A passive intermodulation interference full digital suppression method, system, application and terminal

Abstract

The present invention discloses a fully digital suppression method, system, application and terminal for passive intermodulation interference, and relates to the technical field of wireless communication signal processing. The fully digital suppression method comprises the following steps: determining a PIM effective interference signal falling into the receiving frequency band of a signal receiving end; reconstructing the PIM effective interference signal; down-converting and sampling the radio frequency signal received by the receiving end to obtain an intermediate frequency digital signal; inputting the intermediate frequency digital signal and the intermediate frequency signal component of the reconstructed PIM effective interference signal into an adaptive filter; the adaptive filter executes the following adaptive algorithm: defining and pre-filtering a reference signal and an error signal; obtaining a PIM product weight value update formula based on the reference signal and the error signal after pre-filtering; defining a cost function, minimizing the cost function to obtain a filter tap weight update formula; iteratively updating the PIM product weight value and the filter tap weight to achieve PIM interference signal elimination. The present invention can effectively suppress passive intermodulation interference in a receiver.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication signal processing, and in particular to a passive intermodulation interference full-digital suppression method, system, application and terminal. Background Art

[0002] Passive intermodulation (PIM) refers to a phenomenon in which, in a high-power multi-channel communication system, when a signal containing two or more frequency components passes through passive devices (such as duplexers, isolators, coaxial cables, antennas, etc.), new frequency components other than harmonics are generated, and the new frequency components fall into the receiving frequency band of the receiving end and cause interference. This phenomenon is caused by the nonlinear characteristics of passive devices. When PIM interference falls into the receiving frequency band, it will reduce the signal-to-noise ratio of the entire communication system. With the improvement of receiver sensitivity and the increase of transmitter power, PIM interference will directly affect communication quality, system stability and channel capacity. Passive intermodulation interference in narrowband mobile communication systems can be reduced through frequency band planning and frequency hopping pattern design, but for broadband mobile communication systems, PIM interference problems still exist.

[0003] As the PIM problem becomes increasingly serious, many scholars have begun to study passive intermodulation suppression methods and take measures to control the passive intermodulation power within a certain range, that is, low passive intermodulation design. At present, the basic idea of ​​this research in communication systems is to rely on analog or digital methods to create a passive intermodulation signal with equal power and opposite polarity at the receiving end of the link to offset the interference.

[0004] The prior art proposes a method that takes into account the potential memory effect of PIM, and specifically proposes a PIM elimination technology that operates in the digital front end of the transceiver. Based on the above research, the computational efficiency of the PIM cancellation algorithm and parameter estimation is improved, but this method is mainly aimed at the frequency division duplex (FDD) 5G system and is not suitable for PIM cancellation in satellite communication systems. The prior art verifies the chaotic characteristics of PIM in microwave components and predicts the PIM power based on chaos theory. The chaotic characteristics of PIM are verified by the phase diagram method and the maximum Lyapunov exponent method, and the PIM power at different times is predicted based on the maximum Lyapunov exponent method, but this method relies on the training of test data and cannot suppress PIM in real time.

[0005] In summary, existing PIM suppression methods have the disadvantages of being difficult to suppress passive intermodulation interference in real time and being unsuitable for satellite communication systems. Summary of the invention

[0006] The purpose of the present invention is to provide a fully digital passive intermodulation interference suppression method, system, application and terminal, which can effectively suppress passive intermodulation interference in a receiver and reduce the bit error rate of a communication system. The method has low computational complexity and is easy to implement.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for fully digitally suppressing passive intermodulation interference, comprising the following steps:

[0009] S1. Determine the PIM effective interference signal that falls into the receiving frequency band of the signal receiving end;

[0010] S2. Reconstruct the intermediate frequency signal of the PIM effective interference signal to obtain the reconstructed intermediate frequency signal component of the PIM effective interference signal;

[0011] S3. Down-convert and sample the RF signal received by the receiving end to obtain an intermediate frequency digital signal;

[0012] S4. Input the intermediate frequency digital signal and the intermediate frequency signal component of the reconstructed PIM effective interference signal into the adaptive filter to suppress the PIM interference; the adaptive filter executes an adaptive algorithm, and the adaptive algorithm includes the following steps:

[0013] S40. Define a reference signal and an error signal, perform pre-filtering on the reference signal and the error signal, and obtain the reference signal and the error signal after pre-filtering;

[0014] S41. Obtaining a PIM product weight value update formula based on the pre-filtered reference signal and error signal;

[0015] S42. Define a cost function, minimize the cost function to obtain the filter tap weight update formula;

[0016] S43. Iteratively update the PIM product weight value and the filter tap weight to eliminate the PIM interference signal.

