Passive intermodulation interference elimination method and system for fast time-varying channel, and terminal

Abstract

The invention belongs to the technical field of wireless communication, and relates to a fast time-varying channel-oriented passive intermodulation interference elimination method, which comprises the following steps of: dividing a signal to be transmitted into a plurality of transmitting signal segments, and adding a training sequence in front of each transmitting signal segment; calculating a time-invariant basis coefficient estimation value of each transmitting signal segment based on a discrete ellipsoid basis expansion model; receiving signal segment sampling values in one-to-one correspondence with the transmitting signal segments are calculated; and calculating the passive intermodulation interference signal of the receiving signal segment based on the time-invariant base coefficient estimation value of the transmitting signal segment and the corresponding sampling value of the receiving signal segment, and subtracting the passive intermodulation interference signal of each receiving signal segment from the receiving signal to realize passive intermodulation interference elimination. The invention also discloses a passive intermodulation interference elimination system for the fast time-varying channel and a terminal. The method can cope with the influence of the time-varying channel, estimates the passive intermodulation interference signal passing through the time-varying channel, and is effectively suitable for passive intermodulation interference elimination under the fast time-varying channel.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and particularly to a method, system and terminal for passive intermodulation interference cancellation for fast time-varying channels. Background Art

[0002] At present, the fifth-generation mobile communication technology (5G) network has been applied globally, and both terrestrial communication and satellite communication have developed. However, as communication technology evolves towards the sixth-generation mobile communication technology (6G), a single terrestrial communication network or satellite communication network is difficult to meet various rapidly expanding requirements and applications, and the space-air-ground integrated network architecture has become a major development direction for 6G. The space-air-ground integrated network architecture makes the communication system develop towards high power and high integration, and passive intermodulation has also become an issue that cannot be ignored. Passive Intermodulation (PIM) is a common interference phenomenon in wireless communication systems, which means that under high-power excitation conditions, passive devices such as mesh antennas, duplexers, waveguides, flange connectors, and loads sometimes exhibit non-linear characteristics. When processing signals containing two or more different frequencies, additional signals will be generated at new frequencies (including non-harmonic frequencies). As technology advances towards 6G, satellite communication is also moving towards high-power and high-frequency systems, and the rapidly developing large-scale low-earth orbit satellite constellations have further exacerbated the congestion of space frequencies. The previous interference avoidance method based on frequency planning has become difficult to implement, and the PIM interference problem has become increasingly prominent. The space-air-ground integrated network architecture makes satellite communication and terrestrial communication increasingly adopt transceiver-sharing systems, with higher system integration, more common site-sharing phenomena, and gradually increasing receiver sensitivity.

[0003] Typical intermodulation products are much smaller in power than the normal signals output by passive devices and basically do not affect the transmission quality. However, for communication systems with high receiver sensitivity, once the PIM signal components of the transmitted signal fall into the uplink receiving frequency band, extremely adverse consequences will occur. It may lead to a significant deterioration of the receiver figure of merit and a decline in signal demodulation performance; in extreme cases, it may cause the receiving channel to be blocked, completely masking the effective uplink signal. Especially in systems using full-duplex devices, the power of PIM signals may sometimes exceed the thermal noise level and the isolation ability of the duplexer. Many spacecraft, ground communication base stations, airborne communication systems, and shipborne communication systems have encountered problems of passive intermodulation interfering with system operation during the operation stage. Suppressing passive intermodulation interference is an important research direction, but the generation mechanism of the PIM phenomenon is complex and diverse, and its interference signals have characteristics such as complex memory effects, strong time-variability, and multi-source characteristics, which all bring certain difficulties to the research of suppression methods. Especially in airborne communication systems, there are often many signals transmitted through fast time-varying channels. In such channels, the channel environment changes rapidly over time, resulting in the invalidation of channel estimation results in a short time. The characteristics of fast time-varying channels stem from the high-speed relative movement of the transceiver or scatterers in the communication scenario, causing significant changes in channel parameters in an extremely short time. The core characteristics of this channel are first reflected in the high-dynamic Doppler frequency shift. When the terminal or environmental object moves at a high speed (such as high-speed trains, drones, or low-earth orbit satellites), the signal carrier frequency will generate a fast time-varying frequency shift due to the Doppler effect, and its magnitude is proportional to the movement speed. In addition, fast time-varying channels have an extremely short coherence time, that is, the channel impulse response fails within the order of milliseconds or even microseconds. When the channel coherence time is much less than the signal symbol period, the traditional channel estimation method based on a fixed pilot interval will fail due to information obsolescence, forcing the system to adopt real-time tracking algorithms or dense pilot insertion to maintain link stability. Fast time-varying channels often accompany time-varying multipath fading, manifested as double-selective fading of the signal in the time and frequency dimensions. The time delay and attenuation coefficient of the multipath propagation path fluctuate rapidly due to the dynamic change of the environment, resulting in a sharp fluctuation of the received signal amplitude and a sharp rise in the bit error rate.

