CN111416783B - Circulation-based IQ imbalance adaptive blind compensation method and system - Google Patents

Circulation-based IQ imbalance adaptive blind compensation method and system Download PDF

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CN111416783B
CN111416783B CN202010245842.9A CN202010245842A CN111416783B CN 111416783 B CN111416783 B CN 111416783B CN 202010245842 A CN202010245842 A CN 202010245842A CN 111416783 B CN111416783 B CN 111416783B
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吕方明
贺小勇
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South China University of Technology SCUT
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    • H—ELECTRICITY
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract

The invention belongs to the technical field of communication, and relates to an IQ imbalance adaptive blind compensation method based on circulation, which comprises the following steps: receiving I, Q two paths of unbalanced signals x (n) and intercepting a discrete signal with a certain length; setting a stepping coefficient; conjugate processing is carried out on the received signal x (n) to obtain x*(n); processing the received signal x (n) to obtain a compensated output signal y (n) ═ x (n) + w (n) x*(n), wherein w (n) is a compensation factor; introducing a stepping coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration mode, and further obtaining a compensated output signal y (n). The IQ imbalance adaptive blind compensation method of the present invention can operate in any quadrature receiver setup, whether single-channel or multi-channel, and is independent of any particular structure or characteristics of the ideal baseband equivalent signal. The invention also provides an IQ imbalance adaptive blind compensation system based on circulation.

Description

Circulation-based IQ imbalance adaptive blind compensation method and system
Technical Field
The invention belongs to the technical field of communication, and relates to an IQ imbalance adaptive blind compensation method and system based on circulation.
Background
IQ imbalance refers to the amplitude and phase mismatch between the In-phase (I) and Quadrature-phase (Q) branches of the transmitter and receiver. Ideally, the in-phase and quadrature branches have equal amplitude gain and 90 degree phase offset. However, in an actual communication system, it is generally difficult to achieve the ideal situation, and therefore IQ imbalance occurs. IQ imbalance may occur at the transmitter, non-ideal up-conversion, I and Q branch imbalance filters, digital-to-analog converters, etc. At the receiver, IQ imbalance is caused by non-ideal down-conversion, unbalanced filters, amplification and sampling of the I and Q branches, etc.
A common method for suppressing IQ imbalance starts from hardware, and high-performance analog devices (such as a filter, an amplifier, an analog-to-digital converter, and the like) are adopted, and although the high-performance analog devices can fundamentally suppress the influence of IQ imbalance, the high-performance analog devices generally have larger volume and higher cost, and accordingly, the power consumption and price of the mobile transceiver device are increased. Furthermore, even a high-performance analog device cannot completely suppress IQ imbalance, and its ability to suppress IQ imbalance under different environments (temperature, humidity, and the like) is different, and therefore, it is not practical to suppress IQ imbalance in the analog domain. IQ imbalance cannot be suppressed and compensated in the digital domain by digital signal processing means, but from the analog domain.
However, the existing IQ imbalance compensation algorithm in the digital domain is difficult to consider both high compensation performance and low computation complexity, and it is also difficult to adjust the algorithm structure for different systems.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an IQ imbalance adaptive blind compensation method based on circulation. The method is a parameter-adjustable adaptive blind compensation method and can be used for different IQ unbalanced systems.
The invention also provides an IQ imbalance adaptive blind compensation system based on circulation.
The invention discloses a cycle-based IQ imbalance adaptive blind compensation method, which is realized by adopting the following technical scheme:
a loop-based IQ imbalance adaptive blind compensation method, comprising:
receiving I, Q two paths of unbalanced signals x (n) and intercepting a discrete signal with a certain length;
setting a stepping coefficient;
conjugate processing is carried out on the received signal x (n) to obtain x*(n)；
Processing the received signal x (n) to obtain a compensated output signal y (n) ═ x (n) + w (n) x*(n), wherein w (n) is a compensation factor;
introducing a stepping coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration mode, and further obtaining a compensated output signal y (n).
