Method and apparatus for mitigating in-phase and quadrature mismatch

Abstract

A method and apparatus for mitigating in-phase and quadrature mismatch. A method for optimizing at least one IQMC parameter value for IQMC includes: generating a set of tested IQMC candidate parameter values by performing an iterative method, wherein the iterative method includes: selecting a first IQMC candidate parameter value for the at least one IQMC parameter of the IQMC; using the first IQMC candidate parameter value to determine a performance metric value including at least one of the following: (i) an image rejection ratio (IRR) value, (ii) a signal-to-interference and noise ratio (SINR) value, or (iii) a signal-to-image ratio (SImR) value; and determining a second IQMC candidate parameter value as an update to the first IQMC candidate parameter value. The method for optimizing at least one IQMC parameter value for IQMC also includes: determining an IQMC candidate parameter value from the set of tested IQMC candidate parameter values that optimizes the performance metric value.

Description

[0001] This application is based upon and claims the benefit of U.S. Provisional Patent Application No. 63 / 025,983 filed in the U.S. Patent and Trademark Office on May 15, 2020, and U.S. Non-Provisional Patent Application No. 17 / 117,683 filed in the U.S. Patent and Trademark Office on December 10, 2020. The entire contents of both applications are incorporated herein by reference. Technical Field

[0002] The present disclosure generally relates to communication systems or devices. Specifically, the present disclosure relates to systems and methods for improving the performance of communication systems or devices that may exhibit in-phase (I) and quadrature (Q) mismatch. I and Q mismatch may be referred to herein as "IQMM." Background Art

[0003] Imbalance between the I and Q branches of an orthogonal transmitter (TX) or receiver (RX) can cause interference between specific frequencies after upconversion or downconversion. IQMM can be caused by non-ideal characteristics of the I and Q paths and can degrade TX or RX performance by reducing the effective signal-to-interference ratio. Therefore, compensation for IQMM in the TX and / or RX of an orthogonal transceiver can be helpful. Summary of the Invention

[0004] According to some embodiments, a method for optimizing at least one IQMC parameter value for at least one IQMC parameter of an in-phase (I) and quadrature (Q) mismatch compensator (MC) includes generating a set of tested IQMC candidate parameter values by performing an iterative method until an exit condition is reached, and determining an IQMC candidate parameter value from the set of tested IQMC candidate parameter values that optimizes a performance metric. At least one iteration of the iterative method includes selecting a first IQMC candidate parameter value for the at least one IQMC parameter of the IQMC; determining a performance metric value including at least one of the following using the first IQMC candidate parameter value: (i) an image rejection ratio (IRR) value, (ii) a signal-to-interference and noise ratio (SINR) value, or (iii) a signal-to-image ratio (SImR) value; and determining a second IQMC candidate parameter value as an update to the first IQMC candidate parameter value. The set of tested IQMC candidate parameter values includes at least the first IQMC candidate parameter value and the second IQMC candidate parameter value.

[0005] According to some embodiments, an apparatus configured to optimize at least one IQMC parameter value for at least one IQMC parameter of an IQMC includes a processor and a non-transitory processor-executable medium storing instructions that, when executed by the processor, cause the processor to: generate a set of tested IQMC candidate parameter values by executing an iterative method until an exit condition is reached, and determine an IQMC candidate parameter value from the set of tested IQMC candidate parameter values that optimizes a performance metric. At least one iteration of the iterative method includes: selecting a first IQMC candidate parameter value for the at least one IQMC parameter of the IQMC; determining a performance metric value including at least one of the following using the first IQMC candidate parameter value: (i) an image rejection ratio (IRR) value, (ii) a signal-to-interference-and-noise ratio (SINR) value, or (iii) a signal-to-image ratio (SImR) value; and determining a second IQMC candidate parameter value as an update to the first IQMC candidate parameter value. The tested IQMC candidate parameter values include at least the first IQMC candidate parameter value and the second IQMC candidate parameter value. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Various aspects, features, and advantages of certain embodiments of the present disclosure will be apparent from the following detailed description and accompanying drawings.

[0007] Figure 1A A diagram illustrating at least a portion of a transmitter according to some embodiments of the present disclosure.

[0008] Figure 1B A diagram illustrating at least a portion of a receiver according to some embodiments of the present disclosure.

[0009] Figure 2A A diagram illustrating CV IQMC according to some embodiments of the present disclosure.

[0010] Figure 2B A diagram illustrating CVIQMC according to some embodiments of the present disclosure.

[0011] Figure 2C A diagram illustrating RV IQMC according to some embodiments of the present disclosure.

[0012] Figure 2D A diagram showing CVIQMC according to some embodiments of the present invention.

[0013] Figure 2E A diagram illustrating RV IQMC according to some embodiments of the present disclosure.

[0014] Figure 3 A flowchart of an IQMC parameter optimization method according to some embodiments of the present disclosure is shown.

[0015] Figure 4 A flowchart of an IQMC parameter optimization method according to some embodiments of the present disclosure is shown.

[0016] Figure 5 A diagram illustrating electronic devices in a network environment according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] In this article, embodiments of the present disclosure are described in detail with reference to the accompanying drawings. It should be noted that the same or similar elements can be represented by the same reference numerals / letters even if they are shown in different drawings. In the description herein, specific details such as detailed configuration and components are provided to help fully understand the embodiments of the present disclosure. Various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. For the sake of clarity and conciseness, certain detailed descriptions may be omitted.

[0018] The image rejection ratio (IRR) can be an in-phase (I) to quadrature (Q) mismatch compensator (IQMC) performance metric and can be defined as a function of (i) the signal level generated by a desired input frequency and (ii) the signal level generated by an unwanted image frequency. The function can be, or can involve, or include the ratio of these two quantities. Certain embodiments described herein relate to one or more techniques (e.g., including iterative techniques, machine learning techniques, gradient ascent or gradient descent techniques, or other techniques) that can be used to obtain IQMC parameters that improve (e.g., maximize) the IRR of a TX or RX. For example, the present disclosure provides one or more solutions to the IRR optimization problem using a gradient ascent (or descent) search method and provides compensator architectures in the TX and RX for finding the gradient of a closed-form IRR-related cost function as a function of an IQ impairment parameter and an IQMC parameter.

[0019] The IRR of the TX or RX may be frequency-dependent, and the IRR that is optimized or maximized (at least in part via the selection or setting of IQMC parameters of the TX or RX) may be the minimum IRR in a set of IRRs corresponding to a set of frequencies (e.g., corresponding to a desired frequency band). In some embodiments, the maximized IRR may be another IRR (e.g., an average or median IRR of the set of IRRs).

[0020] The signal-to-interference-plus-noise ratio (SINR) can be an IQMC performance metric and can be defined as a function of: (i) the power of the signal of interest, (ii) the interference power (from one or more (e.g., all) interfering signals), and (iii) the power of the background noise. As an example, the SINR can be defined as a function of the power of the signal of interest and the aggregation (e.g., addition) of the interference power and the power of the background noise. As a more specific example, the SINR can be a function of (e.g., can be equal to) the ratio of (i) the power of the signal of interest to (ii) the sum of the interference power and the power of the background noise. For example, the present disclosure provides one or more solutions to the SINR optimization problem using a gradient ascent (or descent) search method, and provides a compensator architecture in TX and RX for finding the gradient of a closed-form SINR-related cost function as a function of IQ impairment parameters and IQMC parameters.

[0021] The SINR of TX or RX may be frequency-dependent, and the SINR that is maximized (at least in part via the selection or setting of the IQMC parameters of TX or RX) may be the minimum SINR in a set of SINRs corresponding to a set of frequencies (e.g., corresponding to a desired frequency band). In some embodiments, the maximized SINR may be another SINR (e.g., an average or median SINR of the set of SINRs).

[0022] The signal-to-image ratio (SImR) can be an IQMC performance metric and can be defined as a function of (i) the signal level at the desired frequency and (ii) the signal level at the interfering frequency (e.g., the image frequency). The function can indicate the relative strength of the signal level at the desired frequency and the signal level at the interfering frequency (e.g., a ratio), or can indicate the absolute strength of the signal level at the desired frequency and the signal level at the interfering frequency. Specific embodiments described herein relate to one or more techniques (e.g., including iterative techniques, machine learning techniques, gradient ascent or gradient descent techniques, or other techniques) that can be used to obtain IQMC parameters that improve (e.g., maximize) the SImR of a TX or RX. For example, the present disclosure provides one or more solutions to the SImR optimization problem using a gradient ascent (or descent) search method, and provides a compensator architecture in the TX and RX to find the gradient of a closed-form SImR-related cost function as a function of an IQ impairment parameter and an IQMC parameter.

[0023] The SImR of the TX or RX may be frequency-dependent, and the SImR that is maximized (at least in part via the selection or setting of the IQMC parameters of the TX or RX) may be the minimum SImR in a set of SImRs that respectively correspond to a set of frequencies (e.g., corresponding to a desired frequency band). In some embodiments, the maximized SImR may be another SImR (e.g., an average or median SImR of the set of SImRs).

[0024] In this document, specific references and / or descriptions to at least one of the performance metrics discussed above (IRR, SINR, and SImR) may apply to the other performance metrics as will be clear from the context.

[0025] The specific techniques described herein provide for optimizing IQMC parameters for IQMC, or determining or generating optimized IQMC parameters for an IQMC compensator. As used herein, the terms optimization or optimized may refer to improving or being improved. For example, optimizing an IRR value, SINR value, or SImR value may refer to increasing an IRR value, SINR value, or SImR value. The optimized IRR value, SINR value, or SImR value may refer to a maximum IRR value, SINR value, or SImR value in a set of IRR values, SINR values, or SImR values (e.g., a set of test values, default values, or other reference values).

[0026] Figure 1A A diagram showing at least a portion of a transmitter according to some embodiments of the present disclosure. Note that although Figure 1A The example transmitter (TX) 100 depicted in FIG. 1 is a zero intermediate frequency (IF) TX, but in other embodiments, the TX may be implemented as a non-zero IF TX and the techniques described herein may still be applied. Figure 1A Also depicted are the I and Q signal transmission paths in TX 100. TX 100 may be a standalone TX or may be included in a transceiver device or system or any other suitable communication device or system. TX 100 includes one or more of an IQMC 102, a digital-to-analog converter (DAC) 104, an upconverter 106, and a signal aggregator 108.

