Device noise density determination method, device, electronic device and storage medium

Abstract

The present invention provides a method, apparatus, electronic device and storage medium for determining device noise density. The method comprises: obtaining a gate voltage and device parameters of a device, determining an effective value of a first noise fitting parameter of the device according to the gate voltage, determining a first noise density of the device in an inversion region and a second noise density of the device in a subthreshold region based on the device parameters and the effective value of the first noise fitting parameter, and determining a total noise density of the device according to the first noise density and the second noise density. The method can more accurately reflect the actual first noise density (noise density in the inversion region) and second noise density (noise density in the subthreshold region) of the device, thereby improving the accuracy of the first noise density and the second noise density determined according to the device parameters and the effective value of the first noise fitting parameter, thereby improving the accuracy of the total noise density of the semiconductor device obtained by simulation using BSIM4.

Description

Technical Field

[0001] The present invention relates to the field of transistor noise processing technology, and in particular to a device noise density determination method, apparatus, electronic equipment and storage medium. Background Art

[0002] With the development of semiconductor manufacturing technology, the quality requirements for semiconductor devices are becoming increasingly higher. The quality of semiconductor devices is closely related to their noise characteristics. Currently, the quality and reliability of semiconductor devices are mainly screened by detecting and analyzing the properties of semiconductor device noise. The general noise model BSIM4 (Berkeley Short-channel IGFET Model) for detecting and analyzing the properties of semiconductor device noise simulates the noise density in the inversion region and non-inversion region of the semiconductor device using the same fitting parameters. The noise density of the semiconductor device in the subthreshold region and the noise density in the inversion region can be obtained. Among them, the noise density of the semiconductor device in the subthreshold region is close to the noise density of the semiconductor device in the inversion region.

[0003] However, in reality, the noise density of semiconductor devices in the subthreshold region is much greater than the noise density in the inversion region. Therefore, the noise density of the semiconductor in the subthreshold region reflected by the simulation using BSIM4 is not accurate enough, which in turn leads to the total noise density of the semiconductor device reflected by the simulation using BSIM4 being not accurate enough. How to improve the accuracy of the total noise density of the semiconductor device obtained by simulation using BSIM4 is an urgent problem to be solved. Summary of the Invention

[0004] The present invention provides a method, apparatus, electronic device and storage medium for determining device noise density, which can improve the accuracy of a first noise density of a device in an inversion region and a second noise density of a device in a subthreshold region, both of which are determined based on device parameters and the effective value of a first noise fitting parameter, thereby improving the accuracy of the total noise density of the device reflected by the noise model of BSIM4, that is, improving the simulation accuracy of the total noise density of BSIM4, and solving the problem of low simulation accuracy of the total noise density of BSIM4 due to the fact that the noise fitting parameter NOIA used in the noise density model of the device in the inversion region and the noise density model of the device in the subthreshold region is the same constant parameter.

[0005] According to a first aspect of the present invention, a method for determining device noise density is provided, the method comprising:

[0006] Obtaining the gate voltage and device parameters of the device;

[0007] determining a first noise fitting parameter effective value of the device according to the gate voltage;

[0008] Determining a first noise density of the device in an inversion region and a second noise density of the device in a subthreshold region based on the device parameters and the effective value of the first noise fitting parameter;

[0009] The total noise density of the device is determined based on the first noise density and the second noise density.

[0010] According to a second aspect of the present invention, there is provided an apparatus for determining device noise density, the apparatus comprising:

[0011] A parameter acquisition module is used to obtain the gate voltage and device parameters of the device;

[0012] A first determining module, configured to determine an effective value of a first noise fitting parameter of the device according to the gate voltage;

[0013] a second determining module, configured to determine a first noise density of the device in the inversion region and a second noise density of the device in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter;

[0014] A third determining module is configured to determine a total noise density of the device according to the first noise density and the second noise density.

[0015] According to a third aspect of the present invention, there is provided an electronic device comprising a processor and a memory,

[0016] The memory is used to store codes and related data;

[0017] The processor is configured to execute the code in the memory to implement the device noise density determination method as described in any one of the embodiments of the present invention.

