CN113708781A - Radio frequency gain control method, device and communication equipment - Google Patents

Radio frequency gain control method, device and communication equipment Download PDF

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CN113708781A
CN113708781A CN202110931606.7A CN202110931606A CN113708781A CN 113708781 A CN113708781 A CN 113708781A CN 202110931606 A CN202110931606 A CN 202110931606A CN 113708781 A CN113708781 A CN 113708781A
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CN113708781B (en
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李大国
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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Abstract

The embodiment of the invention discloses a radio frequency gain control method, a radio frequency gain control device and communication equipment, which are applied to the technical field of communication and can realize low-cost and high-reliability radio frequency gain control. The method comprises the following steps: acquiring target connection parameters corresponding to the target gain parameters, wherein the target connection parameters are obtained after training a first gain control model based on sample values of a plurality of gain control factors, and the first gain control model is a neural network model which is established aiming at a first radio frequency assembly and is used for carrying out gain control; and configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.

Description

Radio frequency gain control method, device and communication equipment
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to a radio frequency gain control method, a radio frequency gain control device and communication equipment.
Background
The third Generation Partnership Project (3rd Generation Partnership Project, 3gpp) has strict specification requirements on radio frequency gain parameters (including transmission power, transmission power consumption, etc.) of different communication systems (e.g. 2G, 3G, 4G, 5G), so that radio frequency gain control is one of important indexes for measuring the performance of a terminal device, for example, the range and quality of radio frequency signals transmitted by the terminal device can be determined by controlling the transmission power through radio frequency power control. In the existing radio frequency power control scheme of the radio frequency system, power control adjustment is performed on each component of the radio frequency system through two stages of laboratory debugging and factory debugging so as to ensure that the transmission power in the radio frequency system of the terminal equipment meets the 3gpp standard requirement, and power control parameters (which may include power control factors and adjustment weights of the factors) obtained after the debugging are stored in the terminal equipment for subsequent application. However, in the above solution, since the lab requires manual debugging by a chip practitioner, the reliability after debugging is low, and the cost of debugging the device is high in the factory debugging stage, so that it is a problem to be solved urgently to realize the rf gain control with low cost and high reliability.
Disclosure of Invention
The embodiment of the invention provides a radio frequency gain control method, a radio frequency gain control device and communication equipment, which are used for realizing low-cost and high-reliability radio frequency gain control.
In order to solve the above technical problem, the embodiment of the present invention is implemented as follows:
in a first aspect, a radio frequency gain control method is provided, including:
acquiring target connection parameters corresponding to target gain parameters, wherein the target connection parameters are obtained after training a first gain control model based on the sample values of the gain control factors, and the first gain control model is a neural network model which is established for a first radio frequency assembly and is used for performing gain control;
and configuring the plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.
In a second aspect, there is provided a radio frequency gain control apparatus, comprising:
a processor, a memory and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the radio frequency gain control method according to the first aspect.
In a third aspect, there is provided a radio frequency gain control apparatus, comprising:
an obtaining module, configured to obtain a target connection parameter corresponding to a target gain parameter, where the target connection parameter is obtained after training a first gain control model based on sample values of the multiple gain control factors, and the first gain control model is a neural network model established for a first radio frequency component and used for performing gain control;
a configuration module, configured to configure the multiple gain control factors of the first radio frequency component according to the target connection parameter, so as to perform gain control on the first radio frequency component.
In a fourth aspect, there is provided a communication device comprising: a radio frequency gain control apparatus as claimed in the second or third aspect, and a first radio frequency component.
In a fifth aspect, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the radio frequency gain control method according to the first aspect.
A sixth aspect provides a computer program product having a computer program stored thereon, the computer program, when executed by a processor, implementing the radio frequency gain control method according to the first aspect.
The embodiment of the invention provides a radio frequency gain control method, which comprises the steps of obtaining a target connection parameter corresponding to a target gain parameter, wherein the target connection parameter is obtained after training a first gain control model based on a sample value of a plurality of gain control factors, and the first gain control model is a neural network model which is established aiming at a first radio frequency assembly and is used for carrying out gain control; and configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component. Through the scheme, the first gain control model can be trained aiming at the corresponding gain control factors to obtain the target connection parameters corresponding to the target gain parameters, and the gain control factors of the first radio frequency assembly are configured through the target connection parameters, so that the gain control can be carried out on the first radio frequency assembly, the first radio frequency assembly outputs radio frequency signals according to the target gain parameters, the reliability is improved compared with the manual debugging in the prior art, and complicated debugging equipment is not needed, so that the radio frequency gain control with low cost and high reliability can be realized.
Drawings
Fig. 1 is a schematic diagram of a radio frequency system scheme according to an embodiment of the present invention;
fig. 2A is a schematic diagram of an architecture of a radio frequency system according to an embodiment of the present invention;
fig. 2B is a first flowchart illustrating a radio frequency gain control method according to an embodiment of the present invention;
fig. 3 is a second flowchart illustrating a radio frequency gain control method according to an embodiment of the present invention;
fig. 4 is a third schematic flowchart illustrating a radio frequency gain control method according to an embodiment of the present invention;
fig. 5 is a first schematic structural diagram of an rf gain control device according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a radio frequency gain control device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a communication device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "e.g.," an embodiment of the present invention is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
First, the related technical content of the embodiment of the invention is introduced:
as shown in fig. 1, a schematic diagram of a scheme of a wireless Radio frequency system is shown, which mainly includes a baseband chip, a Radio Frequency Integrated Circuit (RFIC), a Radio Frequency Front End (RFFE) chip, and an antenna (antenna).
Research on New Radio (NR) systems currently mainly considers two Frequency bands, Frequency band FR1(Frequency range 1) and Frequency band FR2(Frequency range 2), wherein FR1 and FR2 include Frequency domain ranges as shown in table 1. It should be understood that the embodiments of the present invention may be applied to FR1 and FR2 frequency bands, and may also be applied to other frequency bands, for example, a frequency band from 52.6GHz to 71GHz, or a frequency band from 71GHz to 100GHz, and the like, which is not limited in this application.
Frequency band definition Corresponding frequency band range
FR1 410MHz–7.125GHz
FR2 24.25GHz–52.6GHz
TABLE 1
For FR1 in 2G, 3G, 4G, and NR, a receive (Rx) path and a transmit (Tx) path are provided in the radio frequency front end, and a switch connecting between the receive path or the transmit path and the antenna; a Power Amplifier (PA) matrix is provided in the transmission path.
