CN102035769A - Phase shift keying signal blind detection method based on plural discrete full-feedback neural network - Google Patents
Phase shift keying signal blind detection method based on plural discrete full-feedback neural network Download PDFInfo
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Abstract
The invention discloses a phase shift keying signal blind detection method based on a plural discrete full-feedback neural network. In the method, according to a principle of decreasing energy function of the plural discrete full-feedback neural network, a Hermitian weight matrix capable of directly detecting phase shift keying signals is constructed, so that each multi-phase shift keying (MPSK) signal centralized constellation signal point is a stable equilibrium point of a Hopfield neural network; therefore, the blind detection of the MPSK signals is realized. The method can realize computing targets by only needing extremely short received data, and can be applied to statistic meaningless occasions. The search space is narrowed, the difficulty is reduced, the search time is obviously superior to that of other blind detection algorithms, and the system performance is correspondingly improved.
Description
Technical field
The present invention relates to wireless communication signals process field and field of neural networks, especially relate to the phase shift keyed signal blind Detecting of the receiving terminal of cordless communication network.
Background technology
In digital communication and transmission, because time delay expansion and channel bandwidth limitations, the waveform of a code element in the received signal can expand in other code-element periods, causes intersymbol interference.This non-linear signal amplitude that not only can influence also influences phase value, as everyone knows, multi-system phase shift keyed signal MPSK (Multi-Phase Shift Keying) signal error-resilient performance and anti fading performance are lower, and be very sensitive for non-linear interference, thereby can cause the signal constellation (in digital modulation) distortion.Blind Signal Detection Techniques can effectively be resisted the wireless channel fading characteristic, eliminate intersymbol interference, but traditional blind checking method is all based on second-order statistic or high-order statistic, it is 0 that required data volume all necessarily requires the signal average quite greatly and all, be absorbed in local minimum easily, can not satisfy the requirement of high-speed transfer signal system.Because the minimum value of the target function of solving-optimizing problem, be that the difficult problem of NP (Nondeterministic Polynomial) can be converted into and finds the solution the energy function that a discrete unity-feedback neutral network is Hopfield neural net DHNN (Discrete hopfield neural network), so we can utilize the discrete hopfield neural network decrease speed to be exceedingly fast and are easy to hard-wired advantage.Existing Hopfield neural network model design limitation obviously can not adapt to the demand of mpsk signal blind Detecting research in the modern communications development in the activation primitive of 2PSK.
Many alternative literature methods attempt to overcome this defective, but successful example seldom.Document [J.M.Zurada, Neural Networks.Binary Monotonic and Multiple-Valued.Proc.of the 30th IEEE International Symposium on Multiple-Valued Logic, Portland, Oregon, May 23-25,2000:67-74] continuous activation primitive of many level and corresponding real number field CHNN Hopfield Neural Networks proposed.The weight matrix of its neural net and the source of weight matrix of the present invention and be configured with fundamental difference.The neural net of this document can only solve the associative memory problem, and can not solve the complex field optimal solution problem under the signal unknown situation, i.e. MPSK blind Detecting problem.Utilizing plural discrete hopfield neural network to solve in the mpsk signal blind Detecting problem document never occurs.
Summary of the invention
Technical problem: the objective of the invention is provides a kind of mpsk signal blind checking method based on plural discrete unity-feedback neutral network (being the Hopfield neural net) at the defective and the deficiency of prior art, solved the complex field optimal solution problem under the signal unknown situation, for wireless communication networks provides signal blind checking method accurately.
