CN105827274B - The disturbance restraining method and system of a kind of wireless signal - Google Patents

Abstract

The present invention provides a method and system for suppressing interference of wireless signals, which are applied to a SC-FDMA wireless spread spectrum communication system, including: generating a local frequency domain pilot sequence; performing SC-FDMA wireless spread spectrum communication according to the local frequency domain pilot sequence The frequency domain response corresponding to the channel discrete time domain response of the system is estimated by LS frequency domain channel to obtain the first channel frequency domain response; the time domain noise reduction processing based on the channel PDP decision criterion is performed on the first channel frequency domain response to obtain the second Two-channel frequency domain response; and perform interference detection based on soft threshold on the first channel frequency domain response to obtain the sub-channel interference position identification; perform mask interference suppression on the second channel frequency domain response according to the sub-channel interference position identification, and obtain the second channel interference position identification Frequency domain responses of three channels; performing frequency domain channel equalization on the frequency domain responses of the third channel. The invention reduces the influence of noise on the communication system, effectively suppresses the power spectrum component of the interference, and eliminates the influence of the interference on the communication system.

Description

Method and system for suppressing interference of wireless signals

technical field

The present invention relates to a communication technology, in particular to a method and system for suppressing interference of wireless signals in a SC-FDMA (Single-carrier Frequency-Division Multiple Access) wireless spread spectrum communication system.

Background technique

Since the 21st century, the technology of aviation aircraft and drones has developed rapidly, and the electromagnetic interference environment of aviation wireless spread spectrum communication is relatively complex, and the requirements for anti-interference indicators are also getting higher and higher. Related communication fields are still very valuable for research in this area .

Traditional channel estimation and equalization techniques can compensate the impact of complex channels on the system to a certain extent. At present, channel estimation and equalization techniques that are widely used include: frequency domain channel estimation algorithm based on pilot sequence and channel estimation algorithm based on transform domain. Among them, the frequency domain channel estimation algorithm based on the pilot sequence includes the channel estimation algorithm of the least squares (LeastSquare, LS), the channel estimation algorithm of the minimum mean square error (Minimum Mean Square Error, MMSE) and the linear minimum mean square error criterion ( Linear Minimum Mean Square Error, LMMSE) channel estimation algorithm; channel estimation algorithms based on transform domain include discrete Fourier transform (Discrete FourierTransform, DFT) channel estimation algorithm and single carrier frequency division multiple access (Single Carrier Frequency-Division Multiple Access, SC-FDMA) channel estimation algorithm.

Although channel estimation and equalization techniques can compensate signal interference from complex channels to a certain extent, traditional single-carrier frequency-domain estimation and equalization techniques perform poorly in complex electromagnetic interference environments such as single-frequency and narrow-band interference. Moreover, the special aerospace wireless spread spectrum communication system occupies a wide frequency band, and there are often complex electronic countermeasures in the radio environment, such as high-power single-frequency or narrow-band interference. Simple traditional channel estimation and equalization techniques are no longer able to combat complex electromagnetic interference.

Contents of the invention

In view of the shortcomings of the prior art described above, the object of the present invention is to provide a method and system for suppressing interference of wireless signals, which is used to solve the problem of traditional channel estimation and equalization techniques in SC-FDMA wireless spread spectrum communication systems in the prior art. It cannot effectively solve the problem of the influence of complex electromagnetic interference on the system.

In order to achieve the above object and other related objects, the present invention provides a wireless signal interference suppression method, which is applied to a SC-FDMA wireless spread spectrum communication system. The wireless signal interference suppression method includes: generating a local frequency domain pilot sequence; Perform LS frequency domain channel estimation on the frequency domain response corresponding to the channel discrete time domain response of the SC-FDMA wireless spread spectrum communication system according to the local frequency domain pilot sequence to obtain the first channel frequency domain response; A channel frequency domain response is subjected to time domain noise reduction processing based on channel PDP decision criteria to obtain a second channel frequency domain response; and an interference detection based on a soft threshold is performed on the first channel frequency domain response to obtain subchannel interference positions identification; performing mask interference suppression on the frequency domain response of the second channel according to the subchannel interference position identification to obtain a frequency domain response of the third channel; performing frequency domain channel equalization on the frequency domain response of the third channel.

