Gain control method, chip system and medium

Abstract

The present disclosure provides a gain control method, a chip system and a medium. The method comprises: detecting a received signal to obtain a detection intensity of the received signal; estimating a saturated signal in the received signal and obtaining a saturation loss caused by the saturated signal; and obtaining a gain adjustment value based on the detection intensity and the saturation loss, wherein the saturation loss is used to adjust a reference intensity of the received signal.

Description

Technical Field

[0001] This disclosure relates to the field of communications, and more specifically, to a gain control method, a chip system, and a medium. Background Technology

[0002] Automatic gain control (AGC) technology is a crucial element in ensuring stable signal quality for mobile cellular networks (such as 4G, 5G, or 6G) and broadband wireless communications (such as WiFi). With the evolution of 5G-A (5G-Advanced) and future 6G networks, the continuous expansion of signal bandwidth, the increasing complexity of interference environments, and the application of peak-to-average power ratio (PAPR) signals (such as OFDM) have all raised the requirements for receiver analog-to-digital converters (ADCs) and AGC systems.

[0003] Typically, to avoid saturation, AGC systems often employ conservative approaches, resulting in the ADC's dynamic range not being fully utilized. Summary of the Invention

[0004] The purpose of this disclosure is to overcome the aforementioned deficiencies in the prior art and to provide a gain control method, chip system, and medium.

[0005] According to a first aspect of this disclosure, a gain control method is provided, applied to a gain control device, the method comprising: detecting a received signal to obtain a detection intensity of the received signal; estimating a saturation signal in the received signal and obtaining a saturation loss caused by the saturation signal; and obtaining a gain adjustment value based on the detection intensity and the saturation loss, wherein the saturation loss is used to adjust a reference intensity of the received signal.

[0006] In some embodiments, obtaining a gain adjustment value based on the detection intensity and the saturation loss includes adjusting the reference intensity based on the degree of the saturation loss, wherein the difference between the maximum value of the reference intensity and the full-scale threshold of the analog-to-digital converter is less than a preset threshold; and obtaining a gain adjustment value based on the detection intensity and the reference intensity.

[0007] In some embodiments, obtaining the gain adjustment value based on the detection intensity and the saturation loss includes substituting the saturation signal into a preset cost function expression to obtain a target cost function expression; and solving for the minimum cost of the target cost function expression to obtain the gain adjustment value.

[0008] In some embodiments, the preset cost function expression includes the cost introduced by the saturation signal and the cost introduced by insufficient gain, and bringing the saturation signal into the preset cost function expression includes bringing the saturation signal and the received signal into the preset cost function expression.

[0009] In some embodiments, substituting the saturation loss into a preset cost function expression to obtain a target cost function expression includes: obtaining signal samples in the current period; obtaining sample values ​​in the signal samples; in response to the sample values ​​exceeding a saturation threshold, substituting the sample values ​​into the preset cost function expression to obtain a current target cost function expression; and merging the current target cost function expressions to obtain a total target cost function expression.

[0010] In some embodiments, merging the current target cost function expression to obtain the total target cost function expression includes obtaining a weighting factor of the sample value, the weighting factor representing the saturation depth and / or duration of the sample value; and weighting the current target cost function expression based on the weighting factor.

[0011] In some embodiments, the saturation loss includes signal-to-noise ratio (SNR) loss and / or signal-to-dryness ratio (SINR) loss.

[0012] In some embodiments, estimating the saturated signal in the received signal and obtaining the saturation loss caused by the saturated signal includes: obtaining a saturated signal model, the saturated signal model being used to obtain one or more of the following after sample saturation under different received signal parameters: energy distribution, equivalent noise, and interference characteristics; analyzing the received signal based on the saturated signal model to obtain a saturation estimate, the saturation estimate including one or more of the following: the number and proportion of signal samples exceeding a saturation threshold in the received signal, and energy distribution; and obtaining the saturation loss based on the saturation estimate.

[0013] In some embodiments, the different received signal parameters include one or more of the following: analog-to-digital converter parameters, antenna and radio frequency circuit parameters, signal waveform and communication standard, and interference signal characteristics.

[0014] According to a second aspect of this disclosure, a chip system is provided, including a processor and a communication interface; the communication interface is used to receive and / or transmit data, and / or to provide input and / or output to the processor; the processor is used to implement the method according to the first aspect above.

[0015] According to a third aspect of this disclosure, a computer-readable storage medium is provided having computer-executable instructions stored thereon for performing the method according to the first aspect above.

[0016] According to a fourth aspect of this disclosure, a computer program product is provided, wherein the computer program product is tangibly stored on a computer-readable storage medium and includes computer-executable instructions that, when executed by at least one processor, cause at least one processor to perform the method according to the first aspect described above.

