Data processing method and device, equipment and storage medium

Abstract

A data processing method, device and equipment and storage medium are disclosed. The method comprises determining the probability proportion of a plurality of terminals in a live network at different output powers, determining the power consumption of each terminal in the plurality of terminals at different output powers, and calculating the total power consumption of each terminal based on the probability proportion and the power consumption.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a data processing method, apparatus, device, and storage medium. Background Technology

[0002] Currently, methods for estimating terminal power consumption are relatively simplistic, typically using a typical terminal service model as the power consumption model for prediction. However, actual terminal power consumption depends on more than just the service model used. In other words, even for the same terminal employing the same service model, actual power consumption can vary under certain circumstances. Therefore, relying solely on the service model for power consumption assessment has limitations and cannot accurately predict the actual power consumption of the terminal. Summary of the Invention

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

[0004] The technical solution of this invention is implemented as follows:

[0005] At least one embodiment of the present invention provides a data processing method, the method comprising:

[0006] Determine the probability percentage of multiple terminals in the current network at different output powers; and determine the power consumption of each of the multiple terminals at different output powers;

[0007] Based on the probability ratio and the power consumption, the total power consumption of each terminal is calculated.

[0008] Furthermore, according to at least one embodiment of the present invention, determining the power consumption of each of the plurality of terminals at different output powers includes:

[0009] For each terminal, the power consumption of the corresponding terminal under different output powers is determined by utilizing the different output powers and efficiencies of the corresponding terminal in the existing network.

[0010] Furthermore, according to at least one embodiment of the present invention, calculating the total power consumption of each terminal based on the probability ratio and the power consumption includes:

[0011] For each terminal, the power consumption of the corresponding terminal at different output powers is multiplied by the corresponding probability ratio to obtain multiple first values;

[0012] Summing the multiple first values ​​yields the second value;

[0013] The second value is taken as the total power consumption of the corresponding terminal.

[0014] Furthermore, according to at least one embodiment of the present invention, determining the power consumption of each of the plurality of terminals at different output powers includes:

[0015] For each terminal, when the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, determine the power consumption of the corresponding terminal under different output power.

[0016] Furthermore, according to at least one embodiment of the present invention, calculating the total power consumption of each terminal based on the probability ratio and the power consumption includes:

[0017] The determined probability percentage and the power consumption are stored;

[0018] Using the probability percentage and power consumption stored locally, the total power consumption of each terminal is calculated.

[0019] Furthermore, according to at least one embodiment of the present invention, the method further includes:

[0020] Determine the probability proportion of power amplifiers in multiple terminals in the current network at different output powers; and determine the power consumption of power amplifiers in each terminal at different output powers.

[0021] Based on the probability ratio and the power consumption, calculate the total power consumption of the power amplifier in each terminal.

[0022] At least one embodiment of the present invention provides a data processing apparatus, comprising:

[0023] The first processing unit is used to determine the probability proportion of multiple terminals in the current network at different output powers;

[0024] The second processing unit is used to determine the power consumption of each of the plurality of terminals under different output powers;

[0025] The third processing unit is used to calculate the total power consumption of each terminal based on the probability ratio and the power consumption.

[0026] At least one embodiment of the present invention provides a data processing apparatus, comprising:

[0027] Communication interface,

[0028] The processor is used to determine the probability percentage of multiple terminals in the current network at different output powers; and to determine the power consumption of each of the multiple terminals at different output powers; and to calculate the total power consumption of each terminal based on the probability percentage and the power consumption.

[0029] At least one embodiment of the present invention provides a network device, a processor, and a memory for storing a computer program capable of running on the processor.

[0030] When the processor runs the computer program, it performs the steps of the method described in any one of the above claims for the network device.

[0031] At least one embodiment of the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above methods.

