DEM conversion method for multi-bit quantizer Sigma-Delta modulation system

Abstract

The invention provides a DEM (Digital Elevation Model) conversion method for a multi-bit quantizer Sigma-Delta modulation system, which relates to the technical field of signal processing, and comprises the following steps: signal preprocessing: receiving a digital output signal from a quantizer through an input signal processing module, carrying out input signal judgment, judging whether the signal is exponential power of 2 or not, and if yes, judging whether the signal is exponential power of 2 or not; if the exponential power is 2, entering a tree structure equivalent series circuit and adding randomized disturbance, and if the exponential power is not 2, entering a random disturbance circuit and adding randomized disturbance; and temporary storage and output: temporarily storing the intermediate state data through a data temporary storage module, converting the thermometer code into an analog signal based on a feedback DAC, and feeding back the analog signal to an integrator of the Sigma-Delta modulator. When the signal is the exponential power of 2, the tree structure equivalent series circuit organizes the selection structure of the DAC unit into a tree shape, the selection logic operation is completed in a short time, and when the signal is not the exponential power of 2, randomized disturbance is added through the random disturbance circuit, and the signal is converted into a thermometer code.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and more specifically, to a DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system. Background Art

[0002] The Sigma-Delta (Σ-Δ) modulator is a widely used architecture in high-precision analog-to-digital conversion (ADC) applications, offering advantages such as a high signal-to-noise ratio (SNR) and high dynamic range (DR). Compared to single-bit quantizers, multi-bit quantizers can reduce quantization noise and improve the modulator's effective number of bits (ENOB). However, the use of multi-bit quantizers introduces non-ideal errors in the feedback digital-to-analog converter (DAC), which becomes a key bottleneck affecting modulator performance.

[0003] In a multi-bit Σ-Δ modulator, a feedback DAC converts the quantizer output into an analog signal for the integrator calculation in the next clock cycle. However, due to mismatches in component parameters (such as current sources, capacitor values, and resistor values) during the manufacturing process, different DAC components cannot achieve ideal linear conversion, resulting in nonlinear distortion and reduced dynamic range. These mismatch errors are particularly noticeable in high-precision applications such as audio signal processing, wireless communications, and high-resolution sensors.

[0004] In order to solve the error problem of feedback DAC, the following main methods are used in the existing technology: Calibration: Errors are measured and calibration parameters are stored before the chip leaves the factory to compensate for them. However, this method is affected by environmental factors such as temperature and aging, making it difficult to maintain long-term stability.

[0005] Randomization technology: Randomly selecting DAC elements to balance errors. Although it can reduce the linearity problems caused by mismatch to a certain extent, it cannot effectively optimize the errors of large-scale DAC arrays.

[0006] Dynamic Element Matching (DEM): Dynamically selecting DAC components evenly distributes errors across the entire spectrum, reducing system nonlinear distortion. Data Weighted Averaging (DWA) is the most commonly used DEM technique. However, DWA only achieves first-order mismatch noise shaping. The linear sequence selection mechanism significantly decreases in efficiency as the number of bits increases, and the algorithm also performs thermometer code conversion during randomization. Summary of the Invention

[0007] To solve the above problems, the technical solution adopted in this application is a DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system, comprising: Signal preprocessing: The digital output signal from the quantizer is received through the input signal processing module, and the input signal is judged to determine whether the signal is an exponential power of 2. If it is an exponential power of 2, it enters the tree structure equivalent series circuit and adds random perturbation. If it is not an exponential power of 2, it directly enters the random perturbation circuit to add random perturbation. Temporary storage and output: The intermediate state data is temporarily stored through the data temporary storage module, and the thermometer code is converted into an analog signal based on the feedback DAC and fed back to the integrator of the Sigma-Delta modulator.

[0008] Optionally, the random perturbation circuit performs the following operations: the input signal is added with a k+1 gain by the multiplier and then enters the upper and lower signals for calculation respectively; the upper signal is added with a random signal by an adder, and then the thermometer code is output after the k gain is added by the divider and the multiplier; the lower signal is subtracted from the random signal by a subtractor, and then the thermometer code is output after the k gain is added by the divider and the multiplier. The value of the k gain is determined based on environmental parameter compensation and noise compensation.

[0009] Optionally, the tree-structured equivalent series circuit performs the following operations: the input signal first enters the first perturbation module, adds a random signal +1 or -1, and then enters the multi-level element selection logic module, outputs a selection signal with a bit width of [0,1], and the selection signal is sent to the second perturbation module, and the output signal is obtained after adding a value with an opposite sign to that of the first perturbation module.

[0010] Optionally, environmental parameter compensation is performed based on the following formula: ; Where, Indicates environmental parameter compensation, represents the temperature compensation coefficient, Indicates the operating temperature, represents the ambient temperature, β represents the voltage compensation coefficient, Indicates the actual working voltage, Indicates the designed operating voltage.

