Method and device for calibrating sampling error of multi-channel radio frequency transceiver

Abstract

The present invention proposes a calibration method for sampling errors of a multi-channel radio frequency transceiver, comprising the following steps: using input signals of M parallel-sampled sub-radio frequency channels of an error model of a sampling system to determine whether the M parallel-sampled sub-radio frequency channels of the error model of the sampling system have bias errors, gain errors and time errors; if so, calibrating the bias errors, gain errors and time errors; effectively solving the sampling error problem generated in the process of splicing multi-channel radio frequency signals, and improving the performance and accuracy of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of radio frequency transceivers, and in particular to a method and device for calibrating sampling errors of a multi-channel radio frequency transceiver. Background Art

[0002] Existing multi-channel RF transceiver systems usually use multiple independent RF modules to achieve broadband signal coverage. These systems achieve preliminary signal splicing through hardware design and basic software algorithms, but there are obvious splicing errors when faced with high-precision requirements. In terms of time synchronization, in order to reduce time deviations in multi-channel systems, the existing technology uses high-precision synchronization clocks and calibration signals to achieve time synchronization of each channel. However, due to the existence of clock jitter and signal delay, time synchronization still has certain errors, especially in high-speed and wide-band applications, the error problem is particularly prominent.

[0003] In terms of phase and amplitude calibration technology, phase and amplitude calibration technology is mainly achieved by pre-calibrating each channel before the system is operated. However, this method relies on calibration data in a laboratory environment, and the calibration effect will be affected when the system is operated in different environments. In addition, the pre-calibration method is difficult to adapt to the dynamic changes of the system during actual operation. In terms of temperature compensation, temperature compensation technology reduces the impact of temperature changes on system performance by adding temperature sensors and compensation circuits to the hardware design. However, this method can only alleviate the impact of temperature changes to a certain extent. For complex multi-channel RF systems, more sophisticated calibration methods are still required.

[0004] In terms of digital signal processing technology, digital signal processing (DSP) technology is widely used in modern RF systems to reduce system errors by digitally filtering, equalizing and correcting sampled data. However, the existing DSP algorithms still face the problems of high processing complexity and high real-time requirements when processing multi-channel splicing signals, and it is difficult to completely eliminate all splicing errors. Combining the above-mentioned prior arts, it can be seen that the existing methods have obvious deficiencies in the calibration of splicing sampling errors in multi-channel RF transceiver systems and cannot meet the requirements of high-precision and high-reliability systems.

[0005] In view of this, it is necessary to provide a novel multi-channel RF transceiver sampling error calibration method and device to overcome the above-mentioned defects. Summary of the invention

[0006] The purpose of the present invention is to provide a method and device for calibrating sampling errors of a multi-channel RF transceiver, which effectively solves the sampling error problem generated in the process of splicing multi-channel RF signals and improves the performance and accuracy of the system.

[0007] The technical solution provided by the present invention is implemented as follows: a method for calibrating sampling errors of a multi-channel radio frequency transceiver, characterized in that it comprises the following steps:

[0008] Take x(t) as the input signal of the M parallel sampled sub-RF channels of the error model of the sampling system,

[0009] Determine whether there are bias errors, gain errors and time errors in the M parallel-sampled sub-RF channels of the error model of the sampling system;

[0010] If present, the offset error, gain error and time error are calibrated.

[0011] If it exists, the sample output of the Mth channel is:

[0012] y m [n] = G m x((nM+m)T s -ΔT m )+O m (1)

[0013] The total quantified output of the sampling system is:

[0014]

[0015] Set the input signal to a sinusoidal signal:

[0016]

[0017] In the above formula (3), A is the input signal amplitude, Ω0 is the angular frequency, Represents the phase, and then (nM+m)=k, ω0=Ω0T S , the frequency domain expression is:

[0018]

[0019] The sinusoidal input signal x a (t) is grounded, and the offset of the sub-RF channel is obtained from the quantized output of the multi-channel RF transceiver. The actual sampling time of the m-th sub-RF channel is:

[0020]

[0021] The offset error ΔO of the mth sub-RF channel is obtained by the offset error calculation formula (6): m :

[0022]

[0023] Mathematical statistics methods are used for error calculation and bias error calibration.

