CN114665892A - Radio frequency signal envelope prediction method based on baseband data perception - Google Patents
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Abstract
The invention discloses a radio frequency signal envelope prediction method based on baseband data perception, which is used for a method for obtaining a control voltage signal of an envelope tracking power supply by taking a communication baseband signal as input, and applying a trained radio frequency signal envelope prediction model by taking the baseband signal as input and envelope information corresponding to the baseband signal as output aiming at the baseband signal to obtain envelope information corresponding to the baseband signal and further obtain a first reference voltage signal corresponding to the envelope information; meanwhile, the baseband signal is modulated to obtain serial data corresponding to the baseband signal, multi-carrier modulation transmission is carried out on the serial data to obtain a radio frequency envelope signal, and the radio frequency envelope signal is delayed to obtain a second reference voltage signal matched with the first reference voltage signal in time; and aiming at the first reference voltage signal and the second reference voltage signal, an envelope tracking power supply is applied to obtain a control voltage signal of the envelope tracking power supply.
Description
Technical Field
The invention relates to the technical field of envelope tracking power supply control, in particular to a radio frequency signal envelope prediction method based on baseband data perception.
Background
In order to improve the transmission information quantity in the same frequency band, the modulation strategy in modern mobile communication such as 5G modulates the amplitude, the phase and the frequency of an envelope line radio frequency input signal, the envelope line amplitude of the envelope line input signal is not a constant signal, and the peak-to-average ratio of the radio frequency envelope line signal is continuously improved. In order to ensure that information carried by an envelope input signal is transmitted without distortion, a radio frequency linear power amplifier adopting a constant voltage power supply mode has very low working efficiency. Meanwhile, as the lost electric energy is dissipated in the form of heat, the base station needs to increase the power consumption of air conditioner refrigeration, and heavy electric charge burden is brought to operators. Therefore, the improvement of the radio frequency linear power amplifier efficiency of the base station is the energy-saving source of the modern mobile communication base station. At present, the envelope tracking technology is one of the most promising methods for improving the efficiency of the radio frequency power amplifier. The spectrum contained in the rf envelope signal is rich in energy, but the energy is concentrated in the low frequency part, and relatively less in the high frequency part. The switch converter has high energy processing efficiency and relatively low working bandwidth, and is more suitable for processing low-frequency-band energy. The linear converter has high working bandwidth and low efficiency, and is more suitable for processing high-frequency band energy. The envelope tracking power supply with the combined structure of the linear amplifier and the switch converter can effectively improve the working efficiency of the radio frequency power amplifier.
The reference signal of the switch converter and the linear amplifier in the envelope tracking power supply system usually needs to be generated by modulating the envelope generated by a baseband signal and filtering. The traditional envelope tracking power supply reference signal has a long generation flow and occupies more hardware computing resources. The radio frequency envelope input signal can be sent to a radio frequency linear power amplifier through a longer time delay module so as to be matched with the power supply waveform of an envelope tracking power supply. As can be seen, the envelope detection section and the reference signal generation in the typical envelope tracking power supply scheme require a long time and are computationally expensive. There is a need for a method that can reduce the delay time and improve the operation efficiency. In an envelope tracking power supply, the generation process from a baseband signal to a reference signal in the envelope power supply is complex in operation, and needs to pass through a plurality of links such as modulation, envelope generation and filtering, and the baseband signal and the reference signal in the envelope tracking power supply have large data format and time sequence difference and have no clear corresponding relation. In a modern high-speed communication system, an envelope signal can be changed at a higher speed and with a large amplitude, and a traditional envelope tracking power supply adopts a hardware circuit for tracking, so that the traditional envelope tracking power supply has a considerable time delay and is not beneficial to tracking an envelope.
