A dynamic compression processing method for large bandwidth signal transmission of multi-beam digital phased array

Abstract

The present invention discloses a method for dynamic compression processing of large bandwidth signal transmission of a multi-beam digital phased array, the method comprising: obtaining effective parameters of the current system; determining the minimum bit width b required for each beam based on the effective parameters; comparing the minimum bit width b with the original sampling bit width D; and determining whether to perform data compression based on the comparison result. The present invention can reduce the data transmission bandwidth, ensure system synchronization, achieve low-complexity design, and have strong compatibility.

Description

Technical Field

[0001] The present invention belongs to the field of signal transmission, and particularly relates to a dynamic compression processing method for large-bandwidth signal transmission of a multi-beam digital phased array. Background Art

[0002] With the increasingly wide application of digital phased arrays, their scale is also getting larger. The supported bandwidth may exceed 1 GHz at most, the number of supported beams ranges from several to hundreds, and the number of channels is hundreds, thousands, or even hundreds of thousands. In various large-scale digital phased arrays, the data transmission capacity has become the bottleneck of the system. How to ensure the synchronous transmission of multi-beam large-bandwidth signals between modules has become an important part of large-scale digital phased array systems. Summary of the Invention

[0003] In view of the defects existing in the above-mentioned prior art, the present invention provides a dynamic compression processing method for large-bandwidth signal transmission of a multi-beam digital phased array, including the following steps:

[0004] Step S101, obtaining the effective parameters of the current system, where the effective parameters include the number of beams M of the current system, the fixed throughput T of the system, and the original sampling bit width D;

[0005] Step S103, determining the minimum bit width b required for each beam based on the effective parameters;

[0006] Step S105, comparing the minimum bit width b with the original sampling bit width D;

[0007] Step S107, determining whether to perform data compression based on the comparison result;

[0008] Among them, the step S103 includes:

[0009] Step S1031, calculating the first throughput F required for each beam;

[0010] Step S1033, calculating the minimum bit width b required for each beam based on the first throughput, where , and the ceil function represents rounding up.

[0011] Among them, the step S107 includes:

[0012] Step S1071, if b < D, perform data compression;

[0013] Step S1073, if D ≤ b, reduce the number of beams.

[0014] Among them, the data compression includes the following steps:

[0015] Step (1): Divide the continuous data stream X(n) of each beam into segments of length N, each segment containing N sampling points. Where n = 1, 2, ..., N, m represents the mth beam, m = 1, 2, ..., M;

[0016] Step (2): Determine the maximum absolute value of each segment , n = 1, 2,..., N;

[0017] Step (3): Determine The number of sign bits ;

[0018] Step (4): Keep only The first significant sign bit of of high sign bit, discard the low bit of the segment data Ones digit, get b bits of compressed data ;

[0019] Step (5): The compression factor of each segment Packed in the frame header, and compressed b bits of data Also packed in this frame.

[0020] In the step (5), each beam has an independent frame header and compression coefficient.

[0021] Wherein, the step (4) is expressed by the following formula: ,in, represents b bits of compressed data; Indicates segmentation The maximum absolute value of express b represents the minimum bit width after compression; sign(X) represents the sign function of X, which is 1 when X>0 and -1 when X<0; Reservation The first significant sign bit of ; Reservation Low Bit.

[0022] Wherein, before step S101, the method further includes: executing clock network synchronization in the current system to ensure that modules of different levels in the system are in a synchronous clock domain.

[0023] The first-level module in the system is responsible for sampling and digitizing the M sub-array channels of the receiving antenna array. The sampling data of each sub-array channel is , where n = 1, 2, ..., N, m represents the mth beam, and m = 1,2, ..., M.

[0024] The secondary module in the system compresses the sampled data to generate compressed data. .

[0025] The receiving end of the system buffers M sample points and restores the original data through the frame header and the compression coefficient.

[0026] Compared with the prior art, the present invention has the following advantages:

[0027] This method is suitable for transmitting high-throughput multi-beam data in large digital phased array systems.

[0028] When the hardware transmission capacity is determined, the transmission data bit width can be dynamically adjusted according to the number of beams to achieve the best balance between the number of beams and the signal-to-noise ratio.

