Digital pre-distortion correction method and device, electronic equipment and storage medium
Patent Information
- Application Number
- CN202611112011.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-24
- Publication Date
- 2026-11-03
AI Technical Summary
In existing Wi-Fi systems, digital predistortion correction technology cannot dynamically adjust the balance between power consumption and performance in different application scenarios, leading to problems such as excessive power consumption or performance degradation.
By continuously acquiring baseband information from protocol data units at each layer, forming a baseband information parameter set, and determining whether to enable digital predistortion correction based on preset filtering conditions, the appropriate model complexity is dynamically selected for correction, achieving on-demand activation and dynamic adaptation.
While ensuring communication quality, the system power consumption was significantly reduced, avoiding unnecessary power consumption and performance degradation, and achieving refined power consumption management.
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Figure CN123035498A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of wireless communication technology, and in particular to a digital predistortion correction method, apparatus, electronic device, and storage medium. Background Technology
[0002] With the rapid development of wireless communication technology, the Wireless Fidelity (WiFi or Wi-Fi) standard has evolved to the Wi-Fi 7 era. One of its key features is support for extremely high-order modulation methods such as 4096-Quadrature Amplitude Modulation (QAM) (4K QAM). This places stringent requirements on the signal quality of the transmission link; for example, the Error Vector Magnitude (EVM) must be below -40dB. To meet these requirements, the core component in the RF front-end—the power amplifier (PA)—must operate in a high linearity region. However, traditional linear PAs typically need to operate in a power back-off region far below their saturation point to achieve the required linearity, which leads to a significant reduction in efficiency and becomes one of the main sources of system power consumption.
[0003] To overcome the aforementioned contradictions, Digital Pre-Distortion (DPD) technology is widely used to improve the linearity of Power Amplifiers (PAs). Its core idea is to pre-distort the input signal in the digital domain, making it complementary to the nonlinear characteristics of the PA. This allows the PA to operate in a more efficient region closer to its saturation point, while ensuring the output signal meets the spectral template and EVM requirements. Theoretically, this technique can effectively balance the efficiency and linearity of a PA.
[0004] However, the introduction of DPD technology itself has also brought new power consumption and cost issues. The performance of DPD is highly dependent on the complexity of its mathematical model. To achieve accurate compensation for PA nonlinear distortion, especially in demanding scenarios such as high bandwidth, high power, and high-order modulation, high-order models with a large number of tap coefficients are often required. This directly leads to a surge in the computational load of the digital signal processing (DSP) unit and a significant increase in power consumption. In terminal devices such as Wi-Fi, their maximum transmit power is strictly limited by regulations, far lower than that of cellular communication base stations. This makes the power consumption of DPD processing a particularly prominent proportion of the overall system power budget, making the power consumption issue of DPD itself undeniable.
[0005] In related technologies, DPD correction schemes often employ fixed-period scheduling (e.g., allocating fixed time slices in the digital intermediate frequency domain) and fixed model complexity. To accommodate worst-case scenarios, the system often needs to run under the highest complexity DPD model for extended periods, or undergo global simplification. For example, reducing computational load by pre-setting fixed coefficients lacks flexibility as it doesn't utilize real-time baseband information for dynamic adjustments. Conversely, reducing the computational complexity of the model itself at the algorithm level fails to meet the real-world demand for high-precision DPD models in certain scenarios, thus failing to achieve a dynamic balance between performance and power consumption reduction.
[0006] Furthermore, Wi-Fi protocols exhibit significant uplink and downlink compatibility. In actual transmission, the standard, modulation and coding scheme (MCS), bandwidth, spatial stream count, and transmit power of each Protocol Data Unit (PPDU) dynamically change, resulting in inherent differences in the intensity of DPD correction requirements for each PPDU. However, existing DPD control architectures lack effective utilization of this baseband information, leading to an inability to perform fine-grained power management at the PPDU level. This poses the risk of either "over-correction" or "under-correction." The former wastes power, while the latter may force the Medium Access Control (MAC) layer to reduce the MCS to ensure communication, sacrificing air interface traffic performance.
