Data processing method and device, equipment and storage medium

Abstract

The invention discloses a data processing method and device, equipment and a storage medium. The method comprises the following steps: acquiring a power compensation value of a terminal in an antenna mismatch state; acquiring the downlink signal strength of the network equipment; and compensating the downlink signal strength of the network equipment based on the power compensation value of the terminal in the antenna mismatch state to obtain the compensated downlink signal strength of the network equipment.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a data processing method, device, equipment and storage medium. Background Art

[0002] At present, the existing network obtains the network deployment status by means of many terminals participating in the test, that is, the terminal reports the received base station signal strength such as the reference signal received power (RSRP) and its corresponding location information to the network. The network analyzes the large amount of "public test" data obtained and provided by the terminal, and regards the area with weak RSRP as a weak coverage area, and may optimize the network for the weak coverage area. However, in some cases, the base station signal strength such as RSRP measured by the terminal may be inaccurate, which may lead to deviations in the judgment decision on whether network optimization is needed. Summary of the invention

[0003] In view of this, embodiments of the present application hope to provide a data processing method, apparatus, device and storage medium.

[0004] The technical solution of the embodiment of the present application is implemented as follows:

[0005] The present application provides a data processing method, which is applied to a first device, and the method includes:

[0006] Obtaining a power compensation value of a terminal in an antenna mismatch state;

[0007] Get the downlink signal strength of the network device;

[0008] Based on the power compensation value of the terminal in the antenna mismatch state, the downlink signal strength of the network device is compensated to obtain the compensated downlink signal strength of the network device.

[0009] In addition, according to at least one embodiment of the present application, the acquiring a power compensation value of the terminal in an antenna mismatch state includes:

[0010] Obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0011] Obtaining actual output power of the antenna of the terminal;

[0012] A power compensation value of the terminal in an antenna mismatch state is determined based on the actual output power of the antenna of the terminal and the reflection coefficient.

[0013] In addition, according to at least one embodiment of the present application, the acquiring a power compensation value of the terminal in an antenna mismatch state includes:

[0014] Obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0015] Obtaining the uplink signal strength of the terminal;

[0016] Obtaining a first path loss between the terminal and the network device;

[0017] A power compensation value of the terminal in an antenna mismatch state is determined based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient.

[0018] In addition, according to at least one embodiment of the present application, the method further includes:

[0019] The obtaining of a power compensation value of the terminal in an antenna mismatch state includes:

[0020] Obtaining reflected power of the terminal at an antenna port;

[0021] Determine at least one value according to the power value of the reflected power, wherein any one of the at least one value is less than or equal to the power value of the reflected power;

[0022] A value is selected from the at least one value as a power compensation value of the terminal in an antenna mismatch state.

[0023] In addition, according to at least one embodiment of the present application, the method further includes:

[0024] When the downlink signal strength of the network device after the compensation is less than a preset signal strength threshold, determining that the area where the terminal is located is a downlink weak coverage area;

[0025] When it is determined that the area where the terminal is located is a downlink weak coverage area, it is necessary to perform a network optimization operation.

[0026] In addition, according to at least one embodiment of the present application, the method further includes:

[0027] Acquire a power headroom report sent by the terminal; the power headroom report includes a power headroom value;

[0028] Obtaining a second path loss between the terminal and the network device according to the compensated downlink signal strength of the network device;

[0029] When the power headroom value is less than a preset power headroom threshold and the second path loss is greater than a preset path loss threshold, determining that the area where the terminal is located is an uplink weak coverage area;

[0030] When it is determined that the area where the terminal is located is an uplink weak coverage area, it is necessary to perform a network optimization operation.

[0031] In addition, according to at least one embodiment of the present application, the method further includes:

[0032] Acquire a first information set; the first information set includes a power headroom report sent by the terminal in a p-antenna mismatch state, and time information and / or location information of the terminal in the p-antenna mismatch state; the power headroom report includes a power headroom value; p is an integer greater than or equal to 1;

[0033] Selecting m power headroom values ​​corresponding to the m antenna mismatch states from the first information set; wherein the m power headroom values ​​are all less than a preset power headroom threshold, m is an integer greater than or equal to 1, and m is less than or equal to p;

[0034] Selecting time information and / or location information corresponding to the m power headroom values ​​from the first information set;

[0035] Based on the time information and / or location information corresponding to the m power headroom values, it is determined whether to perform a network optimization operation.

[0036] In addition, according to at least one embodiment of the present application, the determining whether to perform a network optimization operation based on the time information and / or location information corresponding to the m power headroom values ​​includes:

[0037] Based on the time information corresponding to the m power headroom values, m weights are determined; the m weights are multiplied by the downlink signal strength of the network device after compensation obtained under the corresponding m antenna mismatch states to obtain a first downlink signal strength; when the first downlink signal strength is less than a preset signal strength threshold, the area where the terminal is located is determined to be an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, a network optimization operation needs to be performed;

[0038] and / or,

[0039] For each location information corresponding to the m power margin values, when the downlink signal strength of the network device after compensation corresponding to the corresponding location information is less than a preset signal strength threshold, the area where the terminal is located is determined to be an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, it is necessary to perform network optimization operations.

[0040] In addition, according to at least one embodiment of the present application, the acquiring a power compensation value of the terminal in an antenna mismatch state includes: acquiring a power compensation value of the terminal in different antenna mismatch states;

[0041] The compensating the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state includes: compensating the downlink signal strength of the network device respectively based on the power compensation value of the terminal in different antenna mismatch states;

[0042] The method further comprises:

[0043] Comparing the downlink signal strengths of the network device after compensation obtained under different antenna mismatch states to obtain a comparison result;

[0044] When the comparison result indicates that the downlink signal strengths of the network device after compensation under different antenna mismatch states are the same, it is determined that the network coverage of the area where the terminal is located has not changed.

[0045] In addition, according to at least one embodiment of the present application, the method further includes:

[0046] Obtaining an artificial intelligence / machine learning (AI / ML) model, wherein the AI / ML model is used to perform the aforementioned data processing method;

[0047] The training data of the AI / ML model includes:

[0048] A power compensation value of the terminal under different antenna mismatch states;

[0049] or,

[0050] The power compensation value of the terminal in different antenna mismatch states, and the time information and / or location information of the terminal in different antenna mismatch states.

[0051] In addition, according to at least one embodiment of the present application, the AI / ML model is trained by the network device, or trained by operation administration maintenance (OAM), or trained by the terminal.

[0052] The present application provides a data processing method, which is applied to a terminal. The method includes:

[0053] Determining a power compensation value of the terminal in an antenna mismatch state;

[0054] Sending a power compensation value of the terminal in an antenna mismatch state to the first device;

[0055] The power compensation value is used by the first device to compensate for the acquired downlink signal strength of the network device, so as to obtain the compensated downlink signal strength of the network device.

[0056] In addition, according to at least one embodiment of the present application, determining the power compensation value of the terminal in the antenna mismatch state includes:

[0057] Acquire, by means of a power sensing module of the terminal, the reflected power of the terminal at the antenna port, and acquire the input power of the terminal at the antenna port;

[0058] Based on the reflected power and the input power, obtaining a reflection coefficient of the terminal in an antenna mismatch state;

[0059] Based on the reflection coefficient, perform one of the following operations:

[0060] Acquire the actual output power of the antenna of the terminal; determine the power compensation value of the terminal in the antenna mismatch state based on the actual output power of the antenna of the terminal and the reflection coefficient;

[0061] Acquire the uplink signal strength of the terminal, and acquire a first path loss between the terminal and the network device; determine a power compensation value of the terminal in an antenna mismatch state based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient;

[0062] or,

[0063] The reflected power of the terminal at the antenna port is obtained through the power sensing module of the terminal; at least one numerical value is determined according to the power value of the reflected power, wherein any one of the at least one numerical value is less than or equal to the power value of the reflected power; and a numerical value is selected from the at least one numerical value as the power compensation value.

[0064] In addition, according to at least one embodiment of the present application, the method further includes:

[0065] Sending a power headroom report to the first device; the power headroom report comprising a power headroom value;

[0066] The power headroom value is used by the first device to determine whether to perform a network optimization operation in combination with the downlink signal strength of the network device after the compensation.

[0067] In addition, according to at least one embodiment of the present application, the method further includes:

[0068] Acquire time information and / or location information of the terminal in different antenna mismatch states;

[0069] Sending the time information and / or the location information to the first device;

[0070] Among them, the time information and / or location information is used by the first device to determine whether to perform network optimization operations in combination with the downlink signal strength of the network device after compensation, or is used by the first device to train an AI / ML model in combination with the power compensation value of the terminal in an antenna mismatch state.

[0071] The present application provides a data processing device, including:

[0072] An acquisition module is used to obtain a power compensation value of a terminal in an antenna mismatch state; and obtain a downlink signal strength of a network device;

[0073] The first processing module is used to compensate the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state to obtain the compensated downlink signal strength of the network device.

[0074] The present application provides a data processing device, including:

[0075] A second processing module, used to determine a power compensation value of the terminal in an antenna mismatch state;

[0076] The sending module is used to send the power compensation value of the terminal in the antenna mismatch state to the first device.

[0077] At least one embodiment of the present application provides a device, including a processor and a memory for storing a computer program that can be run on the processor.

[0078] Wherein, when the processor is used to run the computer program, it executes the steps of any one of the methods described above on the device side.

[0079] At least one embodiment of the present application provides a terminal, including a processor and a memory for storing a computer program that can be run on the processor.

[0080] Wherein, when the processor is used to run the computer program, it executes the steps of any one of the methods described above on the terminal side.

[0081] At least one embodiment of the present application provides a storage medium having a computer program stored thereon, wherein the computer program implements the steps of any of the above methods when executed by a processor.