[0017] According to the gain control method, chip system, and medium disclosed herein, a signal output from an analog-to-digital converter is received and detected to obtain the signal detection strength. Furthermore, a saturation signal in the received signal is estimated, and the saturation loss caused by the saturation signal is obtained. The performance loss caused by saturation is used to adjust the reference strength of the received signal. Compared to conservative gain control strategies in the prior art, this method can fully utilize the dynamic range of the ADC, thereby improving the signal-to-noise ratio. Attached Figure Description

[0018] Other features and advantages of this disclosure will be better understood through the following detailed description of preferred embodiments in conjunction with the accompanying drawings, wherein the same reference numerals denote the same or similar parts.

[0019] Figure 1 A schematic diagram of the architecture of an exemplary receiving system according to an embodiment of the present disclosure is shown.

[0020] Figure 2a A flowchart of an exemplary automatic gain control method according to an embodiment of the present disclosure is shown.

[0021] Figure 2b A flowchart of an exemplary method for obtaining saturation loss according to an embodiment of this disclosure is shown.

[0022] Figure 3 A flowchart of an exemplary reference intensity adjustment method according to an embodiment of the present disclosure is shown.

[0023] Figure 4 A diagram illustrating the relationship between an exemplary automatic gain control voltage and a signal-to-noise ratio according to an embodiment of this disclosure is shown.

[0024] Figure 5 A flowchart illustrating an exemplary method for obtaining a target cost function according to an embodiment of this disclosure is shown.

[0025] Figure 6a A schematic diagram of an exemplary gain control device according to an embodiment of the present disclosure is shown.

[0026] Figure 6b A schematic diagram of the structure of an exemplary saturation loss acquisition unit according to an embodiment of the present disclosure is shown.

[0027] Figure 7A schematic diagram of the structure of an exemplary communication device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0028] To enable those skilled in the art to better understand the technical solutions of this disclosure, the disclosure will be further described in detail below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the disclosure.

[0029] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of the methods and systems according to various embodiments of this disclosure. It should be noted that the functions marked in the boxes may occur in a different order than that shown in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. Furthermore, in this disclosure, the terms "first," "second," etc., are used only for distinction and not for limiting the order of events, unless otherwise stated.

[0030] The scheme disclosed herein can be applied to various communication systems, such as long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, new radio (NR) and other fifth-generation (5G) mobile communication systems, as well as systems that evolve after 5G, such as sixth-generation (6G) mobile communication systems and communication-sensing integrated systems.

[0031] Typically, the signal strength at the receiver input varies significantly due to factors such as transmit power, transmission distance, weather, and obstructions. Automatic gain control (AGC) is the process of automatically adjusting the amplifier's gain. Receiver circuits have an operating range; if the input signal is too small, noise may overwhelm it; if the input signal is too large, the receiver circuit may overload or saturate, preventing it from functioning properly. The adjustment in AGC aims to maintain a relatively constant output after AGC, or for the signal variation to remain within the linear operating range of subsequent circuits. This ensures the receiver can still function normally when the input signal is too small, and prevents saturation or blockage when the input signal is too large.

[0032] Please see Figure 1 , Figure 1 A schematic diagram of the architecture of a receiving system according to an embodiment of the present disclosure is shown. The receiving system includes a radio frequency front-end, an automatic gain control loop, a digital signal processing unit, and a baseband receiver.

[0033] The RF front end includes low-noise amplifiers, mixers, analog filters, etc. The mixer shifts the RF signal, amplified by the low-noise amplifier, according to the frequency of the local oscillator signal. The analog filter eliminates high-frequency noise and interference in the signal path before ADC conversion, preventing aliasing noise from contaminating the signal.

[0034] The automatic gain control loop includes a variable-gain amplifier (VGA) and an analog-to-digital converter (ADC). The ADC converts the analog signal input to the ADC into a digital signal output. The VGA adjusts the power of its output signal based on the feedback gain value. A digital filter is placed after the ADC to remove digital noise injected during the analog-to-digital conversion. The digital signal processor performs digital signal processing on the signal output from the digital filter.

[0035] Figure 1 The diagram also shows an AGC device. The AGC device can feed back an appropriate gain feedback value to the VGA, thereby adjusting the power of the VGA output signal and improving the accuracy of the digital signal processor's signal resolution.

[0036] Typically, AGC dynamically adjusts the gain to ensure the signal amplitude input to the ADC remains within a safe range, usually below a certain threshold of the ADC's full-scale range, such as a 3-6 dB margin. This conservative strategy reduces signal ripple and ADC overload. However, the strict avoidance of signal saturation in this strategy can lead to underutilization of the ADC's dynamic range. Furthermore, when the signal strength is weak, if the AGC, due to its conservative strategy, does not adjust the gain to the optimal value, the signal amplitude input to the ADC will be even lower, increasing the relative contribution of quantization noise and resulting in a loss of signal-to-noise ratio. Additionally, to avoid saturation, the receiving device typically requires a high-resolution (e.g., 12-bit or higher) ADC and a complex analog front-end to ensure sufficient dynamic range, thus increasing hardware costs.

