CN114928388A - Broadband signal multi-antenna synthesis method based on GPU multi-operation queue concurrent framework - Google Patents
Broadband signal multi-antenna synthesis method based on GPU multi-operation queue concurrent framework Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/084—Equal gain combining, only phase adjustments
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1851—Systems using a satellite or space-based relay
- H04B7/18513—Transmission in a satellite or space-based system
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
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- G06F2209/00—Indexing scheme relating to G06F9/00
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- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention provides a broadband signal multi-antenna synthesis method based on a GPU (graphics processing unit) multi-operation queue concurrent framework, which takes GPU operation queue concurrency as a parallel basis, each operation queue is used for processing a data block of an antenna subband, and the multi-operation queue concurrency is used for realizing rapid cross correlation of antenna signals and reference antenna signals to solve phase difference; meanwhile, a plurality of GPUs concurrently process data of each sub-band, and compared with a traditional broadband signal multi-antenna synthesis method, the method is better in instantaneity and parallelism; the multi-operation queue concurrency method can not only accelerate the calculation module, but also better hide the time consumed by data transmission between the host and the equipment end or between the host and the equipment end, and has better parallelism and real-time property; the parallel processing of multiple antennas, multiple sub-bands and multiple data blocks can be realized; compared with the traditional multi-antenna signal synthesis method, the method has the advantages of higher precision, better real-time performance and stronger expansibility.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a broadband signal multi-antenna synthesis method based on a GPU (graphics processing unit) multi-operation queue concurrent framework, which is suitable for receiving and synthesizing broadband signals sent by satellites or other spacecrafts in a communication system through multiple antennas.
Background
Table 1 shows the comparison of downlink signal parameters of a mainstream satellite internet constellation and a high-throughput satellite, the downlink signal bandwidth of the StarLink and OneWeb constellation is 250MHz, the transmission rate reaches 600Mbit/s, the downlink signal bandwidth of the ViaSlat-1 and the terminal is 500MHz, and the transmission rate also reaches 550 Mbit/s. It can be seen that the downlink signal bandwidth of the mainstream broadband satellite reaches the level of 250-500 MHz. Referring to the concept of ultra-wideband signals, signals with a bandwidth of 20-500 MHz are defined as wideband signals.
TABLE 1 satellite Internet constellation and GEO-HTS parameter comparison
Broadband satellite communications and data transmission services present unprecedented challenges for terrestrial reception devices. At present, a satellite ground station usually adopts a large-caliber parabolic antenna to carry out data transmission service, and the caliber is generally 4m-12 m. The data receiving code rate of the data receiving station of the remote sensing satellite in China reaches 2X 1200Mbps (X frequency band) and 4X 1.5Gbps (Ka frequency band). However, the application of the large-aperture antenna in practice has the following disadvantages: (1) the maneuverability, the concealment and the survivability are poor. (2) The data transmission service Ka has high frequency in equal frequency bands and narrow beam width (taking a 12 m-aperture antenna as an example, the half-power beam width of an S frequency band is 0.79 degrees, while the half-power beam width of the Ka frequency band is only 0.065 degrees), how to reliably realize the high dynamic capture and tracking of the Ka frequency band satellite data, and also puts high requirements on the technical capability of data receiving of a ground station. (3) The satellite is far away from the ground, and the Signal is interfered by free loss and Noise in the transmission process, so that the Signal-to-Noise Ratio (SNR) of the Signal received by the antenna is low, and the back-end processing of the Signal is directly influenced. Therefore, a broadband satellite signal receiving method is urgently needed to be found: the method has the advantages of strong maneuverability, good concealment and high receiving signal-to-noise ratio.
By using the deep space antenna array technology, a plurality of small-caliber antennas form a group array to receive the same satellite signal, and each path of signal is weighted and synthesized by utilizing the correlation of the signal and the irrelevance of noise, thereby realizing the high-quality reception of the broadband satellite signal. However, the utilization of the weighted synthesis of multiple small-aperture antennas to improve the received signal-to-noise ratio of the broadband signal inevitably introduces the following two problems: the number of antennas is large, so that the algorithm complexity is multiplied, a traditional signal processing platform depends on special hardware and firmware, the hardware and the software are tightly coupled, the flexibility and the expansibility of equipment are not high, and data fusion processing is difficult to perform.
