DFE tap coefficient determination method, device, electronic device, and storage medium

Abstract

The present invention provides a method, device, electronic device, and storage medium for determining DFE tap coefficients, relating to the field of communications technology. When the DFE is in a training phase, an FIR filter is trained in a target communication system to obtain training result data including multiple initial tap coefficients and first received symbol data. Then, based on the first received symbol data, noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient are calculated for the multiple initial tap coefficients. When training is determined to be complete based on the first signal-to-noise ratio and the first autocorrelation coefficient, multiple target tap coefficients are screened based on noise power, and a target tap corresponding to each target tap coefficient is determined, thereby disabling all taps in the FIR filter except the target tap. In this way, the tap coefficients of the FIR filter in the DFE are dynamically adjusted and the taps are dynamically switched on and off based on the signal-to-noise ratio and the autocorrelation coefficient, thereby reducing power consumption in data transmission while ensuring stable signal reception.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method, device, electronic device and storage medium for determining DFE tap coefficients. Background Art

[0002] With the rapid development of new energy vehicles in recent years, their intelligence has become increasingly sophisticated. The intelligence of new energy vehicles relies on a large number of sensors. Intelligent new energy vehicles (hereinafter referred to as smart cars) are equipped with high-performance chips that fuse and calculate data collected by various sensors, thereby achieving powerful perception capabilities. With the explosive growth of data volumes, high-speed transmission of sensor data has become a critical link, and long-distance SerDes (serializer / deserializer) and Ethernet communication technologies play an important role in this. Both SerDes and Ethernet rely on DFE (decision feedback equalization) technology to eliminate ISI (intersymbol interference) in the received signal. Furthermore, the specific power consumption of smart cars has always been a bottleneck that has hindered the replacement of traditional vehicles by new energy vehicles. Therefore, data transmission must consider low power design. Summary of the Invention

[0003] The present invention aims to provide a method, device, electronic device and storage medium for determining DFE tap coefficients, so as to reduce the power consumption of data transmission while achieving stable signal reception.

[0004] In a first aspect, an embodiment of the present invention provides a method for determining a DFE tap coefficient, including:

[0005] When a decision feedback equalizer (DFE) is in a training phase, the FIR filter in the DFE is trained in a target communication system based on a maximum number of taps of the FIR filter to obtain training result data; wherein the training result data includes a plurality of initial tap coefficients corresponding to the maximum number of taps and first received symbol data, wherein the first received symbol data includes received symbols corresponding to a plurality of idle symbols transmitted in the target communication system under the plurality of initial tap coefficients;

[0006] Based on the first received symbol data, calculate and obtain noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient under a plurality of the initial tap coefficients;

[0007] Determining a training completion result based on the first signal-to-noise ratio and the first autocorrelation coefficient;

[0008] When the training completion judgment result is training completion, multiple target tap coefficients are screened out from the multiple initial tap coefficients based on the noise power, and a target tap corresponding to each target tap coefficient is determined to close other taps in the FIR filter except the target tap.

[0009] Furthermore, each of the idle symbols is composed of four sub-symbols selected from a sub-symbol set, and the sub-symbol set includes multiple types of sub-symbols; and the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under the multiple initial tap coefficients are calculated based on the first received symbol data, including:

[0010] Acquire, from the first received symbol data, a received symbol sequence corresponding to each type of the sub-symbol within a preset window length;

[0011] Calculating the signal strength corresponding to each type of sub-symbol based on the received symbol sequence corresponding to each type of sub-symbol;

[0012] Based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, the noise power, the first signal-to-noise ratio and the first autocorrelation coefficient under the multiple initial tap coefficients are determined.

[0013] Furthermore, the determining, based on the received symbol sequence and signal strength corresponding to each type of the sub-symbols, the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under the multiple initial tap coefficients includes:

[0014] Based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, an initial autocorrelation coefficient of each type of sub-symbol at a preset step size is calculated;

[0015] The first autocorrelation coefficient is calculated based on the initial autocorrelation coefficients corresponding to each type of the sub-symbols.

[0016] Furthermore, the determining, based on the received symbol sequence and signal strength corresponding to each type of the sub-symbols, the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under the multiple initial tap coefficients includes:

[0017] Based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, noise intensity data corresponding to each type of sub-symbol is calculated;

[0018] The noise power is calculated based on the noise intensity data corresponding to each type of sub-symbol.

[0019] Furthermore, after calculating the noise power based on the noise intensity data corresponding to each type of sub-symbol, the DFE tap coefficient determination method further includes:

[0020] Calculating the signal power according to the signal strength corresponding to each type of sub-symbol;

[0021] The first signal-to-noise ratio is calculated based on the signal power and the noise power.

