CN116401493A - Self-adaptive filtering method suitable for medium-voltage carrier system - Google Patents
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Abstract
The invention belongs to the technical field of power line communication, and particularly discloses a self-adaptive filtering method suitable for a medium-voltage carrier system, which comprises the following steps: according to the computing capacity of the FPGA, the decision system can store the number of sampling points; the FPGA stores a signal containing a plurality of consecutive sampling points as an input signal (background noise); the objective function of the adaptive filter is given, and the filter coefficient is solved by the form of the bias derivative and the inverse matrix based on the input signal. The invention takes the form of storing single-phase noise floor in advance as input signals, and eliminates the requirement of the self-adaptive filter on two paths of signals. In the scene of medium-voltage carrier power line communication, which is similar to the scene of only one path of signal, the method is completely effective. By carrying out iterative parameter calculation on single-phase background noise stored in advance, the next frame or even several frames of data can be effectively filtered, and the signal-to-noise ratio of a link is improved. The invention has low requirement on storage time, namely low requirement on the computing capacity of the chip, and has wide applicability.
Description
Technical Field
The invention belongs to the technical field of power line communication, and particularly relates to a self-adaptive filtering method suitable for a medium-voltage carrier system.
Background
In a common filtering occasion, filtering is performed from the angle of a frequency domain, and a filter meeting the requirement can be conveniently designed only by giving corresponding design indexes. However, in the more general case, the filter operating environment required by people is time-varying, which results in a reduced performance of the filter already designed in advance and even cannot be used, such as a weak and unstable useful signal buried in strong background noise, and adaptive noise cancellation techniques are required to propose a signal in non-stationary and time-varying background noise.
The core of the adaptive noise cancellation technique is an adaptive filter, and the adaptive algorithm controls its parameters to achieve optimal filtering. Different adaptive filtering algorithms have different convergence rates, steady state misadjustments, and algorithm complexity. The adaptive algorithm can be divided into an open-loop algorithm and a closed-loop algorithm depending on whether it is related to the filter output. The adaptive noise cancellation technique utilizes output feedback, belonging to a closed-loop algorithm. This has the advantage of maintaining an optimum output when the filter input changes, and also compensates to some extent for errors in the change of the filter element parameters and operational errors, which have disadvantages of stability problems and convergence speed.
In addition, the adaptive filtering requires processing at least two signals simultaneously, one of which is a phase line containing the signals and noise, and the other of which contains only noise (or has extremely small signal information amplitude). For a medium-voltage carrier system, the three-phase power line has strong coupling phenomenon and can be approximately regarded as only one signal. This presents a significant challenge for adaptive filtering.
Disclosure of Invention
In order to solve the defects or drawbacks of the prior art, the invention provides an adaptive filtering method suitable for a medium voltage carrier system. The invention removes the forced requirement of self-adaptive filtering on two paths of signals, adopts a single-phase noise extraction mode to filter, and finally improves the signal-to-noise ratio of the link.
The technical scheme of the invention is as follows:
an adaptive filtering method suitable for a medium voltage carrier system, comprising the following steps:
s1: calculating the number of sampling points which can be stored by an FPGA computing system, and calculating the number q of sampling points which can be borne by the FPGA within a specified time according to the FPGA computing force;
s2: after the carrier sends the message, the state is changed into a receiving state, and an FPGA in the carrier stores and receives a background noise signal containing continuous q sampling points as an input signal x (n); before the carrier receives a new signal, the FPGA stores one sampling point every time, the first sampling point in the original q sampling points is removed, namely, only the latest q sampling points are always stored in the FGPA;
s3: collecting a current carrier receiving signal as a desired signal d (n); the desired signal d (n) is a superposition of noise and useful signal, where the noise in d (n) has a correlation with x (n) in S2. x (n) is used for canceling noise in d (n) after passing through the adaptive filter, so as to obtain a difference e (n) between a desired signal and an output signal of the model filter;
s4: at a given instant k, the signal vector of input S2 is
Obtaining an objective function xi based on the filter coefficient d (k)；
S5: partial derivative conversion of filter coefficient w (k) of objective function as deterministic correlation matrix R of input signal D (k) And a deterministic cross-correlation vector P between the input signal and the desired signal D (k) Is the product form of (a);
s6: solving R by matrix inversion theory D (k) Replacing complex inverse operation with multiplication and division operation;
s7: solving for P D (k) Calculating w (k), and calculating the objective function xi again d (k)；
S8: in view of the different lengths of the messages of different services, the performance of the filter is further enhanced by fine tuning q.