Technical scheme: a kind of phase shift keyed signal blind checking method based on plural discrete unity-feedback neutral network is characterized in that: utilize the discrete activation primitive of plural number
M=1 wherein, 2 ..., M adopts kinetics equation
Construct plural discrete unity-feedback neutral network, realize the blind Detecting of multi-system phase shift keying mpsk signal, concrete steps are as follows:
1.. receiving terminal receives unique user and sends signal, through over-sampling, obtains the reception equation of discrete time channel:
X
N=SΓ
H,
In the formula, S=[s
L+P(k) ..., s
L+P(k+N-1)]
T=[s
N(k) ..., s
N(k-P-L)]
N * (L+P+1)Be to send the signal battle array, P is a channel exponent number, and L is the equalizer exponent number, and N is a desired data length; s
L+P(k)=[s (k) ..., s (k-L-P)]
TS belongs to set A,
M is the number of phases of phase shift keyed signal, and m is the positive integer smaller or equal to M, and k is a positive integer constantly,
Γ is by h
Jj, jj=0,1 ..., the piece Toeplitz matrix that P constitutes, h
Jj=[h
0..., h
P]
Q * (P+1)It is channel impulse response; Q is an oversample factor; ()
HExpression Hermitian transposition; ()
TThe representing matrix transposition; (X
N)
The q of N * (L+1)=[x
L(k) ..., x
L(k+N-1)]
TBe to receive data battle array, wherein x
L(k)=Γ s
L+P(k);
2.. according to the performance function and the optimization problem of structure
Because the balance point of plural discrete unity-feedback neutral network energy function is exactly an optimum point, the optimization problem of detection signal is mapped on the energy function, weight matrix W=-Q can be set; Wherein,
The estimated value of expression signal, A
NExpression
Be the column vector of N * 1, its each element all belongs to set; When Γ expires column rank, necessarily have
Satisfy Qs
N(k-d)=0.D=0 ..., K+L, and (U
c)
N * (N-(L+P+1))It is singular value decomposition
In basic matrix at the tenth of the twelve Earthly Branches; (0)
(N-(L+P+1)) * (L+1) qBe null matrix, (V)
(L+1) q of q * (L+1)It is basic matrix at the tenth of the twelve Earthly Branches; (U
c)
N * (N-(L+P+1))It is basic matrix at the tenth of the twelve Earthly Branches; (D)
(L+P+1) * (L+1) qIt is the singular value battle array; Therefore, the blind Detecting problem just is converted into
The globally optimal solution problem;
3.. owing to need detection signal is mpsk signal, utilizes the discrete unity-feedback neutral network kinetics equation
Carry out iteration, up to s (k+1)=s (k), the signal that obtain this moment is exactly the extreme point of energy function in " balance point set ", also is separating of the optimization problem of asking; Activation primitive in the formula
M=1 wherein, 2 ..., M, e represents exponential function, and π represents angle, and t is a function argument; Arg (t) is the angle computing, i.e. the phase angle of independent variable t, and l and j are the positive integer smaller or equal to N.
The present invention has set up the optimization performance function that direct blind Detecting sends signal according to the subspace relation between received signal and the transmission signal.With literature method is different so far, the performance function that the present invention set up does not rely on any statistical information.Specifically, the present invention neither relies on the known constellation statistic of priori, does not also rely on any second order or the high-order statistic of received signal, but utilizes the character set under the constellation directly, fully, the blind Detecting problem is converted into finds the solution quadratic programming problem.
Constructed a plural discrete hopfield neural network, realized the mpsk signal blind Detecting by finding the solution the quadratic programming optimal solution.
Beneficial effect: the objective of the invention is provides a kind of mpsk signal blind checking method based on plural discrete unity-feedback neutral network (being the Hopfield neural net) at the defective and the deficiency of prior art, solved the complex field optimal solution problem under the signal unknown situation, for wireless communication networks provides signal blind checking method accurately.
New departure is compared with existing Blind Detect Algorithm, do not rely on any statistical information, neither rely on the known constellation statistic of priori, do not rely on any second order or the high-order statistic of received signal yet, therefore only need a utmost point short receptor data just can realize calculating target, can be applicable to that meaningless occasion of statistic and channel time-varying field close.Fig. 3, Fig. 4 are respectively the signal constellation which of received signal of the present invention and the plural discrete hopfield neural network of process, from two figure as can be seen, and signal blind Detecting works very well.
Description of drawings
The discrete leggy Hopfield nerve net structure chart of Fig. 1 the present invention plural number.
Discrete again activation primitive σ during Fig. 2 M=8 of the present invention
M(t).
Fig. 3 received signal planisphere of the present invention.
Fig. 4 blind Detecting signal constellation which of the present invention.
Embodiment
Before describing in detail, some nouns, symbol and the formula that at first use in the define system:
P: channel exponent number
L: equalizer exponent number
N: this programme algorithm desired data length
Q: oversample factor
M: the number of phases of phase shift keyed signal
()
H: the Hermitian transposition
()
T: matrix transpose
Further describe thought of the present invention below in conjunction with accompanying drawing.
When noise was ignored in definition 1, the reception equation of discrete time channel was defined as follows
X
N=SΓ
H (1)
Wherein, send signal battle array S=[s
L+P(k) ..., s
L+P(k+N-1)]
T=[s
N(k) ..., s
N(k-P-L)]
N * (L+P+1), s
L+P(k)=[s (k) ..., s (k-L-P)]
TΓ is by h
Jj, jj=0,1 ..., the piece Toeplitz matrix that P constitutes, [h
0..., h
P]
Q * (P+1)Be channel impulse response, receiving the data battle array is (X
N)
The q of N * (L+1)=[x
L(k) ..., x
L(k+N-1)]
T, x
L(k)=Γ s
L+P(k).