[0027] As a brief overview, and as presented by Figure 1A As shown by the arrows depicted in FIG, for example, the in-phase signal s is intended to be transmitted I [n] (where "n" is a time index - note that as used herein, certain lowercase letter symbols may be used to indicate functions in the time domain and certain uppercase letter symbols may be used to indicate functions in the frequency domain) is input to the IQMC 102. The orthogonal signal s (e.g., intended for transmission) Q [n] is also input to the IQMC 102. The IQMC 102I [n]Signal and s Q [n] signal is processed and the compensated signal u is converted accordingly I [n] is output to DAC 104, and the compensated signal u is converted accordingly. Q [n] is output to DAC 104. Note that u I [n] can be s I [n] and s Q [n] is a function of both, and s Q [n] can be s I [n] and s Q [n] A function of both.

[0028] DAC 104 converts the compensated signal u I [n] is converted into an analog I signal and the analog I signal is output to the up-converter 106. The up-converter 106 up-converts the analog I signal and outputs the up-converted analog I signal to the signal aggregator 108. Note that throughout the specification, s may be referred to as I [n] signal, u I The [n] signal, the analog I signal, and the up-converted analog I signal are referred to as the I signal.

[0029] DAC 104 converts the compensated signal u Q [n] is converted into an analog Q signal and the analog Q signal is output to the up-converter 106. The up-converter 106 up-converts the analog Q signal and outputs the up-converted analog Q signal to the signal aggregator 108. Note that throughout the specification, s may be referred to as Q [n] signal, u Q [n] signal, analog Q signal and up-converted analog Q signal are called Q signal.

[0030] The signal aggregator 108 is configured to aggregate (eg, add) the analog I signal and the analog Q signal to generate an up-converted signal Z suitable for transmission. The up-converted signal Z is transmitted at Figure 1A Marked as Z RF,TX(t) , to indicate that it is a signal that varies in the time domain and is output by TX at radio frequency (RF).

[0031] Referring to the upconverter 106, the upconverter is configured to upconvert a signal from a baseband frequency to an RF frequency more suitable for transmission. The upconverter 106 includes a first filter 106a, a second filter 106b, a first mixer 106c, a second mixer 106d, a local oscillator (LO) 106e, and a phase shifter 106f.

[0032] The first filter 106a may be any suitable filter, such as an analog filter, a baseband filter, and / or a low-pass filter. The first filter 106a may be an analog baseband (ABB) filter. The first filter 106a may have a ITX The second filter 106b may be similar to the first filter 106a and may have similar features, characteristics, structure and / or functions as the first filter 106a. The second filter 106b may have an impulse response represented by h QTX (t) represents the impulse response. The mismatch (h) between the impulse responses on the I and Q paths of the TX 100 ITX (t) and h QTX (t)(h ITX (t)≠h QTX (t)) may produce a frequency-dependent IQ mismatch (FD-IQMM). Such a mismatch may degrade the IRR, SINR, and / or SImR of the TX 100 (eg, as discussed in detail herein).

[0033] The first mixer 106c can be any suitable mixer for use in the upconverter 106. Generally, a mixer can perform an operation on an input signal, such as multiplying two input signals. The second mixer 106d can be similar to the first mixer 106c and can have any of the features, characteristics, structures, and / or functions of the first mixer 106c.

[0034] LO 106e provides a signal to the first mixer 106c, and this signal can be expressed as in, is the angular frequency of LO 106e. LO 106e also provides a signal (ideally, a signal identical or similar to the signal provided by LO 106e to first mixer 106c) to phase shifter 106f, where phase shifter 106f shifts (e.g., delays) the phase by 90° or approximately 90° and provides the delayed signal to second mixer 106d. Thus, second mixer 106d can ideally be provided with a signal identical or similar to the signal provided to first mixer 106c, but shifted by 90° or approximately 90°. However, in practice, certain non-ideal mismatches may occur that cause the signals actually provided to first mixer 106c and second mixer 106d (e.g., by LO 106e and / or phase shifter 106f) to deviate from ideal values, or certain non-ideal characteristics of first mixer 106c and second mixer 106d may cause the signals to be processed differently than ideal mixers. At least some of these non-ideal mismatches or characteristics can be represented as g in the following equation 1 representing the signal input to the second mixer 106d: TX (Mismatch Gain) and φ Tx (Mismatch phase shift).

[0035] [Equation 1]

[0036]

[0037] When g TX ≠1 and / or φ TX ≠ 0, there is a frequency-independent (FI) IQ mismatch in the TX 100. Such a mismatch may degrade the IRR, SINR, and / or SImR of the TX 100 (e.g., as discussed in detail herein).

[0038] The frequency response in the frequency domain of the baseband equivalent version of the upconverted signal in the TX path (at the outputs of the first and second mixers 106c, 106d) is given by Equation 2 below.

[0039] [Equation 2]

[0040] Z TX (f) = G 1TX (f)U(f)+G 2TX (f)U * (-f)+N TX (f),

[0041] Where U(f) is the frequency response of the baseband TX signal, N TX (f) represents additive TX noise, and G 1TX (f) and G 2TX (f) is defined as Equation 3 below.

[0042] [Equation 3]

[0043]

[0044] Where H in Equation 3 ITX (f) and H QTX (f) show the frequency responses of the first filter 106a and the second filter 106b, respectively. TX =1、φ TX =0 and H ITX (f) = H QTX (f)) In the case of G 2TX (f) and hence the second term in Equation 2 becomes zero. Without any IQMC, the IRR can then be expressed as Equation 4 below (as an example), which is 2TX (f) = 0, so it becomes infinite without IQMM.

[0045] [Equation 4]

[0046]

[0047] However, when G 2TX When (f) is non-zero and when there are some IQMMs, the IRR is finite. Other IQMC performance parameters (such as SINR and / or SImR) may be similarly large in the absence of any IQMMs, and when G 2TX It can be small when (f) is non-zero and when there are some IQMMs.

[0048] IQMC 102 may compensate for IQMM including the above-mentioned IQ mismatch, thereby increasing IRR, SINR and / or SImR of TX 100. IQMC 102 may include, for example, a complex-valued (CV) IQMC (e.g., Figure 2A CV IQMC 202 or Figure 2B ) or real-valued (RV) IQMC (e.g., Figure 2C The IQMC 102 may include one or more components, some examples of which are described below with reference to at least Figure 2A 、 Figure 2B and Figure 2C Certain parameters of these components (or certain parameters of the IQMC itself) may be referred to herein as IQMC parameters or IQMC coefficients. The present disclosure provides methods for determining, selecting, setting, and / or updating IQMC parameters of the IQMC 102 (e.g., using parameters such as Figure 3 ), such that the IRR and SINR and / or SImR of the TX 100 are optimized.

[0049] Figure 1B A diagram illustrating at least a portion of a receiver according to some embodiments of the present disclosure. Figure 1B The example receiver (RX) 110 depicted in FIG. 1 is a zero IF RX, but in other embodiments, the RX 110 may be implemented as a non-zero IF RX and the techniques described herein may still be applied. Figure 1B Also depicted are the I and Q signal receive paths in RX 110. RX 110 may be a standalone RX or may be included in a transceiver device or system or any other suitable communication device or system. RX 110 includes one or more of an IQMC 112, an analog-to-digital converter (ADC) 114, and a downconverter 116.

[0050] As a brief overview, and as presented by Figure 1B As shown by the arrows depicted in FIG, the up-converted signal Z is received by the RX 110 and input to the down-converter 116. The up-converted signal Z is Figure 1B Marked as Z RF,RX(t) , indicating that it is a signal that changes in the time domain and is input to the RX 110 at RF. The downconverter 116 downconverts the upconverted signal Z and outputs an analog I signal and an analog Q signal that are sent to the ADC 114, respectively. One of the ADCs 114 converts the analog I signal into a digital I signal r I [n], and the other of the ADCs 114 converts the analog Q signal into a digital Q signal r Q [n]. Signal r I [n] and r Q [n] is sent to the IQMC 112 which compensates the RX IQMM, thereby generating a compensated I signal y which may be further processed or used by the RX 110 or by a connected component or device I [n] and the compensated Q signal y Q [n]. Compensated I signal y I [n] can be a digital I signal r I [n] and digital Q signal r Q A function of one or both of [n]. The compensated Q signal y Q [n] can be a digital I signal r I [n] and digital Q signal r Q A function of one or both of [n].

[0051] Referring to downconverter 116 in more detail, downconverter 116 is configured to downconvert a signal from RF to baseband frequency. Downconverter 116 includes a third filter 116a, a fourth filter 116b, a third mixer 116c, a fourth mixer 116d, a local oscillator (LO) 116e, and a phase shifter 116f.

[0052] The third mixer 116c can be any suitable mixer for downconverting. As described above, a mixer can generally perform operations on input signals, such as multiplying two input signals. The third mixer 116c can receive the up-converted signal Z and the first signal from the LO 116e, and can mix them to generate an output that is sent to the third filter 116a. The fourth mixer 116d can receive the up-converted signal Z and the second signal from the LO 116e (e.g., via the phase shifter 116f), and can mix them to generate an output that is sent to the fourth filter 116b. The fourth mixer 116d can be similar to the third mixer 116c and can have any features, characteristics, structures and / or functions as the third mixer 116c.

[0053] LO 116e provides the first signal to the third mixer 116c, and this signal can be expressed as: in, is the angular frequency of LO 116e. LO 116e also provides a signal (ideally, a signal identical or similar to the signal provided by LO 116e to mixer 116c) to phase shifter 116f, where phase shifter 116f shifts (e.g., delays) the phase by 90° or approximately 90° and provides the shifted signal to fourth mixer 116d. Thus, fourth mixer 116d can ideally be provided with a signal identical or similar to the signal provided to third mixer 116c, but shifted by 90° or approximately 90°. However, in practice, certain non-ideal mismatches may occur that cause the signals actually provided to third mixer 116c and fourth mixer 116d (e.g., by LO 116e and / or phase shifter 116f) to deviate from ideal values, or certain non-ideal characteristics of the mixers may cause the signals to be processed differently than ideal mixing, and at least some of the non-ideal mismatches can be represented as g in the following equation 5 representing the signal input to fourth mixer 116d. TX (Mismatch Gain) and φ TX (Mismatch phase shift).