[0018] According to a fourth aspect of the present invention, a storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for determining device noise density as described in any one of the embodiments of the present invention is implemented.

[0019] In an embodiment of the present invention, the gate voltage and device parameters of the device are obtained, and the effective value of the first noise fitting parameter of the device is determined based on the gate voltage. Then, based on the device parameters and the effective value of the first noise fitting parameter, the first noise density of the device in the inversion region and the second noise density of the device in the subthreshold region are determined, and the total noise density of the device is determined based on the first noise density and the second noise density. Since the effective value of the first noise fitting parameter is determined based on the gate voltage, changes with the gate voltage, and is not a constant parameter, when determining the first noise density of the device (semiconductor device) in the inversion region and the second noise density in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter, the first noise density and the second noise density are determined based on different effective values ​​of the first noise fitting parameter, so that the transition between the first noise density and the second noise density will not be too smooth, that is, BSIM4 no longer uses the same fitting parameters to simulate the noise density of the inversion region and the non-inversion region of the semiconductor device, but uses different fitting parameters to simulate the noise density of the inversion region and the non-inversion region of the semiconductor device, which can more accurately reflect the actual first noise density (noise density in the inversion region) and second noise density (noise density in the subthreshold region) of the device, so as to improve the accuracy of the determination of the first noise density and the second noise density, and thus improve the accuracy of simulating the total noise density of the semiconductor device using BSIM4. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is a flow chart of a method for determining device noise density provided by an embodiment of the present invention;

[0022] Figure 2 This is a process intention for constructing a noise fitting parameter effective value calculation model in the device noise density determination method provided by an embodiment of the present invention;

[0023] Figure 3 1 is a schematic diagram of a fitting of the effective value of the first noise fitting parameter and the gate voltage provided by an embodiment of the present invention;

[0024] Figure 4 is a structural diagram of a device provided by an embodiment of the present invention;

[0025] Figure 5 1 is a schematic structural diagram of a device noise density determination apparatus provided by an embodiment of the present invention;

[0026] Figure 6 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0028] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way are interchangeable where appropriate, so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or apparatus.

[0029] The technical solution of the present invention is described in detail below with reference to specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0030] Figure 1 This is a flow chart of a device noise density determination method provided by an embodiment of the present invention. This method can be executed by a device noise density determination device, which can be implemented in software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device, such as a computer, a server, etc. The following embodiments will be described using the device integrated into an electronic device as an example. Figure 1 , the method may specifically include the following steps:

[0031] Step 101: Obtain the gate voltage and device parameters of the device.

[0032] Among them, the device can be a Metal Oxide Semiconductor Field Effect Transistor (MOSFET), which is a device made of three materials: metal, oxide (SiO2 or SiN), and semiconductor. The gate voltage can be understood as the voltage used to control the conductive characteristics of the Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET). Device parameters are used to characterize device-related device characteristics. Device parameters are associated with the device type and vary from device to device.

[0033] In the embodiment of the present invention, the gate voltage is associated with the device type, and the gate voltages of devices of different types are different.

[0034] Step 102: Determine an effective value of a first noise fitting parameter of the device according to the gate voltage.

[0035] Among them, the noise model BSIM4 includes an inversion region noise density model of the device in the inversion region and a subthreshold region noise density model of the device in the subthreshold region. The noise fitting parameters used in the inversion region noise density model of the device in the inversion region include a first noise fitting parameter (NOIA), a third noise fitting parameter (NOIB) and a fourth noise fitting parameter (NOIC). The noise fitting parameters used in the subthreshold region noise density model of the device in the subthreshold region also include the first noise fitting parameter (NOIA). The effective value of the above-mentioned first noise fitting parameter can be understood as the effective value of the fitted first noise fitting parameter NOIA.

[0036] In an optional implementation, after the gate voltage of the device is acquired, the effective value of the first noise fitting parameter of the device may be calculated according to the gate voltage.

[0037] Specifically, the effective value of the first noise fitting parameter may be calculated in combination with the gate voltage, the effective value of the inversion region noise, the effective value of the subthreshold region noise, and the like.

[0038] Step 103 : determining a first noise density of the device in the inversion region and a second noise density of the device in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter.