[0082] The data processing method, device, equipment and storage medium provided in the embodiments of the present application obtain the power compensation value of the terminal in the antenna mismatch state; obtain the downlink signal strength of the network device; based on the power compensation value of the terminal in the antenna mismatch state, compensate the downlink signal strength of the network device to obtain the downlink signal strength of the network device after compensation. By adopting the technical solution provided in the embodiments of the present application, when the terminal is in the antenna mismatch state, by compensating the downlink signal strength of the network device, the downlink signal strength of the network device at the location of the terminal can be truly evaluated, which can facilitate the subsequent judgment and decision on whether to perform network optimization operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a schematic diagram of improving terminal power loss through an antenna tuning module in the related art;

[0084] Figure 2 This is a schematic diagram of the implementation process of the data processing method of the embodiment of the present application Figure 1 ;

[0085] Figure 3 This is a schematic diagram of the implementation process of the data processing method of the embodiment of the present application Figure 2 ;

[0086] Figure 4 This is a schematic diagram of the system architecture of the data processing method of the embodiment of the present application;

[0087] Figure 5 This is a schematic diagram of the specific implementation process of the data processing method of the embodiment of the present application. Figure 1 ;

[0088] Figure 6 This is a schematic diagram of the specific implementation process of the data processing method of the embodiment of the present application. Figure 2 ;

[0089] Figure 7 The structure diagram of the data processing device in the embodiment of the present application is shown in FIG. Figure 1 ;

[0090] Figure 8 The structure diagram of the data processing device in the embodiment of the present application is shown in FIG. Figure 2 ;

[0091] Fig. 9 It is a schematic diagram of the composition structure of the device of the embodiment of the present application;

[0092] Fig.10 It is a schematic diagram of the composition structure of the terminal of the embodiment of the present application. DETAILED DESCRIPTION

[0093] Before introducing the technical solutions of the embodiments of the present application, the related technologies will be introduced first.

[0094] In the related technologies, the current network obtains the network deployment situation through the method of "crowdsourcing testing" of terminals (a large number of terminals participate in the testing). That is, the terminal reports the received base station signal strength, such as the reference signal received power (RSRP, Reference Signal Receiver Power), and its corresponding location information to the network together. The network analyzes based on the large amount of "crowdsourcing testing" data obtained from the terminals, regards the area with a weaker RSRP as a weak coverage area, and may need to perform network optimization for this weak coverage area. Or, by using the cell reference signal (CRS, Cell Reference Signal) sent by the base station and the base station downlink reference signal strength measured by the terminal, such as RSRP, the path loss (PL, Path Loss) is calculated, and then combined with the power headroom report (PHR, Power Headroom) reported by the terminal to determine whether there is a weak coverage situation in the current network. Specifically, if the PL is small (for example: PL < 100 dB) and the PHR < 0 (that is, the terminal cannot further increase the uplink power), then it is inclined to judge that there is a weak coverage situation in the current network and network optimization such as adding a site needs to be carried out.

[0095] However, if the RSRP measured by the terminal is inaccurate, it will lead to inaccurate calculation of the PL, and further lead to a deviation in the judgment decision on whether network optimization is needed. The base station signal strength received by the terminal, such as RSRP, is not only related to the actual network coverage level of the current network, but also closely related to the terminal receiving antenna efficiency and the terminal usage scenario (whether there is shielding material around, etc.). When the terminal usage scenario is the same, the base station signal strength (such as RSRP) measured by the terminal is generally mainly related to the receiving antenna efficiency of the terminal. For example: when the antenna efficiency of a certain terminal UE1 at the operating frequency f1 is X%, the RSRP signal strength of the terminal UE1 measuring base station A is RSRP1; when the terminal UE1 does not change its position (the network coverage situation where the terminal UE1 is located does not change), since the user's hand gesture covers the operating frequency f1, at this time the antenna efficiency of the terminal at the operating frequency f1 drops to Y% (Y < X), then the RSRP signal strength RSRP2 of the terminal UE1 measuring base station A at this time < RSRP1. Therefore, there is a situation where the same terminal is at the same position in the cell, but the received base station RSRP signal strength is different.

[0096] Generally, terminal antenna mismatch will lead to reduced antenna efficiency, and there are many reasons for terminal antenna mismatch. For example, if there is an impedance mismatch between the antenna and the RF front-end chip, the terminal will suffer at least 1dB signal strength loss; in different holding postures, the user's hand-held position may cover the terminal antenna, causing the area around the terminal antenna to become a non-free space, affecting signal transmission, which may lead to a signal strength loss of about 3dB. If the "public test" data reported by the terminal shows that the RSRP strength value of a certain cell or a certain cell is low, it may be decided that the network needs to be optimized for the cell or the cell. Therefore, if a large number of antenna mismatch terminals appear in the existing network, the network side will make a negative evaluation of the existing network coverage level that is lower than the actual coverage level, which may lead to the operator making a decision to "need to optimize the network" and increase the number of base station deployments. It can be seen that the low base station signal strength received by the terminal due to the terminal antenna mismatch will likely cause the operator to pay more unnecessary network planning and optimization costs.

[0097] Therefore, accurately understanding the mismatch of the terminal antenna will help the network accurately understand the actual coverage of the existing network and avoid unnecessary network planning and optimization costs for operators. In order to improve the signal strength loss problem caused by antenna mismatch, the relevant technology provides an antenna tuning module, which can improve the signal strength loss caused by antenna mismatch to a certain extent.

[0098] See also Figure 1 , Figure 1 is a schematic diagram of improving terminal power loss through an antenna tuning module in the related art, such as Figure 1 As shown, the parameter control bit of the antenna tuning module in the related art is generally 2 to 3 bits. By presetting parameters, open-loop control (closed-loop system without feedback) is performed, and tuning is performed according to frequency band changes (different tuning parameters are selected according to the frequency band of the terminal). The antenna tuning module can provide 4 to 8 types of antenna impedance matching networks. However, the related art is limited by the inability to optimize according to the actual scenario and the limited accuracy of the tuning matching network, resulting in a very limited tuning effect. It can be seen that there is no method in the prior art that can completely eliminate the mismatch of the terminal antenna, and thus it is still impossible to solve the problem of loss of terminal received signal strength caused by the mismatch of the terminal antenna.

[0099] The embodiments of the present application aim to enable the network to accurately grasp the actual coverage of the existing network when the terminal antenna mismatch cannot be eliminated, thereby avoiding unnecessary network planning and optimization cost expenditures for operators.

[0100] Based on this, in an embodiment of the present application, a power compensation value of the terminal in an antenna mismatch state is obtained; the downlink signal strength of the network device is obtained; based on the power compensation value of the terminal in the antenna mismatch state, the downlink signal strength of the network device is compensated to obtain the downlink signal strength of the network device after compensation.

[0101] In the embodiment of the present application, the downlink signal strength of the network device may refer to the downlink signal strength of the network device received by the terminal in an antenna mismatch state.

[0102] See also Figure 2 , Figure 2 This is a schematic diagram of the implementation flow of the data processing method of the embodiment of the present application, which is applied to the first device, wherein the first device includes but is not limited to a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station, the base station includes but is not limited to a 5G wireless access network, a 6G wireless access network, a 7G wireless access network, etc.), a terminal, an OAM, etc. The method includes steps 201 to 203:

[0103] Step 201: Obtain a power compensation value of a terminal in an antenna mismatch state.

[0104] As an example, the antenna mismatch state may refer to energy reflection when the antenna is mismatched, resulting in transmission energy loss. There are many reasons for the terminal antenna mismatch, for example, if there is an impedance mismatch between the antenna and the RF front-end chip, the terminal may suffer a signal strength loss of more than 1dB; in different holding postures, the user's hand-held position may cover the terminal antenna, causing the area around the terminal antenna to become non-free space, affecting signal transmission, and causing a signal strength loss of about 3dB or more.

[0105] As an example, the antenna mismatch state may include one or more. For example, there are multiple holding postures that cause signal strength loss, wherein one holding posture corresponds to one antenna mismatch state.

[0106] Considering that when the terminal is in an antenna mismatch state, the downlink signal strength of the network device received by the terminal will be lost, that is, due to the problem of the terminal itself, the downlink signal strength of the network device received and perceived by the terminal is inconsistent with the actual signal strength of the network device at the location of the terminal, and there may be a large deviation. In the embodiment of the present application, when the terminal is in an antenna mismatch state, in order to obtain an accurate and real downlink signal strength of the network device at the location of the terminal, a power compensation value of the terminal in the antenna mismatch state can be determined, and the power compensation value is used to compensate the downlink signal strength of the network device obtained by the terminal, so as to obtain an accurate and real downlink signal strength of the network device at the location of the terminal.

[0107] As an example, the power compensation value of the terminal in the antenna mismatch state may refer to a power compensation value for compensating for the downlink signal receiving power of the terminal in the antenna mismatch state.

[0108] The following describes a process for obtaining a power compensation value of a terminal in an antenna mismatch state.

[0109] In some embodiments, the acquiring a power compensation value of the terminal in an antenna mismatch state includes:

[0110] Obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0111] Obtaining actual output power of the antenna of the terminal;

[0112] A power compensation value of the terminal in an antenna mismatch state is determined based on the actual output power of the antenna of the terminal and the reflection coefficient.

[0113] Specifically, they may include:

[0114] First, obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0115] As an example, a power sensing module can be added inside the terminal, wherein the power sensing module can implement a mismatch sensing function, and through the power sensing module, the reflected power B at the antenna port can be obtained; the power sensing module can also obtain the input power A (also called incident power A) at the antenna port.

[0116] According to the following formula, the reflection coefficient Γ of the antenna of the terminal in the antenna mismatch state is calculated:

[0117]

[0118] Wherein, Γ represents the reflection coefficient of the antenna of the terminal in the antenna mismatch state, B represents the reflection power at the antenna port, and A represents the input power at the antenna port of the terminal.

[0119] Here, the mismatch degree of the terminal antenna can be known through the reflection coefficient Γ. For example, if the reflection coefficient Γ is 0, it means that the terminal antenna is in a non-mismatched state. Otherwise, it means that the terminal antenna is in a mismatched state.

[0120] Here, when the executor of the data processing method, that is, the first device, is a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station), or one of OAM, the first device can obtain the reflection coefficient corresponding to the antenna mismatch state sent by the terminal.

[0121] Second, the actual output power of the antenna of the terminal is obtained.

[0122] As an example, the actual output power of the antenna of the terminal may refer to the actual output power emitted by the terminal through the antenna when the terminal is in an antenna mismatch state.

[0123] The actual output power P transmitted by the terminal through the antenna when the terminal is in the antenna mismatch state can be obtained through the reflection coefficient Γ. UE .