[0024] By giving the sampling system an input signal x(t) with a frequency of ω0, the amplitude and gain error G of the sub-RF channel at the angular frequency Ω0 are calculated through time-frequency domain conversion. m Proportional relationship, the input signal x(t) is transformed into discrete time Fourier transform:

[0025]

[0026] Then the sample output y of the mth channel m [n] Doing DTFT, we get the expression:

[0027]

[0028] The digital frequency ω is equal to the product of the analog angular frequency Ω and the period, that is, ω0=Ω0MT s Substitute, MT s represents the sampling period of the Mth RF sampling. According to the Nyquist sampling theorem, when Ω>|πf s |, substitute X(jΩ)=0 into the above formula (8) to obtain:

[0029]

[0030] Substituting the input X(jΩ)=Aπ(δ(Ω-Ω0)-δ(Ω+Ω0)) / j into the above formula (9), we get:

[0031]

[0032] Then find the gain spectrum of the sub-RF channel m at Ω0, substitute ω0 and Ω0<πf s / M, the above formula (10) is converted to:

[0033]

[0034] From the above formula (11), we know that the amplitude of the angular frequency Ω0 and the gain error G of the sub-RF channel are m At the same time, the sampling point of the reference channel ADC0 is set to correspond to the sampling moment when the initial phase is 0, thereby deriving the sub-RF channel ADC m The phase at Ω0 is Get the sub-RF channel gain error ΔG m for:

[0035]

[0036] Input sinusoidal input signal x a (t) Calculate the relevant gain coefficient and signal phase of each sub-RF channel, and obtain the gain error ΔG in the above formula (12) m Perform calibration.

[0037] Δt i Represents the time error between the ideal sampling point and the actual sampling point, ε i [n] represents the error term, x i [n] represents the derivative of the ideal sampling value with respect to time. The actual output with time mismatch error can be constructed as the sum of the error terms proportional to the ideal sampling value and the derivative of the actual sampling output. The output expression of the actual sampling value is:

[0038] y i [n] = x i [n]+ε i [n] (13),

[0039] The sub-RF channel error term ε in the above formula (13) is i [n] = Δt i ·(dx i [n] / dt), the expectation of the product of the ideal sampling value and the derivative of the sub-RF channel is 0, that is, E{ε i [n]}=0, the actual sampled output of the same sub-RF channel is approximated to replace the time derivative to obtain:

[0040]

[0041] Substitute the output in equation (14) into the LMS algorithm iteration model, when the time error value Δt i When E(y i [n]×(dx i [n] / dt)) will also change accordingly, and the resulting sign and time mismatch error value Δt i The sign changes are consistent, and the time mismatch error related quantity is substituted into the LMS algorithm iteration model to obtain the time mismatch error value Δt i ,

[0042] The Taylor formula is used to calculate the ideal sampling value y i [n] is expanded to obtain the actual sampling value after eliminating the first-order error term. The expression is:

[0043]

[0044] The actual sampling value By approximating the time derivative, we get the following formula:

[0045]

[0046] Among them, the estimated sampling value y′ i[n] The actual sampling values ​​of the i-2, i-1, i, i+2, and i+1 sub-RF channels are estimated by the Lagrange interpolation formula. The specific expression is:

[0047]

[0048] Compensate and calibrate the time error value Δt based on the estimated sampling value i .

[0049] If it does not exist, then O m -O0=0、G m / G0=1, the time error between two adjacent sub-RF channels is ΔT m When is 0, the total quantized output of the sub-RF channel of the sampling system is:

[0050]

[0051] On the other hand, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the multi-channel RF transceiver sampling error calibration method when executing the program.

[0052] On the other hand, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the multi-channel RF transceiver sampling error calibration method.

[0053] In yet another aspect, the present invention further provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method for calibrating sampling errors of a multi-channel radio frequency transceiver are implemented.

[0054] Compared with the prior art, the beneficial effect lies in that the sampling error problem generated in the process of splicing multi-channel RF signals can be effectively solved, and the performance and accuracy of the system can be improved. The present invention can be used to build a wideband ultra-wideband RF chip by cascading multiple low-speed, narrow-bandwidth RF transceivers. By effectively solving the sampling error problem generated in the process of splicing multi-channel RF signals, the performance and accuracy of the system can be improved, and the purpose of real-time ultra-wideband high-precision transceiver in the wideband microwave field can be achieved.

[0055] Other features and advantages of the present invention will be set forth in the following description, and part will be apparent from the description, or may be understood through the practice of the present invention. The features and advantages of the present invention may be realized and obtained through the elements and combinations specifically indicated in the appended application scope. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 FIG. 4 is a schematic diagram of multiple channels of a multi-channel radio frequency transceiver in an embodiment of the present invention.

