CN102098258A - Method for removing narrow-band interference and self-adapting filter - Google Patents

Abstract

The embodiment of the present invention relates to the field of signal processing, in particular to a method for removing narrow-band interference and an adaptive filter, which are used to solve the problem in the prior art that removing interference through a fixed-coefficient filter will introduce processing delay and poor real-time performance The problem. The method in the embodiment of the present invention includes: the adaptive filter determines the weight value corresponding to the current sampling moment; the adaptive filter determines the cancellation signal corresponding to the current sampling moment according to the determined weight value and the reference signal sampled at the current sampling moment , wherein the reference signal is generated according to the center frequency of the narrowband interference; the adaptive filter filters the baseband signal sampled at the current sampling moment according to the determined canceling signal corresponding to the current sampling moment, and obtains after removing the narrowband interference baseband signal. By adopting the embodiment of the present invention, the processing delay can be reduced, the real-time performance can be improved, and the effect of interference cancellation can be improved.

Description

A Method and Adaptive Filter for Removing Narrowband Interference

technical field

The invention relates to the field of signal processing, in particular to a method for removing narrowband interference and an adaptive filter.

Background technique

Orthogonal Frequency Division Multiplexing (OFDM) technology is a multi-carrier digital modulation technology and a frequency multiplexing technology. Compared with other modulation techniques and multiplexing techniques, OFDM technology has efficient spectrum utilization efficiency and good anti-multipath interference ability, so it has been widely used in broadcast audio and video fields, as well as military and civilian communication systems. The main applications of OFDM technology include: High-speed Digital Subscriber Line (HDSL), Asymmetric Digital Subscriber Line (ADSL), ETSI (European Telecommunications Standards Institute, European Telecommunications Standards Institute) ) standard digital audio broadcasting (Digital Audio Broadcasting, DAB), digital video broadcasting (Digital Video Broadcasting, DVB), high definition television (High DefinitionTelevision, HDTV), wireless metropolitan area network (WMAN), wireless local area network (WLAN), etc. Especially in the field of wireless metropolitan area network and wireless local area network, the 802.16 series and 802.11 series standards with OFDM technology as the main physical layer technology have been widely used.

OFDM technology uses a large number of orthogonal sub-carriers to carry information that needs to be transmitted. Therefore, OFDM systems are extremely vulnerable to adverse effects of narrowband interference. The narrow-band interference here includes narrow-band interference in the usual sense, and also includes single-frequency interference. Because after the FFT (Fast Fourier Transform) transformation in the OFDM system, the spectrum of the single-frequency signal is no longer a line spectrum but a narrow-band spectrum occupying a certain bandwidth. When the narrowband interference persists, it will cause long-term interference to the system and seriously affect the performance of the OFDM system. However, when the narrowband interference overlaps with the pilot subcarriers used for channel estimation on the spectrum, this adverse effect will be diffused through channel estimation errors, making the performance of the entire system worse.

The current method for interference cancellation is to cancel narrowband interference by constructing a fixed coefficient filter with complex coefficients. However, when constructing the filter coefficients, it is required to know the center frequency of the narrowband interference or its high-precision estimation value, otherwise a satisfactory interference cancellation effect cannot be obtained. The main disadvantage of the filter with fixed coefficients is that the coefficients cannot be adjusted in real time according to environmental changes, so its performance cannot meet the time-varying environmental requirements; and when constructing the coefficients of certain fixed-coefficient filters, prior knowledge about the statistical characteristics of the signal is required Knowledge, these prior knowledge are often unpredictable, or need to be estimated in real time, especially the center frequency of interference, it is impossible to get its true value or a very high-precision estimated value. Therefore, removing interference through a fixed coefficient filter will introduce processing delay, and the real-time performance is relatively poor.

To sum up, at present, removing interference through a fixed coefficient filter will introduce processing delay, and the real-time performance is relatively poor.

Contents of the invention

Embodiments of the present invention provide a method for removing narrowband interference and an adaptive filter to solve the problem in the prior art that removing interference through a fixed-coefficient filter introduces processing delay and poor real-time performance.