Therefore, the algorithm complexity and the parallelism degree of the multi-antenna signal synthesis system are high. The overall required computing power of the multi-antenna signal synthesis system is beyond the range that a common multi-Core Processing Unit (CPU) can bear. Meanwhile, the development of a multi-antenna signal synthesis system is also restricted by the traditional hardware processing platform. In recent years, with the development of high-performance computing technology, a Graphics Processing Unit (GPU) is gradually shifting from a processor dedicated to the image field to a general-purpose parallel computing platform. The GPU has far more operation cores than the CPU, and is more suitable for parallel acceleration processing of data intensive calculation. NVIDIA introduced a Compute Unified Device Architecture (CUDA) in 2007, which simplified the development process of the GPU system, and made the GPU general-purpose computing technology more widely applied in the signal processing field. Therefore, under a general hardware processing platform, a better approach is to adopt a software method to synthesize the broadband satellite signals.
In a multi-antenna signal synthesis system, real-time performance is a key issue in the face of high-complexity signal processing tasks. Therefore, it is necessary to research a new system architecture and a real-time processing technology by combining a virtualization technology and a parallel computing technology with respect to the difficult problem of signal real-time processing.
The existing wideband signal synthesis is mainly a frequency domain full spectrum synthesis method, as shown in fig. 1, and its main idea is: firstly, the speed of the broadband signal is reduced, and the broadband signal is split into sub-bands by using the technologies of channelization, an analysis filter, FFT and the like. And then, obtaining phase differences among different antenna sub-bands by using a phase difference estimation algorithm, further estimating residual time delay and phase between broadband signals, independently performing phase compensation on the sub-bands, synthesizing each antenna sub-band, and finally reconstructing the sub-bands synthesized by each antenna to obtain an original broadband synthesized signal.
The defects of the existing broadband signal multi-antenna synthesis method are mainly reflected in the following aspects:
(1) the number of antennas is large, the signal frequency bandwidth causes multiplication of algorithm complexity, and the traditional FPGA hardware platform is difficult to meet the requirements of large calculation amount and low cost;
(2) the traditional signal processing platform relies on special hardware and firmware, the software and the hardware are tightly coupled, the flexibility and the expansibility of equipment are not high, and hardware resources are not divisible and are distributed according to requirements.
Disclosure of Invention
In view of this, an object of the present invention is to provide a wideband signal multi-antenna synthesis method based on a multi-operation queue concurrent architecture of a GPU, which can improve real-time performance.
A broadband signal multi-antenna synthesis method comprises the following steps:
the first step is as follows: obtaining parallel L-path antenna signals; wherein L is the number of antennas;
the second step: sending the L paths of parallel antenna signals to an idle GPU, performing sub-band splitting operation on each path of antenna signals in a multi-thread parallel mode, splitting the antenna signals into a plurality of sub-band signal data with different center frequencies, and setting the number of sub-bands as N;
the third step: correspondingly sending the N subband signal data of the reference antenna in the L antennas to N GPUs one by one, and setting the data as the GPU 1-GPUN; in each GPU of the N GPUs, splitting sub-bands of the L antennas into M data blocks, respectively copying the M data blocks by using a mode of concurrence of a plurality of operation queues, and performing cross-correlation operation on the non-reference antenna, the sub-bands corresponding to the reference antenna and the corresponding data blocks to obtain a phase difference; obtaining M phase difference results corresponding to L-1 non-reference antennas aiming at the sub-band signal data in each GPU;
the fifth step: fitting the M phase difference results obtained by each sub-band, wherein the intercept of a fitting curve is the value of the phase difference of the sub-band, then performing phase compensation on data of each sub-band by using the phase difference, and adding corresponding sub-band signal data of each antenna after the phase compensation of all sub-bands is completed;
and a sixth step: and reconstructing the sub-band signal data obtained by each GPU in the fifth step to obtain signals with the same bandwidth as the original signals, and realizing synthesis.
Preferably, in the first step, the analog data of the antenna signal is sampled after amplitude adjustment, and then the sampled data is subjected to serial-to-parallel conversion to obtain parallel L-path antenna signals.