[0058] Figure 2 Schematic diagram of bias error in a multi-channel RF transceiver sampling system.

[0059] Figure 3 Schematic diagram of the multi-channel RF transceiver sampling system after bias error calibration.

[0060] Figure 4 Schematic diagram of the gain error of a multi-channel RF transceiver sampling system.

[0061] Figure 5 Schematic diagram of the multi-channel RF transceiver sampling system before and after gain error calibration.

[0062] Figure 6 Schematic diagram of the time error of a multi-channel RF transceiver sampling system.

[0063] Figure 7 Schematic diagram of the Lagrange interpolation formula in an embodiment of the present invention.

[0064] Figure 8 It is a schematic diagram of the flow of compensation calibration after the LMS algorithm iterative model in an embodiment of the present invention.

[0065] Fig. 9 Schematic diagram of the multi-channel RF transceiver sampling system before and after time error compensation calibration. DETAILED DESCRIPTION

[0066] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] In addition, the terms "first", "second", and "third" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first", "second", and "third" may explicitly or implicitly include one or more of the features. In addition, the meaning of "multiple" and "several" refers to two or more, unless otherwise clearly and specifically defined.

[0068] See also Figure 1 The present invention provides a method for calibrating sampling errors of a multi-channel radio frequency transceiver, comprising the following steps:

[0069] S1, taking x(t) as the input signal of the M parallel sampled sub-RF channels of the error model of the sampling system,

[0070] Determine whether there are bias errors, gain errors and time errors in the M parallel-sampled sub-RF channels of the error model of the sampling system;

[0071] If it exists, the sample output of the Mth channel is:

[0072] y m [n] = G m x((nM+m)T s -ΔT m )+O m (1)

[0073] Then the total quantized output of the sampling system is:

[0074]

[0075] Set the input signal to a sinusoidal signal:

[0076]

[0077] In the above formula (3), A is the input signal amplitude, Ω0 is the angular frequency, Represents the phase, and then (nM+m)=k, ω0=Ω0T S , then the frequency domain expression is:

[0078]

[0079] If it does not exist, then O m -O0=0、G m / G0=1, the time error between two adjacent sub-RF channels is ΔT m When is 0, the total quantized output of the sub-RF channel of the sampling system can be known from the above conditions as follows:

[0080]

[0081] S2, the sinusoidal input signal x a (t) is grounded, and the offset of each sub-RF channel is obtained from the quantized output of the multi-channel RF transceiver (the corresponding relationship between the output and input voltage of the multi-channel RF transceiver and the theoretical offset are shown in the following table):

[0082]

[0083] From the corresponding relationship between the output and input of the multi-channel RF transceiver, we can get the value of the sinusoidal input signal x a When (t) is 0, the output data of the multi-channel RF transceiver is 2 24 / 2, but in actual engineering applications, gain errors will occur. In mathematical statistics, data with a frequency less than 1 / 20 are considered accidental errors. Data with a frequency higher than 1 / 20 are retained for weighted average calculation to obtain the offset, that is, the bias error, such as Figure 2 As shown;

[0084] For the bias error, mathematical statistics methods are used for error calculation and bias error calibration; 2000 points are selected for statistics, and each sub-RF channel (ADC) is selected to obtain each bias error ΔO according to the bias error calculation formula, and then bias calibration is performed, such as Figure 3 As shown (where the red line is the sinusoidal input signal x a (t) has a frequency of 100KHz and an amplitude of 1V, and is a waveform line without offset calibration. At this time, the waveform line is not completely symmetrical around the 0 point; the purple line is the waveform line after offset calibration).

[0085] Next, we take the mth sub-RF channel (ADC m ) is used as a reference channel for example. The input sinusoidal input signal x a (t), Δt is the difference in sampling time interval between adjacent channels, G m and O m are the gain and offset of the mth RF sampling channel, y n is the final discrete quantized total output, then the gain error of the mth reference channel is G m / G0=1, bias error is 0 m -O0, sampling time in ideal case without interference (nM+m)T s , where T s is the sampling period of RF sampling, and m is the sub-RF channel number. However, in actual situations, the actual sampling time of each sub-RF channel will have a deviation of ΔT after the signal passes through each conditioning circuit. m Then the actual sampling time m of the mth sub-RF channel is:

[0086]

[0087] The offset error ΔO of the mth sub-RF channel is obtained by the offset error calculation formula (6): m :

[0088]

[0089] Similarly, the offset error of each sub-RF channel calculated according to the above formula (7) is:

[0090] ADC <![CDATA[ADC0]]> <![CDATA[ADC k ]]> <![CDATA[ADC p ]]> <![CDATA[ADC m ]]> ΔO 0.1251 0.3114 0.2078 0.1307

[0091] The offset calibration is performed based on the offset error result described above.

