WO2023050717A1 - 全双工数字自干扰消除方法及装置 - Google Patents

全双工数字自干扰消除方法及装置 Download PDF

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WO2023050717A1
WO2023050717A1 PCT/CN2022/078768 CN2022078768W WO2023050717A1 WO 2023050717 A1 WO2023050717 A1 WO 2023050717A1 CN 2022078768 W CN2022078768 W CN 2022078768W WO 2023050717 A1 WO2023050717 A1 WO 2023050717A1
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signal
link
interference signal
distortion processing
preamble sequence
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PCT/CN2022/078768
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English (en)
French (fr)
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赵艳艳
曹雯
谢敏娜
景焕
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深圳市中兴微电子技术有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/38—Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
    • H04B1/40—Circuits
    • H04B1/50—Circuits using different frequencies for the two directions of communication
    • H04B1/52—Hybrid arrangements, i.e. arrangements for transition from single-path two-direction transmission to single-direction transmission on each of two paths or vice versa
    • H04B1/525—Hybrid arrangements, i.e. arrangements for transition from single-path two-direction transmission to single-direction transmission on each of two paths or vice versa with means for reducing leakage of transmitter signal into the receiver

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  • Embodiments of the present disclosure relate to the field of communication technologies, and in particular to a full-duplex digital self-interference cancellation method and device.
  • SIC Self-Interference Clear
  • the main role of SIC in the propagation domain and the analog domain is to avoid the saturation of the receiver due to the high power of the SI signal.
  • the total power of the received signal exceeds the dynamic range of the ADC (digital-to-analog converter), which limits the accuracy after analog-to-digital conversion.
  • the significance of the digital domain is to eliminate residual SI signals.
  • the digital domain generally adopts an active SIC.
  • the auxiliary chain SIC is one of the active SIC technologies.
  • the auxiliary chain determines the performance of self-interfering signal cancellation. Therefore, how to improve the accuracy of auxiliary chain recovery from interference signal and the generality of the system is an urgent problem to be solved.
  • the disclosure provides a full-duplex digital self-interference cancellation method and device.
  • an embodiment of the present disclosure provides a full-duplex digital self-interference cancellation method, the method includes: before transmitting signals with the peer device in full-duplex mode, according to the preamble sequence sent by the sending link, the The preamble sequence calculates the first interference signal generated by the receiving link and the first reconstructed interference signal obtained by performing predistortion processing on the preamble sequence to obtain a predistortion processing coefficient; In the case of full-duplex signal transmission, perform pre-distortion processing on the first signal sent from the transmission link to the peer device according to the pre-distortion processing coefficient to obtain a second reconstructed interference signal; and according to the Self-interference cancellation is performed on the second reconstructed interference signal and the second interference signal of the receiving link, where the second interference signal of the receiving link is the interference signal generated by the first signal on the receiving link and the A signal obtained by receiving the superimposed second signal sent by the peer device received by the link.
  • the adaptive algorithm includes: least squares LS algorithm, recursive least squares RLS algorithm or least mean square error LMS algorithm.
  • the preamble sequence sent according to the sending link the first interference signal generated by the preamble sequence on the receiving link, and Perform pre-distortion processing on the preamble sequence to reconstruct the first reconstructed interference signal, and use an adaptive algorithm to calculate the pre-distortion processing coefficient, including: according to the current excitation signal in the preamble sequence and the current excitation signal.
  • the generated first interference signal and the current first reconstructed interference signal are used to calculate the current pre-distortion processing coefficient; wherein, the current first reconstructed interference signal is based on the pre-distortion processing coefficient obtained from the previous calculation.
  • pre-distortion processing and reconstruction Obtained by pre-distortion processing and reconstruction; in response to the fact that the iteration end condition is not satisfied, perform pre-distortion processing on the next excitation signal in the preamble sequence according to the current pre-distortion processing coefficient to obtain the next first reconstructed interference signal, so as to calculate The predistortion processing coefficient corresponding to the next excitation signal in the preamble sequence.
  • performing pre-distortion processing on the first signal sent by the transmission link to the peer device according to the pre-distortion processing coefficient to obtain a second reconstructed interference signal includes: responding to the end of the iteration When the condition is satisfied, perform predistortion processing on the first signal sent by the transmission link to the peer device according to the current predistortion processing coefficient, to obtain a second reconstructed interference signal.
  • the satisfaction of the iteration end condition includes: the current number of iterations is equal to the preset number, and the preset number is the same as the number of excitation signals in the preamble sequence; or, the current excitation signal has an impact on the receiving link
  • the difference between the generated first interference signal and the current first reconstructed interference signal is smaller than a preset threshold.
  • an embodiment of the present disclosure also provides a full-duplex digital self-interference cancellation device, including a transmission link, a reception link, an auxiliary link, an adaptive learning module, a pre-distortion processing module, and a self-interference cancellation module, wherein the The pre-distortion processing module is connected to the adaptive learning module, the auxiliary link and the self-interference cancellation module, and the adaptive learning module is connected to the sending link and the receiving link; the sending The link is configured to send the first signal to the peer device when transmitting signals with the peer device in a full-duplex manner; the receiving link is configured to transmit a first signal to the peer device in a full-duplex manner In the case of transmitting a signal, receiving a second signal sent by the peer device; the sending link is also configured to send a preamble sequence before transmitting a signal with the peer device in a full-duplex mode; the adaptive The learning module is configured to, before transmitting signals with the peer device in a full-duplex manner, according to
  • the auxiliary link has the same structure as the sending link, or the auxiliary link has the same structure as the receiving link.
  • the self-adaptive learning module is further configured to calculate the pre-distortion processing coefficients by using the least squares LS algorithm, the recursive least squares RLS algorithm or the least mean square error LMS algorithm.
  • the adaptive learning module is further configured to use the recursive least squares RLS algorithm or the least mean square error LMS algorithm to calculate the predistortion processing coefficient; wherein, according to the current excitation in the preamble sequence signal, the current excitation signal, and the first interference signal generated by the receiving link and the current first reconstruction interference signal to calculate the current pre-distortion processing coefficient, wherein the current first reconstruction interference signal is based on the pre-distortion obtained from the previous calculation
  • the processing coefficient is obtained by performing pre-distortion processing and reconstruction on the current excitation signal; the pre-distortion processing module and the auxiliary link are also configured to, in response to the iteration end condition not being satisfied, according to the current pre-distortion processing coefficient, The next excitation signal in the preamble sequence is subjected to predistortion processing to obtain the next first reconstructed interference signal, so that the adaptive learning module calculates the predistortion processing coefficient corresponding to the next excitation signal in the preamble sequence.
  • the pre-distortion processing module and the auxiliary link are further configured to, in response to the satisfaction of the iteration end condition, send the transmission link to the opposite end according to the current pre-distortion processing coefficient
  • the first signal sent by the device is subjected to pre-distortion processing to obtain a second reconstructed interference signal.
  • the satisfaction of the iteration end condition includes: the current number of iterations is equal to the preset number, and the preset number is the same as the number of excitation signals in the preamble sequence; or, the current excitation signal has an impact on the receiving link
  • the difference between the generated first interference signal and the current first reconstructed interference signal is smaller than a preset threshold.
  • the second interference signal is a signal obtained by superimposing the interference signal generated by the first signal on the receiving link and the second signal received by the receiving link and sent by the peer device.
  • the embodiments of the present disclosure support simultaneous and same-frequency full-duplex signal transmission and reception, and generate pre-distortion processing coefficients through adaptive learning.
  • the accuracy of the pre-distortion processing coefficient can be improved, so that the signal obtained after pre-distortion processing using the pre-distortion processing coefficient can offset the interference signal to the greatest extent, thereby improving the effect of full-duplex digital self-interference cancellation;
  • the pre-distortion processing coefficient has nothing to do with the preamble sequence, the sending link, the receiving link and the signal transmission environment, thus enhancing the flexibility and versatility of the system.