[0004] In response to the above problems, the prior art has proposed a PIM suppression method based on adaptive filtering, but this method has a slow convergence speed and insufficient suppression performance in fast time-varying channels; the prior art has also proposed using neural networks to predict PIM signals, but the computational complexity is relatively high, making it difficult to meet the real-time requirements of the airborne environment. In short, the prior art has not fully considered the characteristics of fast time-varying channels, resulting in problems of failure in fast time-varying scenarios. Summary of the Invention

[0005] The object of the present invention is to propose a passive intermodulation interference cancellation method, system and terminal for fast time-varying channels, aiming at the problem that the prior art does not fully consider the characteristics of fast time-varying channels, resulting in the invalidation of channel estimation results in fast time-varying scenarios. This solution decomposes the channel into a linear combination of several time-varying basis functions and corresponding time-invariant coefficients, estimates the characteristics of the time-varying channel, predicts the state of the future channel, can better cope with the influence of the time-varying channel, estimates the passive intermodulation interference signal after passing through the time-varying channel, and thus realizes the suppression of passive intermodulation interference.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In the first aspect, the present invention provides a passive intermodulation interference cancellation method for fast time-varying channels, including the following steps:

[0008] S1. Divide the signal to be transmitted into multiple transmitted signal segments, add a training sequence before each transmitted signal segment, a transmitted signal segment and the added training sequence form a signal group, and configure a basis function for each signal group;

[0009] S2. The receiving end obtains the received signal, which includes multiple received sequences corresponding one-to-one to the training sequences, and multiple received signal segments corresponding one-to-one to the transmitted signal segments;

[0010] S3. Based on the discrete ellipsoidal basis expansion model, calculate the estimated value of the time-invariant basis coefficient of each transmitted signal segment;

[0011] S4. At the position of each received signal segment, sample using the basis function of the signal group where the transmitted signal segment corresponding to this received signal segment is located, and obtain multiple sampled values of the received signal segments;

[0012] S5. Calculate the passive intermodulation interference signal of this received signal segment based on the estimated value of the time-invariant basis coefficient of the transmitted signal segment and the sampled value of the corresponding received signal segment;

[0013] S6. Subtract the passive intermodulation interference signal of each received signal segment from the received signal to achieve passive intermodulation interference cancellation.

[0014] As a possible implementation, S3 includes the following sub-steps:

[0015] S30. Based on the discrete ellipsoidal basis expansion model, use the basis function of the signal group where each transmitted signal segment is located to sample at the position of the received sequence corresponding to the training sequence in this signal group, and obtain multiple sampled values of the received sequences;

[0016] S31. Multiply each training sequence by the corresponding sampled value of the received sequence to obtain the coefficient of each basis function;

[0017] S32. Perform least - squares estimation on the coefficients of the basis functions of the signal group corresponding to each received sequence and the training sequence therein to obtain the time - invariant basis coefficient estimates of the transmitted signal segment.

[0018] As a possible implementation, S5 includes the following sub - steps:

[0019] S50. Multiply the time - invariant basis coefficient estimates of each transmitted signal segment by the sampled values of the received signal segment corresponding to this transmitted signal segment to obtain the channel parameters at the position where this received signal segment is located after fitting.