[0022] Furthermore, determining a training completion result based on the first signal-to-noise ratio and the first autocorrelation coefficient includes:

[0023] Comparing the first signal-to-noise ratio and the first autocorrelation coefficient with a preset signal-to-noise ratio threshold and a preset autocorrelation coefficient threshold, respectively, to obtain a comparison result;

[0024] Based on the comparison result, the training completion determination result is determined.

[0025] Furthermore, the DFE tap coefficient determination method further includes:

[0026] When the DFE is in a data transmission phase, obtaining second received symbol data; wherein the second received symbol data includes received symbols corresponding to a plurality of data symbols transmitted in the target communication system under a plurality of the target tap coefficients;

[0027] Based on the second received symbol data, calculating and obtaining a second signal-to-noise ratio and a second autocorrelation coefficient under the plurality of target tap coefficients;

[0028] Determining a tap coefficient update determination result based on the second signal-to-noise ratio and the second autocorrelation coefficient;

[0029] When the tap coefficient update determination result is to start updating, the plurality of target tap coefficients are updated.

[0030] In a second aspect, an embodiment of the present invention further provides a DFE tap coefficient determination device, including:

[0031] a training module configured to, when a decision feedback equalizer (DFE) is in a training phase, train a finite impulse response (FIR) filter in the DFE in a target communication system based on a maximum number of taps of the FIR filter to obtain training result data; wherein the training result data includes a plurality of initial tap coefficients corresponding to the maximum number of taps and first received symbol data, wherein the first received symbol data includes received symbols corresponding to a plurality of idle symbols transmitted in the target communication system under the plurality of initial tap coefficients;

[0032] A first calculation module is configured to calculate, based on the first received symbol data, noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient under a plurality of the initial tap coefficients;

[0033] A first determination module is configured to determine a training completion determination result based on the first signal-to-noise ratio and the first autocorrelation coefficient;

[0034] A determination module, when the training completion determination result is training completion, filters out multiple target tap coefficients from the multiple initial tap coefficients based on the noise power, and determines a target tap corresponding to each of the target tap coefficients to close other taps in the FIR filter except the target tap.

[0035] In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the DFE tap coefficient determination method described in the first aspect is implemented.

[0036] In a fourth aspect, an embodiment of the present invention further provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for determining the DFE tap coefficients described in the first aspect is executed.

[0037] Embodiments of the present invention provide a method, apparatus, electronic device, and storage medium for determining DFE tap coefficients. The method determines the DFE tap coefficients through the following process: when the DFE is in a training phase, the FIR filter is trained in a target communication system based on a maximum number of taps of the FIR filter in the DFE to obtain training result data. The training result data includes multiple initial tap coefficients corresponding to the maximum number of taps and first received symbol data, where the first received symbol data includes received symbols corresponding to multiple idle symbols transmitted in the target communication system under the multiple initial tap coefficients. Based on the first received symbol data, noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient are calculated under the multiple initial tap coefficients. Furthermore, a training completion determination result is determined based on the first signal-to-noise ratio and the first autocorrelation coefficient. When the training completion determination result is training completion, multiple target tap coefficients are selected from the multiple initial tap coefficients based on the noise power, and a target tap corresponding to each target tap coefficient is determined to close all taps in the FIR filter except the target tap. In this way, based on the signal-to-noise ratio and autocorrelation coefficient, the tap coefficients of the FIR filter in the DFE are dynamically adjusted and the taps are dynamically switched, thereby reducing the power consumption of data transmission while ensuring stable signal reception. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 An architecture diagram of a four-pair Gigabit Ethernet network provided by an embodiment of the present invention;

[0040] Figure 2 A SerDes architecture provided by an embodiment of the present invention;

[0041] Figure 3 A schematic flow chart of a method for determining DFE tap coefficients provided in an embodiment of the present invention;

[0042] Figure 4 A schematic structural diagram of a DFE tap coefficient determination device provided by an embodiment of the present invention;

[0043] Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] Long-distance SerDes and Ethernet communication technologies play an important role in smart cars, and the unit power consumption of smart cars has always been a bottleneck restricting new energy vehicles from replacing traditional cars. Therefore, data collection, transmission and calculation all need to consider low-power design. Based on this, the embodiment of the present invention provides a DFE tap coefficient determination method, device, electronic device and storage medium, which adopts the DFE filter signal-to-noise ratio and channel correlation tracking method, and can dynamically adjust the DFE training strategy and dynamic switch taps for different transmission channels, thereby reducing the power consumption of data transmission while achieving stable signal reception. It should be noted that the application field of the embodiment of the present invention is not limited to new energy vehicles, but is also applicable to other fields involving SerDes or Ethernet communication technologies and having low-power design requirements.