Preferably, the step of introducing a step coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration manner, and further obtaining the compensated output signal y (n) includes:
introducing a stepping coefficient, and processing the compensation coefficient to obtain: w (n +1) ═ w (n) - μ y (n), where w (n) is a compensation coefficient and μ is a first-order step coefficient;
smoothing the compensation coefficient w (n) to obtain w '(n +1) ═ β w' (n) + (1- β) w (n +1), β is a smoothing coefficient;
continuously taking values of discrete signals, and taking values of the formula y (n) ═ x (n) + w (n) x*(n), w (n +1) ═ w (n) - μ y (n) is subjected to a cyclic treatment;
when the compensation coefficient w (n) tends to be stable, the compensation coefficient value required by the system is obtained, and the compensated receiving signal y (n) is obtained.
Preferably, the process of obtaining the compensation coefficient required by the system comprises:
in order to obtain a compensation coefficient w (n) required by the system, the second-order statistical characteristic of the baseband modulation signal is utilized;
according to the second-order statistical characteristic of the general ideal baseband modulation signal, the baseband modulation signal is complementary with an autocorrelation function:
E[y(n)y(n-τ)]＝0，
Figure BDA0002433955220000021
wherein E [. X [ ]]Indicating a desire;
the matrix expression form is as follows:
E[Y(n)y(n)]0, where y (N) is ═ y (N) y (N-1) y (N-2)]T
Wherein: y (N) is a discrete form of the compensator output signal, τ is any integer, and N is the matrix order;
accordingly, a recursion formula of the high-order compensation coefficient w (n) can be obtained:
E[W(n+1)]＝E[W(n)]-ME[Y(n)y(n)]
simplifying expectations, we obtain:
W(n+1)＝W(n)-MY(n)y(n)
wherein, M ═ diag (μ)1，μ2，μ3，...，μN) Is a stepping coefficient matrix;
thus, the compensation algorithm can be expressed as:
y(n)＝x(n)+W(n)TX*(n)
W(n+1)＝W(n)-MY(n)y(n)
wherein: x*(n) is the conjugate of the complex signal X (n) of the matrix, X*(n)＝[x*(n)x*(n-1)x*(n-2)...x*(n-N+1)]T；W(n)TThe order conversion form of the high-order compensation coefficient W (n);
degenerating to the first order N-1 and adding a smoothing factor β, the expression becomes:
y(n)＝x(n)+wx*(n)
w(n+1)＝w(n)-μy(n)y(n)
w′(n+1)＝βw′(n)+(1-β)w(n+1)
wherein: mu is a first-order step coefficient, x (n) is a discrete form of IQ imbalance signal x (t), x*(n) is the conjugate term of the signal x (n), and w (n) is the compensation factor.
Preferably, the IQ imbalance adaptive blind compensation method further comprises: a received signal x (n) is fixed-point processed.
Preferably, the setting of the step factor includes: the initial step coefficient set is large, coarse calibration is carried out, and after a certain data volume is processed, a small step coefficient is set, and fine calibration is carried out.
The IQ imbalance self-adaptive blind compensation system based on circulation is realized by adopting the following technical scheme:
a loop-based IQ imbalance adaptive blind compensation system, comprising:
a receiving module: used for receiving I, Q two paths of unbalanced signals x (n) and intercepting a discrete signal with a certain length;
setting a module: for setting a stepping coefficient;
conjugation module: for performing conjugation processing on received signal x (n) to obtain x*(n)；
A compensation module: output signal y (n) ═ x (n) + w (n) x for processing received signal x (n) to obtain compensation*(n), wherein w (n) is a compensation factor;
a circulation module: the method is used for introducing a stepping coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration mode, and further obtaining a compensated output signal y (n).
