CN111585690B - Multi-system same-frequency interference cancellation method - Google Patents
Multi-system same-frequency interference cancellation method Download PDFInfo
- Publication number
- CN111585690B CN111585690B CN202010352437.7A CN202010352437A CN111585690B CN 111585690 B CN111585690 B CN 111585690B CN 202010352437 A CN202010352437 A CN 202010352437A CN 111585690 B CN111585690 B CN 111585690B
- Authority
- CN
- China
- Prior art keywords
- interference
- signal
- window
- signals
- frequency
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
- H04K3/00—Jamming of communication; Counter-measures
- H04K3/80—Jamming or countermeasure characterized by its function
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
- H04K3/00—Jamming of communication; Counter-measures
- H04K3/20—Countermeasures against jamming
- H04K3/22—Countermeasures against jamming including jamming detection and monitoring
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
- H04K3/00—Jamming of communication; Counter-measures
- H04K3/80—Jamming or countermeasure characterized by its function
- H04K3/82—Jamming or countermeasure characterized by its function related to preventing surveillance, interception or detection
- H04K3/827—Jamming or countermeasure characterized by its function related to preventing surveillance, interception or detection using characteristics of target signal or of transmission, e.g. using direct sequence spread spectrum or fast frequency hopping
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Noise Elimination (AREA)
Abstract
The invention discloses a multi-system same frequency interference cancellation method, which comprises the following steps: detecting whether an interference signal exists or not, adapting to both continuous signals and burst signals, detecting the interference by adopting a sliding double-window method, judging whether the interference exists or not, and recording the initial position and the end position of the interference under the condition of the interference; initially estimating interference parameters, wherein the parameters comprise time delay, frequency offset and amplitude phase of channel transmission, and completing alignment of two paths of signals and correction of frequency offset by using the estimated parameters; and taking the result of the amplitude-phase estimation as an initial value of the adaptive filter, and adopting a polymorphic LMS tracking loop algorithm to realize the interference cancellation. The invention supports various interferences with different styles, including various modulation signals, single tone, noise frequency modulation and the like, and can be applied to various interference scenes; and the method has universality for different interference patterns.
Description
Technical Field
The invention belongs to the technical field of military communication anti-interference and communication countermeasure, and particularly relates to a multi-system same-frequency interference cancellation method.
Background
In the prior art, the field of military communication anti-interference and communication countermeasure solves the problem of eliminating common-frequency intentional or unintentional interference when own party communicates. The problem of co-frequency interference widely exists in communication, such as the problem of coupling interference of transmitted signals in a co-frequency full duplex communication system, the problem of mutual interference among multiple transceivers in the same communication platform, the problem of eliminating interference signals transmitted by the own party in communication countermeasure, and the like, research organizations and various companies at home and abroad conduct extensive research on the problem, and some patents also exist in the field at present.
For example, the chinese patent discloses a system and method for canceling simultaneous same-frequency self-interference of large transmission power in a multipath environment. The patent mainly processes interference at a radio frequency end, adopts a two-stage interference cancellation method, and obtains an original signal by subtracting an output radio frequency signal and an interference reconstruction signal. The method is mainly suitable for a simultaneous same-frequency system, and the interference pattern is only limited to a continuous signal waveform and is not suitable for counteracting the burst interference.
For example, the chinese patent discloses a method, an apparatus and a system for canceling co-channel interference. The method is mainly applied to the field of microwave communication, and is mainly used for offsetting an interference signal formed by a local transmitting terminal to a local receiving terminal, acquiring the local transmitting signal through a coupler, enabling a coupling signal to pass through an analog interference channel composed of an attenuator, an amplifier, a phase shifter, a time delay line and the like, adjusting the phase to be an odd multiple of 180 degrees different from the interference signal, and then outputting the odd multiple to the receiving terminal through the coupler, thereby realizing the offset of the interference signal. The key point of the method lies in the design of an analog interference channel, which is not suitable for the interference cancellation of digital signals and is also not suitable for the cancellation of burst interference.
That is, the existing interference cancellation method is only suitable for interference cancellation of continuous signals, and for different interference patterns, especially for a sudden interference scenario, the existing method cannot be applied, and has certain limitations in application scenarios.
Therefore, a multi-system co-channel interference cancellation method is urgently needed to be researched.