In an embodiment of the present invention, the local frequency domain pilot sequence is generated by spreading the pilot symbols with an orthogonal variable spreading factor and scrambling with a GOLD sequence.

In an embodiment of the present invention, the orthogonal variable spreading factor adopts a Walsh sequence with a length of 1024.

In an embodiment of the present invention, the frequency domain response of the second channel is first converted to the time domain response of the first channel in the time domain by IDFT transforming the frequency domain response of the first channel; then the decision based on the channel PDP Criteria for time-domain noise reduction processing to obtain the second channel time-domain response, which is finally generated by DFT transformation to the frequency domain; where the decision criterion based on channel PDP is In the formula, h _opt represents the time domain response of the second channel; Indicates the time domain response of the first channel; P _LS indicates the time domain power time spectrum of the LS frequency domain channel estimation, and ρ indicates the power spectrum threshold value.

In an embodiment of the present invention, the power spectrum threshold ρ is determined by the average power and noise power of the local frequency domain pilot sequence.

In an embodiment of the present invention, the sub-channel interference location identifier is calculated by calculating a detection statistic, and selecting a corresponding detection threshold according to an estimated signal-to-noise ratio level; comparing the detection statistic with the detection threshold to determine Generated; wherein, the subchannel interference location is identified as 0≤k≤N-1; U represents the detection statistic, and 0≤k≤N-1, H ₁ represents the frequency domain response of the first channel; V represents the detection threshold.

In an embodiment of the present invention, the third channel frequency domain response is obtained by performing masked interference suppression on the second channel frequency domain response according to the subchannel interference location identifier: 0≤k≤N-1; wherein, H _c represents the frequency domain response of the third channel; H ₂ represents the frequency domain response of the second channel.

In an embodiment of the present invention, the step of performing frequency domain channel equalization on the frequency domain response of the third channel is implemented by using a frequency domain channel equalization algorithm based on MMSE criterion.

The present invention also discloses a wireless signal interference suppression system, which is applied to a SC-FDMA wireless spread spectrum communication system. The wireless signal suppression system includes: a pilot sequence generation module, which is used to generate a local frequency domain pilot sequence; The channel estimation module is used to perform LS frequency domain channel estimation on the frequency response function corresponding to the impulse response of the SC-FDMA wireless spread spectrum communication system according to the local frequency domain pilot sequence to obtain the first channel frequency domain response; The domain noise reduction and interference detection module is used to perform time domain noise reduction processing and interference detection on the first channel frequency domain response, and obtain the second channel frequency domain response and sub-channel interference position identification; the interference suppression module is used to The frequency domain response of the second channel performs mask interference suppression according to the subchannel interference location identifier to obtain a frequency domain response of the third channel; a channel equalization module is used to perform frequency domain channel equalization on the frequency domain response of the third channel .

In an embodiment of the present invention, the time-domain noise reduction and interference detection module includes: a time-domain noise reduction sub-module for performing time-domain noise reduction based on channel PDP decision criteria for the first channel frequency domain response processing to obtain the frequency domain response of the second channel; the interference detection submodule is configured to perform interference detection based on a soft threshold on the frequency domain response of the first channel, and generate the subchannel interference location identifier.

In one embodiment of the present invention, the decision criterion based on channel PDP is In the formula, h _opt represents the time domain response of the second channel; Represents the first channel time domain response corresponding to the first channel frequency domain response; P _LS represents the time domain power time spectrum of the LS frequency domain channel estimation, ρ represents the power spectrum threshold value; and the power spectrum threshold value ρ is determined by the average power and noise power of the local frequency domain pilot sequence.

In an embodiment of the present invention, the interference detection sub-module generates the sub-channel interference location identifier by calculating detection statistics and comparing the detection statistics with a detection threshold, wherein the sub-channel The channel interference location is identified as 0≤k≤N-1; where U represents the detection statistic, and 0≤k≤N-1, where H ₁ represents the frequency domain response of the first channel; V _d-high represents the detection threshold.

In an embodiment of the present invention, the channel equalization module uses a frequency domain channel equalization algorithm based on the MMSE criterion to perform frequency domain channel equalization on the frequency domain response of the third channel.

