments.

[0045] Please see Figure 3 This is a flowchart of a batch scattering parameter compression method provided in an embodiment of this application. The batch scattering parameter compression method provided in this application can be applied to a test system, through which the test system executes the steps of the batch scattering parameter compression method. The batch scattering parameter compression method provided in this application can also be applied to an electronic device, through which the electronic device executes the steps of the batch scattering parameter compression method. The following will describe... Figure 3 The specific process shown will be explained in detail.

[0046] Step 310: Analyze the original scattering parameter file and extract the N-port scattering matrix and structural parameters for each frequency point.

[0047] The raw scattering parameter file can be an SNP file, used to store the S-parameter data of an N-port network, where S represents the S-parameters; N represents the number of ports; and P represents the port.

[0048] For example, the original scattering parameter file can be a TXT format SNP file or a Touchstone format SNP file.

[0049] The raw scattering parameter file can include a header and data blocks. The header stores information such as units and reference impedance, while the data blocks store the scattering parameters at various frequencies. Scattering parameters are a set of parameters used to describe how high-frequency signals are transmitted and reflected in a multi-port network. Scattering parameters describe the scattering behavior of electromagnetic waves when they encounter impedance changes.

[0050] For a two-port network (such as an amplifier, filter, or cable), scattering parameters can include four main components: input reflection coefficient (also known as return loss), which measures how much signal is reflected back from port 1. A lower input reflection coefficient value is better, indicating better matching. Forward transmission coefficient (also known as gain / insertion loss), which measures how much signal is transmitted from port 1 to port 2; for amplifiers, we want it to be greater than 1 (for gain). Backward transmission coefficient (also known as isolation), which measures how much signal is transmitted from port 2 to port 1; a lower back transmission coefficient value is better, indicating higher isolation. Output reflection coefficient, which measures how much signal is reflected back from port 2.

[0051] Scattering parameters are used to analyze and design high-frequency circuits such as amplifiers, filters, mixers, and antennas. Scattering parameters can be measured using a vector network analyzer on a test system.

[0052] Step 320: Determine the first frequency domain coefficients based on the N-port scattering matrix.

[0053] Optionally, a Discrete Cosine Transform (DCT) can be performed on the N-port scattering matrix, thereby decomposing the data in the N-port scattering matrix into a superposition of cosine waves of different frequencies.

[0054] Optionally, a Discrete Fourier Transform (DFT) can be performed on the N-port scattering matrix to determine the first frequency domain coefficients.

[0055] Step 330: Divide the first frequency domain coefficients into orders to determine the first template coefficients and the first residual coefficients.

[0056] For example, the order selected for this order partitioning can be chosen based on the actual required precision. For instance, the order could be chosen as 16.

[0057] Step 340: Quantize the first template coefficients and the first residual coefficients using a quantization function to obtain scattering quantization parameters.

[0058] Optionally, different quantization standards can be used to quantize the first template coefficients and the first residual coefficients. For example, the quantization of the first template coefficients can be achieved using a quantization standard with relatively higher precision, while the quantization of the first residual coefficients can be achieved using a quantization standard with relatively lower precision compared to the first target coefficients.

[0059] Step 350: Package the scattering quantization parameters and structural parameters to obtain a compressed file corresponding to the original scattering parameter file.

[0060] In this embodiment, the scattering quantization parameters and the structural parameters obtained from the previous step 310 are packaged together to obtain the final compressed file.

[0061] Optionally, the scattering quantization parameters and structural parameters can be packaged into a binary byte stream to generate a compressed bitstream file. The compressed bitstream file serves as a compressed version of the original scattering parameter file.

[0062] Of course, to ensure smoother subsequent analysis and better recovery of the original scattering parameter file, some parameters used for compression can also be included in the compressed file during packaging.

[0063] The parameters used in compression may include quantization-related parameters used in the quantization process implemented using a quantization function. The parameters used in compression may also include the order used in dividing the first frequency domain coefficients.

[0064] Through the above steps, the frequency domain coefficients in the original scattering parameter file are first parsed out. The quantization-based processing method can reduce the overall data length. Furthermore, the quantized data can better retain the important information in the original scattering parameters, keeping the errors of data compression and the scattering parameters recovered from the compressed file within a controllable range.

[0065] In this embodiment, the parameters in the N-port scattering matrix described above may include amplitude parameters and phase parameters. Step 320 may include steps 321 and 322.

[0066] Step 321: Convert the amplitude and phase parameters in the N-port scattering matrix into complex representations to obtain the complex scattering matrix.