Preferably, the circulation module comprises:
the compensation coefficient processing module: the method is used for introducing a stepping coefficient, and processing the compensation coefficient to obtain: w (n +1) ═ w (n) - μ y (n), where w (n) is a compensation coefficient and μ is a first-order step coefficient;
a smoothing module: smoothing the compensation coefficient w (n) to obtain w '(n +1) ═ β w' (n) + (1- β) w (n +1), β is a smoothing coefficient;
an iteration module: for continuous evaluation of discrete signals, the formula y (n) ═ x (n) + w (n) x*(n), w (n +1) ═ w (n) - μ y (n) is subjected to a cyclic treatment; when the compensation coefficient w (n) tends to be stable, the compensation coefficient required by the system is obtained, and a compensated receiving signal y (n) is obtained.
Preferably, the IQ imbalance adaptive blind compensation system further comprises:
a fixed point processing module: for performing a fixed-point processing on the received signal x (n).
Preferably, the process of obtaining the compensation coefficient required by the system by the circulation module comprises:
in order to obtain a compensation coefficient w (n) required by the system, the second-order statistical characteristic of the baseband modulation signal is utilized;
according to the second-order statistical characteristic of the general ideal baseband modulation signal, the baseband modulation signal is complementary with an autocorrelation function:
E[y(n)y(n-τ)]＝0，
Figure BDA0002433955220000041
wherein E [. X [ ]]Indicating a desire;
the matrix expression form is as follows:
E[Y(n)y(n)]0, where y (N) is ═ y (N) y (N-1) y (N-2)]T
Wherein: y (N) is a discrete form of the compensator output signal, τ is any integer, and N is the matrix order;
accordingly, a recursion formula of the high-order compensation coefficient w (n) can be obtained:
E[W(n+1)]＝E[W(n)]-ME[Y(n)y(n)]
simplifying expectations, we obtain:
W(n+1)＝W(n)-MY(n)y(n)
wherein, M ═ diag (μ)1，μ2，μ3，...，μN) Is a stepping coefficient matrix;
thus, the compensation algorithm can be expressed as:
y(n)＝x(n)+W(n)TX*(n)
W(n+1)＝W(n)-MY(n)y(n)
wherein: x*(n) is the conjugate of the complex signal X (n) of the matrix, X*(n)＝[x*(n)x*(n-1)x*(n-2)...x*(n-N+1)]T；W(n)TThe order conversion form of the high-order compensation coefficient W (n);
degenerates to first order (N ═ 1) and adds a smoothing coefficient β, the expression becomes:
y(n)＝x(n)+wx*(n)
w(n+1)＝w(n)-μy(n)y(n)
w′(n+1)＝βw′(n)+(1-β)w(n+1)
wherein: mu is a first-order step coefficient, x (n) is a discrete form of IQ imbalance signal x (t), x*(n) is the conjugate term of the signal x (n), and w (n) is the compensation factor.
Preferably, the setting module, in setting the step factor: the initial step coefficient set is large, coarse calibration is carried out, and after a certain data volume is processed, a small step coefficient is set, and fine calibration is carried out.
Compared with the prior art, the invention has at least the following beneficial effects:
1. the invention utilizes the extensive linear filtering of the received baseband signal, utilizes the second-order statistical characteristic of the ideal baseband equivalent signal, introduces the stepping coefficient and the compensation coefficient, and carries out IQ compensation based on the cyclic characteristic.
2. As a parameter-adjustable adaptive blind compensation method, the invention can deal with IQ unbalanced systems under different conditions by adjusting related parameters.
3. The second-order statistical characteristic of the baseband equivalent signal is not influenced by most of non-ideal factors except IQ imbalance, so the method has strong robustness.
4. The invention estimates IQ imbalance in real time in a digital domain, and carries out corresponding compensation aiming at different environments, thereby solving the problem that IQ imbalance degrees are different due to different performances of analog devices under different environments.
5. The method can adapt to the time-varying characteristics of different simulation systems, can adaptively adjust the output along with the performance change of the simulation systems, greatly reduces the compensation cost of IQ imbalance, and continuously improves the performance along with the improvement of chip processes.