[0032] The data processing method, apparatus, device, and storage medium provided in this invention determine the probability proportion of multiple terminals in a current network at different output powers; and determine the power consumption of each of the multiple terminals at different output powers; based on the probability proportion and the power consumption, calculate the total power consumption of each terminal. By employing the technical solution provided in this invention, combined with the actual output power and power consumption of the terminals in the current network, the total power consumption of the terminals is estimated. Compared with related technologies that use the terminal's service model to estimate terminal power consumption, this improves the accuracy of terminal power consumption estimation. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of a business model for estimating terminal power consumption in related technologies;

[0034] Figure 2 This is a schematic diagram illustrating the implementation flow of the data processing method according to an embodiment of the present invention;

[0035] Figure 3 This is a schematic diagram of the specific implementation flow of the data processing method in this embodiment of the invention. Figure 1 ;

[0036] Figure 4 This is a schematic diagram of the specific implementation flow of the data processing method in this embodiment of the invention. Figure 2 ;

[0037] Figure 5 This is a schematic diagram of the composition structure of the data processing device according to an embodiment of the present invention;

[0038] Figure 6 This is a schematic diagram of the composition structure of a network device according to an embodiment of the present invention. Detailed Implementation

[0039] Before introducing the technical solutions of the embodiments of the present invention, the relevant technologies will be explained first.

[0040] In related technologies, Figure 1 This is a schematic diagram of a business model for estimating terminal power consumption in related technologies, such as... Figure 1 As shown, current methods for estimating terminal power consumption are relatively simple. They are generally based on a typical terminal service model as the terminal power consumption model, and then used to estimate terminal power consumption.

[0041] However, the actual power consumption of a terminal is not only related to the service model used by the terminal, but also strongly correlated with the actual network conditions in which the terminal is located. In other words, terminals in areas with good network coverage, such as RSRP > -90dBm, usually have lower output power and lower power consumption; while terminals in areas with poor network coverage, such as RSRP < -110dBm, usually have higher output power, resulting in higher power consumption.

[0042] In other words, even with the same service model, the actual power consumption of a user's terminal will differ depending on the network coverage conditions. Therefore, relying solely on the service model as a power consumption assessment method has limitations and cannot accurately predict the actual power consumption of the terminal.

[0043] Secondly, the business models in related technologies are suitable for evaluating the power consumption of the application processing system (AP+GPU, etc.) of terminal products, but there is a lack of methods in related technologies for effectively evaluating the power consumption performance of the communication system (BBIC+RFIC+RF FEM, etc.) of terminal products in the current network.

[0044] Furthermore, when the terminal is in a screen-off state, the power amplifier (PA) is a major power consumer. For example, when the terminal is transmitting at full power, the PA's power consumption can account for more than 80% of the terminal's total power consumption in the screen-off state. The power amplifier will increase or decrease its output power based on the network coverage of the terminal or the network's output power requirements, thus affecting the terminal's power consumption. Current power consumption assessment methods for the power amplifier in the terminal, a major power consumer, only evaluate the average current of the PA and do not take into account the characteristics of the existing network, making it impossible to assess the power amplifier's power consumption performance in a real-world network. In other words, there is currently no technology or method to assess the power amplifier's power consumption performance in a real-world network, and terminal manufacturers lack a power consumption reference that takes into account the characteristics of the existing network when selecting power amplifiers.

[0045] Based on this, in this embodiment of the invention, the probability proportion of multiple terminals in the existing network at different output powers is determined; and the power consumption of each of the multiple terminals at different output powers is determined; based on the probability proportion and the power consumption, the total power consumption of each terminal is calculated.

[0046] Figure 2 This is a schematic diagram illustrating the implementation flow of the data processing method according to an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes steps 201 to 202:

[0047] Step 201: Determine the probability percentage of multiple terminals in the current network at different output powers; and determine the power consumption of each of the multiple terminals at different output powers.

[0048] It is understood that the existing network may include:

[0049] The existing network within the target location;

[0050] or,

[0051] The existing network within the target city;

[0052] or,

[0053] Existing network within the target country;

[0054] or,

[0055] The current network within the target continent.

[0056] In other words, the scope of "current network" can be large or small. For example, it can be the probability percentage of the current network within a certain factory area, or the probability percentage of the current network within a certain city area, or the probability percentage of the current network within the whole country, or the probability percentage of the current network within the whole of Asia.

[0057] As one implementation method, determining the probability proportion of multiple terminals in the existing network at different output powers may include:

[0058] The network management platform collects network management data from the base station side, processes the data collected from the base station side, and obtains the probability percentage of multiple terminals in the current network at different output powers.