A method for removing narrowband interference provided by an embodiment of the present invention includes:

The adaptive filter determines the weight corresponding to the current sampling moment;

The adaptive filter determines the cancellation signal corresponding to the current sampling time according to the determined weight and the reference signal sampled at the current sampling time, wherein the reference signal is generated according to the center frequency of the narrowband interference;

The adaptive filter filters the baseband signal sampled at the current sampling moment according to the determined cancellation signal corresponding to the current sampling moment, to obtain the baseband signal after the narrowband interference is removed.

An adaptive filter provided by an embodiment of the present invention includes:

A weight determination module, configured to determine the weight corresponding to the current sampling moment;

The signal determination module is used to determine the corresponding cancellation signal at the current sampling time according to the determined weight and the reference signal sampled at the current sampling time, wherein the reference signal is generated according to the center frequency of the narrowband interference;

The filtering module is configured to filter the baseband signal sampled at the current sampling moment according to the determined canceling signal corresponding to the current sampling moment, so as to obtain the baseband signal after the narrowband interference is removed.

According to the weight value corresponding to the current sampling moment and the reference signal sampled at the current sampling moment, the adaptive filter in the embodiment of the present invention determines the cancellation signal corresponding to the current sampling moment, and according to the determined cancellation signal corresponding to the current sampling moment, the The baseband signal sampled at the sampling time is filtered to obtain the baseband signal after the narrowband interference is removed.

Since the embodiment of the present invention removes narrow-band interference through an adaptive filter, the processing delay is reduced and real-time performance is improved, and the adaptive filter can be used to adjust the weight in real time to meet the time-varying environmental requirements and improve the interference cancellation effect.

Furthermore, the implementation of the embodiment of the present invention is simple, the complexity is low, and the response speed is fast, which is more suitable for the OFDM system.

Description of drawings

FIG. 1 is a schematic structural diagram of an adaptive filter according to an embodiment of the present invention;

FIG. 2 is a schematic flowchart of a method for removing narrowband interference according to an embodiment of the present invention;

3A is a schematic diagram of the principle of filtering using a Notch (notch) filter according to an embodiment of the present invention;

FIG. 3B is a schematic diagram of a processing principle of a Notch filter according to an embodiment of the present invention.

Detailed ways

According to the weight value corresponding to the current sampling moment and the reference signal sampled at the current sampling moment, the adaptive filter in the embodiment of the present invention determines the cancellation signal corresponding to the current sampling moment, and according to the determined cancellation signal corresponding to the current sampling moment, the The baseband signal sampled at the sampling time is filtered to obtain the baseband signal after the narrowband interference is removed. Since the embodiment of the present invention removes narrow-band interference through an adaptive filter, the processing delay is reduced and real-time performance is improved, and the adaptive filter can be used to adjust the weight in real time to meet the time-varying environmental requirements and improve the interference cancellation effect.

Wherein, the reference signal is generated according to the center frequency of the narrowband interference.

Specifically, detect and determine whether there is narrow-band interference, estimate the center frequency of narrow-band interference when there is narrow-band interference, and obtain the estimated value f _r of the narrow-band interference center frequency, which will be used as the center of the adaptive filter reference signal frequency.

In a specific implementation process, the presence or absence of narrowband interference may be detected and determined by a narrowband interference detector, and the center frequency of the narrowband interference may be estimated to obtain an estimated value of the center frequency of the narrowband interference.

It should be noted that the embodiment of the present invention is not limited to the narrowband interference detector, and other methods that can detect and determine the presence or absence of narrowband interference, and estimate the center frequency of narrowband interference to obtain the estimated value of the narrowband interference center frequency are applicable Embodiment of the present invention.

Wherein, the reference signal can be generated according to the center frequency of the narrowband interference.

For example, if two reference signals are needed, two orthogonal single-frequency reference signals _rs and r _c can be generated according to formula 1 and formula 2, which are sine reference signals and cosine reference signals with f _r as the center frequency respectively:

r _s (k)＝Csin(2πf _r k)...Formula 1;

r _c (k)=Ccos(2πf _r k)..........Formula 2.

Among them, _rs (k) represents the sine reference signal sampled at the kth sampling moment; r _c (k) represents the cosine reference signal sampled at the kth sampling moment; C is the amplitude of the reference signal, which can be set as required .