[0011] Optionally, noise compensation is performed based on the following formula: ; Where, represents noise compensation, γ represents the noise suppression coefficient, represents the noise power, Indicates the signal power.

[0012] Optionally, the value of k gain is obtained based on the following formula: ; Where k represents the signal gain, N represents the noise compensation weight, and M represents the environmental parameter compensation weight.

[0013] Optionally, the temperature compensation coefficient and the voltage compensation coefficient are calculated as follows: S1: Set experimental conditions that cover the system operating temperature and power supply voltage fluctuation range; S2: Measure the actual system gain at each temperature-voltage combination and calculate the gain deviation; S3: Construct a matrix equation for gain deviation, temperature deviation, and voltage deviation, and solve the temperature compensation coefficient and voltage compensation coefficient by minimizing the sum of squares of the residuals.

[0014] Optionally, the gain is limited to ∈[0.8, 1.2].

[0015] Optionally, the noise compensation weight and the environmental parameter compensation weight are determined based on the following formula:

[0016] Where N represents the noise compensation weight, and M represents the environmental parameter compensation weight.

[0017] Optionally, the input signal discrimination includes: receiving and latching the input binary number x, calculating x-1, performing bitwise AND gate calculation, judging whether the bitwise AND result is all 0 through zero detection, judging whether the input x is non-zero through non-zero detection, combining the results of zero detection and non-zero detection, and outputting the final signal.

[0018] The beneficial effects of the DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system provided in this application are: (1) When the signal is an exponential power of 2, the tree-structured equivalent series circuit can complete the selection logic operation in a shorter time by organizing the selection structure of the DAC unit into a tree shape. It is suitable for high-speed operation and is particularly suitable for high-bandwidth, high-speed Sigma-Delta modulators. For DWA, only first-order mismatch noise shaping can be achieved. The tree-structured equivalent series circuit can be extended to a higher order, more effectively suppressing mismatch noise in the low-frequency region, and improving the overall linearity and effective resolution of the modulator; structurally, it is easier to expand to a multi-bit DAC system, and still maintains a low control logic complexity under a high-bit quantizer. In contrast, the linear sequence selection mechanism of DWA decreases significantly in efficiency when the number of bits increases; DWA requires a logic circuit to convert the binary digital output into a thermometer code, and the algorithm provided in this application also completes the conversion of the thermometer code during the randomization process.

[0019] (2) When the signal is not an exponential power of 2, a random perturbation circuit is used to add random perturbations and convert them into thermometer codes. However, this random perturbation adding method cannot achieve random processing when the input is an exponential power of 2, and it is easy to introduce noise artifacts, affecting the system's spurious-free dynamic range and linearity. Based on the input signal discrimination compensation, a signal processing method is selected to make up for the shortcomings of this algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art.

[0021] Figure 1 This is a structural diagram of a tree-structured equivalent series circuit algorithm provided in an embodiment of the present application; Figure 2 This is a structural diagram of the random perturbation circuit algorithm provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the technical problems, technical solutions and beneficial effects to be solved by this application more clearly understood, this application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0023] Example 1 like Figure 1-Figure 2 As shown, a DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system includes: Signal preprocessing: The digital output signal from the quantizer is received through the input signal processing module, and the input signal is judged to determine whether the signal is an exponential power of 2.

[0024] The input signal processing module includes an input register, a subtractor, a bitwise AND gate array, a zero detector, a non-zero detector, and a combinational logic gate.

[0025] The input signal discrimination process is as follows: Use D flip-flops or latches to form a register array, each bit corresponds to the input binary bit, receive and latch the input binary number x, calculate x-1 through the subtractor, and perform bit-by-bit AND gate calculation through the bit-by-bit AND gate array.

[0026] Zero detection: If all AND gate outputs are 0, the zero detector outputs 1, indicating that the signal is an exponential power of 2; Non-zero detection: If any bit is 1, the non-zero detector outputs 1, indicating that the signal is not 0; Perform an AND operation on the zero test result and the non-zero test result. If the result is 1, it means that the input is an exponential power of 2. If the result is 0, it means that the input is not an exponential power of 2.

[0027] If it is an exponential power of 2, it enters the tree structure equivalent series circuit and adds random perturbations. If it is not an exponential power of 2, it directly enters the random perturbation circuit and adds random perturbations. Temporary storage and output: The intermediate state data is temporarily stored through the data temporary storage module, and the thermometer code is converted into an analog signal based on the feedback DAC and fed back to the integrator of the Sigma-Delta modulator.