[0007] In summary, how to dynamically and precisely control the timing and model complexity of DPD correction based on signal characteristics while ensuring the communication performance of Wi-Fi systems in different application scenarios, thereby effectively reducing the power consumption of DPD itself, is a technical challenge that urgently needs to be solved. Summary of the Invention
[0008] The purpose of this application is to provide a digital predistortion correction method, apparatus, electronic device and storage medium, which realizes on-demand activation of DPD correction and dynamic adaptation of model complexity, and significantly reduces system power consumption while ensuring communication quality.
[0009] To address the aforementioned technical problems, embodiments of this application provide a digital predistortion correction method, comprising: continuously acquiring baseband information of Protocol Data Units (PPDUs) at each layer and forming a baseband information parameter set; determining whether to enable digital predistortion correction based on the baseband information parameter set and preset filtering conditions; when enabling digital predistortion correction, matching a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and the filtering conditions; and performing digital predistortion correction on subsequent PPDUs using the matched digital predistortion model and the baseband information parameter set.
[0010] Embodiments of this application also provide a digital predistortion correction device, comprising: an information acquisition module for continuously acquiring baseband information of protocol data units (PPDUs) at each layer and forming a baseband information parameter set; a correction judgment module for determining whether to enable digital predistortion correction based on the baseband information parameter set and preset filtering conditions; a model selection module for matching a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and the filtering conditions when it is determined that digital predistortion correction is enabled; and a correction execution module for performing digital predistortion correction on subsequent PPDUs using the matched digital predistortion model and the baseband information parameter set.
[0011] Embodiments of this application also provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the digital predistortion correction method described above.
[0012] The embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described digital predistortion correction method.
[0013] In this embodiment, baseband information of protocol data units at each layer is continuously acquired and a baseband information parameter set is formed. Based on the baseband information parameter set and preset filtering conditions, it is determined whether to enable digital predistortion correction (DPD). When DPD is enabled, a DPD model is matched from multiple DPD models of varying complexity based on the baseband information parameter set and filtering conditions. The matched DPD model and the baseband information parameter set are then used to perform DPD correction on subsequent PPDUs. This achieves a shift from on-demand activation to dynamic adaptation of DPD correction, decoupling DPD power consumption from real-time signal quality requirements at the system level. This avoids unnecessary power consumption when there is no correction requirement and prevents performance degradation due to insufficient correction, laying the foundation for refined control. Attached Figure Description
[0014] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.
[0015] Figure 1 This is a flowchart of a digital predistortion correction method according to an embodiment of this application; Figure 2 This is a schematic diagram of a model selection based on baseband information provided according to an embodiment of this application; Figure 3 This is a schematic diagram of a patent signal processing flow according to one embodiment of this application; Figure 4 This is a schematic diagram of the structure of a digital predistortion correction device according to another embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device according to another embodiment of this application. Detailed Implementation
[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been presented in the various embodiments of this application to enable readers to better understand this application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in this application can be implemented. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.
[0017] One embodiment of this application relates to a digital predistortion correction (DPD) method, which can be applied to various computing devices (such as personal computers, servers, mobile terminals, etc.). For ease of understanding, the executing entity of this application will be referred to as the controller. In this embodiment, baseband information of protocol data units at each layer is continuously acquired and a baseband information parameter set is formed. Based on the baseband information parameter set and preset filtering conditions, it is determined whether to enable digital predistortion correction. When it is determined that digital predistortion correction is enabled, a digital predistortion model is matched from multiple digital predistortion models of different complexities according to the baseband information parameter set and filtering conditions. The matched digital predistortion model and the baseband information parameter set are used to perform digital predistortion correction on subsequent PPDUs. This realizes the transformation of DPD correction from on-demand activation to dynamic adaptation, decoupling the DPD power consumption overhead from real-time signal quality requirements at the system level. This avoids invalid power consumption when there is no correction requirement and prevents performance degradation caused by insufficient correction, laying the foundation for refined control. The implementation details of the digital predistortion correction method in this embodiment are described below. The following implementation details are provided for ease of understanding and are not necessary for implementing this solution.
