CN116015554A - Fusion method for heterogeneous signal soft information extraction based on short wave multichannel diversity frame - Google Patents
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Abstract
The invention belongs to the technical field of signal transmission, and particularly relates to a fusion method for heterogeneous signal soft information extraction based on a short-wave multichannel diversity frame, which comprises the following steps: each transmitting station modulates and transmits the information source by using a proper modulation mode and transmission rate; demodulating the signals with different modulations independently, and extracting corresponding symbol soft information; uniformly mapping the symbol soft information into bit soft information; realizing the normalized description of the bit soft information by using a noise model of the bit soft information; the invention provides a method for extracting symbol soft information of heterogeneous signals, which is used for extracting symbol soft information of signals in different modulation modes respectively, analyzing the difference of the symbol soft information in different modulation modes and mapping the symbol soft information to bit soft information by adopting a corresponding mapping method so as to fuse the bit soft information.
Description
Technical Field
The invention belongs to the technical field of signal transmission, and particularly relates to a fusion method for heterogeneous signal soft information extraction based on a short-wave multichannel diversity frame.
Background
Short wave communication is used as a communication mode for performing beyond-the-horizon through the principle of reflection of high-frequency electromagnetic waves by an ionosphere, has the advantages of flexibility, independence of fixed base station equipment and the like, and becomes an irreplaceable communication mode in large-scale area emergency and military fields. The traditional point-to-point communication mode is difficult to compensate the influence of deep fading of short wave signals on communication, so that a diversity receiving technology is generally applied to short wave communication to form a short wave wide area diversity receiving model, a receiving end obtains a plurality of mutually independent branch signals, and accordingly diversity gain is obtained to resist the fading, and anti-interference performance and communication reliability of communication under a short wave severe environment are improved.
At present, under the rapid development of the short wave self-adaptive modulation technology, each distributed station can use an optimal modulation mode according to the own link condition, so that the waveform merging method is invalid due to the heterogeneous link condition. The traditional diversity fusion mode is oriented to the same modulation waveform, so that waveform addition after the same frequency and phase are carried out at the receiving end, and the signal quality is enhanced. When different stations transmit signals using different modulation methods, such as amplitude domain modulation, frequency domain modulation, phase domain modulation, and complex modulation, if waveform addition is used, the bands of different symbols are added in error, so that decoding is wrong.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a fusion method for heterogeneous signal soft information extraction based on a short-wave multichannel diversity frame, which does not use a waveform addition form, combines soft information before decoding after demodulation of each signal, realizes fusion of heterogeneous soft information of a short-wave wide-area diversity model, obtains diversity gain and improves reliability of short-wave communication.
The invention discloses a fusion method for heterogeneous signal soft information extraction based on a short-wave multichannel diversity frame, which mainly comprises the following steps:
step S1, each transmitting station modulates and transmits the information source by using a proper modulation mode and transmission rate;
s2, independently demodulating signals with different modulations, and extracting corresponding symbol soft information;
step S3, the symbol soft information is mapped into bit soft information in a unified way;
s4, realizing the normalized mapping of the bit soft information;
and S5, obtaining diversity gain by utilizing an addition form, and obtaining a decoding result through multi-decision.
Further, the extracting the corresponding symbol soft information in step S2 includes:
the extraction of the composite domain modulation QAM soft information comprises the following steps: the multi-domain joint modulation mode is QAM modulation, information of which is mapped on two signal domains of amplitude and phase, and soft information is described by adopting the distance between a received symbol constellation point and a reference constellation point.
Further, the step S3 includes:
PSK and QAM firstly carry out correlation mapping and then carry out bit mapping; ASK and MFSK directly perform bit mapping.
Further, the correlation map includes:
exchanging the target result set, and assuming that the symbol set is:
P＝{P i |i＝0,1,2,...,M-1}
wherein P is i The corresponding soft information can be described as d i Where M represents the number of symbol soft information, d in QAM i Represents distance d in MPSK i Then represents the absolute value of the angle difference, where d i The value of (2) is a negative correlation, then by taking the NOTIn the way j represents the reference constellation point S j Namely the soft information of the reference constellation point, the soft information S can be obtained j Is a positive correlation description of (a):
further, the bit map includes:
mapping the symbol soft information onto the bit soft information is achieved by mapping 0's of the bit information into-1's constituting a coefficient matrix and then multiplying the coefficient matrix by a symbol soft information vector.