[0039] In the embodiment of the present invention, the device parameters may be understood as parameters of a BSIM4 model required for calculating a first noise density of the device in the inversion region and a second noise density of the device in the subthreshold region.

[0040] In a specific embodiment, device parameters may include, but are not limited to, device temperature, effective mobility, channel current, effective channel length, frequency of the second noise fitting parameter, first model parameters, second model parameters, third model parameters, gate oxide capacitance, source carrier concentration, drain carrier concentration, effective channel width, and channel effect parameters. The first noise density can be understood as the noise density of the device in the inversion region; the second noise density can be understood as the noise density of the device in the subthreshold region.

[0041] Step 104 : determining a total noise density of the device according to the first noise density and the second noise density.

[0042] where total noise density is the final noise density of the device.

[0043] In an embodiment of the present invention, the total noise density may be determined according to a first noise density of the device in the inversion region and a second noise density of the device in the subthreshold region.

[0044] Specifically, the total noise density of the device can be determined by calculating the product and the sum of the first noise density and the second noise density, and then determining the total noise density of the device according to the product and the sum.

[0045] In an embodiment of the present invention, the gate voltage and device parameters of the device are obtained, and the effective value of the first noise fitting parameter of the device is determined based on the gate voltage. Then, based on the device parameters and the effective value of the first noise fitting parameter, the first noise density of the device in the inversion region and the second noise density of the device in the subthreshold region are determined, and the total noise density of the device is determined based on the first noise density and the second noise density. Since the effective value of the first noise fitting parameter is determined based on the gate voltage, changes with the gate voltage, and is not a constant parameter, when determining the first noise density of the device (semiconductor device) in the inversion region and the second noise density in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter, the first noise density and the second noise density are determined based on different effective values ​​of the first noise fitting parameter, so that the transition between the first noise density and the second noise density will not be too smooth, that is, BSIM4 no longer uses the same fitting parameters to simulate the noise density of the inversion region and the non-inversion region of the semiconductor device, but uses different fitting parameters to simulate the noise density of the inversion region and the non-inversion region of the semiconductor device, which can more accurately reflect the actual first noise density (noise density in the inversion region) and second noise density (noise density in the subthreshold region) of the device, so as to improve the accuracy of the determination of the first noise density and the second noise density, and thus improve the accuracy of simulating the total noise density of the semiconductor device using BSIM4.

[0046] In one embodiment, determining the effective value of the first noise fitting parameter of the device according to the gate voltage may be performed by substituting the gate voltage into a pre-built noise fitting parameter effective value calculation model, and determining the effective value of the first noise fitting parameter of the device according to the noise fitting parameter effective value calculation model.

[0047] Specifically, in combination with the above-mentioned embodiments, the gate voltage, the effective value of the inversion region noise and the effective value of the subthreshold region noise can be substituted into the noise fitting parameter effective value calculation model, and the first noise fitting parameter effective value of the device can be calculated based on the noise fitting parameter effective value calculation model.

[0048] In the embodiment of the present invention, the noise fitting parameter effective value calculation model can be expressed by the following formula (1):

[0049]

[0050] Wherein, NOIAeff represents the effective value of the first noise fitting parameter, NOIAH represents the effective value of the subthreshold region noise, NOIAL represents the effective value of the inversion region noise, Vgs represents the gate voltage, V0 represents the first fitting parameter, Vth0 represents the threshold voltage, and MP represents the second fitting parameter. The effective value of the inversion region noise can be understood as the effective value of NOIA of the fitted device in the inversion region, and the effective value of the subthreshold region noise can be understood as the effective value of NOIA of the fitted device in the subthreshold region. The first fitting parameter and the second fitting parameter are fitting parameters determined by the model after fitting and can be constant parameters.

[0051] In some embodiments, as Figure 2 As shown, the construction process of the noise fitting parameter effective value calculation model may include:

[0052] Step 201: Obtain the threshold voltage of the device.

[0053] Step 202: Determine a plurality of gate voltages according to the threshold voltage.

[0054] Step 203: Acquire multiple noise fitting parameters of the device at multiple gate voltages.