[0018] like Figure 1 As shown, in step 101, the controller continuously acquires the baseband information of each layer protocol data unit (PPDU) and forms a baseband information parameter set.
[0019] In Wi-Fi, data packets (PPDUs) are transmitted in units of data. The baseband module is responsible for processing baseband signals (modulation / demodulation, encoding / decoding, etc.). It knows all the parameters (including MCS) of the PPDU to be transmitted. Baseband information can include output protocol type, bandwidth, channel state information (CSI), spatial stream, MCS, power level, and other baseband information, which together form the baseband information parameter set.
[0020] In step 102, the controller determines whether to enable digital predistortion correction based on the baseband information parameter set and preset filtering conditions.
[0021] In one example, step 102 above, determining whether to enable digital predistortion correction (DPD) based on the baseband information parameter set and preset filtering conditions, can be as follows: After complex gain alignment of the baseband information of the current PPDU and the feedback data generated by the power amplifier from the previous PPDU, the error value is calculated. If the error value exceeds a first threshold, it is determined that DPD needs to be enabled; and / or, the feedback data is transformed by a Fast Fourier Transform (FFT) and then processed with a pre-stored spectral intermodulation model. If the output coefficients of the spectral intermodulation model exceed a second threshold, it is determined that DPD needs to be enabled. By introducing two independent upgrade paths—error assessment based on feedback data and baseband data, and correlation coefficient assessment of the spectral intermodulation model—objective and quantitative physical layer decision-making criteria are provided for enabling DPD. This avoids potential misjudgments that might result from blindly judging based solely on protocol parameters, ensuring that the triggering of correction actions truly reflects the current degree of nonlinear degradation of the PA, thus improving control reliability.
[0022] In step 103, when it is determined that digital predistortion correction is enabled, the controller matches a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and screening conditions.
[0023] Step 103 can be implemented in several ways, which are divided into three categories: The first category is to directly perform model matching based on the calculation results obtained from baseband information and PA feedback information; the second category is to perform model matching based on various baseband information (WIFI protocol type, BandWidth, CSI, spatial flow, MCS, power level, etc.) and corresponding screening conditions in the baseband information parameter set; and the third category is to combine the calculation results obtained from baseband information and PA feedback information with various baseband information in the baseband information parameter set to perform model matching together.
[0024] Regarding the first category, corresponding to the example in step 102, in one example, the step 103 of matching a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and screening conditions can be: when digital predistortion correction is enabled and the error value exceeds the first threshold, matching a digital predistortion model with a higher complexity than the current digital predistortion model; and / or, when digital predistortion correction is enabled and the output coefficients of the spectral intermodulation model exceed the second threshold, matching a digital predistortion model with a higher complexity than the current digital predistortion model. This provides a more accurate upgrade path for the model, avoids potential misjudgments due to blindly judging based solely on protocol parameters, and improves the reliability of control. Specifically: The error between baseband data (BBData) and feedback data (fbData) in the baseband information parameter set after complex gain alignment is determined by the magnitude of the error, i.e., fbErr = BBData_align - fbData_align (where fbData_align and BBData_align are the data after complex gain alignment). Simultaneously, the FFT-transformed feedback data (fbData_fft) is correlated with a pre-stored spectral intermodulation model (Spec_mask_model) using the formula cor_coef = corr(fbData_fft, Spec_mask_model), where corr(A, B) is the correlation coefficient between A and B. If the obtained correlation coefficient cor_coef exceeds a certain threshold, the intermodulation is rated, and the optimal DPD model is ultimately selected.