Since the reference signal is a single-frequency signal, it can only store the sampling value in one cycle, and call it cyclically during filtering to save memory resources; if the center frequency of narrow-band interference is slowly time-varying, the sampling value of the reference signal can be calculated by looking up the table .

It should be noted that the embodiment of the present invention is not limited to the above-mentioned method of generating the reference signal using Formula 1 and Formula 2, and other methods that can generate the reference signal according to the center frequency of the narrowband interference are applicable to the embodiment of the present invention.

In the specific implementation process, a reasonable filter bandwidth of the adaptive filter can be obtained by setting the parameters of the adaptive filter, and the adaptive filter can automatically adjust the center frequency of its own filter frequency band, that is, it can track the center frequency of narrow-band interference, Therefore, it is not necessary to know the exact value of the central frequency of the narrow-band interference, but only an approximate value with certain precision.

Wherein, the embodiment of the present invention can be applied to an OFDM system, and can also be applied to a system in which information to be transmitted is carried by a large number of orthogonal subcarriers.

The embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

As shown in FIG. 1 , the adaptive filter according to the embodiment of the present invention includes: a weight determination module 10 , a signal determination module 20 and a filtering module 30 .

The weight determination module 10 is configured to determine the weight corresponding to the current sampling moment.

The signal determination module 20 is configured to determine the corresponding cancellation signal at the current sampling time according to the weight determined by the weight determination module 10 and the reference signal sampled at the current sampling time, wherein the reference signal is generated according to the center frequency of the narrowband interference.

The filtering module 30 is configured to filter the baseband signal sampled at the current sampling moment according to the cancellation signal corresponding to the current sampling moment determined by the signal determining module 20 to obtain the baseband signal after narrowband interference is removed.

Wherein, the weight determination module 10 determines the weight corresponding to the current sampling time according to the weight corresponding to the previous sampling time, the baseband signal after removing the narrowband interference at the previous sampling time, and the reference signal sampled at the previous sampling time.

The specific weight determination module 10 may determine the weight corresponding to the current sampling moment by adopting an adaptive algorithm. There are many kinds of adaptive algorithms, such as Least Mean Square (LMS) algorithm, Recursive Least Squares (RLS) algorithm, normalized LMS algorithm, variable step size LMS algorithm, etc.

The following uses the minimum mean square error algorithm as an example for illustration. Other algorithms are similar to the minimum mean square error algorithm, but the algorithm is different, and will not be repeated here.

If the weight value determination module 10 adopts the minimum mean square error algorithm, it can determine the weight value corresponding to the current sampling moment according to formula three:

$w\left(k\right)=w(k-1)+\mathrm{\μ}[\widehat{\mathrm{the\; y}}(k-1)+\widehat{\mathrm{no}}(k-1)]r(k-1)$ ..........Formula three.

是上一个采样时刻除去窄带干扰后的基带信号中的有用信号，是上一个采样时刻除去窄带干扰后的基带信号中除有用信号外的其他信号(比如噪声干扰等)，

和

构成了上一个采样时刻除去窄带干扰后的基带信号；r(k-1)是在上一个采样时刻采样的参考信号。Among them, w(k) is the weight corresponding to the current sampling moment; w(k-1) is the weight corresponding to the previous sampling moment; μ is the iterative calculation step of the adaptive algorithm;

is the useful signal in the baseband signal after removing the narrowband interference at the last sampling moment, It is the signal other than the useful signal (such as noise interference, etc.) in the baseband signal after removing the narrowband interference at the last sampling moment,

and

It constitutes the baseband signal after removing the narrowband interference at the last sampling moment; r(k-1) is the reference signal sampled at the last sampling moment.

If the current sampling moment is the first sampling moment, the weight corresponding to the last sampling moment is the preset weight, and the baseband signal after removing the narrowband interference at the last sampling moment and the reference signal sampled at the last sampling moment are both is 0.

Among them, the number of weights required by different adaptive filters is also different. Taking the Notch filter as an example, two weights are required, and the weights include the first weight and the second weight; correspondingly, the reference signal includes A first reference signal and a second reference signal.