[0124] According to the following formula, the actual output power P of the antenna of the terminal is calculated: UE :

[0125]

[0126] Among them, P UE represents the actual output power emitted by the terminal through the antenna when the terminal is in the antenna mismatch state, B represents the reflected power at the antenna port, and Γ represents the reflection coefficient of the antenna of the terminal in the antenna mismatch state.

[0127] Here, when the executor of the data processing method, that is, the first device, is a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station), or an OAM, the first device can obtain the reflection coefficient corresponding to the antenna mismatch state sent by the terminal and the reflection power at the antenna port of the terminal, and obtain the actual output power of the antenna of the terminal based on the reflection coefficient corresponding to the antenna mismatch state and the reflection power at the antenna port of the terminal.

[0128] Third, based on the actual output power of the antenna of the terminal and the reflection coefficient, a power compensation value of the terminal in an antenna mismatch state is obtained.

[0129] According to the following formula, the power compensation value of the terminal in the antenna mismatch state is calculated:

[0130]

[0131] Among them, P C represents the power compensation value of the terminal in the antenna mismatch state, P UE represents the actual output power transmitted by the terminal through the antenna when the terminal is in the antenna mismatch state, and Γ represents the reflection coefficient of the antenna of the terminal in the antenna mismatch state.

[0132] In some embodiments, the acquiring a power compensation value of the terminal in an antenna mismatch state includes:

[0133] Obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0134] Obtaining the uplink signal strength of the terminal;

[0135] Obtaining a first path loss between the terminal and the network device;

[0136] A power compensation value of the terminal in an antenna mismatch state is determined based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient.

[0137] Specifically, they may include:

[0138] First, obtain the reflection coefficient corresponding to the antenna mismatch state.

[0139] As an example, a power sensing module can be added inside the terminal, wherein the power sensing module can implement a mismatch sensing function. Through the power sensing module, the reflected power B at the antenna port can be obtained. Through the power sensing module, the input power A (also referred to as incident power A) at the antenna port can also be obtained.

[0140] According to the following formula, the reflection coefficient Γ of the antenna of the terminal in the antenna mismatch state is calculated:

[0141]

[0142] Wherein, Γ represents the reflection coefficient of the antenna of the terminal in the antenna mismatch state, B represents the reflection power at the antenna port, and A represents the input power at the antenna port of the terminal.

[0143] Here, the mismatch degree of the terminal antenna can be known through the reflection coefficient Γ. For example, if the reflection coefficient Γ is 0, it means that the terminal antenna is in a non-mismatched state. Otherwise, it means that the terminal antenna is in a mismatched state.

[0144] Here, when the executor of the data processing method, that is, the first device, is a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station), or one of OAM, the first device can obtain the reflection coefficient corresponding to the antenna mismatch state sent by the terminal.

[0145] Second, the uplink signal strength of the terminal is obtained.

[0146] As an example, the uplink signal strength of the terminal may refer to the uplink signal strength of the terminal received by the network device when the terminal is in an antenna mismatch state.

[0147] The uplink signal strength of the terminal received by the network device is calculated according to the following formula:

[0148] P gNB =P UE -L

[0149] Among them, P gNB Indicates the terminal signal strength received by the network device (such as a base station), P UE It represents the actual output power transmitted by the terminal through the antenna when the terminal is in the antenna mismatch state, and L represents the first path loss between the terminal and the network device, in dB.

[0150] According to the following formula, calculate the actual output power P emitted by the terminal through the antenna when the terminal is in the antenna mismatch state: UE :

[0151]

[0152] Among them, P UE represents the actual output power emitted by the terminal through the antenna when the terminal is in an antenna mismatch state, B represents the reflected power at the antenna port of the terminal, and Γ represents the reflection coefficient of the antenna of the terminal in the antenna mismatch state.

[0153] Here, when the executor of the data processing method, that is, the first device, is a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station), or an OAM, the first device can obtain the uplink signal strength of the terminal sent by the terminal.

[0154] Third, a first path loss between the terminal and the network device is obtained.

[0155] As an example, the downlink reference signal strength sent by the network device to the terminal and the downlink reference signal strength measured by the terminal may be subtracted to obtain a first path loss between the terminal and the network device when the terminal is in an antenna mismatch state.

[0156] Here, when the executor of the data processing method, that is, the first device, is a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station), or an OAM, the first device can obtain the first path loss between the terminal and the network device sent by the terminal.

[0157] Fourth, based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient, a power compensation value of the terminal in an antenna mismatch state is acquired.

[0158] According to the following formula, the power compensation value of the terminal in the antenna mismatch state is calculated:

[0159]

[0160] Among them, P C represents the power compensation value of the terminal in the antenna mismatch state, P gNB represents the uplink signal strength of the terminal received by the network device (such as a base station), L represents the first path loss between the terminal and the network device, and Γ represents the reflection coefficient of the antenna of the terminal in an antenna mismatch state.

[0161] In some embodiments, the acquiring a power compensation value of the terminal in an antenna mismatch state includes:

[0162] Obtaining reflected power of the terminal at an antenna port;

[0163] Determine at least one value according to the power value of the reflected power, wherein any one of the at least one value is less than or equal to the power value of the reflected power;

[0164] A value is selected from the at least one value as the power compensation value.

[0165] That is to say, the power compensation value is not greater than the numerical value of the reflected power.

[0166] Here, when the power compensation value is equal to the power value of the reflected power, the terminal will be compensated to a state where the terminal antenna is completely not mismatched (similar to the free space state). However, in actual use, it may not be necessary to compensate the terminal antenna to the free space state. Therefore, based on the power value of the reflected power, a value not greater than the power value of the reflected power can be determined as the power compensation value.

[0167] Here, the power value of the reflected power is represented by B, the power compensation value is represented by Pc, and the relationship between B and Pc can be described by the power compensation coefficient C, where C=Pc / B, and the value of C can be determined by the operator. When C=1, the terminal can be compensated to the ideal state of antenna lossless transmission.

[0168] Step 202: Obtain the downlink signal strength of the network device.

[0169] As an example, the downlink signal strength of the network device may refer to the downlink signal strength of the network device received by the terminal in an antenna mismatch state.

[0170] Here, when the executor of the data processing method, that is, the first device, is a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), a network device (such as a base station), or one of OAM, the first device can obtain the downlink signal strength of the network device sent by the terminal.

[0171] Step 203: Compensate the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state to obtain the compensated downlink signal strength of the network device.

[0172] As an example, compensating the downlink signal strength of the network device may refer to summing the downlink signal strength value of the network device received by the terminal in the antenna mismatch state with the power compensation value of the terminal in the antenna mismatch state to obtain the compensated downlink signal strength value of the network device.

[0173] As an example, the power compensation value and the downlink signal strength of the network device have the same unit, which is dBm.

[0174] In some embodiments, the method further comprises:

[0175] When the downlink signal strength of the network device after the compensation is less than a preset signal strength threshold, a network optimization operation needs to be performed.

[0176] As an example, when the downlink signal strength of the compensated network device is less than a preset signal strength threshold, the area where the terminal is located is determined to be a downlink weak coverage area; when it is determined that the area where the terminal is located is a downlink weak coverage area, a network optimization operation needs to be performed.

[0177] As an example, the downlink weak coverage area may refer to an area where the signal sent by the network device to the terminal is relatively weak, or may refer to an area where the signal strength transmitted by the network device is less than a certain threshold.

[0178] For example, assume that RSRPn_m+Pcm represents the downlink signal strength of the network device after compensation of terminal n, wherein RSRPn_m represents the downlink signal strength of the network device obtained by terminal n in antenna mismatch state m, and Pcm represents the power compensation value of terminal n in antenna mismatch state m. If RSRPn_m+Pcm is less than the preset signal strength threshold, it is determined that the area where the terminal is located is a downlink weak coverage area, and network optimization operations need to be performed.

[0179] As an example, performing the network optimization operation may refer to increasing the number of base stations in the area where the terminal is located, etc.

[0180] In some embodiments, the method further comprises:

[0181] Acquire a power headroom report sent by the terminal; the power headroom report includes a power headroom value;

[0182] Obtaining a second path loss between the terminal and the network device according to the compensated downlink signal strength of the network device;

[0183] In a case where the power headroom value is less than a preset power headroom threshold and the second path loss is greater than a preset path loss threshold, a network optimization operation needs to be performed.

[0184] As an example, when the power margin value is less than a preset power margin threshold and the second path loss is greater than a preset path loss threshold, it is determined that the area where the terminal is located is an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, it is necessary to perform network optimization operations.

[0185] As an example, the uplink weak coverage area may refer to an area where the signal sent by the terminal to the network device is relatively weak, or may refer to an area where the signal strength transmitted by the terminal is less than a certain threshold.

[0186] As an example, the second path loss between the terminal and the network device may be obtained by subtracting the downlink reference signal strength sent by the network device to the terminal from the downlink signal strength of the network device after compensation.

[0187] For example, assuming that PHR is used to represent the power headroom value and PL is used to represent the second path loss, when PHR is less than 0 and PL is greater than a preset path loss threshold, a network optimization operation needs to be performed.

[0188] As an example, performing the network optimization operation may refer to increasing the number of base stations in the area where the terminal is located, etc.

[0189] It should be noted that when judging whether the area where the terminal is located is an uplink weak coverage area, first look at the PHR: if PHR>0, it is directly judged as a non-weak coverage area and no uplink network optimization is required; if PHR<0, first judge the reason for PHR<0. If PHR<0 is not caused by the interference index of the cell where the terminal is located reaching a certain level, then further judge the PL. If PL is greater than the preset path loss threshold, it can be determined that the area where the terminal is located is an uplink weak coverage area and network optimization operations need to be performed.

[0190] In some embodiments, the method further comprises:

[0191] Acquire a first information set; the first information set includes a power headroom report sent by the terminal in a p-antenna mismatch state, and time information and / or location information of the terminal in the p-antenna mismatch state; the power headroom report includes a power headroom value; p is an integer greater than or equal to 1;

[0192] Selecting m power headroom values ​​corresponding to the m antenna mismatch states from the first information set; wherein the m power headroom values ​​are all less than a preset power headroom threshold, m is an integer greater than or equal to 1, and m is less than or equal to p;

[0193] Selecting time information and / or location information corresponding to the m power headroom values ​​from the first information set;

[0194] Based on the time information and / or location information corresponding to the m power headroom values, it is determined whether to perform a network optimization operation.