[0037] To address the aforementioned problems, one embodiment of this disclosure provides a gain control method. Figure 2a A flowchart of an automatic gain control method 10 according to an embodiment of the present disclosure is shown. Method 10 can be... Figure 6a The gain control device 600 or Figure 7 The communication device 700 is implemented in the method. Method 10 includes steps S11-S13.

[0038] In S11, the received signal is detected to obtain the detection strength of the detection signal.

[0039] The system receives and detects the signal processed by the ADC to obtain the detected signal strength. In some examples, the detected signal strength can be represented by the Received Signal Strength Indicator (RSSI) or signal power. RSSI is used to measure the signal strength received by the receiver in wireless communication.

[0040] In S12, the saturation signal in the received signal is estimated and the saturation loss caused by the saturation signal is obtained.

[0041] In some examples, the saturation signal can be estimated before analog-to-digital conversion (ADC). For instance, a comparator in the analog circuit can compare the input signal with a preset threshold to determine if saturation is present. In other examples, the saturation signal can be estimated after ADC processing. For example, peak detection can be used to directly detect whether the ADC output sample exceeds a saturation threshold range to determine if the sample is saturated. The saturation threshold range can be determined based on the ADC's full-scale range. For example, for a 12-bit ADC, a sample is considered unsaturated if it falls within the range of (-2048, 2047), otherwise it is considered saturated. That is, the saturation signal is determined directly based on the ADC's full-scale range. Alternatively, a sample is considered saturated when it approaches its full-scale value, for example, exceeding 95% of the full-scale range. In other examples, saturation can also be determined by real-time detection of whether the integrator output amplitude exceeds a preset threshold.

[0042] Saturation loss due to saturation signal can be obtained by estimating the saturation signal in the received signal. Saturation loss refers to the quantifiable performance loss resulting from the saturation signal estimation. Saturation loss characterizes the degradation of receiver performance caused by the saturation signal. In some examples, saturation loss may include one or more of the following: signal-to-noise ratio (SNR) loss, signal-to-interference-plus-noise ratio (SINR) loss, increased bit error rate (BER), deterioration of error vector amplitude, and decreased throughput. Among these, SINR loss can reflect the level of interference boost to adjacent channels.

[0043] In S13, the gain is obtained based on the detection intensity and saturation loss, where the saturation loss is used to adjust the reference intensity of the received signal.

[0044] In some examples, the reference strength of the received signal can be represented by Received Signal Strength Indication (RSSI) or signal power. The gain can be calculated based on the difference between the detected signal strength and the reference strength. The reference strength of the received signal represents the target strength of the ADC output signal. For example, if the detected signal strength is P_meas, the target strength is P_target, and the gain adjustment is gain_adjust, where gain_adjust = P_target - P_meas.

[0045] In this step, the saturation loss is used to adjust the reference strength of the received signal; that is, the reference strength changes with fluctuations in the saturation loss. Therefore, the gain adjustment value is dynamically adjusted according to the saturation loss. In some examples, the reference strength of the received signal can be adjusted based on the strength of the saturation loss. When the saturation loss is small, a relatively large reference strength can be set; when the saturation loss is large, a relatively small reference strength can be set. In other words, in this step, the reference strength is no longer limited by the margin in the ADC range, thus fully utilizing the dynamic range of the ADC.

[0046] In method 10, the signal output from the analog-to-digital converter is received and detected to obtain the signal detection strength. Additionally, the saturation signal in the received signal is estimated, and the saturation loss caused by the saturation signal is obtained. The performance loss caused by saturation is used to adjust the reference strength of the received signal. Compared to the conservative gain control strategies in the prior art, method 10 can fully utilize the dynamic range of the ADC, thereby improving the signal-to-noise ratio.

[0047] In some implementations, S12 includes sub-steps S121-S123. Figure 2b A flowchart illustrating a method for obtaining saturation loss according to an embodiment of this disclosure is shown. This method can be... Figure 6a Saturation loss acquisition unit 602 Figure 6b The saturation loss acquisition unit 602 and Figure 7 Any of the implementations of the communication device 700 in the middle.

[0048] In S121, a saturated signal model is obtained. The saturated signal model is used to obtain one or more of the following after sample saturation: energy distribution, equivalent noise, and interference characteristics under different received signal parameters.

[0049] Saturated signal models can be used to simulate signal saturation scenarios. Based on saturated signal models, the saturated signal characteristics of the received signal under corresponding received signal parameters can be analyzed. These signal characteristics include one or more of the following: energy distribution after sample saturation, equivalent noise, and interference characteristics.