The weight determination module 10 needs to determine the first weight value corresponding to the current sampling time according to the first weight value corresponding to the previous sampling time, the baseband signal after removing the narrowband interference at the last sampling time, and the first reference signal sampled at the last sampling time. Weight, and according to the second weight corresponding to the last sampling moment, the baseband signal after removing the narrowband interference at the last sampling moment, and the second reference signal sampled at the last sampling moment, determine the second weight corresponding to the current sampling moment .

Taking the minimum mean square error algorithm as an example, formula 4 and formula 5 can be derived according to formula 3, the weight determination module 10 determines the first weight according to formula 4, and determines the second weight according to formula 5:

$w_{\mathrm{the\; s}}\left(k\right)=w_{\mathrm{the\; s}}(k-1)+\mathrm{\μ}[\widehat{\mathrm{the\; y}}(k-1)+\widehat{\mathrm{no}}(k-1)]r_{\mathrm{the\; s}}(k-1)$ .....Formula 4;

是上一个采样时刻除去窄带干扰后的基带信号中的有用信号，

是上一个采样时刻除去窄带干扰后的基带信号中处有用信号外的其他信号(比如噪声干扰等)，

和

构成了上一个采样时刻除去窄带干扰后的基带信号；r_s(k-1)是在上一个采样时刻采样的第一参考信号。Among them, w _s (k) is the first weight corresponding to the current sampling moment; w _s (k-1) is the first weight corresponding to the previous sampling moment; μ is the iterative calculation step size of the adaptive algorithm;

is the useful signal in the baseband signal after removing the narrowband interference at the last sampling moment,

It is the signal other than the useful signal (such as noise interference, etc.) in the baseband signal after removing the narrowband interference at the last sampling moment,

and

constitutes the baseband signal after removing the narrowband interference at the last sampling moment; r _s (k-1) is the first reference signal sampled at the last sampling moment.

$w_c\left(k\right)=w_c(k-1)+\mathrm{\μ}[\widehat{\mathrm{the\; y}}(k-1)+\widehat{\mathrm{no}}(k-1)]r_c(k-1)$ ......... Formula five;

是上一个采样时刻除去窄带干扰后的基带信号中的有用信号，

是上一个采样时刻除去窄带干扰后的基带信号中处有用信号外的其他信号(比如噪声干扰等)，

和

构成了上一个采样时刻除去窄带干扰后的基带信号；r_c(k-1)是在上一个采样时刻采样的第二参考信号。Among them, w _c (k) is the first weight value corresponding to the current sampling moment; w _c (k-1) is the second weight value corresponding to the previous sampling moment; μ is the iterative calculation step size of the adaptive algorithm;

is the useful signal in the baseband signal after removing the narrowband interference at the last sampling moment,

It is the signal other than the useful signal (such as noise interference, etc.) in the baseband signal after removing the narrowband interference at the last sampling moment,

and

constitutes the baseband signal after the narrowband interference has been removed at the last sampling moment; r _c (k-1) is the second reference signal sampled at the last sampling moment.

It should be noted that if the first weight value is determined according to the first reference signal, the first weight value corresponding to the subsequent sampling time must be based on the first reference signal; correspondingly, if the second weight value is determined according to the first reference signal If the signal is determined, the second weights corresponding to subsequent sampling moments must be based on the second reference signal.

For example, the first reference signal is a sine reference signal, and the second reference signal is a cosine reference signal. If the first weight corresponding to the first sampling moment is determined according to the sine reference signal, and the second weight corresponding to the first sampling moment is determined according to the cosine reference signal, then the first weight corresponding to the subsequent sampling moment must Determined according to the sine reference signal, the second weight corresponding to the subsequent sampling moment must be determined according to the cosine reference signal.

For the signal determination module 20, the offset signal corresponding to the current sampling moment can be determined according to formula six:

${\widehat{\mathrm{no}}}_I\left(k\right)=w\left(k\right)r\left(k\right)$ ..........Formula 6;

是抵消信号；w(k)是当前采样时刻对应的权值；r(k)是在当前采样时刻采样的参考信号。in,

is the offset signal; w(k) is the weight corresponding to the current sampling moment; r(k) is the reference signal sampled at the current sampling moment.