Disclosure of Invention
The invention aims to provide a multi-system same-frequency interference cancellation method, which is used for solving one of the technical problems in the prior art, such as: the existing interference cancellation method is only suitable for interference cancellation of continuous signals, and for different interference patterns, especially for a scene of burst interference, the existing technical method cannot be suitable, and has certain limitation in an application scene. The invention aims to provide a multi-system same-frequency interference cancellation method, which can effectively cancel interference in different forms such as continuous interference, burst interference and the like and interference in different forms such as modulation signals, single tone interference, noise frequency modulation interference and the like. The method is high in practicability, tests are conducted under different practical interference backgrounds, and interference can be effectively eliminated. The key points of the method comprise: 1. the method for multi-state self-adaptive interference cancellation is provided, and has universality for different interference patterns; 2. the frequency tracking problem under the condition of large frequency offset of an actual signal is solved by adopting differential correlation and phase-locked loop tracking technologies; 3. an efficient detection technology is added for the burst interference, the work of the self-adaptive filter is guided through a detection result, and the canceller does not work when the interference does not exist, so that the rapid convergence of the burst interference cancellation is ensured; 4. the synchronization and channel parameter fitting technology aiming at the burst interference is provided, and the high-precision initial estimation of the burst interference parameters is realized.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a multi-system same-frequency interference cancellation method comprises the following steps:
s1: an interference detection step, namely detecting whether an interference signal exists or not, adapting to both continuous signals and burst signals, detecting the interference by adopting a sliding double-window method, judging whether the interference exists or not, and recording the initial position and the end position of the interference under the condition of the interference;
s2: a parameter initial estimation step, in which after the interference is detected in step S1, initial estimation is performed on interference parameters, the parameters include time delay, frequency offset and amplitude phase of channel transmission, and the estimated parameters are used to complete alignment of two paths of signals and correction of frequency offset;
s3: and a multi-state adaptive interference cancellation step, namely, on the basis of the step S2, the result of the amplitude-phase estimation is used as an initial value of the adaptive filter, and the multi-state LMS tracking loop algorithm is adopted to realize the interference cancellation.
Further, the specific content of the detection of the interference by the sliding dual-window method in step S1 is as follows:
adopting sliding double-window method burst detection, starting or stopping the self-adaptive canceller under the guidance of a detection result, and enabling the canceller to work only in the time period when interference occurs, and outputting directly without interference;
the sliding double-window method detects the start and stop of a signal by comparing the signal energy in two adjacent time windows; that is, two adjacent windows with a length of L are assumed and are respectively referred to as windows a and B; when two windows slide on the received signal, the energy falling into the two windows is EAAnd EB：
S 'in the above formula'1Representing a signal sample point sequence, n is a related starting point, and k represents a sample point index in a related window;
during detection, the window A and the window B start to slide; when both windows contain only noise energy, EAAnd EBAre constant, their ratio m is also constant, i.e. m equals 1; the two windows continue to slide, the burst signal gradually enters the window B, the energy of the window B is gradually increased, the window A only contains noise at the moment, and the energy ratio of the two windows is gradually increased; when the window B just contains all burst signals, the window A still only contains all noise energy, the ratio m of the two windows reaches the maximum, and the window B corresponds to the starting moment of the burst signals; then, the window A also gradually contains burst signals, and the energy ratio m of the two windows gradually falls back to 1; when window B contains noise energy, m continues to decrease; when the window B just contains noise, the window A contains burst signals, and the ratio m of the two windows reaches the minimum, the end time of the corresponding burst signals is reached.
Further, in step S2, the specific content of the initial estimation of the time delay is as follows:
the method used for initial estimation of the delay is differential correlation, i.e.,
respectively differentiating the reference interference and the aliasing signal to obtain
dr(n)＝r(n)conj(r(n-τ))；
In the above formula, drAs a result of the difference in the interfering signals,
n is a sampling point index, r is an interference signal s'1For aliasing signals, tau is a difference interval, and the over-sampling multiple of the interference signal is taken for re-correlation to obtain
In the above formula, E represents the average value,
the peak value obtained by correlation, m is the position of correlation calculation, and N is the data volume of correlation calculation; - τmax≤m≤τmax，τmaxDetermining the maximum delay deviation which can be tolerated by the canceller for the size of the time window of the correlation search;
performing sliding correlation on the aliasing signal and the reference signal in a set time window, searching the maximum value of a correlation peak, and recording the position to obtain the relative time delay of the aliasing signal and the reference signal; because the reference signal is a local input and the aliasing signal is a signal transmitted through a physical channel, the accurate channel delay can be obtained through the relative delay.
Further, the specific content of the initial estimation of the frequency difference is as follows:
establishing a signal receiving model
Wherein
The time delay of the previously estimated integer sample point; if the target signal and the noise in r (n) are ignored, y (n) is a single-frequency signal, and the frequency of the single-frequency signal is the frequency difference of the interference signals of the two channels; frequency difference estimation is realized through FFT; that is to say that the first and second electrodes,
z(n)＝abs(FFT(y(n)，L))
z(k)＝max(z(n))
in the above formula, z (n) is the amplitude obtained after FFT calculation, L is the length of FFT calculation, and when n is k, the peak z of the spectrum is obtainedk(ii) a Only the frequency corresponding to the peak value needs to be calculated, namely the frequency difference; using the peak and points on the left and rightCarrying out parabolic fitting; variables a and b are set respectively, and the values are calculated by the following formulas
Obtaining the distance tau between k and the fitted peak value as-b/2 a, and calculating a final frequency offset value on the basis of the distance tau;
in the above formula, FsIs the sampling rate of the signal.
Further, the details of the initial estimation of the amplitude and phase are as follows:
correlating the two signals to obtain
In the above formula, m is the relevant position; taking the maximum value of the correlation peak, wherein the correlation value is the amplitude-phase difference between the two paths of signals;
computing
Carrying out parabolic fitting on the three correlation values;
and obtaining the estimation of the time delay of the fractional sampling point.