[0046] The embodiments of the present invention can be applied, but are not limited to, to transmission architectures based on DFE technology, such as Gigabit Ethernet (1000BASE-T) and SerDes. DFE includes FIR (Finite Impulse Response) filters. Taking 1000BASE-T as an example, it uses Category 5 twisted pair (CAT-5, consisting of four pairs of eight wires), has a transmission distance of 100 meters, and employs full-duplex baseband transmission.

[0047] Figure 1 shows a four-pair Gigabit Ethernet architecture diagram, Figure 1 ECHO refers to echo, NEXT refers to Near-end Cross Talk, and FEXT refers to Far-end Cross Talk. Figure 1 As shown, 1000BASE-T has a transmission rate of 1000 Mb / s, transmitted and received over four wire pairs, with each pair transmitting at a rate of 250 Mb / s. The baseband signal on each pair is modulated at a rate of 125 Mb / s, meaning that one symbol (in 4-ary format) carries two bits of information. The symbols transmitted by the transmitter are selected from four-dimensional, five-level symbols (i.e., using 4D-PAM5 (four-level 2B1Q) encoding, where ±2V, ±1V, and 0V are used to carry symbol information). Each four-dimensional symbol can be viewed as a tuple (An, Bn, Cn, Dn) of one-dimensional five-level symbols drawn from the set {2, 1, 0, –1, –2}, where n is the symbol in the time series. In the absence of data, idle symbols are transmitted, which are a subset of the code group (i.e., 2, 1, 0, –1, –2), with each symbol in the idle symbols restricted to the set {2, 0, –2} to improve synchronization.

[0048] Figure 2 A SerDes architecture is shown. Input data is processed by the ADC (Analog to Digital Converter) module, the FFE (Feed-Forward Equalization) module, and the DFE module before being output. At the same time, the output of the DFE module is processed by the CDR (Clock and Data Recovery) module and the VCO (Voltage-Controlled Oscillator) module before being fed back to the ADC module.

[0049] To facilitate understanding of this embodiment, a method for determining DFE tap coefficients disclosed in an embodiment of the present invention is first introduced in detail.

[0050] An embodiment of the present invention provides a method for determining DFE tap coefficients, which can be performed by an electronic device with data processing capabilities. Figure 3 FIG. 1 is a flow chart of a method for determining a DFE tap coefficient, which mainly includes the following steps S302 to S308:

[0051] Step S302: When the DFE is in a training phase, the FIR filter is trained in the target communication system based on the maximum number of taps of the FIR filter in the DFE to obtain training result data; wherein the training result data includes a plurality of initial tap coefficients corresponding to the maximum number of taps and first received symbol data, and the first received symbol data includes received symbols corresponding to a plurality of idle symbols transmitted in the target communication system under the plurality of initial tap coefficients.

[0052] The maximum number of taps in an FIR filter corresponds to its maximum order. For example, for 1000BASE-T, when the transmission line length is 100m, the FIR filter uses a maximum order of 256, and the maximum number of taps is 256. The target communication system can be an Ethernet communication system or a communication system based on a SerDes architecture. Idle symbols, also known as IDLE symbols, each consist of four sub-symbols selected from a first sub-symbol set. The first sub-symbol set includes multiple sub-symbol types, each of which is transmitted with equal probability. For example, the first sub-symbol set is the set {2, 0, –2}, and each idle symbol consists of four sub-symbols selected from the set {2, 0, –2}. The sub-symbols of -2, 0, and 2 are transmitted with equal probability.

[0053] In some possible embodiments, step S302 may be implemented by the following process: in the target communication system, based on a preset adaptive filtering algorithm, an FIR filter of maximum order is trained by transmitting idle symbols via a transmitter to obtain a set of initial tap coefficients after the FIR filter converges, and receiving symbols corresponding to multiple idle symbols transmitted in the target communication system under the set of initial tap coefficients; wherein the set of initial tap coefficients includes multiple initial tap coefficients corresponding to the maximum number of taps, and the adaptive filtering algorithm may be, but is not limited to, an LMS (Least Mean Square) algorithm. If the maximum number of taps is 256, the number of initial tap coefficients is 256.

[0054] Step S304 : Based on the first received symbol data, noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient under a plurality of initial tap coefficients are calculated.

[0055] In some possible embodiments, step S304 may be implemented by the following sub-steps:

[0056] Sub-step 1: Obtain, from the first received symbol data, a received symbol sequence corresponding to each type of sub-symbol within a preset window length.