[0025] Besides the first type of method mentioned above (direct model selection based on baseband information and PA feedback information), there is a second type that can achieve the matching of a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and screening conditions in step 103. That is: In one example, step 103, matching a digital predistortion model from multiple digital predistortion models of varying complexity based on the baseband information parameter set and selection criteria, can be achieved as follows: During the transmission interval between the current PPDU and the next PPDU, the demand level is calculated using the magnitude of the demand level parameter and the corresponding weights of each demand level parameter. A digital predistortion model is then matched from multiple digital predistortion models of varying complexity based on the demand level. The demand level parameter includes one or any combination of the following: the modulation and coding scheme index value of the current PPDU, the signal bandwidth of the current PPDU, the channel state information of the current PPDU, the spatial stream number of the current PPDU, and the transmit power level. By quantifying baseband parameters such as MCS index, signal bandwidth, CSI, spatial stream number, and transmit power into demand levels, and matching models of corresponding complexity accordingly, refined model selection under multi-factor fusion decision-making is achieved. This allows model adaptation to comprehensively reflect the combined influence of multiple factors such as modulation order, spectral width, and channel conditions on PA linearity, making it more scientific and accurate than single-dimensional judgment. Specifically: The baseband can send MCS parameters to the Digital Intermediate Frequency (DIF) during PPDU intervals. The DIF then selects a DPD model based on the MCS. Wi-Fi transmits data packets (PPDUs), with a brief idle time (PPDU interval) between packets. This interval serves as a "window" for system parameter adjustments and state switching. The DIF (Digital Intermediate Frequency) is responsible for calculating and updating DPD coefficients and performing predistortion processing within the DPD architecture. It is the hardware unit that executes the DPD algorithm. Sending MCS parameters indicates that the baseband uses this PPDU interval to inform the DIF of the current PPDU's MCS value (e.g., MCS0, MCS13), letting the DIF know what level of signal to process next. After receiving the MCS parameters, the DIF selects one from several DPD models of varying complexity to adapt to the current PPDU, according to preset rules. In this example, the principle of adaptation is that different MCS have different requirements for signal quality. The higher the MCS (the higher the modulation order), the more stringent the requirements for PA linearity, and the more complex the DPD model is needed to compensate for distortion. The lower the MCS, the lower the requirements, and a simple model or even no DPD can be used.
[0026] In one example, the complexity of the aforementioned digital predistortion model is positively correlated with the number of effective tap coefficients used in the model. Effective tap coefficients are generated by sequentially masking tap coefficients from both ends of the tap delay chain towards the middle; the more tap coefficients masked, the fewer effective tap coefficients there are. This example simplifies the model by defining the positive correlation between model complexity and the number of effective taps and explicitly using a method of masking from both ends of the tap delay chain towards the middle. It provides a model implementation scheme with smoothly simplifiable computational load reduction, allowing for model complexity switching without refactoring the algorithm architecture, achieved solely through coefficient masking, significantly reducing switching overhead and implementation difficulty. For example: MCS13 uses the full 11th-order DPD tap coefficients (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10); MCS0 uses only third-order coefficients (4, 5, 6) by shielding the taps on both sides of the spectrum. In this example, MCS13 corresponds to 4096-QAM (4K QAM) modulation, which is the highest-order modulation in Wi-Fi 7, requiring extremely high EVM (Error Vector Magnitude) (≤ -40dB) and the most stringent PA linearity. Here, "tap coefficients" refers to the multiplication coefficients corresponding to different delay paths in the DPD digital filter. The numbers in parentheses (0, 1, 2, ..., 10) are the position numbers of these coefficients in the tap delay chain, not the "nonlinear order." "11th order" means there are 11 taps (positions 0 to 10), implying that the DPD model considers 11 signal paths with different delay times for nonlinear compensation. "Complete" means all 11 taps are enabled. This model is the most complex, computationally intensive, and consumes the most power, but offers the highest compensation accuracy, sufficient to meet the stringent requirements of MCS13. MCS0: This is the most basic modulation scheme in Wi-Fi, with extremely low requirements for signal quality. Even some nonlinear distortion in the PA will not affect demodulation. Spectrum masking of the two taps: From the complete 11 taps, the taps at positions 0-3 and 7-10 are turned off (masked) and do not participate in the calculation. Using only third-order coefficients (4, 5, 6) means retaining only the three taps in the middle (positions 4, 5, 6). In other words, reducing from 11 taps to 3 taps significantly reduces model complexity, with computational load reduced to about 1 / 3, and power consumption correspondingly decreased. Since MCS0 has very low linearity requirements, the compensation accuracy provided by these 3 taps is sufficient to meet the spectrum template requirements.