[0067] For example, an N-port scattering matrix S(f) can be extracted for each frequency point, and the amplitude (dB) and phase (degrees) in the N-port scattering matrix S(f) can be converted into complex form. Each matrix element in the N-port scattering matrix S(f) can be represented as:

[0068] ;

[0069] in, This represents the amplitude of the i-th row and j-th column element in the N-port scattering matrix at the f-th frequency point; This represents the phase of the element in the i-th row and j-th column of the N-port scattering matrix at the f-th frequency point.

[0070] Step 322: Transform the real and imaginary parts of the complex scattering matrix to determine the first frequency domain coefficients.

[0071] Step 322 above may include: performing discrete cosine transforms on the real and imaginary parts of the complex scattering matrix respectively to determine the first frequency domain coefficients.

[0072] Among them, the discrete cosine transform can concentrate signal energy into a few low-frequency coefficients.

[0073] Each element of the complex scattering matrix can be... Arrange them into a sequence according to frequency, and perform discrete cosine transform on the real and imaginary parts respectively to obtain the first frequency domain coefficients of the energy concentration.

[0074] Alternatively, the discrete cosine transform can be performed using the DCT-II transform.

[0075] For example, the first frequency domain coefficient can be expressed as: Where DCT() represents the discrete cosine transform function.

[0076] Optionally, step 330 above may include: dividing the first frequency domain coefficients according to a specified order coefficient, wherein the coefficients at or before the specified order coefficients in the first frequency domain coefficients are determined as first template coefficients, and the remaining coefficients are determined as first residual coefficients.

[0077] The specified order coefficient can be a pre-set value. Depending on the actual usage requirements, for example, if higher precision is needed, the specified order coefficient can be set to a relatively large value, while if lower precision is needed, it can be set to a relatively small value. This application's embodiments are not limited to the specific value of the specified order coefficient.

[0078] Taking a specified order coefficient denoted by r as an example, the first r order coefficients of the sequence are truncated to form the first template coefficients. The remaining part is used as the first template coefficient. , can be represented as: ;

[0079] in, This represents the first frequency domain coefficient.

[0080] In this embodiment, the scattering quantization parameters may include template quantization coefficients and residual quantization coefficients. Step 340 may include steps 341 and 342.

[0081] Step 341: Apply the first quantization step size to the first template coefficients and perform quantization step size processing to obtain template quantization coefficients.

[0082] Optionally, the first template coefficients are processed based on the dead zone coefficients to obtain preprocessed template coefficients; the preprocessed template coefficients are then processed using the first quantization step size to obtain template quantization coefficients.

[0083] Step 342: Use the second quantization step size to process the first residual coefficient to obtain the residual quantization coefficient.

[0084] Optionally, the first residual coefficient is processed based on the dead zone coefficient to obtain the preprocessed residual coefficient; the preprocessed residual coefficient is then processed using the second quantization step size to obtain the residual quantization coefficient.

[0085] In this embodiment, the values ​​of the first quantization step size and the second quantization step size can be the same or different. The first quantization step size and the second quantization step size can be selected based on actual accuracy requirements, and this embodiment is not limited to the specific values ​​of the first quantization step size and the second quantization step size.

[0086] For example, the first quantization step size used for quantizing the first template coefficients can be selected to a relatively small value to ensure that the compressed first template coefficients can better maintain high accuracy.

[0087] For example, the value of the second quantization step size can be set to a larger value than the first quantization step size to ensure that the compressed first residual coefficients occupy less space. Under this logic, since the quantization step size of the first template coefficients is relatively smaller, better accuracy can be guaranteed.

[0088] The quantization step size parameter can be categorized as follows: First quantization step size Second quantization step And the dead zone coefficient d ensures that the errors in amplitude and phase are both within an adjustable range.

[0089] Small signals can be suppressed by setting a dead-time coefficient. Specifically, quantization can be implemented using the function Quantize(), which performs sign-preserving uniform quantization on the input data.

[0090] The processing of the first template coefficients can be determined using the following formula:

[0091] ;

[0092] The first residual coefficient can be determined using the following formula:

[0093] ;

[0094] Here, step represents the variable for quantization step size; deadzone represents the variable for dead zone coefficient.

[0095] By quantizing the template coefficients and residual coefficients using the quantization step size and dead zone coefficients mentioned above, the amount of scattering parameter data can be relatively smaller. While sacrificing a small amount of precision, the key information of the template coefficients and residual coefficients can be well preserved.

[0096] In this embodiment, in order to further reduce the data size, the obtained residual quantization coefficients can be further compressed.

[0097] Optionally, the residual quantization coefficients can be compressed using entropy coding compression.