As mentioned above, a wireless signal interference suppression method and system of the present invention are applied to SC-FDMA wireless spread spectrum communication systems. The present invention closely combines frequency domain channel estimation technology and frequency domain channel equalization communication technology, that is, steps of time domain noise reduction processing based on PDP decision criterion and interference detection based on soft threshold are added to channel discrete time domain response. Compared with the traditional time-domain noise suppression method based on the maximum delay L _max , the time-domain noise reduction processing based on PDP judgment can further reduce the impact of noise on the system; The high-value strong interference detection process can automatically detect specific interference frequency ranges, and the improved soft threshold detection decision selects the threshold according to the estimated signal-to-noise ratio, effectively suppressing the power spectrum components of interference, and eliminating the impact of interference on the system.

Description of drawings

FIG. 1 is a schematic flowchart of a method for suppressing interference of wireless signals disclosed in an embodiment of the present invention.

Fig. 2 is a schematic diagram showing the generation and multiplexing structure of local frequency domain pilot sequences in a wireless signal interference suppression method disclosed in an embodiment of the present invention.

FIG. 3 is a block diagram of anti-interference communication in a method for suppressing interference of wireless signals disclosed in an embodiment of the present invention.

FIG. 4 is a schematic diagram of a performance curve of time-domain noise reduction based on a channel PDP decision criterion of a wireless signal interference suppression method disclosed in an embodiment of the present invention.

FIG. 5 is a schematic diagram of a single-frequency anti-interference performance curve of a wireless signal interference suppression method disclosed in an embodiment of the present invention.

Fig. 6 is a schematic structural diagram of a wireless signal interference suppression system disclosed by an embodiment of the basic invention.

Component designation description

S10～S50 steps

610 pilot sequence generation module

620 channel estimation module

630 Temporal Noise Reduction and Interference Detection Module

631 Temporal noise reduction sub-module

632 Interference detection sub-module

640 Interference Suppression Module

650 channel equalization module

Detailed ways

Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

Please refer to attached picture. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the components in actual implementation. Dimensional drawing, the type, quantity and proportion of each component can be changed arbitrarily during actual implementation, and the component layout type may also be more complicated.

A wireless signal interference suppression method and system of the present invention is a channel estimation and channel equalization system with strong anti-interference ability proposed on the basis of closely combining frequency domain channel estimation and equalization communication technology. The present invention adopts the time-domain suppression noise technology based on the decision criterion of channel PDP (Power Delay Profile, power delay spectrum) to suppress white noise interference, such as AWGN, sea clutter and other clutter interference; adopts interference detection technology based on soft threshold , combined with mask interference suppression, further suppresses single-frequency and narrow-band interference.

Example 1

This embodiment discloses a wireless signal interference suppression method applied to an SC-FDMA wireless spread spectrum communication system, which is used to suppress noise and solve the interference of a characteristic single frequency or narrow band to the system.

As shown in FIG. 1, the interference suppression method for wireless signals in this embodiment includes:

Step S10, generating a local frequency domain pilot sequence;

The generation of the local frequency domain pilot in this embodiment refers to the design idea of CDMA (Code Division Multiple Access, Code Division Multiple Access) pilot generation, as shown in FIG. 2 . The pilot symbol p is spread by OVSF (Orthogonal Variable Spreading Factor, Orthogonal Variable Spreading Factor) and then multiplexed into the data signal. Using the design idea of CDMA pilot generation, the generated local frequency domain pilot sequence will not temporarily use independent time slot resources, which simplifies the frame structure.

As shown in Figure 2, the pilot symbol p is spread by a Walsh sequence with a length of 1024, and then obtained by scrambling with a Gold sequence. Wherein, the length of the Gold sequence used for scrambling is 1024, and is generated using a generator polynomial in the LTE (Long Term Evolution, Long Term Evolution) protocol. Add the compound symbols scrambled by the Gold sequence to a single carrier and pass DFT-S-OFDM (Discrete Fourier Transform-Spread OFDM, discrete Fourier transform spread spectrum orthogonal frequency division multiple access technology) technology To achieve single-carrier communication, after inserting the cyclic prefix CP (Cyclic Prefix), it is sent to the RF front end.

In this embodiment, the pilot symbol p=(1+i)/2 is spread by a Walsh sequence of length M, scrambled by a Gold sequence of length M, and then multiplied by the power factor b to obtain the local Frequency Domain Pilot Sequence.

Step S20, performing LS frequency domain channel estimation on the frequency domain response corresponding to the channel discrete time domain response of the SC-FDMA wireless spread spectrum communication system according to the local frequency domain pilot sequence to obtain a first channel frequency domain response.