If the adaptive filter of the embodiment of the present invention needs two weights, the signal determination module 20 multiplies the determined first weight corresponding to the current sampling time with the first reference signal sampled at the current sampling time to obtain the current sampling time The corresponding first processed signal is multiplied by the determined second weight value corresponding to the current sampling time and the second reference signal sampled at the current sampling time to obtain the second processed signal corresponding to the current sampling time, and the first processed signal and the second The two processed signals are added to obtain the cancellation signal corresponding to the current sampling moment.

Specifically, formula 7 can be derived according to formula 6, and the signal determination module 20 can obtain the offset signal corresponding to the current sampling moment according to formula 7:

${\widehat{\mathrm{no}}}_I\left(k\right)=w_{\mathrm{the\; s}}\left(k\right)r_{\mathrm{the\; s}}\left(k\right)+w_c\left(k\right)r_c\left(k\right)$ ..........Formula VII;

是当前采样时刻对应的抵消信号；w_s(k)是当前采样时刻对应的第一权值；r_s(k)是在当前采样时刻采样的第一参考信号；w_s(k)r_s(k)是当前采样时刻对应的第一处理信号；w_c(k)是当前采样时刻对应的第二权值；r_c(k)是在当前采样时刻采样的第二参考信号；w_c(k)r_c(k)是当前采样时刻对应的第二处理信号。in,

is the offset signal corresponding to the current sampling moment; w _s (k) is the first weight corresponding to the current sampling moment; _rs (k) is the first reference signal sampled at the current sampling moment; w _s (k) _rs ( k) is the first processed signal corresponding to the current sampling moment; w _c (k) is the second weight value corresponding to the current sampling moment; r _c (k) is the second reference signal sampled at the current sampling moment; w _c (k ) _rc (k) is the second processed signal corresponding to the current sampling moment.

Wherein, the filtering module 30 may subtract the baseband signal sampled at the current sampling moment from the determined cancellation signal corresponding to the current sampling moment, and the obtained signal is the baseband signal after narrowband interference is removed.

Specifically, the signal obtained by the filtering module 30 according to Formula 8 is the baseband signal after the narrowband interference is removed:

$\widehat{\mathrm{the\; y}}\left(k\right)+\widehat{\mathrm{no}}\left(k\right)=\mathrm{the\; s}\left(k\right)-{\widehat{\mathrm{no}}}_I\left(k\right)$ .........Formula eight;

是当前采样时刻除去窄带干扰后的基带信号中的有用信号，

是当前采样时刻除去窄带干扰后的基带信号中除有用信号外的其他信号，

构成了当前采样时刻除去窄带干扰后的基带信号；s(k)是在当前采样时刻采样的基带信号；

是当前采样时刻确定的当前采样时刻对应的抵消信号。in,

is the useful signal in the baseband signal after removing the narrowband interference at the current sampling moment,

It is the signal other than the useful signal in the baseband signal after removing the narrowband interference at the current sampling time,

Constitute the baseband signal after the narrowband interference is removed at the current sampling moment; s(k) is the baseband signal sampled at the current sampling moment;

is the cancellation signal corresponding to the current sampling time determined by the current sampling time.

As shown in Figure 2, the method for removing narrowband interference in the embodiment of the present invention includes the following steps:

Step 201, the adaptive filter determines the weight corresponding to the current sampling moment.

Step 202, the adaptive filter determines the corresponding cancellation signal at the current sampling time according to the determined weight and the reference signal sampled at the current sampling time, wherein the reference signal is generated according to the center frequency of the narrowband interference.

Step 203 , the adaptive filter filters the baseband signal sampled at the current sampling moment according to the determined cancellation signal corresponding to the current sampling moment, to obtain the baseband signal after narrowband interference is removed.

In step 201, the adaptive filter determines the weight corresponding to the current sampling time according to the weight corresponding to the previous sampling time, the baseband signal after removing the narrowband interference at the previous sampling time, and the reference signal sampled at the previous sampling time.

A specific adaptive filter may use a self-response algorithm to determine the weight corresponding to the current sampling moment. There are many kinds of adaptive algorithms, such as minimum mean square error algorithm, recursive least squares algorithm, normalized LMS algorithm, variable step size LMS algorithm, etc.