[0028] When the signal is an exponential power of 2, the tree-structured equivalent series circuit can complete the selection logic operation in a shorter time by organizing the selection structure of the DAC unit into a tree shape. It is suitable for high-speed operation and is particularly suitable for high-bandwidth, high-speed Sigma-Delta modulators. For DWA, only first-order mismatch noise shaping can be achieved. The tree-structured equivalent series circuit can be expanded to higher orders, more effectively suppressing mismatch noise in the low-frequency region, and improving the overall linearity and effective resolution of the modulator; structurally, it is easier to expand to multi-bit DAC systems, and still maintains low control logic complexity under high-bit quantizers. In contrast, the linear sequence selection mechanism of DWA decreases significantly in efficiency when the number of bits increases; DWA requires a logic circuit to convert the binary digital output into a thermometer code, and the algorithm provided in this application also completes the conversion of the thermometer code during the randomization process.

[0029] When the signal is not an exponential power of 2, a random perturbation circuit is used to add random perturbations and convert them into thermometer codes. However, this random perturbation addition method cannot achieve randomization when the input is an exponential power of 2, and it is easy to introduce noise artifacts, affecting the system's spurious-free dynamic range and linearity. Based on the input signal discrimination compensation, a signal processing method is selected to make up for the shortcomings of the algorithm.

[0030] like Figure 2 As shown, the random perturbation circuit performs the following operations: the input signal is added with a k+1 gain by the multiplier and then enters the upper and lower signals for calculation respectively. The upper signal is added with a random signal by the adder, and then the thermometer code is output after the k gain is added by the divider and the multiplier. The random signal is subtracted from the lower signal by the subtractor, and then the thermometer code is output after the k gain is added by the divider and the multiplier. The value of the k gain is determined based on the environmental parameter compensation and the noise compensation.

[0031] Environmental parameter compensation is based on the following formula: ; Where, Indicates environmental parameter compensation, represents the temperature compensation coefficient, Indicates the operating temperature, represents the ambient temperature, β represents the voltage compensation coefficient, Indicates the actual working voltage, Indicates the designed operating voltage.

[0032] The calculation process of temperature compensation coefficient and voltage compensation coefficient is: S1: Set experimental conditions that cover the system operating temperature and power supply voltage fluctuation range; S2: Measure the actual system gain at each temperature-voltage combination and calculate the gain deviation; S3: Construct a matrix equation for gain deviation, temperature deviation, and voltage deviation, and solve the temperature compensation coefficient and voltage compensation coefficient by minimizing the sum of squares of the residuals.

[0033] The temperature range covers the system operating temperature, with multiple temperature points set at ΔT intervals. The voltage range covers the power supply voltage fluctuation range, with multiple voltage points set at ΔV intervals. The input signal is kept fixed, and only the temperature and voltage are changed.

[0034] The actual gain of the system can be measured using the time domain measurement method, which is calculated based on the ratio of the peak-to-peak value of the output signal to the peak-to-peak value of the input signal.

[0035] The system gain deviation is: ; Where, represents the system gain deviation, is the actual gain of the system, is the nominal gain of the system.

[0036] Construct the relationship between gain deviation and environmental parameters: ; The N sets of data obtained from the experiment are used to construct a matrix, and the optimal solution is obtained using the least squares method by minimizing the residual sum of squares.

[0037] Examples include: The ambient temperature is 25°C, the designed operating voltage is 3.3V, and the experimental data are shown in Table 1.

[0038] Table 1 Experimental data table

[0039] The calculated deviations are: T1=0℃, V1=0V, k1=0; T2 = 10℃, V2=0V, k2=-0.02; T3=0℃, V3=-0.3V, k3=0.05; T4=20℃, V4=0.3V, k4=-0.03; ; ; 0; -0.133.

[0040] Where, T1 represents the temperature difference between the working temperature and the ambient temperature in the first set of experiments, V1 represents the difference between the actual working voltage and the designed working voltage in the first set of experiments. k1 represents the gain deviation in the first set of experiments, and the subscripts thereafter are similar.

[0041] Noise compensation is based on the following formula: ; Where, represents noise compensation, γ represents the noise suppression coefficient, represents the noise power, Indicates the signal power.

[0042] The value of k gain is obtained based on the following formula: ; Where k represents the signal gain, N represents the noise compensation weight, and M represents the environmental parameter compensation weight.

[0043] The gain is limited to ∈[0.8, 1.2]. By controlling the gain value, we can prevent the noise shaping capability from being reduced due to a too low gain, which will cause residual low-frequency noise. At the same time, we can prevent the nonlinear distortion caused by excessive gain. When the value of k exceeds the limit, we take the endpoint value, which is 0.8 below the limit and 1.2 above the limit.