  • FIG. 1 is a schematic diagram of a full-duplex digital communication system architecture according to an embodiment of the present disclosure
  • FIG. 2 is a schematic flowchart of a full-duplex digital self-interference cancellation method provided by an embodiment of the present disclosure
  • FIG. 3 is a schematic flowchart of calculating and obtaining pre-distortion processing coefficients by using an adaptive algorithm provided by an embodiment of the present disclosure
  • FIG. 4 is a schematic diagram of a full-duplex digital self-interference cancellation device provided by an embodiment of the present disclosure
  • FIG. 5 is another schematic diagram of a full-duplex digital self-interference cancellation device provided by an embodiment of the present disclosure.
  • Embodiments described herein may be described with reference to plan views and/or cross-sectional views by way of idealized schematic illustrations of the present disclosure. Accordingly, the example illustrations may be modified according to manufacturing techniques and/or tolerances. Therefore, the embodiments are not limited to the ones shown in the drawings but include modifications of configurations formed based on manufacturing processes. Accordingly, the regions illustrated in the figures have schematic properties, and the shapes of the regions shown in the figures illustrate the specific shapes of the regions of the elements, but are not intended to be limiting.
  • An embodiment of the present disclosure provides a full-duplex digital self-interference cancellation method, and the method is applied to the system shown in FIG. 1 .
  • signals are transmitted between device A and device B in a full-duplex manner, and device A and device B are peer devices.
  • the transmission link (Tx) of device A sends a first signal to device B, and the first signal generates an interference signal SI1 to the Rx link of device A.
  • the receive link (Rx) of device A receives the second signal sent by device B.
  • the transmit link (Tx) of device B sends a second signal to device A, and the second signal generates an interference signal SI2 to the Rx link of device B.
  • the receive link (Rx) of device B receives the first signal sent by device A.
  • the full-duplex digital self-interference cancellation method provided by the embodiment of the present disclosure is applied to a device for full-duplex communication (that is, a full-duplex digital self-interference cancellation device).
  • a full-duplex digital self-interference cancellation device The structure of the full-duplex digital self-interference cancellation device is shown in Figure 4 It includes a transmission link (Tx), a reception link (Rx), an auxiliary link, an adaptive learning module, a pre-distortion processing module (DPD) and a self-interference cancellation module (SIC).
  • the pre-distortion processing module is connected with an adaptive learning module, an auxiliary link and a self-interference cancellation module (SIC).
  • the adaptive learning module is connected with the sending link and the receiving link.
  • the principle of full-duplex digital self-interference cancellation is as follows: copy the baseband IQ (In-phase Quadrature, in-phase quadrature) signal of the transmitted signal in the digital domain, and then use an additional transmitter chain (ie, the transmission chain) to generate the signal for the SIC The signal is fed back to the receiver (receive chain), which subtracts the reconstructed interfering signal generated by the auxiliary chain from the total signal.
  • baseband IQ In-phase Quadrature, in-phase quadrature
  • the full-duplex digital self-interference cancellation method includes the following steps:
  • Step 21 before transmitting signals with the peer device in full-duplex mode, according to the preamble sent by the sending link, the first interference signal generated by the preamble on the receiving link, and the first interference signal reconstructed by performing pre-distortion processing on the preamble - Reconstructing the interference signal, using an adaptive algorithm to calculate the pre-distortion processing coefficients.
  • the first transmission link of the device sends a preamble sequence X(n), and the preamble sequence X(n) includes multiple (n) consecutive excitation signals, During the process of sending the preamble sequence X(n), the excitation signal of the preamble sequence X(n) generates the first interference signal y ord1 to the receiving link.
  • the device and the peer device have not yet carried out signal transmission, therefore, only the first interference signal y ord1 generated by the preamble sequence X(n) is in the receiving link of the device .
  • the adaptive learning module uses an adaptive algorithm to calculate the pre-distortion processing coefficients according to the preamble sequence X(n) sent by the transmission link, the first interference signal y ord1 and the first reconstructed interference signal y aux1 , and The calculated pre-distortion processing coefficients are sent to the pre-distortion processing module (DPD).
  • the first reconstructed interference signal y aux1 is an interference signal obtained by performing pre-distortion processing on the preamble sequence X(n) by the pre-distortion processing module (DPD) and the auxiliary link.
  • the adaptive learning module can use the existing adaptive algorithm to calculate the pre-distortion processing coefficient.
  • the self-adaptive algorithm automatically adjusts the processing method, processing order, and processing parameters according to the data characteristics of the processed data during the processing and analysis process. , boundary conditions or constraints, so that it adapts to the statistical distribution characteristics and structural characteristics of the processed data, so as to obtain the best processing effect algorithm.
  • Step 22 In the case of full-duplex signal transmission with the peer device, perform pre-distortion processing on the first signal sent from the transmission link to the peer device according to the pre-distortion processing coefficient to obtain a second reconstructed interference signal.
  • the corresponding pre-distortion processing coefficients are adaptively learned, and the next stage can be entered, that is, the stage of full-duplex communication with the peer device.
  • the transmission link of the local device sends a first signal to the peer device, and the first signal is a useful signal without interference.
  • the first signal generates an interference signal y ord1-2 to the receiving link.
  • the pre-distortion processing module (DPD) and the auxiliary link perform pre-distortion processing on the first signal (that is, the loopback signal of the transmission link) according to the pre-distortion processing coefficient calculated in step 21, to obtain the second reconstructed interference signal y aux2 , the pre-distortion
  • the processing module (DPD) sends the second reconstructed interference signal y aux2 to the self-interference cancellation module (SIC), wherein the second reconstructed interference signal y aux2 is a reconstruction signal of the second interference signal y ord2 .
  • Step 23 perform self-interference cancellation according to the second reconstructed interference signal and the second interference signal of the receiving link, wherein the second interference signal of the receiving link is the interference signal generated by the first signal to the receiving link and received by the receiving link A signal obtained by superimposing the second signal sent by the peer device.
  • the self-interference cancellation module (SIC) of the device implements self-interference cancellation by subtracting the second reconstructed interference signal y aux2 from the second interference signal y ord2 of the receiving link, wherein the second interference signal of the receiving link
  • the signal yord2 is a signal obtained by superimposing the interference signal yord1-2 generated by the first signal on the receiving link and the second signal received by the receiving link and sent by the peer device.
  • the second reconstructed interference signal y aux2 can be offset as much as possible with the interference signal y ord1-2 generated by the first signal to the receiving link, so as to restore the second signal to the greatest extent.
  • the calculated pre-distortion processing coefficients are more accurate through self-adaptive learning of the pre-distortion processing coefficients, and correspondingly, the second signal can be accurately restored to improve the full-duplex digital self-interference cancellation effect.
  • the full-duplex digital self-interference cancellation method uses the preamble sequence sent by the transmission link and the first interference signal generated by the preamble sequence on the receiving link before transmitting signals with the peer device in full-duplex mode and the first reconstructed interference signal obtained by performing pre-distortion processing and reconstruction on the preamble sequence, using an adaptive algorithm to calculate the pre-distortion processing coefficient; in the case of transmitting signals with the peer device in full-duplex mode, according to the pre-distortion processing coefficient
  • the sending link performs pre-distortion processing on the first signal sent by the peer device to obtain a second reconstructed interference signal, and performs self-interference cancellation according to the second reconstructed interference signal and the second interference signal of the receiving link, and the second interference
  • the signal is a superimposed signal of the interference signal generated by the first signal on the receiving link and the second signal sent by the peer device received by the receiving link; the embodiment of the present disclosure supports simultaneous same-frequency full-duplex signal transmission and reception, And the
  • the accuracy of the pre-distortion processing coefficients can be improved, so that the signal obtained after pre-distortion processing using the pre-distortion processing coefficients can offset the interference signal to the greatest extent, thereby improving the full-duplex
  • the pre-distortion processing coefficient has nothing to do with the preamble sequence, transmission link, reception link and signal transmission environment, thus enhancing the flexibility and versatility of the system.