Define 2 for formula (1), when Γ expires column rank, structural behavior function and optimization problem
Wherein,
M is the number of phases of phase shift keyed signal, and m is the positive integer less than M,
The estimated value of expression signal, A
NExpression
Be the column vector of N * 1, wherein each element all belongs to set A.
When Γ expires column rank, necessarily have
Satisfy Qs
N(k-d)=0.D=0 ..., K+L, and (U
c)
N * (N-(L+K+1))It is singular value decomposition
In basic matrix at the tenth of the twelve Earthly Branches.In fact, the blind Detecting problem is exactly the globally optimal solution problem of formula (3).
Fig. 1 is plural discrete hopfield nerve net structure chart, discrete again activation primitive σ when Fig. 3 is K=8
K(t) figure.
1) kinetics equation of this nerve net is
{ s wherein
j(k) ∈ A|j=1,2 ..., N}; w
LjBe the element in the plural weight matrix, M is the number of phases of phase shift keyed signal.The discrete activation primitive of plural number
Wherein e represents exponential function, and π represents angle, and t is a function argument; Arg (t) is the angle computing, i.e. the phase angle of independent variable t, and m is the positive integer smaller or equal to M, l and j are the positive integer smaller or equal to N.
The plural number of the M=8 correspondence activation primitive σ that disperses
M(t) as shown in Figure 2.
2) energy function
Theorem 1: in the plural discrete hopfield nerve net that employing formula (4) shown in Figure 2, formula (5) are described, if W is the Hermitian matrix, W=W
H, the energy function of this nerve net under the asynchronous working pattern can be used formula (6) statement so.
Being write as quadratic form is
Illustrate the blind Detecting that how to realize the multi-system phase shift keying below, concrete steps are as follows:
1.. receiving terminal receives unique user and sends signal, through over-sampling, obtains the reception equation of discrete time channel:
X
N=SΓ
H,
In the formula, channel exponent number is P=5, and the equalizer exponent number is L=6, under the 8PSK RST, and desired data length N=200; S belongs to set A,
M=8, m are the positive integer smaller or equal to M.Γ is by h
Jj, jj=0,1 ..., the piece Toeplitz matrix that P constitutes, h
Jj=[h
0..., h
P]
Q * (P+1)It is channel impulse response; Oversample factor q=3.
Channel
For synthesizing complex channel in 2 footpaths through oversample factor q=3 over-sampling.Wherein: h
R(α, t-τ
Rj), h
I(α, t-τ
Ij) be respectively roll-off factor α=0.1, delay factor τ
Rj, τ
IjThe raised cosine pulse response that produces at random; ω
Rj, ω
IjBe equally distributed random weight coefficient between (0,1), t is an independent variable.
2.. calculate again
(U wherein
c)
N * (N-(L+P+1))It is singular value decomposition
In basic matrix at the tenth of the twelve Earthly Branches.Weight matrix W=-Q is set; Therefore, the blind Detecting problem just is converted into
The globally optimal solution problem;
3.. owing to need detection signal is the 8PSK signal, utilizes the discrete unity-feedback neutral network kinetics equation
Carry out iteration, up to s (k+1)=s (k), the signal that obtain this moment is exactly the extreme point of energy function in " balance point set ", also is separating of the optimization problem of asking; Activation primitive in the formula
M=1 wherein, 2 ..., 8.L and j are the positive integer smaller or equal to N=200.