Preferably, the first step is performed at the host side.
Preferably, in the second step, the L-path parallel antenna signals are sent to the idle GPU through the DDS middleware technology.
The invention has the following beneficial effects:
the invention provides a broadband signal multi-antenna synthesis method based on a GPU (graphics processing unit) multi-operation queue concurrent framework, which takes GPU operation queue concurrency as a parallel basis, each operation queue is used for processing a data block of an antenna subband, and the multi-operation queue concurrency is used for realizing rapid cross correlation of antenna signals and reference antenna signals to solve phase difference; meanwhile, a plurality of GPUs concurrently process data of each sub-band, and compared with a traditional broadband signal multi-antenna synthesis method, the method is better in instantaneity and parallelism; the traditional thread parallel method can only accelerate the calculation time, but cannot accelerate the data transmission time; the multi-operation queue concurrency method can accelerate the computing module, can better hide the time consumed by the transmission of data between the host and the equipment end or between the host and the equipment end, and has better parallelism and real-time property; the parallel processing of multiple antennas, multiple sub-bands and multiple data blocks can be realized; compared with the traditional multi-antenna signal synthesis method, the method has the advantages of higher precision, better instantaneity and stronger expansibility.
Figure illustrating
Fig. 1 is a block diagram of a conventional frequency domain full spectrum synthesis method.
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The technical problem solved by the invention is as follows: the system takes the GPU as a data processing device of a core, can effectively reduce the pressure of operand on the system, and can improve the performance of signal synthesis and reduce the synthesis loss by utilizing the floating point operation capability of the GPU. The method adopts GPU multi-operation queue concurrency as a parallel operation basis, and simultaneously applies parallel optimization modes such as multi-GPU concurrency, multi-operation queue concurrency, multi-thread concurrency and the like. The operation time consumption of the GPU platform is mainly focused on data transmission and actual operation. If the traditional GPU thread parallel operation method is adopted, simultaneous parallel processing of multiple paths of signals can be realized, but data transmission and operation modules are independent in the processing process of a certain path of signal, operation can be performed only after all data of the path of signal are transmitted, and a large amount of time is consumed for transmitting all data of the path of signal at one time. According to the multi-operation queue concurrent architecture provided by the patent, each operation queue is used for processing one data block in one path of antenna signals, and the multi-operation queue concurrency can better hide the time consumed by data transmission between GPUs and simultaneously realize concurrent operation of multiple paths of signals.
The method is based on a GPU platform, a section of longer data is split into a plurality of data blocks, and the parallelism of the system is improved by simultaneously processing in a multi-operation queue concurrent mode, so that the real-time performance of the system is improved.
In the conventional thread parallel method, taking a certain path of signal as an example, before operation, after all data of the path of signal needs to be transmitted to the GPU, a plurality of threads are started to operate on the data at the same time, each thread processes part of the data therein, and after all threads are calculated, all the data are transmitted to the CPU or the next device. The method can accelerate the calculation time by utilizing a thread parallel acceleration method, so that the time consumption is mainly focused on the data transmission. The method is also a mainstream method for acceleration based on the GPU and a commonly used method.
The invention adopts a multi-operation queue concurrent architecture, and blocks the data before calculation into N data blocks. And constructing a plurality of operation queues by using the N GPUs, wherein each operation queue processes one data block, so that the data transmission time of each operation queue is shortened to be 1/N of the previous data transmission time, and the calculation time is not changed. And because the plurality of operation queues use different GPUs, the operation queues are not interfered with each other, and the time consumed by data transmission can be reduced on the whole by realizing the concurrence of the plurality of operation queues.
When the number of points of each signal is too large, the data can be divided into more data blocks, so that the number of the needed GPUs is increased. In theory, the data can be divided into any number of data blocks to operate, so that the overall time consumption is minimized, but the more data blocks are divided, the more GPUs are needed. Therefore, the number of the data blocks can be reasonably set to achieve the maximum benefit on the basis of simultaneously considering real-time performance (overall time consumption) and resource cost (the number of GPUs).
Fig. 2 is a detailed flow chart of the GPU-based broadband signal multi-antenna synthesis method.