[0059] Here, the network management platform determines the probability percentage of multiple terminals in the existing network at different output powers, which can specifically include:

[0060] Step 1: The network management platform collects network management data from the base station side.

[0061] Here, the network management data may refer to the Power Headroom Report (PHR).

[0062] Here, when multiple terminals access the network, the base station configures periodic PHR reporting for each terminal. When each terminal is in connected state and performing uplink services, each terminal periodically reports its PHR; the PHR carries PH and Pcmax information. PH represents the cell power margin, and Pcmax represents the maximum output power.

[0063] Step 2: The network management platform parses the PHR reported by each terminal to the base station to obtain PH and Pcmax information.

[0064] Step 3: When PH is greater than or equal to 0, calculate the actual output power of each terminal in the current network according to the following formula (1). When PH is less than 0, calculate the actual output power of each terminal in the current network according to the following formula (2).

[0065] P cmax -PH=P out (1)

[0066] PH-P cmax =P out (2)

[0067] Among them, P out This indicates the actual output power of the terminal.

[0068] Step 4: The network management platform counts the total number of multiple terminals and the number of terminals at each output power point. Based on the total number of multiple terminals and the number of terminals at each output power point, the probability percentage of multiple terminals at different output power is calculated.

[0069] Assuming that the calculated output power according to the above formulas (1) and (2) includes 10dBm, 20dBm, and 30dBm, and the total number of multiple terminals is 100, there are 10 terminals with an output power of 10dBm, 20 terminals with an output power of 20dBm, and 30 terminals with an output power of 30dBm. Then the probability percentages are: 10 / 100 = 10%, 20 / 100 = 20%, and 30 / 100 = 30%.

[0070] It should be noted that the network management platform can collect network management data (PHR) reported by all its subordinate base stations within a T-period. Following steps 1 to 4 above, it can obtain the real-time output power and probability percentage of each terminal that initiates uplink services within a T-period. That is, the percentage of the number of terminals with an output power of a certain dBm to the total number of terminals. Then, it can also draw a data graph of the output power points and probability percentages of each terminal.

[0071] Taking T=24 hours as an example, by fitting the trend chart obtained within 24 hours, a daily power distribution trend chart can be obtained (which can identify the main power concentration points), resulting in a statistically meaningful distribution model with output power on the horizontal axis and daily power on the vertical axis. Similarly, statistical models of the coverage areas of base stations under the current network management platform can be obtained monthly and yearly, and the main power concentration points at each stage can be further identified.

[0072] As another implementation, determining the probability proportion of multiple terminals in the existing network at different output powers may include:

[0073] The network management platform obtains the probability percentage of multiple terminals in the current network at different output powers from the base station side.

[0074] Here, the network management platform determines the probability percentage of multiple terminals in the existing network at different output powers, which can specifically include:

[0075] Step 1: The base station obtains network management data reported by multiple terminals.

[0076] Here, the network management data may refer to PHR.

[0077] Here, when multiple terminals access the network, the base station configures each terminal to periodically report its PHR. When each terminal is in a connected state and performing uplink services, each terminal periodically reports its PHR; the PHR carries PH and Pcmax information.

[0078] Step 2: The base station parses the PHR reported by each terminal to the base station to obtain PH and Pcmax information.

[0079] Step 3: When PH is greater than or equal to 0, calculate the actual output power of each terminal in the current network according to formula (1) above. When PH is less than 0, calculate the actual output power of each terminal in the current network according to formula (2) above.

[0080] Step 4: The base station counts the total number of multiple terminals and the number of terminals at each output power point. Based on the total number of multiple terminals and the number of terminals at each output power point, the probability ratio of multiple terminals at different output powers is calculated.

[0081] Assuming that the calculated output power according to the above formulas (1) and (2) includes 10dBm, 20dBm, and 30dBm, and the total number of multiple terminals is 100, there are 10 terminals with an output power of 10dBm, 20 terminals with an output power of 20dBm, and 30 terminals with an output power of 30dBm. Then the probability percentages are: 10 / 100 = 10%, 20 / 100 = 20%, and 30 / 100 = 30%.