  • the adaptive algorithm may include: least squares LS algorithm, recursive least squares RLS algorithm or least mean square error LMS algorithm.
  • the RLS algorithm and the LMS algorithm need iteration, and the LS algorithm does not need iteration, but the LS algorithm needs to use a large amount of data for fitting, which is not conducive to hardware implementation.
  • the learning effect of the pre-distortion processing coefficient is better, which can be used as a comparison of other adaptive learning algorithms .
  • the RLS algorithm or the LMS algorithm is used to calculate the pre-distortion coefficient, as shown in FIG.
  • the signal and the first reconstructed interference signal obtained by performing pre-distortion processing and reconstruction on the leading sequence are calculated using an adaptive algorithm to obtain the pre-distortion processing coefficient (ie step 21), including the following steps:
  • Step 211 Calculate the current predistortion processing coefficient according to the current excitation signal in the preamble sequence, the first interference signal generated by the current excitation signal on the receiving link, and the current first reconstructed interference signal.
  • the current first reconstructed interference signal is obtained by performing pre-distortion processing and reconstruction on the current excitation signal according to the pre-distortion processing coefficient obtained from the previous calculation.
  • the sending link sends an excitation signal in the preamble sequence X(n)
  • the excitation signal generates a first interference signal y ord1 to the receiving link.
  • the adaptive learning module performs pre-distortion processing and reconstruction on the excitation signal according to the excitation signal, the first interference signal y ord1 generated by the excitation signal to the receiving link, and the pre-distortion processing coefficient obtained from the previous calculation to obtain Calculate the current pre-distortion processing coefficient of the first reconstructed interference signal y aux1 .
  • the predistortion processing coefficient calculated according to the current excitation signal is calculated based on the predistortion processing coefficient obtained from the previous excitation signal, that is, the result obtained in this iteration (that is, the current predistortion processing coefficient) is based on the previous
  • the second iteration result that is, the previous pre-distortion processing coefficient
  • Step 212 judging whether the iteration end condition is satisfied, if so, execute step 22 ; if not, execute step 213 .
  • the pre-distortion processing module and the auxiliary link judge whether the iteration end condition is satisfied, and if the iteration end condition is satisfied, the iteration is ended, and the currently calculated pre-distortion processing coefficient is used as the final self-interference cancellation.
  • the pre-distortion processing coefficient that is, according to the current pre-distortion processing coefficient, perform pre-distortion processing on the first signal sent by the transmission link to the peer device to obtain the second reconstruction interference signal (i.e. perform step 22); if the iteration end condition is not If it is satisfied, the iteration needs to be continued, and step 213 is executed.
  • Step 213 Perform predistortion processing on the next excitation signal in the preamble sequence according to the current predistortion processing coefficient to obtain the next first reconstructed interference signal, so as to calculate the predistortion processing coefficient corresponding to the next excitation signal in the preamble sequence.
  • the transmission link sends the next excitation signal (for example, the third excitation signal) of the preamble sequence, the predistortion processing module and the auxiliary link according to the second
  • the pre-distortion processing coefficient corresponding to the first excitation signal performs pre-distortion processing on the current third excitation signal to obtain the first reconstructed interference signal corresponding to the third excitation signal, and according to the third excitation signal and the third excitation signal
  • the first interference signal generated by the link and the first reconstructed interference signal corresponding to the third excitation signal are received, and the predistortion processing coefficient corresponding to the third excitation signal is calculated, that is, for the next iterative calculation.
  • step 212 is continued, that is, after each iterative calculation of the predistortion coefficients, it is necessary to judge whether the iteration end condition is met, so as to determine whether to end the iterative process.
  • the satisfaction of the iteration end condition includes: the current number of iterations is equal to the preset number, and the preset number is the same as the number of excitation signals in the preamble sequence; The difference between the first interference signal and the current first reconstructed interference signal is smaller than a preset threshold.
  • the pre-distortion processing coefficients are calculated for all (that is, n) excitation signals in the preamble sequence X(n)
  • the pre-distortion processing coefficient corresponding to the last excitation signal is used as the final pre-distortion processing coefficient, that is, after the preset number of iterations, no matter whether the current pre-distortion processing coefficients really converge, the iteration will end.
  • the predistortion processing coefficients have converged at this time, and the Even if the preset number of iterations has not been reached, the iteration ends.
  • the calculation process of the pre-distortion processing coefficients will be described below by taking the LS algorithm, the RLS algorithm, and the LMS algorithm as examples respectively.
  • the LS algorithm does not require iteration, but it needs to use a large amount of data for fitting, so it is not conducive to hardware implementation.
  • the adaptive learning effect is better, and it can be used as a comparison with other adaptive learning algorithms.
  • y si is the interference signal entering the digital side of the receiving chain, is the interference signal reconstructed by the pre-distortion processing module and the auxiliary link.
  • the pre-distortion processing coefficients may be calculated in a progressive iterative manner.
  • Both the RLS algorithm and the LMS algorithm belong to this iterative algorithm, and both can be used in the embodiments of the present disclosure.
  • the RLS algorithm and the LMS need to input different observation values. After each new observation data, on the basis of the previous estimation results, according to the recursive algorithm, the newly introduced observation data can be used to correct the previous estimation results. A new estimate of the parameter is thus derived.
  • e i (n) d i (n)-y i (n), wherein, e i (n) is an error, d i (n) is an expected value, and y i (n) is an estimated value;
  • ⁇ i is an error
  • the forgetting factor ⁇ is an integer less than 1.
  • the iterative equation of the RLS algorithm can be expressed as:
  • the LMS algorithm selects an appropriate convergence factor so that the error between the actual calculation result and the expected response searches downward along the steepest direction of the surface with each iteration.
  • e i (n) is the error
  • d i (n) is the expected value
  • y i (n) is the estimated value
  • E(h) is the error.
  • the iterative equation of the LMS algorithm can be expressed as:
  • the interference signal is reconstructed, and the pre-distortion processing coefficient is obtained through multiple iterative calculations using an adaptive learning technology, so that the pre-distortion processed signal can offset the interference signal to the greatest extent.
  • the embodiments of the present disclosure can enable radio equipment to realize a true same-frequency full-duplex mode, and effectively improve spectrum efficiency.
  • SI self-interference
  • the interference signal is reconstructed in the digital domain, and then the reconstructed interference signal is subtracted from the total received signal to achieve the purpose of eliminating interference.
  • Combining adaptive learning pre-distortion processing coefficients with pre-distortion processing improves the versatility of digital SIC (self-interference cancellation), uses adaptive learning algorithms to iterate multiple times, and finally achieves the desired digital SIC effect.
  • an embodiment of the present disclosure also provides a full-duplex digital self-interference cancellation device.
  • the full-duplex digital self-interference cancellation device includes a transmission link 101, a reception link 102, Auxiliary link 103, adaptive learning module 104, pre-distortion processing module 105 and self-interference elimination module 106, wherein the pre-distortion processing module 105 is connected with adaptive learning module 104, auxiliary link 103 and self-interference elimination module 106, Adaptive learning module 104 is connected with sending link 101 and receiving link 102 .
  • the sending link 101 is configured to send a first signal to the peer device when transmitting signals with the peer device in a full-duplex manner.