[0195] In some embodiments, the determining whether to perform a network optimization operation based on time information and / or location information corresponding to the m power headroom values ​​includes:

[0196] Based on the time information corresponding to the m power headroom values, m weights are determined; the m weights are multiplied by the downlink signal strength of the network device after compensation obtained under the corresponding m antenna mismatch states to obtain a first downlink signal strength; when the first downlink signal strength is less than a preset signal strength threshold, a network optimization operation needs to be performed;

[0197] and / or,

[0198] For each piece of position information corresponding to the m power headroom values, when the downlink signal strength of the network device after compensation corresponding to the corresponding position information is less than a preset signal strength threshold, a network optimization operation needs to be performed.

[0199] As an example, when the first downlink signal strength is less than a preset signal strength threshold, the area where the terminal is located is determined to be an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, a network optimization operation needs to be performed.

[0200] As an example, when the downlink signal strength of the network device after compensation corresponding to the corresponding location information is less than a preset signal strength threshold, the area where the terminal is located is determined to be an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, network optimization operations need to be performed.

[0201] As an example, the time information may refer to the duration of the terminal being in the antenna mismatch state, or may refer to the moment when the terminal is in the antenna mismatch state. For example, T is used to represent the time information. If T is equal to 3 minutes, it means that the duration of the terminal being in the antenna mismatch state is 3 minutes. If T is equal to 8 o'clock, it means that the moment when the terminal is in the antenna mismatch state is 8 o'clock.

[0202] As an example, the location information may refer to geographical location information of the terminal when it is in an antenna mismatch state. For example, P represents the location information, and assuming that P is cell A in city A, it means that the geographical location of the terminal when it is in an antenna mismatch state is cell A in city A.

[0203] First, m power margin values ​​corresponding to m antenna mismatch states are selected from the first information set, and the m power margin values ​​are all less than a preset power margin threshold, which are represented by PHR1, PHR2, ..., PHRm respectively. Time information corresponding to the m power margin values ​​is selected from the first information set, which are represented by T1, T2, ..., Tm respectively. Position information corresponding to the m power margin values ​​is selected from the first information set, which are represented by P1, P2, ..., Pm respectively.

[0204] Then, the downlink signal strength of the network device after compensation obtained by terminal n in the m antenna mismatch state is determined, and is represented by RSRPn_1+Pc1, RSRPn_2+Pc2, ..., RSRPn_m+Pcm respectively, where Pcm represents the power compensation value of terminal n in the antenna mismatch state m.

[0205] Finally, when the time information represents the duration of the terminal being in the antenna mismatch state, the duration corresponding to each antenna mismatch state is summed to obtain the total duration, and the duration corresponding to each antenna mismatch state is ratioed to the total duration to obtain the weight corresponding to each downlink signal strength. The greater the corresponding duration, the greater the weight of the downlink signal strength. The downlink signal strength values ​​corresponding to different durations are multiplied by the corresponding weights to obtain the first downlink signal strength. When the first downlink signal strength is less than the preset signal strength threshold, a network optimization operation needs to be performed.

[0206] For example, there are three antenna mismatch states. The downlink signal strength of the network device after compensation of the terminal in the three antenna mismatch states is represented by RSRP1+Pc1, RSRP2+Pc2, and RSRP3+Pc3, respectively. The corresponding durations are 1 minute, 2 minutes, and 3 minutes, respectively. The larger the duration, the greater the weight of the downlink signal strength. Multiply the downlink signal strength values ​​corresponding to different durations by the corresponding weights to obtain the first downlink signal strength RSRP=(RSRP1+Pc1)×(1 / 6)+(RSRP2+Pc2)×(2 / 6)+(RSRP3+Pc3)×(3 / 6), where 6 refers to the total duration of 6 minutes, that is, 1 minute, 2 minutes, and 3 minutes are summed to obtain 6 minutes, and the weights are 1 / 6, 2 / 6, and 3 / 6, respectively. If the first downlink signal strength value is less than the preset signal strength threshold, it is necessary to perform network optimization operations.

[0207] In the case where the time information represents the moment when the terminal is in an antenna mismatch state, the duration corresponding to each antenna mismatch state is counted, the duration corresponding to each antenna mismatch state is summed to obtain the total duration, the duration corresponding to each antenna mismatch state is ratioed to the total duration, and the weight corresponding to each downlink signal strength is obtained. The greater the corresponding duration, the greater the weight of the downlink signal strength. The downlink signal strength values ​​corresponding to different durations are multiplied by the corresponding weights to obtain the first downlink signal strength. When the first downlink signal strength is less than the preset signal strength threshold, a network optimization operation needs to be performed.

[0208] For example, there are four antenna mismatch states. The downlink signal strength of the network device after compensation of the terminal in the four antenna mismatch states is represented by RSRP1+Pc1, RSRP2+Pc2, RSRP3+Pc3, and RSRP4+Pc4, respectively, and the corresponding times are 8:00, 8:01, 8:02, and 8:03, respectively. Among them, the time periods corresponding to (RSRP1+Pc1) and (RSRP3+Pc3) are 8:00 to 8:01 and 8:02 to 8:03, respectively, with a total duration of 2 minutes. The time period corresponding to (RSRP2+Pc2) is 8:01 to 8:02, with a total duration of 1 minute. The total duration corresponding to (RSRP4+Pc4) is 0 minute. The larger the corresponding duration, the greater the weight of the downlink signal strength. The downlink signal strength values ​​corresponding to different durations are multiplied by the corresponding weights to obtain the first downlink signal strength RSRP = (RSRP1 + Pc1) × (1 / 3) + (RSRP2 + Pc2) × (1 / 3) + (RSRP3 + Pc3) × (1 / 3) + (RSRP4 + Pc4) × (0 / 3), where 3 refers to the total duration of 3 minutes, that is, 2 minutes, 1 minute, and 0 minutes are summed to get 3 minutes, and the weights are 1 / 3, 1 / 3, 1 / 3, and 0 / 3 respectively. If the first downlink signal strength value is less than the preset signal strength threshold, it is necessary to perform network optimization operations.

[0209] For each location information corresponding to the m power margin values, when the downlink signal strength of the network device after compensation corresponding to the corresponding location information is less than a preset signal strength threshold, the area where the terminal is located is determined to be an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, it is necessary to perform network optimization operations.

[0210] For example, there are three antenna mismatch states. The downlink signal strength of the network device after compensation of the terminal in the three antenna mismatch states is represented by RSRP1+Pc1, RSRP2+Pc2, and RSRP3+Pc3, respectively. The corresponding geographical locations are cell 1, cell 1, and cell 2 in city A. If the RSRP1+Pc1 corresponding to cell 1 is less than the preset signal strength threshold, it is necessary to perform network optimization operations; if the RSRP2+Pc2 corresponding to cell 1 is less than the preset signal strength threshold, it is necessary to perform network optimization operations; if the RSRP3+Pc3 corresponding to cell 2 is less than the preset signal strength threshold, it is necessary to perform network optimization operations.

[0211] It should be noted that when a network optimization operation needs to be performed, the time for performing the network optimization operation can also be indicated. For example, assuming that the indicated time for performing the network optimization operation is 8 o'clock in the evening, the network optimization operation will be performed at 8 o'clock in the evening.

[0212] It should be noted that when it is necessary to perform a network optimization operation, the geographical location range in which the network optimization operation can be performed can also be indicated. For example, assuming that it is determined through judgment that cell 1 where the terminal is located needs to perform a network optimization operation, but cell 1 does not belong to the geographical location range in which the network optimization operation can be performed, then cell 1 cannot perform the network optimization operation.

[0213] It should be noted that after obtaining the downlink signal strength of the network device after compensation, the terminal may be in the following two situations:

[0214] In the first case, the terminal is still in an antenna mismatch state. The antenna mismatch state may mean that when the antenna is mismatched, energy reflection may occur, resulting in transmission energy loss.

[0215] As an example, when the terminal is in an antenna mismatch state, the reflection coefficient Γ of the antenna is not equal to 0, and the reflection power B at the antenna port is not equal to 0.

[0216] In the second case, the terminal is in a non-antenna mismatch state, and the non-antenna mismatch state may mean that when the antenna is completely matched, lossless transmission of terminal power can be achieved.

[0217] As an example, when the terminal is in a non-antenna mismatch state, the reflection coefficient Γ of the antenna is equal to 0, and the reflection power B at the antenna port is equal to 0.

[0218] In this way, when performing network optimization operations on a large number of terminals, for example, assuming that the total number of terminals in the antenna mismatch state is 100, after compensating for the downlink signal strength of the network device received by the terminal, assuming that 20 of the 100 terminals are still in the antenna mismatch state, that is, the antenna reflection coefficient is not 0, and the remaining 80 terminals are in the non-antenna mismatch state, that is, the antenna reflection coefficient is 0. In this case, for the 100 terminals, the downlink signal strength of the network device after compensation is used to determine whether to perform network optimization operations.

[0219] Alternatively, assuming that the 100 terminals are still in different mismatch states, for the 100 terminals, the downlink signal strength of the network device after compensation is still used to determine whether to perform network optimization operations. Among them, for the 100 terminals, after compensating for the downlink signal strength of the network device received by the terminal, the mismatch state of the antenna of the terminal is alleviated to varying degrees.

[0220] In some embodiments,

[0221] The obtaining of the power compensation value of the terminal in the antenna mismatch state comprises: obtaining the power compensation value of the terminal in different antenna mismatch states;

[0222] The compensating the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state includes: compensating the downlink signal strength of the network device respectively based on the power compensation value of the terminal in different antenna mismatch states;

[0223] The method further comprises:

[0224] Comparing the downlink signal strengths of the network device after compensation obtained under different antenna mismatch states to obtain a comparison result;

[0225] When the comparison result indicates that the downlink signal strengths of the network device after compensation under different antenna mismatch states are the same, it is determined that the network coverage of the area where the terminal is located has not changed.

[0226] As an example, the same may mean that the downlink signal strength of the network device after compensation under different antenna mismatch states is exactly the same, or the difference in the downlink signal strength of the network device after compensation under every two antenna mismatch states may also be considered the same within a preset range.