[0057] The preset window length M is much smaller than the total number N of idle symbols transmitted during the training process, and can be set according to actual needs and is not limited here. For example, N=10000, M=1000.

[0058] A received symbol sequence can be constructed for each type of sub-symbol. For example, all received symbols corresponding to 2 within a preset window length are arranged in chronological order to obtain a received symbol sequence corresponding to 2. Considering that sub-symbols of different types with equal absolute values ​​have the same signal strength, received symbols corresponding to sub-symbols of different types with equal absolute values ​​can also be combined to construct a received symbol sequence. For example, all received symbols corresponding to 2 and -2 within a preset window length are arranged in chronological order to obtain a received symbol sequence corresponding to 2 and -2.

[0059] Sub-step 2: Based on the received symbol sequence corresponding to each type of sub-symbol, calculate the signal strength corresponding to each type of sub-symbol.

[0060] The signal strength corresponding to each type of sub-symbol is equal to the average value of the absolute values ​​of each received symbol in the corresponding received symbol sequence.

[0061] Sub-step 3: determining the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under multiple initial tap coefficients based on the received symbol sequence and signal strength corresponding to each type of sub-symbol.

[0062] In a specific implementation, the first autocorrelation coefficient can be obtained as follows: based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, an initial autocorrelation coefficient for each type of sub-symbol is calculated at a preset step size; and based on the initial autocorrelation coefficients corresponding to each type of sub-symbol, a first autocorrelation coefficient is calculated. The preset step size L can be set based on actual needs and is not limited here, for example, L = 10. The first autocorrelation coefficient can be the average of the initial autocorrelation coefficients.

[0063] The noise power can be obtained by: calculating the noise intensity data corresponding to each type of sub-symbol based on the received symbol sequence and signal strength corresponding to each type of sub-symbol; and calculating the noise power based on the noise intensity data corresponding to each type of sub-symbol.

[0064] The first signal-to-noise ratio may be obtained in the following manner: calculating the signal power according to the signal strength corresponding to each sub-symbol; and calculating the first signal-to-noise ratio based on the signal power and the noise power.

[0065] Step S306: Determine a training completion result based on the first signal-to-noise ratio and the first autocorrelation coefficient.

[0066] In some possible embodiments, the first signal-to-noise ratio and the first autocorrelation coefficient may be compared with a preset signal-to-noise ratio threshold and a preset autocorrelation coefficient threshold, respectively, to obtain a comparison result; and a training completion determination result may be determined based on the comparison result.

[0067] Specifically, when the comparison result is that the first signal-to-noise ratio is greater than the signal-to-noise ratio threshold, and the first autocorrelation coefficient is greater than the autocorrelation coefficient threshold, the training completion determination result is determined to be training completion, and then step S308 is executed; when the comparison result is that the first signal-to-noise ratio is less than or equal to the signal-to-noise ratio threshold, or the first autocorrelation coefficient is less than or equal to the autocorrelation coefficient threshold, it is determined whether the current training duration reaches the preset training duration; when the current training duration reaches the preset training duration, the training completion determination result is determined to be training completion, and then step S308 is executed; when the current training duration does not reach the preset training duration, the training completion determination result is determined to be training incomplete, and then the received symbol sequence corresponding to each type of sub-symbol in the next window is continuously obtained from the first received symbol data, and the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient are calculated, etc.

[0068] The signal-to-noise ratio threshold, the autocorrelation coefficient threshold, and the preset training duration can all be set according to actual needs and are not limited here. For example, the preset training duration can be the duration corresponding to transmitting 10,000 idle symbols.

[0069] Step S308, when the training completion determination result is training completion, multiple target tap coefficients are screened out from multiple initial tap coefficients based on noise power, and a target tap corresponding to each target tap coefficient is determined to close other taps in the FIR filter except the target tap.

[0070] The power corresponding to each initial tap coefficient can be calculated first, such as the initial tap coefficient h k The corresponding power is |h k | 2 Then, multiple target tap coefficients whose power exceeds the noise power are selected from the multiple initial tap coefficients. This method retains the effective filter taps, achieves adaptive adjustment of the filter order, shortens data transmission delay and filtering calculation time, and reduces computing power consumption.