[0020] S51. Multiply this transmitted signal segment by the channel parameters at the position where this received signal segment is located after fitting to obtain the estimate of the passive inter - modulation interference signal of this received signal segment, which is the passive inter - modulation interference signal of this received signal segment.

[0021] As a possible implementation, the following method is used to obtain the received signal:

[0022] S rPIM = Ah + S n

[0023] where S n represents noise, represents the m - th received signal segment, h m represents the channel impulse response when the m - th training sequence is sent, A m represents the Toeplitz matrix formed by the m - th training sequence, and T represents the transpose.

[0024] As a possible implementation, the received signal S rPIM is represented by the following method:

[0025]

[0026] where A n,: represents the n - th row sequence of A, B m = [B m (1), …, B m (N)] represents the sampled values of the m - th basis function in the training sequence, b m = [b k,m , …, B ―k+1,m represents the coefficients of the m - th basis function,

[0027] As a possible implementation, the following method is used to calculate the time - invariant basis coefficient estimates of each transmitted signal segment:

[0028]

[0029] Among them, represents the time-invariant basis coefficient estimation value of the transmitted signal segment, represents the cost function, S rPIM represents the received signal, A m represents the Toeplitz matrix formed by the m-th training sequence, represents the augmented matrix of matrix A, T represents the transpose, and H represents the conjugate;

[0030] Let the partial derivative of the cost function with respect to be 0:

[0031]

[0032] Solve to obtain: Then the least squares estimation solution of is:

[0033]

[0034] As a possible implementation, the training sequence is a Zadoff-Chu sequence.

[0035] In a second aspect, the present invention provides a passive intermodulation interference cancellation system based on an extended model, including:

[0036] A signal group construction unit, configured to divide the signal to be transmitted into multiple transmitted signal segments, add a training sequence before each transmitted signal segment, a transmitted signal segment and a training sequence form a signal group, and configure a basis function for each signal group;

[0037] A time-invariant basis coefficient estimation value calculation unit, configured to calculate the time-invariant basis coefficient estimation value of each transmitted signal segment based on the discrete ellipsoidal basis expansion model;

[0038] A received signal segment sampling value calculation unit, configured to sample at the position of each received signal segment by using the basis function of the signal group where the transmitted signal segment corresponding to the received signal segment is located, to obtain multiple received signal segment sampling values;

[0039] A passive intermodulation interference signal reconstruction unit, configured to calculate the reconstructed passive intermodulation interference signal of the received signal segment based on the time-invariant basis coefficient estimation value of the transmitted signal segment and the corresponding received signal segment sampling value;

[0040] A passive intermodulation interference cancellation unit, configured to subtract the reconstructed passive intermodulation interference signal of each received signal segment from the received signal to achieve passive intermodulation interference cancellation.

[0041] In a third aspect, the present invention provides a terminal, including a processor and a communication interface coupled to the processor. The processor is configured to run a computer program or instruction to implement the method for passive intermodulation interference cancellation for fast time-varying channels provided in the first aspect.

[0042] Compared with the prior art, the beneficial effects produced by the present invention are as follows:

[0043] 1. The method for passive intermodulation interference cancellation for fast time-varying channels proposed by the present invention uses an extended model for PIM interference cancellation. Through experiments, it is verified that this method can effectively eliminate PIM interference and solve the problem that PIM interference is difficult to eliminate in fast time-varying channels.

[0044] 2. The method for passive intermodulation interference cancellation for fast time-varying channels proposed by the present invention can obtain estimated channel parameters by calculating time-invariant basis coefficients that remain unchanged and then multiplying them by basis functions. After that, the order of PM products in the received frequency band is estimated, a required matrix is constructed, and then multiplied by the obtained channel parameters to realize the reconstruction of PIM interference signals passing through fast time-varying channels, which is effectively applicable to PIM interference cancellation in fast time-varying channels.