[0227] In some embodiments, the method further comprises:

[0228] Obtaining an AI / ML model, wherein the AI / ML model is used to execute the data processing method described in the above embodiment;

[0229] The training data of the AI / ML model includes:

[0230] A power compensation value of the terminal under different antenna mismatch states;

[0231] or,

[0232] The power compensation value of the terminal in different antenna mismatch states, and the time information and / or location information of the terminal in different antenna mismatch states.

[0233] In some embodiments, the AI / ML model is trained by the network device, or trained by the OAM, or trained by the terminal.

[0234] In some embodiments, obtaining the AI / ML model includes:

[0235] Sending the training data to the OAM;

[0236] Receive the AI / ML model returned by the OAM.

[0237] In some embodiments, obtaining the AI / ML model includes:

[0238] sending the training data to the terminal;

[0239] Receive the AI / ML model returned by the terminal.

[0240] In the embodiment of the present application, the following advantages are possessed:

[0241] (1) Obtaining a power compensation value of the terminal in an antenna mismatch state; obtaining a downlink signal strength of a network device; compensating the downlink signal strength of the network device based on the power compensation value of the terminal in an antenna mismatch state to obtain the downlink signal strength of the network device after compensation. In this way, the downlink signal strength of the network device at the location of the terminal can be truly evaluated, which can also facilitate the subsequent execution of network optimization operations.

[0242] (2) This application proposal aims to enable the network to accurately grasp the actual coverage of the existing network through AI / ML model training, even when the terminal antenna mismatch cannot be eliminated, thereby avoiding unnecessary network planning and optimization costs for operators.

[0243] See also Figure 3 , Figure 3 301 is a schematic diagram of the implementation flow of the data processing method of the embodiment of the present application, which is applied to a terminal. The method includes steps 301 to 302:

[0244] Step 301: determine a power compensation value of a terminal in an antenna mismatch state.

[0245] Step 302: Send a power compensation value of the terminal in an antenna mismatch state to the first device; wherein the power compensation value is used by the first device to compensate for the acquired downlink signal strength of the network device to obtain the compensated downlink signal strength of the network device.

[0246] As an example, the first device includes but is not limited to a server (deployed by an operator), a third-party server (deployed by a manufacturer other than an operator), network equipment (such as a base station, the base station includes but is not limited to a 5G wireless access network, a 6G wireless access network, a 7G wireless access network, etc.), a terminal, OAM, etc.

[0247] In some embodiments, determining a power compensation value of the terminal in an antenna mismatch state includes:

[0248] Obtaining, through a power sensing module of the terminal, a reflected power of the terminal at an antenna port, and obtaining an input power of the terminal at the antenna port; obtaining a reflection coefficient of the terminal in an antenna mismatch state based on the reflected power and the input power;

[0249] Based on the reflection coefficient, perform one of the following operations:

[0250] Acquire the actual output power of the antenna of the terminal; determine the power compensation value of the terminal in the antenna mismatch state based on the actual output power of the antenna of the terminal and the reflection coefficient;

[0251] Acquire the uplink signal strength of the terminal, and acquire a first path loss between the terminal and the network device; determine a power compensation value of the terminal in an antenna mismatch state based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient;

[0252] or,

[0253] The reflected power of the terminal at the antenna port is obtained through the power sensing module of the terminal; at least one numerical value is determined according to the power value of the reflected power, wherein any one of the at least one numerical value is less than or equal to the power value of the reflected power; and a numerical value is selected from the at least one numerical value as the power compensation value.

[0254] It should be noted that the process of determining the power compensation value of the terminal in the antenna mismatch state based on the reflection coefficient has been described above and will not be repeated here.

[0255] In some embodiments, the method further comprises:

[0256] Sending a power headroom report to the first device; the power headroom report comprising a power headroom value;

[0257] The power headroom value is used by the first device to determine whether to perform a network optimization operation in combination with the downlink signal strength of the network device after the compensation.

[0258] As an example, the first device obtains a power margin report sent by the terminal; the power margin report includes a power margin value; the second path loss between the terminal and the network device is obtained through the downlink signal strength of the network device after compensation; when the power margin value is less than a preset power margin threshold and the second path loss is greater than a preset path loss threshold, it is determined that the area where the terminal is located is an uplink weak coverage area; when it is determined that the area where the terminal is located is an uplink weak coverage area, it is necessary to perform network optimization operations.

[0259] As an example, the second path loss between the terminal and the network device may be obtained by subtracting the downlink reference signal strength sent by the network device to the terminal from the downlink signal strength of the network device after compensation.

[0260] For example, assuming that PHR is used to represent the power headroom value and PL is used to represent the second path loss, when PHR is less than 0 and PL is greater than a preset path loss threshold, a network optimization operation needs to be performed.

[0261] As an example, performing the network optimization operation may refer to increasing the number of base stations in the area where the terminal is located, etc.

[0262] In some embodiments, the method further comprises:

[0263] Sending a first information set to the first device; the first information set includes a power headroom report sent by the terminal in a p-antenna mismatch state, and time information and / or location information of the terminal in the p-antenna mismatch state; the power headroom report includes a power headroom value; p is an integer greater than or equal to 1;

[0264] The first information set is used by the terminal to determine whether to perform a network optimization operation.

[0265] In some embodiments, the method further comprises:

[0266] Acquire time information and / or location information of the terminal in different antenna mismatch states;

[0267] Sending the time information and / or the location information to the first device;

[0268] Among them, the time information and / or location information is used by the first device to determine whether to perform network optimization operations in combination with the downlink signal strength of the network device after compensation, or is used by the first device to train an AI / ML model in combination with the power compensation value of the terminal in an antenna mismatch state.

[0269] As an example, the time information may refer to the duration of the terminal being in the antenna mismatch state, or may refer to the moment when the terminal is in the antenna mismatch state. For example, T is used to represent the time information. If T is equal to 3 minutes, it means that the duration of the terminal being in the antenna mismatch state is 3 minutes. If T is equal to 8 o'clock, it means that the moment when the terminal is in the antenna mismatch state is 8 o'clock.

[0270] As an example, the location information may refer to geographical location information of the terminal when it is in an antenna mismatch state. For example, P represents the location information, and assuming that P is cell A in city A, it means that the geographical location of the terminal when it is in an antenna mismatch state is cell A in city A.

[0271] In some embodiments, the method further comprises:

[0272] Get training data;

[0273] Using the training data, training the AI / ML model;

[0274] sending the AI / ML model to the first device;

[0275] The training data of the AI / ML model includes:

[0276] A power compensation value of the terminal under different antenna mismatch states;

[0277] or,

[0278] The power compensation value of the terminal in different antenna mismatch states, and the time information and / or location information of the terminal in different antenna mismatch states.

[0279] In the embodiment of the present application, the following advantages are possessed:

[0280] (1) Obtaining a power compensation value of the terminal in an antenna mismatch state; obtaining a downlink signal strength of a network device; compensating the downlink signal strength of the network device based on the power compensation value of the terminal in an antenna mismatch state to obtain the downlink signal strength of the network device after compensation. In this way, the downlink signal strength of the network device at the location of the terminal can be truly evaluated, which can also facilitate the subsequent execution of network optimization operations.

[0281] (2) This application proposal aims to enable the network to accurately grasp the actual coverage of the existing network through AI / ML model training, even when the terminal antenna mismatch cannot be eliminated, thereby avoiding unnecessary network planning and optimization costs for operators.

[0282] See also Figure 4 , Figure 4 Schematic diagram of the system architecture of the data processing method of the embodiment of the present application. Figure 4 As shown, it is taken as an example that the parameter configuration module, power perception module, time perception module, and location perception module are located inside the terminal, and the power compensation calculation module, mismatch data collection module (Mismatch Data Collection), and network planning and optimization decision module (Actor) are located outside the terminal. Among them, the power compensation calculation module may include a model training module and a model inference module.

[0283] Both the model training module and the model reasoning module can be deployed in network devices, such as base stations, including but not limited to 5G wireless access networks such as gNB, 6G wireless access networks, and 7G wireless access networks; the model reasoning module can also be deployed in network devices, such as base stations, while the model training module is deployed in OAM. The network planning and optimization decision module can be deployed independently or in conjunction with OAM.

[0284] right Figure 4 The modules are described as follows:

[0285] 1) The mismatch data collection module is used to provide input data for model training and model reasoning of AI / ML models.

[0286] Input data, including: reflection coefficient Γ and / or reflection power B from the power sensing module, duration sensing information T, location sensing information P, actual output power P of the antenna of the terminal UE , the uplink signal strength P of the terminal received by the network device gNB , the first path loss L between the terminal and the network device, the power compensation value Pc of the terminal in the antenna mismatch state, and can also include feedback data from the network planning and optimization decision module (Feedback, such as whether to decide to add new base stations and other network devices, the location of new base stations and other network devices, etc.), and output data from the power compensation calculation module (Output, such as the downlink signal strength of the network device after compensation). These data can be used as raw data, and there is no need to prepare data for AI / ML algorithms (data cleaning, data formatting, data conversion, etc.).

[0287] The duration perception information T and the position perception information P are optional reporting information. The position perception information P may be relatively rough position perception information, for example, information on a physical cell identifier (PCI) of a cell perceived by the terminal.

[0288] 2) Power compensation calculation module:

[0289] The model training module is responsible for the training, testing, and verification of AI / ML models and generates metrics for model performance. The trained, tested, and verified AI / ML models are deployed to the model inference module through model deployment or update (Model Deployment / Update).

[0290] The model inference module is used to provide the inference output (prediction or decision) of the AI / ML model and feedback the results to the model training module. The model performance feedback of the model inference module can be sent to the model training module through model performance feedback, so that the model training module can train and optimize the AI / ML model. The process of feeding back the results to the model training module is an optional process.

[0291] Specifically, based on the input data, a power compensation value of the terminal in an antenna mismatch state is obtained, and then based on the power compensation value of the terminal in the antenna mismatch state, the downlink signal strength of the network device is compensated to obtain the compensated downlink signal strength of the network device.

[0292] Here, the inference output may be the downlink signal strength of the network device after compensation.

[0293] Here, the inference output can take the following forms:

[0294] The first method uses the downlink signal strength of the network device after compensation, such as RSRPn_m+Pcm, where RSRPn_m+Pcm represents the downlink signal strength of the network device after compensation of terminal n, m represents the antenna mismatch state, RSRPn_m represents the downlink signal strength of the network device received by terminal n in the antenna mismatch state m, and Pcm represents the power compensation value of terminal n in the antenna mismatch state m.