[0071] An embodiment of the present invention provides a method for determining DFE tap coefficients. The method determines DFE tap coefficients through the following process: When the DFE is in a training phase, the FIR filter is trained in a target communication system based on the maximum number of taps in the DFE to obtain training result data. The training result data includes multiple initial tap coefficients corresponding to the maximum number of taps and first received symbol data, where the first received symbol data includes received symbols corresponding to multiple idle symbols transmitted in the target communication system under the multiple initial tap coefficients. Based on the first received symbol data, the noise power, first signal-to-noise ratio, and first autocorrelation coefficient under the multiple initial tap coefficients are calculated. Furthermore, a training completion determination result is determined based on the first signal-to-noise ratio and the first autocorrelation coefficient. When the training completion determination result is training completion, multiple target tap coefficients are selected from the multiple initial tap coefficients based on the noise power, and target taps corresponding to each target tap coefficient are determined, thereby disabling all taps in the FIR filter except the target tap. In this way, the tap coefficients of the FIR filter in the DFE are dynamically adjusted and the taps are dynamically switched on and off based on the signal-to-noise ratio and autocorrelation coefficient, thereby reducing power consumption during data transmission while ensuring stable signal reception.

[0072] After the training is completed and all taps except the target tap in the FIR filter are closed, the target communication system enters the data transmission mode. The embodiment of the present invention also provides a method for updating the DFE tap coefficients in the data transmission mode, as shown in the following steps a to d:

[0073] Step a: When the DFE is in a data transmission phase, second received symbol data is obtained; wherein the second received symbol data includes received symbols corresponding to multiple data symbols transmitted in the target communication system under multiple target tap coefficients.

[0074] The data symbol is also a NORMAL symbol, and each data symbol is composed of four sub-symbols selected from the second sub-symbol set. The second sub-symbol set includes multiple types of sub-symbols. For example, the second sub-symbol set is the set {2, 1, 0, -1, –2}, and each data symbol is composed of four sub-symbols selected from the set {2, 1, 0, -1, –2}.

[0075] Step b: Based on the second received symbol data, calculate and obtain a second signal-to-noise ratio and a second autocorrelation coefficient under multiple target tap coefficients.

[0076] The specific calculation method of the second signal-to-noise ratio and the second autocorrelation coefficient can refer to the corresponding content of the calculation of the first signal-to-noise ratio and the first autocorrelation coefficient, which will not be repeated here. It should be noted that the preset step size L0 used in calculating the second autocorrelation coefficient (for example, L0 = 100) is larger than the preset step size L used in calculating the first autocorrelation coefficient (for example, L = 10).

[0077] Step c: determining a tap coefficient update decision result based on the second signal-to-noise ratio and the second autocorrelation coefficient.

[0078] The second signal-to-noise ratio and the second autocorrelation coefficient can be compared with a preset signal-to-noise ratio threshold and a preset autocorrelation coefficient threshold, respectively, to obtain a comparison result; based on the comparison result, a tap coefficient update determination result is determined. Specifically, when the comparison result is that the second signal-to-noise ratio is less than the signal-to-noise ratio threshold, or the second autocorrelation coefficient is less than the autocorrelation coefficient threshold, the tap coefficient update determination result is determined to be to start updating; when the comparison result is that the second signal-to-noise ratio is greater than or equal to the signal-to-noise ratio threshold, and the second autocorrelation coefficient is greater than or equal to the autocorrelation coefficient threshold, the tap coefficient update determination result is determined to be not to update temporarily. The signal-to-noise ratio threshold in the data transmission phase and the signal-to-noise ratio threshold in the training phase can be the same or different; the autocorrelation coefficient threshold in the data transmission phase and the autocorrelation coefficient threshold in the training phase can be the same or different.

[0079] Step d: When the tap coefficient update determination result is to start updating, the plurality of target tap coefficients are updated.

[0080] When the tap coefficient update determination result indicates that an update is enabled, the DFE tap coefficient update mode is enabled, and the coefficient update is stopped until the first signal-to-noise ratio is greater than or equal to the signal-to-noise ratio threshold and the first autocorrelation coefficient is greater than or equal to the autocorrelation coefficient threshold, or until a preset update duration is reached. The specific update method can be referenced in related prior art and will not be further described here.

[0081] The above-mentioned DFE tap coefficient updating method adopts the DFE filter signal-to-noise ratio and channel correlation tracking method for dynamic updating, thereby reducing the power consumption of data transmission while achieving stable signal reception.

[0082] For ease of understanding, the specific process of the above-mentioned DFE tap coefficient determination method is introduced below.

[0083] 1. A DFE adaptive filter (i.e., FIR filter) based on the LMS algorithm has a maximum register of 256 (i.e., the order of the DFE adaptive filter), and the DFE tap coefficient is the coefficient h(i), where i=1, 2, 3, ..., 256.