[0082] Step 5: The base station reports the calculated probability percentages of multiple terminals at different output powers to the network management platform.

[0083] As another implementation method, determining the probability proportion of multiple terminals in the existing network at different output powers may include:

[0084] Here, the network management platform determines the probability percentage of multiple terminals in the existing network at different output powers, which can specifically include:

[0085] Step 1: The network management platform collects network management data from the base station side.

[0086] Here, the network management data may refer to PHR.

[0087] Here, when multiple terminals access the network, the base station configures each terminal to periodically report its PHR. When each terminal is in a connected state and performing uplink services, each terminal periodically reports its PHR; the PHR carries PH and Pcmax information.

[0088] Step 2: The network management platform parses the PHR reported by each terminal to the base station to obtain PH and Pcmax information.

[0089] Step 3: The network administrator imports the parsed PH and Pcmax information into an Excel spreadsheet installed on the network management platform.

[0090] Step 4: In the Excel spreadsheet, when PH is greater than or equal to 0, calculate the actual output power of each terminal in the network according to the above formula (1); when PH is less than 0, calculate the actual output power of each terminal in the network according to the above formula (2).

[0091] Step 5: The network management platform counts the total number of multiple terminals and the number of terminals at each output power point. Based on the total number of multiple terminals and the number of terminals at each output power point, it calculates the probability percentage of multiple terminals at different output powers.

[0092] Assuming that the calculated output power according to the above formulas (1) and (2) includes 10dBm, 20dBm, and 30dBm, and the total number of multiple terminals is 100, there are 10 terminals with an output power of 10dBm, 20 terminals with an output power of 20dBm, and 30 terminals with an output power of 30dBm. Then the probability percentages are: 10 / 100 = 10%, 20 / 100 = 20%, and 30 / 100 = 30%.

[0093] In one embodiment, determining the power consumption of each of the plurality of terminals at different output powers includes:

[0094] For each terminal, the power consumption of the corresponding terminal under different output powers is determined by utilizing the different output powers and efficiencies of the corresponding terminal in the existing network.

[0095] It should be noted that determining the power consumption of each terminal at different output power requires specialized power consumption testing tools.

[0096] In other words, after determining the different output powers of each terminal in the existing network, a specialized power consumption testing tool is used to test the efficiency of the terminal under different output powers.

[0097] In other words, terminal manufacturers can use specialized power consumption testing tools to test the efficiency of the terminal at different output powers and provide the data to the network management platform; alternatively, laboratory personnel can use specialized power consumption testing tools to test the efficiency of the terminal at different output powers and store the efficiency data obtained in the network management platform.

[0098] Here, the power consumption of each terminal at different output powers can be calculated according to the following formula (3), as follows:

[0099] P 0_n =P out_n ÷E n (3)

[0100] Among them, P 0_n P represents the power consumption of the terminal at different output powers. out_n E represents the actual output power of the terminal. n This indicates the efficiency of the terminal at different output powers.

[0101] In one embodiment, determining the power consumption of each of the plurality of terminals at different output powers includes:

[0102] For each terminal, when the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, determine the power consumption of the corresponding terminal under different output power.

[0103] Step 202: Based on the probability ratio and the power consumption, calculate the total power consumption of each terminal.

[0104] In one embodiment, calculating the total power consumption of each terminal based on the probability ratio and the power consumption includes:

[0105] The determined probability percentage and the power consumption are stored locally;

[0106] Using the probability percentage and power consumption stored locally, the total power consumption of each terminal is calculated.

[0107] In other words, the determined probability ratio and power consumption can be stored locally first, and then the stored probability ratio and power consumption can be used to calculate the total power consumption of each terminal.

[0108] In one embodiment, calculating the total power consumption of each terminal based on the probability ratio and the power consumption includes:

[0109] For each terminal, the power consumption of the corresponding terminal at different output powers is multiplied by the corresponding probability ratio to obtain multiple first values;

[0110] Summing the multiple first values ​​yields the second value;

[0111] The second value is taken as the total power consumption of the corresponding terminal.