[0017] As a possible implementation method, the intermediate frequency signal of the PIM effective interference signal is reconstructed. Specifically, a power series model is used to reconstruct the intermediate frequency signal of the PIM effective interference signal using the intermediate frequency signal or the baseband signal before the initial transmission signal is up-converted.

[0018] As a possible implementation manner, the reference signal is an intermediate frequency digital signal, and the error signal is a difference between the intermediate frequency digital signal and an intermediate frequency signal component of the reconstructed PIM effective interference signal.

[0019] As a possible implementation method, the reference signal and the error signal are pre-filtered, specifically:

[0020]

[0021] Where x(i) is the reference signal, e(i) is the error signal, a is the pre-filter parameter, L is the filter order, i is the i-th iteration, and T represents the transpose operation. is the reference signal after pre-filtering, is the error signal after pre-filtering.

[0022] As a possible implementation method, the PIM product weight value update formula is:

[0023]

[0024] Where b(i) represents the weight value of the PIM product, and b(i) = [b0(i), b1(i), ..., b M (i)] T , i is the i-th iteration, M represents the number of PIM products falling into the receiving band except the lowest-order product, μ b is the step length, is the reference signal after pre-filtering, is the error signal after pre-filtering, and T represents the transpose operation.

[0025] As a possible implementation, the cost function is:

[0026]

[0027] Where λ∈(0,1] is the forgetting factor that controls the performance of the algorithm, |e(j,i)| is the error signal, w(i) is the filter tap weight, p represents the p-norm, i represents the i-th iteration, j represents the j-th added term in the i-th iteration, X(j) represents the signal before upconversion in the j-th iteration, and s rec (j) represents the intermediate frequency digital signal in the jth iteration, and b represents the weight value of each order PIM product;

[0028] The filter tap weight update formula is:

[0029] w(i)=w(i-1)+k(i)[s rec (i)-w T (i-1)X(i)b];

[0030] Among them, w(i) is the filter tap weight, k(i) is the gain matrix, s rec (i) represents the intermediate frequency digital signal in the i-th iteration, X(i) represents the signal before up-conversion in the i-th iteration, and b represents the weight value of each order PIM product.

[0031] In a second aspect, the present invention provides a passive intermodulation interference all-digital suppression system, comprising:

[0032] The intermediate frequency signal reconstruction unit reconstructs the intermediate frequency signal of the PIM effective interference signal by using the intermediate frequency signal or the baseband signal of the initial transmission signal using a power series model to obtain the intermediate frequency signal component of the reconstructed PIM effective interference signal;

[0033] The intermediate frequency digital signal acquisition unit performs down-conversion sampling on the radio frequency signal received by the receiving end to obtain an intermediate frequency digital signal;

[0034] The adaptive algorithm execution unit defines a reference signal and an error signal, performs pre-filtering on the reference signal and the error signal to obtain the reference signal and the error signal after the pre-filtering; obtains a PIM product weight value update formula based on the reference signal and the error signal after the pre-filtering; defines a cost function, minimizes the cost function to obtain a filter tap weight update formula; iteratively updates the PIM product weight value and the filter tap weight to minimize the PIM effective interference signal.

[0035] In a third aspect, the present invention provides an application of a fully digital passive intermodulation interference suppression method, and a high-power multi-channel communication system applies the fully digital passive intermodulation interference suppression method provided in the first aspect.