[0027] In one example, as a precaution, if the coefficients fail to be updated in time due to hardware scheduling delays during the PPDU interval, the current PPDU will use the DPD coefficients of the previous PPDU to avoid correction interruption.
[0028] In one example, when the current protocol is Direct Sequence Spread Spectrum (DSSS), and the current PPDU's transmit signal meets the spectrum template requirements and digital predistortion correction (DPD) is enabled, DPD is directly disabled. For this specific DSSS scenario, by directly disabling DPD while meeting the spectrum template requirements, the inherent limitations of the protocol are utilized to achieve extreme energy saving with "zero overhead" in extremely low-power-sensitive scenarios, further exploring the potential for power optimization. Specifically: when the baseband DSSS protocol meets the spectrum template requirements, a command to disable DPD is issued during PPDU intervals to reduce power consumption.
[0029] Under the same conditions, besides the MCS (i.e., the index value of the current PPDU modulation and coding strategy is positively correlated with the complexity of the digital predistortion model) mentioned above, many other parameters will have different correlations with the complexity of the model, such as: wider signal bandwidth, channel state information, spatial stream number, transmit power level, etc. These situations will be explained separately below: In one example, the signal bandwidth of the current PPDU is positively correlated with the complexity of the digital predistortion (DPD) model; that is, under the same conditions, the wider the signal bandwidth, the higher the complexity requirement of the DPD model and the greater the power consumption. Therefore, a complex model can be used for DPD correction and iteration of PPDUs with large bandwidth, while a simple model can be used for DPD iteration of PPDUs with small bandwidth to reduce power consumption. Specifically, the baseband sends the occupied bandwidth of the current PPDU to the DIF during the PPDU interval, and the DIF switches the DPD coefficients according to the bandwidth. For example, a full 11th-order DPD tap coefficient (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) is used under a 160MHz bandwidth; under a 20MHz bandwidth, the taps on both sides are shielded by spectrum, and only the third-order coefficients (4, 5, 6) are used.
[0030] In one example, the difference between the current PPDU's channel state information and the preset channel state threshold is positively correlated with the complexity of the digital predistortion model. That is, PPDUs with good spatial channel conditions have higher DPD correction requirements and choose a complex DPD model, while PPDUs with poor channel conditions have lower DPD correction requirements and choose a simpler DPD model. Specifically, the baseband performs PPDU-level DPD correction control based on CSI (Channel State Information) to achieve optimal energy consumption.
[0031] In one example, the spatial stream count of the current PPDU is positively correlated with the complexity of the digital predistortion model. This means that multi-stream PPDUs have higher DPD correction requirements and therefore choose a complex DPD model, while single-stream PPDUs have lower DPD correction requirements and therefore choose a simpler DPD model. Specifically, the baseband performs PPDU-level DPD correction control based on the stream count to achieve optimal energy consumption.
[0032] In one example, the transmit power level is positively correlated with the complexity of the digital predistortion model. Specifically: low-power PPDUs operate in the PA linear region and do not require DPD correction. The baseband parameter set DPD correction judgment module issues a command to disable DPD correction for this PPDU to save power.