[0092] S3. By giving the sampling system an input signal x(t) with a frequency of ω0, the amplitude and gain error G of the sub-RF channel at the angular frequency Ω0 can be calculated through time-frequency domain conversion. m Proportional relationship, the input signal x(t) is transformed into discrete time Fourier transform:

[0093]

[0094] Then the sample output y of the mth channel m [n] Doing DTFT, we get the expression:

[0095]

[0096] The digital frequency ω is equal to the product of the analog angular frequency Ω and the period, that is, ω0=Ω0MT s Substitute, MT s represents the sampling period of the Mth RF sampling. According to the Nyquist sampling theorem, when Ω>|πf s |, substitute X(jΩ)=0 into the above formula (8) to obtain:

[0097]

[0098] Substituting the input X(jΩ)=Aπ(δ(Ω-Ω0)-δ(Ω+Ω0)) / j into the above formula (9), we get:

[0099]

[0100] Then find the gain spectrum of the sub-RF channel m at Ω0, substitute ω0 and Ω0<πf s / M, the above formula (10) is converted to:

[0101]

[0102] From the above formula (11), it can be seen that the amplitude of the angular frequency Ω0 is related to the gain error G of the sub-RF channel mAt the same time, the sampling point of the reference channel ADC0 (the first sub-RF channel) is set to correspond to the sampling moment when the initial phase is 0, such as Figure 4 As shown, the sub-RF channel ADC can be derived m The phase at Ω0 is Get the sub-RF channel gain error ΔG m for:

[0103]

[0104] Input sinusoidal input signal x a (t) (frequency is 10KHz, amplitude is 100mV), calculate the relevant gain coefficient and signal phase of each sub-RF channel, and obtain the gain error ΔG in the above formula (12) m Calibrate, the frequency domain waveforms before and after calibration are as follows Figure 5 shown.

[0105] Before calibration, there are obvious distortion spectra at 14.6KHz and 17.9KHz. After calibration, the mismatch effect caused by the gain error is significantly improved. The overall dynamic performance comparison before and after calibration is shown in the following table;

[0106]

[0107] The SFDR of the adopted system was improved from 49.42dB before calibration to 95.58dB, an improvement of 46.16dB; the SNDR was improved from 47.53dB before calibration to 79.42dB, an improvement of 31.89dB; and the ENOB was improved from 7.61bits before calibration to 12.90bits, an improvement of 5.29bits.

[0108] S4. After the time error value is iterated through the LMS algorithm iterative model, compensation calibration is performed.

[0109] When the time is ideal, the output signal after sampling by each sub-RF channel is orthogonal to its derivative. When there is a time error, the output signal and its derivative lose the orthogonal relationship. Based on this relationship, we calculate the expected value of the product of the output signal and the derivative to estimate the error, and perform compensation calibration after iterating the error value through the LMS algorithm iterative model.

[0110] Specifically, Δt i Represents the time mismatch error between the ideal sampling point and the actual sampling point, ε i [n] represents the error term, x i [n] represents the derivative of the ideal sampling value with respect to time. The actual output with time mismatch error can be constructed as the sum of the error terms proportional to the ideal sampling value and the derivative of the actual sampling output. The output expression of the actual sampling value is:

[0111] y i [n] = x i [n]+ε i [n] (13),

[0112] The sub-RF channel error term ε in the above formula (13) is i [n] = Δt i ·(dx i [n] / dt),

[0113] Since the ideal sampling value is orthogonal to its corresponding first-order derivative, the expectation of the product of the ideal sampling value and the derivative of the sub-RF channel is 0, that is, E{ε i [n]}=0, the actual sampled output of the same sub-RF channel is approximated to replace the time derivative to obtain the following derivation:

[0114]

[0115] Substitute the output in equation (14) into the LMS algorithm iteration model. When the time mismatch error value Δt i When E(y i [n]×(dx i [n] / dt)) will also change accordingly, and the resulting sign and time mismatch error value Δt i The sign changes are consistent, and the time mismatch error related quantity is substituted into the LMS algorithm iteration model to obtain the time mismatch error value Δt i ,like Figure 6 shown.