Further, the bit soft information normalization mapping in step S4 includes:
and carrying out data statistics analysis on the bit soft information and noise thereof to obtain a certain statistical model modeling obeyed by the bit soft information of a certain moment, uniformly mapping the bit soft information into a probability form of the bit soft information, and limiting the value of the soft information within the range of [0,1 ].
Further, the unified mapping of the bit soft information to the probability form of the bit soft information includes:
assuming that the noise of the bit soft information is subject to Gaussian distribution, the bit mapped soft information is defined as occurrence of events B and A 0 An event representing that bit is 0, A 1 An event representing the bit being 1, A 0 And A 1 Is 2 mutually incompatible events.
Probability P (B|A) 0 ) And P (B|A) 1 ) The description is as follows:
wherein S is soft information after bit mapping, mu 0 、σ 0 Normal distribution of metric values for bits 0Parameters, mu 1 、σ 1 Is a normal distribution parameter of a metric value of 1.
According to the posterior probability formula:
wherein P (A) 0 ) Representing the probability that the current bit value in the received information is 0, P (A 1 ) Representing the probability that the current bit value in the received information is 1, the transmitted value needs to satisfy P (A 0 )＝P(A 1 ) Finally, the conversion from the metric value of the bit soft information to the probability value is obtained:
P(A 0 i B) and P (A) 1 I B) is the final normalized bit soft information, denoted as m (0) and m (1).
Further, the step S5 includes:
adding and fusing the normalized bit soft information, and taking larger values in M (0) and M (1) as decoding results:
M(0)＝m1(0)+m2(0)+,...,ms(0)
M(1)＝m1(1)+m2(1)+,...,ms(1)
and in the same way, mi (0) is a normalized bit soft information value with a certain bit of 0 of the ith branch, M (0) is a fusion added value with a certain corresponding bit of 0 of all branches, mi (1) is a normalized bit soft information value with a certain bit of 1 of the ith branch, and M (1) is a fusion added value with a certain corresponding bit of 1 of all branches.
The invention provides a method for extracting symbol soft information of heterogeneous signals, which is used for extracting symbol soft information of signals modulated by an amplitude domain, a frequency domain, a phase domain and a composite domain respectively; the difference of symbol soft information in different modulation modes is analyzed, the symbol soft information is mapped to bit soft information by adopting a corresponding mapping method, so that the bit soft information is fused, heterogeneous soft information of a short-wave wide-area diversity model is fused by carrying out the two points, diversity gain is obtained, and the reliability of short-wave communication is improved.
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FIG. 1 is a flow chart of an algorithm of the present invention;
FIG. 2 is a schematic diagram of an amplitude domain modulated waveform 2ASK soft information extraction method according to the present invention;
fig. 3 is a schematic diagram of a method for extracting soft information from a frequency domain modulation waveform MFSK (m=4) of the present invention;
fig. 4 is a schematic diagram of a method for extracting soft information from a phase-domain modulated waveform MPSK (m=8) according to the present invention;
FIG. 5 is a schematic diagram of a method for extracting 16QAM soft information from a composite domain modulation waveform according to the present invention;
FIG. 6 is a schematic diagram of a composite domain modulation waveform 16QAM bit map of the present invention;
fig. 7 is a schematic diagram of a normalized mapping of the soft information of the 16QAM bits of the complex domain modulated waveform of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and specifically described below with reference to the drawings in the embodiments of the present invention. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention.
The invention provides a fusion method for heterogeneous signal soft information extraction based on a short-wave multichannel diversity framework, which mainly comprises the following steps as shown in fig. 1:
in step S1, each transmitting station modulates and transmits the source using a suitable modulation scheme and transmission rate.
Further, a threshold decision method based on a signal-to-noise ratio or a threshold selection method based on an error rate can be adopted by selecting a proper modulation mode through an adaptive modulation technology.
And S2, independently demodulating the signals with different modulations, and extracting corresponding symbol soft information.