[0033] Regarding the third type, in one example, baseband data and PA port feedback data can also be combined with the aforementioned baseband parameter-level information (CSI, BW, MCS, etc.) to ultimately work together to select the optimal DPD model. For ease of understanding, the following example illustrates a complete and concrete implementable device for executing the method described in this application, with the specific process as follows: Figure 2 As shown, since this example is one specific implementation of the above method, the relevant technical details mentioned in the above method are still valid in this example and presented in a more specific way, but this does not mean that this is the only way of presentation. To reduce repetition, they will not be repeated here. Specifically: Baseband information such as WIFI protocol type, Bandwidth, CSI, spatial stream, MCS, and power level are input as elements of the baseband parameter set to the baseband parameter set DPD correction judgment module. BBdata and fbData data are input to the air interface spectrum intermodulation judgment module. The air interface intermodulation judgment module evaluates the intermodulation baseband data and the feedback data from the PA port. The air interface spectrum intermodulation judgment module determines the intermodulation based on the error between the baseband data BBData and the feedback data fbData after complex gain alignment, i.e., fbErr = BBData_align - fbData_align (where fbData_align and BBData_align are the data after complex gain alignment). Simultaneously, the feedback data (fbData_fft) after FFT transformation is correlated with the pre-stored spectrum intermodulation model Spec_mask_model using the operation cor_coef = corr(fbData_fft, Spec_mask_model), where corr(A, B) is the correlation coefficient between A and B. If the obtained correlation coefficient cor_coef exceeds a certain threshold, the intermodulation is rated. The rating result of the air interface intermodulation judgment module will be input into the baseband parameter set DPD correction judgment module. This module, combined with other baseband parameter level information (CSI, BW, MCS, etc.), will ultimately select the optimal DPD model. The other baseband parameter level information is used to calculate the demand level through their respective weights. The demand level and the rating result of the air interface intermodulation judgment module also have their respective weights. The optimal DPD model is calculated through a preset formula, and finally, a DPD PPDU level trigger signal is output to indicate digital predistortion correction for subsequent PPDUs.
[0034] In step 104, the controller performs digital predistortion correction on subsequent PPDUs using the matched digital predistortion model and baseband information parameter set.
[0035] Signal processing flow as follows Figure 3As shown, the baseband power level, BBData, CSI, current count, protocol type, MCS, and BW are input to the DPD model selection module. Combined with fbData, the selected model outputs a PPDU-level DPD model. The baseband, PPDU-level DPD model, and fbData are input to the model parameter calculation module. The controller in step 104 performs digital predistortion correction on subsequent PPDUs using the matched digital predistortion model and baseband information parameter set, outputting PD coefficients. The baseband and PD coefficients are input to the PD and output normally to the PA, thus outputting the final result.
[0036] In this implementation, baseband information of protocol data units at each layer is continuously acquired and a baseband information parameter set is formed. Based on the baseband information parameter set and preset filtering conditions, it is determined whether to enable digital predistortion correction (DPD). When DPD is enabled, a DPD model is matched from multiple DPD models of varying complexity based on the baseband information parameter set and filtering conditions. The matched DPD model and the baseband information parameter set are then used to perform DPD correction on subsequent PPDUs. This achieves a shift from on-demand activation to dynamic adaptation of DPD correction, decoupling DPD power consumption from real-time signal quality requirements at the system level. This avoids unnecessary power consumption when there is no correction requirement and prevents performance degradation due to insufficient correction, laying the foundation for refined control.
[0037] The steps described above are for clarity only. In practice, they can be combined into one step or some steps can be split into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this application. Adding insignificant modifications or introducing insignificant designs to the algorithm or process, but without changing the core design of the algorithm and process, are also within the scope of protection of this application.
[0038] Another embodiment of this application relates to a digital predistortion correction device, such as... Figure 4 As shown, it includes: an information acquisition module 401, used to continuously acquire baseband information of each layer protocol data unit (PPDU) and form a baseband information parameter set; a correction judgment module 402, used to determine whether to enable digital predistortion correction based on the baseband information parameter set and preset filtering conditions; a model selection module 403, used to match a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and the filtering conditions when it is determined that the digital predistortion correction is enabled; and a correction execution module 404, used to perform digital predistortion correction on subsequent PPDUs using the matched digital predistortion model and the baseband information parameter set.
[0039] In one example, based on the baseband information parameter set and preset filtering conditions, it is determined whether to enable digital predistortion correction, including: performing complex gain alignment on the baseband information of the current PPDU and the feedback data generated by the power amplifier of the previous PPDU, and calculating the error value; when the error value exceeds the first threshold, it is determined that digital predistortion correction needs to be enabled; and / or, performing FFT transformation on the feedback data and operation with the input pre-stored spectrum intermodulation model; when the output coefficient of the spectrum intermodulation model exceeds the second threshold, it is determined that digital predistortion correction needs to be enabled.