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FIG. 1 is a simplified flowchart of a loop-based IQ imbalance adaptive blind compensation method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of IQ imbalance of a signal according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a compensator according to an embodiment of the present invention;
FIG. 4 is a graph illustrating the variation trend of the compensation coefficient w (n) according to an embodiment of the present invention;
fig. 5 is a constellation diagram after IQ imbalance compensation according to an embodiment of the present invention.
Detailed Description
Specific embodiments of the present invention will be described below with reference to the accompanying drawings, but the present invention is not limited thereto.
Example 1
A cyclic-based IQ imbalance adaptive blind compensation method, as shown in fig. 1, mainly includes:
receiving IQ unbalanced signals, setting a stepping coefficient, processing the received signals, introducing the stepping coefficient to obtain a compensation coefficient in a cyclic iteration mode, and further obtaining compensated output signals, wherein the detailed implementation process is analyzed below.
FIG. 2 is an IQ imbalance diagram illustrating IQ imbalance caused by a received signal due to non-ideal effects, wherein: hnom(f) Representing the low-pass filter frequency response, H, on the linkI(f) And HQ(f) Respectively representing the frequency response (ideally, H) generated by the I path and Q path carrier signals after passing through the link and influenced by other non-ideal factorsI(f)＝HQ(f) 1), g and
Figure BDA0002433955220000052
respectively representing mismatch amplitude and mismatch phase, SLO，I(t)＝cos(ωLOt) and
Figure BDA0002433955220000053
respectively representing Local Oscillator (LO) signals of the I path and the Q path, and r (t) is a sending signal. Without loss of generality, the low pass filter frequency response H will be neglected in the followingnom(f) The impact of the process.
In time domain analysis, the mathematical model of the signal with IQ imbalance can be expressed as:
Figure BDA0002433955220000051
wherein:
Figure BDA0002433955220000061
Figure BDA0002433955220000062
SLO(t) is the received IQ imbalance signal, ωLOIs the carrier frequency, r (t) is the transmit signal, j is the imaginary unit, g is the mismatch magnitude,
Figure BDA0002433955220000063
for mismatched phase, t is time unitA bit.
Assuming that z (t) is an ideal IQ signal, the frequency domain analysis is performed on the carrier signal x (t) with IQ imbalance to obtain the following formula:
X(f)＝G1(f)Z(f)+G2(f)Z*(-f)
wherein:
Figure BDA0002433955220000064
Figure BDA0002433955220000065
in the above formula, Z (f) is a frequency domain representation of Z (t), Z*(-f) is a frequency domain representation of the z (t) conjugate term, G1(f) For the frequency-domain representation of the gain of the signal z (t), G2(f) Is a frequency domain representation of the gain of the conjugate term of the signal z (t). HI(f) And HQ(f) Respectively representing the frequency response of the I and Q paths (ideally, H)I(f)＝HQ(f) 1), g is the mismatch amplitude,
Figure BDA0002433955220000066
is the mismatch phase.
In the time domain, x (t) can be expressed as:
x(t)＝g1(t)*z(t)+g2(t)*z*(t) (1)
wherein, g1(t)、g2(t) are each G1(f)、G2(f) Time domain representation of (2), z*(t) is the conjugate term of the ideal IQ signal z (t). As can be seen from the above equation, the mismatch compensation for x (t) is simply to eliminate g2(t)*z*(t) of (d). The following compensators can be used for compensation, let:
y(t)＝w1(t)*x(t)+w2(t)*x*(t) (2)
wherein: w is a1(t)、w2(t) is the compensator compensation coefficient, y (t) is the output signal of the compensator, x*(t) is the conjugate term of the signal x (t)。
Substituting formula (1) into formula (2) yields the following formula:
y(t)＝(w1(t)*g1(t)+w2(t)*g2 *(t))*z(t)+(w1(t)*g2(t)+w2(t)*g1 *(t))*z*(t)
for compensation purposes, only w needs to be made1(t)*g2(t)+w2(t)*g1 *(t)＝0。
For simplicity, normalization was performed to yield:
w1(t)＝δ(t)，w2(t)＝w(t) (3)
where δ (t) is the impulse response, and w (t) is the normalized compensation coefficient.