[0036] In a fourth aspect, the present invention provides a terminal, comprising a processor and a communication interface coupled to the processor, wherein the processor is used to run a computer program or instruction to implement the fully digital passive intermodulation interference suppression method provided in the first aspect.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. The fully digital passive intermodulation interference suppression method provided by the present invention defines a new cost function using an algorithm. The newly defined cost function avoids the situation where the cost function tends to infinity when the error signal approaches 0 during the calculation process, and at the same time enables the algorithm to have better performance and stronger stability.

[0039] 2. The fully digital passive intermodulation interference suppression method provided by the present invention iteratively updates two groups of parameters based on the coordinate descent method, and each group of parameters uses a different update formula in the iteration, thereby improving the algorithm performance and making the final PIM reconstructed signal more accurate, thereby accurately removing the interference component in the signal.

[0040] 3. The fully digital passive intermodulation interference suppression method provided by the present invention adds a pre-filtering process before adaptively updating parameters, removes the correlation between PIM products of various orders, reduces the degree of eigenvalue divergence and improves the convergence speed of the algorithm.

[0041] 4. The passive intermodulation interference full digital suppression method proposed in the present invention can effectively suppress PIM interference in the signal transmission process. Compared with the traditional adaptive filtering method, it has better convergence performance and can achieve lower bit error rate and higher signal-to-interference ratio gain. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0043] Figure 1 Flow chart of a fully digital passive intermodulation interference suppression method in an embodiment of the present invention;

[0044] Figure 2 It is a principle diagram of a fully digital passive intermodulation interference suppression method in an embodiment of the present invention;

[0045] Figure 3 Schematic diagram of the improved recursive minimum p-norm algorithm based on logarithmic transformation adopted by the adaptive filter in the embodiment of the present invention;

[0046] Figure 4 This is a time domain comparison diagram of the PIM interference signal before and after being suppressed under the conditions of a signal-to-noise ratio of 7dB and a signal-to-interference ratio of 0dB in an embodiment of the present invention;

[0047] Figure 5 It is a simulation curve diagram of the bit error rate obtained under a fixed signal-to-noise ratio changing with the interference-to-signal ratio in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, words such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. For example, the first threshold and the second threshold are only used to distinguish different thresholds, and their order is not limited. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0049] It should be noted that, in the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0050] In the present invention, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. The following at least one item (items) or similar expressions thereof refer to any combination of these items, including any combination of single items (items) or plural items (items). For example, at least one item (items) of a, b or c can mean: a, b, c, the combination of a and b, the combination of a and c, the combination of b and c, or the combination of a, b and c, where a, b, c can be single or multiple.

[0051] Existing PIM suppression methods have many shortcomings in practical applications, such as relying on training with test data and being unable to suppress PIM in real time, and being unsuitable for satellite communication systems. To solve the above problems, the present invention provides a fully digital passive intermodulation interference suppression method, system, application and terminal, which are suitable for satellite communication systems and can effectively suppress PIM interference during signal transmission.

[0052] In a first aspect, the present invention provides a fully digital passive intermodulation interference suppression method, see Figure 1 , including the following steps:

[0053] S1. Determine the PIM effective interference signal that falls into the receiving frequency band of the signal receiving end;

[0054] As an example, by analyzing the number of carriers, transmission frequency and other information of the transmitted signal, the possible PIM products of each order are predicted. Multiple-order PIM products will be generated during signal transmission, and the higher the order, the smaller the energy of the PIM interference signal, and the smaller the impact on signal transmission. Usually, the receiving frequency band of the receiving end is known, and the PIM effective interference signal falling into the receiving frequency band can be determined by calculating the center frequency of the received signal. The PIM effective interference signal falling into the receiving frequency band is an interference signal that has a greater impact on signal transmission. Therefore, when suppressing interference, only the PIM effective interference signal falling into the receiving frequency band needs to be considered.

[0055] S2. Reconstruct the intermediate frequency signal of the PIM effective interference signal to obtain the reconstructed intermediate frequency signal component of the PIM effective interference signal;

[0056] As a possible implementation method, the intermediate frequency signal of the PIM effective interference signal is reconstructed. Specifically, a power series model is used to reconstruct the intermediate frequency signal of the PIM effective interference signal using the intermediate frequency signal or the baseband signal before the initial transmission signal is up-converted.