[0116] The estimated time mismatch error value Δt i Then, according to the ideal sampling value y i [n], actual sampling value Estimated sampling value y′ i [n] These parameters serve as the key to the subsequent time error compensation, which calibrates the time error based on the estimated time parameters.

[0117] The actual sampling value is composed of the ideal sampling value and the time error value. In order to eliminate the influence of the time mismatch error, this compensation method uses Taylor formula to calculate the ideal sampling value y i [n] is expanded. At the same time, since the proportion of high-order error expansion terms is very small, only the first-order error terms are considered, and the actual sampling value after eliminating the first-order error terms can be obtained. The expression is:

[0118]

[0119] And because the ideal sampling time sampling value y of the sub-RF channeli [n] cannot be obtained, and the derivative with respect to time is also unknown. By approximating the time derivative, we get the following formula:

[0120]

[0121] Among them, the estimated sampling value y′ i [n] is estimated by the Lagrange interpolation formula, such as Figure 7 As shown, the actual time sampling values ​​of the i-2, i-1, i, i+2, and i+1 sub-RF channels are obtained. The specific expression is:

[0122]

[0123] Compensate and calibrate the time mismatch error value Δt based on the estimated sampling value i .

[0124] In order to prove the effectiveness of the time error correction algorithm for each sub-RF channel, a sinusoidal input signal x is input. a (t) (frequency is 100KHz, amplitude is 1V), the time mismatch error of the sampled output signal is sent to the LMS algorithm iteration model for compensation calibration, such as Figure 8 shown.

[0125] The spectrum comparison of the sampling system before and after the time error calibration is as follows: Fig. 9 As shown, in Fig. 9 There are three obvious time mismatch errors before calibration, at 28.32KHz, 61.83KHz and 67.47KHz respectively. The optimization comparison of various dynamic indicators before and after calibration is shown in the following table:

[0126]

[0127] The SFDR of the system is improved from 37.78 dB to 94.41 dB, the SNDR is improved from 35.16 dB to 81.42 dB, and the ENOB is improved from 5.54 bits to 13.23 bits, which effectively solves the sampling error problem generated in the process of splicing multi-channel radio frequency signals, and improves the performance and accuracy of the system. The present invention can be used to realize the construction of a wideband ultra-wideband radio frequency chip by cascading multiple low-speed and narrow-bandwidth radio frequency transceivers, and effectively solves the sampling error problem generated in the process of splicing multi-channel radio frequency signals, improves the performance and accuracy of the system, and achieves the purpose of real-time ultra-wideband high-precision transceiver in the wideband microwave field.

[0128] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0129] In particular, according to some embodiments of the present disclosure, the process described above can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0130] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a mission data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated mission data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0131] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperTextTransferProtocol), and may be interconnected with any form or medium of digital task data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0132] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: in response to detecting a query operation on a production collaboration document in a switch production line management application, determines the network connection status of the switch production line management application; in response to determining that the network connection status of the switch production line management application represents an offline state, replaces the web page entry information corresponding to the production collaboration document with target entry file information, and loads target web page resource information to display the web page of the production collaboration document offline in the switch production line management application, wherein the target entry file information is file information of a pre-downloaded entry file corresponding to the web page of the production collaboration document, and the target web page resource information is locally stored resource information corresponding to the web page; in response to determining that the network connection status of the switch production line management application represents an online state, and the web page resource information corresponding to the production collaboration document is not stored locally, downloads the web page resource information of the web page from the production line document server, wherein the web page resource information includes an entry file and resource information; according to the web page resource information, displays the web page of the production collaboration document in the switch production line management application, and stores the web page resource information in a local database.

[0133] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including product-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0134] The present invention is not limited to what is described in the specification and implementation modes, and therefore additional advantages and modifications can be easily realized by those skilled in the art. Therefore, without departing from the spirit and scope of the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details, representative devices, and illustrative examples shown and described herein.