Disclosure of Invention
The invention aims to provide a radio frequency signal envelope prediction method based on baseband data perception, which can directly generate information required by an envelope tracking power supply from a baseband signal through a radio frequency envelope prediction model, effectively improve the speed of generating a reference voltage waveform of a radio frequency power amplifier by the envelope tracking power supply, reduce the delay of the radio frequency envelope signal and the calculation requirement on hardware, and solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: a radio frequency signal envelope prediction method based on base band data perception is used for obtaining a control voltage signal of an envelope tracking power supply based on a communication base band signal as input, aiming at the base band signal, applying a trained radio frequency signal envelope prediction model which takes the base band signal as input and envelope information corresponding to the base band signal as output to obtain envelope information corresponding to the base band signal, and further obtaining a first reference voltage signal corresponding to the envelope information; meanwhile, the baseband signal is modulated to obtain serial data corresponding to the baseband signal, multi-carrier modulation transmission is carried out on the serial data to obtain a radio frequency envelope signal, the radio frequency envelope signal is delayed, and a second reference voltage signal matched with the first reference voltage signal in time is obtained; and aiming at the first reference voltage signal and the second reference voltage signal, an envelope tracking power supply is applied to obtain a control voltage signal of the envelope tracking power supply.
Further, the radio frequency signal envelope prediction model is obtained by a training method a as follows based on presetting each communication baseband sample signal: acquiring envelope information corresponding to each communication baseband sample signal according to a preset envelope information extraction method; and training a preset network to be trained by taking the communication baseband sample signal as input and the envelope information corresponding to the communication baseband sample signal as output to obtain a radio frequency signal envelope prediction model.
Further, the envelope signal extraction method is obtained by the following steps a to C:
step A: b, taking each communication baseband sample signal as input, obtaining serial data corresponding to each communication baseband sample signal through modulation, wherein the baseband sample signals are a series of random 0 and 1 bit signals, and then entering the step B;
and B, step B: taking serial data as input, obtaining a radio frequency envelope signal through multi-carrier modulation transmission, and then entering the step C; and C: and (3) taking the radio frequency envelope signal as input, and obtaining envelope information through an envelope information extraction module.
Further, training the preset network to be trained through steps S11-S13 to obtain a radio frequency signal envelope prediction model:
step S11, loading the baseband sample signal to the training network, and then proceeding to step S12;
step S12, using the baseband sample signal as input, obtaining serial-parallel code element through data sampling and serial-parallel processing, then entering step S13;
step S13: and (4) taking the serial-parallel code elements as input, and obtaining envelope information through multi-carrier data fitting.
Further, the training method a comprises: and separating the envelope information to obtain two information matrixes, namely an envelope peak value and a corresponding time point thereof, and an envelope valley value and a corresponding time point thereof.
Further, the data sampling and serial-parallel processing in step S12 includes equally dividing the bits into symbols according to a preset communication modulation algorithm, and then performing serial-parallel processing and conversion on the symbols according to the number of carriers.
Furthermore, the multi-carrier fitting unit comprises two parallel fitting units for respectively inputting the serial-parallel code elements at the same time.
Further, the process of constructing the rf signal envelope prediction model further includes: and (3) periodically executing the training method A to continuously update and optimize the radio frequency signal envelope prediction model so as to improve the prediction accuracy.
Furthermore, the envelope signal extraction method uses a findpeaks peak searching function program to obtain the peak value and the valley value of the envelope signal and envelope information of the corresponding time point.
Compared with the prior art, the radio frequency signal envelope prediction method based on baseband data perception has the following technical effects by adopting the technical scheme: the radio frequency signal envelope prediction model integrates the processes of generating signals by a modulation module, a multi-carrier modulation transmission module and an envelope information extraction module, and greatly reduces the system time delay and required hardware resources. The information perception is carried out on the baseband data by using the neural network, and the envelope tracking power supply can acquire the change rule of the envelope signal in advance and track the envelope with large change more quickly and accurately. The speed of generating the reference voltage required by the radio frequency power amplifier by the envelope tracking power supply can be effectively increased, the radio frequency signal delay and the calculation requirement on hardware are reduced, and finally the power supply of the base station power supply is more reliable and energy-saving.
Drawings
FIG. 1 is a schematic diagram of an envelope tracking power supply according to the present invention;
fig. 2 is a schematic diagram illustrating a principle of constructing a radio frequency signal envelope prediction model according to an embodiment of the present invention.