[0054] [Equation 5]

[0055]

[0056] When g RX ≠1 and / or φ RX ≠0, there is a frequency-independent (FI) IQ mismatch in the RX 110. Such a mismatch may degrade the IRR, SINR, and / or SImR of the RX 110 (e.g., as discussed in detail below).

[0057] The third filter 116a may be any suitable filter, such as an analog filter, a baseband filter, and / or a low-pass filter. The third filter 116a may receive the output of the third mixer 116c as an input. The third filter 116a may have a filter structure composed of h IRX The fourth filter 116b may be similar to the third filter 116a and may have any of the features, characteristics, structures and / or functions of the third filter 116a. The fourth filter 116b may receive the output of the fourth mixer 116d as an input. The fourth filter 116b may have a frequency response represented by h QRX (t) represents the impulse response. The impulse response (h) on the I path and Q path of RX 110 IRX (t) and h QRX (t)(h IRX (t)≠h QRXA mismatch between the RX 110 and the RX 110 may produce a frequency-dependent IQMM (FD-IQMM). Such a mismatch may degrade the IRR, SINR, and / or SImR of the RX 110 (eg, as discussed in detail herein).

[0058] As an example, the frequency response of the received baseband signal may be expressed as in Equation 6 below.

[0059] [Equation 6]

[0060]

[0061] Where R(f) is the frequency response of the received baseband signal, Z RX (f) is the frequency response of the baseband equivalent of the received signal at the input of the third mixer 116c and the fourth mixer 116d, N RX (f) is the additive RX noise, and G 1RX (f) and G 2RX (f) is defined as Equation 7 below.

[0062] [Equation 7]

[0063]

[0064] Where H in Equation 7 IRX (f) and H QRX (f) denote the frequency responses of the third filter 116a and the fourth filter 116b, respectively. The second term in Equation 6 represents the interfering image signal due to the RX IQMM.

[0065] The IQMC 112 may compensate for IQMMs including the IQMMs discussed above. The IQMC 112 may include, for example, a CV IQMC (e.g., Figure 2D ) or RV IQMC (e.g., Figure 2E RV IQMC 208 shown in FIG. ). IQMC 112 may include one or more components, some examples of which are described below with reference to at least Figure 2D and Figure 2E Certain parameters of these components (or certain parameters of the IQMC itself) may be referred to herein as IQMC parameters or IQMC coefficients. The present disclosure provides methods for determining, selecting, setting, and / or updating IQMC parameters of the IQMC 112 (e.g., using parameters such as Figure 3 ), such that the IRR, SINR, and / or SImR of the RX 110 are improved.

[0066] Now refer to Figures 2A to 2E, describes certain IQMC configurations according to certain embodiments. The apparatus, methods, and techniques disclosed herein are not necessarily limited to Figures 2A to 2E The specific IQMC configuration shown in is provided, and other IQMC configurations may be implemented as appropriate.

[0067] Figure 2A FIG. 1 is a diagram illustrating a CV IQMC according to some embodiments of the present disclosure. The CV IQMC 202 (which may be referred to herein as IQMC 202 for simplicity) may include a processor configured to implement a delay T D The IQMC 202 may receive a signal s[n] (e.g., Figure 1A The in-phase signal s shown I [n] and / or quadrature signal s Q The received signal s[n] = s I [n]+js Q [n] passes through a delay component 202a in a first path of the IQMC 202. In a second path of the IQMC 202, the received signal s[n] passes through a complex conjugate operator 202b (which is configured to output the complex conjugate of the input signal) and then passes through a complex-valued filter 202c. The complex-valued filter 202c may have L tap weights and may have an impulse response as shown in Equation 8 below.

[0068] [Equation 8]

[0069]

[0070] Among them, w TX，i are the tap weights, and i indexes the taps.

[0071] The outputs of the two paths are aggregated (eg, added) by an aggregator 202d, and the aggregator 202d outputs a compensated signal u[n]. The compensated signal u[n] may include Figure 1A The signal u shown in I [n] and / or signal u Q [n].

[0072] IQMC 202 may have certain IQMC parameters including L tap weights of complex-valued filter 202c. The techniques described herein (e.g., Figure 3 ) to determine, configure and / or set the IQMC parameters of the IQMC 202 to increase or maximize Figure 1A100 . Once the IQMC parameters are determined, the IQMC 202 can be configured to implement these parameters. Such implementation can be done at the time of manufacture or in the field, and in some embodiments, can be done dynamically (e.g., according to a maintenance schedule, or based on the condition of or feedback from a transmitter or transceiver containing the IQMC 202).

[0073] The following provides an example of a general mathematical model of signals processed by IQMC 202 in TX 100. The general mathematical model is also applied to certain example IQMCs including IQMC 202 below.

[0074] As shown in Equation 9 below, we can write the frequency response U(f) of the pre-compensated signal in TX 100 (such as used in Equation 2 above) as a function of the pure baseband signal using IQMC 202.

[0075] [Equation 9]

[0076] U(f)=F 1TX (f)S(f)+F 2TX (f)S*(-f)

[0077] Among them, F 1TX (f) and F 2TX (f) is a function of IQMC parameters and / or characteristics. By substituting Equation 9 into Equation 2, the baseband equivalent of the upconverted signal will be as shown in Equation 10 below.

[0078] [Equation 10]

[0079]

[0080] For IQMC 202, F 1TX (f) and F 2TX (f) can be expressed as the following equation 11.

[0081] [Equation 11]

[0082]

[0083] F 2TX (f) = W Tx (f)

[0084] Among them, W TX (f) can represent the frequency response w of the filter TX [n].

[0085] The following provides an example of a mathematical model for the IRR in the TX 100. One example formula for modeling the IRR of the TX 100 is shown in Equation 12 below.

[0086] [Equation 12]

[0087]

[0088] Using Equation 12 above to model the IRR of TX 100, and the above equation for F for IQMC 202 1TX (f) and F 2TX Equation 11 of (f) can mathematically model the IRR for the IQMC 202. Using the techniques described herein, such an IRR can be optimized.

[0089] The following provides an example of a mathematical model for the Signal to Interference and Noise Ratio (SINR) in the TX 100. An example formula for modeling the SINR of the TX 100 is shown in Equation 13 below.

[0090] [Equation 13]

[0091]

[0092] in, is the normalized TX noise variance, expressed as, for example, Equation 14 below.

[0093] [Equation 14]

[0094]

[0095] The IQMC coefficients can be determined by maximizing or increasing the SINR, which takes into account both IQMM and noise effects. When the noise power is significant (e.g., comparable to or greater than the noise power of the image signal level), maximizing the SINR can provide significant improvements in system throughput.

[0096] In some of the above equations, we assume that at frequencies f1, ..., f K G 1TX (f), G 2TX (f) is known (e.g., by using the baseband frequencies f1, ..., f K However, it is possible to estimate the relative mismatch, but not the G 1TX (f), G 2TX (f) There is no independent reasonable estimate. The following provides an estimate of the relative mismatch even for G when the estimate is known. 1TX (f), G 2TX(f) Some techniques may be used without independent reasonable estimates.

[0097] The following parameters as functions of gain and filter mismatch are defined as the following Equation 15.

[0098] [Equation 15]

[0099]

[0100] In view of this, the IRR can be estimated as in Equation 16 below.

[0101] [Equation 16]

[0102]

[0103] Assume φ TX and V TX (f) is known (e.g., such as by using the baseband frequencies f1, ..., f K The iterative technique described herein may be used to determine improved IQMC coefficients (e.g., referring to Figure 3 and Figure 4 ).

[0104] Some applications involve determining SImR instead of, or in addition to, IRR or SINR. Similar to IRR or SINR, SImR can indicate the characteristics or quality of TX IQMC. One example way to express TX SImR is as shown in Equation 17 below.

[0105] [Equation 17]

[0106]

[0107] The techniques presented herein may be used to determine and / or implement IQMC parameters for improving, increasing, or maximizing IRR, SINR, or SImR, such as defining w TX [n] (tap weights of the complex-valued filter 202c) or the limit W TX [n](w TX The tap weights of the frequency domain response or Fourier transform (e.g., fast Fourier transform or other Fourier transform) of [n].

[0108] Figure 2B is a diagram of a CVIQMC according to some embodiments of the present disclosure. For the sake of brevity, the CVIQMC 203 may be referred to herein as the IQMC 203. The IQMC 203 may include a processor configured to implement a delay T DThe IQMC 203 may include a delay component 203a, a complex filter 203b (e.g., a finite impulse response (FIR) filter), a real-valued operator 203c (configured to pass the real-valued part of the signal and block the imaginary part of the signal), and a signal aggregator 203d. The IQMC 203 may receive a signal s[n] (e.g., Figure 1A The in-phase signal s shown I [n] and / or quadrature signal s Q The received signal s[n] = s I [n]+js Q [n] passes through delay component 203a in the first path of IQMC 203. In the second path of IQMC 203, the received signal s[n] passes through complex-valued filter 203b. Complex-valued filter 203b may have L tap weights and may have an impulse response as shown in Equation 18 below.

[0109] [Equation 18]

[0110]

[0111] w TX,i are the tap weights, and i indexes the taps.

[0112] The output of the complex filter 203b is sent to the real value operator 203c, which passes the real value component of the signal to the aggregator 203d and blocks the imaginary component of the signal. The outputs of the two paths are aggregated (e.g., added) by the signal aggregator 203d, and the signal aggregator 203d outputs the compensated signal u[n]. The compensated signal u[n] may include Figure 1A The signal s shown in I [n] and / or signal s Q [n].