Further, the symbol soft information extraction method specifically comprises the following steps:
A. amplitude domain modulation ASK soft information extraction
The conventional envelope detection method of ASK is as follows: after receiving the signal, the exchange signal is converted into a direct current signal through a rectifying circuit, the envelope of the baseband signal can be filtered out through a low-pass filter, and finally the signal is output through judgment, so that the demodulation of the ASK signal is completed.
The extraction of soft information is that when deciding, the bit is not directly output as 0 or 1, but the specific value of deciding is directly output as symbol soft information. As shown in fig. 2, the sampling decision result after the low-pass filtering is directly output.
B. Frequency domain modulated MFSK soft information extraction
Assuming that the received signal is ideally synchronized, short-time Fourier transform analysis is performed on the received signal, the step length of a window function of short-time Fourier transform is the same as the code element time, the number of Fourier transform points is enabled to meet the condition that the frequency spectrum resolution is the same as the carrier frequency interval of the FSK signal, and the time domain signal is converted into a time domain.
And analyzing the frequency spectrum of each symbol in the time-frequency domain information, wherein the frequency components corresponding to the frequency spectrum in the frequency domain distribution when the signal is taken are obtained because the frequencies corresponding to different symbols at the transmitting end are known. I.e. the energy vector of the energy information as a whole is the soft information of the received symbol.
The extraction method when m=4 is as shown in fig. 3, where T S Representing the length of a single symbol, the baud rate is 1/T S . As can be seen from the figure, for a particular transmission symbol S i The corresponding soft information is f j (j=0, 1,.,. M-1), which is a soft information vector of length M, where each value represents a corresponding location
Energy information. The scheme outputs the energy vector f as soft information as a whole.
C. Phase domain modulated MPSK soft information extraction
The receiving end receives MPSK signal s(t)＝acos(w c t)-bsin(w c t) are respectively associated with cos (w c t) and-sin (w) c t) multiplying and integrating, and obtaining amplitude values a and b of the I path and the Q path through sampling judgment according to the following formula. It is mapped on a constellation diagram, a representing the value of the abscissa and b representing the value of the ordinate.
In the above, w c For carrier frequency T being t0=2n/w c Is an integer multiple of (a).
The phase arctanb/a of the received symbol calculated from a, b is denoted as θ.
The absolute value of the angle difference Δθi between θ and the phase of the 4 reference constellation points nearest to the received symbol is calculated, (i=0 to 3), and if Δθ exceeds 180 °, Δθ=360° - θ because the range of the angle difference is [0, n ].
Obtaining 4 phase soft information values delta theta of the MPSK symbol 0 ,Δθ 1 ,Δθ 2 ,Δθ 3 。
The extraction method when m=8 is as shown in fig. 4, and although the received demodulated symbol is described by constellation points, the amplitude of the symbol is not changed, so only the phase domain carries modulation information.
D. Complex domain modulated QAM soft information extraction
The multi-domain joint modulation mode is QAM modulation, information of which is mapped on two signal domains of amplitude and phase, and constellation diagram description of soft information is shown in fig. 5.
Similar to PSK, when a, b are found, the soft information cannot be described by the phase alone. The magnitude of the distance between the received symbol constellation point and the reference constellation point is used to describe the soft information.
The distances between the constellation position of the actual received symbol (p) and the nearest four 16QAM standard constellation points in the figure are d respectively 0 ,d 1 ,d 2 ,d 3 Note that here, unlike the way in which energy soft information is described, the smaller the distance, the higher the degree of reliability is represented.
And step S3, uniformly mapping the symbol soft information into bit soft information.
Further, PSK and QAM are subjected to correlation mapping first, and then bit mapping is carried out; ASK and MFSK directly perform bit mapping.
Further, the mapping of the bit soft information is specifically as follows:
A. correlation mapping
The correlation mapping mainly solves the problem that the magnitude of soft information is different. Exchanging the target result set, and assuming that the symbol set is:
P＝{P i |i＝0,1,2,...,M-1}
wherein P is i The corresponding soft information can be described as d i Where M represents the number of symbol soft information, d in QAM i Represents distance d in MPSK i Then the absolute value of the angle difference is represented. Here d i The value of (2) is a negative correlation, then j represents the reference constellation point, S, by taking the non-form j Namely the soft information of the reference constellation point, the soft information S can be obtained j Is a positive correlation description of (a):
taking the example of FIG. 5, the complex modulation 16QAM has
S0, S1, S2, S3 represent soft information of four symbols 1001, 1011, 1101, 1111 in fig. 5, respectively. d0, d1, d2, d3 represent distance values of the reception constellation point P from the nearest four reference constellation points 1001, 1011, 1101, 1111, respectively, in the figure.