Detailed Description
For a better understanding of the technical content of the present invention, specific embodiments are described below in conjunction with the appended drawings:
aspects of the present invention are described in the present invention with reference to the accompanying drawings, and embodiments of the present invention are not limited to the drawings. It should be understood that the present invention can be realized by any of the concepts and embodiments described above and described in detail below, since the disclosed concepts and embodiments are not limited to any embodiment. It should be noted that the terms "upper", "lower", "left", "right", "front", "rear", and the like used in the present invention are for clarity of description only, and are not intended to limit the scope of the present invention, and changes or modifications of the relative relationship thereof are also considered to be within the scope of the present invention without substantial technical changes. Some aspects of the present disclosure may be used alone or in any suitable combination with other aspects of the present disclosure.
As shown in fig. 1, a method for predicting an envelope of a radio frequency signal based on baseband data sensing is used to obtain a control voltage signal of an envelope tracking power supply based on a communication baseband signal as an input, apply a trained radio frequency signal envelope prediction model constructed based on a neural network, which takes the baseband signal as the input and envelope information corresponding to the baseband signal as an output, to obtain envelope information corresponding to the baseband signal, and further obtain a first reference voltage signal corresponding to the envelope information. And simultaneously, modulating the baseband signal to obtain serial data corresponding to the baseband signal, then carrying out multi-carrier modulation transmission on the serial data to obtain a radio frequency envelope signal, and delaying the radio frequency envelope signal to obtain a second reference voltage signal which is matched with the first reference voltage signal in time. And aiming at the first reference voltage signal and the second reference voltage signal, an envelope tracking power supply is applied to obtain a control voltage signal of the envelope tracking power supply.
The envelope tracking power supply structure of fig. 1 includes a radio frequency envelope prediction model, a modulation module, a multi-carrier modulation transmission module, and a delay link. And a modulation module for processing the baseband signal according to a communication modulation algorithm including, for example, QAM, to generate serial data for input to the multicarrier modulation transmission module. And the delay module is connected between the modulation module and the linear power amplifier and used for adaptively adjusting the delay time length by combining the real-time operation efficiency of the radio frequency signal envelope prediction model so as to enable the power supply signals of the RF signal and the envelope tracking power supply to synchronously reach the linear power amplifier. The delay module of this embodiment is different from the delay module in the conventional envelope tracking power supply, and the conventional delay module needs to offset the sum of the operation times of the modulation module, the multi-carrier modulation transmission module and the envelope information extraction module, and usually adopts a very long delay mode.
Fig. 2 is a schematic diagram of an envelope prediction model structure of an rf signal according to an embodiment of the present invention, wherein the envelope tracking power supply structure is adjusted on the basis of a conventional envelope tracking power supply structure. In this embodiment, the radio frequency signal envelope prediction model directly replaces the operation process of the three links of the modulation module, the multi-carrier modulation transmission module and the envelope information extraction module, and envelope information can be directly obtained according to the introduced baseband signal;
envelope information is directly obtained through a radio frequency signal envelope prediction model, a modulation module and a multi-carrier modulation transmission module are still introduced into the other branch line, and a delay module only needs to offset the difference between the operation time of the radio frequency envelope prediction model and the operation time of the modulation module, so that the adopted time is extremely short, and the time difference is shorter and shorter along with the optimization and perfection of the radio frequency envelope prediction model, so that the speed of generating a reference voltage waveform required by a radio frequency power amplifier by an envelope tracking power supply is effectively improved.
As shown in fig. 2, the radio frequency signal envelope prediction model includes a data processing unit and a multicarrier data fitting unit. The data processing unit is used for leading in the baseband signal generated by the modulation module, equally dividing bit into code elements according to the adopted communication modulation algorithm, performing serial-parallel conversion processing on the code elements according to the number of carriers, and preparing to input the code elements into the multi-carrier data fitting unit. The multi-carrier data fitting unit comprises two parallel fitting units and is used for fitting the code elements subjected to serial-parallel conversion with envelope information imported from the envelope information extraction module to finally obtain peak values, corresponding time points, valley values and corresponding time points.