[0295] The second method uses the second path loss between the terminal and the network device obtained by the downlink signal strength of the network device after the compensation and the power headroom value in the power headroom report sent by the terminal, such as [PL, PHR].

[0296] The third method uses the downlink signal strength of the network device after compensation and the power headroom value in the power headroom report sent by the terminal, as well as the time information and / or location information of the terminal in the antenna mismatch state, such as [RSRPn_m+Pcm, PHRm, Tm]. Among them, RSRPn_m+Pcm represents the downlink signal strength of the network device after compensation of terminal n, m represents the antenna mismatch state, PHRm represents the power headroom value corresponding to the antenna mismatch state m, and Tm represents the time information of the terminal in the antenna mismatch state.

[0297] 3) Network planning and optimization decision module, which is used to perform corresponding network optimization operations after receiving the reasoning output (prediction or decision) of the module reasoning module.

[0298] Here, performing network optimization operations may refer to increasing the number of network devices such as base stations gNB in ​​the area where the terminal is located.

[0299] Here, the downlink signal strength of the network device after compensation can be used to determine whether to perform the network optimization operation. The specific implementation process has been described above and will not be repeated here.

[0300] It is also possible to determine whether to perform network optimization operations based on the second path loss obtained through the downlink signal strength of the network device after the compensation and the power headroom report sent by the terminal. The specific implementation process has been described above and will not be repeated here.

[0301] Alternatively, it may be determined whether to perform the network optimization operation based on the power headroom value and the time information and / or location information of the terminal in the antenna mismatch state. The specific implementation process has been described above and will not be repeated here.

[0302] See also Figure 5 , Figure 5 It is a schematic diagram of a specific implementation flow of the data processing method of an embodiment of the present application. Taking the model training module and the model reasoning module as examples, the model training module and the model reasoning module are both located in the base station and the network optimization decision module is independently deployed. The base station includes but is not limited to 5G wireless access network, namely the next generation wireless access network (NG-RAN, NG Radio Access Network), 6G wireless access network, 7G wireless access network, etc. Figure 5 The base station is represented by NG-RAN node n, such as Figure 5 As shown, the method includes steps 501 to 505:

[0303] Step 501: NG-RAN node n configures the UE and requests the UE to provide mismatch data.

[0304] Here, the mismatch data may include: the reflection coefficient Γ or the reflection power B of the antenna of the UE in the antenna mismatch state, the duration perception information T, and the position perception information P.

[0305] Here, the mismatch data may also include: the reflection coefficient Γ and / or the reflection power B of the antenna of the UE in the antenna mismatch state, as well as the time information T of the UE in the antenna mismatch state and / or the position information P of the UE in the antenna mismatch state.

[0306] Step 502: The UE performs mismatch data perception or mismatch data collection.

[0307] As an example, a power sensing module may be added inside the UE, and the reflected power B at the antenna port may be acquired through the power sensing module, and the input power A at the antenna port may be acquired through the power sensing module.

[0308] According to the following formula, the reflection coefficient Γ of the UE antenna in the antenna mismatch state is calculated:

[0309]

[0310] Wherein, Γ represents the reflection coefficient of the antenna of the UE in the antenna mismatch state, B represents the reflected power at the antenna port, and A represents the input power at the antenna port of the UE.

[0311] Here, the mismatch degree of the UE antenna can be known through the reflection coefficient Γ. For example, if the reflection coefficient Γ is 0, it means that the terminal antenna is in a non-mismatched state, otherwise, it means that the terminal antenna is in a mismatched state.

[0312] The terminal can sense the "reflected power" through the power sensing module. When the reflected power is not 0, it is in the antenna mismatch state; or when the "reflection coefficient" obtained by further combining the reflected power and the incident power is not 0, it can also be judged to be in the antenna mismatch state.

[0313] It should be noted that not all cases where the reflected power is not 0 or the reflection coefficient is not 0 are considered to be in an "antenna mismatch state". In actual use, a certain threshold range can be set according to the actual situation. When the reflected power exceeds a certain threshold or the reflection coefficient is greater than a certain threshold, it can be considered to be in an "antenna mismatch state".

[0314] Step 503: The UE reports the mismatch data to NG-RAN node n.

[0315] Here, the mismatch data can be used as input data for the model training module of the AI / ML model.

[0316] Here, the mismatch data can also be used as input data for the model reasoning module of the AI / ML model.

[0317] Here, the AI / ML model is trained based on the mismatch data provided by the terminal, and the AI / ML model generates prediction information (Output) based on the accumulated information in the past, that is, the output of the downlink signal strength of the compensated network device that should be used at this time, such as RSRPn_m+Pcm, where RSRPn_m+Pcm represents the downlink signal strength of the compensated network device of terminal n, and m represents the antenna mismatch state. In other words, n represents the identifier of different terminals, and m represents the different mismatch states of the terminal, which can be used to represent the data identifier of different downlink signal strengths of the same base station received by the same terminal.

[0318] When training the model, it is assumed that the terminal UE1 is in a certain mismatch state S1. At this time, the downlink signal strength of the base station A received by the terminal UE1 is RSRP1_1. At this time, the mismatch state of the terminal UE1 can be characterized by the reflected power B1 or the reflection coefficient Γ1. Assuming that UE1 can be corrected to the ideal non-mismatched state S0, the downlink signal strength of the base station A received by the terminal UE1 should be RSRP1_1+Pc1, and Pc1 is the power compensation value of the terminal in the antenna mismatch state S1. Assuming that the terminal UE1 is in a certain mismatch state S2, the downlink signal strength of the base station A received by the terminal UE1 is RSRP1_2. At this time, the mismatch state of the terminal UE1 can be characterized by the reflected power B2 or the reflection coefficient Γ2. Assuming that UE1 can be corrected to the ideal non-mismatched state S0, the downlink signal strength of the base station A received by the terminal UE1 should be RSRP1_2+Pc2, and Pc2 is the power compensation value of the terminal in the antenna mismatch state S2.

[0319] If the position of UE1 does not change when it is in the above-mentioned mismatch states S1 and S2, then the downlink signal strength RSRP1_1+Pc1 of base station A received by terminal UE1 after correction should be approximately equal to RSRP1_2+Pc2. It can be inferred that the network coverage situation of UE1 does not change significantly when it is in the above-mentioned mismatch states S1 and S2.

[0320] Step 504: NG-RAN node n performs model reasoning based on the AI / ML model according to the mismatch data, and generates a reasoning output and sends it to the network planning and optimization decision module.

[0321] Here, the inference output may be the downlink signal strength of the network device after compensation.

[0322] Here, the inference output can take the following forms:

[0323] The first method uses the downlink signal strength of the network device after compensation, such as RSRPn_m+Pcm, where RSRPn_m+Pcm represents the downlink signal strength of the network device after compensation of terminal n, m represents the antenna mismatch state, RSRPn_m represents the downlink signal strength of the network device received by terminal n in the antenna mismatch state m, and Pcm represents the power compensation value of terminal n in the antenna mismatch state m.

[0324] The second method uses the second path loss between the terminal and the network device obtained by the downlink signal strength of the network device after the compensation and the power headroom value in the power headroom report sent by the terminal, such as [PL, PHR].

[0325] The third method uses the downlink signal strength of the network device after compensation and the power headroom value in the power headroom report sent by the terminal, as well as the time information and / or location information of the terminal in the antenna mismatch state, such as [RSRPn_m+Pcm, PHRm, Tm]. Among them, RSRPn_m+Pcm represents the downlink signal strength of the network device after compensation of terminal n, m represents the antenna mismatch state, PHRm represents the power headroom value corresponding to the antenna mismatch state m, and Tm represents the time information of the terminal in the antenna mismatch state.

[0326] Step 505: The network planning and optimization decision module determines whether to perform network optimization operations.

[0327] That is, it analyzes whether it is necessary to initiate network planning and optimization and / or how to perform network planning and optimization, and outputs the analysis results of the necessity and / or implementation plan of network planning and optimization. The analysis results can also be fed back to NG-RAN node n.

[0328] Here, performing network optimization operations may refer to increasing the number of network devices such as base stations gNB in ​​the area where the terminal is located.

[0329] Here, the downlink signal strength of the network device after compensation can be used to determine whether to perform the network optimization operation. The specific implementation process has been described above and will not be repeated here.

[0330] It is also possible to determine whether to perform network optimization operations based on the second path loss obtained through the downlink signal strength of the network device after the compensation and the power headroom report sent by the terminal. The specific implementation process has been described above and will not be repeated here.

[0331] Alternatively, it may be determined whether to perform the network optimization operation based on the power headroom value and the time information and / or location information of the terminal in the antenna mismatch state. The specific implementation process has been described above and will not be repeated here.

[0332] It should be noted that when judging whether to perform network optimization operations in combination with the time information of the terminal in the antenna mismatch state, if the duration of a certain downlink signal strength (RSRP) received by the terminal is relatively long, even if there is a certain terminal antenna mismatch, the network planning and optimization decision module can also consider making network planning and optimization decisions for the downlink signal strength that is likely to appear in the existing network, so as to ensure the speed experience of terminal users in the existing network.

[0333] Here, we can also combine the UE model information to provide information on terminal antenna mismatch of different models of terminals in different locations and environments of the existing network, provide more reference information for operators' network optimization and planning, and help operators make more accurate network optimization and planning decisions.

[0334] In this example, the following advantages are achieved:

[0335] (1) Based on the mismatch data reported by terminals, AI / ML model training is introduced to help the network accurately grasp the actual coverage of the existing network, avoid unnecessary network planning and optimization costs for operators, and / or help operators make network planning and optimization decisions that help improve the speed experience of terminal users in the existing network.

[0336] (2) AI / ML model training is performed through NG-RAN node n to help the network accurately understand the actual coverage of the existing network, avoid unnecessary network planning and optimization costs for operators, and / or help operators make network planning and optimization decisions that help improve the speed experience of terminal users in the existing network.