[0050] In some examples, different received signal parameters include one or more of the following: analog-to-digital converter parameters, antenna and RF circuit parameters, signal waveform and communication standard, and interference signal characteristics. ADC device parameters include one or more of the following: bit depth, full-scale voltage, sampling rate, and dynamic range. The type of received signal reflects the preprocessing characteristics of the signal before it reaches the ADC, such as antenna gain and RF link gain. The communication standard represents the waveform of the received signal, such as OFDM. Interference signal characteristics include one or more of the following: interference type, center frequency, bandwidth, power level, and modulation method. The above parameters and the corresponding saturation signal estimation methods constitute a saturation signal model. After acquiring the received signal, it can be estimated based on the above parameters and the saturation signal estimation model.

[0051] In S122, the received signal is analyzed based on the saturation signal model to obtain a saturation estimate. The saturation estimate includes one or more of the following: the number of signal samples exceeding the saturation threshold in the received signal, their proportion, and the energy distribution.

[0052] Saturation estimation of the received signal can be performed based on prior parameters such as the signal characteristic model provided by the saturation signal model. In some examples, saturation estimation may include sample counting and saturation energy estimation. Sample counting can count the number and proportion of signal samples exceeding the saturation threshold. The number and proportion of samples can be used to quantify the frequency of saturation occurrence. In saturation energy estimation, the energy distribution of the saturated signal for each sample can be calculated to assess the impact of the degree of saturation on signal quality.

[0053] In S123, the saturation loss is obtained based on the saturation estimate.

[0054] In this step, the statistical results of the saturation estimate are transformed into a quantifiable loss, which is used to assess the specific impact of the saturation signal.

[0055] In some implementations, the reference strength can be adjusted based on the degree of saturation loss. For example, the degree of loss can be represented by the difference between the signal-to-noise ratio (SNR) or signal-to-dryness ratio (SINR) corresponding to the saturated signal and the corresponding upper limit that the receiving device can achieve.

[0056] In some examples, step S13 may include the following sub-steps S131-S132.

[0057] In S131, the reference strength is adjusted based on the degree of saturation loss, wherein the difference between the maximum value of the reference strength and the full-scale threshold of the analog-to-digital converter is less than a preset threshold.

[0058] When the saturation loss is small, the corresponding reference strength is relatively large. This value can be set to the strength corresponding to the ADC's full-scale threshold or slightly higher. In other words, the difference between the maximum value of the reference strength and the full-scale threshold of the analog-to-digital converter is less than a preset threshold. Unlike existing gain control techniques, this step allows the signal to approach or even slightly exceed the ADC's saturation threshold. When the signal strength is weak, the ADC's dynamic range can be fully utilized, and the gain can be increased, thus improving the signal-to-noise ratio.

[0059] In S132, the gain adjustment value is obtained based on the detection intensity and the reference intensity.

[0060] The gain adjustment value is obtained based on the detection intensity and the signal reference intensity adjusted based on the degree of saturation loss.

[0061] In some implementations, the reference intensity can be adjusted according to the range of saturation loss. Figure 3 A flowchart of a reference intensity adjustment method 20 according to an embodiment of the present disclosure is shown. Method 20 can be derived from... Figure 6a The gain control device 600 or Figure 7 The communication device in the middle is used for implementation. Method 20 includes S21-S26.

[0062] In S21, the saturation loss is statistically analyzed.

[0063] In S22, it is determined whether the saturation loss is lower than a preset minimum threshold. If yes, proceed to S23; otherwise, proceed to S24.

[0064] In S23, if the saturation loss is less than the preset minimum threshold, it indicates that the degree of saturation loss is low and the saturation signal has little impact on performance. Therefore, the reference strength can be increased to improve the signal-to-noise ratio.

[0065] In S24, it is determined whether the saturation loss is greater than the preset maximum threshold. If yes, proceed to S25; otherwise, it means that the saturation loss is between the preset minimum threshold and the preset maximum threshold, and proceed to S26.

[0066] In S25, if the saturation loss is greater than the preset maximum threshold, it indicates that the degree of saturation loss is high and the saturation signal has a significant impact on performance, so the reference strength can be reduced.

[0067] In S26, the reference strength is maintained in response to the saturation loss being between a preset minimum threshold and a preset maximum threshold.

[0068] In some examples, the preset minimum threshold or preset maximum threshold can be set according to the performance of the receiving device, for example, by a value near the upper limit of the performance that the receiving device needs to achieve (minimum saturation loss) or the lower limit of the performance it can tolerate (maximum saturation loss).

[0069] In some examples, the reference strength or gain adjustment value can be adjusted by quantizing the cost of saturation. Specifically, step S13 may include the following sub-steps S1311-S1322.

[0070] In S1311, the saturation signal is substituted into the preset cost function expression to obtain the target cost function expression.

[0071] In this step, the estimation result of the saturation signal is transformed into a quantifiable control cost. A preset cost function expression can be determined based on the saturation signal estimation model, and the saturation signal is substituted into the preset cost function expression to obtain the target cost function expression.

[0072] In S1312, the target cost function expression is minimized to obtain the gain adjustment value. The minimized cost solution can be solved by iterative solution, lookup table search, analytical solution or combination method.