[0113] IQMC 203 may have certain IQMC parameters including L tap weights of complex-valued filter 203b. The techniques described herein (e.g., Figure 3 ) to determine, configure and / or set the IQMC parameters of the IQMC 203 to increase or maximize Figure 1A 100 . Once the IQMC parameters are determined, the IQMC 203 can be configured to implement those parameters. This implementation can be done at the time of manufacture or in the field, and in some embodiments, can be done dynamically (e.g., according to a maintenance schedule, or based on the condition of or feedback from a transmitter or transceiver containing the IQMC 203).

[0114] Referring to Equations 9 and 10, for IQMC 203, F 1TX (f) and F 2TX (f) can be expressed as in the following equation 19.

[0115] [Equation 19]

[0116]

[0117] Among them, W TX (f) can represent the frequency response w of the filter TX [n]. This, in conjunction with Equation 11, provides an example of a mathematical model for the IRR of the TX 100 including the IQMC 203. Additionally, this, in conjunction with Equation 12, provides an example of a mathematical model for the SINR of the TX 100 including the IQMC 203. Additionally, the above equations for F 1TX (f) and F 2TX The expression of (f) in conjunction with Equation 17 provides an example of a mathematical model for SImR of a TX 100 including an IQMC 203. With the above in mind, Equation 20 below provides an example of a mathematical model for IRR in a TX 100 including an IQMC 203.

[0118] [Equation 20]

[0119]

[0120] Among them, V TX (f) is defined as in Equation 15.

[0121] The techniques presented herein may be used to determine and / or implement IQMC parameters for improving, increasing, or maximizing IRR, SINR, and / or SImR, such as defining w TX [n] tap weight or limit W TX (f)(w TX The tap weights of the frequency domain response or Fourier transform (e.g., fast Fourier transform or other Fourier transform) of [n].

[0122] Figure 2C A diagram illustrating an RV IQMC according to some embodiments of the present disclosure. For brevity, the RV IQMC 204 may be referred to herein as IQMC 204. Figure 2C The IQMC 204 shown in FIG. 1 may include a controller configured to provide a delay T DThe delay component 204a is configured to receive a digitized input signal s, a multiplier 204b configured to multiply at least one input based on a multiplication factor, an aggregator 204c configured to aggregate (e.g., add) at least two input signals, and a real-valued filter 204d (e.g., an FIR filter). The delay component 204a can receive a digitized input signal s I [n], and a delay T can be introduced D To generate the compensated signal u I [n]. Input signal s I [n] may be input to the multiplier 204b, wherein the multiplier 204b multiplies the input signal s based on the real-valued cross-multiplication factor input to the multiplier 204b. I [n] is multiplied. The multiplied signal is input to the signal aggregator 204c, and the input signal S Q [n] is also input to the signal aggregator 204c. The signal aggregator 204c processes the multiplied signal and the input signal s Q [n] are aggregated (eg, added) and the resulting signal is output to real-valued filter 204d. Real-valued filter 204d may have L tap weights and may have an impulse response as shown in Equation 21 below.

[0123] [Equation 21]

[0124]

[0125] d TX,i is the tap weight, and i indexes the tap. The real-valued filter 204d outputs the compensated signal u Q [n].

[0126] IQMC 204 may have a real-valued cross-multiplication factor α that is input to multiplier 204b. TX and certain IQMC parameters of the L tap weights of the real-valued filter 204d. The techniques described herein (e.g., Figure 3 ) to determine, configure and / or set the IQMC parameters of the IQMC 204 to increase or maximize Figure 1A 100 . Once the IQMC parameters are determined, the IQMC 204 can be configured to implement those parameters. Such implementation can be done at the time of manufacture or in the field, and in some embodiments, can be done dynamically (e.g., according to a maintenance schedule, or based on the condition of or feedback from a transmitter or transceiver containing the IQMC 204).

[0127] Referring to Equation 9 and Equation 10, for the IQMC 204, it can be expressed as the following Equation 22.

[0128] [Equation 22]

[0129]

[0130] Among them, D TX (f) can represent the frequency response of the filter d TX [n]. This, in conjunction with Equation 11, provides an example of a mathematical model for the IRR of the TX 100 including the IQMC 204. Additionally, this, in conjunction with Equation 12, provides an example of a mathematical model for the SINR of the TX 100 including the IQMC 204. Additionally, the above equations for F 1TX (f) and F 2TX The expression of (f) in conjunction with Equation 17 provides an example of a mathematical model for the SImR of the TX 100 including the IQMC 204 .

[0131] Furthermore, Equation 23 below provides an example of a mathematical model for IRR in the TX 100 including the IQMC 204 .

[0132] [Equation 23]

[0133]

[0134] Among them, V TX (f) is defined as in Equation 15.

[0135] The techniques presented herein may be used to determine and / or implement IQMC parameters for improving, increasing, or maximizing IRR, SINR, and / or SImR, such as defining D TX [n] tap weight or limit d TX (f)(d TX The tap weights and / or α of the frequency domain response or Fourier transform (e.g., Fast Fourier Transform or other Fourier Transform) of [n] TX .

[0136] Figure 2D A diagram illustrating a CVIQMC according to some embodiments of the present disclosure. For simplicity, the CVIQMC 206 may be referred to herein as the IQMC 206. The IQMC 206 may include a processor configured to implement a delay T D The IQMC 206 may receive a signal r[n] (e.g., Figure 1B The in-phase signal r shown I [n] and / or quadrature signal r Q The received signal r[n] = r I [n]+jr Q [n] passes through a delay component 206a in the first path of the IQMC 206. In the second path of the IQMC 206, the received signal r[n] passes through a real-valued operator 206b, which passes the real-valued components of the input signal and blocks the imaginary components of the input signal. The output of the real-valued operator 206b is then sent to a complex-valued filter 206c. The complex-valued filter 206c may have L tap weights and may have an impulse response as shown in Equation 24 below.

[0137] [Equation 24]

[0138]

[0139] Among them, w RX，i are L tap weights and i indexes the taps. The outputs of the two paths are aggregated (eg, added) by a signal aggregator 206d, and the signal aggregator 206d outputs a compensated signal y[n]. The compensated signal y[n] may include Figure 1B The in-phase signal y shown I [n] and / or quadrature signal y Q [n].

[0140] IQMC 206 may have certain IQMC parameters including L tap weights of complex-valued filter 206c. The techniques described herein (e.g., Figure 3 ) to determine, configure and / or set the IQMC parameters of the IQMC 206 to increase or maximize Figure 1B , and the IRR and SINR and / or SImR of the RX 110 shown in FIG. Once the IQMC parameters are determined, the IQMC 206 can be configured to implement those parameters. Such implementation can be done at the time of manufacture or in the field, and in some embodiments, can be done dynamically (e.g., according to a maintenance schedule, or based on the condition of or feedback from a receiver or transceiver including the IQMC 206).

[0141] An example of a general mathematical model for signals processed by IQMC 112 in RX 110 is provided below. This general mathematical model is also applied below to certain example IQMCs (including IQMC 206).

[0142] We can use the IQMC 206 to write the frequency response of the compensated signal in the RX 110 as Equation 25 below.

[0143] [Equation 25]

[0144] Y(f)=F 1RX (f)R(f)+F 2RX (f)R * (-f)

[0145] Among them, F 1RX (f) and F 2RX (f) is a function of IQMC parameters and / or characteristics. By using Equation 6 and Equation 25, the compensated RX signal will be expressed as the following Equation 26.

[0146] [Equation 26]

[0147]

[0148] For IQMC 206, F 1RX (f) and F 2RX (f) can be expressed as the following Equation 27.

[0149] [Equation 27]

[0150]

[0151] Among them, W RX (f) can represent the frequency response w of the filter RX [n].

[0152] The following provides an example of a mathematical model for the IRR in the RX 110. One example formula for modeling the IRR of the RX 110 is shown in Equation 28 below.

[0153] [Equation 28]

[0154]

[0155] Using Equation 28 above for modeling the IRR of the RX 110, and the F above for the IQMC 206 1TX (f), F 2TX Equation 27 of (f) can mathematically model the IRR of the IQMC 206. Using the techniques described herein, such an IRR can be optimized.

[0156] The following provides an example of a mathematical model for the Signal to Interference and Noise Ratio (SINR) in the RX 110. An example formula for modeling the SINR of the RX 110 is shown in Equation 29 below.

[0157] [Equation 29]

[0158]

[0159] in, is the normalized RX noise variance, It can be expressed as the following equation 30.

[0160] [Equation 30]

[0161]

[0162] The IQMC coefficients may be determined by maximizing or increasing the SINR, which takes into account both the IQMM and noise effects. When the noise power is significant (e.g., comparable to or greater than the noise power of the image signal level), maximizing the SINR may provide significant improvements in system throughput. 1RX (f) and F 2RX Equation 27 of (f) Using Equation 29 above, the SINR for RX 110 with IQMC 206 can be mathematically modeled.

[0163] In some of the above derivations, we assume that at frequencies f1, ..., f K G 1RX (f), G 2RX (f) is known (e.g., by using the baseband frequencies f1, ..., f K However, it is possible to estimate the relative mismatch, but not the G 1RX (f), G 2RX (f) There is no independent reasonable estimate. The following provides an estimate of the relative mismatch even for G when the estimate is known. 1RX (f), G 2RX (f) Some techniques may be used without independent reasonable estimates.

[0164] The following provides an example of a mathematical model for the IRR in the RX 110. The following parameters are defined as functions of gain and filter mismatch as shown in Equation 31 below.

[0165] [Equation 31]

[0166]

[0167] An example formula for modeling the IRR of the RX 110 including the IQMC 206 is shown below in Equation 32.

[0168] [Equation 32]

[0169]

[0170] Some applications involve determining SImR instead of, or in addition to, IRR or SINR. Similar to IRR or SINR, SImR can indicate the performance or quality of IQMC. One example way to express SImR for RX is shown in Equation 33 below.

[0171] [Equation 33]

[0172]

[0173] The techniques presented herein may be used to determine and / or implement IQMC parameters for improving, increasing, or maximizing IRR, SINR, and / or SImR, such as defining w RX [n] (tap weights of the complex-valued filter 206c) or define W RX (f)(w RX The tap weights of the frequency domain response or Fourier transform (e.g., fast Fourier transform or other Fourier transform) of [n].