  • the receiving link 102 is configured to receive the second signal sent by the peer device when transmitting signals with the peer device in a full-duplex mode.
  • the sending link 101 is further configured to send a preamble before transmitting signals with the peer device in a full-duplex manner.
  • the adaptive learning module 104 is configured to, before transmitting signals with the peer device in a full-duplex manner, pre-order the first interference signal generated by the receiving link and the preamble sequence according to the preamble sequence sent by the transmission link, and the preamble sequence.
  • the first reconstructed interference signal obtained through distortion processing and reconstruction is calculated by using an adaptive algorithm to obtain pre-distortion processing coefficients.
  • the pre-distortion processing module 105 and the auxiliary link 103 are configured to perform pre-distortion processing and reconstruction on the preamble sequence to obtain the first reconstructed interference signal;
  • the processing coefficient performs predistortion processing on the first signal sent by the sending link 101 to the peer device to obtain a second reconstructed interference signal.
  • the self-interference cancellation module 106 is configured to perform self-interference cancellation according to the second reconstructed interference signal and the second interference signal of the receiving link, wherein the second interference signal received by the receiving link 102 is the first signal to the receiving link A signal obtained by superimposing the generated interference signal and the second signal received by the receiving link and sent by the peer device.
  • the structure of the auxiliary link 103 is the same as that of the sending link 101 , or the structure of the auxiliary link 103 is the same as that of the receiving link 102 .
  • the structure of the auxiliary link 103 is the same as that of the receiving link 102 as an example for illustration.
  • the auxiliary link 103 and the receiving link 102 may include: an analog-to-digital converter ADC, a low-pass filter (Low-pass filter, LPF) and a receiving link radio frequency module (Rx RF), wherein the receiving The link radio frequency module, the low-pass filter and the analog-to-digital converter are connected in sequence, the analog-to-digital converter is connected to the self-interference cancellation module 106 , and the receiving link radio frequency module is connected to the antenna of the receiving link 102 .
  • ADC analog-to-digital converter
  • LPF low-pass filter
  • Rx RF receiving link radio frequency module
  • Receive chain 102 can comprise: digital-to-analog converter DAC, low-pass filter and transmit link radio frequency module (Tx RF), wherein, transmit link radio frequency module, low-pass filter and digital-to-analog converter are connected in sequence, digital-to-analog The converter is connected to the pre-distortion processing module 105 , and the radio frequency module of the sending link is connected to the antenna of the sending link 101 .
  • Tx RF transmit link radio frequency module
  • the adaptive learning module 104 is configured to calculate the pre-distortion processing coefficients by using the least squares LS algorithm, the recursive least squares RLS algorithm or the least mean square error LMS algorithm.
  • the adaptive learning module 104 is configured to use the recursive least squares RLS algorithm or the least mean square error LMS algorithm to calculate the predistortion processing coefficients, wherein, according to the current excitation signal in the preamble sequence, The current excitation signal calculates the current pre-distortion processing coefficient for the first interference signal generated by the receiving link and the current first reconstruction interference signal, wherein the current first reconstruction interference signal is based on the pre-distortion processing coefficient obtained from the previous calculation It is obtained by performing pre-distortion processing on the current excitation signal and reconstructing it.
  • the pre-distortion processing module 105 and the auxiliary link 103 are configured to perform pre-distortion processing on the next excitation signal in the preamble sequence according to the current pre-distortion processing coefficient in response to the iteration end condition not being satisfied, to obtain the next The interference signal is reconstructed first, so that the adaptive learning module calculates the predistortion processing coefficient corresponding to the next excitation signal in the preamble sequence.