Substituting equation (3) into equation (2) yields, in the discrete domain:
y(n)＝x(n)+w(n)*x*(n)
wherein w (n) is the compensator compensation coefficient, y (n) is the discrete form of the compensator output signal, x (n) is the discrete form of the IQ imbalance signal x (t)*(n) is the conjugate of signal x (n).
The structure of the compensator is shown in fig. 3, and the optimal compensation coefficient w (n) is, as viewed from the frequency domain:
Figure BDA0002433955220000071
WOPT(f) is the optimal frequency domain expression of the compensation coefficient w (n).
In order to obtain the compensation coefficient w (n) required by the system, the second-order statistical characteristics of the following modulation signals need to be utilized.
According to the second-order statistical characteristics of the general ideal baseband modulation signals (QAM, QPSK and the like except BPSK), the complementary autocorrelation function of the baseband modulation signals is as follows:
E[y(n)y(n-τ)]＝0，
Figure BDA0002433955220000072
wherein E [. X [ ]]Indicating a desire.
The matrix expression form is as follows:
E[Y(n)y(n)]0, where y (N) is ═ y (N) y (N-1) y (N-2)]T
Wherein: y (N) is a discrete form of the compensator output signal, τ is an arbitrary integer, and N is the matrix order.
Accordingly, a recursion formula of the high-order compensation coefficient w (n) can be obtained:
E[W(n+1)]＝E[W(n)]-ME[Y(n)y(n)]
simplifying expectations, we obtain:
W(n+1)＝W(n)-MY(n)y(n)
wherein, M ═ diag (μ)1，μ2，μ3，...，μN) Is a matrix of stepping coefficients.
Thus, the compensation algorithm can be expressed as:
y(n)＝x(n)+W(n)TX*(n)
W(n+1)＝W(n)-MY(n)y(n)
wherein: x*(n)＝[x*(n)x*(n-1)x*(n-2)...x*(n-N+1)]TW (n) is a high-order compensation coefficient, W (n)TIn the form of a rank of the higher order compensation coefficient w (n).
Degenerates to first order (N ═ 1) and adds a smoothing coefficient β, the expression becomes:
y(n)＝x(n)+wx*(n)
w(n+1)＝w(n)-μy(n)y(n)
w′(n+1)＝βw′(n)+(1-β)w(n+1)
mu in the formula is the first-order step coefficient, x (n) is the discrete form of IQ imbalance signal x (t), x*(n) is the conjugate term of the signal x (n), and w (n) is the compensation factor.
The configuration value of the stepping coefficient is divided into two parts, the initially configured stepping coefficient is larger, and the purpose of rapid convergence is achieved. When the compensation coefficient is close to the required convergence value, a smaller coefficient is configured to achieve the purpose of improving the performance.