[0045] 3. The method for passive intermodulation interference cancellation for fast time-varying channels proposed by the present invention uses a discrete ellipsoidal basis expansion model that does not require data-driven training, which can significantly reduce the variance and bias of the traditional periodogram method through multi-taper spectral analysis and is easier to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings described herein are used to provide a further understanding of the present invention and form a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0047] Figure 1 is a flowchart of the method for passive intermodulation interference cancellation for fast time-varying channels in an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of the principle of the method for passive intermodulation interference cancellation for fast time-varying channels in an embodiment of the present invention;

[0049] Figure 3 is a curve of the bit error rate performance of the communication system varying with the signal-to-noise ratio before and after adopting this method under the condition of SIR = -10dB in an embodiment of the present invention;

[0050] Figure 4 is a curve of the bit error rate performance of the communication system varying with the signal-to-interference ratio before and after adopting this method under the condition of SNR = 0dB in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] For the convenience of clearly describing the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish identical or similar items with basically the same functions and roles. For example, the first threshold and the second threshold are only used to distinguish different thresholds, and do not limit their sequence. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and the terms "first" and "second" do not necessarily limit being different.

[0052] It should be noted that in the present invention, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "exemplary" or "for example" aims to present relevant concepts in a specific way.

[0053] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. The following at least one (item) or its similar expression refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b or c can represent: 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 and c can be single or multiple.

[0054] The embodiments of the present invention aim to provide a method, system and terminal for passive intermodulation interference cancellation for fast time-varying channels. Fully considering the characteristics of fast time-varying channels, the channel is decomposed into a linear combination of several time-varying basis functions and corresponding time-invariant coefficients, the characteristics of the time-varying channel are estimated, the state of the future channel is predicted, and it can better cope with the influence of the time-varying channel, estimate the passive intermodulation interference signal after passing through the time-varying channel, so as to achieve the suppression of passive intermodulation interference.

[0055] In a first aspect, the embodiments of the present invention provide a method for passive intermodulation interference cancellation for fast time-varying channels, see Figure 1 , including the following steps:

[0056] S1. Divide the signal to be transmitted into multiple transmitted signal segments, add a training sequence before each transmitted signal segment, a transmitted signal segment and the added training sequence form a signal group, and configure a basis function for each signal group.

[0057] See Figure 2 , as an example, divide the signal to be transmitted into m segments of transmitted signals, which are respectively labeled as: transmitted signal segment 1, transmitted signal segment 2, transmitted signal segment 3... transmitted signal segment m, and add a training sequence before each segment of transmitted signal, correspondingly labeled as: training sequence 1, training sequence 2, training sequence 3... training sequence m. It should be noted that this solution does not make specific requirements on the length and quantity of the divided segments of transmitted signals, and any division method does not affect the realization of the effect of this solution.

[0058] As a possible implementation, the training sequence is a Zadoff-Chu sequence.

[0059] S2. The receiving end obtains the received signal, which includes multiple received sequences corresponding one by one to the training sequences, and multiple received signal segments corresponding one by one to the segments of transmitted signals.

[0060] See Figure 2 , as an example, divide the signal to be transmitted into m segments of transmitted signals, add a training sequence before each segment of transmitted signal, and then transmit it through the channel to the receiving end. The received signal at the receiving end includes received sequences corresponding one by one to the training sequences, that is, received sequence 1, received sequence 2, received sequence 3... received sequence m, and received signal segments corresponding one by one to the segments of transmitted signals, that is, received signal segment 1, received signal segment 2, received signal segment 3... received signal segment m.

[0061] S3. Based on the discrete prolate spheroidal basis expansion model, calculate the time-invariant basis coefficient estimation value of each segment of transmitted signal;

[0062] The discrete prolate spheroidal basis expansion model (DPS-BEM) is a signal model based on discrete prolate spheroidal sequences, aiming to perform an optimal energy concentration representation for signals with a limited time length and a limited frequency band. The discrete prolate spheroidal basis expansion model does not require data-driven training, can significantly reduce the variance and bias of the traditional periodogram method through multi-taper spectral analysis, and is simpler to implement.

[0063] As a possible implementation, S3 includes the following sub-steps:

[0064] S30. Based on the discrete prolate spheroidal basis expansion model, use the basis function of the signal group where each segment of transmitted signal is located to sample the position of the received sequence corresponding to the training sequence in this signal group, and obtain multiple received sequence sampling values;

[0065] As an example, for the i-th segment of transmitted signal, 1 ≤ i ≤ m, use the basis function i to sample the received sequence corresponding to the training sequence i, that is, the position of the received sequence i, and obtain the received sequence sampling value i.