The radio frequency signal envelope prediction model is based on presetting each communication baseband sample signal, so that baseband signal samples sequentially pass through a modulation module, a multi-carrier modulation transmission module and an envelope information extraction module to generate corresponding envelope information samples. The modulation module is used for processing the baseband signal according to a communication modulation algorithm such as QAM and the like to generate serial data input to the multi-carrier modulation transmission module; the multi-carrier modulation transmission module is used for processing the input pre-modulation signal and generating a multi-carrier modulated radio frequency signal; and the envelope information extraction module is used for generating a key information string containing peak values, valley values and corresponding time points according to the envelope curve by a certain algorithm. Secondly, loading the envelope information to obtain an information matrix, and caching a data matrix corresponding to the baseband signal and the envelope information as sample data so as to facilitate the neural network to read and learn. The data processing unit is used for leading in the baseband signal generated by the modulation module, equally dividing the bit into code elements according to the adopted communication modulation algorithm, performing serial-parallel conversion processing on the code elements according to the number of carriers, and preparing to input the code elements into the multi-carrier data fitting unit. The multi-carrier data fitting unit comprises two parallel neural networks, the output peak value and the corresponding time point, the valley value and the corresponding time point are trained respectively, and network parameters are independent. The training principles of the two neural networks are similar, but the network parameters are independent of each other. And after the training of the radio frequency signal envelope prediction model is finished, the imported baseband signal is input into the radio frequency signal envelope prediction model to predict and generate envelope information. And finally, loading the baseband signal and the envelope information after the data processing into an artificial neural network, and enabling the neural network to directly predict and generate the radio-frequency signal envelope information through the baseband signal.
Acquiring envelope information corresponding to each communication baseband sample signal according to a preset envelope information extraction method; and training a preset network to be trained by taking the communication baseband sample signal as input and the envelope information corresponding to the communication baseband sample signal as output to obtain a radio frequency signal envelope prediction model. This is another reason why the radio frequency signal envelope prediction model is adopted in this embodiment to directly replace the operation process of the three links of the modulation module, the multi-carrier modulation transmission module and the envelope information extraction module, and compared with the modulated signal, the original baseband signal is more regular. The envelope signal extraction method is obtained through the following steps A to C: step A: taking each communication baseband sample signal as input, and obtaining serial data corresponding to each communication baseband sample signal through modulation, wherein the baseband sample signals are a series of random 0 and 1 bit signals, and the step B: taking serial data as input, obtaining a radio frequency envelope signal through multi-carrier modulation transmission, and then entering the step C; and C: and (3) taking the radio frequency envelope signal as input, and obtaining envelope information through an envelope information extraction module.
After that, the preset network to be trained is trained through steps S11 to S13, so as to obtain a radio frequency signal envelope prediction model, where the radio frequency signal envelope prediction model is used to process the introduced baseband signal, and output and fit envelope information required in the envelope tracking power supply, and the obtained envelope information includes the peak value and the valley value of the envelope and time points corresponding to the peak value and the valley value of the envelope. Step S11, loading the baseband sample signal to the training network, and then proceeding to step S12; step S12 is to take the baseband sample signal as input, perform data sampling and serial-parallel processing to obtain serial-parallel symbols, and then proceed to step S13; and step S13, fitting the serial-parallel converted code element with the imported envelope information to finally obtain the envelope information of the radio frequency signal.
The training method of the radio frequency signal envelope prediction model comprises the following steps: envelope information is separated, and two information matrixes, namely an envelope peak value and a corresponding time point thereof, and an envelope valley value and a corresponding time point thereof, are obtained.
The data processing in step S12 includes dividing the bits into equal parts according to a preset communication modulation algorithm, and then performing serial-to-parallel processing and conversion on the symbols according to the number of carriers.
And training a radio frequency signal envelope prediction model to continuously update and optimize the radio frequency signal envelope prediction model. Specifically, a baseband signal sample can be obtained periodically, the baseband signal sample is enabled to sequentially pass through a modulation module, a multi-carrier modulation transmission module and an envelope information extraction module to generate a corresponding envelope information sample, and the baseband signal sample and the envelope information sample are led into a radio frequency signal envelope prediction model to generate required envelope information; and optimizing and updating the envelope prediction model by comparing the predicted envelope information with envelope information samples generated by the envelope information extraction module.