The beneficial effects of the invention are as follows: in the form of storing single-phase noise floor in advance as an input signal, the requirement of an adaptive filter on two paths of signals is eliminated. The performance is degraded compared to the adaptive filter calculated in real time. But is fully effective in a scenario like medium voltage carrier power line communication where there is only one signal. By carrying out iterative parameter calculation on single-phase background noise stored in advance, the next frame or even several frames of data can be effectively filtered, and the signal-to-noise ratio of a link is improved. The invention has low requirement on storage time, namely low requirement on the computing capacity of the chip, and has wide applicability.
Drawings
Fig. 1 is a diagram of a method for eliminating noise by an adaptive filtering method suitable for a medium voltage carrier system according to an embodiment of the present invention.
Fig. 2 is a flowchart of an adaptive filtering method suitable for a medium voltage carrier system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 2, the specific flow of this embodiment is as follows:
s1: and calculating the number of the sampling points which can be stored by the system according to the FPGA. And calculating the number q of sampling points which can be carried by the FPGA in a specified time according to the calculation force of the FPGA.
The amount of computation required for each sample point is analyzed as follows: s is S D Computational requirements 4*n 2 +n multiplications, (3 n-2) n additions; p (P) D The computation requires 2n multiplications and n additions. The calculation of w (k) requires n 2 Multiplication and (n-1) addition.
S2: after the carrier sends the message, the state is changed into a receiving state, and the FPGA stores the background noise signals containing continuous q sampling points as input signals x (n). The storage time is
Second, where Q is the sampling rate, in MHZ. The storage time must be greater than the difference between the end of a message sent by the carrier and the time of a message received by the carrier. To ensure that the stored signal is noise free of carrier signals; if the carrier machine does not detect the carrier signal, the FPGA stores the signals of q sampling points newly, the latest storage is reserved, and the previous storage is deleted;
s3: the carrier currently receives the signal as the desired signal d (n), where the noise in d (n) has a correlation with x (n) in S2. As shown in fig. 1, after x (n) passes through the adaptive filter, the x (n) is used for canceling noise in d (n) to obtain a difference e (n) between a desired signal and an output signal of the model filter;
s4: at a given instant k, the signal vector input to step S2
Where N is the number of filters. The filter coefficient is w j (k) J=0, 1,2, …, N, w is adjusted by adaptation j (k) To achieve a minimization of the objective function (sum of squares of the difference e (n) between the desired signal and the model filter output signal). The objective function is defined as:
where d (i) is a desired signal at i, ε (i) =e (n) is a posterior output error at i, λ is an exponential weighting factor, also called forgetting factor, and the larger the value, the smaller the contribution of old data to coefficient update.
S5: solving an objective function
Is to be->
Deterministic correlation matrix for conversion into an input signal>
And a deterministic cross-correlation vector between the input signal and the desired signal +.>
Is a product of the two.
To calculate xi d (k) For the minimum value of w (k), the partial derivative of w (k) is calculated, and the partial derivative is set to 0, and the formula is as follows:
the following relationship is obtained:
s6: obtaining a deterministic correlation matrix by using matrix inversion quotients
The inverse matrix formula of (2) is:
from the above equation, complex matrix inversion operations are replaced with common multiply-divide calculations, whereas serial systems are well suited for such iterative calculations.
S7: from solutions
Re-calculating w (k) in S5, and obtaining an objective function xi in S4 according to the re-calculated w (k) d (k) Wherein->
S8: in view of the different lengths of the messages of different services, the performance of the filter is further enhanced by fine tuning q.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and a person skilled in the art may still make modifications and equivalents to the specific embodiments of the present invention with reference to the above embodiments, and any modifications and equivalents not departing from the spirit and scope of the present invention are within the scope of the claims of the present invention as filed herewith.