[0055] Step 204 : Adjust at least one noise fitting parameter among the multiple noise fitting parameters, and perform parameter fitting of the effective value of the noise fitting parameter based on the adjusted noise fitting parameter to obtain a noise fitting parameter effective value calculation model.

[0056] In an optional embodiment, the first noise fitting parameter can be changed while the second noise fitting parameter, the third noise fitting parameter and the fourth noise fitting parameter are kept unchanged to perform parameter fitting of the effective value of the first noise fitting parameter and obtain a noise fitting parameter effective value calculation model.

[0057] For example, Vth0 represents the threshold voltage of the device, and VDD represents the power supply voltage; to obtain the threshold voltage Vth0, different gate voltages can be Vth0-0.2V, Vth0-0.1V, Vth0, Vth0+0.1V, Vth0+0.2V, VDD / 2 and VDD, wherein, before obtaining the first noise fitting parameter, the second noise fitting parameter, the third noise fitting parameter and the fourth noise fitting parameter of the device under multiple gate voltages, it is also necessary to set the drain voltage Vd to 0.1V, VDD=2Vd, the source voltage Vs to 0V, and the substrate voltage Vb to 0V.

[0058] Specifically, the first noise fitting parameter (NOIA), the second noise fitting parameter (ef), the third noise fitting parameter (NOIB) and the fourth noise fitting parameter (NOIC) of the device at multiple gate voltages are obtained, as shown in Table 1. By changing the multiple first noise fitting parameters to obtain multiple first noise fitting parameters (NOIA1, NOIA2, NOIA3, NOIA4, NOIA5, NOIA6, NOIA7), keeping the multiple second noise fitting parameters, the multiple third noise fitting parameters and the multiple fourth noise fitting parameters unchanged, and using formula (1) to perform parameter fitting of the effective values ​​of the first noise fitting parameters at different gate voltages, it can be obtained as follows: Figure 3 The fitting diagram of the effective value of the first noise fitting parameter and the gate voltage is shown in FIG. Figure 3 , NOIAH, NOIAL, V0, and MP in formula (1) can be determined, and then the functional relationship between the effective value of the first noise fitting parameter and the gate voltage can be obtained, that is, formula (1). When actually determining the effective value of the first noise fitting parameter of the device, the effective value of the first noise fitting parameter of the device can be determined by only obtaining the gate voltage.

[0059] Table 1 Noise fitting parameters at different gate voltages

[0060]

[0061] In some embodiments, the device may be Figure 4 The multi-finger gate structure shown in FIG. Figure 4 The S is the source terminal and D is the drain terminal.

[0062] In the above embodiment, by setting the structure of the device to a multi-finger gate structure, the total width of the device channel can be increased, so that the source-drain current of the device in the subthreshold region meets the preset conditions at different gate voltages, such as being greater than 0.1uA, etc., thereby ensuring the data accuracy of the first noise fitting parameter, the second noise fitting parameter, the third noise fitting parameter, and the fourth noise fitting parameter of the device in the subthreshold region obtained at different gate voltages, so as to improve the reliability and accuracy of the constructed formula (1) (i.e., the noise fitting parameter effective value calculation model). Furthermore, the accuracy of the effective value of the first noise fitting parameter of the device determined based on the noise fitting parameter effective value calculation model can be improved, ensuring the accuracy of determining the first noise density and the second noise density based on the device parameters and the effective value of the first noise fitting parameter, and further improving the accuracy of determining the total noise density of the device based on the first noise density and the second noise density, that is, further improving the simulation accuracy of the total noise density of BSIM4.

[0063] In an optional embodiment, the device parameters mentioned above, namely temperature, effective mobility, channel current, effective channel length, frequency of the second noise fitting parameter, first model parameter, second model parameter, third model parameter, gate oxide capacitance, source carrier concentration, drain carrier concentration, effective channel width, channel effect parameter and effective value of the first noise fitting parameter, can be substituted into the inversion region noise density model, and the first noise density of the device in the inversion region can be calculated using the inversion region noise density model.