The following uses the minimum mean square error algorithm as an example for illustration. Other algorithms are similar to the minimum mean square error algorithm, but the algorithm is different, and will not be repeated here.

If the adaptive filter adopts the minimum mean square error algorithm, the weight corresponding to the current sampling moment can be determined according to formula three.

If the current sampling moment is the first sampling moment, the weight corresponding to the last sampling moment is the preset weight, and the baseband signal after removing the narrowband interference at the last sampling moment and the reference signal sampled at the last sampling moment are both is 0.

Among them, the number of weights required by different adaptive filters is also different. Taking the Notch filter as an example, two weights are required, and the weights include the first weight and the second weight; correspondingly, the reference signal includes A first reference signal and a second reference signal.

In step 201, the adaptive filter needs to determine the weight corresponding to the current sampling time according to the first weight value corresponding to the previous sampling time, the baseband signal after removing narrowband interference at the previous sampling time, and the first reference signal sampled at the previous sampling time. , and according to the second weight value corresponding to the last sampling moment, the baseband signal after removing the narrowband interference at the last sampling moment, and the second reference signal sampled at the last sampling moment, determine the first weight corresponding to the current sampling moment Two weights.

Taking the minimum mean square error algorithm as an example, formula 4 and formula 5 can be derived according to formula 3. The adaptive filter determines the first weight value according to formula 4, and determines the second weight value according to formula 5.

It should be noted that if the first weight value is determined according to the first reference signal, the first weight value corresponding to the subsequent sampling time must be based on the first reference signal; correspondingly, if the second weight value is determined according to the first reference signal If the signal is determined, the second weights corresponding to subsequent sampling moments must be based on the second reference signal.

For example, the first reference signal is a sine reference signal, and the second reference signal is a cosine reference signal. If the first weight corresponding to the first sampling moment is determined according to the sine reference signal, and the second weight corresponding to the first sampling moment is determined according to the cosine reference signal, then the first weight corresponding to the subsequent sampling moment must Determined according to the sine reference signal, the second weight corresponding to the subsequent sampling moment must be determined according to the cosine reference signal.

In step 202, for the adaptive filter, the cancellation signal corresponding to the current sampling moment can be determined according to Formula 6.

If the adaptive filter of the embodiment of the present invention needs two weights, then in step 202, the adaptive filter multiplies the determined first weight corresponding to the current sampling moment by the first reference signal sampled at the current sampling moment, Obtain the first processed signal corresponding to the current sampling moment, multiply the determined second weight value corresponding to the current sampling moment by the second reference signal sampled at the current sampling moment, obtain the second processed signal corresponding to the current sampling moment, and multiply the first The processed signal is added to the second processed signal to obtain a cancellation signal corresponding to the current sampling moment.

Specifically, Formula 7 can be derived according to Formula 6, and the adaptive filter can obtain the cancellation signal corresponding to the current sampling moment according to Formula 7.

In step 203, the adaptive filter may subtract the baseband signal sampled at the current sampling moment from the determined cancellation signal corresponding to the current sampling moment, and the obtained signal is the baseband signal after narrowband interference is removed.

Specifically, the signal obtained by the adaptive filter according to Formula 8 is the baseband signal after narrowband interference is removed.

The adaptive filter in this embodiment of the present invention may be a Notch filter, such as a notch filter, a notch filter, etc., or other adaptive filters. In the following, description will be made by taking the adaptive filter of the embodiment of the present invention as a Notch filter as an example.

As shown in FIG. 3A, in the schematic diagram of the principle of filtering using the Notch filter in the embodiment of the present invention:

First, the narrowband interference detector detects and judges whether there is narrowband interference, and estimates the center frequency of the narrowband interference when there is narrowband interference, and obtains an estimated value f _r of the narrowband interference center frequency.

Then, a sine reference signal _rs and a cosine reference signal _rc are generated according to the center frequency of the narrowband interference.