In order to further verify the result of the invention, the verification is carried out by a specific simulation experiment:
step 1, receiving I, Q two unbalanced signals x (n) ═ imbI + imbQ by using a 16QAM modulation mode, and intercepting discrete data with a certain length, wherein x (n) is a received signal, and imbI and imbQ are I, Q unbalanced signals respectively;
step 2, performing fixed-point processing on the data, namely x (n) double (fi (x (n), 1, 12, 11)), so as to facilitate the following processes: fi () is rounding to zero, double () is converting parameters to double precision floating point type;
step 3, setting a stepping coefficient, wherein the initial stepping coefficient is large (for example, mu is 2^ -9), performing coarse calibration to achieve the purpose of fast convergence, processing a certain data volume (for example, the data volume i is 2^14), setting a small stepping coefficient (for example, mu is 2^ -17), and performing fine calibration to achieve the purpose of improving performance;
step 4, conjugate processing is carried out on the received signals x (n) to obtain x*(n)；
Step 5, processing the received signal x (n) to obtain a compensated signal y (n) ═ x (n) + w (n) x*(n), wherein w (n) is a compensation factor;
step 6, processing the compensation coefficient, where w (n +1) ═ w (n) — μ y (n), where w (n) is the compensation coefficient and μ is the first-order step coefficient;
step 7, smoothing the compensation coefficient w (n) to obtain w '(n +1) ═ β w' (n) + (1- β) w (n + 1);
step 8, continuously taking values of the discrete signals, and taking values of the formula y (n) ═ x (n) + w (n) x*(n), wherein w (n +1) ═ w (n) — μ y (n) is subjected to cyclic treatment;
step 9, obtaining a compensated received signal y (n) when the compensation coefficient w (n) tends to be stable, where fig. 4 shows a variation trend of the compensation coefficient w (n), and fig. 5 is a constellation diagram of the system after IQ compensation.
Example 2
A loop-based IQ imbalance adaptive blind compensation system, comprising:
a receiving module: for receiving I, Q two paths of signals x (n) with unbalance and intercepting discrete signals with certain length.
A fixed point processing module: for performing a fixed-point processing on the received signal x (n).
Setting a module: for setting the step factor. The setting module is in the process of setting the stepping coefficient: the initial step coefficient set is large, coarse calibration is carried out, and after a certain data volume is processed, a small step coefficient is set, and fine calibration is carried out.
Conjugation module: for performing conjugation processing on received signal x (n) to obtain x*(n)。
A compensation module: output signal y (n) ═ x (n) + w (n) x for processing received signal x (n) to obtain compensation*(n), wherein w (n) is a compensation factor;
a circulation module: the method is used for introducing a stepping coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration mode, and further obtaining a compensated output signal y (n).
Specifically, the circulation module includes:
the compensation coefficient processing module: the method is used for introducing a stepping coefficient, and processing the compensation coefficient to obtain: w (n +1) ═ w (n) - μ y (n), where w (n) is a compensation coefficient and μ is a first-order step coefficient;
a smoothing module: smoothing the compensation coefficient w (n) to obtain w '(n +1) ═ β w' (n) + (1- β) w (n +1), β is a smoothing coefficient;
an iteration module: for continuous evaluation of discrete signals, the formula y (n) ═ x (n) + w (n) x*(n), w (n +1) ═ w (n) - μ y (n) is subjected to a cyclic treatment; when the compensation coefficient w (n) tends to be stable, the compensation coefficient required by the system is obtained, and a compensated receiving signal y (n) is obtained.
The process of obtaining the compensation coefficient required by the system by the circulation module comprises the following steps:
in order to obtain a compensation coefficient w (n) required by the system, the second-order statistical characteristic of the baseband modulation signal is utilized;
according to the second-order statistical characteristic of the general ideal baseband modulation signal, the baseband modulation signal is complementary with an autocorrelation function:
E[y(n)y(n-τ)]＝0，
Figure BDA0002433955220000091
wherein E [. X [ ]]Indicating a desire;
the matrix expression form is as follows:
E[Y(n)y(n)]0, where y (N) is ═ y (N) y (N-1) y (N-2)]T
Wherein: y (N) is a discrete form of the compensator output signal, τ is any integer, and N is the matrix order;
accordingly, a recursion formula of the high-order compensation coefficient w (n) can be obtained:
E[W(n+1)]＝E[W(n)]-ME[Y(n)y(n)]
simplifying expectations, we obtain:
W(n+1)＝W(n)-MY(n)y(n)
wherein, M ═ diag (μ)1，μ2，μ3，...，μN) Is a stepping coefficient matrix;
thus, the compensation algorithm can be expressed as:
y(n)＝x(n)+W(n)TX*(n)
W(n+1)＝W(n)-MY(n)y(n)
wherein: x*(n) is the conjugate of the complex signal X (n) of the matrix, X*(n)＝[x*(n)x*(n-1)x*(n-2)...x*(n-N+1)]T；W(n)TIn the form of a rank of the higher order compensation coefficient w (n).