After the local frequency domain pilot sequence is generated, the LS frequency domain channel estimation is used in the wireless receiver to track, analyze and suppress the high intensity frequency domain interference. Analyze the results of LS frequency domain channel estimation to detect the distribution of single frequency and narrowband interference in the frequency domain channel; at the same time, transform the LS frequency domain estimation results into the time domain, and select the tap corresponding to the channel maximum path delay as the time domain white Noise suppression windowing threshold. Combining the channel estimation and equalization technology, the specific anti-interference structure of this embodiment is shown in FIG. 3 .

The digital front-end output data of the wireless receiver passes through the synchronization unit and removes the single carrier symbol after the cyclic prefix CP Where M is the number of samples of a discrete single carrier symbol.

As shown in FIG. 3 , the signal y(n) after passing through the channel and removing the cyclic prefix CP in this embodiment represents a received discrete single-carrier symbol in a time domain, where 0≤n≤M-1; among them, h(n) is the channel discrete time domain response; x(n) is the transmitted discrete symbol; w(n) represents discrete and independent Gaussian white noise; The symbols represent convolution operations. And, the channel discrete time domain response In the formula, a _l represents the gain of the path, l represents the time delay of different paths, and L represents the maximum path CIR (Channel Impulse Response, channel impulse response) of the channel. In this embodiment, a discrete single carrier symbol in the time domain has a total of 2048 samples, that is, M=2048.

And, what the present embodiment adopts is LS frequency-domain channel estimation, therefore, need to convert the channel discrete time-domain response into the channel discrete frequency-domain response, namely to the discrete single carrier of a time domain through DFT (Discrete FourierTransform, discrete FourierTransform, discrete Fourier Transform) leaf transform), and at the same time perform subcarrier demapping on the DFT-transformed frequency domain data, then the frequency domain output of the kth subcarrier can be expressed as: Y(k)=X(k)H(k)+W(k) ,0≤k≤N-1; among them, X represents the frequency domain response of sending discrete symbols, W(k) represents the frequency domain response of Gaussian white noise, H(k) represents the discrete frequency domain response of the channel, and N represents the frequency domain sub Number of frequency domain samples after carrier demapping.

The channel estimation in the frequency domain is carried out by the LS criterion, and the frequency domain response of the first channel after the initial estimation of the channel is obtained as:

Among them, Y(k) is the frequency domain response of receiving discrete single carrier symbols, and P(k) is the local frequency domain pilot sequence.

Step S30, performing time-domain noise reduction processing based on channel PDP decision criteria on the first channel frequency domain response to obtain a second channel frequency domain response; and performing interference based on a soft threshold on the first channel frequency domain response detection to obtain the sub-channel interference location identifier.

It is not difficult to see from formula (1) that after LS frequency domain channel estimation, there is still a lot of noise interference. Therefore, noise reduction processing is generally performed on the frequency domain response of the first channel in the time domain.

Therefore, IDFT (InverseDiscreteFourierTransform, Inverse Discrete Fourier Transform) transformation is first performed on the first channel frequency domain response to obtain the first channel time domain response corresponding to the first channel frequency domain response which is:

At present, since most of the CIR energy is concentrated on the first few L taps, it is more commonly used to zero the noise power outside the channel taps, which can reduce the impact of white noise interference on the system to a certain extent. Among them, the interference with white noise characteristics includes free space noise obeying Gaussian distribution, and sea clutter interference obeying Rayleigh distribution and lognormal distribution. Therefore, assuming that the maximum channel impulse response tap length is L _max , the time-domain channel response after noise suppression is:

Among them, L _max =L _τ +S; L _τ represents the maximum multipath delay in the channel environment of the system, S represents the signal transmission bandwidth, and the time-domain noise suppression algorithm usually selects the maximum delay as the CP length. It can be seen from the above decision criteria that when the current channel multipath delay is less than L _max , choosing a fixed channel delay response threshold will often introduce more noise. Secondly, when the multipath delay is relatively bad, that is, when the maximum multipath delay value is large, such as a bad urban channel model, since the proportion of signal energy distribution with a large delay path is often small, the largest L _max is selected As a decision threshold, although more delay information is obtained, more noise is inevitably introduced.