Claims (7)
1. The self-adaptive filtering method suitable for the medium-voltage carrier system is characterized by comprising the following steps of:
s1: calculating the number of sampling points which can be stored by an FPGA computing system, and calculating the number q of sampling points which can be borne by the FPGA within a specified time according to the FPGA computing force;
s2: after the carrier sends the message, the state is changed into a receiving state, and an FPGA in the carrier stores and receives a background noise signal containing continuous q sampling points as an input signal x (n); before the carrier receives a new signal, the FPGA stores one sampling point every time, the first sampling point in the original q sampling points is removed, namely, only the latest q sampling points are always stored in the FGPA;
s3: collecting a carrier receiving signal as a desired signal d (n); the desired signal d (n) is a superposition of noise and useful signal, where the noise in d (n) has a correlation with x (n) in S2; x (n) is used for canceling noise in d (n) after passing through the adaptive filter, so as to obtain a difference e (n) between a desired signal and an output signal of the model filter;
s4: at a given instant k, the signal vector of input S2 is
Obtaining an objective function xi based on the filter coefficient d (k)；
S5: solving a filter coefficient for an objective function
Is used as a deterministic correlation matrix of the input signal +.>
And a deterministic cross-correlation vector between the input signal and the desired signal +.>
Is the product form of (a);
s6: solving by matrix inversion theory
Replacing complex inverse operation with multiplication and division operation;
s7: solving for
Calculating w (k), and calculating the objective function xi again d (k)；
S8: in view of the different lengths of the messages of different services, the performance of the filter is further enhanced by fine tuning q.
2. An adaptive filtering method for a medium voltage carrier system according to claim 1, wherein the calculation amount required for each sampling point in step S1 is analyzed as follows: s is S D Calculation requires 4×n2+n multiplications, (3 n-2) n additions; p (P) D 2n multiplications and n additions are needed for calculation; the computation of w (k) requires n2 multiplications and (n-1) additions.
3. The adaptive filtering method for medium voltage carrier system according to claim 1, wherein after the step S2 carrier sends a message, the step S2 carrier is switched to a receiving state, the FPGA stores a signal x containing q consecutive sampling points as an input signal, and the storage time is
Second, where Q is the sampling rate, units MHZ; the storage time must be greater than the time difference between the end of the message sending by the carrier and the message receiving by the carrier, so as to ensure that the stored signal is the background noise without carrier signal; if the carrier machine does not detect the carrier signal, the FPGA stores the signals of q sampling points newly, then the latest storage is reserved, and the previous storage is deleted.
4. An adaptive filtering method for medium voltage carrier systems according to claim 1, characterized in that said step S4, at a given instant k, inputs an input boostPreviously stored signal vector of q sampling points
Wherein N is the number of filters; the filter coefficient is w j (k) J=0, 1,2, …, N, w is adjusted by adaptation j (k) To achieve a minimization of an objective function (sum of squares of the difference e (n) between the desired signal and the model filter output signal), the objective function being defined as:
where d (i) is a desired signal at i, ε (i) =e (n) is a posterior output error at i, λ is an exponential weighting factor, also called forgetting factor, and the larger the value, the smaller the contribution of old data to coefficient update.
5. The adaptive filtering method for medium voltage carrier system according to claim 1, wherein said step S5 finds an objective function
Is to be->
Deterministic correlation matrix for conversion into an input signal>
And a deterministic cross-correlation vector between the input signal and the desired signal +.>
Is the product form of (a);
to calculate xi d (k) For the minimum value of w (k), the partial derivative of w (k) is calculated, and the partial derivative is set to 0, and the formula is as follows:
the following relationship is obtained:
6. the adaptive filtering method for medium voltage carrier system according to claim 1, wherein said step S6 obtains a deterministic correlation matrix using matrix inversion arguments
The inverse matrix formula of (2) is:
7. an adaptive filtering method for a medium voltage carrier system according to claim 1, wherein in step S7
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| CN117014260B (en) * | 2023-10-07 | 2024-01-02 | 芯迈微半导体(上海)有限公司 | Loading method and loading device for channel estimation filter coefficient |
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