Claims (1)
1. the phase shift keyed signal blind checking method based on plural discrete unity-feedback neutral network is characterized in that: utilize the discrete activation primitive of plural number
M=1 wherein, 2 ..., M adopts kinetics equation
Construct plural discrete unity-feedback neutral network, realize the blind Detecting of multi-system phase shift keying mpsk signal, concrete steps are as follows:
1.. receiving terminal receives unique user and sends signal, through over-sampling, obtains the reception equation of discrete time channel:
X
N=SΓ
H,
In the formula, S=[s
L+P(k) ..., s
L+P(k+N-1)]
T=[s
N(k) ..., s
N(k-P-L)]
N * (L+P+1)Be to send the signal battle array, P is a channel exponent number, and L is the equalizer exponent number, and N is a desired data length; s
L+P(k)=[s (k) ..., s (k-L-P)]
TS belongs to set A,
M is the number of phases of phase shift keyed signal, and m is the positive integer smaller or equal to M, and k is a positive integer constantly,
Γ is by h
Jj, jj=0,1 ..., the piece Toeplitz matrix that P constitutes, h
Jj=[h
0..., h
P]
Q * (P+1)It is channel impulse response; Q is an oversample factor; ()
HExpression Hermitian transposition; ()
TThe representing matrix transposition; (X
N)
The q of N * (L+1)=[x
L(k) ..., x
L(k+N-1)]
TBe to receive data battle array, wherein x
L(k)=Γ s
L+P(k);
2.. according to the performance function and the optimization problem of structure
Because the balance point of plural discrete unity-feedback neutral network energy function is exactly an optimum point, the optimization problem of detection signal is mapped on the energy function, weight matrix W=-Q can be set;
Wherein,
The estimated value of expression signal, A
NExpression
Be the column vector of N * 1, its each element all belongs to set; When Γ expires column rank, necessarily have
Satisfy Qs
N(k-d)=0, d=0 ..., K+L, and (U
c)
N * (N-(L+P+1))It is singular value decomposition
In basic matrix at the tenth of the twelve Earthly Branches; (0)
(N-(L+P+1)) * (L+1) qBe null matrix, (V)
(L+1) q of q * (L+1)It is basic matrix at the tenth of the twelve Earthly Branches; (U
c)
N * (N-(L+P+1))It is basic matrix at the tenth of the twelve Earthly Branches; (D)
(L+P+1) * (L+1) qIt is the singular value battle array; Therefore, the blind Detecting problem just is converted into
The globally optimal solution problem;
3.. owing to need detection signal is mpsk signal, utilizes the discrete unity-feedback neutral network kinetics equation
Carry out iteration, up to s (k+1)=s (k), the signal that obtain this moment is exactly the extreme point of energy function in " balance point set ", also is separating of the optimization problem of asking; Activation primitive in the formula
M=1 wherein, 2 ..., M, e represents exponential function, and π represents angle, and t is a function argument; Arg (t) is the angle computing, i.e. the phase angle of independent variable t, and l and j are the positive integer smaller or equal to N.
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Cited By (4)
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---|---|---|---|---|
CN103152133A (en) * | 2013-02-26 | 2013-06-12 | 南京邮电大学 | Hysteretic all feedback neural network-based signal blind detection method |
CN103973623A (en) * | 2014-05-28 | 2014-08-06 | 郑州大学 | Multi-system phase shift keying signal detection system |
CN107346991A (en) * | 2017-06-22 | 2017-11-14 | 北京工业大学 | A kind of multichannel mpsk signal renovation process based on Phase sensitive amplification |
CN108390838A (en) * | 2018-01-12 | 2018-08-10 | 温州大学 | Non-Gaussian noise system blind balance method based on noise energy ratio minimum |
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WO2008086044A1 (en) * | 2007-01-13 | 2008-07-17 | Yi Sun | Local maximum likelihood detection in a communication system |
CN101719885A (en) * | 2009-11-27 | 2010-06-02 | 南京邮电大学 | Multi-level signal blind detection method based on discrete unity-feedback neutral network |
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WO2008086044A1 (en) * | 2007-01-13 | 2008-07-17 | Yi Sun | Local maximum likelihood detection in a communication system |
CN101719885A (en) * | 2009-11-27 | 2010-06-02 | 南京邮电大学 | Multi-level signal blind detection method based on discrete unity-feedback neutral network |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103152133A (en) * | 2013-02-26 | 2013-06-12 | 南京邮电大学 | Hysteretic all feedback neural network-based signal blind detection method |
CN103973623A (en) * | 2014-05-28 | 2014-08-06 | 郑州大学 | Multi-system phase shift keying signal detection system |
CN103973623B (en) * | 2014-05-28 | 2017-02-15 | 郑州大学 | Multi-system phase shift keying signal detection system |
CN107346991A (en) * | 2017-06-22 | 2017-11-14 | 北京工业大学 | A kind of multichannel mpsk signal renovation process based on Phase sensitive amplification |
CN107346991B (en) * | 2017-06-22 | 2019-10-29 | 北京工业大学 | A kind of multichannel mpsk signal regeneration method based on Phase sensitive amplification |
CN108390838A (en) * | 2018-01-12 | 2018-08-10 | 温州大学 | Non-Gaussian noise system blind balance method based on noise energy ratio minimum |
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