Claims

1. A method for calibrating sampling error of a multi-channel radio frequency transceiver, characterized in that: The steps include: Take x(t) as the input signal of the M parallel sampled sub-RF channels of the error model of the sampling system, Determine whether there are bias errors, gain errors and time errors in the M parallel-sampled sub-RF channels of the error model of the sampling system; If present, the offset error, gain error and time error are calibrated; Then the sampling output of the Mth channel is: y m [n]=G m x((nM+m)T s -ΔT m )+O m (1), The total quantified output of the sampling system is: Set the input signal to a sinusoidal signal: In the above formula (3), A is the input signal amplitude, Ω0 is the angular frequency, Represents the phase, and then (nM+m)=k, ω0=Ω0T S , the frequency domain expression is: The sinusoidal input signal x a (t) is grounded, and the offset of the sub-RF channel is obtained from the quantized output of the multi-channel RF transceiver. The offset error ΔO of the mth sub-RF channel is obtained by the offset error calculation formula (6): m : Mathematical statistics methods are used for error calculation and bias error calibration.

2. The method for calibrating sampling error of a multi-channel RF transceiver according to claim 1, characterized in that: By giving the sampling system an input signal x(t) with a frequency of ω0, the amplitude and gain error G of the sub-RF channel at the angular frequency Ω0 are calculated through time-frequency domain conversion. m Proportional relationship, the input signal x(t) is transformed into discrete time Fourier transform: Then the sample output y of the mth channel m [n] Doing DTFT, we get the expression: The digital frequency ω is equal to the product of the analog angular frequency Ω and the period, that is, ω0=Ω0MT s Substitute, MT s represents the sampling period of the Mth RF sampling. According to the Nyquist sampling theorem, when Ω>|πf s |, substitute X(jΩ)=0 into the above formula (8) to obtain: Enter X(jΩ)=Aπ(δ(Ω-Ω0)-δ(Ω+Ω0)) / j Substituting into the above equation (9) we get: Then find the gain spectrum of the sub-RF channel m at Ω0, substitute ω0 and Ω0<πf s / M, the above formula (10) is converted to: From the above formula (11), we know that the amplitude of the angular frequency Ω0 and the gain error G of the sub-RF channel are m At the same time, the sampling point of the reference channel ADC0 is set to correspond to the sampling moment when the initial phase is 0, thereby deriving the sub-RF channel ADC m The phase at Ω0 is Get the sub-RF channel gain error ΔG m for: Input sinusoidal input signal x a (t) Calculate the relevant gain coefficient and signal phase of each sub-RF channel, and obtain the gain error ΔG in the above formula (12) m Perform calibration.

3. The method for calibrating sampling error of a multi-channel RF transceiver as claimed in claim 2, characterized in that: Δt i Represents the time error between the ideal sampling point and the actual sampling point, ε i [n] represents the error term, x i [n] represents the derivative of the ideal sampling value with respect to time. The actual output with time mismatch error can be constructed as the sum of the error terms proportional to the ideal sampling value and the derivative of the actual sampling output. The output expression of the actual sampling value is: y i [n]=x i [n]+ε i [n] (13), The sub-RF channel error term ε in the above formula (13) is i [n] = Δt i ·(dx i [n] / dt), the expectation of the product of the ideal sampling value and the derivative of the sub-RF channel is 0, that is, E{ε i [n]}=0, the actual sampled output of the same sub-RF channel is approximated to replace the time derivative to obtain: Substitute the output in equation (14) into the LMS algorithm iteration model, when the time error value Δt i When E(y i [n]×(dx i [n] / dt)) will also change accordingly, and the resulting sign and time mismatch error value Δt i The sign changes are consistent, and the time mismatch error related quantity is substituted into the LMS algorithm iteration model to obtain the time mismatch error value Δt i , The Taylor formula is used to calculate the ideal sampling value y i [n] is expanded to obtain the actual sampling value after eliminating the first-order error term. The expression is: The actual sampling value By approximating the time derivative, we get the following formula: Among them, the estimated sampling value y′ i [n] The actual sampling values ​​of the i-2, i-1, i, i+2, and i+1 sub-RF channels are estimated by the Lagrange interpolation formula. The specific expression is: Compensate and calibrate the time error value Δt based on the estimated sampling value i .

4. The method for calibrating sampling error of a multi-channel RF transceiver according to claim 1, wherein: If it does not exist, then O m -O0=0、G m / G0=1, the time error between two adjacent sub-RF channels is ΔT m When is 0, the total quantized output of the sub-RF channel of the sampling system is:

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for calibrating sampling errors of a multi-channel radio frequency transceiver according to any one of claims 1 to 4 are implemented.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for calibrating sampling errors of a multi-channel radio frequency transceiver according to any one of claims 1 to 4 are implemented.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for calibrating sampling errors of a multi-channel radio frequency transceiver according to any one of claims 1 to 4 are implemented.

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