Further, the specific content of implementing interference cancellation by using the polymorphic LMS tracking loop algorithm is as follows:
waiting for a link; that is, when no interference is detected, the filter does not operate;
counteracting a link; that is, the first interference is detected, the filter coefficient is initialized, the operation is started, and the coefficient is updated iteratively;
keeping a link; that is, after the interference disappears, the filter coefficient is kept and the next interference is waited for; after the interference occurs, counting the offset state again, and updating the coefficient in an iterative manner;
resetting; that is, if there is no interference for a long time, the timeout condition is reached, i.e., the filter coefficient is reset, and the standby state is entered again.
Further, after the initial estimation of the frequency difference is completed, a step of calculating a frequency difference estimation error is also performed, which specifically includes:
introducing a phase-locked loop, wherein a structure of a second-order phase-locked loop, namely a closed-loop structure of a phase discriminator, a loop filter and a voltage-controlled oscillator, is adopted, and two inputs of the phase discriminator are respectively a main channel received signal and reconstruction interference; setting the output phase of the voltage-controlled oscillator at n time to
Then the interference is reconstructed as
The phase error output by the phase detector can then be simply obtained by correlation of the received waveforms of the main and auxiliary channels, as follows:
in the above formula, r (n) is an interference signal, m represents the position of the correlation, and l is the size of the time window selected when the correlation is performed.
Compared with the prior art, the invention has the beneficial effects that:
1. the method supports various types of interference, including various modulation signals, single tone, noise frequency modulation and the like, and can be applied to various interference scenes; universal for different interference patterns;
2. the method is specially optimized for the burst interference, can quickly capture the burst interference, accurately estimate the interference parameters and solve the problem of quick convergence of the burst interference cancellation;
3. interference capture is carried out by adopting a waveform correlation method, so that the method can adapt to a wider range of interference-to-signal ratio;
4. the method adopts a differential correlation technology, and overcomes the problem of interference capture under the condition of large frequency offset;
5. a phase-locked loop is introduced into the self-adaptive offset loop, so that the problem of phase tracking during long-time operation is solved, and offset loss is reduced.
Drawings
FIG. 1 is a schematic workflow diagram of an embodiment of the present invention.
Fig. 2 is a schematic diagram of a burst detection process by a double window method according to an embodiment of the present invention.
Fig. 3 is a diagram of a frequency offset parabolic fit in accordance with an embodiment of the present invention.
FIG. 4 is a schematic diagram of a magnitude and phase estimation parabolic fit according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of the basic principle of adaptive interference cancellation according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of an adaptive FIR filter structure according to an embodiment of the present invention.
FIG. 7 is a state transition diagram according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of a second order pll according to an embodiment of the present invention.
Fig. 9 is a schematic diagram of an interference signal cancellation test according to an embodiment of the present invention.
Fig. 10 is a schematic diagram of an interference cancellation device corresponding to a multi-system co-channel interference cancellation method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to fig. 1 to 10 of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
a multi-system same-frequency interference cancellation method comprises the following steps:
s1: an interference detection step, namely detecting whether an interference signal exists or not, adapting to both continuous signals and burst signals, detecting the interference by adopting a sliding double-window method, judging whether the interference exists or not, and recording the initial position and the end position of the interference under the condition of the interference;
s2: a parameter initial estimation step, in which after the interference is detected in step S1, initial estimation is performed on interference parameters, the parameters include time delay, frequency offset and amplitude phase of channel transmission, and the estimated parameters are used to complete alignment of two paths of signals and correction of frequency offset;
s3: and a multi-state adaptive interference cancellation step, namely, on the basis of the step S2, the result of the amplitude-phase estimation is used as an initial value of the adaptive filter, and the multi-state LMS tracking loop algorithm is adopted to realize the interference cancellation.
The interference detection step is used for detecting whether the interference signal exists or not, and is adaptive to both continuous signals and burst signals. The module adopts a sliding double-window method to detect interference, judges whether the interference exists or not, and records the initial position and the end position of the interference under the condition of the interference.
The initial parameter estimation step performs initial estimation on interference parameters, including channel time delay, frequency offset, amplitude, phase and the like, completes alignment of two paths of signals and correction of the frequency offset by using the estimated parameters, and uses the amplitude and phase estimation values as initial coefficients of an LMS filter to ensure that a subsequent cancellation loop enters lock.
And the multi-state adaptive interference cancellation step adopts a multi-state LMS tracking loop algorithm to realize interference cancellation, and the result of amplitude and phase estimation is used as the initial value of the adaptive filter. In order to overcome the error of frequency estimation, a phase tracking module is added in the processing algorithm.
The work flow is as shown in figure 1:
after the equipment is started, firstly completing the configuration of each module parameter, and starting operation;
detecting interference signals in real time, recording interference positions when the interference signals are detected, and starting the next processing;
finishing the estimation of various parameters, including channel transmission delay, frequency offset, amplitude, phase and the like, finishing the alignment of two paths of signals and the correction of the frequency offset by using the detected parameters, taking the amplitude and phase estimation values as the coefficients of an LMS filter, and entering a cancellation processing link;
and reconstructing the interference component in the aliasing signal by using the estimated values of the amplitude and the phase, and subtracting the aliasing signal and the reconstructed interference signal to obtain the original user signal. And calculating the power of the two paths of signals in real time to obtain an interference-signal ratio, and outputting the interference-signal ratio and the cancelled signals at the same time.