[0337] See also Figure 6 , Figure 6 It is a schematic diagram of a specific implementation flow of the data processing method of an embodiment of the present application. Taking the model training module and the model reasoning module as examples, the model training module and the network optimization decision module are both located in the base station and are independently deployed. The base station includes but is not limited to 5G wireless access network, namely NG-RAN, 6G wireless access network, 7G wireless access network, etc. Figure 6 The base station is represented by NG-RAN node n, such as Figure 6 As shown, the method includes steps 601 to 605:

[0338] Step 601: NG-RAN node n configures the UE and requests the UE to provide mismatch data.

[0339] Step 602: The UE performs mismatch data perception or mismatch data collection.

[0340] Here, the implementation process of mismatch data perception or mismatch data collection has been described above and will not be repeated here.

[0341] Step 603: The UE reports the collected mismatch data to NG-RAN node n.

[0342] Step 604: NG-RAN node n sends the mismatch data reported by the UE to OAM.

[0343] Step 605: OAM performs model training based on the AI / ML model according to the mismatch data.

[0344] Step 606: OAM deploys / updates the AI / ML model to NG-RAN node n.

[0345] Step 607: The UE reports mismatch data used for model inference to NG-RAN node n.

[0346] Step 608: NG-RAN node n performs model reasoning based on the AI / ML model according to the mismatch data, and generates a reasoning output and sends it to the network planning and optimization decision module.

[0347] Here, NG-RAN node n can also send model performance feedback to OAM.

[0348] Step 609: The network planning and optimization decision module determines whether to perform network optimization operations.

[0349] That is, it analyzes whether it is necessary to start network planning and optimization and / or how to perform network planning and optimization, and outputs the analysis results of the necessity and / or implementation plan of network planning and optimization, and can also feed back the analysis results to OAM.

[0350] Here, performing network optimization operations may refer to increasing the number of network devices such as base stations gNB in ​​the area where the terminal is located.

[0351] Here, the downlink signal strength of the network device after compensation can be used to determine whether to perform the network optimization operation. The specific implementation process has been described above and will not be repeated here.

[0352] It is also possible to determine whether to perform network optimization operations based on the second path loss obtained through the downlink signal strength of the network device after the compensation and the power headroom report sent by the terminal. The specific implementation process has been described above and will not be repeated here.

[0353] Alternatively, it may be determined whether to perform the network optimization operation based on the power headroom value and the time information and / or location information of the terminal in the antenna mismatch state. The specific implementation process has been described above and will not be repeated here.

[0354] In this example, the following advantages are achieved:

[0355] (1) Based on the mismatch data reported by terminals, AI / ML model training is introduced to help the network accurately grasp the actual coverage of the existing network, avoid unnecessary network planning and optimization costs for operators, and / or help operators make network planning and optimization decisions that help improve the speed experience of terminal users in the existing network.

[0356] (2) AI / ML model training through OAM helps the network to accurately grasp the actual coverage of the existing network, avoid unnecessary network planning and optimization costs for operators, and / or help operators make network planning and optimization decisions that help improve the speed experience of terminal users in the existing network.

[0357] In order to implement the data processing method of the embodiment of the present application, the embodiment of the present application also provides a data processing device, which is arranged in the first device. Figure 7Schematic diagram of the structure of the data processing device according to the embodiment of the present application. Figure 7 As shown, the device comprises:

[0358] The acquisition module 71 is used to obtain the power compensation value of the terminal in the antenna mismatch state; obtain the downlink signal strength of the network device;

[0359] The first processing module 72 is configured to compensate the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state to obtain the compensated downlink signal strength of the network device.

[0360] In some embodiments, the acquisition module 71 is used to:

[0361] Obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0362] Obtaining actual output power of the antenna of the terminal;

[0363] A power compensation value of the terminal in an antenna mismatch state is determined based on the actual output power of the antenna of the terminal and the reflection coefficient.

[0364] In some embodiments, the acquisition module 71 is used to:

[0365] Obtaining a reflection coefficient corresponding to the antenna mismatch state;

[0366] Obtaining the uplink signal strength of the terminal;

[0367] Obtaining a first path loss between the terminal and the network device;

[0368] A power compensation value of the terminal in an antenna mismatch state is determined based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient.

[0369] In some embodiments, the acquisition module 71 is used to:

[0370] Obtaining reflected power of the terminal at an antenna port;

[0371] Determine at least one value according to the power value of the reflected power, wherein any one of the at least one value is less than or equal to the power value of the reflected power;

[0372] A value is selected from the at least one value as a power compensation value of the terminal in an antenna mismatch state.

[0373] In some embodiments, the device is further used to:

[0374] When the downlink signal strength of the network device after the compensation is less than a preset signal strength threshold, a network optimization operation needs to be performed.

[0375] In some embodiments, the device is further used to:

[0376] Acquire a power headroom report sent by the terminal; the power headroom report includes a power headroom value;

[0377] Obtaining a second path loss between the terminal and the network device according to the compensated downlink signal strength of the network device;

[0378] In a case where the power headroom value is less than a preset power headroom threshold and the second path loss is greater than a preset path loss threshold, a network optimization operation needs to be performed.

[0379] In some embodiments, the device is further used to:

[0380] Acquire a first information set; the first information set includes a power headroom report sent by the terminal in a p-antenna mismatch state, and time information and / or location information of the terminal in the p-antenna mismatch state; the power headroom report includes a power headroom value; p is an integer greater than or equal to 1;

[0381] Selecting m power headroom values ​​corresponding to the m antenna mismatch states from the first information set; wherein the m power headroom values ​​are all less than a preset power headroom threshold, m is an integer greater than or equal to 1, and m is less than or equal to p;

[0382] Selecting time information and / or location information corresponding to the m power headroom values ​​from the first information set;

[0383] Based on the time information and / or location information corresponding to the m power headroom values, it is determined whether to perform a network optimization operation.

[0384] In some embodiments, the device is further used to:

[0385] Based on the time information corresponding to the m power headroom values, m weights are determined; the m weights are multiplied by the downlink signal strength of the network device after compensation obtained under the corresponding m antenna mismatch states to obtain a first downlink signal strength; when the first downlink signal strength is less than a preset signal strength threshold, a network optimization operation needs to be performed;

[0386] and / or,

[0387] For each piece of position information corresponding to the m power headroom values, when the downlink signal strength of the network device after compensation corresponding to the corresponding position information is less than a preset signal strength threshold, a network optimization operation needs to be performed.

[0388] In some embodiments, the acquisition module 71 is further used to acquire a power compensation value of the terminal under different antenna mismatch states;

[0389] The first processing module 72 is also used to compensate the downlink signal strength of the network device based on the power compensation value of the terminal in different antenna mismatch states; compare the downlink signal strength of the network device after compensation under different antenna mismatch states to obtain a comparison result; when the comparison result indicates that the downlink signal strength of the network device after compensation under different antenna mismatch states is the same, it is determined that the network coverage of the area where the terminal is located has not changed.

[0390] In some embodiments, the device is further used to:

[0391] Obtaining an AI / ML model, wherein the AI / ML model is used to execute the data processing method;

[0392] The training data of the AI / ML model includes:

[0393] A power compensation value of the terminal under different antenna mismatch states;

[0394] or,

[0395] The power compensation value of the terminal in different antenna mismatch states, and the time information and / or location information of the terminal in different antenna mismatch states.

[0396] In some embodiments, the AI / ML model is trained by the network device, or trained by the OAM, or trained by the terminal.

[0397] In actual application, the acquisition unit 71 can be implemented by a communication interface in a data processing device; the first processing unit 72 can be implemented by a processor in the data processing device.

[0398] It should be noted that: when the data processing device provided in the above embodiment performs data processing, only the division of the above program modules is used as an example. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the data processing device provided in the above embodiment and the data processing method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0399] In order to implement the data processing method of the embodiment of the present application, the embodiment of the present application also provides a data processing device, which is arranged in a terminal. Figure 8 Schematic diagram of the structure of the data processing device according to the embodiment of the present application. Figure 8 As shown, the device comprises:

[0400] A second processing module 81, configured to determine a power compensation value of the terminal in an antenna mismatch state;

[0401] The sending module 82 is used to send the power compensation value of the terminal in the antenna mismatch state to the first device; wherein the power compensation value is used by the first device to compensate the acquired downlink signal strength of the network device to obtain the compensated downlink signal strength of the network device.

[0402] In some embodiments, the second processing module 81 is used to:

[0403] Obtaining, through a power sensing module of the terminal, a reflected power of the terminal at an antenna port, and obtaining an input power of the terminal at the antenna port; obtaining a reflection coefficient of the terminal in an antenna mismatch state based on the reflected power and the input power;

[0404] Based on the reflection coefficient, perform one of the following operations:

[0405] Acquire the actual output power of the antenna of the terminal; determine the power compensation value of the terminal in the antenna mismatch state based on the actual output power of the antenna of the terminal and the reflection coefficient;

[0406] Acquire the uplink signal strength of the terminal, and acquire a first path loss between the terminal and the network device; determine a power compensation value of the terminal in an antenna mismatch state based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient;

[0407] or,

[0408] The reflected power of the terminal at the antenna port is obtained through the power sensing module of the terminal; at least one numerical value is determined according to the power value of the reflected power, wherein any one of the at least one numerical value is less than or equal to the power value of the reflected power; and a numerical value is selected from the at least one numerical value as the power compensation value.

[0409] In some embodiments, the device is further used to:

[0410] Sending a power headroom report to the first device; the power headroom report comprising a power headroom value;

[0411] The power headroom value is used by the first device to determine whether to perform a network optimization operation in combination with the downlink signal strength of the network device after the compensation.

[0412] In one embodiment, the device is further used for:

[0413] Acquire time information and / or location information of the terminal in different antenna mismatch states;

[0414] Sending the time information and / or the location information to the first device;

[0415] Among them, the time information and / or location information is used by the first device to determine whether to perform network optimization operations in combination with the downlink signal strength of the network device after compensation, or is used by the first device to train an AI / ML model in combination with the power compensation value of the terminal in an antenna mismatch state.

[0416] In actual application, the sending unit 82 can be implemented by a communication interface in a data processing device; the second processing unit 81 can be implemented by a processor in the data processing device.