[0057] As an example, the discrete form of the intermediate frequency signal component of the reconstructed PIM effective interference signal can be expressed as:

[0058]

[0059] in, represents the intermediate frequency signal component of the reconstructed PIM effective interference signal, w k is the weight of each tap of the filter, L is the filter order, b m represents the weight value of each order PIM product, M represents the number of PIM products except the lowest order product falling into the receiving frequency band, and x m is the baseband signal before up-conversion, k represents the kth tap coefficient, m represents the weight value of the mth PIM product, and i represents the i-th iteration.

[0060] Formula (1) can be expressed in matrix form as follows:

[0061]

[0062] Where w=[w0 w1…w L-1 ] T is the filter weight vector, b=[b0 b1…b M-1 ] T is the weight value vector of PIM products, X(i) represents the signal before up-conversion in the i-th iteration.

[0063] S3. Down-convert and sample the RF signal received by the receiving end to obtain an intermediate frequency digital signal;

[0064] As an example, the receiving end receives a radio frequency signal, which is a signal returned by a ground satellite receiving station after receiving a transmitted signal. The carrier frequency of the radio frequency signal is down-converted and an intermediate frequency digital signal is obtained after sampling.

[0065] S4. Input the intermediate frequency digital signal and the intermediate frequency signal component of the reconstructed PIM effective interference signal into the adaptive filter to suppress the PIM interference; the adaptive filter executes an adaptive algorithm, and the adaptive algorithm includes the following steps:

[0066] S40. Define a reference signal and an error signal, perform pre-filtering on the reference signal and the error signal, and obtain the reference signal and the error signal after pre-filtering;

[0067] As a possible implementation manner, the reference signal is an intermediate frequency digital signal, and the error signal is a difference between the intermediate frequency digital signal and an intermediate frequency signal component of the reconstructed PIM effective interference signal.

[0068] Exemplarily, the error signal expression is:

[0069]

[0070] Where e(i) is the error signal, s rec (i) represents the intermediate frequency digital signal, Represents the intermediate frequency signal component of the reconstructed PIM effective interference signal.

[0071] As a possible implementation method, the reference signal and the error signal are pre-filtered, specifically:

[0072]

[0073] Where x(i) is the reference signal, e(i) is the error signal, a is the pre-filter parameter, L is the filter order, i is the i-th iteration, and T represents the transpose operation. is the reference signal after pre-filtering, is the error signal after pre-filtering.

[0074] The present invention adds a pre-filtering process before adaptively updating parameters, removes the correlation between PIM products of various orders, reduces the divergence of eigenvalues, and improves the convergence speed of the algorithm.

[0075] S41. Obtaining a PIM product weight value update formula based on the pre-filtered reference signal and error signal;

[0076] As a possible implementation method, the PIM product weight value update formula is:

[0077]

[0078] Where b(i) represents the weight value of the PIM product, and b(i) = [b0(i), b1(i), ..., b M (i)] T , i is the i-th iteration, M represents the number of PIM products falling into the receiving band except the lowest-order product, μ b is the step size, satisfying 0<μ<2 / λ max ,λ max The input correlation matrix X T The largest eigenvalue of w is the reference signal after pre-filtering, is the error signal after pre-filtering, and T represents the transpose operation.

[0079] S42. Define a cost function, minimize the cost function to obtain the filter tap weight update formula;

[0080] As a possible implementation, the cost function J(i) is:

[0081]

[0082] Where λ∈(0,1] is the forgetting factor that controls the performance of the algorithm, |e(j,i)| is the error signal, w(i) is the filter tap weight, p represents the p-norm, i represents the i-th iteration, j represents the j-th added term in the i-th iteration, X(j) represents the signal before upconversion in the j-th iteration, and s rec (j) represents the intermediate frequency digital signal in the jth iteration, and b represents the weight value of each order PIM product.

[0083] The algorithm used in the present invention defines a new cost function, which avoids the situation where the cost function tends to infinity when the error signal |e(j,i)| approaches 0 during the calculation process, and at the same time enables the algorithm to have better performance and stronger stability.