Degenerating to the first order N-1 and adding a smoothing factor β, the expression becomes:
y(n)＝x(n)+wx*(n)
w(n+1)＝w(n)-μy(n)y(n)
w′(n+1)＝βw′(n)+(1-β)w(n+1)
wherein: mu is a first-order step coefficient, x (n) is a discrete form of IQ imbalance signal x (t), x*(n) is the conjugate term of the signal x (n), and w (n) is the compensation factor.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.

Claims (6)

1. A loop-based IQ imbalance adaptive blind compensation method, comprising:
receiving I, Q two paths of unbalanced signals x (n) and intercepting a discrete signal with a certain length;
setting a stepping coefficient; setting a large initial stepping coefficient, performing coarse calibration, processing a certain data volume, setting a small stepping coefficient, and performing fine calibration; conjugate processing is carried out on the received signal x (n) to obtain x*(n)；
Processing the received signal x (n) to obtain a compensated output signal y (n) ═ x (n) + w (n) x*(n), wherein w (n) is a compensation factor;
introducing a stepping coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration mode, and further obtaining a compensated output signal y (n); the method specifically comprises the following steps:
introducing a stepping coefficient, and processing the compensation coefficient to obtain: w (n +1) ═ w (n) - μ y (n), where w (n) is a compensation coefficient and μ is a first-order step coefficient;
smoothing the compensation coefficient w (n) to obtain w '(n +1) ═ β w' (n) + (1- β) w (n +1), β is a smoothing coefficient;
continuously taking values of discrete signals, and taking values of the formula y (n) ═ x (n) + w (n) x*(n), w (n +1) ═ w (n) - μ y (n) is subjected to a cyclic treatment;
when the compensation coefficient w (n) tends to be stable, the compensation coefficient value required by the system is obtained, and the compensated receiving signal y (n) is obtained.
2. The IQ imbalance adaptive blind compensation method according to claim 1, wherein the process of obtaining the compensation coefficients required by the system comprises:
utilizing the second-order statistical characteristic of the baseband modulation signal;
according to the second-order statistical characteristic of the ideal baseband modulation signal, the baseband modulation signal is complementary with an autocorrelation function:
Figure FDA0003201636310000011
wherein E [. X [ ]]Indicating a desire;
the matrix expression form is as follows:
E[Y(n)y(n)]0, where y (N) ═ y (N) y (N-1) y (N-2) … y (N-N +1)]T
Wherein: y (N) is a discrete form of the compensator output signal, τ is any integer, and N is the matrix order;
obtaining a recursion formula of a high-order compensation coefficient W (n):
E[W(n+1)]＝E[W(n)]-ME[Y(n)y(n)]
simplifying expectations, we obtain:
W(n+1)＝W(n)-MY(n)y(n)
wherein, M ═ diag (μ)1，μ2，μ3，…，μN) Is a stepping coefficient matrix;
the compensation algorithm is represented as:
y(n)＝x(n)+W(n)TX*(n)
W(n+1)＝W(n)-MY(n)y(n)
wherein: x*(n) is the conjugate of the complex signal X (n) of the matrix, X*(n)＝[x*(n)x*(n-1)x*(n-2)…x*(n-N+1]T; w (n) T is a rank conversion form of a high-order compensation coefficient W (n);
degenerating to the first order N-1 and adding a smoothing factor β, the expression becomes:
y(n)＝x(n)+wx*(n)
w(n+1)＝w(n)-μy(n)y(n)
w′(n+1)＝βw′(n)+(1-β)w(n+1)
wherein: mu is a first-order step coefficient, x (n) is a discrete form of IQ imbalance signal x (t), x*(n) is the conjugate term of the signal x (n), and w (n) is the compensation factor.