[0417] It should be noted that: when the data processing device provided in the above embodiment performs data processing, only the division of the above program modules is used as an example. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the data processing device provided in the above embodiment and the data processing method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0418] The present application also provides a device, such as Fig. 9 As shown, including:

[0419] A first communication interface 91, capable of exchanging information with other devices;

[0420] The first processor 92 is connected to the first communication interface 91 and is used to execute the method provided by one or more technical solutions of the device side when running a computer program. The computer program is stored in the first memory 93.

[0421] It should be noted that: the specific processing process of the first processor 92 and the first communication interface 91 is detailed in the method embodiment, which will not be repeated here.

[0422] Of course, in actual application, the various components in the device 90 are coupled together through the bus system 94. It is understood that the bus system 94 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 94 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig. 9 Various buses are labeled as bus system 94 .

[0423] The first memory 93 in the embodiment of the present application is used to store various types of data to support the operation of the device 90. Examples of such data include: any computer program used to operate on the device 90.

[0424] The method disclosed in the above embodiment of the present application can be applied to the first processor 92, or implemented by the first processor 92. The first processor 92 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the first processor 92. The above-mentioned first processor 92 may be a general-purpose processor, a digital data processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The first processor 92 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the first memory 93. The first processor 92 reads the information in the first memory 93 and completes the steps of the above method in combination with its hardware.

[0425] The present application also provides a terminal, such as Fig.10 As shown, including:

[0426] The second communication interface 101 is capable of exchanging information with other devices;

[0427] The second processor 102 is connected to the second communication interface 101 and is used to execute the method provided by one or more technical solutions on the terminal side when running a computer program. The computer program is stored in the second memory 103.

[0428] It should be noted that: the specific processing process of the second processor 102 and the second communication interface 101 is detailed in the method embodiment, which will not be repeated here.

[0429] Of course, in actual application, the various components in the terminal 100 are coupled together through the bus system 104. It can be understood that the bus system 104 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 104 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig.10 Various buses are labeled as bus system 104 .

[0430] The second memory 103 in the embodiment of the present application is used to store various types of data to support the operation of the terminal 100. Examples of such data include: any computer program used to operate on the terminal 100.

[0431] The method disclosed in the above embodiment of the present application can be applied to the second processor 102, or implemented by the second processor 102. The second processor 102 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the second processor 102. The above-mentioned second processor 102 may be a general-purpose processor, a digital data processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The second processor 102 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in the second memory 103, and the second processor 102 reads the information in the second memory 103, and completes the steps of the above method in combination with its hardware.

[0432] In an exemplary embodiment, the device 90 and the terminal 100 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned method.

[0433] It can be understood that the memory (first memory 93, second memory 103) of the embodiment of the present application can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM).The memories described in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0434] In an exemplary embodiment, the present application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, for example, a memory storing a computer program, and the computer program can be executed by the first processor 92 of the device 90 to complete the steps of the aforementioned device-side method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0435] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0436] In addition, the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0437] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A data processing method, characterized in that: Applied to a first device, the method includes: Obtaining a power compensation value of a terminal in an antenna mismatch state; Get the downlink signal strength of the network device; Based on the power compensation value of the terminal in the antenna mismatch state, the downlink signal strength of the network device is compensated to obtain the compensated downlink signal strength of the network device.

2. The method according to claim 1, characterized in that The obtaining of a power compensation value of the terminal in an antenna mismatch state includes: Obtaining a reflection coefficient corresponding to the antenna mismatch state; Obtaining actual output power of the antenna of the terminal; A power compensation value of the terminal in an antenna mismatch state is determined based on the actual output power of the antenna of the terminal and the reflection coefficient.

3. The method according to claim 1, characterized in that The obtaining of a power compensation value of the terminal in an antenna mismatch state includes: Obtaining a reflection coefficient corresponding to the antenna mismatch state; Obtaining the uplink signal strength of the terminal; Obtaining a first path loss between the terminal and the network device; A power compensation value of the terminal in an antenna mismatch state is determined based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient.

4. The method according to claim 1, characterized in that: The obtaining of a power compensation value of the terminal in an antenna mismatch state includes: Obtaining reflected power of the terminal at an antenna port; Determine at least one value according to the power value of the reflected power, wherein any one of the at least one value is less than or equal to the power value of the reflected power; A value is selected from the at least one value as a power compensation value of the terminal in an antenna mismatch state.

5. The method according to claim 1, characterized in that The method further comprises: When the downlink signal strength of the network device after the compensation is less than a preset signal strength threshold, a network optimization operation needs to be performed.

6. The method according to claim 1, characterized in that The method further comprises: Acquire a power headroom report sent by the terminal; the power headroom report includes a power headroom value; Obtaining a second path loss between the terminal and the network device according to the compensated downlink signal strength of the network device; In a case where the power headroom value is less than a preset power headroom threshold and the second path loss is greater than a preset path loss threshold, a network optimization operation needs to be performed.

7. The method according to claim 1, characterized in that The method further comprises: Acquire a first information set; the first information set includes a power headroom report sent by the terminal in a p-antenna mismatch state, and time information and / or location information of the terminal in the p-antenna mismatch state; the power headroom report includes a power headroom value; p is an integer greater than or equal to 1; Selecting m power headroom values ​​corresponding to the m antenna mismatch states from the first information set; wherein the m power headroom values ​​are all less than a preset power headroom threshold, m is an integer greater than or equal to 1, and m is less than or equal to p; Selecting time information and / or location information corresponding to the m power headroom values ​​from the first information set; Based on the time information and / or location information corresponding to the m power headroom values, it is determined whether to perform a network optimization operation.

8. The method according to claim 7, characterized in that The determining whether to perform a network optimization operation based on the time information and / or location information corresponding to the m power headroom values ​​includes: Based on the time information corresponding to the m power headroom values, m weights are determined; the m weights are multiplied by the downlink signal strength of the network device after compensation obtained under the corresponding m antenna mismatch states to obtain a first downlink signal strength; when the first downlink signal strength is less than a preset signal strength threshold, a network optimization operation needs to be performed; and / or, For each piece of position information corresponding to the m power headroom values, when the downlink signal strength of the network device after compensation corresponding to the corresponding position information is less than a preset signal strength threshold, a network optimization operation needs to be performed.

9. The method according to claim 1, characterized in that: The obtaining of the power compensation value of the terminal in the antenna mismatch state comprises: obtaining the power compensation value of the terminal in different antenna mismatch states; The compensating the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state includes: compensating the downlink signal strength of the network device respectively based on the power compensation value of the terminal in different antenna mismatch states; The method further comprises: Comparing the downlink signal strengths of the network device after compensation obtained under different antenna mismatch states to obtain a comparison result; When the comparison result indicates that the downlink signal strengths of the network device after compensation under different antenna mismatch states are the same, it is determined that the network coverage of the area where the terminal is located has not changed.

10. The method according to any one of claims 1 to 9, characterized in that: The method further comprises: Obtaining an artificial intelligence / machine learning AI / ML model, wherein the AI / ML model is used to execute the data processing method; The training data of the AI / ML model includes: A power compensation value of the terminal under different antenna mismatch states; or, The power compensation value of the terminal in different antenna mismatch states, and the time information and / or location information of the terminal in different antenna mismatch states.

11. The method according to claim 10, characterized in that The AI / ML model is trained by the network device, or trained by operation and maintenance management OAM, or trained by the terminal.

12. A data processing method, characterized in that: Applied to a terminal, the method comprises: Determining a power compensation value of the terminal in an antenna mismatch state; Sending a power compensation value of the terminal in an antenna mismatch state to the first device; The power compensation value is used by the first device to compensate for the acquired downlink signal strength of the network device, so as to obtain the compensated downlink signal strength of the network device.

13. The method according to claim 12, characterized in that The determining a power compensation value of the terminal in an antenna mismatch state includes: Obtaining, through a power sensing module of the terminal, a reflected power of the terminal at an antenna port, and obtaining an input power of the terminal at the antenna port; obtaining a reflection coefficient of the terminal in an antenna mismatch state based on the reflected power and the input power; Based on the reflection coefficient, perform one of the following operations: Acquire the actual output power of the antenna of the terminal; determine the power compensation value of the terminal in the antenna mismatch state based on the actual output power of the antenna of the terminal and the reflection coefficient; Acquire the uplink signal strength of the terminal, and acquire a first path loss between the terminal and the network device; determine a power compensation value of the terminal in an antenna mismatch state based on the uplink signal strength of the terminal, the first path loss, and the reflection coefficient; or, The reflected power of the terminal at the antenna port is obtained through the power sensing module of the terminal; at least one numerical value is determined according to the power value of the reflected power, wherein any one of the at least one numerical value is less than or equal to the power value of the reflected power; and a numerical value is selected from the at least one numerical value as the power compensation value.

14. The method according to claim 12, characterized in that The method further comprises: Sending a power headroom report to the first device; the power headroom report comprising a power headroom value; The power headroom value is used by the first device to determine whether to perform a network optimization operation in combination with the downlink signal strength of the network device after the compensation.

15. The method according to claim 12, characterized in that The method further comprises: Acquire time information and / or location information of the terminal in different antenna mismatch states; Sending the time information and / or the location information to the first device; Among them, the time information and / or location information is used by the first device to determine whether to perform network optimization operations in combination with the downlink signal strength of the network device after compensation, or is used by the first device to train an AI / ML model in combination with the power compensation value of the terminal in an antenna mismatch state.

16. A data processing device, characterized in that: include: An acquisition module is used to obtain a power compensation value of a terminal in an antenna mismatch state; Get the downlink signal strength of the network device; The first processing module is used to compensate the downlink signal strength of the network device based on the power compensation value of the terminal in the antenna mismatch state to obtain the compensated downlink signal strength of the network device.

17. A data processing device, characterized in that: include: A second processing module, used to determine a power compensation value of the terminal in an antenna mismatch state; The sending module is used to send the power compensation value of the terminal in the antenna mismatch state to the first device.

18. A device, characterized in that comprising a processor and a memory for storing a computer program capable of being executed on the processor, Wherein, when the processor is used to run the computer program, it executes the steps of the method described in any one of claims 1 to 11.

19. A terminal, characterized in that: comprising a processor and a memory for storing a computer program capable of being executed on the processor, Wherein, when the processor is used to run the computer program, it executes the steps of the method described in any one of claims 12 to 15.

20. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 11, or implements the steps of the method according to any one of claims 12 to 15.

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