[0174] Figure 2E A diagram illustrating an RV IQMC according to some embodiments of the present disclosure. For brevity, the RV IQMC 208 may be referred to herein as IQMC 208. Figure 2E The IQMC 208 shown in FIG. 1 may include a controller configured to provide a delay T D The delay component 208a may receive a digitized input signal r, a multiplier 208b configured to multiply at least one input based on a multiplication factor, an aggregator 208c configured to aggregate (e.g., add) at least two input signals, and a real-valued filter 208d (e.g., an FIR filter). I [n], and a delay T can be introduced D To generate the compensated signal y I [n]. Compensated signal y I [n] may be input to multiplier 208b, wherein multiplier 208b is based on a real-valued cross-multiplication factor α input to multiplier 208b. RX To compensate the signal y I [n] is multiplied. The multiplied signal is input to the signal aggregator 208c. Input signal r Q [n] is input to the real-valued filter 208d. The real-valued filter 208d may have L tap weights and may have an impulse response as shown in Equation 34 below.

[0175] [Equation 34]

[0176]

[0177] Among them, d RX，i are the tap weights, and i indexes the taps.

[0178] The real-valued filter 208d outputs the filtered signal to the signal aggregator 208c. The signal aggregator 208c aggregates (eg, adds) the multiplied signal and the filtered signal and outputs the resultant signal r Q [n].

[0179] IQMC 208 may have a real-valued cross-multiplication factor α that is input to multiplier 208b. RX and certain IQMC parameters of the L tap weights of the real-valued filter 208d. The techniques described herein (e.g., Figure 3 ) to determine, configure and / or set the IQMC parameters of the IQMC 208 to increase or maximize Figure 1B . Once the IQMC parameters are determined, the IQMC 208 can be configured to implement those parameters. Such implementation can be done at the time of manufacture or in the field, and in some embodiments, can be done dynamically (e.g., according to a maintenance schedule, or based on the condition of or feedback from a receiver or transceiver that includes the IQMC 208).

[0180] For IQMC 208, F 1RX (f) and F 2RX (f) can be expressed as the following Equation 35.

[0181] [Equation 35]

[0182]

[0183] Among them, D RX (f) can represent the frequency response of the filter d RX [n].

[0184] Using Equation 32 above for modeling the IRR of the RX 110, and the F for the IQMC 208 1RX (f) and F 2RX Equation 35 above at (f) can mathematically model the IRR of the IQMC 208. Using the techniques described herein, such an IRR can be optimized.

[0185] In some of the above derivations, we assume that at frequencies f1, ..., f K G 1RX (f), G 2RX(f) is known (e.g., by using the baseband frequencies f1, ..., f K However, it is possible to estimate the relative mismatch, but not the G 1RX (f), G 2RX (f) There is no independent reasonable estimate. The following provides an estimate of the relative mismatch even for G when the estimate is known. 1RX (f), G 2RX (f) Some techniques may be used without independent reasonable estimates.

[0186] The following provides an example of a mathematical model for the IRR in the RX 110. An example formula for modeling the IRR of the RX 110 including the IQMC 208 is shown below in Equation 36:

[0187] [Equation 36]

[0188]

[0189] Among them, V RX (f) is defined as in Equation 31.

[0190] The techniques presented herein can be used to determine and / or implement IQMC parameters for improving, increasing, or maximizing IRR, such as defining d RX The tap weights of [n] (the tap weights of the real-valued filter 208d) or the limit D RX (f)(d RX The tap weights and / or α of the frequency domain response or Fourier transform (e.g., Fast Fourier Transform or other Fourier Transform) of [n] RX .

[0191] In addition, in conjunction with the F 1RX (f) and F 2RX The above equation 35 of (f) uses equation 29 to mathematically model the SINR for the RX 110 with the IQMC 208.

[0192] Additionally, some applications involve determining SImR instead of, or in addition to, determining IRR or SINR. Similar to IRR or SINR, SImR can indicate the performance or quality of IQMC. One example way to express the SImR of RX is as shown in Equation 33. Using this equation and the F for IQMC 208 1RX (f) and F 2RX The above equation 35 of (f) can mathematically model the SImR of the RX including the IQMC 208.

[0193] Figure 3 The IQMC parameter optimization method according to some embodiments of the present disclosure is shown. The IQMC parameter optimization method 300 can be performed by a computing device including a communication device (such as a device including a TX and / or RX, or a device including an IQMC being optimized or tested). The IQMC parameter optimization method 300 can also be performed by a computing device that does not include an IQMC being optimized or tested.

[0194] As a brief overview, the described IQMC parameter optimization method 300 includes setting initial IQMC parameter values (S302), determining performance metric values using the IQMC parameter values (S304), and determining whether to perform another iteration (S306). If, at operation (S306), the computing device determines to perform another iteration, the IQMC parameter optimization method 300 proceeds to operation (S308) including updating the IQMC parameter values and returns to operation (S304). Otherwise, the IQMC parameter optimization method S300 proceeds to determining an optimal IQMC parameter value from a set of tested IQMC parameter values (S310).

[0195] The IQMC parameter optimization method 300 is an iterative technique that provides for determining IQMC parameters that increase or maximize a performance metric such as IRR, SINR, and / or SImR of a TX chain or RX chain. The iterative technique may include, for example, a gradient ascent or gradient descent technique such as Figure 4 ), or other suitable iterative techniques, such as Newton's method.

[0196] In general, IRR, SINR, and SImR can be frequency-dependent, and the techniques described herein can be implemented to determine or set IQMC parameters for increasing or maximizing the IRR, SINR, or SImR of a TX or RX chain for a specific frequency, for a specific set of frequencies, and / or for a function of one or more frequencies (e.g., the average IRR, SINR, or SImR over a set of frequencies). For example, these techniques can be used to determine or set IQMC parameters for increasing or maximizing the lowest IRR in a set of IRRs corresponding to a set of frequencies of interest (such as the frequencies of a specific channel being used by a TX, RX, or transceiver). The lowest IRR is typically (but not always) found at the edges of the channel rather than in the middle of the channel (e.g., at edges corresponding to 5% or less, 10% or less, or 15% or less of the total frequency band of the channel), and IQMC parameters can be selected to increase or maximize the IRR for one or more frequencies corresponding to such edges. In other embodiments, different criteria can be used to select the IRR (corresponding to a specific frequency) to be increased or maximized. For example, iterative techniques may be used to determine or set IQMC parameters for increasing or maximizing the minimum geometric mean of IRR per component carrier (CC) in a carrier aggregation (CA) scheme. SINR and SImR may be optimized in a similar manner as described above for IRR.

[0197] exist Figure 3 In operation S302, the computing device sets initial IQMC parameter values. The IQMC parameter values may be any suitable IQMC parameter values for any suitable IQMC parameter, including any IQMC parameter discussed herein, such as tap weights of filters for TX or RX IQMC and / or real-valued cross-multiplication factors (e.g., when optimizing IQMC parameters for RV IQMC). The initial IQMC parameter values may be selected in any suitable manner, such as, for example, by performing an optimization without the assumption of an IQMM.

[0198] At operation 304, the computing device determines a performance metric value using at least one candidate parameter value (e.g., using an initial IQMC parameter value or using an updated IQMC parameter value). Note that in some embodiments, a candidate parameter value is selected for one IQMC parameter, and in other embodiments, a respective candidate parameter value is selected for each of a plurality of IQMC parameters. The performance metric may include an IRR, SINR, and / or SImR for a communication device including an IQMC whose at least one parameter is being optimized. The performance metric value may be estimated using a real or simulated IQMC that implements or utilizes the candidate parameter values.

[0199] In some embodiments, the IQMC parameter optimization method S300 is an iterative gradient ascent or gradient descent method, and at S304, the computing device uses the IQMC parameters to determine a performance metric and a gradient of the performance metric. The performance metric may be calculated, for example, as described herein. For example, F may be used in calculating the performance metric. 1TX / RX (f) and F 2TX / RX (f) or φ TX / RX and V TX / RX Some values of (f) are IQMM parameters at the TX chain and the RX chain, where the IQMM parameters may be known a priori or may be, for example, pilot signals sent by the chains (e.g., at continuous-time baseband frequencies ±f1, ..., ±f K Send a pilot signal) and use the recorded results of this propagation to estimate F 1TX / RX (f) and F 2TX / RX (f) or φ TX / RX and V TX / RX (f) is used to estimate. In some embodiments, it can be assumed that the frequencies ±f1, ..., ±f K F 1TX / RX (f) and F 2TX / RX (f) or φ TX / RX and V TX / RX (f) are estimated and these can be used to obtain the IQMC parameter values.

[0200] Any suitable technique (such as the following for Figure 4 In some embodiments, an iterative technique is used to determine or set the IQMC parameter value that optimizes the minimum geometric mean of the IRR per CC in the CA scheme, and the calculation of the gradient may include converting the performance metric to a logarithmic scale and using a regularized expectation.

[0201] In operation S306, the computing device determines whether to perform another iteration. This determination can be based on, for example, the expiration of a timeout period, the reaching of a predetermined number of iterations, the loss of the iteration (in embodiments using a loss function) being at or below a predetermined threshold, the performance metric of the iteration being calculated to be at or above a predetermined threshold (e.g., at or above the performance metric for another frequency or set of frequencies of interest in the channel), or a combination thereof. Other criteria may also be appropriately included in the determination of whether to perform another iteration. If the computing device determines to perform another iteration, the method proceeds to operation S308. If the computing device determines not to perform another iteration, the method proceeds to operation S310.

[0202] In operation S308, the computing device updates the IQMC candidate parameter values. The computing device may update the IQMC candidate parameter values using the current IQMC candidate parameter values, using the performance metric values calculated in operation S304, using a plurality of previous IQMC candidate parameter values, using a change in the performance metric values calculated for the plurality of previous IQMC candidate parameter values, or in any other suitable manner. For example, in some embodiments, a gradient ascent method is implemented, and as follows for Figure 4 As described above, one or more IQMC parameter values are changed along the gradient direction. Then, in the next iteration of the IQMC parameter optimization method 300, these updated parameters are used in operation S304.