For FR2 in NR, an antenna and other radio frequency front-end devices have been integrated as a millimeter wave antenna system integrated chip, which mainly includes a phase shifter matrix, a PA matrix, and an antenna matrix.
3gpp has strict specification requirements on radio frequency transmission power of different communication systems (2G, 3G, 4G, 5G), and terminal equipment needs to transmit radio frequency signals strictly according to the transmission power required by network equipment, so radio frequency power control is one of important indexes for measuring the performance of the terminal equipment. The radio frequency power control in the wireless communication system is also implemented by controlling the four modules, i.e., the baseband chip, the radio frequency transceiver chip, the radio frequency front-end chip and the antenna, as shown in fig. 1, and the specific power control scheme is implemented by the following two aspects:
(1) a chip engineer in a laboratory completes debugging of a power control scheme of a part of terminal samples according to chip characteristics and 3gpp standard requirements, controls and adjusts the power of each module, ensures that the transmitting power of an antenna of experimental terminal equipment meets the 3gpp standard requirements, and applies the power control scheme and power control data to all terminal equipment;
(2) after the first-step optimization debugging, all terminal devices can initially normally transmit, but due to the influence of individual differences of internal devices of the terminal devices, the transmission power of the antenna may not necessarily meet the requirement of the 3gpp specification, so that all terminal devices need to be calibrated in a factory, and the power of the antenna port of each terminal device can be ensured to meet the 3gpp specification by calibrating based on the first-step power control scheme and the power control data.
Through the debugging of the power scheme, the power control can be realized, but the following problems exist:
1) the optimization debugging of the chip in the laboratory needs higher requirements on the experience of practitioners, meanwhile, the debugging time is longer, the human factors are uncontrollable, and the power control efficiency of each module cannot be well optimized and combined;
2) in the current scheme, the radio frequency power control is complex, and in order to make the radio frequency power control well, a plurality of power control modes such as a Digital Pre-Distortion (DPD) mode, an Envelope Tracking (ET) mode and the like are introduced, so that the power control becomes complex and the chip cost becomes high;
3) with the increase of communication systems, communication control schemes become complex, power control schemes become more and more complex, factory production calibration time is increased, factory yield is seriously affected, expensive production equipment is needed, a large amount of production resources are occupied, and terminal cost is higher and higher;
4) for the RF2 in NR, the antenna and other RF front-end devices such as PA are already integrated in one chip, and meanwhile, because the communication frequency is high, the conductive line loss is large when the conventional LTE method is used for verification test.
In order to solve the above problems, a low-cost, high-reliability radio frequency gain control is realized. The embodiment of the invention provides a radio frequency gain control method, a radio frequency gain control device and communication equipment, which can obtain a target connection parameter corresponding to a target gain parameter, wherein the target connection parameter is obtained by training a first gain control model based on sample values of a plurality of gain control factors, and the first gain control model is a neural network model which is established aiming at a first radio frequency component and is used for carrying out gain control; and configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.
The radio frequency gain control method provided by the embodiment of the invention can be applied to a radio frequency gain control device or communication equipment, and the radio frequency gain control device can be a functional module or a functional entity for realizing the radio frequency gain control method in the communication equipment.
In the embodiment of the present invention, the related communication device may be a network device or a terminal device.
The terminal device may be referred to as a User Equipment (UE), an access terminal, a subscriber unit, a subscriber station, a mobile station, a remote terminal, a mobile device, a user terminal, a wireless communication device, a user agent, a user equipment, etc.
The terminal device may be a Station (ST) in a WLAN, and may be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with Wireless communication function, a computing device or other processing device connected to a Wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a next generation communication system such as an NR Network, or a terminal device in a future evolved Public Land Mobile Network (PLMN) Network, and the like. In the embodiment of the invention, the terminal equipment can be deployed on land, including indoor or outdoor, handheld, wearable or vehicle-mounted; can also be deployed on the water surface (such as a ship and the like); and may also be deployed in the air (e.g., airplanes, balloons, satellites, etc.).
The terminal device may also be a Mobile Phone (Mobile Phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an Augmented Reality (AR) terminal device, a wireless terminal device in industrial control (industrial control), a wireless terminal device in self driving (self driving), a wireless terminal device in remote medical (remote medical), a wireless terminal device in smart grid (smart grid), a wireless terminal device in transportation safety (transportation safety), a wireless terminal device in smart city (smart city), a wireless terminal device in smart home (smart home), or the like.
The network device related to the embodiment of the invention can be an access network device. The access network device may be a long-term evolution (LTE) system, a Next Radio (NR) system, or an evolved base station (evolved Node B) in an authorized assisted access long-term evolution (LAA-LTE) system, which may be an eNB or an e-NodeB) macro base station, a micro base station (also referred to as a "small base station"), a pico base station, an Access Point (AP), a Transmission Point (TP), or a new generation base station (g-NodeB). In this embodiment of the present invention, the network device may be a device for communicating with a mobile device, and the network device may be an Access Point (AP) in a WLAN, a Base Transceiver Station (BTS) in GSM or CDMA, a Base Station (NodeB, NB) in WCDMA, an evolved Node B (eNB or eNodeB) in LTE, a relay Station or an Access Point, a vehicle-mounted device, a wearable device, and a network device (gNB) in an NR network, or a network device in a PLMN network for future evolution, or a network device in an NTN network. In this embodiment of the present invention, a network device may provide a service for a cell, and a terminal device communicates with the network device through a transmission resource (e.g., a frequency domain resource or a spectrum resource) used by the cell, where the cell may be a cell corresponding to the network device (e.g., a base station), and the cell may belong to a macro base station or a base station corresponding to a Small cell (Small cell), and the Small cell may include: urban cells (Metro cells), Micro cells (Micro cells), Pico cells (Pico cells), Femto cells (Femto cells), and the like, and the small cells have the characteristics of small coverage area and low transmission power, and are suitable for providing high-rate data transmission services.