The various components of the system are described in detail below.
And an interference detection step:
in the interference cancellation process, a process is required for convergence of the filter coefficients. For continuous interference, the adaptive filter coefficients will continue to track stably after this convergence process. However, in the burst interference disappearance period, the filter coefficients converge to all 0 directions, and when the next burst comes, the filter coefficients converge to the optimal solution direction again. A periodic burst will therefore cause the filter to converge repeatedly between the optimal solution and 0, and in particular the convergence period after the burst starts is not negligible with respect to the burst duration, which will cause a reduction in cancellation performance.
Aiming at the problem, double-window method burst detection is introduced, the self-adaptive canceller is started or stopped under the guidance of a detection result, the canceller works only in the period when interference occurs, and the output is directly conducted without the interference, so that data confusion caused by idle running of the canceller in the period when the interference disappears is avoided.
The double window method can accurately detect the start and stop of the signal by comparing the signal energy in two adjacent time windows. Two adjacent windows of length L are designed, referred to as windows a and B, respectively. When two windows slide on the received signal, the energy falling into the two windows is EAAnd EB：
S 'in the above formula'1Representing a sequence of signal samples, n being the start of the correlation, k representing the index of the samples within the correlation window.
Upon detection, window a and window B begin to slide. When both windows contain only noise energy, EAAnd EBAre constant (proportional to the noise power) and their ratio m (equal to about 1) is also constant. The two windows continue to slide, the burst signal gradually enters the window B, the energy of the window B is gradually increased, the window A only contains noise at the moment, and the energy ratio of the two windows is gradually increased. When the window B exactly contains all burst signals, the window a still only contains all noise energy, and the ratio m of the two windows reaches the maximum (equal to the signal-to-noise ratio), the starting time of the corresponding burst signal is at this time. Thereafter, the window a also gradually contains the burst signal, and the energy ratio m of the two windows gradually falls back to 1. When window B contains noise energy, m continues to decrease. When the window B just contains noise and the window A contains burst signals, the ratio m of the two windows reaches the minimum (equal to the reciprocal of the signal-to-noise ratio)This corresponds to the end time of the burst signal. The whole process is shown in fig. 2.
A parameter estimation step:
the parameter estimation comprises three modules of time delay estimation, frequency offset estimation and amplitude and phase estimation. Considering that the channel delay and frequency offset change are small in one-time communication process, the delay estimation and frequency offset estimation only need to be carried out at the initial moment, and tracking is carried out through an LMS filter in the cancellation process. For continuous interference, the amplitude and phase estimation only needs to be carried out at the initial moment, but for burst interference, the amplitude and phase estimation must be carried out burst by burst. Meanwhile, in order to ensure the cancellation of the short-time burst interference, the LMS filter must be converged quickly, which requires that the results of the frequency difference estimation and the amplitude and phase estimation must be very accurate, and the initial coefficient of the LMS filter is determined according to the results of the frequency difference estimation and the amplitude and phase estimation.
And (3) time delay estimation:
the purpose of the time delay estimation is to align the reference signal and the aliasing signal, and the adopted method is differential correlation, so that larger frequency offset can be tolerated.
Respectively differentiating the reference interference and the aliasing signal to obtain
dr(n)＝r(n)conj(r(n-τ))
In the above formula, drAs a result of the difference in the interfering signals,
n is a sampling point index, r is an interference signal s'1For aliasing signals, tau is a difference interval, and oversampling multiples of interference signals are taken to reduce the correlation between data and reduce crosstalk influence. Re-correlating to obtain
In the above formula, E represents the average value,
the peak value obtained by correlation, m is the position of correlation calculation, and N is the data volume of correlation calculation; - τmax≤m≤τmax，τmaxThe maximum delay skew that the canceller can tolerate is determined for the size of the correlation search time window.
And performing sliding correlation on the aliasing signal and the reference signal in a set time window, searching the maximum value of a correlation peak, and recording the position to obtain the relative time delay of the aliasing signal and the reference signal. Because the reference signal is a local input and the aliasing signal is a signal transmitted through a physical channel, the accurate channel delay can be obtained through the relative delay.
And (3) frequency difference fitting estimation:
the frequency difference and amplitude-phase initial estimation is one of the important links for realizing the whole interference cancellation, and the initial estimation precision of the two-dimensional parameters influences whether a subsequent loop can be correctly locked or not. Wherein, the initial estimated value of the frequency difference is used for removing the frequency difference between the two paths of signals; the initial estimate of the amplitude phase is used for initialization of the loop filter coefficients. Considering the application of the burst interference cancellation, the method adopts a parabolic fitting algorithm to improve the accuracy of initial value estimation and shorten the convergence time of an interference canceller, which is particularly important for the burst interference cancellation.