[0084] For example, an improved recursive minimum p-norm algorithm based on logarithmic transformation is used, and the principle diagram is shown in Figure 2 , this algorithm can minimize the cost function J(i), and the partial derivative of the cost function J(i) gradient is obtained:

[0085]

[0086] Among them, sign{e(j,i)}=e(j,i) / |e(j,i)|, let equation (8) be 0 to obtain:

[0087]

[0088] Simplifying the above formula, we can get:

[0089]

[0090] in, is a quantity different from the standard 2-norm algorithm. Note that the a posteriori error signal e(j,i) cannot be obtained in practice, so the algorithm uses a recursive strategy to update by using w(i-1) to calculate e(j,i), and the value of w(i) depends on the calculation of ν(j,i). w(i) can be calculated as follows:

[0091] w(i)=P(i)r(i); (11)

[0092] in

[0093] To simplify the overall complexity of the algorithm, let:

[0094]

[0095] For simplicity, the following derivation and analysis use ν(i,i)=ν(i). To avoid the high computational burden of matrix inversion, P(i) is updated using Woodbury's inverse matrix theorem, which yields:

[0096] P(i)=λ -1 P(i-1)-λ -1 k(i)b T X T (i)P(i-1); (14)

[0097] In the initial stage, P(0)=(1 / σ)I=δI, where σ>0, σ is 0.01, δ>0, and I is a unit diagonal matrix. Its gain matrix k(i) is defined as:

[0098]

[0099] According to formula (14), formula (15) can be simplified as:

[0100] k(i)=P(i)ν(i)X(i)b; (16)

[0101] Substituting formula (13) into formula (12), we can obtain:

[0102]

[0103] According to equations (16) and (17), the filter tap weight update formula can be obtained as follows:

[0104] w(i)=w(i-1)+k(i)[s rec (i)-w T (i-1)X(i)b]; (18)

[0105] Among them, w(i) is the filter tap weight, k(i) is the gain matrix, s rec (i) represents the intermediate frequency digital signal in the i-th iteration, X(i) represents the signal before up-conversion in the i-th iteration, and b represents the weight value of each order PIM product.

[0106] S43. Iteratively update the PIM product weight value and the filter tap weight to eliminate the PIM interference signal.

[0107] The present invention iteratively updates two groups of parameters based on the coordinate descent method, and each group of parameters uses a different updating formula in the iteration, which improves the algorithm performance and makes the final PIM reconstructed signal more accurate, thereby accurately removing the interference component in the signal.

[0108] To facilitate understanding of the technical solution of the present application, further description is given below in conjunction with specific embodiments.

[0109] See also Figure 3 In this embodiment, an S-band communication satellite is selected to simulate the situation where passive intermodulation interference falls into a large receiving frequency band, and then the passive intermodulation interference full-digital suppression method of the present invention is used to suppress passive intermodulation interference.

[0110] The transmission signal frequency refers to UTRAband I, the downlink frequency range is 2110MHz~2170MHz, and a dual-carrier transmission signal is selected. The center frequencies of the dual-carrier transmission signals are f1=2120MHz and f2=2160MHz respectively; the signal modulation method is BPSK, the output symbol rate is 1Mbanud, no channel coding is used, and the shaping filter uses a root raised cosine filter with a roll-off coefficient α of 0.35.

[0111] It is known that the receiving frequency range of the receiving end is 1900~2000MHz. Among them, a set of receiving signal center frequencies is set to f UP =1950MHz. After analysis, the 7th, 9th and 11th order PIM products fall into the receiving frequency band, and the center frequencies are 4f1-3f2=2000MHz, 5f1-4f2=1960MHz, 6f1-5f2=1920MHz respectively. In addition, there is also ultra-high-order PIM interference that falls into the receiving frequency band, but because its power is very small, it has almost no effect on the received signal. Therefore, when performing interference suppression, only the suppression of the 7th, 9th and 11th order PIM products is considered. In this embodiment, the filter order L is 25, and the number of PIM products M except the lowest order product falling into the receiving frequency band is 2. The p value in the cost function based on the p-norm logarithmic transformation is 1.2, and the forgetting factor λ of the control algorithm performance is 0.995, and w(0)=0.