The technical scheme of the embodiment of the invention can be applied to various communication systems, such as: a Global System for Mobile communications (GSM) System, a Code Division Multiple Access (CDMA) System, a Wideband Code Division Multiple Access (WCDMA) System, a General Packet Radio Service (GPRS), a Long Term Evolution (Long Term Evolution, LTE) System, an Advanced Long Term Evolution (LTE-A) System, a New Radio (NR) System, an Evolution System of an NR System, an LTE (LTE-based Access to unlicensed spectrum, an LTE-U) System on an unlicensed spectrum, an NR (NR-based Access to unlicensed spectrum, an NR-U) System on an unlicensed spectrum, a Non-Terrestrial communication network (UMTS-based network, UMTS) System, a Universal Mobile telecommunications network (UMTS) System, WLAN), Wireless Fidelity (WiFi), a fifth Generation communication (5th-Generation, 5G) system, or other communication systems, etc.
As shown in fig. 2A, a schematic diagram of an architecture of a radio frequency system provided in an embodiment of the present invention is shown, where the radio frequency system includes: a baseband chip, a radio frequency transceiver chip, a radio frequency front-end chip, an antenna, and a neural network chip, where the neural network chip may be a microprocessor (GPU) or a Central Processing Unit (CPU), and the radio frequency gain control method provided in the embodiment of the present invention will be exemplarily described below with reference to the schematic architecture diagram of the radio frequency system shown in fig. 2A.
As shown in fig. 2B, a schematic flow chart of a radio frequency gain control method according to an embodiment of the present invention is shown, where the method flow includes:
201. and acquiring target connection parameters corresponding to the target gain parameters.
The first gain control model is a neural network model which is established for the first radio frequency component and used for gain control, and the target connection parameters are obtained after the first gain control model is trained on sample values based on a plurality of gain control factors.
Optionally, a plurality of sets of corresponding relationships between gain parameters and connection parameters may be stored in the communication device in advance. For example, the following table 2 is an exemplary description in which n sets of gain parameters and connection parameters are stored in the form of a correspondence table.
Gain parameter 1 Connection parameter 1
Gain parameter 2 Connection parameter 2
Gain parameter 3 Connection parameter 3
…… ……
Gain parameter n Connection parameter n
TABLE 2
Optionally, the communication device may pre-store a correspondence between the target gain parameter and the target connection parameter, for example, the correspondence between the target gain parameter and the target connection parameter may be one of the n stored correspondences, where n is greater than or equal to 2.
Since the manner of obtaining the connection parameter corresponding to the gain parameter is the same for different gain parameters and connection parameters, the following takes a specific process of obtaining the target connection parameter corresponding to the target gain parameter as an exemplary description.
Before the above 201, the communication device may first train the first gain control model based on sample values of a plurality of gain control factors of the first radio frequency component to obtain a target gain control model, and then correspondingly store a target gain parameter and a target connection parameter for the plurality of gain control factors, where the target connection parameter includes: the connection weights and bias values between any two adjacent hidden layers of the target gain control model.
The error between the first gain parameter output by the target gain control model and the target gain parameter is smaller than or equal to a first error threshold, and the first gain control model is a neural network model which is established aiming at the first radio frequency component and is used for carrying out gain control.
The training process may be performed one or more times during the process of training the first gain control model to obtain the target gain control model based on the gain control factors of the first rf component. Specifically, the following training steps a, b, and c may be performed in a loop until an error between the gain parameter output by the adjusted first gain control model and the target transmission gain is less than or equal to a first error threshold, and the adjusted first gain control model is used as the target gain control model.
a. A plurality of gain control factors of the first radio frequency component are input into the first gain control model.
b. And acquiring the gain parameter output by the first gain control model.
c. And adjusting the connection parameters in the first gain control model according to the error between the gain parameters output by the first gain control model and the target gain parameters.
Wherein the connection parameters include: the connection weights and bias values between any two adjacent hidden layers of the first gain control model.
The number of times of cyclically executing the training steps a, b and c may be one or more, so as to enable the error between the gain parameter output by the first gain control model and the target gain parameter to be less than or equal to the first error threshold.
It should be noted that, in the embodiment of the present invention, the first error threshold may be set according to the training precision of the first gain control model, which is not limited in the embodiment of the present invention.
In an embodiment of the present invention, the first rf component may include one or more devices in an rf system. Optionally, taking the radio frequency system shown in fig. 2A as an example, the first radio frequency component includes at least one of the following components:
(A) a baseband chip;
correspondingly, the first gain control model is a neural network model which is established for the baseband chip and used for carrying out gain control.
(B) A baseband chip and a radio frequency transceiver chip;
correspondingly, the first gain control model is a neural network model which is established aiming at the baseband chip and the radio frequency transceiver chip and is used for carrying out gain control.
(C) The radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip and a radio frequency front end;
correspondingly, the first gain control model is a neural network model which is established for the baseband chip, the radio frequency transceiver chip and the radio frequency front end and is used for performing gain control.
(D) The radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip, a radio frequency front end and an antenna;
correspondingly, the first gain control model is a neural network model which is established for the baseband chip, the radio frequency transceiver chip, the radio frequency front end and the antenna and is used for carrying out gain control.
(E) The radio frequency transceiver chip and the radio frequency front end;
correspondingly, the first gain control model is a neural network model which is established for the radio frequency transceiver chip and the radio frequency front end and is used for performing gain control.
(F) The radio frequency transceiver chip, the radio frequency front end and the antenna;
correspondingly, the first gain control model is a neural network model which is established for the radio frequency transceiver chip, the radio frequency front end and the antenna and is used for performing gain control.
(G) A radio frequency front end and an antenna;
correspondingly, the first gain control model is a neural network model which is established for the radio frequency front end and the antenna and is used for carrying out gain control.
(H) An antenna.
Correspondingly, the first gain control model is a neural network model established for the antenna for performing gain control.
Optionally, the gain control according to the embodiment of the present invention includes but is not limited to at least one of the following:
1. transmit power control, i.e. control of the transmit power for the first radio frequency component;
2. transmission power consumption control, i.e. control of the transmission power consumption for the first radio frequency component;
3. received signal strength control, i.e., control of received signal strength for the first radio frequency component.
The following will describe the rf gain control method provided in the embodiment of the present invention in detail by taking the gain control as the transmit power control as an example:
in the rf system shown in fig. 2A, the transmitting power P is mainly determined by the baseband chip, the rf transceiver chip, the rf front-end chip and the antenna.