[0084] 2. Taking 1000BASE-T as an example, when the DFE is in the training phase, the transmitter transmits the IDLE symbol {-2, 0, 2}; during the data transmission phase, the transmitter transmits the NORMAL symbol {-2, -1, 0, 1, 2}.

[0085] 3. During the DFE training phase, the signal-to-noise ratio (SNR) of the IDLE symbols {-2, 0, 2} (assuming the three symbols are transmitted with equal probability) is tracked and calculated.

[0086] 4. The received symbol for {-2, 2} is denoted as y[k] out , the received symbol of {0} is recorded as y[k] inner , assuming that the training duration of DFE is 10,000 symbol times (N=10,000, i.e., the preset training duration is the transmission duration corresponding to 10,000 quaternary symbols).

[0087] 5. Calculate signal strength: (transmitted symbols are -2 and received symbols are 2, each M), and (The number of received symbols whose transmission symbol is 0 is M), where M is the number of symbols accumulated over a certain period of time (sliding window accumulation window length M, step length L), and M<<N.

[0088] Calculate the signal autocorrelation coefficient

[0089] 6. Calculate signal power:

[0090] 7. Calculate the noise intensity: σ out [k]=y[k] out -S out and σ inner [k]=y[k] inner -S inner .

[0091] 8. Calculate the noise power:

[0092] 9. Calculate the signal-to-noise ratio: When the signal-to-noise ratio exceeds the threshold: And when the signal autocorrelation coefficient exceeds the threshold: R hh >corr th , turn off DFSE (Decision Feedback Sequence Estimation) mode and stop DFE tap coefficient training, otherwise complete the training after the preset training time.

[0093] DFSE mode is used to eliminate feedback interference and suppress noise. It requires high computational power and consumes a lot of electricity. If convergence occurs before the preset training duration (i.e., the signal-to-noise ratio exceeds the threshold and the signal autocorrelation coefficient exceeds the threshold), transmission conditions are favorable and DFSE mode can be disabled. If convergence does not occur after the preset training duration, transmission conditions are poor and DFSE mode should remain enabled.

[0094] 10. Calculate the power of each DFE tap (i.e. FIR Tap): P h (i)=|h(i)| 2 ,i=1,2,3,...,256.

[0095] 11. Close all P h (i)<σ 2 of the tap and enter data transfer mode.

[0096] 12. When DFE is working in the data transmission phase, the received symbol of {-1, 1} is recorded as y[k] mid .

[0097] 13. Calculate signal strength So we can get the signal power Noise intensity σ mid [k]=y[k] mid -S mid , noise power Autocorrelation coefficient

[0098] Among them, the signal strength S corresponding to {-2, 2} out and noise intensity σ out [k], and the signal strength S corresponding to {0} inner and noise intensity σ inner [k] can refer to the corresponding calculation method in the aforementioned training stage.

[0099] 14. Calculate the signal-to-noise ratio and autocorrelation coefficient periodically with a longer step size (L0). or , reopen the DFE tap coefficient update mode until and When the preset update time is reached, the coefficient update is stopped.

[0100] The present invention proposes an adaptive DFE tap coefficient generation and update method based on a digital DSP (Digital Signal Processing) solution. It also proposes a DFE filter signal-to-noise ratio and channel correlation tracking method. It dynamically adjusts the DFE training strategy and dynamically switches taps for different transmission channels, thereby reducing data transmission power consumption while ensuring stable signal reception.

[0101] Corresponding to the above-mentioned DFE tap coefficient determination method, an embodiment of the present invention further provides a DFE tap coefficient determination device. Figure 4 The structure diagram of a DFE tap coefficient determination device shown in FIG. 1 includes:

[0102] A training module 401 is configured to, when a decision feedback equalizer (DFE) is in a training phase, train a finite impulse response (FIR) filter in the DFE in a target communication system based on a maximum number of taps of the FIR filter to obtain training result data; wherein the training result data includes a plurality of initial tap coefficients corresponding to the maximum number of taps and first received symbol data, wherein the first received symbol data includes received symbols corresponding to a plurality of idle symbols transmitted in the target communication system under the plurality of initial tap coefficients;

[0103] A first calculation module 402 is configured to calculate, based on the first received symbol data, noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient under a plurality of initial tap coefficients;

[0104] A first determination module 403 is configured to determine a training completion determination result based on the first signal-to-noise ratio and the first autocorrelation coefficient;

[0105] Determination module 404, when the training completion determination result is training completion, screens out multiple target tap coefficients from multiple initial tap coefficients based on noise power, and determines a target tap corresponding to each target tap coefficient to close other taps in the FIR filter except the target tap.