[0098] The following example illustrates the compression of batch scattering parameters based on the steps of the aforementioned batch scattering parameter compression method. Taking a scattering parameter file with 4 ports and 1000 frequency points as an example, a single scattering parameter file is approximately 260KB in size. After compression using the aforementioned batch scattering parameter compression method, with the specified order coefficient value being 16 (r=16), only approximately 512 template coefficients and approximately 2000 residual coefficients need to be saved. After quantization processing, the template coefficient portion occupies approximately 0.5KB, and the residual coefficient portion, after entropy encoding compression, is approximately 1.4KB, for a total storage size of approximately 1.9KB. The scattering parameter test data per wafer is reduced from approximately 5GB of original files to approximately 30MB.

[0099] As can be seen from the above examples, the method provided in this application can significantly reduce the storage space required by the test system.

[0100] Please see Figure 4 This is a flowchart of a batch scattering parameter decompression method provided in an embodiment of this application. The batch scattering parameter decompression method provided in this application can be applied to a test system, through which the test system executes the steps of the batch scattering parameter decompression method. The batch scattering parameter decompression method provided in this application can also be applied to an electronic device, through which the electronic device executes the steps of the batch scattering parameter decompression method. The following will describe... Figure 4 The specific process shown will be explained in detail.

[0101] Step 410: The compressed file to be processed is parsed to obtain quantization coefficients and structural parameters.

[0102] The compressed file to be processed is the file obtained by using the batch scattering parameter compression method described above.

[0103] Step 420: Apply the inverse quantization function to the quantization coefficients to perform inverse quantization processing, and obtain the second template coefficients and the second residual coefficients.

[0104] For example, the inverse quantization function can be Dequantize().

[0105] The inverse quantization step size used for inverse quantization of the quantization coefficients can be the same as the quantization step size used in obtaining the compressed file to be processed. Taking the first quantization step size as... The second quantization step size is For example, in the case of inverse quantization, it can also be used and .

[0106] Based on this, the inverse quantization of the template coefficients in the quantization coefficients can be expressed by the following formula:

[0107] ;

[0108] The inverse quantization of the residual coefficients in the quantization coefficients can be expressed by the following formula:

[0109] .

[0110] Step 430: Combine the second template coefficients and the second residual coefficients to obtain the second frequency domain coefficients.

[0111] The second template coefficients and the second residual coefficients are combined into a second frequency domain coefficient matrix, which can be the complete DCT coefficient matrix: .

[0112] Step 440: Perform reset processing based on the second frequency domain coefficients to obtain the reset scattering matrix.

[0113] Optionally, step 440 may include steps 441 and 442.

[0114] Step 441: Perform inverse discrete cosine transform on the second frequency domain coefficients to obtain the complex scattering sequence.

[0115] Alternatively, the inverse discrete cosine transform can be the IDCT-II transform.

[0116] The complex scattering sequence can be determined by the following formula: ;

[0117] Among them, IDCT() can represent the inverse discrete cosine transform; This represents a complex scattering sequence.

[0118] Step 442: Obtain the reset scattering matrix based on the complex scattering sequence.

[0119] By recombining the complex sequences into a complex matrix, the reset scattering matrix can be determined.

[0120] In this embodiment, step 442 may include steps 4421 to 4423.

[0121] Step 4421: Reassemble the complex scattering sequence into a set of complex matrices with frequency points as the dimension.

[0122] Step 4422: Perform reciprocity correction on the complex matrix at each frequency point to obtain the corrected complex matrix.

[0123] For example, reciprocity modification can be achieved through the following formula: ;

[0124] Where S represents a complex matrix at a frequency point.

[0125] Step 4423: For the modified complex matrix, singular value decomposition is performed to constrain all singular values ​​to be less than or equal to a set value, thereby obtaining the reset scattering matrix.

[0126] For example, passive projection can be performed on a modified complex matrix, specifically by constraining all singular values ​​through Singular Value Decomposition (SVD).

[0127] The set value can be 1 or any other positive real number.

[0128] Step 450: Regenerate the scattering parameter file based on the reset scattering matrix.

[0129] The restored reset scattering matrix is ​​regenerated into an SNP file in amplitude (dB) and phase (degree) format.

[0130] The batch scattering parameter compression method and the batch scattering parameter decompression method described above can be inverse processes. The batch scattering parameter compression method can compress the original scattering parameter file, while the batch scattering parameter decompression method is the process of restoring the file compressed by the batch scattering parameter compression method.

[0131] In the above implementation of this application, a complete scattering parameter matrix is ​​synthesized after decoding, and reciprocity and passive constraints are introduced to balance data compression and physical consistency of scattering parameters.

[0132] The batch scattering parameter compression and decompression methods provided in this application only require conventional matrix operations (DCT / IDCT and SVD) and are suitable for embedding in any simulation or measurement software.

[0133] Furthermore, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the batch scattering parameter compression method or the batch scattering parameter decompression method described in the above method embodiments.