In communication systems, rf power control is a typical multi-factor control problem. Optionally, the factors affecting the power control of the baseband chip, the radio frequency transceiver chip, the radio frequency front end, and the antenna are respectively as follows:
the power control factors of the baseband chip mainly include: signal strength, frequency, temperature, device process level, etc. In the embodiment of the invention, X represents a set of sample values of a power control factor of a baseband chip, and X is ═ X1,x2,x3...xi]Wherein x is1,x2,x3...xiSample values representing i different power control factors of the baseband chip, wherein i is greater than or equal to 2;
the power control factors of the radio frequency transceiver chip mainly include: various stages of power amplifiers, channels, temperature, voltage, device process levels, etc. In the embodiment of the invention, Y represents a set of sample values of power control factors of a radio frequency transceiver chip, and Y is [ Y ═ Y [ ]1,y2,y3...yj]Wherein, y1,y2,y3...yjSample values representing j different power control factors of the radio frequency transceiver chip, wherein j is greater than or equal to 2;
the power control factors of the radio frequency front end chip mainly include: power amplifier, voltage, temperature, device process level, device Printed Circuit Board (PCB) layout, etc. In the embodiment of the invention, Z represents a set of power control factor sample values of a radio frequency front-end chip, and Z is [ Z ═1,z2,z3...zm]Wherein z is1,z2,z3...zmSample values representing m different power control factors of a radio frequency front-end chip, wherein m is greater than or equal to 2;
the power control factors of the antenna mainly include: antenna shape, working frequency range, temperature, PCB layout modeAnd the like. In the embodiment of the invention, V represents a set of power control factor sample values of an antenna, and V is ═ V1,v2,v3...vn]Wherein v is1,v2,v3...vnSample values representing n power control factors for the antenna.
Because radio frequency power control in wireless communication is a typical multi-factor control problem, the embodiment of the invention provides that a neural network control unit is adopted to carry out self-learning training on the performance of each radio frequency component, dynamic power distribution of each radio frequency component based on power control factors is realized, and the transmitting power of a terminal is ensured to be in an optimal state.
In the embodiment of the present invention, the power control process for components in a radio frequency system based on a neural network may be divided into: 1) the method comprises a self-learning training stage and a 2) training result using stage, wherein the self-learning training stage 1) is specifically realized as follows:
1) a self-learning training stage, in which a Multi-layer neural network (MLP) algorithm is used for learning and training, and the stage mainly includes static analysis and learning of the influence of power control factors of each component in a radio frequency system on power, and the specific algorithm is implemented as follows:
the MLP neural network algorithm is the most effective multi-layer neural network learning method, and is mainly characterized in that signals are transmitted in a forward direction, errors are propagated in a backward direction, and the final output of the neural network is enabled to be as close to the expected output as possible by continuously adjusting connection parameters (including weight values and bias values) in the neural network; with reference to the radio frequency system shown in fig. 2A in the embodiment of the present invention, an algorithm process is described by taking a first radio frequency component composed of a baseband chip and a radio frequency transceiver chip as an example, where a neural network model is constructed, and a corresponding neural network model (i.e., a first gain control model) may be defined as follows:
an input layer: the input to the neural network is XY ═ x1,x2,x3...xi,y1,y2,y3...yj](ii) a Wherein X represents a set of sample values of the power control factor of the baseband chip, Y represents a set of sample values of the power control factor of the radio frequency transceiver chip, and X1,x2,x3...xiSample values representing i different power control factors of the baseband chip, i being greater than or equal to 2, y1,y2,y3...yjAnd j is greater than or equal to 2 and represents sample values of j different power control factors of the radio frequency transceiver chip.
An output layer: p ═ P1,p2,p3...pk]Where P represents the set of transmit powers obtained from training in the training process, P1,p2,p3...pkIn the k training processes, the output transmission power after each training is obtained, wherein k is greater than or equal to 1.
Hidden layer: h(l)Representing the neuron output of the l-th hidden layer,
Figure BDA0003211024000000101
wherein L is greater than or equal to 1 and less than or equal to L, s is the number of layer I neurons,
Figure BDA0003211024000000102
respectively representing the outputs of different s neurons;
suppose that
Figure BDA0003211024000000103
Represents the connection weight from the r-th neuron of the l-1 layer to the t-th neuron of the l layer,
Figure BDA0003211024000000104
represents the bias value of the t-th neuron of the l layer,
Figure BDA0003211024000000105
and
Figure BDA0003211024000000106
i.e. connection parameters, then
Figure BDA0003211024000000107
And for layer 1 in the hidden layer,
Figure BDA0003211024000000108
where f () is the activation function of the neuron.
A neural network model from the power control factor to the output transmitting power can be established according to the functional expression, and the connection parameters corresponding to each hidden layer can be updated through repeated training for k times, namely
Figure BDA0003211024000000109
And
Figure BDA00032110240000001010
so that the error between the finally calculated transmission power and the preset target transmission power is smaller than or equal to the first error threshold, and the trained neural network model is considered as a target power control model (corresponding to the target gain control model).
Further, the target power control model can be obtained
Figure BDA00032110240000001011
And
Figure BDA00032110240000001012
and will be
Figure BDA00032110240000001013
And
Figure BDA00032110240000001014
and storing the data in the communication equipment for later use in power control.
Optionally, the learnt
Figure BDA0003211024000000111
And
Figure BDA0003211024000000112
stored in a Non-Volatile Memory (NVM).
202. And configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.
Wherein the target connection parameters include: the connection weights and bias values between any two adjacent hidden layers of the target gain control model.
Optionally, configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter includes: calculating target values of the plurality of gain control factors according to the target connection parameters and the sample values of the plurality of gain control factors; and configuring a plurality of gain control factors of the first radio frequency component according to the target values of the plurality of gain control factors so as to control the gain of the first radio frequency component.
Further, the calculating the target values of the gain control factors according to the target connection parameters and the sample values of the gain control factors includes: performing a first operation according to the target connection parameter and the sample values of the plurality of gain control factors to obtain target values of the plurality of gain control factors; the first operation is an inverse operation for the trained first gain control model. Here, the trained first gain control model is the target gain control model, that is, the first operation is an inverse operation for the target gain control model.