[0106] Furthermore, each idle symbol is composed of four sub-symbols selected from a sub-symbol set, and the sub-symbol set includes multiple types of sub-symbols; the above-mentioned first calculation module 402 is specifically used to: obtain a received symbol sequence corresponding to each type of sub-symbol within a preset window length from the first received symbol data; based on the received symbol sequence corresponding to each type of sub-symbol, calculate the signal strength corresponding to each type of sub-symbol; based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, determine the noise power, the first signal-to-noise ratio and the first autocorrelation coefficient under multiple initial tap coefficients.

[0107] Furthermore, the first calculation module 402 is further configured to: calculate an initial autocorrelation coefficient of each type of sub-symbol at a preset step length based on the received symbol sequence and signal strength corresponding to each type of sub-symbol; and calculate a first autocorrelation coefficient based on the initial autocorrelation coefficients corresponding to each type of sub-symbol.

[0108] Furthermore, the first calculation module 402 is further configured to: calculate noise intensity data corresponding to each type of sub-symbol based on the received symbol sequence and signal strength corresponding to each type of sub-symbol; and calculate noise power based on the noise intensity data corresponding to each type of sub-symbol.

[0109] Furthermore, the first calculation module 402 is further configured to: calculate the signal power according to the signal strength corresponding to each sub-symbol; and calculate the first signal-to-noise ratio based on the signal power and the noise power.

[0110] Furthermore, the first determination module 403 is specifically configured to: compare the first signal-to-noise ratio and the first autocorrelation coefficient with a preset signal-to-noise ratio threshold and a preset autocorrelation coefficient threshold respectively to obtain a comparison result; and determine a training completion determination result based on the comparison result.

[0111] Furthermore, the above device also includes:

[0112] an acquisition module, configured to acquire second received symbol data when the DFE is in a data transmission phase; wherein the second received symbol data includes received symbols corresponding to a plurality of data symbols transmitted in a target communication system under a plurality of target tap coefficients;

[0113] A second calculation module is configured to calculate a second signal-to-noise ratio and a second autocorrelation coefficient under a plurality of target tap coefficients based on the second received symbol data;

[0114] A second determination module, configured to determine a tap coefficient update determination result based on a second signal-to-noise ratio and a second autocorrelation coefficient;

[0115] The updating module is used to update multiple target tap coefficients when the tap coefficient update determination result is to start updating.

[0116] The DFE tap coefficient determination device provided in this embodiment has the same implementation principle and technical effects as those of the aforementioned DFE tap coefficient determination method embodiment. For the sake of brief description, any matters not mentioned in the DFE tap coefficient determination device embodiment may be referred to the corresponding contents in the aforementioned DFE tap coefficient determination method embodiment.

[0117] like Figure 5 As shown, an embodiment of the present invention provides an electronic device 500, including: a processor 501, a memory 502 and a bus. The memory 502 stores a computer program that can be run on the processor 501. When the electronic device 500 is running, the processor 501 and the memory 502 communicate through the bus, and the processor 501 executes the computer program to implement the above-mentioned DFE tap coefficient determination method.

[0118] Specifically, the memory 502 and processor 501 can be general-purpose memories and processors, which are not specifically limited here.

[0119] An embodiment of the present invention further provides a storage medium storing a computer program that, when executed by a processor, executes the DFE tap coefficient determination method described in the preceding method embodiments. The storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), RAM, a magnetic disk, or an optical disk.

[0120] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not limiting, and thus other examples of the exemplary embodiments may have different values.

[0121] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0123] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0124] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining DFE tap coefficients, characterized in that: include: When a decision feedback equalizer (DFE) is in a training phase, the FIR filter in the DFE is trained in a target communication system based on a maximum number of taps of the FIR filter to obtain training result data; wherein the training result data includes a plurality of initial tap coefficients corresponding to the maximum number of taps and first received symbol data, wherein the first received symbol data includes received symbols corresponding to a plurality of idle symbols transmitted in the target communication system under the plurality of initial tap coefficients; Based on the first received symbol data, calculate and obtain noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient under a plurality of the initial tap coefficients; Determining a training completion result based on the first signal-to-noise ratio and the first autocorrelation coefficient; When the training completion determination result is that the training is completed, a plurality of target tap coefficients are screened out from the plurality of initial tap coefficients based on the noise power, and a target tap corresponding to each of the target tap coefficients is determined to close other taps in the FIR filter except the target tap; The DFE tap coefficient determination method further includes: When the DFE is in a data transmission phase, obtaining second received symbol data; wherein the second received symbol data includes received symbols corresponding to a plurality of data symbols transmitted in the target communication system under a plurality of the target tap coefficients; Based on the second received symbol data, calculating and obtaining a second signal-to-noise ratio and a second autocorrelation coefficient under the plurality of target tap coefficients; Determining a tap coefficient update determination result based on the second signal-to-noise ratio and the second autocorrelation coefficient; When the tap coefficient update determination result is to start updating, the plurality of target tap coefficients are updated.