The envelope signal extraction method adopts a findpeaks peak searching function writing program to obtain the peak value, the valley value, the envelope information of the envelope signal corresponding to the peak value of the envelope and the envelope information of the envelope signal corresponding to the valley value of the envelope.
In the present embodiment, the correspondence between the baseband signal and the information required in the envelope tracking power supply system is trained by using an artificial intelligence algorithm such as a neural network. The trained neural network can quickly respond to the baseband signal change and generate envelope information required in an envelope tracking power supply system. Through supervised learning in machine learning, the relation between the data quantity and the output quantity of training can be supervised and guided by the neural network. The multi-carrier data fitting unit comprises two parallel neural networks, the two neural networks are used for respectively training output peak values and corresponding time points, valley values and corresponding time points, the training principles of the two neural networks are similar, but the network parameters are independent. Supervised learning may help adjust the structure and connection point weights of the two networks to continually increase the accuracy of the predictions. The source of the supervised learning signal is shown in fig. 2. After the neural network is trained, the three links of the original modulation module, the multi-carrier modulation transmission module and the envelope information extraction module can be directly replaced by the neural network. And generating a key information string containing a peak value, a valley value and a corresponding time point, and directly or indirectly supplying the key information string to a circuit in the envelope tracking power supply. The neural network can continuously obtain envelope information generated by a baseband signal through a traditional modulation module, a multi-carrier modulation transmission module and an envelope information extraction module, and the neural network trains parameter configuration in a neural network algorithm and optimizes a network structure through learning a result generated by a traditional method so as to improve the accuracy of envelope information prediction.
Correspondingly, the embodiment of the invention provides a radio frequency signal envelope prediction method based on baseband data perception, and the prediction generation method comprises a radio frequency envelope prediction model building module, a baseband signal loading module, a modulation module, a multi-carrier modulation transmission module, an envelope information extraction module and a radio frequency signal envelope prediction model.
The radio frequency signal envelope prediction model building module is used for building an envelope prediction model based on a neural network; the baseband signal loading module is used for loading a baseband signal to the radio frequency signal envelope prediction model; the modulation module is used for processing the baseband signals according to a communication modulation algorithm including QAM to generate envelope line radio frequency signals input into the multi-carrier modulation transmission module; and the multi-carrier modulation transmission module is used for processing the input pre-modulation signal and generating a multi-carrier modulated radio frequency signal. The envelope information extraction module is used for extracting information of the envelope information of the radio frequency signal output by the multi-carrier modulation transmission module, and acquiring a maximum value, a minimum value and a corresponding time point according to a certain algorithm so as to facilitate hardware to track the envelope. And the radio frequency signal envelope prediction model is used for processing the introduced baseband signal, outputting and fitting envelope information required in the envelope tracking power supply, wherein the obtained envelope information contains the peak value and the valley value of the envelope and corresponding time points. The fitting process of the radio frequency signal envelope prediction model comprises the following steps: leading in a baseband signal generated by a modulation module, dividing bit into code elements equally according to an adopted communication modulation algorithm, and then performing serial-parallel conversion processing on the code elements according to the number of carriers; envelope information output by the envelope information extraction module is imported, and the code elements after serial-parallel conversion are fitted with the imported envelope information to finally obtain the envelope information of the radio frequency signal.
The radio frequency signal envelope prediction method based on baseband data perception can directly or indirectly generate envelope information required by an envelope tracking power supply from a baseband signal, and replaces a modulation module, an envelope generation module and a reference generation module in a typical envelope tracking power supply framework. The radio frequency signal envelope prediction model integrates the processes of generating signals by three modules, and greatly reduces the system time delay and required hardware resources. Compared with the prior art, the technical scheme has the following technical effects: the invention uses the neural network to sense the information of the baseband data, the envelope tracking power supply can acquire the change rule of the envelope signal in advance, and track the envelope with large change more quickly and accurately, thereby effectively improving the speed of the envelope tracking power supply for generating the reference voltage required by the radio frequency power amplifier, and reducing the delay of the radio frequency signal and the calculation requirement on hardware. And finally, the power supply of the base station power supply can be more reliable and energy-saving.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention should be determined by the claims.