Based on the above problems, this embodiment proposes an improved time-domain noise reduction process based on the decision criterion of the channel PDP, wherein the decision criterion based on the channel PDP is expressed as:

In the formula, h _opt (n) is the time domain response of the second channel, P _LS (n) is the time domain power delay spectrum of LS frequency domain channel estimation, ρ is the power spectrum threshold value, and the power spectrum threshold value ρ The value depends on the average power of the local frequency domain pilot sequence, namely Among them, E[|P(k)| ² ] represents the average power of the local frequency domain pilot sequence, Indicates the noise power of the scene.

Then perform DFT transformation on the second channel time domain response h _opt (n), so as to obtain the second channel frequency domain response H ₂ (k).

Further, the average power of the local frequency domain pilot sequence is:

E[|P(k)| ² ]＝b·E[|Y _i (k)| ² ]; (3)

In the formula, b is the pilot power factor, since the power of the received signal y _i (n) is modulated to unit 1, the power of the frequency-domain pilot sequence can be obtained according to the above formula as b. The noise power is expressed as:

Further, in order to implement interference suppression in environments with different SNRs, this embodiment also proposes an interference detection based on a soft threshold for the frequency domain response of the first channel. It adopts different threshold values for interference suppression under high SNR and low SNR environments, so as to improve interference suppression performance under low SNR conditions. Select a specific threshold value V, set the detection statistic U to detect and judge the frequency domain response of the first channel obtained after LS frequency domain channel estimation, so as to obtain the frequency domain physical layer subchannel of single frequency and narrowband interference Interference location identification:

Among them, the calculation expression of detection statistics is:

In the formula, H ₁ (k) represents the frequency domain response of the first channel.

In this embodiment, when the channel is in a high signal-to-noise ratio environment, that is, SNR _est >0dB, the detection threshold is set to V _d-high , the detection statistic U is analyzed, and the strong interference higher than the threshold value The sub-channels are distinguished, and the judgment rule is as follows:

Similarly, when the channel is in a low SNR environment, the low SNR detection threshold V _d-low is used to detect and judge interference. In the formula, sc_index(k) is the sub-channel interference location identifier. If the current sub-channel statistic is greater than the threshold, it will be marked as 0, otherwise it will be marked as 1.

Step S40, performing mask interference suppression on the frequency domain response of the second channel according to the subchannel interference location identifier to obtain a frequency domain response of the third channel.

The obtained sub-channel interference location identifier sc_index is used as the condition for fast interference suppression, and the frequency domain response of the third channel is obtained after interference suppression:

Step S50, performing frequency domain channel equalization on the frequency domain response of the third channel.

The present invention adopts frequency domain equalization to avoid complex matrix operations, and effectively reduces the implementation complexity of channel equalization based on the existing high-efficiency IP core algorithm module. The frequency domain channel equalization algorithm based on MMSE criterion can be expressed as:

Among them, SNR _est is the estimated signal-to-noise ratio of the currently received symbol, Y _o (k) is the output frequency domain response of the discrete data symbol after equalization, and Y _i (k) is the input frequency domain response of the discrete data symbol, is the complex conjugate of H _c (k). And, from formula (3) and formula (4), the estimated signal-to-noise ratio SNR _est can be expressed as:

It should be noted that the division of steps in the above method is only for clarity of description. During implementation, some steps can be combined into one step or split into multiple steps. As long as they contain the same logical relationship, they are all included in this patent Within the scope of protection; adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of the algorithm and process are all within the scope of protection of the patent.

Further, in order to verify the noise suppression and single-frequency anti-interference performance of the wireless signal interference suppression method of this embodiment, a system simulation platform was built using Matlab tools, and the simulation results were analyzed. This simulation is aimed at the SC-FDMA wireless spread spectrum communication system, and the time domain noise reduction performance and interference suppression performance are carried out in the AWGN channel model and the fading channel model respectively. Among them, the relevant configuration parameters of the SC-FDMA wireless spread spectrum communication system are detailed in Table 1 below; the fading channel model adopts a typical rural model (cost207RAx6) channel model, and its parameter configuration is detailed in Table 2 below.