[0112] In this embodiment, under the conditions of a signal-to-noise ratio of 7 dB and a signal-to-interference ratio of 0 dB, the passive intermodulation interference full digital suppression method of the present invention is used to suppress passive intermodulation interference, see Figure 4 , which is a time domain comparison diagram before and after the effective PIM interference signal is eliminated. By comparison, it can be observed that the signal containing PIM interference can basically overlap with the initial signal after passing through the adaptive filter, indicating that the algorithm can effectively eliminate the PIM interference signal. Figure 5 , which is a simulation image of the bit error rate curve changing with the signal-to-interference ratio when the signal-to-noise ratio is 3dB. It can be seen from the image that the bit error rate curve after interference suppression is basically consistent with the curve without PIM interference, and the bit error rate is significantly lower than the signal with PIM interference.

[0113] The above embodiments show that the passive intermodulation interference full digital suppression method proposed in the present invention can effectively suppress PIM interference in the signal transmission process, has better convergence performance than the traditional adaptive filtering method, and can achieve lower bit error rate and higher signal-to-interference ratio gain.

[0114] In a second aspect, the present invention provides a passive intermodulation interference all-digital suppression system, comprising:

[0115] The intermediate frequency signal reconstruction unit reconstructs the intermediate frequency signal of the PIM effective interference signal by using the intermediate frequency signal or the baseband signal of the initial transmission signal using a power series model to obtain the intermediate frequency signal component of the reconstructed PIM effective interference signal;

[0116] The intermediate frequency digital signal acquisition unit performs down-conversion sampling on the radio frequency signal received by the receiving end to obtain an intermediate frequency digital signal;

[0117] An adaptive algorithm execution unit defines a reference signal and an error signal, performs pre-filtering on the reference signal and the error signal to obtain the reference signal and the error signal after the pre-filtering; obtains a PIM product weight value update formula based on the reference signal and the error signal after the pre-filtering; defines a cost function, minimizes the cost function to obtain a filter tap weight update formula; iteratively updates the PIM product weight value and the filter tap weight to minimize the PIM effective interference signal.

[0118] In a third aspect, the present invention provides an application of a fully digital passive intermodulation interference suppression method, and a high-power multi-channel communication system applies the fully digital passive intermodulation interference suppression method provided in the first aspect.

[0119] The present invention can provide technical support for the development of high-power, high-sensitivity integrated space-ground communication systems, reduce the design difficulty of communication payload antenna systems, and improve their reliability, which is innovative and has application value. At the same time, the present invention can also be extended to communication systems that are prone to self-interference under conditions such as unstable temperature and humidity and easy aging of components in industrial application environments, providing technical support for future integrated space-ground communication systems and industrial Internet applications.

[0120] In a fourth aspect, the present invention provides a terminal, comprising a processor and a communication interface coupled to the processor, wherein the processor is used to run a computer program or instruction to implement the fully digital passive intermodulation interference suppression method provided in the first aspect.

[0121] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the drawings, etc. In the specification, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit can implement several functions listed in the specification. Certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0122] Although the present invention has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present invention. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present invention and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present invention. Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, the present invention is intended to include such modifications and variations if they fall within the scope of the present invention and its equivalents.