Establishing a signal receiving model:
wherein
Is the previously estimated integer sample time delay. It is obvious that if r (n) is ignored for the target signal and the noise, y (n) is a single frequency signal, which is the frequency difference between the two channel interference signals. Therefore, the frequency difference estimation can be achieved by the FFT.
z(n)＝abs(FFT(y(n)，L))
z(k)＝max(z(n))
In the above formula, z (n) is the amplitude obtained after FFT calculation, L is the length of FFT calculation, and when n is k, the peak z of the spectrum is obtainedk. At this time, only the frequency corresponding to the peak value needs to be calculated, i.e. the frequency difference. In order to obtain a frequency difference value as accurate as possible, parabolic fitting is performed by using the peak value and points on the left side and the right side. Variables a and b are set respectively, and the values are calculated by the following formulas
The distance tau between k and the peak value is obtained as-b/2 a, and the final frequency deviation value is calculated on a sub-basis
In the above formula, FsIs the sampling rate of the signal.
The parabolic fit is shown in figure 3 below.
And (3) amplitude-phase fitting estimation:
the result of the amplitude and phase estimation is used for initialization of the filter tap coefficients to shorten the convergence time of the adaptive interference canceller, which is particularly important for bursty interference cancellation.
Correlating the two signals to obtain
In the above formula, m is the relevant position. And taking the maximum value of the correlation peak, wherein the correlation value is the amplitude-phase difference between the two paths of signals.
Computing
Three correlation values, and then parabolic fitting
And obtaining the estimation of the time delay of the fractional sampling point. The principle of parabolic fitting is shown in fig. 4 below.
Multi-state adaptive interference cancellation:
fig. 5 is a basic schematic diagram of a multi-state LMS cancellation loop, where r is s1+s2+n0Mixing the signals for the main channel, where s1As interfering signal components, s2Is a target signal, n0Being noise, the secondary channel clean interference signal s'1As a reference signal. Adaptive filter generation of approximation s1Output of (2)
This output is subtracted from the received signal to produce the system output.
The adaptive filter in the present system employs an FIR direct type structure as shown in fig. 6 below.
Since the adaptive cancellation utilizes the correlation of interference signal components between the main and auxiliary channels, no analysis processing is required for the interference signals. For burst and continuous different interference patterns and complex and diversified interference signal specifications, as long as the receiving condition of a single interference source of a secondary channel can be met, the undifferentiated processing of co-channel interference suppression can be realized. The characteristic not only avoids the link of interference signal analysis and processing, but also enables the algorithm and the equipment to have universal applicability to interference patterns, and even if the intentional interference of unknown formats set by some enemies is faced, the method can be used for processing.
Compared with the traditional LMS cancellation structure, the polymorphic LMS cancellation loop structure adopted in the scheme introduces a control mechanism of interference detection in order to adapt to the short-time burst interference signal, and the coefficient of the adaptive filter is guided to be updated through a detection result. The cancellation loop has the following states:
in a waiting state, when the interference is not detected, the filter does not work;
a cancellation state, wherein a first interference is detected, a filter coefficient is initialized, operation is started, and the coefficient is updated in an iterative manner;
and keeping the state, keeping the filter coefficient after the interference disappears, and waiting for the arrival of the next interference. After the interference occurs, counting the offset state again, and updating the coefficient in an iterative manner;
and resetting the state, if no interference exists for a long time, resetting the filter coefficient and entering the waiting state again.
The state transition diagram is shown in FIG. 7 as follows:
since there will always be an error in the frequency offset estimation, in order to overcome the influence of the error on the cancellation, the system introduces a phase-locked loop technology, and adopts a structure of a second-order phase-locked loop, as shown in fig. 8 below. The phase detector mainly comprises a phase detector, a loop filter and a voltage-controlled oscillator.
In interference cancellation, the design of the phase detector is very critical. Since the phase difference between the reconstructed interference and the real interference is to be reflected, it is obvious that the two inputs of the phase discriminator should be the main channel received signal and the reconstructed interference, respectively. Setting the output phase of the voltage-controlled oscillator at n time to
Then the interference is reconstructed as
The phase error output by the phase detector can be simply obtained by the correlation operation of the received waveforms of the main channel and the auxiliary channel
In the above formula, r (n) is an interference signal, m represents the position of the correlation, and l is the size of the time window selected when the correlation is performed. In order to reduce the design difficulty of the loop filter, the value of L can be increased, so that the jitter of the phase error is reduced. On the other hand, however, increasing L also means increasing complexity and processing delay, so in practice a compromise is made to choose a reasonable value.
Firstly, on the basis of the scheme, a cancellation test for continuous interference signals is carried out, as shown in fig. 9;
the test steps are as follows:
1. connecting equipment according to the test block diagram, and starting testing;
2. setting the output frequency of a signal channel to be 950MHz, the output level to be-30 dB, the modulation mode to be QPSK, the modulation rate to be 20kBd and the C/N value to be 10 dB; the output frequency of the interference channel is 950MHz, the output level is-20 dB, no noise exists, the modulation mode is QPSK, and the modulation rate is consistent with the source signal.