According to the radio frequency gain control method provided by the embodiment of the invention, the target connection parameter corresponding to the target gain parameter can be obtained, the target connection parameter is obtained after training the first gain control model based on the sample values of a plurality of gain control factors, and the first gain control model is a neural network model which is established aiming at the first radio frequency component and is used for carrying out gain control; and configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component. Through the scheme, the first gain control model can be trained aiming at the corresponding gain control factors to obtain the target connection parameters corresponding to the target gain parameters, and the gain control factors of the first radio frequency assembly are configured through the target connection parameters, so that the gain control can be carried out on the first radio frequency assembly, the first radio frequency assembly outputs radio frequency signals according to the target gain parameters, the reliability is improved compared with the manual debugging in the prior art, and complicated debugging equipment is not needed, so that the radio frequency gain control with low cost and high reliability can be realized.
As shown in fig. 3, a schematic flow chart of another rf gain control method provided in the embodiment of the present invention is shown, where the method flow includes:
301. and training the first gain control model based on the sample values of the gain control factors of the first radio frequency component to obtain the target gain control model.
Optionally, for an embodiment in which the first rf component includes at least one of (E), (F), (G), and (H), the above 301 may further need to introduce an input gain parameter as an input for training the first gain control model. That is, obtaining the target gain control model may include: the first gain control model is trained based on a plurality of gain control factors of the first radio frequency component and the input gain parameters to obtain a target gain control model.
The input gain parameter is a gain parameter of a second radio frequency component, and the second radio frequency component inputs a radio frequency signal to the first radio frequency component.
Optionally, the input gain parameter is a gain parameter of the second rf component after gain control.
For example, assuming that the first rf component is (E) an rf transceiver chip and an rf front end, the second rf component may be a baseband chip.
As an example, assume that the first rf component is (F) an rf transceiver chip, an rf front end, and an antenna; the second radio frequency component may be a baseband chip.
Illustratively, assume that the first radio frequency component is a (G) radio frequency front end and antenna; the second rf component may be an rf transceiver chip and a baseband chip, or the second rf component may be an rf transceiver chip.
For example, assuming that the first rf component is an (H) antenna, the second rf component may be an rf front end, an rf transceiver chip and a baseband chip, or the second rf component may be an rf front end.
302. And correspondingly storing the target gain parameters and the target connection parameters aiming at the plurality of gain control factors.
Wherein the target connection parameters include: the connection weights and bias values between any two adjacent hidden layers of the target gain control model.
Through the above 301 and 302, the first gain control model may be trained for a plurality of corresponding gain control factors, the obtained target gain control model with the first gain parameter close to the target gain parameter is obtained, and the target gain parameter and the target connection parameter corresponding to the target gain control model are stored, so that the correspondingly stored target connection data may be used as a parameter for performing power control when the target gain parameter needs to be output subsequently.
303. And acquiring target connection parameters corresponding to the target gain parameters.
The target connection parameter is obtained by training the first gain control model based on the sample values of the gain control factors, that is, obtained through 301 and 302.
304. And configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.
The above 303 and 304 correspond to the above 2) training result using stage, in which the target transmission power corresponding to the first radio frequency component may be determined first, and the target connection parameter stored in the previous training result and matched with the target transmission power is obtained from the communication device, and according to the target connection parameter, a plurality of power control factors of the first radio frequency component are configured to perform power control on the first radio frequency component.
In some optional implementations, since the communication device has different requirements for the radio frequency gain parameter in different application scenarios, at this stage, the current application scenario of the communication device may be identified first, and the target gain parameter of the first radio frequency component corresponding to the current application scenario is determined.
That is to say, in the embodiment of the present invention, before the foregoing 301, taking the communication device applied by the method as a terminal device as an example, a current application scenario of the terminal device may also be determined according to usage data of the terminal device, and then a target gain parameter (such as a target transmit power) of the first radio frequency component corresponding to the current application scenario is determined.
Wherein the usage data of the terminal device comprises at least one of the following:
(1) the residual capacity of the terminal equipment;
(2) the temperature of the terminal device;
(3) holding mode of the terminal device;
(4) serving base station of the terminal device.
In a possible implementation manner, when it is determined that the terminal device is currently in a low power scene according to the remaining power of the terminal device, the transmission power needs to be reduced in the scene to save the power consumption of the terminal device.
In a possible implementation manner, when it is determined that the terminal device is currently in a high-temperature scene according to the temperature of the terminal device, in order to avoid overheating of the terminal device in the scene, the transmission power may be reduced, so as to reduce a problem of terminal device heating caused by a higher transmission power of the terminal device.
In another possible implementation manner, when it is determined that the terminal device is in a non-use state according to a holding manner of the terminal device, the transmission power may be reduced; when the terminal device is in a use state, the transmission power can be increased, so that the limitation of the transmission distance of the terminal device due to the limitation of the transmission power in the process of using the terminal device is avoided.
In another possible implementation manner, a corresponding transmission power range configured by a serving base station for a current scenario of a terminal device may be determined according to the serving base station of the terminal device, and the transmission power of the terminal device may be determined within the transmission power range. Optionally, the transmit power of the terminal device may be selected in consideration of other factors (e.g., remaining power of the terminal device, temperature of the terminal device, etc.) within the transmit power range.
It should be noted that, besides the usage parameters of several terminal devices shown in (1), (2), (3) and (4), the usage scenario of the terminal device may also be determined by the usage parameters of other terminal devices.
Optionally, in the embodiment of the present invention, a neural network model for identifying a usage scenario of the terminal device may be further established, and the neural network model is trained according to usage parameters of the terminal device in different scenarios, so as to obtain a scenario identification model. In subsequent use, the use parameters of the terminal device acquired in real time can be used as the input of the scene recognition model, the current application scene output by the scene recognition model correspondingly is acquired, the target transmission power of the first radio frequency assembly corresponding to the current application scene is determined, and then the target connection parameters stored in the terminal device correspondingly can be determined according to the target transmission power.
It should be noted that, the above describes taking gain control as transmit power control as an example, and for implementation manners of other gain controls, such as transmit power consumption, received signal strength, and the like, the implementation manners are similar to the implementation manner of the transmit power control process, and details are not repeated in the embodiments of the present invention.
In some possible implementations, a self-learning training flag may be employed to identify whether trained target connection parameters for the first radio frequency component are stored in the communication device.
If the self-learning training mark exists in the terminal equipment, the fact that the corresponding target connection parameter of the first radio frequency component already exists in the terminal equipment is indicated, and subsequent gain control can be carried out; if the self-learning training mark does not exist in the terminal equipment, it is indicated that the target connection parameter stored aiming at the first radio frequency component does not exist in the terminal equipment, and the target connection parameter needs to be acquired through neural network training.