It should be noted that in 16QAM, m=16, but in the above formula, only a subset of the nearest 4 points is used for operation, which is because in 16QAM, the distance between constellation points at a longer distance is larger, the accuracy is extremely low, and in order to reduce the calculation amount consumption in the fusion process, it can be generally removed from the identification frame P to be fused, so as to achieve the purpose of efficient calculation.
B. Bit mapping
The bit mapping mainly solves the problem of different degrees of freedom of soft information. Taking 16QAM in fig. 5 as an example, this process is shown in fig. 6. S for receiving symbol P in FIG. 5 0 ,S 1 ,S 2 ,S 3 A total of M (m=4) soft information are described, and as shown in the constellation diagram, the corresponding bit information is 1001, 1011, 1101, 1111, respectively. The mapping of M symbol soft information onto N bits of soft information can thus be achieved by mapping 0 to-1 to form the coefficient matrix in fig. 6 and then multiplying the coefficient matrix by the symbol soft information vector.
At this time, the 4-bit soft information represented by symbol P is: b (B) 0 ,B 1 ,B 2 ,B 3 。
One 16QAM symbol represents 4bit information. Meaning that the four bits of soft information calculated from the received symbol P have values of B 0 ,B 1 ,B 2 ,B 3 。
And S4, realizing the normalized mapping of the bit soft information.
Further, the bit soft information normalization mapping includes:
the normalization mapping is mainly to perform data statistics analysis on bit soft information and noise thereof to obtain a certain statistical model modeling probably obeyed by the bit soft information of a certain moment, uniformly map the bit soft information into a probability form of the bit soft information, and limit the value of the soft information in a range of [0,1 ].
It is assumed that the noise of the bit soft information follows a gaussian distribution as shown in fig. 7. B in the figure is soft information after bit mapping, and is defined as occurrence event B, A 0 An event representing that bit is 0, A 1 An event representing the bit being 1, A 0 And A 1 Is 2 mutually incompatible events.
Probability P (B|A in the figure 0 ) And P (B|A) 1 ) The description is as follows:
wherein S is soft information after bit mapping, mu 0 、σ 0 Normal distribution parameter, μ, for a metric value of 0 bits 1 、σ 1 Is a normal distribution parameter of a metric value of 1.
According to the posterior probability formula:
wherein P (A) 0 ) Representing the probability that the current bit value in the received information is 0, P (A 1 ) Representing the probability that the current bit value in the received information is 1, the transmitted value needs to satisfy P (A 0 )＝P(A 1 ) Finally, the conversion from the metric value of the bit soft information to the probability value is obtained:
P(A 0 i B) and P (A) 1 I B) is the final normalized bit soft information, denoted as m (0) and m (1).
And S5, obtaining diversity gain by utilizing an addition form, and obtaining a decoding result through multi-decision.
Further, the method comprises the steps of:
adding and fusing the normalized bit soft information, and taking larger values in M (0) and M (1) as decoding results:
M(0)＝m1(0)+m2(0)+,...,ms(0)
M(1)＝m1(1)+m2(1)+,...,ms(1)
mi (0) is a normalized bit soft information value of which a certain bit of the ith branch is 0. M (0) is the fusion-added value of 0 for a corresponding bit of all branches. Similarly, mi (1) is a normalized bit soft information value with a certain bit of 1 in the ith branch. M (1) is the fusion-added value of 1 for a corresponding bit for all branches.
The above examples should be understood as illustrative only and not limiting the scope of the invention. Various changes and modifications to the present invention may be made by one skilled in the art after reading the teachings herein, and such equivalent changes and modifications are intended to fall within the scope of the invention as defined in the appended claims.