The first step is as follows: in the data receiving module, analog data is subjected to amplitude adjustment and then sent to an analog-to-digital conversion (ADC) module for sampling, then the sampled data is subjected to serial-to-parallel conversion, and serial L antenna signals acquired by the ADC are converted into parallel L antenna signals, and the operation is carried out at a host end.
The second step is that: and sending the L paths of parallel antenna signals to an idle GPU0 through a DDS middleware technology, and performing sub-band splitting operation on each path of antenna signals in a multi-thread parallel mode to split the antenna signals into a plurality of sub-bands with different center frequencies, wherein the number of the sub-bands is set to be N.
The third step: respectively sending N subbands of a reference antenna in the L antennas to N GPUs, and setting the N subbands as the GPUs 1-GPUN; taking GPU1 as an example, in GPU1, subband 1 of all antennas needs to be cross-correlated with subband 1 of the reference antenna to obtain a phase difference. And optimizing the flow by using a multi-operation queue concurrent framework, namely splitting each sub-band of each antenna into M data blocks, respectively copying the M data blocks by using a plurality of operation queues in a concurrent mode, and performing cross-correlation operation on the M data blocks and the sub-bands and the corresponding data blocks corresponding to the reference antennas to obtain a phase difference. Each antenna requires M operation queues, L-1 antennas except the reference antenna, and therefore (L-1) × M operation queues are required in each GPU, and therefore each GPU needs to contain at least (L-1) × M non-default stream processors. For each sub-band, calculating each data block of L-1 non-reference antennas, the sub-band corresponding to the reference antenna and the corresponding data block to obtain a phase difference result;
the fifth step: and fitting the phase difference result obtained by each sub-band, wherein the intercept of a fitting curve is the value of the phase difference, then independently performing phase compensation on each sub-band data by using the phase difference, and after the phase compensation of all the sub-bands is completed, adding the corresponding sub-band signal data of each antenna to obtain the sub-band data with higher signal-to-noise ratio.
And a sixth step: and reconstructing the sub-band data obtained by each GPU in the fifth step to obtain a signal with the same bandwidth as the original signal, and enhancing the signal-to-noise ratio of the signal.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A method for multi-antenna synthesis of wideband signals, comprising:
the first step is as follows: obtaining parallel L-path antenna signals; wherein L is the number of antennas;
the second step is that: sending the L paths of parallel antenna signals to an idle GPU, performing sub-band splitting operation on each path of antenna signals in a multi-thread parallel mode, splitting the antenna signals into a plurality of sub-band signal data with different center frequencies, and setting the number of sub-bands to be N;
the third step: correspondingly sending the N subband signal data of the reference antenna in the L antennas to N GPUs one by one, and setting the data as the GPU 1-GPUN; in each GPU of the N GPUs, sub-bands of the L antennas are divided into M data blocks, the M data blocks are respectively copied by utilizing a mode that a plurality of operation queues are concurrent, cross-correlation operation is carried out on the non-reference antenna, the sub-bands corresponding to the reference antenna and the corresponding data blocks, and phase difference is obtained; obtaining M phase difference results corresponding to L-1 non-reference antennas aiming at sub-band signal data in each GPU;
the fifth step: fitting the M phase difference results obtained by each sub-band, wherein the intercept of a fitting curve is the value of the phase difference of the sub-band, then performing phase compensation on data of each sub-band by using the phase difference, and adding corresponding sub-band signal data of each antenna after the phase compensation of all the sub-bands is completed;
and a sixth step: and reconstructing the sub-band signal data obtained by each GPU in the fifth step to obtain signals with the same bandwidth as the original signals, and realizing synthesis.
2. The method as claimed in claim 1, wherein in the first step, the analog data of the antenna signal is sampled after amplitude adjustment, and then the sampled data is converted from serial to parallel to obtain parallel L-path antenna signals.
3. The method for multi-antenna synthesis of broadband signals according to claim 1, wherein the first step is performed at a host side.
4. The method as claimed in claim 1, wherein the second step sends the L-path parallel antenna signals to the idle GPU via DDS middleware.
5. The method as claimed in claim 1, wherein in the first step, the analog data of the antenna signal is sampled after amplitude adjustment, and then the sampled data is converted from serial to parallel to obtain parallel L-path antenna signals.
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