[0134] The computer program products of the batch scattering parameter compression method and the batch scattering parameter decompression method provided in the embodiments of this application include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the steps of the batch scattering parameter compression method and the batch scattering parameter decompression method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed methods can also be implemented in other ways. The method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0136] In addition, the method steps in the various embodiments of this application can be integrated together to form an independent part for execution, or each method step can be executed by a separate module, or two or more steps can be formed into an independent part for execution.

[0137] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. It should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0138] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0139] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A batch scatter parameter compression method, characterized by, The method comprises the following steps: Parses the original scattering parameter file to extract the N-port scattering matrix and structural parameters for each frequency point; The parameters in the N-port scattering matrix include amplitude parameters and phase parameters; Convert the amplitude parameters and phase parameters in the N-port scattering matrix into complex number representation to obtain a complex scattering matrix; Discrete cosine transform is performed on the real part and the imaginary part of the complex scattering matrix respectively to determine first frequency domain coefficients; The first frequency domain coefficients are divided into first template coefficients and first residual coefficients; Quantization processing is performed on the first template coefficients and the first residual coefficients using a quantization function to obtain scattering quantization parameters; The scattering quantization parameters and the structural parameters are packaged to obtain a compressed file corresponding to the original scattering parameter file.

2. The method of claim 1, wherein, The first frequency domain coefficients are divided into first template coefficients and first residual coefficients, which comprises the following steps: The first frequency domain coefficients are divided into first template coefficients and first residual coefficients according to a specified order, wherein the coefficients before or at the specified order in the first frequency domain coefficients are determined as the first template coefficients, and the remaining coefficients are determined as the first residual coefficients.

3. The method of claim 1, wherein, The scattering quantization parameters include template quantization coefficients and residual quantization coefficients; The quantization processing is performed on the first template coefficients and the first residual coefficients using a quantization function to obtain scattering quantization parameters, which comprises the following steps: The first template coefficients are quantized using a first quantization step to obtain template quantization coefficients; The first residual coefficients are quantized using a second quantization step to obtain residual quantization coefficients.

4. The method of claim 3, wherein, The quantization processing is performed on the first template coefficients using a first quantization step to obtain template quantization coefficients, which comprises the following steps: The first template coefficients are processed based on a dead zone coefficient to obtain preprocessed template coefficients; The preprocessed template coefficients are quantized using a first quantization step to obtain template quantization coefficients.

5. The method of claim 3, wherein, The quantization processing is performed on the first residual coefficients using a second quantization step to obtain residual quantization coefficients, which comprises the following steps: The first residual coefficients are processed based on a dead zone coefficient to obtain preprocessed residual coefficients; The preprocessed residual coefficients are quantized using a second quantization step to obtain residual quantization coefficients.

6. A method of bulk scatter parameter decompression, the method comprising: The batch scattering parameter decompression method comprises the following steps: A to-be-processed compressed file is parsed to obtain quantization coefficients and structural parameters; wherein the to-be-processed compressed file is a file processed by the batch scattering parameter compression method of any one of claims 1-5; Inverse quantization processing is performed on the quantization coefficients using an inverse quantization function to obtain second template coefficients and second residual coefficients; The second template coefficients and the second residual coefficients are merged to obtain second frequency domain coefficients; Discrete cosine inverse transform is performed on the second frequency domain coefficients to obtain a complex scattering sequence; The complex scattering sequence is recombined into a complex matrix set in the frequency point dimension; The reciprocity correction is performed on the complex matrix of each frequency point to obtain a corrected complex matrix; The singular value decomposition is performed on the corrected complex matrix to constrain all singular values to be less than or equal to a set value, and a complex scattering matrix is obtained; The scattering parameter file is regenerated based on the complex scattering matrix.

7. A test system, characterized by It comprises: a probe station and a vector network analyzer; the probe station is used to connect a device under test; the vector network analyzer is used to apply a high-frequency signal to the device under test, measure the response of the device under test, and perform the steps in the batch scattering parameter compression method of any one of claims 1-5 or the steps in the batch scattering parameter decompression method of claim 6.

8. An electronic device, comprising: It comprises: a processor and a memory, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the machine readable instructions are executed by the processor to perform the steps in the batch scattering parameter compression method of any one of claims 1-5 or the steps in the batch scattering parameter decompression method of claim 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, which is executed by the processor to perform the steps in the batch scattering parameter compression method of any one of claims 1-5 or the steps in the batch scattering parameter decompression method of claim 6.

10. A computer program product, characterised in that, The computer program product comprises a computer program, which is executed by the processor to implement the batch scattering parameter compression method of any one of claims 1-5 or the batch scattering parameter decompression method of claim 6.

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