[0073] A preset algorithm can be used to minimize the cost of the target cost function expression, yielding the gain adjustment value when the cost is minimized. In some examples, the obtained gain adjustment value is a specific value or a range.

[0074] To better illustrate this point, the following example uses an OFDM waveform to explain how to obtain the gain adjustment value through a cost function.

[0075] Assuming the original OFDM time-domain signal is as follows: x ( n ) indicates that its power is ,in [·] represents the expected value (or statistical average). The additive white Gaussian noise at the receiver is... Its power is The peak-shaving threshold is set to A, and the peak-shaving signal is expressed by formula (1): (1) in, It is the phase of the original signal.

[0076] Distortion signal introduced by peak clipping The distortion power is expressed by formula (2). Expressed by formula (3): (2) (3)

[0077] Without peak clipping, the receiver performance signal-to-noise ratio is defined according to formula (4) as follows: (4) in, The average power of the signal. The average power of the noise. This represents the upper limit of performance in the ideal linear case. Equation (4) can be converted to the logarithmic field according to Equation (5): (5)

[0078] The total noise after peak clipping includes the original noise. and distortion noise .because d ( n It is generated by the signal processing at the transmitting end, while Since the peaking is introduced by the channel, we assume that the two are unrelated. Furthermore, although peak clipping slightly reduces the average signal power, this effect is negligible, especially when the peak clipping threshold is not set too strictly. Therefore, it can still be approximated. The power of the useful signal. Based on these assumptions, the total effective noise power after peak clipping is the sum of the channel noise power and the distortion noise power. That is, the signal-to-noise ratio in the linear domain is shown in Equation (6), and in the logarithmic domain it is shown in Equation (7). It can be seen that distortion noise and channel noise together degrade the received signal-to-noise ratio. (6) (7)

[0079] The signal-to-noise ratio loss is the difference between the original signal-to-noise ratio and the peak-shaving signal-to-noise ratio on the dB scale, as shown in formula (8). (8)

[0080] Substituting formulas (5) and (7) into formula (8) yields formula (9). (9)

[0081] Using the properties of logarithmic operations, formula (9) can be transformed into formula (10). (10)

[0082] Then, we can obtain the concise expression (11) of formula (10). (11)

[0083] For Gaussian signals x ( n The distortion noise power can be calculated by integration. Let the normalization threshold be... Threshold with signal standard deviation The ratio, that is Normalized threshold The value of is a dimensionless parameter; the larger the value, the less severe the peak clipping; the smaller the value, the more severe the peak clipping. The average power of the distortion noise can be obtained from formula (12). (12) in, Let be the probability density function of a Gaussian variable.

[0084] make ,but It is a standard Gaussian variable, and The lower limit of integration becomes Substituting into formula (12) yields formula (13). (13) Here, the standard normal PDF (see formula (14)) and the standard normal CDF (see formula (15)) are defined. (14) (15)

[0085] Expand the integrand And use the known integral results of the following equations (16)-(18). (16) (17) (18)

[0086] Substituting into formula (13), we get: (19)

[0087] Thus, the ratio of distortion noise power to signal power can be obtained from formula (20). (20)

[0088] Substituting formula (20) into formula (11) yields formula (21). (twenty one)

[0089] It is understandable that Formula (21) is based on the statistical assumptions of OFDM signals (complex Gaussian). For other signals (e.g., single-carrier signals), the specific expression of Formula (21) is different, but the above analysis steps are similar. In addition, Formula (21) is calculated based on SNR. In some other examples, it can be calculated based on SINR. Since the interference is frequency selective, it can be analyzed and calculated separately for each frequency sub-band.

[0090] In obtaining the gain adjustment value, formula (21) can be used as the preset cost function expression. The original signal-to-noise ratio can be obtained based on the estimated saturation signal. The minimum tolerable signal-to-noise ratio loss is determined based on the link budget. Then, using formula (21), the normalized threshold corresponding to the tolerable signal-to-noise ratio loss that satisfies the objective cost function expression is found through numerical methods or table lookup. Finally, the peak reduction threshold is obtained. And based on this, obtain the gain adjustment value.

[0091] In the example above, the gain adjustment takes into account the cost caused by the saturation signal. In other examples, the gain adjustment may consider not only the cost caused by the saturation signal but also the cost introduced by insufficient gain; that is, the preset cost function expression includes both the cost introduced by saturation loss and the cost introduced by insufficient gain.

[0092] In some implementations, gain adjustment can be achieved by quantifying costs, taking into account saturation loss, or by using a multi-dimensional approach. Figure 4 A diagram illustrating the relationship between automatic gain control voltage and signal-to-noise ratio in one embodiment of this disclosure is shown.