[0066] S31. Multiply each training sequence by the corresponding received sequence samples to obtain the coefficients of each basis function;

[0067] As an example, multiply the training sequence i by the corresponding received sequence samples, that is, the samples i, to obtain the coefficient of the basis function i.

[0068] S32. Perform least squares estimation on each received sequence with the coefficients of the basis functions in the signal group where the corresponding training sequence is located to obtain the time-invariant basis coefficient estimates of the transmitted signal segment.

[0069] As an example, perform least squares estimation on the received sequence i with the coefficient of the basis function i to obtain the time-invariant basis coefficient estimate of the transmitted signal segment i.

[0070] The process of calculating the time-invariant basis coefficient estimates of the transmitted signal segment is as follows: First, the received signal obtained at the receiving end is:

[0071] S rPIM = Ah + S n

[0072] where S n represents noise, represents the m-th received signal segment, h m represents the channel impulse response when transmitting the m-th training sequence, A m represents the Toeplitz matrix formed by the m-th training sequence, and T represents the transpose.

[0073] The received signal S rPIM can be expressed as:

[0074]

[0075] where A n,: represents the n-th row sequence of A, B m = [B m (1), …, B m (N)] represents the sampling values of the m-th basis function in the training sequence, b m = [b k,m , …, B ―k+1,m represents the coefficient of the m-th basis function,

[0076] The time-invariant basis coefficient estimates of the transmitted signal segment are calculated using the cost function as follows:

[0077]

[0078] Among them, represents the time-invariant basis coefficient estimation value of the transmission signal segment, represents the cost function, S rPM represents the received signal, A m represents the Toeplitz matrix formed by the m-th training sequence, represents the augmented matrix of matrix A, T represents the transpose, and H represents the conjugate;

[0079] Let the partial derivative of the cost function with respect to be 0:

[0080]

[0081] Solve to obtain: Then the least squares estimation solution of

[0082]

[0083] S4. At the position where each received signal segment is located, sample using the basis function of the signal group where the corresponding transmitted signal segment is located to obtain multiple received signal segment sampling values;

[0084] As an example, for the received signal segment i, sample at the position where the received signal segment i is located using the basis function i to obtain the received signal segment sampling value i.

[0085] S5. Calculate the passive intermodulation interference signal of the received signal segment based on the time-invariant basis coefficient estimation value of the transmitted signal segment and the corresponding received signal segment sampling value;

[0086] As a possible implementation, S5 includes the following sub-steps:

[0087] S50. Multiply the time-invariant basis coefficient estimation value of each transmitted signal segment by the received signal segment sampling value corresponding to the transmitted signal segment to obtain the channel parameter at the position where the received signal segment is located;

[0088] As an example, multiply the time-invariant basis coefficient estimation value of the transmitted signal segment i by the corresponding received signal segment sampling value, that is, the received signal segment sampling value i, to obtain the channel parameter at the position where the received signal segment i is located.

[0089] S51. Multiply the transmitted signal segment by the channel parameter at the position where the received signal segment is located to obtain the estimated value of the passive intermodulation interference signal of the received signal segment, which is the passive intermodulation interference signal of the received signal segment.

[0090] As an example, multiply the transmitted signal segment i by the channel parameters at the position of the fitted received signal segment i to obtain the estimated value of the passive intermodulation interference signal of the received signal segment i.

[0091] S6. Subtract the passive intermodulation interference signal of each received signal segment from the received signal to achieve passive intermodulation interference cancellation.

[0092] As an example, subtract the estimated value of the passive intermodulation interference signal of the received signal segment i from the received signal segment i, and subtract the estimated values of all m passive intermodulation interference signals from all m received signal segments, achieving the effect of passive intermodulation interference cancellation.