[0112] Here, we can calculate the product of the power consumption of each terminal at different output powers and the corresponding probability ratio according to the following formula (4), as follows:

[0113] P prob_n =P 0_n ×P n (4)

[0114] Among them, P prob_n P represents the product of the terminal's power consumption at different output powers and the corresponding probability percentage. 0_n This indicates that the terminal is at different output power P out_n Power consumption under P n This indicates that the terminal is at different output power P out_n The probability percentage of each case. n takes values ​​from 1 to N, where N is an integer greater than 1.

[0115] Here, the total power consumption of each terminal can be calculated according to the following formula (5), that is, the second value is as follows:

[0116] P sum =P prob_1 +P prob_2 +......+P prob_n (5)

[0117] Among them, P sum P represents the total power consumption of the terminal. prob_1 This indicates that the terminal outputs power P out_1 The first value of P prob_2 This indicates that the terminal outputs power P out_2 The first value below, and so on, P prob_n This indicates that the terminal outputs power P out_n The first value below.

[0118] In one embodiment, the method further includes:

[0119] Determine the probability proportion of power amplifiers in multiple terminals in the current network at different output powers; and determine the power consumption of power amplifiers in each terminal at different output powers.

[0120] Based on the probability ratio and the power consumption, calculate the total power consumption of the power amplifier in each terminal.

[0121] It is understandable that determining the probability proportion of power amplifiers in multiple terminals in the current network at different output powers is similar to determining the probability proportion of multiple terminals in the current network at different output powers, and will not be elaborated here. Determining the power consumption of the power amplifier in each terminal at different output powers is similar to determining the power consumption of each terminal at different output powers, and will not be elaborated here.

[0122] It is understandable that the probability ratio of power amplifiers in multiple terminals in the current network at different output powers is determined; when the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, the power consumption of the power amplifiers in the corresponding terminal at different output powers is determined. In this way, the total power consumption of the power amplifiers in each terminal can be calculated based on the determined probability ratio and power consumption.

[0123] It should be noted that the data processing method provided in this embodiment of the invention can also be used to evaluate the total power consumption of the power amplifiers in the terminal in the existing network. The method for determining the total power consumption of the power amplifiers in the terminal is similar to the method for determining the total power consumption of the terminal, and will not be described again here.

[0124] The embodiments of the present invention have the following advantages:

[0125] (1) Determine the probability ratio of multiple terminals in the current network at different output powers; and determine the power consumption of each terminal in the multiple terminals at different output powers; based on the probability ratio and the power consumption, calculate the total power consumption of each terminal. Compared with the method of estimating terminal power consumption using the terminal's service model in related technologies, this method can combine the actual output power and power consumption of the terminal in the current network, thereby improving the accuracy of estimating terminal power consumption, making up for the defects and deficiencies in the terminal power consumption estimation system in related technologies, and further improving the terminal power consumption estimation system.

[0126] (2) Combining the actual output power and power consumption of the terminal in the screen-off state can significantly improve the accuracy of terminal power consumption prediction in the screen-off state.

[0127] (3) It is applicable to evaluating the total power consumption of the terminal and also applicable to evaluating the total power consumption of the power amplifier in the terminal.

[0128] Figure 3 This is a schematic diagram illustrating the specific implementation flow of the data processing method according to an embodiment of the present invention, as shown below. Figure 3 As shown, the method includes steps 301 to 303:

[0129] Step 301: Determine the probability percentage of power amplifiers in multiple terminals in the current network at different output powers.

[0130] Here, based on the probability ratio, a model can be obtained of the proportion of different output powers of the power amplifier in the terminal in the current network; this proportion model represents the correspondence between the output power of the power amplifier in the terminal and the probability ratio.

[0131] Step 302: Determine the power consumption of the power amplifier in each terminal at different output powers.

[0132] Here, power consumption can refer to power consumption.

[0133] Here, specialized power consumption testing tools can be used to test the efficiency of the power amplifier in the terminal at different output powers.