  • the pre-distortion processing module 105 and the auxiliary link 103 are further configured to, in response to the satisfaction of the iteration end condition, send the transmission link to the peer device according to the current pre-distortion processing coefficient
  • the first signal is subjected to pre-distortion processing to obtain a second reconstructed interference signal.
  • the satisfaction of the iteration end condition includes: the current number of iterations is equal to the preset number, and the preset number is the same as the number of excitation signals in the preamble sequence; or, the current excitation signal has an impact on the receiving link
  • the difference between the generated first interference signal and the current first reconstructed interference signal is smaller than a preset threshold.
  • full-duplex digital self-interference cancellation method and device described in the disclosed embodiments of the present invention compared with the prior art, it supports simultaneous and same-frequency full-duplex transmission and reception, and generates DPD pre-distortion processing coefficients through an adaptive learning module , which enhances the flexibility and versatility of the system.
  • the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be composed of several physical components. Components cooperate to execute.
  • Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit .
  • Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media).
  • computer storage media includes both volatile and nonvolatile media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. permanent, removable and non-removable media.
  • Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, tape, magnetic disk storage or other magnetic storage devices, or can Any other medium used to store desired information and which can be accessed by a computer.
  • communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media .

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Abstract

本公开提供一种全双工数字自干扰消除方法，包括：在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、前导序列对接收链路产生的第一干扰信号和对前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；在与对端设备采用全双工方式传输信号的情况下，根据预失真处理系数对发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号，并根据第二重建干扰信号和接收链路的第二干扰信号进行自干扰消除，第二干扰信号为第一信号对接收链路产生的干扰信号与接收链路接收到的由对端设备发送的第二信号叠加后的信号。本公开还提供一种全双工数字自干扰消除装置。

Description

全双工数字自干扰消除方法及装置
相关申请的交叉引用
本公开要求在2021年9月29日提交国家知识产权局、申请号为202111152888.7、发明名称为“全双工数字自干扰消除方法及装置”的中国专利申请的优先权，该申请的全部内容通过引用结合在本公开中。
技术领域
本公开的实施例涉及通信技术领域，具体涉及一种全双工数字自干扰消除方法及装置。
背景技术
随着无线通信***的发展，无线频谱资源越来越紧张，5G(5th Generation Mobile Communication Technology，第五代移动通信技术)等其他无线***需要为用户提供越来越来高的数据速率，以满足用户的接入服务需求。上一代移动通信主要使用半双工传输方式。在使用全双工时，发送/接收通常使用不同的频段。由于干扰的原因，无线电信号在同一频段进行发射和接收一般是不可能的。近年来全双工有了新含义：设备可以在相同的时间和相同的频率上进行发送和接收。实现全双工面临的主要挑战是自干扰(Self-Interference，SI)信号，即从发射链路泄漏到接收链路中的部分传输信号。然而，从总的接收信号中消除自干扰信号是非常困难的，需要从天线、射频、数字三个方面进行SIC(自干扰消除，Self-Interference Clear)。其中，SIC在传播域和模拟域中的主要作用是避免由于SI信号的高功率造成的接收机的饱和。接收信号的总功率超过ADC(数模转换器)的动态范围会限制模数转换后的精度。数字域的意义在于消除残余SI信号。数字域一般采取有源SIC。辅助链SIC是有源SIC技术之一。辅助链决定了自干扰信号消除的性能。因此，如何提高辅助链恢复自干扰信号的精确 度以及***的通用性是亟待解决的问题。
发明内容
本公开提供一种全双工数字自干扰消除方法及装置。
第一方面，本公开实施例提供一种全双工数字自干扰消除方法，所述方法包括：在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、所述前导序列对所述接收链路产生的第一干扰信号和对所述前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；在与对端设备采用全双工方式传输信号的情况下，根据所述预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号；以及根据所述第二重建干扰信号和所述接收链路的第二干扰信号进行自干扰消除，所述接收链路的第二干扰信号是所述第一信号对所述接收链路产生的干扰信号与所述接收链路接收到的由所述对端设备发送的第二信号叠加后的信号。
在一些实施实例中，所述自适应算法包括：最小二乘LS算法、递推最小二乘RLS算法或最小均方误差LMS算法。
在一些实施实例中，在所述自适应算法为RLS算法或LMS算法的情况下，所述根据发送链路发送的前导序列、所述前导序列对所述接收链路产生的第一干扰信号和对所述前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数，包括：根据所述前导序列中当前的激励信号、当前的激励信号对接收链路产生的第一干扰信号和当前的第一重建干扰信号，计算当前的预失真处理系数；其中，所述当前的第一重建干扰信号根据前次计算得到的预失真处理系数对当前的激励信号进行预失真处理重建得到；响应于迭代结束条件不满足，根据所述当前的预失真处理系数，对所述前导序列中下一个激励信号进行预失真处理，得到下一个第一重建干扰信号，以便计算所述前导序列中下一个激励信号对应的预失真处理系数。
在一些实施实例中，所述根据所述预失真处理系数对所述发送链路向 所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号，包括：响应于迭代结束条件满足，根据所述当前的预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
在一些实施实例中，所述迭代结束条件满足包括：当前的迭代次数等于预设次数，所述预设次数与所述前导序列中激励信号的数量相同；或者，当前的激励信号对接收链路产生的第一干扰信号与当前的第一重建干扰信号之差小于预设阈值。