[0093] In a second aspect, an embodiment of the present invention provides a passive intermodulation interference cancellation system based on an extended model, including:

[0094] A signal group construction unit, configured to divide the signal to be transmitted into multiple transmitted signal segments, add a training sequence before each transmitted signal segment, a transmitted signal segment and a training sequence form a signal group, and configure a basis function for each signal group;

[0095] A time-invariant basis coefficient estimated value calculation unit, configured to calculate the estimated value of the time-invariant basis coefficient of each transmitted signal segment based on the discrete ellipsoidal basis expansion model;

[0096] A received signal segment sampling value calculation unit, configured to sample at the position of each received signal segment using the basis function of the signal group where the transmitted signal segment corresponding to the received signal segment is located, to obtain multiple received signal segment sampling values;

[0097] A passive intermodulation interference signal reconstruction unit, configured to calculate the reconstructed passive intermodulation interference signal of the received signal segment based on the estimated value of the time-invariant basis coefficient of the transmitted signal segment and the corresponding received signal segment sampling value;

[0098] A passive intermodulation interference cancellation unit, configured to subtract the reconstructed passive intermodulation interference signal of each received signal segment from the received signal to achieve passive intermodulation interference cancellation.

[0099] In a third aspect, an embodiment of the present invention provides a terminal, including a processor and a communication interface coupled to the processor, where the processor is configured to run a computer program or instruction to implement the passive intermodulation interference cancellation method for a fast time-varying channel provided in the first aspect.

[0100] Next, use the MATLAB simulation platform to perform a simulation test on the passive intermodulation interference cancellation method for a fast time-varying channel proposed in this embodiment to further illustrate the effect of this solution.

[0101] In the simulation, a dual-carrier signal is used to reconstruct the PIM interference signal. To simplify the calculation, the power series model is used for the PIM signal model. It can be calculated that the PIM products falling within the receiving frequency band are the 7th, 9th, and 11th order products. The basis expansion model uses the discrete prolate spheroidal basis expansion model (DPS-BEM). All the parameters used in the simulation experiment are shown in Table 1:

[0102] Table 1 Simulation Experiment Parameters

[0103]

[0104] See Figure 3 , which is the curve of the system bit error rate varying with the signal-to-noise ratio after PIM cancellation using the passive intermodulation interference cancellation method for fast time-varying channels proposed in this embodiment. At this time, the signal-to-interference ratio is -10 dB. It can be seen from the figure that the bit error rate of the system has been significantly reduced. Considering the signal-to-noise ratio gain when the bit error rate is 10 -2 , the gain exceeds 4 dB. It is proved that this method can effectively reduce the impact of PIM on the communication system. Figure 4 Then, when the signal-to-noise ratio is 0 dB, it is the image of the system bit error rate varying with the signal-to-interference ratio before and after using this method. At this time, considering the signal-to-interference ratio gain when the bit error rate is 10 -2 , it can be seen that the signal-to-interference ratio gain exceeds 10 dB.

[0105] Although the present invention has been described in connection with various embodiments, however, in the process of implementing the claimed invention, those skilled in the art can understand and achieve other variations of the disclosed embodiments by viewing the drawings, the disclosure content, and the drawings' description. In the specification, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude the case of multiple. 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.

[0106] Although the present invention has been described in connection with specific features and their embodiments, obviously, various modifications and combinations can be made to it without departing from the spirit and scope of the present invention. Accordingly, this specification and the drawings are merely exemplary descriptions of the present invention and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of the present invention. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A method for passive intermodulation interference cancellation for fast time-varying channels, characterized in that It includes the following steps: S1. Divide the signal to be transmitted into multiple transmitted signal segments, add a training sequence before each transmitted signal segment. A transmitted signal segment and the added training sequence form a signal group, and configure a basis function for each signal group; S2. The receiving end obtains a received signal, which includes multiple received sequences corresponding one-to-one to the training sequences, and multiple received signal segments corresponding one-to-one to the transmitted signal segments; S3. Based on the discrete ellipsoidal basis expansion model, calculate the time-invariant basis coefficient estimation value of each transmitted signal segment; S4. At the position of each received signal segment, sample using the basis function of the signal group where the transmitted signal segment corresponding to this received signal segment is located, to obtain multiple received signal segment sampling values; S5. Based on the time-invariant basis coefficient estimation value of the transmitted signal segment and the corresponding received signal segment sampling value, calculate the passive intermodulation interference signal of this received signal segment; S6. Subtract the passive intermodulation interference signal of each received signal segment from the received signal to achieve passive intermodulation interference cancellation.