2. The DFE tap coefficient determination method according to claim 1, wherein: Each of the idle symbols is composed of four sub-symbols selected from a sub-symbol set, the sub-symbol set including multiple types of sub-symbols; the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under the multiple initial tap coefficients are calculated based on the first received symbol data, including: Acquire, from the first received symbol data, a received symbol sequence corresponding to each type of the sub-symbol within a preset window length; Calculating the signal strength corresponding to each type of sub-symbol based on the received symbol sequence corresponding to each type of sub-symbol; Based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, the noise power, the first signal-to-noise ratio and the first autocorrelation coefficient under the multiple initial tap coefficients are determined.

3. The DFE tap coefficient determination method according to claim 2, wherein: The determining, based on the received symbol sequence and signal strength corresponding to each type of the sub-symbols, the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under the multiple initial tap coefficients includes: Based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, an initial autocorrelation coefficient of each type of sub-symbol at a preset step size is calculated; The first autocorrelation coefficient is calculated based on the initial autocorrelation coefficients corresponding to each type of the sub-symbols.

4. The method for determining DFE tap coefficients according to claim 2, wherein: The determining, based on the received symbol sequence and signal strength corresponding to each type of the sub-symbols, the noise power, the first signal-to-noise ratio, and the first autocorrelation coefficient under the multiple initial tap coefficients includes: Based on the received symbol sequence and signal strength corresponding to each type of sub-symbol, noise intensity data corresponding to each type of sub-symbol is calculated; The noise power is calculated based on the noise intensity data corresponding to each type of sub-symbol.

5. The DFE tap coefficient determination method according to claim 4, wherein: After calculating the noise power based on the noise intensity data corresponding to each type of sub-symbol, the DFE tap coefficient determination method further includes: Calculating the signal power according to the signal strength corresponding to each type of sub-symbol; The first signal-to-noise ratio is calculated based on the signal power and the noise power.

6. The DFE tap coefficient determination method according to claim 1, wherein: The determining a training completion result based on the first signal-to-noise ratio and the first autocorrelation coefficient includes: Comparing the first signal-to-noise ratio and the first autocorrelation coefficient with a preset signal-to-noise ratio threshold and a preset autocorrelation coefficient threshold, respectively, to obtain a comparison result; Based on the comparison result, the training completion determination result is determined.

7. A DFE tap coefficient determination device, characterized in that: include: a training module configured to, when a decision feedback equalizer (DFE) is in a training phase, train a finite impulse response (FIR) filter in the DFE in a target communication system based on a maximum number of taps of the FIR filter to obtain training result data; wherein the training result data includes a plurality of initial tap coefficients corresponding to the maximum number of taps and first received symbol data, wherein the first received symbol data includes received symbols corresponding to a plurality of idle symbols transmitted in the target communication system under the plurality of initial tap coefficients; A first calculation module is configured to calculate, based on the first received symbol data, noise power, a first signal-to-noise ratio, and a first autocorrelation coefficient under a plurality of the initial tap coefficients; A first determination module is configured to determine a training completion determination result based on the first signal-to-noise ratio and the first autocorrelation coefficient; a determination module, which, when the training completion determination result is that the training is completed, screens out a plurality of target tap coefficients from the plurality of initial tap coefficients based on the noise power, and determines a target tap corresponding to each of the target tap coefficients, so as to close other taps in the FIR filter except the target tap; The DFE tap coefficient determination device further includes: an acquisition module, configured to acquire second received symbol data when the DFE is in a data transmission phase; wherein the second received symbol data includes received symbols corresponding to a plurality of data symbols transmitted in the target communication system under a plurality of the target tap coefficients; A second calculation module is configured to calculate, based on the second received symbol data, a second signal-to-noise ratio and a second autocorrelation coefficient under the plurality of target tap coefficients; A second determination module, configured to determine a tap coefficient update determination result based on the second signal-to-noise ratio and the second autocorrelation coefficient; An updating module is configured to update the plurality of target tap coefficients when the tap coefficient update determination result is to start updating.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the DFE tap coefficient determination method according to any one of claims 1 to 6 is implemented.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the DFE tap coefficient determination method according to any one of claims 1 to 6 is executed.

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