[0134] Here, the power consumption of the power amplifier in the terminal at different output powers can be calculated according to the following formula (6), as follows:

[0135] PPA _n =PPA out_n ÷PAE n (6)

[0136] Among them, PPA _n PPA represents the power consumption of the power amplifier in the terminal at different output powers. out_n PAE represents the different output powers of the power amplifier in the terminal. n This indicates the efficiency of the power amplifier in the terminal at different output powers.

[0137] Here, PPA _n Multiplying by a time period gives the energy consumption of the power amplifier in the terminal during that time period.

[0138] Here, the power consumption of the power amplifier in the terminal at different output powers can also be calculated according to the following formula (7), as follows:

[0139] PPA _n =VccPA _n ×IccPA_ n (7)

[0140] Among them, PPA _n VccPA represents the power consumption of the power amplifier in the terminal at different output powers. _n IccPA_ represents the operating voltage of the power amplifier in the terminal obtained through testing. n This indicates the operating current of the power amplifier in the terminal, obtained through testing.

[0141] Step 303: Based on the probability ratio and the power consumption, calculate the total power consumption of the power amplifier in each terminal.

[0142] Here, we can calculate the product of the power consumption of the power amplifier in each terminal at different output powers and the corresponding probability ratio according to the following formula (8), as follows:

[0143] PPA prob_n =PPA _n ×P n (8)

[0144] Among them, PPA prob_n This indicates that the power amplifier in each terminal has different output power PPAs. out_n The product of power consumption and the corresponding probability percentage, PPA _n This indicates that the power amplifier in the terminal has different output power PPAs. out_n Power consumption under P n This indicates that the power amplifiers in multiple terminals in the current network have different output power PPAs. out_n The probability percentage of each case. n takes values ​​from 1 to N, where N is an integer greater than 1.

[0145] Here, the total power consumption of the power amplifier in each terminal can be calculated according to the following formula (9), as follows:

[0146] PPA sum =PPA prob_1 +PPA prob_2 +......+PPA prob_n (9)

[0147] Among them, PPA sum This represents the total power consumption of the power amplifiers in each terminal.

[0148] Table 1 is a schematic diagram of the probability ratio of the power amplifier (PA) in the terminal at different output powers and the corresponding power consumption. As shown in Table 1, taking the output power of the PA in the terminal as P1 as an example, we determine the probability ratio of the PA in the terminal at output power P1 as B1%, and determine the power consumption of the PA in the terminal at output power P1 as P1 / A1. Thus, we can obtain the product of the power consumption of the PA in the terminal at output power PA1 and the corresponding probability ratio as B1×P1 / A1.

[0149] Table 1

[0150]

[0151]

[0152] Table 2 is a schematic diagram of the total power consumption of the power amplifier (PA) in the terminal. As shown in Table 2, the probability ratio of the PA in the terminal at different output powers is determined, and the power consumption of the PA in the terminal at different output powers is determined. Based on the determined probability ratio and power consumption, the final total power consumption of the PA, PPAsum, can be obtained.

[0153] Table 2

[0154]

[0155]

[0156] This example has the following advantages:

[0157] (1) It is applicable to evaluating the total power consumption of power amplifiers in terminals, significantly optimizing the power consumption prediction system of power amplifiers in terminals, improving the accuracy of power consumption prediction of power amplifiers in terminals, helping to optimize the power consumption performance of power amplifiers in terminals, and providing a reference for power consumption performance in terminal selection of power amplifiers.

[0158] Figure 4 This is a schematic diagram illustrating the specific implementation flow of the data processing method according to an embodiment of the present invention, as shown below. Figure 4 As shown, the method includes steps 401 to 403:

[0159] Step 401: Determine the probability proportion of power amplifiers in multiple terminals in the current network at different output powers.

[0160] Here, based on the probability ratio, a model can be obtained of the proportion of different output powers of the terminal in the current network; this proportion model represents the correspondence between the terminal output power and the probability ratio.

[0161] Step 402: When the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, determine the power consumption of the corresponding terminal's power amplifier at different output powers.

[0162] Here, power consumption can refer to power consumption.