Table 1 System related configuration parameters

Table 2 Typical rural fading channel parameters

Moreover, the SC-FDMA wireless spread spectrum communication system simulated this time will also be subject to single-frequency interference. Single-frequency interference refers to the interference signal using a single sine wave or multiple sine waves. In this simulation, within the signal bandwidth of 7.68MHz, a random frequency point interference is generated for each cycle single carrier symbol, superimposed on the symbol, and the interference power is preset. The interference model for this simulation is: Wherein, I is the interference signal, f is the frequency value of the interference generated randomly, k is the serial number of the data point, f _s =15.36MHz indicates the system sampling frequency; BW=7.68MHz indicates the signal bandwidth.

The simulation of the noise reduction performance in the time domain is to simulate the minimum mean square error (Mean Square Error, MSE) of the LS estimation of different signal-to-noise ratios (Signal-to-NoiseRatio, SNR) before and after the noise reduction processing. Moreover, in order to verify the performance of the time-domain noise reduction processing proposed in this embodiment, the simulation of the time-domain noise reduction performance is carried out under the AWGN channel model and the fading channel model respectively, using the traditional fixed CIR time-delay window noise reduction and this time-domain noise reduction respectively. The time-domain noise reduction based on the channel PDP decision criterion of the embodiment. The simulation results of this time-domain noise reduction performance are shown in Fig. 4 . From the comparison in Fig. 4, it can be observed that under the environment of the AWGN channel model and the typical fading channel model, the time-domain noise reduction processing based on the decision criterion based on the channel PDP proposed in this embodiment has a better suppression effect on white noise.

The simulation of single-frequency anti-interference performance is to simulate the value of the bit error rate under different signal-to-interference ratios. Moreover, in order to verify the performance of the anti-jamming processing proposed in this embodiment, the bit error rate curves after the anti-jamming processing of this embodiment and the bit error rate curves without the anti-jamming processing of this embodiment (jamming detection and masking based on soft threshold) are respectively simulated. Interference suppression) bit error rate curves for easy comparison. The simulation results of the anti-jamming performance are shown in Fig. 5. From the comparison in FIG. 5 , it can be observed that when the bit error rate is at the level of 10 ⁻³ , the system performance has a gain of 8.6 dB after the single-frequency anti-interference processing (I-Cancellation) of this embodiment.

Example 2

This embodiment discloses a wireless signal interference suppression system, which is applied to an SC-FDMA wireless spread spectrum communication system. The wireless signal interference suppression system of this embodiment is mainly used for suppressing noise and solving interference to the system by a characteristic single frequency or narrow band.

As shown in FIG. 6, the wireless signal interference suppression system of this embodiment includes:

A pilot sequence generating module 610, configured to generate a local frequency domain pilot sequence. The pilot sequence generation module 610 refers to the design idea of CDMA (Code Division Multiple Access, Code Division Multiple Access) pilot generation, as shown in FIG. 2 . The pilot symbol p is spread by OVSF (Orthogonal Variable Spreading Factor, Orthogonal Variable Spreading Factor) and then multiplexed into the data signal. Using the design idea of CDMA pilot generation, the generated local frequency domain pilot sequence will not temporarily use independent time slot resources, which simplifies the frame structure.

The channel estimation module 620 is used to perform LS frequency domain channel estimation on the frequency response function corresponding to the impulse response of the SC-FDMA wireless spread spectrum communication system according to the local frequency domain pilot sequence, and generate the first channel frequency domain response:

Perform DFT transformation on the received discrete single-carrier symbols in a time domain to obtain the channel discrete frequency domain response H(k); and then perform frequency domain channel estimation through the LS criterion to obtain the first channel frequency domain after the initial channel estimation The response is:

Among them, Y(k) is the frequency domain response of receiving discrete single carrier symbols, and P(k) is the local frequency domain pilot sequence.

The time domain noise reduction and interference detection module 630 is configured to perform time domain noise reduction processing and interference detection on the first channel frequency domain response, and generate a second channel frequency domain response and a subchannel interference location identifier.

Wherein, the time-domain noise reduction and interference detection module 630 includes a time-domain noise reduction sub-module 631 and an interference detection sub-module 632:

The time-domain noise reduction sub-module 631 is configured to perform time-domain noise reduction processing based on the channel PDP decision criterion on the first channel frequency domain response to obtain the second channel frequency domain response:

First, IDFT transform is performed on the first channel frequency domain response to obtain the first channel time domain response corresponding to the first channel frequency domain response H ₁ (k)

Secondly, the time domain response to the first channel Carry out the time domain noise reduction process based on the decision criterion of channel PDP, obtain described second channel time domain response h _opt (n):

In the formula, h _opt (n) is the time domain response of the second channel, P _LS (n) is the time domain power delay spectrum of LS frequency domain channel estimation, ρ is the power spectrum threshold value, and the power spectrum threshold value ρ The value depends on the average power of the local frequency domain pilot sequence, namely Among them, E[|P(k)| ² ] represents the average power of the local frequency domain pilot sequence, Indicates the noise power of the scene.