[0064] In a specific embodiment, the inversion region noise density model can be expressed by the following formula (2):

[0065]

[0066] Among them, S id,inv (f) represents the first noise density of the device in the inversion region, k B represents the constant quantity, T represents the temperature, q represents the charge constant, μ eff represents the effective mobility, I ds represents the channel current, C oxe represents the gate oxide capacitance, L eff represents the effective channel length, LINTNOI represents the first model parameter, A bulk represents the second model parameter, NOIAeff represents the effective value of the first noise fitting parameter, N0 represents the source end carrier concentration, N l Represents the drain carrier concentration, N * represents the third model parameter, ef represents the second noise fitting parameter, f ef represents the frequency of the second noise fitting parameter, NOIB represents the third noise fitting parameter, NOIC represents the fourth noise fitting parameter, Lclm represents the channel effect parameter, W eff Represents the effective channel width.

[0067] In an embodiment of the present invention, the first noise density of the device in the inversion region is determined by substituting the temperature, effective mobility, channel current, effective channel length, frequency of the second noise fitting parameter, first model parameter, second model parameter, third model parameter, gate oxide capacitance, source carrier concentration, drain carrier concentration, effective channel width, channel effect parameter and effective value of the first noise fitting parameter into the inversion region noise density model. The effective value of the first noise fitting parameter NOIAeff changes with the gate voltage, so that the transition between the first noise density of the device in the inversion region determined according to the device parameters and the effective value of the first noise fitting parameter and the second noise density of the device in the subthreshold region will not be too smooth, and the actual first noise density and second noise density of the device can be reflected more accurately, thereby improving the accuracy of the first noise density of the device in the inversion region determined according to the device parameters and the effective value of the first noise fitting parameter, thereby improving the accuracy of the total noise density of the device reflected by the noise model of BSIM4, that is, improving the simulation accuracy of the total noise density of BSIM4.

[0068] In one embodiment, the effective value of the first noise fitting parameter, temperature, channel current, effective channel length, effective channel width, frequency of the second noise fitting parameter and the third model parameter can also be substituted into the subthreshold region noise density model, and the second noise density of the device in the subthreshold region can be calculated using the subthreshold region noise density model.

[0069] In the embodiment of the present invention, the subthreshold region noise density model can be expressed by the following formula (3):

[0070]

[0071] Among them, S id,subVt (f) represents the second noise density of the device in the subthreshold region, NOIAeff represents the effective value of the first noise fitting parameter, k B represents the constant quantity, T represents the temperature, I ds Represents the channel current, W eff Indicates the effective channel width, L eff represents the effective channel length, ef represents the second noise fitting parameter, f ef The frequency of the second noise fitting parameter, N * represents the third model parameter.

[0072] In an embodiment of the present invention, the second noise density of the device in the subthreshold region is determined by substituting the effective value of the first noise fitting parameter, temperature, channel current, effective channel length, effective channel width, frequency of the second noise fitting parameter and the third model parameter into the subthreshold region noise density model. This is equivalent to replacing the constant parameter (first noise fitting parameter NOIA) used in the original noise density model of the device in the subthreshold region with the effective value of the first noise fitting parameter NOIAeff that changes with the gate voltage. Since NOIAeff can better reflect the change of the effective value of the first noise fitting parameter with the gate voltage, the transition between the first noise density of the device in the inversion region and the second noise density of the device in the subthreshold region determined according to the device parameters and the effective value of the first noise fitting parameter will not be too smooth, and the actual first noise density and second noise density of the device can be reflected more accurately, thereby improving the accuracy of the second noise density of the device in the subthreshold region determined according to the device parameters and the effective value of the first noise fitting parameter, thereby improving the accuracy of the total noise density of the device reflected by the noise model of BSIM4, that is, improving the simulation accuracy of the total noise density of BSIM4.

[0073] As described above, when determining the total noise density of a device, the product and the sum of the first noise density and the second noise density may be calculated, and the total noise density of the device may be determined based on the product and the sum.

[0074] In an optional implementation, the first noise density and the second noise density may be substituted into a total noise density model, and the total noise density of the device may be determined using the total noise density model.

[0075] In the embodiment of the present invention, the total noise density model can be expressed by the following formula (4):

[0076]

[0077] Among them, S id (f) represents the total noise density of the device, S id,inv (f) represents the first noise density of the device in the inversion region, S id,subVt (f) shows the second noise density of the device in the subthreshold region.