3. Inputting corresponding frequency value, gain, bandwidth and the like on equipment software according to the frequency value and level value of the output of the source signal, the interference signal and the counteracting signal set in the step 2), and selecting a 'hardware real-time' mode in an equipment processing mode menu;
4. starting processing, adjusting the signal level to reach the specified value, setting the parameters of the demodulator, checking the Eb/N0 value displayed by the demodulator, and filling the detection result into the test table;
5. turning off interference, starting processing, checking the Eb/N0 value displayed by the demodulator, and filling the detection result into a test table;
6. subtracting the Eb/N0 value under the condition of no interference from the Eb/N0 value under the condition of interference, and filling the subtraction result into the offset loss of the test table;
7. and (5) modifying the modulation mode and the modulation rate of the signal and the interference according to the test record table, repeating the steps 1-6, and recording the test data.
Test records (as in the following table):
secondly, carrying out a cancellation test on the burst interference signal, as shown in fig. 9;
the test steps are as follows:
1. connecting equipment according to the test block diagram, and starting testing;
2. setting the output frequency of a signal channel to be 950MHz, the output level to be-30 dB, the modulation mode to be QPSK, the modulation rate to be 20kBd and the C/N value to be 10 dB; the output frequency of the interference channel is 950MHz, a burst interference signal file is selected, the output level is set to be-20 dB, no noise exists, and the modulation rate is consistent with the source signal.
3. Inputting corresponding frequency value, gain, bandwidth and the like on equipment software according to the frequency value and level value of the output of the source signal, the interference signal and the counteracting signal set in the step 2), and selecting a 'hardware real-time' mode in an equipment processing mode menu;
4. starting processing, adjusting the signal level to reach the specified value, setting the parameters of the demodulator, checking the Eb/N0 value displayed by the demodulator, and filling the detection result into the test table;
5. turning off interference, starting processing, checking the Eb/N0 value displayed by the demodulator, and filling the detection result into a test table;
6. subtracting the Eb/N0 value under the condition of no interference from the Eb/N0 value under the condition of interference, and filling the subtraction result into the offset loss of the test table;
7. and (5) modifying the modulation mode and the modulation rate of the signal and the interference according to the test record table, repeating the steps 1-6, and recording the test data.
Test records (as in the following table):
thirdly, carrying out a cancellation test under the condition of large frequency offset, as shown in fig. 9;
the test steps are as follows:
1. and connecting the equipment according to the test block diagram, and starting the test.
2. Setting the output frequency of a signal channel to be 950MHz and the output level to be-20 dB, wherein the modulation modes are BPSK respectively, the modulation rate is 2MBd, and the C/N value is 10 dB; the output frequency of the interference channel is 950MHz, the output level is-20 dB, no noise exists, the modulation mode is BPSK, and the modulation rate is consistent with the source signal.
3. Inputting corresponding intermediate frequency value, gain, bandwidth and the like on equipment software according to the frequency value and level value of the source signal (frequency offset setting), interference signal and counteracting signal output, modulation rate and other parameters set in 2), and selecting a 'hardware real-time' mode in an equipment processing mode menu;
4. starting processing, demodulating the cancellation output by using demodulation equipment, recording the error rate, and filling the detection result into a test form;
5. the interference is closed, the 'processing' is started, the modulation bandwidth, the modulation mode, the interference-to-signal ratio and the bit error rate of the input signal of the equipment are detected on the demodulation equipment, and the detection result is filled in a test table;
6. inquiring a corresponding Eb/N0 value in a tool BERTOOLS of MATLAB according to the error code rate value in the test table, and filling the Eb/N0 value into the test table; subtracting the Eb/N0 value under the condition of no interference from the Eb/N0 value under the condition of interference, and filling the subtraction result into the offset loss of the test table;
7. and (4) according to the test record table, setting a signal channel frequency point through a software interface to change the frequency offset of the mixed signal, and repeating the steps 1-5.
Test records (as in the following table):
the above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.