Claims (9)
1. A radio frequency signal envelope prediction method based on base band data perception is used for obtaining a control voltage signal of an envelope tracking power supply based on a communication base band signal as input, and is characterized in that a trained radio frequency signal envelope prediction model which takes the base band signal as input and envelope information corresponding to the base band signal as output is applied to the base band signal to obtain envelope information corresponding to the base band signal, and further obtain a first reference voltage signal corresponding to the envelope information; meanwhile, the baseband signal is modulated to obtain serial data corresponding to the baseband signal, multi-carrier modulation transmission is carried out on the serial data to obtain a radio frequency envelope signal, and the radio frequency envelope signal is delayed to obtain a second reference voltage signal matched with the first reference voltage signal in time; and aiming at the first reference voltage signal and the second reference voltage signal, an envelope tracking power supply is applied to obtain a control voltage signal of the envelope tracking power supply.
2. The method for predicting the envelope of the radio-frequency signal based on the baseband data perception according to claim 1, wherein the envelope prediction model of the radio-frequency signal is obtained by a training method as follows based on preset baseband sample signals of each communication: acquiring envelope information corresponding to each communication baseband sample signal according to a preset envelope information extraction method; and training a preset network to be trained by taking the communication baseband sample signal as input and the envelope information corresponding to the communication baseband sample signal as output to obtain a radio frequency signal envelope prediction model.
3. The method for predicting the envelope of the radio frequency signal based on the baseband data perception according to claim 2, wherein the envelope signal extracting method is obtained by the following steps a to C:
step A: b, taking each communication baseband sample signal as input, obtaining serial data corresponding to each communication baseband sample signal through modulation, wherein the baseband sample signals are a series of random 0 and 1 bit signals, and then entering the step B;
and B: taking serial data as input, obtaining a radio frequency envelope signal through multi-carrier modulation transmission, and then entering the step C;
and C: and (3) taking the radio frequency envelope signal as input, and obtaining envelope information through an envelope information extraction module.
4. The method for predicting the envelope of the radio frequency signal based on the baseband data perception as claimed in claim 2, wherein the preset network to be trained is trained through steps S11-S13 to obtain a radio frequency signal envelope prediction model:
step S11, loading the baseband sample signal to the training network, and then proceeding to step S12;
step S12, using the baseband sample signal as input, obtaining serial-parallel code element through data sampling and serial-parallel processing, then entering step S13;
and step S13, obtaining envelope information by taking the serial-parallel code elements as input and fitting the multicarrier data.
5. The method for predicting the envelope curve of the radio-frequency signal based on the baseband data perception according to claim 2, wherein the A training method comprises: envelope information is separated, and two information matrixes, namely an envelope peak value and a corresponding time point thereof, and an envelope valley value and a corresponding time point thereof, are obtained.
6. The method for predicting the envelope of a radio frequency signal based on baseband data sensing of claim 4, wherein the data sampling and serial-parallel processing in step S12 includes equally dividing bits into symbols according to a predetermined communication modulation algorithm, and then performing serial-parallel processing and conversion on the symbols according to the number of carriers.
7. The method as claimed in claim 3, wherein the multi-carrier fitting unit comprises two parallel fitting units for inputting serial and parallel symbols respectively at the same time.
8. The method for predicting the envelope curve of the radio frequency signal based on the baseband data perception according to claim 1, wherein the process of constructing the radio frequency signal envelope prediction model further comprises: and periodically executing an A training method to continuously update and optimize the radio frequency signal envelope prediction model.
9. The method as claimed in claim 3, wherein the envelope signal extracting method uses a findpeaks peak-finding function program to obtain the peak value, the valley value, the envelope peak value corresponding time point and the envelope valley value corresponding time point of the envelope signal.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210172081.8A CN114665892A (en) | 2022-02-24 | 2022-02-24 | Radio frequency signal envelope prediction method based on baseband data perception |
| PCT/CN2022/127327 WO2023159988A1 (en) | 2022-02-24 | 2022-10-25 | Control signal generation method for switch converter in envelope tracking power source, and storage medium and electronic apparatus |
| US18/321,723 US20230291357A1 (en) | 2022-02-24 | 2023-05-22 | Method for predicting envelope features and generating switching converter control signal in envelope tracking power supply, storage medium, and electronic device |
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