The target connection parameter is a connection parameter obtained from a target gain control model, the error between a first gain parameter output by the target gain control model and the target gain parameter is smaller than or equal to a first error threshold, and the first gain control model is a neural network model which is established aiming at a first radio frequency assembly and is used for carrying out gain control.
According to the radio frequency gain control method provided by the embodiment of the invention, the target connection parameter corresponding to the target gain parameter can be obtained, the target connection parameter is obtained after training the first gain control model based on the sample values of a plurality of gain control factors, and the first gain control model is a neural network model which is established aiming at the first radio frequency component and is used for carrying out gain control; and configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component. Through the scheme, the first gain control model can be trained aiming at the corresponding gain control factors to obtain the target connection parameters corresponding to the target gain parameters, and the gain control factors of the first radio frequency assembly are configured through the target connection parameters, so that the gain control can be carried out on the first radio frequency assembly, the first radio frequency assembly outputs radio frequency signals according to the target gain parameters, the reliability is improved compared with the manual debugging in the prior art, and complicated debugging equipment is not needed, so that the radio frequency gain control with low cost and high reliability can be realized.
Optionally, as shown in fig. 4, an embodiment of the present invention further provides a gain control method, where the method includes:
401. and acquiring target connection parameters corresponding to the target gain parameters.
402. And configuring a plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.
The target connection parameter is obtained by the terminal device through the embodiments 301 and 302 shown in fig. 3, and the target connection parameter and the target gain parameter are stored in the communication device correspondingly.
403. And acquiring the actual gain parameter output by the first radio frequency component.
Optionally, in the embodiment of the present invention, the actual gain parameter and the target gain parameter are corresponding physical quantities, for example, when the target gain parameter indicates a physical quantity of the transmission power, the actual gain parameter also indicates the physical quantity of the transmission power; when the target gain parameter indicates the physical quantity of transmission power consumption, the actual gain parameter also indicates the physical quantity of transmission power consumption.
When the target gain parameter indicates a physical quantity, i.e., transmission power, the actual gain parameter may be transmission power actually detected in the radio frequency system.
The transmission power in the rf system varies non-linearly with the power control factor, and a saturation region may occur. In the embodiment of the invention, a power feedback point can be set in the radio frequency system to detect the actual transmitting power after power control so as to evaluate the effect of power control.
As shown in fig. 2A, M is a power feedback point located between the rf transceiver chip and the rf front end, at which the actual transmission power of the point may be detected by a power sensor, and the target gain control model is further optimized by using the actual transmission power to obtain updated target connection parameters.
In fig. 2A, the point M is mainly to evaluate the transmission power of the first rf component composed of the baseband chip and the rf transceiver chip, and if there is a large error between the actual transmission power detected according to the point M and the target transmission power during the previous training, the training of the first rf component composed of the baseband chip and the rf transceiver chip can be continued.
404. An error of the actual gain parameter from the target gain parameter is determined.
Aiming at power control, the actual gain parameter is the actual transmitting power detected by the M point, the target gain parameter is the target transmitting power, and the error between the actual transmitting power and the target transmitting power is determined.
405. And if the error between the actual gain parameter and the target gain parameter is greater than a second error threshold, training a target gain control model based on a plurality of gain control factors of the first radio frequency component.
The relationship between the error between the actual transmitting power and the target transmitting power and the second error threshold can be judged, and when the error between the actual gain parameter and the target gain parameter is greater than the second error threshold, it is described that after the power control is performed on the baseband chip and the radio frequency transceiver chip according to the target connection parameter stored corresponding to the target transmitting power, the obtained actual transmitting power has a larger deviation with the expected target transmitting power, so that the target connection parameter stored in the middle may need to be updated, so as to enable the matching degree in the subsequent power control.
It should be noted that, in the embodiment of the present invention, the second error threshold may be the same as or different from the first error threshold, and may be specifically set according to the training accuracy of the first gain control model and the target gain control model, which is not limited herein.
406. And updating the target connection parameters stored corresponding to the target gain parameters according to the trained target gain control model until the error between the first gain parameters and the target gain parameters is less than or equal to a third error threshold.
Wherein the third error threshold is less than the first error threshold.
When the error between the actual gain parameter and the target gain parameter is greater than the second error threshold, it can be said that the target connection parameter used in the current power control does not meet the actual power control requirement, therefore, the current target power control model can be further trained, when the training is carried out again, the control range of the error can be reduced, namely, the first error threshold is changed into a third error threshold with smaller value, so when the error between the first gain parameter and the target gain parameter is less than or equal to the third error threshold as the condition of training cut-off, the trained target gain control model which better meets the actual power control requirement can be obtained, the target connection parameters which are correspondingly stored with the target gain parameters are updated by the trained target gain control model, it can be ensured that the restored target connection parameters can be closer to the actual power control requirements.
In the above embodiment, a power feedback point is set in the actual radio frequency system, so that after the training result is subjected to power control according to the embodiment of the present invention, the training result (i.e., the connection parameter) stored before the training result is compared with the target transmission power, so that when the error between the training result and the target transmission power is large, it can be stated that the training result (i.e., the connection parameter) stored before is not matched in the actual application, so that the target gain control model trained between the training results can be continuously retrained again based on the actual transmission power to obtain the optimized gain control model, the target connection parameter is extracted from the optimized gain control model, and the target connection parameter stored corresponding to the target gain parameter is updated. Further, in the radio frequency system shown in fig. 2A, the power feedback point may also be set at other positions, specifically, the setting of the position of the power feedback point matches the setting of the first radio frequency component defined in the embodiment of the present invention.
For example, as shown in fig. 2A, a power feedback point may be further set at N, and the actual transmission power is detected by the power inductor, and accordingly, the first rf component may be in the following cases:
(D) the radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip, a radio frequency front end and an antenna;
(F) the radio frequency transceiver chip, the radio frequency front end and the antenna;
(G) a radio frequency front end and an antenna;
(H) an antenna.
Referring to fig. 2A, a power feedback point N is located at an antenna port, and is mainly used for evaluating a final transmission power of a terminal device, in an embodiment of the present invention, when the first radio frequency component includes a radio frequency front end and an antenna, performance of the radio frequency front end and the antenna may be analyzed, if a larger error exists between an actual transmission power detected according to the point N and a target transmission power in a previous training, training may be continued on the first radio frequency component including the radio frequency front end and the antenna, and training may be performed on other radio frequency components at an upper end of the radio frequency front end and the antenna in a communication system again, for example, training may be performed on a radio frequency component including a baseband chip and a radio frequency transceiver chip.