[0029] By compressing the original sampled data and transmitting b-bit compressed data, the transmission bandwidth requirement is greatly reduced;

[0030] During the compression and decompression process, the synchronous transmission of the frame header and compression coefficient information ensures that the receiving end can accurately restore the original sampled data, which can ensure the time synchronization of the entire receiving-compression-transmitting link and avoid phase and amplitude errors;

[0031] By concentrating complex digital signal processing in the secondary and tertiary modules, the primary module is only responsible for simple synchronous sampling, reducing the complexity of the front-end circuit. This hierarchical design helps reduce system cost and power consumption.

[0032] This method can adapt to system requirements with different numbers of beams and sampling points by simply adjusting the number of compressed bits and the number of decompressed bits. It can be applied to a variety of high-speed data transmission systems, such as the Internet of Things systems, edge computing, mobile base stations, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present disclosure will become readily understood. In the accompanying drawings, several embodiments of the present disclosure are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0034] Figure 1 is a flow chart showing a method for dynamic compression processing of large bandwidth signal transmission of a multi-beam digital phased array according to an embodiment of the present invention;

[0035] Figure 2is a block diagram showing a large bandwidth signal transmission dynamic compression processing system of a multi-beam digital phased array according to an embodiment of the present invention;

[0036] Figure 3 The present invention is based on the embodiment of the present invention. Figure 2 A data compression flow chart of the system shown; and

[0037] Figure 4 The present invention is based on the embodiment of the present invention. Figure 2 Data decompression flow chart of the system shown. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0040] It should be understood that although the terms first, second, third, etc. may be used to describe ... in the embodiments of the present invention, these ... should not be limited to these terms. These terms are only used to distinguish .... For example, without departing from the scope of the embodiments of the present invention, the first ... may also be referred to as the second ..., and similarly, the second ... may also be referred to as the first ....

[0041] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0042] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0043] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0044] The optional embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0045] Example 1

[0046] like Figure 1 As shown, the present invention discloses a method for evaluating dynamic compression processing of large bandwidth signal transmission of a multi-beam digital phased array, comprising the following steps:

[0047] Step S101, obtaining effective parameters of the current system, wherein the effective parameters include the number of beams M, the system fixed throughput T, and the original sampling bit width D of the current system;

[0048] Step S103: determining the minimum bit width b required for each beam based on the effective parameters;

[0049] Step S105, comparing the minimum bit width b with the original sampling bit width D;

[0050] Step S107: Determine whether to perform data compression based on the comparison result.

[0051] Example 2

[0052] The present invention proposes a method for dynamic compression processing of large bandwidth signal transmission of a multi-beam digital phased array, comprising the following steps:

[0053] Step S101, obtaining effective parameters of the current system, wherein the effective parameters include the number of beams M, the system fixed throughput T, and the original sampling bit width D of the current system;

[0054] Step S103: determining the minimum bit width b required for each beam based on the effective parameters;

[0055] Step S105, comparing the minimum bit width b with the original sampling bit width D;

[0056] Step S107: Determine whether to perform data compression based on the comparison result;

[0057] Wherein, the step S103 includes:

[0058] Step S1031: Calculate the first throughput F required for each beam;

[0059] Step S1033: Based on the first throughput, calculate the minimum bit width b required for each beam, where , where the ceil function represents rounding up.

[0060] If the number of beams M in the current system and the fixed throughput T (bits / second) of the system, then

[0061] The throughput required for each beam: F = T / M.

[0062] Among them, the step S107 includes:

[0063] Step S1071: If b < D, perform data compression;

[0064] Step S1073: If D ≤ b, reduce the number of beams.

[0065] Among them, the data compression includes the following steps:

[0066] Step (1): Divide the continuous data stream X(n) of each beam into segments of length N, and each segment contains N sampling points where n = 1, 2,..., N, m represents the mth beam, m = 1, 2,..., M;

[0067] Step (2): Determine the maximum absolute value of each segment , n = 1, 2,..., N;

[0068] Step (3): Determine the number of sign bits ;

[0069] Step (4): Only retain the first valid sign bit of, discard the high number of sign bits of, discard the low number of bits of this segment of data, and obtain b-bit compressed data ;

[0070] Step (5): Pack the compression coefficient of each segment in the frame header, and also pack the compressed b-bit data in this frame.