Claims (8)
1. The fusion method for heterogeneous signal soft information extraction based on the short-wave multichannel diversity framework is characterized by comprising the following steps of:
step S1, each transmitting station modulates and transmits the information source by using a proper modulation mode and transmission rate;
s2, independently demodulating signals with different modulations, and extracting corresponding symbol soft information;
step S3, the symbol soft information is mapped into bit soft information in a unified way;
s4, realizing the normalized mapping of the bit soft information;
and S5, obtaining diversity gain by utilizing an addition form, and obtaining a decoding result through multi-decision.
2. The fusion method for heterogeneous signal soft information extraction based on short-wave multichannel diversity framework of claim 1, wherein the extracting of the corresponding symbol soft information in step S2 comprises:
the extraction of the composite domain modulation QAM soft information comprises the following steps: the multi-domain joint modulation mode is QAM modulation, information of which is mapped on two signal domains of amplitude and phase, and soft information is described by adopting the distance between a received symbol constellation point and a reference constellation point.
3. The fusion method of heterogeneous signal soft information extraction based on short-wave multi-channel diversity framework according to claim 1, wherein the step S3 comprises:
PSK and QAM firstly carry out correlation mapping and then carry out bit mapping; ASK and MFSK directly perform bit mapping.
4. A fusion method of heterogeneous signal soft information extraction based on a short wave multi-channel diversity framework according to claim 3, wherein the correlation mapping comprises:
wherein S is j For this purpose soft information, d, of the reference constellation point j i The symbol P i Corresponding soft information, d in QAM i Represents distance d in MPSK i Representing the absolute value of the angle difference, the symbol set P is:
P＝{P i |i＝0,1,2,...,M-1}
where M represents the number of symbol soft information.
5. A fusion method of heterogeneous signal soft information extraction based on a short wave multi-channel diversity framework according to claim 3, wherein the bit map comprises:
mapping the symbol soft information onto the bit soft information is achieved by mapping 0's of the bit information into-1's constituting a coefficient matrix and then multiplying the coefficient matrix by a symbol soft information vector.
6. The fusion method for heterogeneous signal soft information extraction based on short-wave multichannel diversity framework of claim 1, wherein the bit soft information normalization mapping in step S4 comprises:
and carrying out data statistics analysis on the bit soft information and noise thereof to obtain a certain statistical model modeling obeyed by the bit soft information of a certain moment, uniformly mapping the bit soft information into a probability form of the bit soft information, and limiting the value of the soft information within the range of [0,1 ].
7. The fusion method for heterogeneous signal soft information extraction based on short wave multi-channel diversity framework according to claim 6, wherein uniformly mapping the bit soft information into a probability form of the bit soft information comprises:
assuming that the noise of the bit soft information is subject to Gaussian distribution, the bit mapped soft information is defined as occurrence of events B and A 0 An event representing that bit is 0, A 1 An event representing the bit being 1, A 0 And A 1 2 mutually incompatible events;
probability P (B|A) 0 ) And P (B|A) 1 ) The description is as follows:
wherein S is soft information after bit mapping, mu 0 、σ 0 Normal distribution parameter, μ, for a metric value of 0 bits 1 、σ 1 A normal distribution parameter that is a metric value with bit 1;
according to the posterior probability formula:
wherein P (A) 0 ) Representing the probability that the current bit value in the received information is 0, P (A 1 ) Representing the probability that the current bit value in the received information is 1, the transmitted value needs to satisfy P (A 0 )＝P(A 1 ) Finally, the bit soft is obtainedConversion of metric values to probability values for information:
P(A 0 i B) and P (A) 1 I B) is the final normalized bit soft information, denoted as m (0) and m (1).
8. The fusion method of heterogeneous signal soft information extraction based on short-wave multi-channel diversity framework according to claim 1, wherein the step S5 comprises:
adding and fusing the normalized bit soft information, and taking larger values in M (0) and M (1) as decoding results:
M(0)＝m1(0)+m2(0)+,...,ms(0)
M(1)＝m1(1)+m2(1)+,...,ms(1)
and in the same way, mi (0) is a normalized bit soft information value with a certain bit of 0 of the ith branch, M (0) is a fusion added value with a certain corresponding bit of 0 of all branches, mi (1) is a normalized bit soft information value with a certain bit of 1 of the ith branch, and M (1) is a fusion added value with a certain corresponding bit of 1 of all branches.
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