Since the rf front end and the antenna are easily affected by the device layout and other environmental factors in the terminal device, and different affecting factors may be generated for different products, and the baseband chip and the rf transceiver chip are less affected by the outside than the baseband chip and the rf transceiver chip, the rf gain control may be performed for the rf component composed of the baseband chip and the rf transceiver chip according to the method in the embodiment, and the rf gain control may be performed for the rf component composed of the rf front end and the antenna.
When training the neural network for the rf component composed of the rf front-end chip and the antenna, a training process similar to the above-described training process for the rf component composed of the baseband chip and the rf transceiver chip may be performed, where the difference is that for the input layer, the input of the neural network is ZV ═ z1,z2,z3...zm,v1,v2,v3...vn]Wherein Z represents a set of power control factor sample values of the radio frequency front-end chip, V represents a set of power control factor sample values of the antenna, and Z1,z2,z3...zmSample values representing m different power control factors of a radio frequency front-end chip, wherein m is greater than or equal to 2; v. of1,v2,v3...vnSample values representing n power control factors for the antenna.
Optionally, the radio frequency transceiver chip may also be used as an input of the neural network according to a gain parameter (e.g., transmission power) after the gain control, so as to train the neural network.
Furthermore, when power control is performed, each module in the radio frequency system needs to be in a linear working interval to avoid being in a saturated working interval, and meanwhile, the transmission power is required to be in continuous linear change to avoid saturation interval and discontinuous change of the power control.
As shown in fig. 5, an embodiment of the present invention provides an rf gain control apparatus, including:
an obtaining module 501, configured to obtain a target connection parameter corresponding to a target gain parameter, where the target connection parameter is obtained after training a first gain control model based on sample values of multiple gain control factors, and the first gain control model is a neural network model established for a first radio frequency component and used for performing gain control;
a configuration module 502, configured to configure a plurality of gain control factors of the first rf component according to the target connection parameter, so as to perform gain control on the first rf component.
Optionally, the configuration module 502 is specifically configured to perform a first operation according to the target connection parameter and the sample values of the multiple gain control factors to obtain target values of the multiple gain control factors; the first operation is an inverse operation aiming at the trained first gain control model;
and configuring a plurality of gain control factors of the first radio frequency component according to the target values of the plurality of gain control factors so as to control the gain of the first radio frequency component.
Optionally, the rf gain control device further includes:
a training module 503, configured to train the first gain control model based on sample values of multiple gain control factors of the first radio frequency component before the obtaining module 501 obtains the target connection parameter corresponding to the target gain parameter, so as to obtain the target gain control model, where an error between the first gain parameter output by the target gain control model and the target gain parameter is smaller than or equal to a first error threshold;
a saving module 504, configured to correspondingly save the target gain parameter and the target connection parameters for the multiple gain control factors, where the target connection parameters include: the connection weights and bias values between any two adjacent hidden layers of the target gain control model.
Optionally, the training module 503 is specifically configured to:
the following training steps are performed in a loop:
inputting a plurality of gain control factors of a first radio frequency component into a first gain control model;
acquiring a gain parameter output by a first gain control model;
adjusting the connection parameters in the first gain control model according to the error between the gain parameters output by the first gain control model and the target gain parameters;
and taking the adjusted first gain control model as the target gain control model until the error between the gain parameter output by the adjusted first gain control model and the target transmission gain is less than or equal to a first error threshold.
Optionally, the first radio frequency component includes any one of:
a baseband chip;
a baseband chip and a radio frequency transceiver chip;
the radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip and a radio frequency front end;
the radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip, a radio frequency front end and an antenna;
the radio frequency transceiver chip and the radio frequency front end;
the radio frequency transceiver chip, the radio frequency front end and the antenna;
a radio frequency front end and an antenna;
an antenna.
Optionally, the first radio frequency component comprises any one of the following;
the radio frequency transceiver chip and the radio frequency front end;
the radio frequency transceiver chip, the radio frequency front end and the antenna;
a radio frequency front end and an antenna;
an antenna;
the training module 503 is specifically configured to:
training the first gain control model based on sample values of a plurality of gain control factors of the first radio frequency component and input gain parameters to obtain a target gain control model;
the input gain parameter is a gain parameter of a second radio frequency component, and the second radio frequency component is a radio frequency component for inputting radio frequency signals to the first radio frequency component.
Optionally, the training module 503 is further configured to: acquiring an actual gain parameter output by a first radio frequency assembly;
determining an error between the actual gain parameter and the target gain parameter;
and if the error between the actual gain parameter and the target gain parameter is equal to or smaller than a second error threshold, training the target gain control model based on sample values of a plurality of gain control factors of the first radio frequency component, knowing that the error between the first gain parameter and the target gain parameter is smaller than or equal to a third error threshold, and updating a target connection parameter which is stored corresponding to the target gain parameter according to the target gain control model obtained after training, wherein the third error threshold is smaller than the first error threshold.
Optionally, the training module 503 is further configured to: configuring a plurality of gain control factors of a first radio frequency assembly according to the target connection parameters so as to determine the current application scene of the terminal equipment according to the use data of the terminal equipment before performing gain control on the first radio frequency assembly;
determining a target gain parameter of a first radio frequency component corresponding to a current application scene;
wherein the usage data comprises at least one of:
remaining power, temperature, holding mode, serving base station.
Optionally, the gain control comprises at least one of:
controlling the transmission power;
controlling transmission power consumption;
and controlling the strength of the received signal.
As shown in fig. 6, an embodiment of the present invention further provides a radio frequency gain control apparatus, where the radio frequency control apparatus includes: a memory 601 and a processor 602, and a computer program stored on the memory 601 and executable on the processor 602, wherein the computer program when executed by the processor can implement the rf gain control method in the above method embodiments.
Optionally, the rf gain control apparatus may be a radio frequency system as shown in fig. 2A, or the rf gain control apparatus may include the radio frequency system as shown in fig. 2A, and the function of the processor 602 in fig. 6 may be implemented by a neural network chip (e.g., GPU) in the radio frequency system as shown in fig. 2A, or the function of the processor 602 in fig. 6 may be implemented by a neural network chip and a baseband chip in the radio frequency system as shown in fig. 2A, where the neural network chip may be used to mainly implement a training process for the gain control model, for example, a training process for the first gain control model and the target gain control model, and the baseband chip may be used to mainly implement a process for performing power control by using connection parameters (e.g., target connection parameters) of the trained gain control model after training.