又一方面，本公开实施例还提供全双工数字自干扰消除装置，包括发送链路、接收链路、辅助链路、自适应学习模块、预失真处理模块和自干扰消除模块，其中，所述预失真处理模块与所述自适应学习模块、所述辅助链路和所述自干扰消除模块相连，所述自适应学习模块与所述发送链路和所述接收链路相连；所述发送链路被配置成，在与对端设备采用全双工方式传输信号的情况下，向对端设备发送第一信号；所述接收链路被配置成，在与对端设备采用全双工方式传输信号的情况下，接收所述对端设备发送的第二信号；所述发送链路还被配置成，在与对端设备采用全双工方式传输信号之前，发送前导序列；所述自适应学习模块被配置成，在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、所述前导序列对所述接收链路产生的第一干扰信号和对所述前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；所述预失真处理模块和所述辅助链路被配置成，对所述前导序列进行预失真处理重建得到第一重建干扰信号；以及，在与对端设备采用全双工方式传输信号的情况下，根据所述预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号；所述自干扰消除模块被配置成，根据所述第二重建干扰信号和所述接收链路的第二干扰信号进行自干扰消除，所述接收链路的第二干扰信号是所述第一信号对所述接收链路产生的干扰信号与所述接收链路接收到的由所述对端设备发送的第二信号叠加后的信号。
在一些实施实例中，所述辅助链路的结构与所述发送链路的结构相同， 或者，所述辅助链路的结构与所述接收链路的结构相同。
在一些实施实例中，所述自适应学习模块还被配置成，采用最小二乘LS算法、递推最小二乘RLS算法或最小均方误差LMS算法计算得到预失真处理系数。
在一些实施实例中，所述自适应学习模块还被配置成，采用递推最小二乘RLS算法或最小均方误差LMS算法计算得到预失真处理系数；其中，根据所述前导序列中当前的激励信号、当前的激励信号对接收链路产生的第一干扰信号和当前的第一重建干扰信号，计算当前的预失真处理系数，其中，当前的第一重建干扰信号根据前次计算得到的预失真处理系数对当前的激励信号进行预失真处理重建得到；所述预失真处理模块和所述辅助链路还被配置成，响应于迭代结束条件不满足，根据所述当前的预失真处理系数，对所述前导序列中下一个激励信号进行预失真处理，得到下一个第一重建干扰信号，以便所述自适应学习模块计算所述前导序列中下一个激励信号对应的预失真处理系数。
在一些实施实例中，所述预失真处理模块和所述辅助链路还被配置成，响应于迭代结束条件满足，根据所述当前的预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
在一些实施实例中，所述迭代结束条件满足包括：当前的迭代次数等于预设次数，所述预设次数与所述前导序列中激励信号的数量相同；或者，当前的激励信号对接收链路产生的第一干扰信号与当前的第一重建干扰信号之差小于预设阈值。
根据本公开实施例提供的全双工数字自干扰消除方法，在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、前导序列对接收链路产生的第一干扰信号和对前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；在与对端设备采用全双工方式传输信号的情况下，根据预失真处理系数对发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号，并根据第二重建干扰信号和接收链路的第二干扰信号进行自干扰消除， 其中，第二干扰信号为第一信号对接收链路产生的干扰信号与接收链路接收到的由对端设备发送的第二信号叠加后的信号。本公开实施例支持同时同频全双工信号发送和接收，并通过自适应学习生成预失真处理系数。一方面，可以提高预失真处理系数的精确度，这样利用预失真处理系数进行预失真处理后得到的信号可以最大程度将干扰信号抵消，从而提高全双工数字自干扰消除效果；另一方面，预失真处理系数与前导序列、发送链路、接收链路以及信号传输环境无关，因此增强了***的灵活性和通用性。
附图说明
图1为本公开实施例的全双工数字通信***架构的示意图；
图2为本公开实施例提供的全双工数字自干扰消除方法的流程示意图；
图3为本公开实施例提供的采用自适应算法计算得到预失真处理系数的流程示意图；
图4为本公开实施例提供的全双工数字自干扰消除装置的示意图；
图5为本公开实施例提供的全双工数字自干扰消除装置的另一示意图。
具体实施方式
在下文中将参考附图更充分地描述示例实施例，但是所述示例实施例可以以不同形式来体现且不应当被解释为限于本文阐述的实施例。反之，提供这些实施例的目的在于使本公开透彻和完整，并将使本领域技术人员充分理解本公开的范围。
如本文所使用的，术语“和/或”包括一个或多个相关列举条目的任何和所有组合。
本文所使用的术语仅用于描述特定实施例，且不意欲限制本公开。如本文所使用的，单数形式“一个”和“该”也意欲包括复数形式，除非上下文另外清楚指出。还将理解的是，当本说明书中使用术语“包括”和/或“由……制成”时，指定存在所述特征、整体、步骤、操作、元件和/ 或组件，但不排除存在或添加一个或多个其他特征、整体、步骤、操作、元件、组件和/或其群组。
本文所述实施例可借助本公开的理想示意图而参考平面图和/或截面图进行描述。因此，可根据制造技术和/或容限来修改示例图示。因此，实施例不限于附图中所示的实施例，而是包括基于制造工艺而形成的配置的修改。因此，附图中例示的区具有示意性属性，并且图中所示区的形状例示了元件的区的具体形状，但并不旨在是限制性的。
除非另外限定，否则本文所用的所有术语(包括技术和科学术语)的含义与本领域普通技术人员通常理解的含义相同。还将理解，诸如那些在常用字典中限定的那些术语应当被解释为具有与其在相关技术以及本公开的背景下的含义一致的含义，且将不解释为具有理想化或过度形式上的含义，除非本文明确如此限定。
本公开实施例提供一种全双工数字自干扰消除方法，所述方法应用于如图1所示的***中。如图1所示，设备A与设备B之间通过全双工方式传输信号，设备A和设备B互为对端设备。设备A的发送链路(Tx)向设备B发送第一信号，第一信号对设备A的Rx链路产生干扰信号SI1。同时，设备A的接收链路(Rx)接收设备B发送的第二信号。设备B的发送链路(Tx)向设备A发送第二信号，第二信号对设备B的Rx链路产生干扰信号SI2。同时，设备B的接收链路(Rx)接收设备A发送的第一信号。
本公开实施例提供的全双工数字自干扰消除方法，应用于进行全双工通信的设备(即全双工数字自干扰消除装置)，全双工数字自干扰消除装置的结构如图4所示，包括发送链路(Tx)、接收链路(Rx)、辅助链路、自适应学习模块、预失真处理模块(DPD)和自干扰消除模块(SIC)。预失真处理模块与自适应学习模块、辅助链路和自干扰消除模块(SIC)相连，。自适应学习模块与发送链路和接收链路相连。全双工数字自干扰消除原理如下：在数字域中复制发射信号的基带IQ(In-phase Quadrature，同相正交)信号，然后使用附加的发射机链(即发送链路)生成用于SIC的信号并将其反馈给接收机(接收链路)，接收机从总的信号中减去辅助 链生成的重建的干扰信号。
结合图4和图2所示，根据本公开实施例所述的全双工数字自干扰消除方法包括以下步骤：
步骤21，在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、前导序列对接收链路产生的第一干扰信号和对前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数。
在本设备与对端设备采用全双工方式传输信号之前，本设备先的发送链路先发送前导序列X(n)，前导序列X(n)包括多个(n个)连续的激励信号，在发送前导序列X(n)的过程中，前导序列X(n)的激励信号对接收链路产生第一干扰信号y ord1。需要说的是，在发送前导序列X(n)阶段，本设备与对端设备尚未进行信号传输，因此，本设备的接收链路中只有前导序列X(n)产生的第一干扰信号y ord1。
在本步骤中，自适应学习模块据发送链路发送的前导序列X(n)、第一干扰信号y ord1和第一重建干扰信号y aux1，采用自适应算法计算得到预失真处理系数，并将计算得到预失真处理系数发送给预失真处理模块(DPD)。其中，第一重建干扰信号y aux1是预失真处理模块(DPD)和辅助链路对前导序列X(n)进行预失真处理重建得到的干扰信号。自适应学习模块可以采用现有的自适应算法计算预失真处理系数，自适应(self-adaptive)算法是在处理和分析过程中,根据处理数据的数据特征自动调整处理方法、处理顺序、处理参数、边界条件或约束条件,使其与所处理数据的统计分布特征、结构特征相适应,以取得最佳的处理效果的算法。
步骤22，在与对端设备采用全双工方式传输信号的情况下，根据预失真处理系数对发送链路向对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
前导序列X(n)发送完毕之后，相应的预失真处理系数也自适应学习得到，就可以进入下一阶段，即与对端设备进行全双工通信的阶段。
在本步骤中，在本设备与对端设备采用全双工方式传输信号的过程中， 本设备的发送链路向对端设备发送第一信号，第一信号为无干扰的有用信号。此时，第一信号对接收链路产生干扰信号y ord1-2。预失真处理模块(DPD)和辅助链路根据步骤21计算得到的预失真处理系数对第一信号(即发送链路的回环信号)进行预失真处理，得到第二重建干扰信号y aux2，预失真处理模块(DPD)将第二重建干扰信号y aux2发送给自干扰消除模块(SIC)，其中，第二重建干扰信号y aux2是对第二干扰信号y ord2的重建信号。
步骤23，根据第二重建干扰信号和接收链路的第二干扰信号进行自干扰消除，其中，接收链路的第二干扰信号是第一信号对接收链路产生的干扰信号与接收链路接收到的由对端设备发送的第二信号叠加后的信号。
在本步骤中，本设备的自干扰消除模块(SIC)通过将接收链路的第二干扰信号y ord2减去第二重建干扰信号y aux2实现自干扰消除，其中，接收链路的第二干扰信号y ord2是第一信号对接收链路产生的干扰信号y ord1-2与接收链路接收到的由对端设备发送的第二信号叠加后的信号。
根据本实施例，自干扰消除的过程表述为：接收链路的第二干扰信号y ord2-第二重建干扰信号y aux2＝第一信号对接收链路产生的干扰信号y ord1-2+第二信号-第二重建干扰信号y aux2。由此可以看出，第二重建干扰信号y aux2基于预失真处理系数得到。若预失真处理系数准确、合理，那么第二重建干扰信号y aux2越接近第一信号对接收链路产生的干扰信号y ord1-2。在经过自干扰消除后，可以尽可能将第二重建干扰信号y aux2与第一信号对接收链路产生的干扰信号y ord1-2相抵消，从而最大程度还原第二信号。而本公开实施例通过自适应学习预失真处理系数，计算得到的预失真处理系数精确度更高，相应可以准确还原第二信号，提高全双工数字自干扰消除效果。