[0078] Figure 5 FIG. 1 is a schematic diagram of a device noise density determination apparatus according to an embodiment of the present invention, which is suitable for executing a device noise density determination method according to an embodiment of the present invention. Figure 5 As shown, the device may specifically include:

[0079] Parameter acquisition module 301, used to obtain the gate voltage and device parameters of the device;

[0080] A first determining module 302 is configured to determine an effective value of a first noise fitting parameter of the device according to the gate voltage;

[0081] A second determining module 303 is configured to determine a first noise density of the device in the inversion region and a second noise density of the device in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter;

[0082] The third determining module 304 is configured to determine a total noise density of the device according to the first noise density and the second noise density.

[0083] Optionally, the first determining module 302 is specifically configured to:

[0084] Substitute the gate voltage into a pre-built noise fitting parameter effective value calculation model to determine a first noise fitting parameter effective value of the device. The noise fitting parameter effective value calculation model is:

[0085]

[0086] Among them, NOIAeff represents the effective value of the first noise fitting parameter, NOIAH represents the effective value of the subthreshold region noise, NOIAL represents the effective value of the inversion region noise, Vgs represents the gate voltage, V0 represents the first fitting parameter, Vth0 represents the threshold voltage, and MP represents the second fitting parameter.

[0087] Furthermore, the device also includes a model building module for building the noise fitting parameter effective value calculation model;

[0088] Model building modules, specifically for:

[0089] obtaining a threshold voltage of the device;

[0090] determining a plurality of gate voltages based on the threshold voltage;

[0091] Obtaining a plurality of noise fitting parameters of the device at the plurality of gate voltages;

[0092] At least one noise fitting parameter among the multiple noise fitting parameters is adjusted, and parameter fitting of the effective value of the noise fitting parameter is performed based on the adjusted noise fitting parameter to obtain the noise fitting parameter effective value calculation model.

[0093] Optionally, the device is a multi-finger gate structure.

[0094] Optionally, the device parameters include temperature, effective mobility, channel current, effective channel length, frequency of the second noise fitting parameter, first model parameter, second model parameter, third model parameter, gate oxide capacitance, source carrier concentration, drain carrier concentration, effective channel width, and channel effect parameter of the device;

[0095] The second determining module 303 determines a first noise density of the device in the inversion region according to the device parameters and the effective value of the first noise fitting parameter, including:

[0096] The temperature, the effective mobility, the channel current, the effective channel length, the frequency of the second noise fitting parameter, the first model parameter, the second model parameter, the third model parameter, the gate oxide capacitance, the source carrier concentration, the drain carrier concentration, the effective channel width, the channel effect parameter, and the effective value of the first noise fitting parameter are substituted into the inversion region noise density model to determine the first noise density of the device in the inversion region. The inversion region noise density model is:

[0097]

[0098] Among them, S id,inv (f) represents the first noise density of the device in the inversion region, k B represents the constant quantity, T represents the temperature, q represents the charge constant, μ eff represents the effective mobility, I ds represents the channel current, C oxe represents the gate oxide capacitance, L eff represents the effective channel length, LINTNOI represents the first model parameter, A bulk represents the second model parameter, NOIAeff represents the effective value of the first noise fitting parameter, N0 represents the source end carrier concentration, N l Represents the drain carrier concentration, N * represents the third model parameter, ef represents the second noise fitting parameter, f ef represents the frequency of the second noise fitting parameter, NOIB represents the third noise fitting parameter, NOIC represents the fourth noise fitting parameter, L clm represents the channel effect parameter, W eff Represents the effective channel width.

[0099] Optionally, the second determining module 303 determines a second noise density of the device in the subthreshold region according to the device parameter and the effective value of the first noise fitting parameter, including:

[0100] Substituting the effective value of the first noise fitting parameter, the temperature, the channel current, the effective channel length, the effective channel width, the frequency of the second noise fitting parameter, and the third model parameter into a subthreshold region noise density model to determine a second noise density of the device in the subthreshold region, the subthreshold region noise density model is:

[0101]

[0102] Among them, S id,subVt (f) represents the second noise density of the device in the subthreshold region, NOIAeff represents the effective value of the first noise fitting parameter, k B represents the constant quantity, T represents the temperature, I ds Represents the channel current, W eff Indicates the effective channel width, L eff represents the effective channel length, ef represents the second noise fitting parameter, f ef The frequency of the second noise fitting parameter, N * represents the third model parameter.