Finally, DFT transform is performed on the second channel time domain response h _opt (n), so as to obtain the second channel frequency domain response H ₂ (k).

The interference detection submodule 632 is configured to perform interference detection based on a soft threshold on the frequency domain response of the first channel, and generate the subchannel interference location identifier. It adopts different threshold values for interference suppression under high SNR and low SNR environments, so as to improve interference suppression performance under low SNR conditions. The interference detection sub-module 632 selects a specific threshold value V, sets the detection statistic U to detect and judge the first channel frequency domain response H ₁ (k) obtained after LS frequency domain channel estimation, thereby obtaining a single-frequency, narrow-band The subchannel interference location identification of the frequency domain physical layer of the interference:

Among them, the calculation expression of detection statistics is:

The interference suppression module 640 is configured to perform masked interference suppression on the frequency domain response of the second channel according to the subchannel interference location identifier, and generate a frequency domain response of the third channel:

The interference suppression module 640 uses the obtained subchannel interference location identifier sc_index as a condition for fast interference suppression, and obtains the frequency domain response of the third channel after suppressing the interference:

The channel equalization module 650 is configured to perform frequency domain channel equalization on the frequency domain response of the third channel.

In this embodiment, frequency domain equalization is adopted to avoid complex matrix operations, and based on the existing high-efficiency IP core algorithm module, the implementation complexity of channel equalization is effectively reduced. The frequency domain channel equalization algorithm based on MMSE criterion can be expressed as:

In addition, in order to highlight the innovative part of the present invention, units that are not closely related to solving the technical problem proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

It is not difficult to find that this embodiment is a system embodiment corresponding to the first embodiment, and this embodiment can be implemented in cooperation with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment, and will not be repeated here to reduce repetition. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied in the first embodiment.

In summary, a wireless signal interference suppression method and system of the present invention is applied to an SC-FDMA wireless spread spectrum communication system. The present invention closely combines the frequency domain channel estimation technology and the frequency domain channel equalization communication technology, that is, the steps of time domain noise reduction processing based on PDP decision criterion and interference detection based on soft threshold are added to channel discrete time domain response. Compared with the traditional time-domain noise suppression method based on the maximum delay L _max , the time-domain noise reduction processing based on PDP decision can further reduce the impact of noise on the system; The high-value strong interference detection process can automatically detect specific interference frequency ranges, and the improved soft threshold detection decision selects the threshold according to the estimated signal-to-noise ratio, effectively suppressing the power spectrum components of interference, and eliminating the impact of interference on the system. Therefore, the present invention effectively overcomes various shortcomings in the prior art and has high industrial application value.

The above-mentioned embodiments only illustrate the principles and effects of the present invention, but are not intended to limit the present invention. Anyone skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by those skilled in the art without departing from the spirit and technical ideas disclosed in the present invention should still be covered by the claims of the present invention.

Claims (7)

1. A kind of 1. disturbance restraining method of wireless signal, applied to SC-FDMA spread spectrum radio communications systems, which is characterized in that institute The disturbance restraining method for stating wireless signal includes：

   The local frequency-domain pilot sequence of generation；

   According to channel dispersion time domain response pair of the local frequency-domain pilot sequence to the SC-FDMA spread spectrum radio communications systems The frequency domain response answered carries out LS channel estimation in frequency domain, obtains the first channel frequency domain response；

   Carry out composing the time domain noise reduction processing of the decision rule of delay PDP to first channel frequency domain response based on channel power, Obtain second channel frequency domain response；And the Interference Detection based on soft-threshold is carried out to first channel frequency domain response, obtain son Channel disturbance station location marker；Wherein, the second channel frequency domain response is that first channel frequency domain response first is passed through IDFT Transformation is converted to the first channel time domain response of time domain；The decision rule for composing delay PDP based on channel power again carries out time domain drop Processing of making an uproar obtains second channel time domain response, eventually passes through DFT transform and is generated to frequency domain；Wherein, it is composed based on channel power Delay PDP decision rule be