本公开实施例提供的全双工数字自干扰消除方法，在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、前导序列对接收链路产生的第一干扰信号和对前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；在与对端设备采用全双工方式传输信号的情况下，根据预失真处理系数对发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号， 并根据第二重建干扰信号和接收链路的第二干扰信号进行自干扰消除，第二干扰信号为第一信号对接收链路产生的干扰信号与接收链路接收到的由对端设备发送的第二信号叠加后的信号；本公开实施例支持同时同频全双工信号发送和接收，并通过自适应学习生成预失真处理系数，一方面，可以提高预失真处理系数的精确度，这样利用预失真处理系数进行预失真处理后得到的信号可以最大程度将干扰信号抵消，从而提高全双工数字自干扰消除效果；另一方面，预失真处理系数与前导序列、发送链路、接收链路以及信号传输环境无关，因此增强了***的灵活性和通用性。
在一些实施例中，自适应算法可以包括：最小二乘LS算法、递推最小二乘RLS算法或最小均方误差LMS算法。RLS算法和LMS算法需要迭代，LS算法不需要迭代，但是LS算法需要使用大量的数据做拟合，不利于硬件实现，预失真处理系数的学习效果比较好，可以作为其他自适应学习算法的对照。
在一些实施例中，在采用RLS算法或LMS算法计算预失真处理系数的情况下，如图3所示，所述根据发送链路发送的前导序列、前导序列对接收链路产生的第一干扰信号和对前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数(即步骤21)，包括以下步骤：
步骤211，根据前导序列中当前的激励信号、当前的激励信号对接收链路产生的第一干扰信号和当前的第一重建干扰信号，计算当前的预失真处理系数。
当前的第一重建干扰信号根据前次计算得到的预失真处理系数对当前的激励信号进行预失真处理重建得到。发送链路发送前导序列X(n)中的一个激励信号后，该激励信号对接收链路产生第一干扰信号y ord1。
在本步骤中，自适应学习模块根据该激励信号、该激励信号对接收链路产生的第一干扰信号y ord1和根据前次计算得到的预失真处理系数对该激励信号进行预失真处理重建得到的第一重建干扰信号y aux1，计算当前的预失真处理系数。也就是说，根据当前的激励信号计算得到的预失真处理系数是基于前一个激励信号计算得到的预失真处理系数计算的，即本次迭代 得到的结果(即当前的预失真处理系数)基于前次迭代结果(即前一次的预失真处理系数)计算，这样通过不断迭代才能得到最优的预失真处理系数。
步骤212，判断迭代结束条件是否满足，若满足，则执行步骤22；若不满足，则执行步骤213。
在针对前导序列X(n)中的一个激励信号计算得到该激励信号对应的预失真处理系数之后，一次迭代过程结束。在本步骤中，预失真处理模块和辅助链路判断迭代结束条件是否满足，若迭代结束条件满足，则结束迭代，将当前计算得到的预失真处理系数作为最终的用于进行自干扰消除所使用的预失真处理系数，即根据当前的预失真处理系数对发送链路向对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号(即执行步骤22)；若迭代结束条件不满足，则需要继续迭代，则执行步骤213。
步骤213，根据当前的预失真处理系数，对前导序列中下一个激励信号进行预失真处理，得到下一个第一重建干扰信号，以便计算前导序列中下一个激励信号对应的预失真处理系数。
在本步骤中，在判断出迭代结束条件不满足，且发送链路发送了前导序列的下一个激励信号(例如第3个激励信号)的情况下，预失真处理模块和辅助链路根据第2个激励信号对应的预失真处理系数对当前的第3个激励信号进行预失真处理，得到第3个激励信号对应的第一重建干扰信号，并根据第3个激励信号、第3个激励信号对接收链路产生的第一干扰信号和第3个激励信号对应的第一重建干扰信号，计算第3个激励信号对应的预失真处理系数，即以便进行下一次迭代计算。
需要说明的是，在执行完步骤213之后，继续执行步骤212，也就是说，每进行一次预失真处理系数的迭代计算之后，都需要判断是否满足迭代结束条件，以确定是否结束迭代过程。
针对前导序列X(n)中的一个激励信号计算得到一个预失真处理系数，完成一次迭代计算，本次迭代计算依赖于前一次迭代计算的结果，直至迭代计算的结构(即预失真处理系数)逐渐收敛，从而自适应学习得到 精确的预失真处理系数。
在一些实施例中，所述迭代结束条件满足包括：当前的迭代次数等于预设次数，预设次数与所述前导序列中激励信号的数量相同；或者，当前的激励信号对接收链路产生的第一干扰信号与当前的第一重建干扰信号之差小于预设阈值。也就是说，针对前导序列X(n)中的全部(即n个)激励信号均计算了预失真处理系数之后，迭代结束，将最后一个激励信号对应的预失真处理系数作为最终的预失真处理系数，即迭代了预设次数之后，无论当前的预失真处理系数是否真正收敛，都结束迭代。或者，一旦某个激励信号对接收链路产生的第一干扰信号y ord1与该激励信号对应的第一重建干扰信号y aux1之差小于预设阈值，说明此时预失真处理系数已经收敛，此时即使尚未达到预设的迭代次数，也结束迭代。
为清楚说明本公开实施例的方案，下面分别以LS算法、RLS算法和LMS算法为例对预失真处理系数的计算过程进行说明。
(1)LS算法
LS算法不需要迭代，但是需要使用大量的数据做拟合，因此不利于硬件实现，自适应学习效果比较好，可以作为其他自适应学习算法的对照。
∑[f(x,h(0),h(1),...,h(n-1))-y] 2＝min；其中，x为输入值，y为期望值。
Figure PCTCN2022078768-appb-000001
其中，y si是进入到接收链路数字侧的干扰信号，
Figure PCTCN2022078768-appb-000002
是经过预失真处理模块和辅助链路重建的干扰信号。
为方便硬件实现，可以取渐进迭代的方式来计算预失真处理系数，RLS算法和LMS算法都属于这种迭代算法，都可以在本公开实施例中使用。RLS算法与LMS需要输入不同的观测值，其可以在每一次新的观测数据后，就在前次估计结果的基础上，根据递推算法利用新引入的观测数据对前次估计结果进行修正，从而推出参数的新的估计值。
(2)RLS算法
Figure PCTCN2022078768-appb-000003
e i(n)＝d i(n)-y i(n)，其中，e i(n)为误差，d i(n)为期望值，y i(n)为估计值；
Figure PCTCN2022078768-appb-000004
Figure PCTCN2022078768-appb-000005
Figure PCTCN2022078768-appb-000006
其中，ε i为误差，遗忘因子λ为小于1的整数。
因为λ是小于1的整数，越早的结果权重越小。对h求偏导，整理可得到：
Figure PCTCN2022078768-appb-000007
定义：
Figure PCTCN2022078768-appb-000008
Figure PCTCN2022078768-appb-000009
R iw＝P i
Figure PCTCN2022078768-appb-000010
P i+1＝λP i+d i+1x i+1。
定义：
Figure PCTCN2022078768-appb-000011
RLS算法迭代方程可以表述为：
h i＝h i-1+k ie i|i-1；其中，
Figure PCTCN2022078768-appb-000012
(3)LMS算法
LMS算法是选取合适的收敛因子，使得实际计算结果与期望响应的误差随着每一次迭代沿曲面最陡方向向下搜索。
Figure PCTCN2022078768-appb-000013
Figure PCTCN2022078768-appb-000014
e i(n)＝d i(n)-y i(n)；
Figure PCTCN2022078768-appb-000015
其中，e i(n)为误差，d i(n)为期望值，y i(n)为估计值。
Figure PCTCN2022078768-appb-000016
Figure PCTCN2022078768-appb-000017
其中，E(h)为误差。
Figure PCTCN2022078768-appb-000018
h i+1＝h i+u*g＝h i+u*e*x。
LMS算法的迭代方程可以表述为：
Figure PCTCN2022078768-appb-000019
其中，
Figure PCTCN2022078768-appb-000020
Figure PCTCN2022078768-appb-000021
Figure PCTCN2022078768-appb-000022
本公开实施例通过重建干扰信号，并采用自适应学习技术通过多次迭代计算得到预失真处理系数，使得经过预失真处理的信号可以最大程度的将干扰信号抵消。本公开实施例可使无线电设备能够实现真正的同频全双工模式，有效提高频谱效率。针对5G等无线全双工通信***中SI(自干扰)信号，在数字域通过重建干扰信号，然后在总的接收信号中减去该重建的干扰信号，以达到消除干扰的目的。将自适应学习预失真处理系数和预失真处理相结合，提高数字SIC(自干扰消除)的通用性，利用自适应学习算法迭代多次，最终达到期望的数字SIC效果。
基于相同的技术构思，本公开实施例还提供一种全双工数字自干扰消除装置，如图4所示，所述全双工数字自干扰消除装置包括发送链路101、 接收链路102、辅助链路103、自适应学习模块104、预失真处理模块105和自干扰消除模块106，其中，预失真处理模块105与自适应学习模块104、辅助链路103和自干扰消除模块106相连，自适应学习模块104与发送链路101和接收链路102相连。
发送链路101被配置成，在与对端设备采用全双工方式传输信号的情况下，向对端设备发送第一信号。
接收链路102被配置成，在与对端设备采用全双工方式传输信号的情况下，接收对端设备发送的第二信号。
发送链路101进一步被配置成，在与对端设备采用全双工方式传输信号之前，发送前导序列。
自适应学习模块104被配置成，在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、前导序列对接收链路产生的第一干扰信号和对前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数。
预失真处理模块105和辅助链路103被配置成，对前导序列进行预失真处理重建得到第一重建干扰信号；以及，在与对端设备采用全双工方式传输信号的情况下，根据预失真处理系数对发送链路101向对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