[0103] Optionally, the third determining module 304 is specifically configured to:

[0104] Substituting the first noise density and the second noise density into a total noise density model, and determining the total noise density of the device based on the total noise density model, the total noise density model is:

[0105]

[0106] Among them, S id (f) represents the total noise density of the device, S id,inv (f) represents the first noise density of the device in the inversion region, S id,subVt (f) shows the second noise density of the device in the subthreshold region.

[0107] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0108] The device noise density determination apparatus provided in an embodiment of the present invention can obtain the gate voltage and device parameters of the device, determine the effective value of the first noise fitting parameter of the device according to the gate voltage, determine the first noise density of the device in the inversion region and the second noise density of the device in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter, and determine the total noise density of the device according to the first noise density and the second noise density. The technical solution of the present invention, because the effective value of the first noise fitting parameter determined according to the gate voltage is no longer a constant parameter, can better reflect the change of the effective value of the first noise fitting parameter with the gate voltage, and thus the transition between the first noise density of the device (semiconductor device) in the inversion region and the second noise density of the device in the subthreshold region determined according to the device parameters and the effective value of the first noise fitting parameter will not be too smooth, that is, BSIM4 no longer uses the same fitting parameters to simulate the noise density of the inversion region and the non-inversion region of the semiconductor device, but uses different fitting parameters to simulate the noise density of the inversion region and the non-inversion region of the semiconductor device, which can more accurately reflect the noise density of the semiconductor device. The actual first noise density (noise density in the inversion region) and second noise density (noise density in the subthreshold region) of the device improve the accuracy of the first noise density of the device in the inversion region and the accuracy of the second noise density of the device in the subthreshold region determined according to the device parameters and the effective value of the first noise fitting parameters, thereby improving the accuracy of the total noise density of the semiconductor device obtained by simulation using BSIM4, and solving the problem that the total noise density of the semiconductor device reflected by simulation using BSIM4 is not accurate enough because BSIM4 simulates the noise density in the inversion region and non-inversion region of the semiconductor device by using the same fitting parameters.

[0109] In one embodiment, an electronic device is provided, which may be a server. Figure 6 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0110] Please refer to Figure 6 , provides an electronic device 50, comprising:

[0111] processor 51; and

[0112] a memory 52 for storing executable instructions of the processor;

[0113] The processor 51 is configured to execute the above-mentioned method by executing the executable instructions.

[0114] The processor 51 can communicate with the memory 52 via a bus 53 .

[0115] The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, programs, and a database. The internal memory provides an environment for the operation of the operating system and programs in the non-volatile storage medium. The database of the electronic device is used to store data such as gate voltage, device parameters, effective value of a first noise fitting parameter, first noise density, second noise density, and total noise density. When executed by the processor, the program implements the aforementioned method for determining device noise density.

[0116] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method when executed by a processor.

[0117] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining device noise density, characterized in that: The method comprises: Obtaining the gate voltage and device parameters of the device; Determining a first noise fitting parameter effective value of the device according to the gate voltage includes: Substitute the gate voltage into a pre-built noise fitting parameter effective value calculation model to determine a first noise fitting parameter effective value of the device. The noise fitting parameter effective value calculation model is: in, represents the effective value of the first noise fitting parameter, represents the effective value of subthreshold noise, represents the effective value of the inversion region noise, represents the gate voltage, represents the first fitting parameter, represents the threshold voltage, represents the second fitting parameter; Determining a first noise density of the device in an inversion region and a second noise density of the device in a subthreshold region based on the device parameters and the effective value of the first noise fitting parameter; The total noise density of the device is determined based on the first noise density and the second noise density.