   In formula, h_optRepresent the second channel time domain response；Represent described first Channel time domain responds；P_LSIt represents to represent power spectrum threshold value along spectrum, ρ during the time-domain power of LS channel estimation in frequency domain；

   The second channel frequency domain response according to the subchannel interference position is identified and carries out mask AF panel, obtains third Channel frequency domain response；Wherein, the subchannel interference position mark is to calculate detection statistic, and according to estimation signal-to-noise ratio water It is flat, choose corresponding detection threshold；The detection statistic and the detection threshold are compared and generated；Wherein, institute Subchannel interference position is stated to be identified asU represents the detection statistics Amount, andH₁Represent first channel frequency domain response；V represents the detection Thresholding；N represents frequency domain number of samples；The third channel frequency domain response is：

   Wherein, H_cRepresent the third channel frequency domain response；

   H₂Represent the second channel frequency domain response；

   Frequency domain channel equalization is carried out to the third channel frequency domain response.
2. 2. the disturbance restraining method of wireless signal according to claim 1, it is characterised in that：The local pilot tone sequence Row are by the way that frequency pilot sign is spread by Orthogonal Variable Spreading Factor OVSF, and are scrambled by GOLD sequences to generate.
3. 3. the disturbance restraining method of wireless signal according to claim 2, it is characterised in that：Orthogonal variable spread spectrum because Son use length for 1024 Walsh sequences.
4. 4. the disturbance restraining method of wireless signal according to claim 1, it is characterised in that：The power spectrum threshold value ρ It is determined by the mean power and noise power of the local frequency-domain pilot sequence.
5. 5. the disturbance restraining method of wireless signal according to claim 1, it is characterised in that：It is described to the third channel The step of frequency domain response progress frequency domain channel equalization is to use to realize based on the frequency domain channel equalization algorithm of MMSE criterion.
6. 6. a kind of Interference Suppression System of wireless signal, applied to SC-FDMA spread spectrum radio communications systems, it is characterised in that：Institute The suppression system for stating wireless signal includes：

   Pilot frequency sequence generation module, for generating local frequency-domain pilot sequence；

   Channel estimation module, for according to the local frequency-domain pilot sequence to the SC-FDMA spread spectrum radio communications systems The corresponding frequency response function of shock response carries out LS channel estimation in frequency domain, obtains the first channel frequency domain response；

   Time domain noise reduction and interference detection module, for carrying out time domain noise reduction processing and interference inspection to first channel frequency domain response It surveys, and obtains second channel frequency domain response and subchannel interference position mark；

   AF panel module carries out mask for being identified to the second channel frequency domain response according to the subchannel interference position AF panel obtains third channel frequency domain response；

   Channel equalization module, for carrying out frequency domain channel equalization to the third channel frequency domain response；

   The time domain noise reduction and interference detection module include：

   The judgement that time domain noise reduction submodule is used to carry out composing delay PDP to first channel frequency domain response based on channel power is accurate Time domain noise reduction processing then, obtains the second channel frequency domain response；

   Interference Detection submodule for carrying out the Interference Detection based on soft-threshold to first channel frequency domain response, generates institute State subchannel interference position mark；Based on channel power compose delay PDP decision rule be

   In formula, h_optRepresent second channel time domain response；Represent corresponding first channel time domain of first channel frequency domain response Response；P_LSIt represents to represent power spectrum threshold value along spectrum, ρ during the time-domain power of LS channel estimation in frequency domain；And the power spectrum thresholding Value ρ is determined by the mean power and noise power of the local frequency-domain pilot sequence；The Interference Detection submodule is to pass through meter Detection statistic is calculated, and the detection statistic and detection threshold are compared and generates the subchannel interference position and identifies , wherein, the subchannel interference position is identified asFormula In, U represents the detection statistic, andIn formula, H₁Represent first letter Road frequency domain response；V_d-highRepresent the detection threshold, N represents frequency domain number of samples.
7. 7. the Interference Suppression System of wireless signal according to claim 6, it is characterised in that：The channel equalization module is adopted Frequency domain channel equalization is carried out to the third channel frequency domain response with based on the frequency domain channel equalization algorithm of MMSE criterion.