[0040] In one example, a digital predistortion model is matched from multiple digital predistortion models of different complexities based on the baseband information parameter set and screening conditions. This includes: when digital predistortion correction is enabled and the error value exceeds a first threshold, matching a digital predistortion model with a higher complexity than the current digital predistortion model; and / or, when digital predistortion correction is enabled and the output coefficients of the spectral intermodulation model exceed a second threshold, matching a digital predistortion model with a higher complexity than the current digital predistortion model.
[0041] In one example, the complexity of a digital predistortion model is positively correlated with the number of effective tap coefficients used in the digital predistortion model; effective tap coefficients are generated by sequentially masking tap coefficients from both ends of the tap delay chain of the digital predistortion model toward the middle, and the more tap coefficients are masked, the fewer effective tap coefficients there are.
[0042] In one example, a digital predistortion model is matched from multiple digital predistortion models of different complexities based on the baseband information parameter set and filtering conditions. This includes: during the transmission interval between the current PPDU and the next PPDU, calculating the demand level by the magnitude of the demand level parameter and the weights corresponding to each demand level parameter, and matching a digital predistortion model from multiple digital predistortion models of different complexities based on the demand level; wherein, the demand level parameter includes one of the following or any combination thereof: the modulation and coding strategy index value of the current PPDU, the signal bandwidth of the current PPDU, the channel state information of the current PPDU, the spatial stream number of the current PPDU, and the transmit power level.
[0043] In one example, the magnitude of the modulation and coding strategy index value of the current PPDU is positively correlated with the complexity of the digital predistortion model; the signal bandwidth of the current PPDU is positively correlated with the complexity of the digital predistortion model; the difference between the channel state information of the current PPDU and the preset channel state threshold is positively correlated with the complexity of the digital predistortion model; the spatial stream number of the current PPDU is positively correlated with the complexity of the digital predistortion model; and the transmit power level is positively correlated with the complexity of the digital predistortion model.
[0044] In one example, when the current protocol is DSSS, the current PPDU's transmitted signal meets the spectrum template requirements, and digital predistortion correction is enabled, digital predistortion correction is directly disabled.
[0045] In this implementation, baseband information of protocol data units at each layer is continuously acquired and a baseband information parameter set is formed. Based on the baseband information parameter set and preset filtering conditions, it is determined whether to enable digital predistortion correction (DPD). When DPD is enabled, a DPD model is matched from multiple DPD models of varying complexity based on the baseband information parameter set and filtering conditions. The matched DPD model and the baseband information parameter set are then used to perform DPD correction on subsequent PPDUs. This achieves a shift from on-demand activation to dynamic adaptation of DPD correction, decoupling DPD power consumption from real-time signal quality requirements at the system level. This avoids unnecessary power consumption when there is no correction requirement and prevents performance degradation due to insufficient correction, laying the foundation for refined control.
[0046] It is not difficult to see that this embodiment is a device embodiment corresponding to the above method embodiment, and this embodiment can be implemented in conjunction with the above method embodiment. The relevant technical details mentioned in the above method embodiment are still valid in this embodiment, and will not be repeated here to reduce repetition. Accordingly, the relevant technical details mentioned in this embodiment can also be applied to the above method embodiment.
[0047] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problem proposed in this application; however, this does not mean that other units are absent from this embodiment.
[0048] Another embodiment of this application relates to an electronic device, such as... Figure 5 As shown, it includes at least one processor 501; and a memory 502 communicatively connected to the at least one processor; wherein the memory 502 stores instructions executable by the at least one processor 501, the instructions being executed by the at least one processor 501 to enable the at least one processor 501 to perform the digital predistortion correction method as described above.
[0049] The memory 502 and processor 501 are connected via a bus, which can include any number of interconnecting buses and bridges. The bus connects various circuits of one or more processors 501 and memory 502 together. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by processor 501 is transmitted over a wireless medium via an antenna, which further receives data and transmits it to processor 501.
[0050] Processor 501 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory 502 can be used to store data used by processor 501 during operation.
[0051] Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the method embodiments described above.
[0052] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
[0053] Those skilled in the art will understand that the above embodiments are specific implementations of this application, and in practical applications, various changes can be made in form and detail without departing from the spirit and scope of this application.