和抵消信号

Finally, the Notch filter filters the input baseband signal (s=y+n+n _I ) according to the sine reference signal _rs and cosine reference signal _rc to obtain the baseband signal after narrowband interference is removed

and offset signal

As shown in Figure 3B, in the schematic diagram of the processing principle of the Notch filter of the embodiment of the present invention, there are three signals, one of which is a baseband signal s, including a useful signal y, a narrowband interference signal n ₁ and other interference signals n; the other is a sinusoidal signal Reference signal r _s ; the last path is cosine reference signal r _c .

Among them, the sine reference signal r _s and the cosine reference signal r _c are stored in the Notch filter, such as storing the sampling value in one cycle, then the Notch filter will receive a signal, that is, the baseband signal S; it can also be combined with the baseband signal s Similar to sending the sine reference signal _rs and the cosine reference signal _rc to the Notch filter, the Notch filter will receive three signals, namely the baseband signal S, the sine reference signal _rs and the cosine reference signal _rc .

The Notch filter determines the first processed signal corresponding to the current sampling time according to the sinusoidal reference signal r _s (k) sampled at the current sampling time and the first weight w _s (k) corresponding to the current sampling time

The Notch filter determines the second processed signal corresponding to the current sampling time according to the cosine reference signal r _c (k) sampled at the current sampling time and the second weight w _c (k) corresponding to the current sampling time

和当前采样时刻对应的第二处理信号

得到当前采样时刻对应的抵消信号

Notch filter according to the first processing signal corresponding to the current sampling moment

The second processed signal corresponding to the current sampling moment

Get the offset signal corresponding to the current sampling moment

对在当前采样时刻采样的基带信号s(k)进行滤波，得到当前采样时刻对应的除去窄带干扰后的基带信号

The Notch filter cancels the signal according to the current sampling moment

Filter the baseband signal s(k) sampled at the current sampling moment to obtain the baseband signal corresponding to the current sampling moment after removing narrowband interference

以及窄带干扰信号的估计波形

After a period of convergence, the two weights of the Notch filter will converge close to the optimal linear filter weights under the minimum mean square error criterion (assuming that the minimum mean square error algorithm is used), then the result is to offset the narrowband Output signal after interference

and the estimated waveform of the narrowband interfering signal

将是y+n最小均方误差估计，而

将是n_I最小均方误差估计。

可以直接用下一步处理，例如信道估计、解调、译码等等，

可以用于对原始信号的校准和修正等。After the adaptive convergence process ends,

will be the y+n minimum mean square error estimate, while

will be the n _I minimum mean square error estimate.

It can be processed directly in the next step, such as channel estimation, demodulation, decoding, etc.,

It can be used for calibration and correction of the original signal, etc.

The adaptive filtering in the embodiment of the present invention can be realized by using various hardware devices, not only general-purpose processors, single-chip microcomputers and dedicated digital signal processors, but also programmable logic devices and the like.

It can be seen from the above embodiments that the adaptive filter in the embodiment of the present invention determines the weight corresponding to the current sampling moment; the adaptive filter determines the weight corresponding to the current sampling moment according to the determined weight and the reference signal sampled at the current sampling moment. Cancellation signal, wherein the reference signal is generated according to the center frequency of the narrowband interference; the adaptive filter filters the baseband signal sampled at the current sampling moment according to the determined cancellation signal corresponding to the current sampling moment, and obtains the baseband signal after removing the narrowband interference Signal.

The embodiment of the present invention fully utilizes the cyclic prefix time as the convergence time of the adaptive filter.

Since the embodiment of the present invention removes narrow-band interference through an adaptive filter, the processing delay is reduced and real-time performance is improved, and the adaptive filter can be used to adjust the weight in real time to meet the time-varying environmental requirements and improve the interference cancellation effect.

Furthermore, the implementation of the embodiment of the present invention is simple, the complexity is low, and the response speed is fast, which is more suitable for the OFDM system.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and equivalent technologies thereof, the present invention also intends to include these modifications and variations.