[0203] In operation S310, one or more optimal, high-performance, or best-performance IQMC parameter values from a set of tested IQMC candidate parameter values (e.g., a set of IQMC candidate parameter values used in at least one iteration of the IQMC parameter optimization method S300) are identified, determined, or selected and may be implemented in the IQMC (e.g., the IQMC may be adjusted to achieve the optimal IQMC parameter values). Thus, the IQMC is implemented using optimized IQMC parameters for increasing or maximizing the IRR of the TX chain or RX chain. This improved IRR may improve the performance of a device including or implementing the TX chain or RX chain.

[0204] Figure 4 A flow chart showing an IQMC parameter optimization method according to some embodiments of the present disclosure is shown. Figure 4 , Figure 4 An example of a gradient ascent (or gradient descent) method for iteratively determining IQMC parameters that maximizes or increases the lowest IRR in a set of IRRs corresponding to a set of frequencies of interest in a TX chain or an RX chain is shown. Although the example method depicted uses IRR as the IQMC performance metric, a similar method can be implemented using SINR and / or SImR.

[0205] As a general overview, Figure 4The example IQMC parameter optimization method 400 shown includes selecting an initial solution (S402) and determining whether additional iterations are appropriate (S404). If it is determined at this operation that additional iterations are appropriate (No in S404), the example IQMC parameter optimization method 400 proceeds to selecting a frequency corresponding to a minimum IRR in a set of IRRs of interest (S406), determining a gradient (S408), updating IQMC parameters using the gradient (S410), incrementing an iteration index or count (S412), and returning to operation S404. If it is determined at operation S404 that additional iterations are not appropriate (Yes in S404), the example IQMC parameter optimization method 400 proceeds to identifying an iteration index with a minimum IRR (S414) and setting IQMC parameters corresponding to the iteration index identified in operation S414 (S416). The process then ends (S418).

[0206] The following provides some example mathematical frameworks and background that may be used when implementing the IQMC parameter optimization method 400. The following provides, among other things, tools for defining performance metrics as a function of one or more IQMC parameters and gradients of performance metrics for the one or more IQMC parameters that may be used when implementing the IQMC parameter optimization method S400.

[0207] Let x denote a vector of coefficients of the IQMC block in TX or RX. x in RV IQMC may be expressed as in Equation 37 below, and x in CV IQMC may be expressed as in Equation 38 below.

[0208] [Equation 37]

[0209] x=[α TX / RX , d TX / RX，0 ,...,d TX / RX，L-1 ] T

[0210] [Equation 38]

[0211] x=[Re{w TX / RX，0}, ..., Re{w TX / RX，L-1},Im{w TX / RX，0}, ..., Im{w TX / RX，L-1} T

[0212] To maximize the IRR, the optimization problem can be formulated as Equation 39 below.

[0213] [Equation 39]

[0214]

[0215] Among them, the cost function Depends on the IQMC parameter x. For IRR maximization, the cost function is the selected / measured continuous time frequency f=f1, ..., f over the desired frequency band K IRR TX / RX (f) function. For SINR maximization, the cost function is the selected / measured continuous time frequency f=f1, ..., f over the desired frequency band K SINR at TX / RX (f) is a function of

[0216] The above optimization problem can be solved, for example, using a gradient ascent (GA) search method (although other methods can also be used), which is The iterative update rule is given by the following equation 40.

[0217] [Equation 40]

[0218]

[0219] in, represents the function of the iteration index, and μ in Equation 40 represents For CV IQMC It can be the following equation 41, and for RV IQMC It can be the following equation 42.

[0220] [Equation 41]

[0221]

[0222] [Equation 42]

[0223]

[0224] The starting point x0 may be chosen appropriately (e.g., a non-IQMC solution may be used). Iterations are continued until convergence is reached or the maximum number of allowed iterations is reached. The IQMC coefficients are then set to the IQMC coefficients that provide the optimized (in this case, maximum) cost function in the iteration of the IQMC parameter optimization method 400.

[0225] make represents the set of desired continuous time frequencies over the desired frequency band: Some example cost functions for IRR maximization are Equation 43 below.

[0226] [Equation 43]

[0227]

[0228] Equation 43 uses Equation 44 to express the minimum IRR at the desired frequency.

[0229] [Equation 44]

[0230]

[0231] [Equation 45]

[0232]

[0233] Equation 45 expresses the average value of the IRR over the desired frequency using Equation 46 below.

[0234] [Equation 46]

[0235]

[0236] [Equation 47]

[0237]

[0238] Equation 47 expresses the geometric mean of the IRR at the desired frequency using Equation 48 below (note that since maximization in the log domain is equivalent to maximization in the linear scale, the gradient calculation of the geometric mean can be simpler if the IRR is converted to a log scale and the canonical mean is used instead).

[0239] [Equation 48]

[0240]

[0241] [Equation 49]

[0242]

[0243] Equation 49 represents the minimum geometric mean of IRR per CC in a carrier aggregation scenario, where is a set of selected frequencies that are within the frequency range of the kth CC.

[0244] Some example cost functions for SINR maximization are Equation 50 below.

[0245] [Equation 50]

[0246]

[0247] Equation 50 expresses the minimum SINR at the desired frequency using Equation 51 below.

[0248] [Equation 51]

[0249]

[0250] [Equation 52]

[0251]

[0252] Equation 52 uses Equation 53 to express the sum throughput over the desired frequency.

[0253] [Equation 53]

[0254]

[0255] To use Equation 43 to Equation 53 and calculate The gradient of f1, ..., f K G 1TX (f), G 2TX (f) or G 1RX (f), G 2RX (f) Estimates are made and use them to optimize the IQMC coefficients.

[0256] The gradient of IRR with respect to the IQMC coefficient can be calculated as shown in Equation 54 below.

[0257] [Equation 54]

[0258]

[0259] Among them, J1(f), J2(f), and It can be expressed as the following equations 55 to 58.

[0260] [Equation 55]

[0261]

[0262] [Equation 56]

[0263]

[0264] [Equation 57]

[0265]

[0266] [Equation 58]

[0267]

[0268] Similarly, the gradient of SINR with respect to the IQMC coefficient can be calculated as shown in Equation 59 and Equation 60 below.

[0269] [Equation 59]

[0270]

[0271] [Equation 60]

[0272]

[0273] Among them, J1(f), J2(f), and is defined in Equations 54 to 58. J3(f) and its gradient are defined as in Equations 61 and 62 below.

[0274] [Equation 61]

[0275] J3(f)=|F 1RX (f)| 2 +|F 2RX (f)| 2

[0276] [Equation 62]

[0277]

[0278] Continuous time frequency f k The discrete Fourier transform (DFT) vector at is defined as in Equation 63 below.

[0279] [Equation 63]

[0280]

[0281] Among them, F s Denotes the sampling rate at which IQMC operates. Assuming that an FIR filter of length L is used, IQMC is defined as shown in the following equations 64 to 68.

[0282] [Equation 64]

[0283]

[0284] [Equation 65]

[0285]

[0286] [Equation 66]

[0287]

[0288] [Equation 67]

[0289]

[0290] [Equation 68]

[0291]

[0292] Among them, these five filter parameters are respectively related to Figures 2A to 2E Then, for the IQMC Figure 2A The IQMC 202 shown in It can be calculated as shown in the following equations 69 to 71.

[0293] [Equation 69]

[0294] x=[Re{w 1TX，0}, ..., Re{w 1TX，L-1},Im{w 1TX，0}, ..., Im{w 1TX，L-1}] T

[0295] [Equation 70]

[0296]

[0297] [Equation 71]

[0298]

[0299] Among them, w 1，TX is the following equation 72.

[0300] [Equation 72]

[0301] w 1,TX =[w 1TX,0 ,...,w 1TX,L-1 ] T

[0302] against Figure 2B The IQMC 203 shown in It can be calculated as shown in the following equations 73 to 75.

[0303] [Equation 73]

[0304] x=[Re{w 2TX，0}, ..., Re{w 2TX，L-1},Im{w 2TX，0}, ..., Im{w 2TX，L-1}] T

[0305] [Equation 74]

[0306]

[0307] [Equation 75]

[0308]

[0309] Among them, w 2，TX is Equation 76 below.

[0310] [Equation 76]

[0311] w 2，TX =[w 2TX，0 ,...,w 2TX，L-1 ] T

[0312] against Figure 2C The IQMC 204 shown in It can be calculated as shown in the following equations 77 to 79.

[0313] [Equation 77]

[0314]

[0315] [Equation 78]

[0316]

[0317] [Equation 79]

[0318]

[0319] Among them, d TX is the following equation 80.

[0320] [Equation 80]

[0321] d TX =[d TX,0 ,...,d TX,L-1 ] T

[0322] against Figure 2D The IQMC 206 shown in It can be calculated as shown in the following equations 81 to 83.

[0323] [Equation 81]

[0324] x=[Re{w RX,0},...,Re{w RX,L-1},Im{w RX,0},...,Im{w RX,L-1}] T

[0325] [Equation 82]

[0326]

[0327] [Equation 83]

[0328]

[0329] Among them, W RX is the following equation 84.

[0330] [Equation 84]

[0331] w RX =[w RX,0 ,...,w RX,L-1 ] T against Figure 2E The IQMC 208 shown in It can be calculated as shown in the following equations 85 to 87.

[0332] [Equation 85]

[0333] x=[α RX ,d T RX ] T =[α RX ,d RX,0 ,...,d RX,L-1 ] T

[0334] [Equation 86]

[0335]

[0336] [Equation 87]

[0337]

[0338] Among them, d RX is the following equation 88.

[0339] [Equation 88]

[0340] d RX =[d RX,0 ,...,d RX,L-1 ] T

[0341] The above equations provide some examples of mathematical modeling, where when the frequencies f1, ..., f K G 1TX (f), G 2TX (f) or G 1RX (f), G2RX (f) is known (e.g., by using the baseband frequencies f1, ..., f K These examples may be appropriate when a pilot signal is sent at each location to estimate .