3. The IQ imbalance adaptive blind compensation method according to claim 1, wherein the IQ imbalance adaptive blind compensation method further comprises: a received signal x (n) is fixed-point processed.
4. A loop-based IQ imbalance adaptive blind compensation system, comprising:
a receiving module: used for receiving I, Q two paths of unbalanced signals x (n) and intercepting a discrete signal with a certain length;
setting a module: for setting a stepping coefficient; the setting module is in the process of setting the stepping coefficient: setting a large initial stepping coefficient, performing coarse calibration, processing a certain data volume, setting a small stepping coefficient, and performing fine calibration; conjugation module: for performing conjugation processing on received signal x (n) to obtain x*(n)；
A compensation module: output signal y (n) ═ x (n) + w (n) x for processing received signal x (n) to obtain compensation*(n), wherein w (n) is a compensation factor;
a circulation module: the device is used for introducing a stepping coefficient and smoothing the compensation coefficient w (n), obtaining the compensation coefficient w (n) required by the system in a loop iteration mode, and further obtaining a compensated output signal y (n);
the circulation module includes:
the compensation coefficient processing module: the method is used for introducing a stepping coefficient, and processing the compensation coefficient to obtain: w (n +1) ═ w (n) - μ y (n), where w (n) is a compensation coefficient and μ is a first-order step coefficient;
a smoothing module: smoothing the compensation coefficient w (n) to obtain w '(n +1) ═ β w' (n) + (1- β) w (n +1), β is a smoothing coefficient;
an iteration module: for continuous evaluation of discrete signals, the formula y (n) ═ x (n) + w (n) x*(n), w (n +1) ═ w (n) - μ y (n) is subjected to a cyclic treatment; when the compensation coefficient w (n) tends to be stable, the compensation coefficient required by the system is obtained, and a compensated receiving signal y (n) is obtained.
5. The IQ imbalance adaptive blind compensation system according to claim 4, wherein the IQ imbalance adaptive blind compensation system further comprises:
a fixed point processing module: for performing a fixed-point processing on the received signal x (n).
6. The IQ imbalance adaptive blind compensation system according to claim 4, wherein the process of the loop module obtaining the compensation coefficients required by the system comprises:
utilizing the second-order statistical characteristic of the baseband modulation signal;
according to the second-order statistical characteristic of the ideal baseband modulation signal, the baseband modulation signal is complementary with an autocorrelation function:
Figure FDA0003201636310000031
wherein E [. X [ ]]Indicating a desire;
the matrix expression form is as follows:
E[Y(n)y(n)]0, where y (N) ═ y (N) y (N-1) y (N-2) … y (N-N +1)]T
Wherein: y (N) is a discrete form of the compensator output signal, τ is any integer, and N is the matrix order;
obtaining a recursion formula of a high-order compensation coefficient W (n):
E[W(n+1)]＝E[W(n)]-ME[Y(n)y(n)]
simplifying expectations, we obtain:
W(n+1)＝W(n)-MY(n)y(n)
wherein, M ═ diag (μ)1，μ2，μ3，…，μN) Is a stepping coefficient matrix;
the compensation algorithm is represented as:
y(n)＝x(n)+w(n)TX*(n)
W(n+1)＝W(n)-MY(n)y(n)
wherein: x*(n) is the conjugate of the complex signal X (n) of the matrix, X*(n)＝[x*(n)x*(n-1)x*(n-2)…x*(n-N+1]T; w (n) T is a rank conversion form of a high-order compensation coefficient W (n);
degenerates to first order (N ═ 1) and adds a smoothing coefficient β, the expression becomes:
y(n)＝x(n)+wx*(n)
w(n+1)＝w(n)-μy(n)y(n)
w′(n+1)＝βw′(n)+(1-β)w(n+1)
wherein: mu is a first-order step coefficient, x (n) is a discrete form of IQ imbalance signal x (t), x*(n) is the conjugate term of the signal x (n), and w (n) is the compensation factor.
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