2. The method according to claim 1, characterized in that Constructing the noise fitting parameter effective value calculation model, including: obtaining a threshold voltage of the device; determining a plurality of gate voltages based on the threshold voltage; Obtaining a plurality of noise fitting parameters of the device at the plurality of gate voltages; At least one noise fitting parameter among the multiple noise fitting parameters is adjusted, and parameter fitting of the effective value of the noise fitting parameter is performed based on the adjusted noise fitting parameter to obtain the noise fitting parameter effective value calculation model.

3. The method according to claim 1, characterized in that The device has a multi-finger gate structure.

4. The method according to claim 1, wherein The device parameters include the temperature of the device, effective mobility, channel current, effective channel length, frequency of the second noise fitting parameter, first model parameter, second model parameter, third model parameter, gate oxide capacitance, source carrier concentration, drain carrier concentration, effective channel width, and channel effect parameter; Determining a first noise density of the device in the inversion region according to the device parameter and the effective value of the first noise fitting parameter includes: The temperature, the effective mobility, the channel current, the effective channel length, the frequency of the second noise fitting parameter, the first model parameter, the second model parameter, the third model parameter, the gate oxide capacitance, the source carrier concentration, the drain carrier concentration, the effective channel width, the channel effect parameter, and the effective value of the first noise fitting parameter are substituted into the inversion region noise density model to determine the first noise density of the device in the inversion region. The inversion region noise density model is: in, Represents the first noise density of the device in the inversion region, represents a constant quantity, Indicates temperature, represents the charge constant, represents the effective mobility, represents the channel current, represents the gate oxide capacitance, represents the effective channel length, represents the first model parameter, represents the second model parameter, represents the effective value of the first noise fitting parameter, represents the carrier concentration at the source end, represents the drain carrier concentration, represents the third model parameter, represents the second noise fitting parameter, represents the frequency of the second noise fitting parameter, represents the third noise fitting parameter, represents the fourth noise fitting parameter, represents the channel effect parameter, Indicates the effective channel width.

5. The method according to claim 4, characterized in that Determining a second noise density of the device in a subthreshold region according to the device parameter and the effective value of the first noise fitting parameter includes: Substituting the effective value of the first noise fitting parameter, the temperature, the channel current, the effective channel length, the effective channel width, the frequency of the second noise fitting parameter, and the third model parameter into a subthreshold region noise density model to determine a second noise density of the device in the subthreshold region, the subthreshold region noise density model is: in, Represents the second noise density of the device in the subthreshold region, represents the effective value of the first noise fitting parameter, represents a constant quantity, Indicates temperature, represents the channel current, represents the effective channel width, represents the effective channel length, represents the second noise fitting parameter, represents the frequency of the second noise fitting parameter, represents the third model parameter.

6. The method according to claim 1, characterized in that Determining the total noise density of the device according to the first noise density and the second noise density includes: Substituting the first noise density and the second noise density into a total noise density model, and determining the total noise density of the device based on the total noise density model, the total noise density model is: in, represents the total noise density of the device, Represents the first noise density of the device in the inversion region, Represents the second noise density of the device in the subthreshold region.

7. A device for determining device noise density, characterized in that: The device comprises: A parameter acquisition module is used to obtain the gate voltage and device parameters of the device; A first determining module, configured to determine an effective value of a first noise fitting parameter of the device according to the gate voltage, includes: Substitute the gate voltage into a pre-built noise fitting parameter effective value calculation model to determine a first noise fitting parameter effective value of the device. The noise fitting parameter effective value calculation model is: in, represents the effective value of the first noise fitting parameter, represents the effective value of subthreshold noise, represents the effective value of the inversion region noise, represents the gate voltage, represents the first fitting parameter, represents the threshold voltage, represents the second fitting parameter; a second determining module, configured to determine a first noise density of the device in the inversion region and a second noise density of the device in the subthreshold region based on the device parameters and the effective value of the first noise fitting parameter; A third determining module is configured to determine a total noise density of the device according to the first noise density and the second noise density.

8. An electronic device, characterized in that: Including processor and memory, The memory is used to store codes and related data; The processor is configured to execute the code in the memory to implement the device noise density determination method according to any one of claims 1 to 6.

9. A storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for determining device noise density according to any one of claims 1 to 6 is implemented.

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