[0342] Equations 13, 15, 16, 22, and 24 provide some examples of mathematical modeling of IRR, where these examples can be found in G 1TX (f), G 2TX (f) or G 1RX (f), G 2RX (f) is not known alone but V TX (f) and φ TX or V RX (f) and φ RX is known (e.g., by using the baseband frequencies f1, ..., f K The following provides some examples of mathematical modeling of the gradient of the cost function corresponding to such IRR modeling.

[0343] In order to calculate this cost function gradient Can make Represents the index of the frequency with the minimum IRR value at the lth iteration. Continuous time frequency f k The DFT vector at can be defined as in Equation 89 below.

[0344] [Equation 89]

[0345]

[0346] Among them, F s represents the sampling rate at which IQMC operates. The cost function for the RV IQMC coefficients for TX can then be given by the following equations 90 to 92: gradient.

[0347] [Equation 90]

[0348]

[0349] [Equation 91]

[0350]

[0351] [Equation 92]

[0352]

[0353] Cost function for RV IQMC coefficients of RX The gradient of can be given by Equations 93 to 95 below.

[0354] [Equation 93]

[0355]

[0356] [Equation 94]

[0357]

[0358] [Equation 95]

[0359]

[0360] Similar steps can be followed for other cost functions and the gradients of CV IQMC or other IQMC structures can be obtained. The cost function can be appropriately selected to optimize the desired performance metric. For example, for SImR, using the formula shown in Equation 17 or Equation 33, any of the following example cost functions represented as Equations 96 to 99 below can be defined.

[0361] [Equation 96]

[0362]

[0363] Equation 96 is the minimum SImR at the desired frequency (frequency of interest).

[0364] [Equation 97]

[0365]

[0366] Equation 97 is the average value of SImR at the desired frequency.

[0367] [Equation 98]

[0368]

[0369] Equation 98 is the geometric mean of SImR at the desired frequency.

[0370] [Equation 99]

[0371]

[0372] Equation 99 is the minimum geometric mean of SImR per component carrier (CC) in a carrier aggregation (CA) scenario.

[0373] Using these example cost functions, the gradient of the selected SImR can be calculated using a similar framework as described above for IRR. In addition, the specific IRR or SINR for optimization (i.e., the IRR or SINR corresponding to a specific frequency) can be selected from a similar list as above, for example, the minimum IRR or SINR over the desired frequency, the average IRR or SINR over the desired frequency, the geometric mean IRR or SINR over the desired frequency, or the minimum geometric mean IRR or SINR per CC in a CA scenario. Optimization of other IRRs, SINRs, or SImRs (i.e., IRRs, SINRs, or SImRs corresponding to different frequencies) can also be implemented using the techniques described herein when appropriate.

[0374] Figure 5 A diagram illustrating an electronic device in a network environment according to some embodiments of the present disclosure. Figure 5 , an electronic device 501 in a network environment 500 can communicate with an electronic device 502 via a first network 598 (e.g., a short-range wireless communication network such as a Wi-Fi network), or can communicate with an electronic device 504 or a server 508 via a second network 599 (e.g., a long-range wireless communication network). The electronic device 501 can communicate with the electronic device 504 via the server 508. The electronic device 501 may include a processor 520, a memory 530, an input device 550, a sound output device 555, a display device 560, an audio module 570, a sensor module 576, an interface 577, a haptic module 579, a camera module 580, a power management module 588, a battery 589, a communication module 590, a subscriber identification module (SIM) 596, and / or an antenna module 597. In one embodiment, at least one of the components (e.g., the display device 560 or the camera module 580) may be omitted from the electronic device 501, or one or more other components may be added to the electronic device 501. In one embodiment, some of the components may be implemented as a single integrated circuit (IC). For example, the sensor module 576 (e.g., a fingerprint sensor, an iris sensor, or an illumination sensor) may be embedded in the display device 560 (e.g., a display), or the display device 560 may further include one or more sensors in addition to the sensor module 576.

[0375] In some embodiments, the electronic device 501 may include the TX 100 or the RX 110 (or both). The electronic device 501 may include an IQMC (including Figures 2A to 2E In some embodiments, the electronic device 501 may include a device configured to implement an IQMC optimization technique (such as Figure 3 The IQMC parameter optimization method 300 shown or Figure 4 A computing device for the IQMC parameter optimization method 400 shown.

[0376] The processor 520 can execute, for example, software (e.g., program 540) to control at least one other component of the electronic device 501 coupled to the processor 520 (e.g., hardware or software component), and can perform various data processing and / or calculations. As at least part of the data processing and / or calculations, the processor 520 can load commands or data received from another component (e.g., sensor module 576 or communication module 590) into the volatile memory 532, process the commands or data stored in the volatile memory 532, and store the resulting data in the non-volatile memory 534. The processor 520 can include a main processor 521 (e.g., a central processing unit (CPU) or an application processor (AP)) and an auxiliary processor 523 (e.g., a graphics processing unit (GPU), an image signal processor (ISP), a sensor hub processor, or a communication processor (CP)) that can operate independently of the main processor 521 or in conjunction with the main processor 521. Additionally or alternatively, the auxiliary processor 523 can be adapted to consume less power than the main processor 521 and / or perform specific functions. The auxiliary processor 523 may be implemented separately from the main processor 521 or as part of the main processor 521 .

[0377] The auxiliary processor 523 may control at least some of the functions or states related to at least one of the components of the electronic device 501 (e.g., the display device 560, the sensor module 576, or the communication module 590) in place of the main processor 521 when the main processor 521 is in an inactive (e.g., sleep) state, or control at least some of the functions or states related to at least one of the components of the electronic device 501 (e.g., the display device 560, the sensor module 576, or the communication module 590) together with the main processor 521 when the main processor 521 is in an active state (e.g., executing an application). According to one embodiment, the auxiliary processor 523 (e.g., an image signal processor or a communication processor) may be implemented as part of another component (e.g., the camera module 580 or the communication module 590) that is functionally related to the auxiliary processor 523.

[0378] The memory 530 may store various data used by at least one component of the electronic device 501 (e.g., the processor 520 or the sensor module 576). The various data may include, for example, software (e.g., the program 540) and input data or output data for commands related thereto. The memory 530 may include a volatile memory 532 and / or a non-volatile memory 534.

[0379] The program 540 may be stored as software in the memory 530 and may include, for example, an operating system (OS) 542 , middleware 544 , or applications 546 .

[0380] The input device 550 may receive a command or data from outside the electronic device 501 (eg, a user) to be used by another component of the electronic device 501 (eg, the processor 520). The input device 550 may include, for example, a microphone, a mouse, and / or a keyboard.

[0381] The sound output device 555 can output sound signals to the outside of the electronic device 501. The sound output device 555 can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as playing multimedia or records, and the receiver can be used to receive incoming calls. According to one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0382] The display device 560 can visually provide information to the outside of the electronic device 501 (e.g., a user). The display device 560 may include, for example, a display, a holographic device, and / or a projector, and a control circuit for controlling a corresponding one of the display, the holographic device, and the projector. According to one embodiment, the display device 560 may include a touch circuit adapted to detect a touch, or a sensor circuit adapted to measure the strength of the force caused by the touch (e.g., a pressure sensor).

[0383] The audio module 570 can convert sound into an electrical signal, and vice versa. According to one embodiment, the audio module 570 can obtain sound via the input device 550 and / or output sound via the sound output device 555 or an earphone of an external electronic device 502 directly (e.g., wired) or wirelessly coupled to the electronic device 501.

[0384] The sensor module 576 can detect the operating state (e.g., power or temperature) of the electronic device 501 and / or the environmental state (e.g., the state of the user) outside the electronic device 501, and then generate an electrical signal or data value corresponding to the detected state. The sensor module 576 may include, for example, a gesture sensor, a gyroscope sensor, an atmospheric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, and / or an illumination sensor.

[0385] The interface 577 may support one or more designated protocols for the electronic device 501 to be directly (e.g., wired) or wirelessly coupled to the external electronic device 502. According to one embodiment, the interface 577 may include, for example, a High-Definition Multimedia Interface (HDMI), a Universal Serial Bus (USB) interface, a Secure Digital (SD) card interface, and / or an audio interface.

[0386] The connection end 578 may include a connector via which the electronic device 501 can be physically connected to the external electronic device 502. According to one embodiment, the connection end 578 may include, for example, an HDMI connector, a USB connector, an SD card connector, and / or an audio connector (e.g., a headphone connector).

[0387] The haptic module 579 may convert electrical signals into mechanical stimulation (eg, vibration or motion) and / or electrical stimulation that can be recognized by the user via tactile or kinesthetic sense. According to one embodiment, the haptic module 579 may include, for example, a motor, a piezoelectric element, and / or an electrical stimulator.

[0388] The camera module 580 may capture still images or moving images. According to one embodiment, the camera module 580 may include one or more lenses, image sensors, image signal processors, and / or flashes.

[0389] The power management module 588 may manage power supplied to the electronic device 501. The power management module 588 may be implemented as, for example, at least a portion of a power management integrated circuit (PMIC).

[0390] The battery 589 may supply power to at least one component of the electronic device 501. According to one embodiment, the battery 589 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, and / or a fuel cell.

[0391] The communication module 590 can support establishing a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device 501 and an external electronic device (e.g., electronic device 502, electronic device 504 and / or server 508), and perform communication via the established communication channel. The communication module 590 may include one or more communication processors that can operate independently of the processor 520 (e.g., AP), and can support direct (e.g., wired) communication and / or wireless communication. According to one embodiment, the communication module 590 may include a wireless communication module 592 (e.g., a cellular communication module, a short-range wireless communication module and / or a global navigation satellite system (GNSS) communication module) or a wired communication module 594 (e.g., a local area network (LAN) communication module or a power line communication (PLC) module). A corresponding one of these communication modules can communicate via a first network 598 (e.g., a short-range communication network such as Bluetooth®). Wireless Fidelity (Wi-Fi) Direct and / or Infrared Data Association (IrDA) standards) or a second network 599 (e.g., a telecommunications network such as a cellular network, the Internet, and / or a computer network (e.g., a LAN or wide area network (WAN))) to communicate with an external electronic device. is a registered trademark of Bluetooth SIG, Inc., Kirkland, WA. These various types of communication modules can be implemented as a single component (e.g., a single IC), or can be implemented as multiple components (e.g., multiple ICs) separated from each other. The wireless communication module 592 can use the user information (e.g., International Mobile Subscriber Identity (IMSI)) stored in the user identification module 596 to identify and authenticate the electronic device 501 in the communication network (such as the first network 598 or the second network 599).