[0071] Among them, each beam in the step (5) has an independent frame header and compression coefficient.

[0072] Wherein, the step (4) is expressed by the following formula: ,in, represents b bits of compressed data; Indicates segmentation The maximum absolute value of express b represents the minimum bit width after compression; sign(X) represents the sign function of X, which is 1 when X>0 and -1 when X<0; Reservation The first significant sign bit of ; Reservation Low Bit.

[0073] Wherein, before step S101, the method further includes: executing clock network synchronization in the current system to ensure that modules of different levels in the system are in a synchronous clock domain.

[0074] The first-level module in the system is responsible for sampling and digitizing the M sub-array channels of the receiving antenna array. The sampling data of each sub-array channel is , where n = 1, 2, ..., N, m represents the mth beam, and m = 1,2, ..., M. The first-level module needs to ensure that the sampling time of the M sub-array channels is completely synchronized.

[0075] The secondary module in the system compresses the sampled data to generate compressed data. The secondary module needs to ensure that the time frames of the M compressed data streams are aligned, and the frame headers and compression coefficients are synchronized.

[0076] The third-level module is responsible for decompressing and DA-converting the compressed data stream. The third-level module needs to ensure the synchronous output of M-channel decompressed data to drive the transmitting antenna array.

[0077] Among them, the first-level module has synchronization of sampling time, the second-level module has time alignment of data frames, and the third-level module has synchronous output of decompressed data.

[0078] The receiving end of the system buffers M sample points and restores the original data through the frame header and the compression coefficient.

[0079] The formula is:

[0080] ,in, is the b-bit compressed data of beam m; is the D-bit decompressed data of sampling point n in beam m; the left shift (Db) bit is to expand the b-bit data to D bits; the right shift The bit is to be based on the coefficient Restore the original N-bit data, where the coefficient It will vary with different sub-array channels.

[0081] Example 3

[0082] like Figure 2 As shown, a large-bandwidth signal transmission dynamic compression processing system of a multi-beam digital phased array is consistent with an embodiment of the present invention. The system main control module synchronizes all modules such as the sub-arrays of the first-level module, the second-level module, the third-level module, etc. in the same clock network through the synchronization signal of the clock network.

[0083] The system master control module uses the synchronization signal of the clock network to achieve the receiving and transmitting synchronization accuracy of all channels of each level of modules to the picosecond level, achieving phase-level synchronization.

[0084] The system main control module calculates the actual bit width required under a fixed throughput based on the number of beams. Assuming the sampling bit width is D bits, the maximum bit width that can be satisfied after the throughput is determined is N bits (N<D), and the bit width compression begins.

[0085] Compression: Segment the continuous data stream of each beam, assuming that M sample points are a group, find the maximum value of the group and determine the number of sign bits K, retain only the first valid sign bit, cut off the remaining higher sign bits (K-1 bits), and cut off NK low-order data bits at the same time, and obtain a data compression factor of NK. In this way, the high K-1 bits are cut off, the low NK bits are cut off, and N bits of data are retained.

[0086] Transmission: The compression coefficients are framed and transmitted. The frame format includes a frame header, a compression coefficient, and truncated data. Each beam has an independent frame header and an independent compression coefficient.

[0087] like Figure 3 As shown, the data compression process consistent with the embodiment of the present invention is as follows:

[0088] (a) Perform system clock network synchronization to ensure that the three levels of modules are in the same clock domain;

[0089] (b) Execute the synchronous acquisition and transmission of the system to ensure the synchronous reception and synchronous transmission of all channels of all sub-arrays from the first-level module to the third-level module;

[0090] (c) configuring the compressed bit width according to the number of beams;

[0091] (d) executing a data compression algorithm according to the setting of the compression bit width, and transmitting the compressed data;

[0092] (e) decompressing the data according to the agreed compression bit width setting;

[0093] (f) If the number of beams changes, repeat (c)-(e).