Claims
1. A digital predistortion correction method, characterized in that, include: Continuously acquire baseband information of each layer protocol data unit (PPDU) and assemble it into a baseband information parameter set; Based on the baseband information parameter set and preset filtering conditions, determine whether to enable digital predistortion correction; When it is determined that the digital predistortion correction is enabled, a digital predistortion model is matched from multiple digital predistortion models of different complexities according to the baseband information parameter set and the filtering conditions; The digital predistortion correction is performed on subsequent PPDUs using the matched digital predistortion model and the baseband information parameter set.
2. The digital predistortion correction method according to claim 1, characterized in that, The step of determining whether to enable digital predistortion correction based on the baseband information parameter set and preset filtering conditions includes: The baseband information of the current PPDU and the feedback data generated by the power amplifier of the previous PPDU are subjected to complex gain alignment and the error value is calculated. When the error value exceeds the first threshold, it is determined that digital predistortion correction needs to be enabled. And / or, The feedback data is transformed by a fast Fourier transform and then processed with the input pre-stored spectral intermodulation model. When the output coefficients of the spectral intermodulation model exceed the second threshold, it is determined that digital predistortion correction needs to be enabled.
3. The digital predistortion correction method according to claim 2, characterized in that, The step of matching a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and the filtering conditions includes: When the digital predistortion correction is enabled and the error value exceeds the first threshold, a digital predistortion model with a higher complexity than the current digital predistortion model is matched. And / or, When the digital predistortion correction is enabled and the output coefficients of the spectral intermodulation model exceed the second threshold, a digital predistortion model with a higher complexity than the current digital predistortion model is matched.
4. The digital predistortion correction method according to claim 1, characterized in that, The complexity of the digital predistortion model is positively correlated with the number of effective tap coefficients used in the digital predistortion model; The effective tap coefficients are generated by sequentially masking the tap coefficients from both ends of the tap delay chain of the digital predistortion model toward the middle. The more tap coefficients that are masked, the fewer the effective tap coefficients.
5. The digital predistortion correction method according to claim 1, characterized in that, The step of matching a digital predistortion model from multiple digital predistortion models of different complexities based on the baseband information parameter set and the filtering conditions includes: During the transmission interval between the current PPDU and the next PPDU, the demand level is calculated by the magnitude of the demand level parameter and the weight corresponding to each demand level parameter. Based on the demand level, a digital predistortion model is matched from multiple digital predistortion models of different complexities. The demand level parameters include one or any combination of the following: The current PPDU's modulation and coding strategy index value, the current PPDU's signal bandwidth, the current PPDU's channel state information, the current PPDU's spatial stream number, and the transmit power level.
6. The digital predistortion correction method according to claim 5, characterized in that, The magnitude of the modulation and coding strategy index value of the current PPDU is positively correlated with the complexity of the digital predistortion model; The signal bandwidth of the current PPDU is positively correlated with the complexity of the digital predistortion model; The difference between the current PPDU channel state information and the preset channel state threshold is positively correlated with the complexity of the digital predistortion model. The spatial stream number of the current PPDU is positively correlated with the complexity of the digital predistortion model; The transmit power level is positively correlated with the complexity of the digital predistortion model.
7. The digital predistortion correction method according to claim 1, characterized in that, The method further includes: If the current protocol is DSSS, the current PPDU's transmitted signal meets the spectrum template requirements, and the digital predistortion correction is already enabled, then the digital predistortion correction is directly disabled.
8. A digital predistortion correction device, characterized in that, include: The information acquisition module is used to continuously acquire baseband information of each layer protocol data unit (PPDU) and form a baseband information parameter set. The correction judgment module is used to determine whether to enable digital predistortion correction based on the baseband information parameter set and preset filtering conditions. The model selection module is used to match a digital predistortion model from multiple digital predistortion models of different complexities according to the baseband information parameter set and the filtering conditions when it is determined that the digital predistortion correction is enabled. The correction execution module is used to perform digital predistortion correction on subsequent PPDUs using the matched digital predistortion model and the baseband information parameter set.
9. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the digital predistortion correction method as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the digital predistortion correction method according to any one of claims 1 to 7.