自干扰消除模块106被配置成，根据第二重建干扰信号和接收链路的第二干扰信号进行自干扰消除，其中，接收链路102接收到的第二干扰信号是第一信号对接收链路产生的干扰信号与接收链路接收到的由对端设备发送的第二信号叠加后的信号。
在一些实施例中，辅助链路103的结构与发送链路101的结构相同，或者，辅助链路103的结构与接收链路102的结构相同。
在本公开实施例中，以辅助链路103的结构与接收链路102的结构相同为例进行说明。如图5所示，辅助链路103和接收链路102可以包括：模数转换器ADC、低通滤波器(Low-pass filter，LPF)和接收链路射频模块(Rx RF)，其中，接收链路射频模块、低通滤波器和模数转换器依次连 接，模数转换器与自干扰消除模块106相连，接收链路射频模块与接收链路102的天线相连。
接收链路102可以包括：数模转换器DAC、低通滤波器和发送链路射频模块(Tx RF)，其中，发送链路射频模块、低通滤波器和数模转换器依次连接，数模转换器与预失真处理模块105相连，发送链路射频模块与发送链路101的天线相连。
在一些实施例中，自适应学习模块104被配置成，采用最小二乘LS算法、递推最小二乘RLS算法或最小均方误差LMS算法计算得到预失真处理系数。
在一些实施例中，自适应学习模块104被配置成，采用递推最小二乘RLS算法或最小均方误差LMS算法计算得到预失真处理系数，其中，根据所述前导序列中当前的激励信号、当前的激励信号对接收链路产生的第一干扰信号和当前的第一重建干扰信号，计算当前的预失真处理系数，其中，当前的第一重建干扰信号根据前次计算得到的预失真处理系数对当前的激励信号进行预失真处理重建得到。
预失真处理模块105和辅助链路103被配置成，响应于迭代结束条件不满足，根据所述当前的预失真处理系数，对所述前导序列中下一个激励信号进行预失真处理，得到下一个第一重建干扰信号，以便所述自适应学习模块计算所述前导序列中下一个激励信号对应的预失真处理系数。
在一些实施例中，预失真处理模块105和辅助链路103还被配置成，响应于迭代结束条件满足，根据所述当前的预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
在一些实施例中，所述迭代结束条件满足包括：当前的迭代次数等于预设次数，所述预设次数与所述前导序列中激励信号的数量相同；或者，当前的激励信号对接收链路产生的第一干扰信号与当前的第一重建干扰信号之差小于预设阈值。
采用本发公开实施例所述的全双工数字自干扰消除方法和装置，与现 有技术相比，支持同时同频全双工发送和接收，并通过自适应学习模块产生DPD预失真处理系数，增强了***的灵活性和通用性。
本领域普通技术人员可以理解，上文中所公开方法中的全部或某些步骤、装置中的功能模块/单元可以被实施为软件、固件、硬件及其适当的组合。在硬件实施方式中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理组件的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些物理组件或所有物理组件可以被实施为由处理器，如中央处理器、数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被实施为集成电路，如专用集成电路。这样的软件可以分布在计算机可读介质上，计算机可读介质可以包括计算机存储介质(或非暂时性介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的，术语计算机存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、程序模块或其他数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其他存储器技术、CD-ROM、数字多功能盘(DVD)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其他的介质。此外，本领域普通技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其他传输机制之类的调制数据信号中的其他数据，并且可包括任何信息递送介质。
本文已经公开了示例实施例，并且虽然采用了具体术语，但它们仅用于并仅应当被解释为一般说明性含义，并且不用于限制的目的。在一些实例中，对本领域技术人员显而易见的是，除非另外明确指出，否则可单独使用与特定实施例相结合描述的特征、特性和/或元素，或可与其他实施例相结合描述的特征、特性和/或元件组合使用。因此，本领域技术人员将理解，在不脱离由所附的权利要求阐明的本发明的范围的情况下，可进行各种形式和细节上的改变。

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  1. 一种全双工数字自干扰消除方法，所述方法包括：
    在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、所述前导序列对所述接收链路产生的第一干扰信号和对所述前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；
    在与对端设备采用全双工方式传输信号的情况下，根据所述预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号；以及
    根据所述第二重建干扰信号和所述接收链路的第二干扰信号进行自干扰消除，所述接收链路的第二干扰信号是所述第一信号对所述接收链路产生的干扰信号与所述接收链路接收到的由所述对端设备发送的第二信号叠加后的信号。
  2. 如权利要求1所述的方法，其中，所述自适应算法包括：最小二乘LS算法、递推最小二乘RLS算法或最小均方误差LMS算法。
  3. 如权利要求2所述的方法，其中，在所述自适应算法为RLS算法或LMS算法的情况下，所述根据发送链路发送的前导序列、所述前导序列对所述接收链路产生的第一干扰信号和对所述前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数，包括：
    根据所述前导序列中当前的激励信号、当前的激励信号对接收链路产生的第一干扰信号和当前的第一重建干扰信号，计算当前的预失真处理系数；其中，所述当前的第一重建干扰信号根据前次计算得到的预失真处理系数对当前的激励信号进行预失真处理重建得到；以及
    响应于迭代结束条件不满足，根据所述当前的预失真处理系数，对所 述前导序列中下一个激励信号进行预失真处理，得到下一个第一重建干扰信号，以便计算所述前导序列中下一个激励信号对应的预失真处理系数。
  4. 如权利要求3所述的方法，其中，所述根据所述预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号，包括：
    响应于迭代结束条件满足，根据所述当前的预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
  5. 如权利要求3所述的方法，其中，所述迭代结束条件满足包括：
    当前的迭代次数等于预设次数，所述预设次数与所述前导序列中激励信号的数量相同；或者，当前的激励信号对接收链路产生的第一干扰信号与当前的第一重建干扰信号之差小于预设阈值。
  6. 一种全双工数字自干扰消除装置，包括发送链路、接收链路、辅助链路、自适应学习模块、预失真处理模块和自干扰消除模块，其中，所述预失真处理模块与所述自适应学习模块、所述辅助链路和所述自干扰消除模块相连，所述自适应学习模块与所述发送链路和所述接收链路相连；
    所述发送链路被配置成，在与对端设备采用全双工方式传输信号的情况下，向对端设备发送第一信号；
    所述接收链路被配置成，在与对端设备采用全双工方式传输信号的情况下，接收所述对端设备发送的第二信号；
    所述发送链路进一步被配置成，在与对端设备采用全双工方式传输信号之前，发送前导序列；
    所述自适应学习模块被配置成，在与对端设备采用全双工方式传输信号之前，根据发送链路发送的前导序列、所述前导序列对所述接收链路产 生的第一干扰信号和对所述前导序列进行预失真处理重建得到的第一重建干扰信号，采用自适应算法计算得到预失真处理系数；
    所述预失真处理模块和所述辅助链路被配置成，对所述前导序列进行预失真处理重建得到第一重建干扰信号；以及，在与对端设备采用全双工方式传输信号的情况下，根据所述预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号；
    所述自干扰消除模块被配置成，根据所述第二重建干扰信号和所述接收链路的第二干扰信号进行自干扰消除，所述接收链路的第二干扰信号是所述第一信号对所述接收链路产生的干扰信号与所述接收链路接收到的由所述对端设备发送的第二信号叠加后的信号。
  7. 如权利要求6所述的装置，其中，所述辅助链路的结构与所述发送链路的结构相同，或者，所述辅助链路的结构与所述接收链路的结构相同。
  8. 如权利要求6所述的装置，其中，所述自适应学习模块用于，采用最小二乘LS算法、递推最小二乘RLS算法或最小均方误差LMS算法计算得到预失真处理系数。
  9. 如权利要求8所述的装置，其中，所述自适应学习模块还被配置成，采用递推最小二乘RLS算法或最小均方误差LMS算法计算得到预失真处理系数；其中，根据所述前导序列中当前的激励信号、当前的激励信号对接收链路产生的第一干扰信号和当前的第一重建干扰信号，计算当前的预失真处理系数，其中，当前的第一重建干扰信号根据前次计算得到的预失真处理系数对当前的激励信号进行预失真处理重建得到；
    所述预失真处理模块和所述辅助链路还被配置成，响应于迭代结束条件不满足，根据所述当前的预失真处理系数，对所述前导序列中下一个激励信号进行预失真处理，得到下一个第一重建干扰信号，以便所述自适应 学习模块计算所述前导序列中下一个激励信号对应的预失真处理系数。
  10. 如权利要求9所述的装置，其中，所述预失真处理模块和所述辅助链路还被配置成，响应于迭代结束条件满足，根据所述当前的预失真处理系数对所述发送链路向所述对端设备发送的第一信号进行预失真处理，得到第二重建干扰信号。
  11. 如权利要求9所述的装置，其中，所述迭代结束条件满足包括：
    当前的迭代次数等于预设次数，所述预设次数与所述前导序列中激励信号的数量相同；或者，当前的激励信号对接收链路产生的第一干扰信号与当前的第一重建干扰信号之差小于预设阈值。
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