[0093] Curves 1 and 2 represent the SNR as a function of control voltage under different influencing conditions. Curve 1 shows the effect of signal saturation. In Curve 1, when signal saturation occurs, the SNR decreases with increasing control voltage due to signal distortion and interference. Curve 2 shows the effect of insufficient gain or quantization noise. In Curve 2, the SNR increases with increasing control voltage because the ADC bit width utilization is improved.

[0094] From the perspective of receiving performance loss Figure 4 Curve 1 shows a positive correlation between SNR loss due to saturation and control voltage, while curve 2 shows a negative correlation between SNR loss due to insufficient gain or quantization noise and control voltage. A balance needs to be struck between signal saturation and insufficient gain during the acquisition of the control voltage.

[0095] Therefore, in adjusting the gain based on the quantization cost, the costs caused by underquantization and saturation signal can be considered comprehensively. In some examples, the above-mentioned preset cost function expression may include the cost introduced by saturation loss and the cost introduced by underweight gain.

[0096] For example, a preset cost function can be constructed based on formula (22): (twenty two) in, The cost introduced by saturation signals, The cost introduced for insufficient gain, and These are their respective weighting coefficients. It increases monotonically with the increase of control voltage or equivalent signal reference strength, and can be obtained by referring to formula (21). . It decreases monotonically as the control voltage or the equivalent signal reference strength increases.

[0097] In some examples, the relative magnitudes of the weighting coefficients can be set according to the specific characteristics of the receiving device. For instance, when the receiving device is extremely sensitive to distortion (such as in a high-order QAM system). It can be set relatively high. For example, when the ADC has a low bit depth, quantization noise is a major limitation. It can be set to a relatively high level.

[0098] After determining the preset cost function expression (22), the estimated value of the saturated signal and the received signal can be input into it, and the value of the total cost function within the feasible control voltage range can be calculated. Then, the control voltage or equivalent signal reference strength that minimizes the total cost can be found. According to the above multi-dimensional dynamic adjustment method, it is possible to... Figure 4 Find the control voltage value or range that corresponds to the smaller decrease in SNR in curve 1 and the significant increase in SNR in curve 2.

[0099] exist Figure 4 In the diagram, V1 represents the control voltage determined according to existing methods. In this case, the control voltage has a certain margin relative to the full-scale range of the ADC. The control voltage determined according to the total cost function described above is V2, where V2 > V1. In this case, the effects of saturation signals and insufficient gain are quantized and integrated, thereby fully utilizing the dynamic range of the ADC.

[0100] The aforementioned controllable saturation automatic gain control method exhibits stronger robustness in strong interference environments by precisely controlling the degree of saturation. For example, for strong out-of-band interference signals, this scheme allows the interference signal to saturate, thereby maintaining linear amplification of the useful signal within the band and avoiding a decrease in the signal-to-noise ratio of the useful signal due to a reduction in overall gain. Furthermore, in impulse interference environments, this scheme can quickly respond to interference impulses and allow them to saturate while maintaining precise gain control of the useful signal, thus effectively improving the signal-to-noise ratio in impulse noise environments.

[0101] Furthermore, this approach eliminates the need for a high-resolution (e.g., 12 bits or higher) ADC to ensure sufficient dynamic range, allowing the use of a lower-resolution ADC and enabling it to achieve performance comparable to that of a high-resolution ADC. Additionally, the simplified analog front-end simplifies circuit design and reduces power consumption and cost due to the reduced number of gain stages and lower linearity requirements.

[0102] In some implementations, the saturation signal in S1311 can be obtained by substituting the signal into the preset cost function expression using the signal within the statistical period. Figure 5 A flowchart of a method 50 for obtaining a target cost function according to an embodiment of this disclosure is provided. Method 50 can be derived from... Figure 6a The gain control device 600 or Figure 7 The communication device in the middle is used for implementation. Method 50 includes S51-S56.

[0103] In S51, signal samples within the current period are acquired. Multiple time-domain sampling points or signal samples are received within a predetermined time period.

[0104] In S52, sample values ​​from the signal samples are acquired. In some examples, the sample values ​​can be obtained by absolute value or by calculating the square value. They are typically represented by signal level or power indicators.

[0105] In S53, the sample value is compared with the saturation threshold. If the saturation threshold is exceeded, proceed to S54; otherwise, proceed to S56.

[0106] In S54, in response to a sample value exceeding a saturation threshold, the sample value is substituted into a preset cost function expression to obtain the current target cost function expression. In this step, the cost of the current saturated sample value, such as SNR loss or SINR loss, is calculated.

[0107] In S55, the current objective cost function expressions are merged to obtain the total objective cost function expression. The objective cost function expressions of the current samples are merged into the total objective cost function expression. Then, the process returns to S52 to calculate the next sample value, iterating through all samples within the current period.

[0108] S56 indicates that no cost needs to be calculated, meaning that the value is zero when the preset cost function expression is obtained by merging.

[0109] In some examples, the merging process in S55 includes weighting the various current objective cost function expressions to improve their accuracy. For example, S55 may include substeps S551-S552.