Claims

1. A fully digital method for suppressing passive intermodulation (PIM) interference, characterized in that: The steps include: S1. Determine the PIM effective interference signal that falls into the receiving frequency band of the signal receiving end; S2. Reconstruct the intermediate frequency signal of the PIM effective interference signal to obtain the reconstructed intermediate frequency signal component of the PIM effective interference signal; S3. Down-convert and sample the RF signal received by the receiving end to obtain an intermediate frequency digital signal; S4. Input the intermediate frequency digital signal and the reconstructed intermediate frequency signal component of the PIM effective interference signal into an adaptive filter to suppress PIM interference; the adaptive filter executes an adaptive algorithm, and the adaptive algorithm comprises the following steps: S40. Define a reference signal and an error signal, perform pre-filtering on the reference signal and the error signal, and obtain a pre-filtered reference signal and an error signal; S41. Obtaining a PIM product weight value update formula based on the pre-filtered reference signal and error signal; S42. Define a cost function, the cost function is: Where λ∈(0,1] is the forgetting factor that controls the performance of the algorithm, |e(j,i)| is the error signal, w(i) is the filter tap weight, p represents the p-norm, i represents the i-th iteration, j represents the j-th added term in the i-th iteration, X(j) represents the signal before upconversion in the j-th iteration, and s rec (j) represents the intermediate frequency digital signal in the jth iteration, and b represents the weight value of each order PIM product; the filter tap weight update formula is obtained by minimizing the cost function, and the filter tap weight update formula is: w(i)=w(i-1)+k(i)[s rec (i)-w T (i-1)X(i)b]; Among them, w(i) is the filter tap weight, k(i) is the gain matrix, s rec (i) represents the intermediate frequency digital signal in the i-th iteration, X(i) represents the signal before up-conversion in the i-th iteration, and b represents the weight value of each order PIM product; S43. Iteratively update the PIM product weight value and the filter tap weight value to eliminate the PIM interference signal.

2. The method for fully digitally suppressing passive intermodulation (PIM) interference according to claim 1, characterized in that: The intermediate frequency signal of the PIM effective interference signal is reconstructed, specifically, a power series model is adopted to reconstruct the intermediate frequency signal of the PIM effective interference signal by using the intermediate frequency signal or the baseband signal before the initial transmission signal is up-converted.

3. The method for fully digitally suppressing passive intermodulation (PIM) interference according to claim 1, characterized in that: The reference signal is the intermediate frequency digital signal, and the error signal is the difference between the intermediate frequency digital signal and the intermediate frequency signal component of the reconstructed PIM effective interference signal.

4. The method for suppressing passive intermodulation (PIM) interference digitally according to claim 1, characterized in that: The reference signal and the error signal are pre-filtered, specifically: Where x(i) is the reference signal, e(i) is the error signal, a is the pre-filter parameter, L is the filter order, i is the i-th iteration, and T represents the transpose operation. is the reference signal after pre-filtering, is the error signal after pre-filtering.

5. The method for fully digitally suppressing passive intermodulation (PIM) interference according to claim 4, characterized in that: The PIM product weight value update formula is: Where b(i) represents the weight value of the PIM product, and b(i) = [b0(i), b1(i), ..., b M (i)] T , i is the i-th iteration, M represents the number of PIM products falling into the receiving band except the lowest-order product, μ b is the step length, is the reference signal after pre-filtering, is the error signal after pre-filtering, and T represents the transpose operation.

6. A passive intermodulation (PIM) interference all-digital suppression system, characterized in that: A method for performing a fully digital passive intermodulation (PIM) interference suppression method as claimed in any one of claims 1 to 5, comprising: An intermediate frequency signal reconstruction unit, which uses a power series model to reconstruct the intermediate frequency signal of the PIM effective interference signal using the intermediate frequency signal or baseband signal of the initial transmission signal to obtain a reconstructed intermediate frequency signal component of the PIM effective interference signal; The intermediate frequency digital signal acquisition unit performs down-conversion sampling on the radio frequency signal received by the receiving end to obtain an intermediate frequency digital signal; An adaptive algorithm execution unit defines a reference signal and an error signal, performs pre-filtering on the reference signal and the error signal to obtain the reference signal and the error signal after the pre-filtering; obtains a PIM product weight value update formula based on the reference signal and the error signal after the pre-filtering; defines a cost function, minimizes the cost function to obtain a filter tap weight update formula; iteratively updates the PIM product weight value and the filter tap weight to minimize the PIM effective interference signal.

7. A high-power multi-channel communication system using a fully digital passive intermodulation interference suppression method, characterized in that: A high-power multi-channel communication system applies the passive intermodulation (PIM) interference full digital suppression method described in any one of claims 1 to 5.

8. A terminal comprising a processor and a communication interface coupled to the processor, wherein the processor is configured to run a computer program or instruction to implement the fully digital passive intermodulation (PIM) interference suppression method according to any one of claims 1 to 5.

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