[0094] like Figure 4 As shown in FIG. 1 , it is a decompressed data process consistent with the embodiment of the present invention. During the decompression process, the receiving end first caches the M sample points, finds the frame header by sliding comparison during the caching process, and after finding the frame header, the compression coefficient can be restored through the framing format, and the data decompression is started according to the starting position of the segmented data. The specific process is to first expand the compressed data N bits to D bits through the complement sign bit, and then shift the data left by NK bits (compression coefficient) to obtain the decompressed beam data.

[0095] When the number of beams configured in the system changes, the required bit width is recalculated and a new compression bit width N value is executed.

[0096] Example 4

[0097] Assuming that the beam data to be transmitted after beam synthesis in the system is complex, the I and Q path widths are 20 bits each, the data sampling rate is 500Msps, and considering 8B10B encoding, the required transmission rate for one beam data is at least 2*20 bits*500*10 / 8=25Gbps. When there is only 20Gbps transmission capacity in the transmission system, it is necessary to consider compressing the data bit width; under the above assumptions, considering the transmission frame header and compression coefficient after data compression, 2 10Gbps optical fibers can transmit data with an IQ bit width of 15 bits at most. Therefore, the beam data can be compressed to 15 bits and transmitted. If it is not compressed, the high-speed interface cannot transmit the beam normally.

[0098] Example 5

[0099] An embodiment of the present disclosure provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the method steps described in the above embodiment.

[0100] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. Computer readable signal media may also be any computer readable medium other than computer readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0101] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0102] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (AN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0103] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0104] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0105] The above introduces the preferred embodiments of the present invention, which is intended to make the spirit of the present invention clearer and easier to understand, but is not intended to limit the present invention. All modifications, substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection outlined by the claims attached to the present invention.

Claims

1. A method for dynamic compression processing of large bandwidth signal transmission of a multi-beam digital phased array, characterized in that: It includes the following steps: Step S101: Obtain the effective parameters of the current system, where the effective parameters include the number of beams M of the current system, the system fixed throughput T, and the original sampling bit width D; Step S103: Determine the minimum bit width b required for each beam based on the effective parameters; Step S105: Compare the minimum bit width b with the original sampling bit width D; Step S107: Determine whether to perform data compression based on the comparison result; The step S103 includes: Step S1031: Calculate the first throughput F required for each beam; Step S1033: Calculate the minimum bit width b required for each beam based on the first throughput F, where: , where the ceil function means rounding up; The step S107 includes: Step S1071: If b < D, perform data compression; Step S1073: If D ≤ b, reduce the number of beams; The data compression includes the following steps: Step (1): Divide the continuous data stream X(n) of each beam into segments of length N, each segment containing N sampling points. Where n = 1, 2, ..., N, m represents the mth beam, m = 1, 2, ..., M; Step (2): Determine the maximum absolute value of each segment , n = 1, 2, ..., N; Step (3): Determine The number of sign bits ; Step (4): Keep only The first significant sign bit of of high sign bit, discard the low bit of the segment data Ones digit, get b bits of compressed data ; Step (5): The compression factor of each segment Packed in the frame header, and compressed b bits of data Also packed in this frame, each beam has an independent frame header and compression factor; Among them, the step (4) is expressed by the formula as follows: ； in, represents b bits of compressed data; Indicates segmentation The maximum absolute value of express b represents the minimum bit width after compression; sign(X) represents the sign function of X, which is 1 when X>0 and -1 when X<0; Reservation The first significant sign bit of ; Reservation Low Bit.

2. The method according to claim 1, characterized in that: Before the step S101, it also includes: Performing clock network synchronization in the current system to ensure that modules at different levels in the system are in the synchronous clock domain.

3. The method according to claim 1, characterized in that: The first-level module in the system is responsible for sampling and digitizing the M sub-array channels of the receiving antenna array. The sampling data of each sub-array channel is , where n = 1, 2, ..., N, m represents the mth beam, and m = 1, 2, ..., M.

4. The method according to claim 1, characterized in that: The secondary module in the system compresses the sampled data to generate compressed data .

5. The method according to claim 1, characterized in that: The receiving end of the system caches M samples and restores the original data through the frame header and the compression coefficient.

Images