Claims (10)

1. A method for removing narrowband interference, characterized in that the method comprises: The adaptive filter determines the weight corresponding to the current sampling moment; The adaptive filter determines the cancellation signal corresponding to the current sampling time according to the determined weight and the reference signal sampled at the current sampling time, wherein the reference signal is generated according to the center frequency of the narrowband interference; The adaptive filter filters the baseband signal sampled at the current sampling moment according to the determined cancellation signal corresponding to the current sampling moment, to obtain the baseband signal after the narrowband interference is removed. 2. The method according to claim 1, wherein the adaptive filter determines the weight corresponding to the current sampling point comprising: The adaptive filter determines the weight corresponding to the current sampling time according to the weight corresponding to the previous sampling time, the baseband signal after removing the narrowband interference at the previous sampling time, and the reference signal sampled at the previous sampling time. 3. The method according to claim 2, wherein the weight comprises a first weight and a second weight, and the reference signal comprises a first reference signal and a second reference signal; The adaptive filter determining the weight corresponding to the current sampling point includes: The adaptive filter determines the first weight corresponding to the current sampling time according to the first weight value corresponding to the previous sampling time, the baseband signal after removing narrowband interference at the previous sampling time, and the first reference signal sampled at the previous sampling time. Weight; The adaptive filter determines the second weight corresponding to the current sampling time according to the second weight value corresponding to the previous sampling time, the baseband signal after removing the narrowband interference at the previous sampling time, and the second reference signal sampled at the previous sampling time. weight. 4. The method according to claim 3, wherein the adaptive filter determines the corresponding cancellation signal at the current sampling moment comprising: The adaptive filter multiplies the determined first weight corresponding to the current sampling moment by the first reference signal sampled at the current sampling moment to obtain a first processed signal corresponding to the current sampling moment; The adaptive filter multiplies the determined second weight corresponding to the current sampling moment by the second reference signal sampled at the current sampling moment to obtain a second processed signal corresponding to the current sampling moment; The adaptive filter adds the first processed signal and the second processed signal to obtain a cancellation signal corresponding to the current sampling moment. 5. The method according to any one of claims 1 to 4, wherein the adaptive filter filtering the baseband signal sampled at the current sampling moment comprises: The adaptive filter subtracts the baseband signal sampled at the current sampling moment from the determined cancellation signal corresponding to the current sampling moment, and the obtained signal is the baseband signal after narrowband interference is removed. 6. An adaptive filter, characterized in that the adaptive filter comprises: A weight determination module, configured to determine the weight corresponding to the current sampling moment; The signal determination module is used to determine the corresponding cancellation signal at the current sampling time according to the determined weight and the reference signal sampled at the current sampling time, wherein the reference signal is generated according to the center frequency of the narrowband interference; The filtering module is configured to filter the baseband signal sampled at the current sampling moment according to the determined canceling signal corresponding to the current sampling moment, so as to obtain the baseband signal after the narrowband interference is removed. 7. adaptive filter as claimed in claim 6, is characterized in that, described weight determination module is used for: The weight corresponding to the current sampling time is determined according to the weight corresponding to the previous sampling time, the baseband signal after removing the narrowband interference at the previous sampling time, and the reference signal sampled at the previous sampling time. 8. adaptive filter as claimed in claim 7, is characterized in that, described weight determination module is used for: When the weight includes the first weight and the second weight, and the reference signal includes the first reference signal and the second reference signal, the narrowband is removed according to the first weight corresponding to the last sampling moment and the last sampling moment Based on the interfered baseband signal and the first reference signal sampled at the last sampling moment, determine the first weight corresponding to the current sampling moment, and remove the narrowband interference based on the second weight corresponding to the last sampling moment and the last sampling moment The baseband signal and the second reference signal sampled at the last sampling time are used to determine the second weight corresponding to the current sampling time. 9. adaptive filter as claimed in claim 8, is characterized in that, described signal determination module is used for: Multiplying the determined first weight corresponding to the current sampling moment with the first reference signal sampled at the current sampling moment to obtain the first processed signal corresponding to the current sampling moment, and multiplying the determined second weight corresponding to the current sampling moment with the current The second reference signal sampled at the sampling time is multiplied to obtain a second processed signal corresponding to the current sampling time, and the first processed signal and the second processed signal are added to obtain a cancellation signal corresponding to the current sampling time. 10. The adaptive filter according to any one of claims 6 to 9, wherein the filtering module is used for: The baseband signal sampled at the current sampling moment is subtracted from the determined cancellation signal corresponding to the current sampling moment, and the obtained signal is the baseband signal after the narrowband interference is removed.

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