[0163] Here, when the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, the power consumption of each terminal's power amplifier at different output powers can be calculated according to the following formula (10), as follows:

[0164] PUE _n =PUE out_n ÷E n (10)

[0165] Among them, PUE _nPUE represents the power consumption of the power amplifier in the terminal at different output powers when the terminal is in a screen-off state and is performing a specific continuous uplink service. out_n E represents the different output powers of the power amplifier in the terminal when the terminal is in a screen-off state and is performing a specific continuous uplink service. n This indicates the efficiency of the power amplifier in the terminal at different output powers when the terminal is in a screen-off state and is performing a specific continuous uplink service.

[0166] Step 403: Based on the probability ratio and the power consumption, calculate the total power consumption of the power amplifier in each terminal.

[0167] Here, we can combine the probability proportions of power amplifiers in multiple terminals in the current network at different output powers, as well as the efficiency of the power amplifiers in the terminals at different output powers, to obtain the power consumption of the power amplifiers in the terminals at different output powers. Then, we sum the power consumption of the power amplifiers in the terminals at different output powers to obtain the total power consumption of the power amplifiers in the terminal.

[0168] Table 3 is a schematic diagram of the total power consumption of the power amplifier (PA) in the terminal. As shown in Table 3, the probability ratio of the PA in the terminal at different output powers is determined. When the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, the power consumption of the PA in the terminal at different output powers is determined. Based on the determined probability ratio and power consumption, the final total power consumption PUEsum of the PA can be obtained.

[0169] Table 3

[0170]

[0171]

[0172] This example has the following advantages:

[0173] (1) Evaluate the power consumption performance of the communication system of different terminals when they are in a screen-off state and a specific continuous uplink service state.

[0174] In other words, it provides an evaluation method for assessing the power consumption (baseband IC, BBIC, radio frequency IC, radio frequency front-end modules, etc.) of terminal products in the existing communication system.

[0175] To implement the data processing method of the present invention, the present invention also provides a data processing device. Figure 5This is a schematic diagram of the composition structure of the data processing device according to an embodiment of the present invention, as shown below. Figure 5 As shown, the device includes:

[0176] The first processing unit 51 is used to determine the probability ratio of multiple terminals in the current network at different output powers.

[0177] The second processing unit 52 is used to determine the power consumption of each of the plurality of terminals under different output powers;

[0178] The third processing unit 53 is used to calculate the total power consumption of each terminal based on the probability ratio and the power consumption.

[0179] In one embodiment, the second processing unit 52 is specifically used for:

[0180] For each terminal, the power consumption of the corresponding terminal under different output powers is determined by utilizing the different output powers and efficiencies of the corresponding terminal in the existing network.

[0181] In one embodiment, the third processing unit 53 is specifically used for:

[0182] For each terminal, the power consumption of the corresponding terminal at different output powers is multiplied by the corresponding probability ratio to obtain multiple first values;

[0183] Summing the multiple first values ​​yields the second value;

[0184] The second value is taken as the total power consumption of the corresponding terminal.

[0185] In one embodiment, the second processing unit 52 is specifically used for:

[0186] For each terminal, when the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, determine the power consumption of the corresponding terminal under different output power.

[0187] In one embodiment, the third processing unit 53 is specifically used for:

[0188] The determined probability percentage and the power consumption are stored;

[0189] Using the probability percentage and power consumption stored locally, the total power consumption of each terminal is calculated.

[0190] In one embodiment, the device is further configured to:

[0191] Determine the probability proportion of power amplifiers in multiple terminals in the current network at different output powers; and determine the power consumption of power amplifiers in each terminal at different output powers.

[0192] Based on the probability ratio and the power consumption, calculate the total power consumption of the power amplifier in each terminal.

[0193] In practical applications, the first processing unit 51, the second processing unit 52, and the third processing unit 53 can be implemented by the processor in the data processing device.

[0194] It should be noted that the data processing apparatus provided in the above embodiments is only illustrated by the division of the above program modules. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the apparatus can be divided into different program modules to complete all or part of the processing described above. In addition, the data processing apparatus and data processing method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0195] This invention also provides a network device, such as... Figure 6 As shown, it includes:

[0196] Communication interface 61 enables information exchange with other devices;

[0197] The processor 62, connected to the communication interface 61, is used to execute the methods provided by one or more technical solutions on the network device side when running a computer program. The computer program is stored in the memory 63.