As shown in fig. 7, an embodiment of the present invention provides a communication device, including: a radio frequency gain control device 701 and a first radio frequency component 702.
Alternatively, the rf gain control device 701 in the communication device shown in fig. 7 may be as shown in fig. 6, or, as the rf gain control device shown in fig. 5, the first rf component 702 in fig. 7 may be implemented by any one of the following components in fig. 2A:
a baseband chip;
a baseband chip and a radio frequency transceiver chip;
the radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip and a radio frequency front end;
the radio frequency transceiver comprises a baseband chip, a radio frequency transceiver chip, a radio frequency front end and an antenna;
the radio frequency transceiver chip and the radio frequency front end;
the radio frequency transceiver chip, the radio frequency front end and the antenna;
a radio frequency front end and an antenna;
an antenna.
An embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the radio frequency gain control method provided in the foregoing method embodiments is implemented, and the same technical effect can be achieved, and in order to avoid repetition, details are not repeated here.
The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (13)

1. A method for radio frequency gain control, comprising:
acquiring target connection parameters corresponding to target gain parameters, wherein the target connection parameters are obtained after training a first gain control model based on the sample values of the gain control factors, and the first gain control model is a neural network model which is established for a first radio frequency assembly and is used for performing gain control;
and configuring the plurality of gain control factors of the first radio frequency component according to the target connection parameter so as to perform gain control on the first radio frequency component.
2. The method of claim 1, wherein configuring a plurality of gain control factors for the first rf component according to the target connection parameter comprises:
performing a first operation according to the target connection parameter and the sample values of the gain control factors to obtain target values of the gain control factors; the first operation is an inverse operation for the trained first gain control model;
and configuring the plurality of gain control factors of the first radio frequency component according to the target values of the plurality of gain control factors so as to perform gain control on the first radio frequency component.
3. The method according to claim 1, wherein before obtaining the target connection parameter corresponding to the target gain parameter, the method further comprises:
training a first gain control model based on sample values of the gain control factors of the first radio frequency component to obtain a target gain control model, wherein the error between a first gain parameter output by the target gain control model and the target gain parameter is smaller than or equal to a first error threshold;
correspondingly saving the target gain parameters and target connection parameters for the plurality of gain control factors, wherein the target connection parameters comprise: connection weights and bias values between any two adjacent hidden layers of the target gain control model.
4. The method of claim 3, wherein training a first gain control model based on sample values of the gain control factors of the first RF component to obtain a target gain control model comprises:
the following training steps are performed in a loop:
inputting sample values of a plurality of gain control factors of the first radio frequency component into the first gain control model;
acquiring a gain parameter output by the first gain control model;
adjusting a connection parameter in the first gain control model according to an error between a gain parameter output by the first gain control model and the target gain parameter;
and taking the adjusted first gain control model as the target gain control model until the error between the gain parameter output by the adjusted first gain control model and the target transmission gain is less than or equal to a first error threshold.
5. The method of any of claims 1 to 4, wherein the first radio frequency component comprises any of:
a baseband chip;
the baseband chip and the radio frequency transceiver chip;
the baseband chip, the radio frequency transceiver chip and the radio frequency front end;
the baseband chip, the radio frequency transceiver chip, the radio frequency front end and the antenna;
the radio frequency transceiver chip and the radio frequency front end;
the radio frequency transceiver chip, the radio frequency front end and the antenna;
the radio frequency front end and the antenna;
the antenna.
6. The method of claim 3, wherein the first radio frequency component comprises any one of;
the radio frequency transceiver chip and the radio frequency front end;
the radio frequency transceiver chip, the radio frequency front end and the antenna;
the radio frequency front end and the antenna;
the antenna;
the sample values of the gain control factors based on the first radio frequency component are used for training a first gain control model to obtain a target gain control model, including:
training the first gain control model based on sample values of a plurality of gain control factors of the first radio frequency component and input gain parameters to obtain a target gain control model;
the input gain parameter is a gain parameter of a second radio frequency component, and the second radio frequency component is a radio frequency component which inputs a radio frequency signal to the first radio frequency component.
7. The method of claim 3, wherein after configuring the plurality of gain control factors of the first RF component to gain control the first RF component according to the target connection parameter, further comprising:
acquiring an actual gain parameter output by the first radio frequency component;
determining an error of the actual gain parameter from the target gain parameter;
if the error between the actual gain parameter and the target gain parameter is greater than a second error threshold, training the target gain control model based on sample values of the gain control factors until the error between the first gain parameter and the target gain parameter is less than or equal to a third error threshold, updating the target connection parameter stored corresponding to the target gain parameter according to the trained target gain control model, wherein the third error threshold is less than the first error threshold.
8. The method of claim 1, wherein before configuring the plurality of gain control factors of the first radio frequency component to gain control the first radio frequency component according to the target connection parameter, the method further comprises:
determining a current application scene of the terminal equipment according to the use data of the terminal equipment;
determining the target gain parameter of a first radio frequency component corresponding to the current application scenario;
wherein the usage data comprises at least one of:
remaining power, temperature, holding mode, serving base station.
9. The method of claim 1, wherein the gain control comprises at least one of:
controlling the transmission power;
controlling transmission power consumption;
and controlling the strength of the received signal.
10. A radio frequency gain control apparatus, comprising:
a processor, a memory and a program or instructions stored on the memory and executable on the processor, the program or instructions when executed by the processor implementing the radio frequency gain control method of any one of claims 1 to 9.
11. A radio frequency gain control apparatus, comprising:
an obtaining module, configured to obtain a target connection parameter corresponding to a target gain parameter, where the target connection parameter is obtained after training a first gain control model based on sample values of the multiple gain control factors, and the first gain control model is a neural network model established for a first radio frequency component and used for performing gain control;
a configuration module, configured to configure the multiple gain control factors of the first radio frequency component according to the target connection parameter, so as to perform gain control on the first radio frequency component.
12. A communication device, comprising: the radio frequency gain control apparatus of claim 10 or 11, and the first radio frequency component.
13. A computer-readable storage medium, comprising: a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the radio frequency gain control method of any one of claims 1 to 9.
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