[0392] The antenna module 597 can transmit signals and / or power to the outside of the electronic device 501 (e.g., an external electronic device), and / or receive signals and / or power from the outside of the electronic device 501 (e.g., an external electronic device). According to one embodiment, the antenna module 597 may include one or more antennas, and thus, at least one antenna suitable for a communication scheme used in a communication network such as the first network 598 and / or the second network 599 can be selected by, for example, the communication module 590 (e.g., the wireless communication module 592). Signals and / or power can then be transmitted and / or received between the communication module 590 and the external electronic device via the selected at least one antenna.

[0393] At least some of the above components can be coupled to each other and communicatively transmit signals (e.g., commands and / or data) therebetween via an inter-peripheral communication scheme (e.g., a bus, general purpose input output (GPIO), a serial peripheral interface (SPI), and / or a mobile industry processor interface (MIPI)).

[0394] According to one embodiment, commands and / or data may be sent and / or received between the electronic device 501 and the external electronic device 504 via a server 508 coupled to the second network 599. Each of the electronic device 502 and the electronic device 504 may be a device of the same type or a different type as the electronic device 501. All or some of the operations to be performed at or by the electronic device 501 may be performed at one or more of the external electronic devices 502, 504, or 508. For example, if the electronic device 501 is to perform a function and / or service automatically or in response to a request from a user or another device, the electronic device 501 may request one or more external electronic devices 502, 504, 508 to perform at least a portion of the function and / or service instead of, or in addition to, performing the function and / or service. The one or more external electronic devices that receive the request may execute at least a portion of the requested function and / or service and / or additional functions and / or additional services related to the request, and transmit the execution results to the electronic device 501. The electronic device 501 may provide the results as at least a portion of the reply to the request with or without further processing. To this end, for example, cloud computing technology, distributed computing technology, and / or client-server computing technology may be used.

[0395] One embodiment may be implemented as software (e.g., program 540) comprising one or more instructions stored in a storage medium (e.g., internal memory 536 or external memory 538) readable by a machine (e.g., electronic device 501). For example, the processor 520 of the electronic device 501 may call at least one of the one or more instructions stored in the storage medium with or without one or more other components under the control of the processor 520 and execute the instruction. Thus, the machine may be operated to perform at least one function according to the called at least one instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. The term "non-transitory" indicates that the storage medium is a tangible device and does not include signals (e.g., electromagnetic waves), but the term does not distinguish between data being semi-permanently stored in the storage medium and data being temporarily stored in the storage medium.

[0396] According to one embodiment, the method of the present disclosure may be included and provided in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read-only memory (CD-ROM)), or distributed online (e.g., downloaded or uploaded) via an application store (e.g., PlayStore™), or distributed directly between two user devices (e.g., smart phones). If distributed online, at least a portion of the computer program product may be temporarily generated or at least temporarily stored in a machine-readable storage medium (such as a memory of a manufacturer's server, a memory of an application store's server, or a memory of a relay server).

[0397] The present disclosure provides various modifications and various embodiments. It should be understood that the present disclosure is not limited to the various embodiments explicitly described or detailed herein, and that the present disclosure includes modifications, equivalents, and alternatives within the scope of the present disclosure.

[0398] Although can use comprise such as first, second etc. ordinal number term to describe various elements, element is not limited by such term.Such term is used to distinguish an element from another element, and does not imply any particular order.As used herein, term " and / or " comprises any and all combinations of one or more related items.Unless context clearly states otherwise, otherwise singular form is intended to include plural form.In the present disclosure, it should be understood that term " comprises " or " has " the existence of indicating characteristic, quantity, step, operation, structural element, part or its combination, and does not exclude the existence of one or more other characteristics, quantity, step, operation, structural element, part or its combination, or adds the possibility of one or more other characteristics, quantity, step, operation, structural element, part or its combination.

[0399] According to one embodiment, at least one of the above-mentioned components (e.g., a manager, a set of processor-executable instructions, a program, or a module) may include a single entity or multiple entities. One or more of the above-mentioned components may be omitted, or one or more other components may be added. Alternatively or additionally, multiple components (e.g., a manager, a set of processor-executable instructions, a program, or a module) may be integrated into a single component. In this case, the integrated component may still perform one or more functions of each of the multiple components in the same or similar manner as the functions performed by the corresponding one of the multiple components before integration. The operations performed by the manager, a set of processor-executable instructions, a program, a module, or another component may be performed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations may be performed in a different order or omitted, or one or more other operations may be added.

Claims

1. A method for optimizing at least one IQMC parameter value of at least one IQMC parameter of an in-phase I and quadrature Q mismatch compensator MC IQMC, comprising: A set of tested IQMC candidate parameter values is generated by executing an iterative method until an exit condition is reached, wherein at least one iteration of the iterative method comprises: selecting a first IQMC candidate parameter value for the at least one IQMC parameter of the IQMC; selecting a frequency corresponding to a minimum performance metric value, the performance metric value comprising at least one of the following: (i) an image rejection ratio (IRR) value, (ii) a signal to interference and noise ratio (SINR) value, or (iii) a signal to image ratio (SImR) value; determining a performance metric value for the selected frequency using the first IQMC candidate parameter value; and determining a second IQMC candidate parameter value that is an update to the first IQMC candidate parameter value, The set of IQMC candidate parameter values to be tested includes at least a first IQMC candidate parameter value and a second IQMC candidate parameter value, and The IQMC candidate parameter value that optimizes the performance metric value is determined by selecting the IQMC candidate parameter value having the largest performance metric value from the set of tested IQMC candidate parameter values.

2. The method according to claim 1, wherein The iterative method is a gradient ascent method or a gradient descent method, and the iterative method further comprises calculating the gradient of the performance metric value.

3. The method according to claim 2, wherein: The gradient ascent method or the gradient descent method uses a cost function that is a function of the at least one IQMC parameter.

4. The method according to claim 3, wherein: The cost function is also a function of I and Q mismatch IQMM parameters corresponding to an up-conversion circuit or a down-conversion circuit directly or indirectly connected to the IQMC.

5. The method according to claim 3, wherein: The at least one IQMC parameter comprises at least one tap weight of a filter of the IQMC.

6. The method according to claim 5, wherein: The IQMC comprises a real-valued RV IQMC including a multiplier, and the at least one IQMC parameter comprises a real-valued cross-multiplication factor input to the multiplier.

7. The method of claim 1, wherein: The IQMC includes a complex-valued CV IQMC.

8. The method of claim 1, wherein: The IQMC includes a real-valued RV IQMC.

9. The method of claim 1, wherein: The performance metric value includes the IRR value, and the IRR value is a minimum IRR value in a set of IRR values of the IQMC, wherein the set of IRR values corresponds to different frequencies.

10. The method of claim 1, wherein: The performance metric value includes the IRR value, and the IRR value is a minimum arithmetic or geometric mean of IRR values per carrier unit CC in a carrier aggregation (CA) scheme.

11. An apparatus configured to optimize at least one IQMC parameter value for at least one IQMC parameter of an in-phase I and quadrature Q mismatch compensator MC IQMC, comprising: processor; as well as A non-transitory processor-executable medium storing instructions that, when executed by a processor, cause the processor to: A set of tested IQMC candidate parameter values is generated by executing an iterative method until an exit condition is reached, wherein at least one iteration of the iterative method comprises: selecting a first IQMC candidate parameter value for the at least one IQMC parameter of the IQMC; selecting a frequency corresponding to a minimum performance metric value, the performance metric value comprising at least one of the following: (i) an image rejection ratio (IRR) value, (ii) a signal to interference and noise ratio (SINR) value, or (iii) a signal to image ratio (SImR) value; determining a performance metric value for the selected frequency using the first IQMC candidate parameter value; and determining a second IQMC candidate parameter value that is an update to the first IQMC candidate parameter value, The set of IQMC candidate parameter values to be tested includes at least a first IQMC candidate parameter value and a second IQMC candidate parameter value, and The IQMC candidate parameter value that optimizes the performance metric value is determined by selecting the IQMC candidate parameter value having the largest performance metric value from the set of tested IQMC candidate parameter values.

12. The device according to claim 11, wherein The iterative method is a gradient ascent method or a gradient descent method, and the iterative method further comprises calculating the gradient of the performance metric value.

13. The device of claim 12, wherein: The gradient ascent method or the gradient descent method uses a cost function that is a function of the at least one IQMC parameter.

14. The apparatus of claim 13, wherein: The cost function is also a function of I and Q mismatch IQMM parameters corresponding to an up-conversion circuit or a down-conversion circuit directly or indirectly connected to the IQMC.

15. The apparatus of claim 13, wherein: The at least one IQMC parameter comprises at least one tap weight of a filter of the IQMC.

16. The apparatus of claim 15, wherein: The IQMC comprises a real-valued RV IQMC, wherein the real-valued RVIQMC comprises a multiplier and the at least one IQMC parameter comprises a real-valued cross-multiplication factor input to the multiplier.

17. The apparatus of claim 11, wherein: The IQMC includes a complex-valued CV IQMC.

18. The apparatus of claim 11, wherein: The IQMC includes a real-valued RV IQMC.

19. The apparatus of claim 11, wherein: The performance metric value includes the IRR value, and the IRR value is a minimum IRR value in a set of IRR values of the IQMC, wherein the set of IRR values corresponds to different frequencies.

20. The apparatus of claim 11, wherein The performance metric value includes the IRR value, and the IRR value is a minimum arithmetic or geometric mean of IRR values per carrier unit CC in a carrier aggregation (CA) scheme.

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