[0044] The noise compensation weight and environmental parameter compensation weight are determined based on the following formula:

[0045] Environmental parameters have clear limit standards. For example, the temperature limit is -40°C to 80°C, and the power supply voltage fluctuation range is ±10% of the nominal voltage. If the above limits are exceeded, the environmental parameters are considered to have exceeded the limit. The noise power exceeding the limit can be determined in the following ways: 1. The noise power is significantly higher than the signal power. For example, if the noise power accounts for more than 10%, it is considered that the noise power exceeds the limit. 2. The signal-to-noise ratio drops below the threshold; 3. Spectrum analysis detected a sudden increase in noise power in the high-frequency region.

[0046] The above identification methods are selected or used simultaneously according to actual conditions.

[0047] like Figure 1-Figure 2 As shown in the figure, the tree-structured equivalent series circuit performs the following operations: the input signal first enters the first perturbation module, adds a random signal +1 or -1, and then enters the multi-level element selection logic module, outputting a selection signal with a bit width of [0,1]. The selection signal is sent to the second perturbation module, and the output signal is obtained by adding a value with an opposite sign to that of the first perturbation module. The circuit structure of the first perturbation module and the second perturbation module is the same as that of the random perturbation circuit.

[0048] The present invention can be widely used in the field of high-precision analog-to-digital conversion, and is particularly suitable for the following application scenarios: High-precision audio signal processing including Hi-Fi audio, professional recording equipment, wireless communication base stations; biomedical sensors; precision measuring instruments; industrial control and automation equipment.

[0049] Weak physiological signals are easily affected by environmental noise. Noise compensation can improve the signal-to-noise ratio and ensure the effective extraction of weak signals. Industrial environmental temperature has a significant impact, and environmental parameter compensation can effectively eliminate nonlinear errors caused by environmental interference.

[0050] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system, characterized in that: include: Signal preprocessing: The digital output signal from the quantizer is received through the input signal processing module, and the input signal is judged to determine whether the signal is an exponential power of 2. If it is an exponential power of 2, it enters the tree structure equivalent series circuit and adds random perturbation. If it is not an exponential power of 2, it directly enters the random perturbation circuit to add random perturbation. Temporary storage and output: The intermediate state data is temporarily stored through the data temporary storage module, and the thermometer code is converted into an analog signal based on the feedback DAC and fed back to the integrator of the Sigma-Delta modulator.

2. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 1, wherein: The random perturbation circuit performs the following operations: the input signal is added with a k+1 gain by a multiplier and then enters the upper and lower signals for calculation respectively; the upper signal is added with a random signal by an adder, and then a thermometer code is output after the k gain is added by a divider and a multiplier; the lower signal is subtracted from the random signal by a subtractor, and then a thermometer code is output after the k gain is added by a divider and a multiplier. The value of the k gain is determined based on environmental parameter compensation and noise compensation.

3. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 1, wherein: The tree-structured equivalent series circuit performs the following operations: the input signal first enters the first perturbation module, adds a random signal +1 or -1, and then enters the multi-level element selection logic module, outputting a selection signal with a bit width of [0, 1]. The selection signal is sent to the second perturbation module, and the output signal is obtained by adding a value with an opposite sign to that of the first perturbation module.

4. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 2, wherein: The environmental parameter compensation is performed based on the following formula: ； Where, Indicates environmental parameter compensation, represents the temperature compensation coefficient, Indicates the operating temperature, represents the ambient temperature, β represents the voltage compensation coefficient, Indicates the actual working voltage, Indicates the designed operating voltage.

5. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 2, wherein: The noise compensation is performed based on the following formula: ； Where, represents noise compensation, γ represents the noise suppression coefficient, represents the noise power, Indicates the signal power.

6. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 2, wherein: The value of the k gain is obtained based on the following formula: ； Where k represents the signal gain, N represents the noise compensation weight, and M represents the environmental parameter compensation weight.

7. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 4, characterized in that: The calculation process of the temperature compensation coefficient and the voltage compensation coefficient is: S1: Set experimental conditions that cover the system operating temperature and power supply voltage fluctuation range; S2: Measure the actual system gain at each temperature-voltage combination and calculate the gain deviation; S3: Construct a matrix equation for gain deviation, temperature deviation, and voltage deviation, and solve the temperature compensation coefficient and voltage compensation coefficient by minimizing the sum of squares of the residuals.

8. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 2, wherein: The gain is limited to ∈[0.8, 1.2].

9. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 6, wherein: The noise compensation weight and the environmental parameter compensation weight are determined based on the following formula: Where N represents the noise compensation weight, and M represents the environmental parameter compensation weight.

10. The DEM conversion method for a multi-bit quantizer Sigma-Delta modulation system according to claim 1, wherein: The input signal discrimination includes: receiving and latching an input binary number x, calculating x-1, performing bitwise AND gate calculation, judging whether the bitwise AND result is all 0s through zero detection, judging whether the input x is non-zero through non-zero detection, combining the results of zero detection and non-zero detection, and outputting a final signal.

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