[0198] It should be noted that the specific processing procedures of the processor 62 and the communication interface 61 are detailed in the method embodiment and will not be repeated here.

[0199] Of course, in practical applications, the various components in network device 60 are coupled together through bus system 64. It can be understood that bus system 64 is used to implement communication between these components. In addition to a data bus, bus system 64 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 6 The general labeled all buses as Bus System 64.

[0200] The memory 63 in this embodiment is used to store various types of data to support the operation of the network device 60. Examples of such data include any computer program used to operate on the network device 60.

[0201] The methods disclosed in the embodiments of this application can be applied to the processor 62, or implemented by the processor 62. The processor 62 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 integrated logic circuit of the hardware or by instructions in the form of software in the processor 62. The processor 62 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 62 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this application can be directly reflected as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in the memory 63. The processor 62 reads the information in the memory 63 and completes the steps of the aforementioned method in combination with its hardware.

[0202] In an exemplary embodiment, the network device 60 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0203] It is understood that the memory (memory 63) in the embodiments of this application can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but 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), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0204] In an exemplary embodiment, the present invention also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, such as a memory storing a computer program, which can be executed by the processor 62 of the network device 60 to complete the steps described in the aforementioned network device-side method. The computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM.

[0205] It should be noted that terms such as "first" and "second" are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0206] Furthermore, the technical solutions described in the embodiments of the present invention can be combined arbitrarily without conflict.

[0207] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A data processing method, characterized in that, The method includes: Determine the probability percentage of multiple terminals in the current network at different output powers; and determine the power consumption of each of the multiple terminals at different output powers; the probability percentage is calculated based on the total number of multiple terminals and the number of terminals at each output power point. Based on the probability ratio and the power consumption, the total power consumption of each terminal is calculated.

2. The method according to claim 1, characterized in that, Determining the power consumption of each of the plurality of terminals at different output powers includes: For each terminal, the power consumption of the corresponding terminal under different output powers is determined by utilizing the different output powers and efficiencies of the corresponding terminal in the existing network.

3. The method according to claim 1 or 2, characterized in that, The calculation of the total power consumption of each terminal based on the probability ratio and the power consumption includes: For each terminal, the power consumption of the corresponding terminal at different output powers is multiplied by the corresponding probability ratio to obtain multiple first values; Summing the multiple first values ​​yields the second value; The second value is taken as the total power consumption of the corresponding terminal.

4. The method according to claim 1, characterized in that, Determining the power consumption of each of the plurality of terminals at different output powers includes: For each terminal, when the corresponding terminal is in a screen-off state and is performing a specific continuous uplink service, determine the power consumption of the corresponding terminal under different output power.

5. The method according to claim 1, characterized in that, The calculation of the total power consumption of each terminal based on the probability ratio and the power consumption includes: The determined probability percentage and the power consumption are stored; Using the probability percentage and power consumption stored locally, the total power consumption of each terminal is calculated.

6. The method according to claim 1, characterized in that, The method further includes: Determine the probability proportion of power amplifiers in multiple terminals in the current network at different output powers; and determine the power consumption of power amplifiers in each terminal at different output powers. Based on the probability ratio and the power consumption, calculate the total power consumption of the power amplifier in each terminal.

7. A data processing apparatus, characterized in that, include: The first processing unit is used to determine the probability proportion of multiple terminals in the current network at different output powers; The probability percentage is calculated based on the total number of multiple terminals and the number of terminals at each output power point. The second processing unit is used to determine the power consumption of each of the plurality of terminals under different output powers; The third processing unit is used to calculate the total power consumption of each terminal based on the probability ratio and the power consumption.

8. A data processing apparatus, characterized in that, include: Communication interface, The processor is used to determine the probability percentage of multiple terminals in the current network at different output powers. The probability ratio is calculated based on the total number of multiple terminals and the number of terminals at each output power point; and the power consumption of each terminal at different output powers is determined; based on the probability ratio and the power consumption, the total power consumption of each terminal is calculated.

9. A network device, characterized in that, This includes a processor and memory for storing computer programs that can run on the processor. When the processor is used to run the computer program, it performs the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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