Claims (3)
1. A multi-system same-frequency interference cancellation method is characterized by comprising the following steps:
s1: an interference detection step, namely detecting whether an interference signal exists or not, adapting to both continuous signals and burst signals, detecting the interference by adopting a sliding double-window method, judging whether the interference exists or not, and recording the initial position and the end position of the interference under the condition of the interference;
s2: a parameter initial estimation step, in which after the interference is detected in step S1, initial estimation is performed on interference parameters, the parameters include time delay, frequency offset and amplitude phase of channel transmission, and the estimated parameters are used to complete alignment of two paths of signals and correction of frequency offset;
s3: a multi-state adaptive interference cancellation step, namely on the basis of the step S2, taking the result of amplitude-phase estimation as an initial value of the adaptive filter, and adopting a multi-state LMS tracking loop algorithm to realize interference cancellation;
the specific content of the interference detection by the sliding dual-window method in step S1 is as follows:
adopting sliding double-window method burst detection, starting or stopping the self-adaptive canceller under the guidance of a detection result, and enabling the canceller to work only in the time period when interference occurs, and outputting directly without interference;
the sliding double-window method detects the start and stop of a signal by comparing the signal energy in two adjacent time windows; that is, two adjacent windows with a length of L are assumed and are respectively referred to as windows a and B; when two windows slide on the received signal, the energy falling into the two windows is EAAnd EB：
S 'in the above formula'1Representing a signal sample point sequence, n is a related starting point, and k represents a sample point index in a related window;
during detection, the window A and the window B start to slide; when both windows contain only noise energy, EAAnd EBAre constant, their ratio m is also constant, i.e. m equals 1; the two windows continue to slide, the burst signal gradually enters the window B, the energy of the window B is gradually increased, the window A only contains noise at the moment, and the energy ratio of the two windows is gradually increased; when the window B just contains all burst signals, the window A still only contains all noise energy, the ratio m of the two windows reaches the maximum, and the window B corresponds to the starting moment of the burst signals; then, the window A also gradually contains burst signals, and the energy ratio m of the two windows gradually falls back to 1; when window B contains noise energy, m continues to decrease; when the window B just contains noise, the window A contains burst signals, the ratio m of the two windows reaches the minimum, and the end time of the burst signals corresponds to the end time;
in step S2, the specific content of the initial estimation of the time delay is as follows:
the method used for initial estimation of the delay is differential correlation, i.e.,
respectively differentiating the reference interference and the aliasing signal to obtain
dr(n)＝r(n)conj(r(n-τ))；
In the above formula, drAs a result of the difference in the interfering signals,
n is a sampling point index, r is an interference signal s'1For aliasing signals, tau is a difference interval, and the over-sampling multiple of the interference signal is taken for re-correlation to obtain
In the above formula, E represents the average value,
the peak value obtained by correlation, m is the position of correlation calculation, and N is the data volume of correlation calculation; - τmax≤m≤τmax，τmaxDetermining the maximum delay deviation which can be tolerated by the canceller for the size of the time window of the correlation search;
performing sliding correlation on the aliasing signal and the reference signal in a set time window, searching the maximum value of a correlation peak, and recording the position to obtain the relative time delay of the aliasing signal and the reference signal; because the reference signal is a local input signal and the aliasing signal is a signal transmitted by a physical channel, the accurate channel time delay can be obtained through the relative time delay;
in step S2, the specific content of the initial estimation of the frequency difference is as follows:
establishing a signal receiving model
Wherein
The time delay of the previously estimated integer sample point; if the target signal and the noise in r (n) are ignored, y (n) is a single-frequency signal, and the frequency of the single-frequency signal is the frequency difference of the interference signals of the two channels; frequency difference estimation is realized through FFT; that is to say that the first and second electrodes,
z(n)＝abs(FFT(y(n),L))
z(k)＝max(z(n))
in the above formula, z (n) is an amplitude obtained after FFT calculation, L is a length of FFT calculation, and when n is k, a peak z (k) of a frequency spectrum is obtained; only the frequency corresponding to the peak value needs to be calculated, namely the frequency difference; carrying out parabolic fitting by utilizing the peak value and the points on the left side and the right side; variables a and b are set respectively, and the values are calculated by the following formulas
Obtaining the distance tau between k and the fitted peak value as-b/2 a, and calculating a final frequency offset value on the basis of the distance tau;
in the above formula, FsIs the sampling rate of the signal;
in step S2, the details of the initial estimation of the amplitude and phase are as follows:
correlating the two signals to obtain
In the above formula, m is the relevant position; taking the maximum value of the correlation peak, wherein the correlation value is the amplitude-phase difference between the two paths of signals;
computing
Carrying out parabolic fitting on the three correlation values;
and obtaining the estimation of the time delay of the fractional sampling point.
2. The multi-system co-channel interference cancellation method according to claim 1, wherein in step S3, the specific content of interference cancellation implemented by using the polymorphic LMS tracking loop algorithm is as follows:
waiting for a link; that is, when no interference is detected, the filter does not operate;
counteracting a link; that is, the first interference is detected, the filter coefficient is initialized, the operation is started, and the coefficient is updated iteratively;
keeping a link; that is, after the interference disappears, the filter coefficient is kept and the next interference is waited for; after the interference occurs, counting the offset state again, and updating the coefficient in an iterative manner;
resetting; that is, if there is no interference for a long time, the timeout condition is reached, i.e., the filter coefficient is reset, and the standby state is entered again.