2. The passive intermodulation interference cancellation method for fast time-varying channels according to claim 1, wherein The S3 includes the following sub-steps: S30. Based on the discrete ellipsoidal basis expansion model, use the basis function of the signal group where each transmitted signal segment is located to sample at the position of the received sequence corresponding to the training sequence in this signal group, to obtain multiple received sequence sampling values; S31. Multiply each training sequence by the corresponding received sequence sampling value to obtain the coefficient of each basis function; S32. Perform least squares estimation on each received sequence and the coefficient of the basis function of the signal group where the corresponding training sequence is located to obtain the time-invariant basis coefficient estimation value of the transmitted signal segment.

3. The passive intermodulation interference cancellation method for fast time-varying channels according to claim 1, characterized in that The S5 includes the following sub-steps: S50. Multiply the time-invariant basis coefficient estimation value of each transmitted signal segment by the sampling value of the received signal segment corresponding to this transmitted signal segment to obtain the channel parameter fitted at the position of this received signal segment; S51. Multiply this transmitted signal segment by the channel parameter fitted at the position of this received signal segment to obtain the estimated value of the passive intermodulation interference signal of this received signal segment, which is the passive intermodulation interference signal of this received signal segment.

4. The passive intermodulation interference cancellation method for fast time-varying channels according to claim 1, characterized in that The received signal is obtained by the following method: S rPIM = Ah + S n Among them, S n represents noise, S rm represents the m-th received signal segment, h m represents the channel impulse response when transmitting the m-th training sequence, A m represents the Toeplitz matrix formed by the m-th training sequence, and T represents the transpose.

5. The passive intermodulation interference cancellation method for fast time-varying channels according to claim 4, characterized in that The received signal S is represented by the following method rPIM : Among them, A n,: represents the nth row sequence of A, and B m = [B m (1), …, B m (N)] represents the sampling values of the mth basis function in the training sequence, and b m = [b k,m , …, B ―k+1,m represents the coefficients of the mth basis function.

6. The passive intermodulation interference cancellation method for a fast time-varying channel according to claim 5, characterized in that, The time-invariant basis coefficient estimation value of each transmitted signal segment is calculated by the following method: Among them, represents the time-invariant basis coefficient estimation value of the transmitted signal segment, represents the cost function, S rPIM represents the received signal, A m represents the Toeplitz matrix formed by the m-th training sequence, represents the augmented matrix of matrix A, T represents the transpose, and H represents the conjugate; Set the partial derivative of the cost function with respect to to 0: Obtained by solving: Then The least squares estimation solution of is:

7. The method for passive intermodulation interference cancellation for fast time-varying channels according to claim 1, characterized in that The training sequence is a Zadoff-Chu sequence.

8. A passive intermodulation interference cancellation system based on an extended model, characterized in that, It includes: A signal group construction unit, which is used to divide the signal to be transmitted into multiple transmitted signal segments, add a training sequence before each transmitted signal segment. A transmitted signal segment and a training sequence form a signal group, and configure a basis function for each signal group; A time-invariant basis coefficient estimation value calculation unit, which is used to calculate the time-invariant basis coefficient estimation value of each transmitted signal segment based on the discrete ellipsoidal basis expansion model; A received signal segment sampling value calculation unit, which is used to sample at the position of each received signal segment using the basis function of the signal group where the transmitted signal segment corresponding to this received signal segment is located, to obtain multiple received signal segment sampling values; A passive intermodulation interference signal reconstruction unit, which is used to calculate the reconstructed passive intermodulation interference signal of this received signal segment based on the time-invariant basis coefficient estimation value of the transmitted signal segment and the corresponding received signal segment sampling value; A passive intermodulation interference cancellation unit is used to subtract the reconstructed passive intermodulation interference signal of each received signal segment from the received signal, so as to achieve passive intermodulation interference cancellation.

9. A terminal includes a processor and a communication interface coupled to the processor. The processor is configured to run a computer program or instruction to implement the passive intermodulation interference cancellation method for a fast time-varying channel according to any one of claims 1 to 7.

Images