[0110] In S551, the weighting factor of the sample value is obtained, which represents the saturation depth and / or duration of the sample value.

[0111] In S552, the current objective cost function expression is weighted based on weighting factors.

[0112] Figure 6a A schematic diagram of a gain control device 600 according to an embodiment of the present disclosure is shown. The gain control device 600 includes a detection unit 601, a saturation loss acquisition unit 602, and a gain adjustment unit 603. The detection unit 601 is configured to detect a received signal to acquire the detection intensity of the received signal. The saturation loss acquisition unit 602 is configured to estimate a saturation signal in the received signal and acquire the saturation loss caused by the saturation signal. The gain adjustment unit 603 is configured to acquire a gain adjustment value based on the detection intensity and the saturation loss, wherein the saturation loss is used to adjust a reference intensity of the received signal. Detailed descriptions of the detection unit 601, the saturation loss acquisition unit 602, and the gain adjustment unit 603 can be found above. Figures 2a-5 The relevant text sections will not be elaborated upon here.

[0113] Figure 7 The diagram shows a structural schematic of a communication device 700 according to an embodiment of this disclosure. The communication device 700 can be used to implement the gain control function in the above-described method. The communication device 700 is a device with computing and / or communication capabilities. Here, the communication device can be a physical device, a communication module, component, or chip within a physical device, a communication module, component, or chip within a terminal device, or a device used in conjunction with a physical device. In one embodiment of this disclosure, the communication device can be a chip system. A chip system can be composed of chips or can include chips and other discrete components.

[0114] like Figure 7 As shown, the communication device 700 includes a processor 701. In one possible implementation, it may also include at least one communication interface 702, or the processor 701 and the communication interface 702 may be coupled. In yet another possible implementation, it may also include at least one memory 703, which may be integrated with the processor 701, disposed separately, or located outside the communication device 700. It should be understood that this disclosure does not limit the number of processors and memories in the communication device 700.

[0115] Processor 701 is a module for performing calculations and may include any one or more of the following: controller (e.g., memory controller), logic circuit, baseband processor, central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), digital signal processor (DSP), coprocessor (assisting the central processing unit in completing corresponding processing and applications), field programmable gate array (FPGA), application specific integrated circuit (ASIC), microcontroller unit (MCU).

[0116] Communication interface 702 is used to provide information input or output to at least one processor. In some examples, communication interface 702 can be used to receive data transmitted externally and / or transmit data externally. Communication interface 702 can be an input / output interface, a wired link interface including such as an Ethernet cable, or a wireless link interface (Wi-Fi, Bluetooth, general wireless transmission, and other wireless communication technologies, etc.). Optionally, communication interface 702 may also include a transmitter (such as a radio frequency transmitter, antenna, etc.) or a receiver coupled to the interface.

[0117] Memory 703 provides storage space, which may optionally store application data, user data, operating system and computer programs, configuration files, etc. Memory 703 may include volatile memory, such as random access memory (RAM). Memory 703 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0118] The communication device 700 may also include a bus 704, which may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 7 The bus 704 may be represented by a single line, but this does not mean that there is only one bus or one type of bus. The bus 704 may include a path for transmitting information between various components of the communication device 700 (e.g., memory 703, processor 701, communication interface 702).

[0119] In embodiments of this disclosure, memory 703 stores executable instructions, and processor 701 executes these executable instructions to implement the aforementioned method, for example... Figures 2a-5 The methods described in the embodiments are not repeated here. That is, the memory 703 stores instructions for performing the above methods.

[0120] When the aforementioned communication device 700 is a chip used in a terminal, the terminal chip receives information from other modules (such as an RF module or antenna) within the terminal. This information is sent to the terminal by other terminals or network devices. Alternatively, the terminal chip outputs information to other modules (such as an RF module or antenna) within the terminal, which is information sent by the terminal to other terminals or network devices.

[0121] When the aforementioned communication device 700 is a chip used in a network device, the network device chip receives information from other modules (such as radio frequency modules or antennas) in the network device. This information is sent to the network device by a terminal or other network device. Alternatively, the network device chip outputs information to other modules (such as radio frequency modules or antennas) in the network device, which is information sent by the network device to a terminal or other network device.

[0122] An embodiment of this disclosure may also provide a computer program product including computer instructions that, when executed on at least one processor, implement the aforementioned, for example... Figures 2a-5 The methods in the embodiments, etc.

[0123] In one possible implementation, the computer program product can be a software installation package or an image package, which can be downloaded and executed on a computing device when the aforementioned method is required.

[0124] One embodiment of this disclosure may also provide a computer program for implementing the foregoing examples. Figures 2a-5 The methods in the embodiments, etc.

[0125] One embodiment of this disclosure also provides a computer-readable storage medium. The computer-readable storage medium includes instructions for implementing the foregoing, for example... Figures 2a-5 The method described in the embodiments.

[0126] The computer-readable storage medium can be any available medium that the communication device can store, or a data storage device such as a data center that contains one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media, or semiconductor media (e.g., solid-state drives).

[0127] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0128] Furthermore, although exemplary embodiments have been described herein, their scope includes any and all embodiments based on this disclosure that have equivalent steps, modifications, omissions, combinations (e.g., schemes involving overlapping embodiments), adaptations, or alterations. The steps in the claims are to be interpreted broadly based on the language used in the claims and are not limited to the examples described in this specification or during the implementation of this disclosure, which are to be interpreted as non-exclusive. Therefore, this specification and examples are intended to be considered illustrative only, and the true scope and spirit are indicated by the various claims in the claims and the full scope of their equivalents.

[0129] The above description is intended to be illustrative and not restrictive. For example, the above examples (or one or more thereof) can be used in combination with each other. Other embodiments can be used by those skilled in the art when reading the above description. Furthermore, in the above specific embodiments, various features may be grouped together to simplify this disclosure. Features disclosed that are not claimed in the claims are not essential to any claim. Rather, the subject matter of this disclosure may be less than all the features of a particular disclosed embodiment.

[0130] Therefore, the claims are incorporated herein by way of example or embodiment, wherein each claim is an independent, separate embodiment, and these embodiments are contemplated to be combined with each other in various combinations or arrangements. The scope of protection of this disclosure should be determined by reference to the appended claims and the full scope of their equivalents.

Claims

1. A gain control method applied to a gain control device, the method comprising: The received signal is detected to obtain the detection intensity of the received signal; Estimate the saturation signal in the received signal and obtain the saturation loss caused by the saturation signal; as well as A gain adjustment value is obtained based on the detection intensity and the saturation loss, wherein the saturation loss is used to adjust the reference intensity of the received signal.

2. The gain control method according to claim 1, wherein, Obtaining the gain adjustment value based on the detection intensity and the saturation loss includes, The reference strength is adjusted based on the degree of saturation loss, wherein the difference between the maximum value of the reference strength and the full-scale threshold of the analog-to-digital converter is less than a preset threshold. as well as The gain adjustment value is obtained based on the detection intensity and the reference intensity.

3. The gain control method according to claim 1 or 2, wherein, Obtaining the gain adjustment value based on the detection intensity and the saturation loss includes, The saturation signal is substituted into a preset cost function expression to obtain the target cost function expression; as well as The target cost function expression is minimized to obtain the gain adjustment value.

4. The gain control method according to claim 3, wherein, The preset cost function expression includes the cost introduced by the saturation signal and the cost introduced by insufficient gain. Furthermore, substituting the saturation signal into the preset cost function expression includes... Substitute the saturation signal and the received signal into a preset cost function expression.

5. The gain control method according to claim 3, wherein, Substituting the saturation loss into a preset cost function expression yields the target cost function expression, which includes: Obtain signal samples within the current period; Obtain the sample values ​​from the signal samples; In response to the sample value exceeding the saturation threshold, the sample value is substituted into a preset cost function expression to obtain the current target cost function expression; as well as Merge the current target cost function expressions to obtain the total target cost function expression.

6. The gain control method according to claim 5, wherein, The combined current objective cost function expressions to obtain the total objective cost function expression include: Obtain the weighting factor of the sample value, wherein the weighting factor represents the saturation depth and / or duration of the sample value; as well as The current objective cost function expression is weighted based on the weighting factor.

7. The gain control method according to claim 1, wherein, The saturation loss includes signal-to-noise ratio (SNR) loss and / or signal-to-dryness ratio (SINR) loss.

8. The gain control method according to claim 1, wherein, Estimating the saturation signal in the received signal and obtaining the saturation loss caused by the saturation signal includes, A saturated signal model is obtained, which is used to obtain one or more of the following: energy distribution, equivalent noise, and interference characteristics after sample saturation under different received signal parameters; The received signal is analyzed based on the saturated signal model to obtain a saturation estimate, which includes one or more of the following: the number and proportion of signal samples exceeding the saturation threshold in the received signal; and the energy distribution. The saturation loss is obtained based on the saturation estimate.

9. The gain control method according to claim 8, wherein, The different received signal parameters include one or more of the following: analog-to-digital converter parameters, antenna and radio frequency circuit parameters, signal waveform and communication standard, and interference signal characteristics.

10. A chip system comprising a processor and a communication interface; the communication interface being configured to receive and / or transmit data, and / or to provide inputs and / or outputs to the processor; the processor being configured to implement the gain control method according to any one of claims 1 to 9.

11. A computer-readable storage medium, wherein, The computer-readable storage medium has computer-executable instructions stored thereon for performing the gain control method according to any one of claims 1 to 9.

12. A computer program product, wherein, The computer program product is tangibly stored on a computer-readable storage medium and includes computer-executable instructions that, when executed by at least one processor, cause at least one processor to perform the gain control method according to any one of claims 1 to 9.

Images