3. The method according to claim 1, wherein in step S2, after the initial estimation of the frequency difference is completed, the step of calculating the estimated error of the frequency difference is further performed, specifically as follows:
introducing a phase-locked loop, wherein a structure of a second-order phase-locked loop, namely a closed-loop structure of a phase discriminator, a loop filter and a voltage-controlled oscillator, is adopted, and two inputs of the phase discriminator are respectively a main channel received signal and reconstruction interference; setting the output phase of the voltage-controlled oscillator at n time to
Then the interference is reconstructed as
The phase error output by the phase detector can then be simply obtained by correlation of the received waveforms of the main and auxiliary channels, as follows:
in the above formula, r (n) is an interference signal, m represents the position of the correlation, and l is the size of the time window selected when the correlation is performed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010352437.7A CN111585690B (en) | 2020-04-28 | 2020-04-28 | Multi-system same-frequency interference cancellation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010352437.7A CN111585690B (en) | 2020-04-28 | 2020-04-28 | Multi-system same-frequency interference cancellation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111585690A CN111585690A (en) | 2020-08-25 |
| CN111585690B true CN111585690B (en) | 2021-02-12 |
Family
ID=72126220
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010352437.7A Active CN111585690B (en) | 2020-04-28 | 2020-04-28 | Multi-system same-frequency interference cancellation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111585690B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113285737B (en) * | 2021-04-01 | 2022-04-15 | 清华大学 | Method and system for eliminating signal interference in LoRa collision decoding |
| CN113258984B (en) * | 2021-04-29 | 2022-08-09 | 东方红卫星移动通信有限公司 | Multi-user self-adaptive frequency offset elimination method and device, storage medium and low-orbit satellite communication system |
| CN115189861B (en) * | 2022-07-06 | 2024-04-19 | 中国电子科技集团公司第五十四研究所 | Bidirectional single-pass frequency synchronization method based on coherent frequency difference measurement |
| CN115622845B (en) * | 2022-12-04 | 2023-03-31 | 成都云溯新起点科技有限公司 | Co-channel interference cancellation method, system, equipment and medium of time-varying channel |
| CN116055271A (en) * | 2023-01-13 | 2023-05-02 | 重庆大学 | Burst signal detection method of double sliding windows under specific waveform structure |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101997787A (en) * | 2009-08-25 | 2011-03-30 | Tcl集团股份有限公司 | MMSE-DFE (Minimum Mean Square Error-Decision Feedback Equalization) joint detection method and system |
| CN102065033A (en) * | 2010-11-03 | 2011-05-18 | 三维通信股份有限公司 | Repeater with ICS function and implementation method thereof |
| CN109889218A (en) * | 2019-04-02 | 2019-06-14 | 成都云溯新起点科技有限公司 | A kind of identification of single channel co-channel interference and counteracting method |
| CN109981506A (en) * | 2019-01-24 | 2019-07-05 | 西北工业大学 | A kind of all-digital demodulation method based on open loop structure |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7925164B2 (en) * | 2006-08-30 | 2011-04-12 | Broadlight Ltd. | Method and system for power management control in passive optical networks |
-
2020
- 2020-04-28 CN CN202010352437.7A patent/CN111585690B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101997787A (en) * | 2009-08-25 | 2011-03-30 | Tcl集团股份有限公司 | MMSE-DFE (Minimum Mean Square Error-Decision Feedback Equalization) joint detection method and system |
| CN102065033A (en) * | 2010-11-03 | 2011-05-18 | 三维通信股份有限公司 | Repeater with ICS function and implementation method thereof |
| CN109981506A (en) * | 2019-01-24 | 2019-07-05 | 西北工业大学 | A kind of all-digital demodulation method based on open loop structure |
| CN109889218A (en) * | 2019-04-02 | 2019-06-14 | 成都云溯新起点科技有限公司 | A kind of identification of single channel co-channel interference and counteracting method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111585690A (en) | 2020-08-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111585690B (en) | Multi-system same-frequency interference cancellation method | |
| CN109962714B (en) | Electromagnetic spectrum umbrella cover digital domain self-interference suppression method and system | |
| EP1197049B1 (en) | A method and apparatus for performing dc-offset compensation in a radio receiver | |
| JP4718075B2 (en) | Apparatus and method for compensating for interference of direct conversion transceiver | |
| US7301993B2 (en) | Channel estimation in a spread spectrum receiver | |
| US7239675B2 (en) | GFSK receiver | |
| US5974098A (en) | Received signal detector for digital demodulator | |
| CN109962732B (en) | Calibration device and method for high-speed data transmission baseband test equipment | |
| AU5989601A (en) | A receiver device for a mobile radio communication unit employing a speed estimator | |
| WO2002032067A1 (en) | Method for automatic frequency control | |
| US11336492B2 (en) | Chaotic shape-forming and matched filter-based wireless communication method | |
| CN110912847A (en) | GMSK signal demodulation method | |
| JPH04229734A (en) | Receiver composed of apparatus evaluating frequency transition | |
| US6249518B1 (en) | TDMA single antenna co-channel interference cancellation | |
| US6438362B1 (en) | Method and apparatus for SIR measurement | |
| AU682689B2 (en) | CDMA communication system | |
| KR101019171B1 (en) | Frequency error correction by using remodulation | |
| CN110824412B (en) | Non-coherent spread spectrum transponder distance zero value high-precision measurement system | |
| Latva-aho et al. | Delay trackers for multiuser CDMA receivers | |
| JP3649542B2 (en) | Nonlinear signal correlator and method thereof | |
| Xhonneux et al. | A maximum-likelihood-based two-user receiver for lora chirp spread-spectrum modulation | |
| JP2001077744A (en) | Synchronous detection device, transmission and reception device, and interference removal device of mobile communication system | |
| CN115622845B (en) | Co-channel interference cancellation method, system, equipment and medium of time-varying channel | |
| Wang et al. | A Pseudo-Code-Aided Carrier Synchronization Method for THz Communication System | |
| Palestini et al. | Integrated NAV-COM systems: Assisted code acquisition and interference mitigation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |