CN102035769B - Phase shift keying signal blind detection method based on plural discrete full-feedback neural network - Google Patents

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

Phase shift keyed signal blind checking method based on plural discrete unity-feedback neutral network

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, due to time delay expansion and channel bandwidth limitations, the waveform that receives a code element in signal can expand in other code-element periods, causes intersymbol interference.This non-linear signal amplitude that not only can affect also affects 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 Fading Characteristics of Outdoor Time-variant Wireless Channel, eliminate intersymbol interference, but traditional blind checking method is all take second-order statistic or high-order statistic as the basis, it is 0 that required data volume all necessarily requires quite greatly and all the signal average, easily be absorbed in local minimum, can not satisfy the requirement of high-speed transfer signal system.Minimum value due to 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 be 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] the 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 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) for 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 plural discrete activation primitive

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 the unique user transmitted signal, through over-sampling, obtains the reception equation of discrete time channel:

X _N＝SΓ ^H，

In 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 the transmitted signal battle array, P is channel exponent number, and L is the equalizer exponent number, and N is 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 less than or equal to M, and k is positive integer constantly,

Γ is by h _jj, jj=0,1 ..., the block Toeplitz matrix that P consists of, h _jj=[h ₀..., h _P] _{Q * (P+1)}It is channel impulse response; Q is 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)] ^TReceive data battle array, wherein x _L(k)=Γ s _L+P(k);

2.. according to performance function and the optimization problem of structure

Because the balance point of plural discrete unity-feedback neutral network energy function is exactly optimum point, the optimization problem of detection signal is mapped on 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 belongs to set; During the full column rank of Γ, 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) q}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) q}It is the singular value battle array; Therefore, the blind Detecting problem just is converted into

The globally optimal solution problem;

3.. because the need detection signal is mpsk signal, utilize the discrete unity-feedback neutral network kinetics equation

Carry out iteration, until s (k+1)=s (k), the signal that obtain this moment is exactly the extreme point of energy function in " equilibrium point ", also is the solution of required optimization problem; Activation primitive in formula M=1 wherein, 2 ..., M, e represents exponential function, and π represents angle, and t is 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 less than or equal to N.

The present invention has set up the Optimal performance function of direct blind detection transmitted signal according to the subspace relation that receives between signal and transmitted signal.From literature method is different so far, the performance function that the present invention sets 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 that receive signal, but utilizes directly, fully the character set under constellation, the blind Detecting problem is converted into finds the solution quadratic programming problem.

Construct 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) for 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 that receive signal yet, therefore only need utmost point short receptor data just can realize calculating target, can be applicable to the meaningless occasion of statistic and channel time-varying field and close.Fig. 3, Fig. 4 are respectively the signal constellation (in digital modulation) figure that the present invention receives signal and the plural discrete Hopfield neural network of process, can find out signal blind Detecting works very well from two figure.

Description of drawings

The discrete leggy Hopfield nerve net structure chart of Fig. 1 the present invention plural number.

Multiple discrete activation primitive σ during Fig. 2 M=8 of the present invention _M(t).

Fig. 3 the present invention receives signal constellation (in digital modulation) figure.

Fig. 4 blind Detecting signal constellation (in digital modulation) of the present invention figure.

Embodiment

Before describing in detail, some nouns, symbol and the formula that at first use in 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, transmitted 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 block Toeplitz matrix that P consists of, [h ₀..., h _P] _{Q * (P+1)}Be channel impulse response, the receive 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), during the full column rank of Γ, structural behavior function and optimization problem

${\mathrm{<figure-callout\; id="0"\; label="J"\; filenames="HSA00000357634800021.png,HSA00000357634800022.png"\; state="\{\{state\}\}">J</figure-callout>}}_0=s_N^H(k-d)Q{s}_N(k-d)=s^H\mathrm{Qs}---\left(2\right)$

$\hat{s}=\underset{\hat{s}\&Element;A^N}{\arg \min }\left\{J_0\right\}---\left(3\right)$

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 belongs to set A.

During the full column rank of Γ, 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, multiple discrete activation primitive σ when Fig. 3 is K=8 _K(t) figure.

1) kinetics equation of this nerve net is

$s_l(k+1)={\mathrm{\&sigma;}}_M\left(e^{i(\mathrm{\&pi;}/M)}\underset{j}{\mathrm{\&Sigma;}}{w}_{\mathrm{lj}}{s}_j\left(k\right)\right)---\left(4\right)$

{ s wherein _j(k) ∈ A|j=1,2 ..., N}; w _ljBe the element in plural weight matrix, M is the number of phases of phase shift keyed signal.The discrete activation primitive of plural number

${\mathrm{\&sigma;}}_M\left(t\right)=e^{i\frac{2(m-1)}{M}\mathrm{\&pi;}},\frac{2(m-1)}{M}\mathrm{\&pi;}\&le;\arg \left(t\right)<\frac{2m}{M}\mathrm{\&pi;},\&ForAll;m=\mathrm{1,2},\&CenterDot;\&CenterDot;\&CenterDot;,M---\left(5\right)$

Wherein e represents exponential function, and π represents angle, and t is function argument; Arg (t) is the angle computing, i.e. the phase angle of independent variable t, and m is the positive integer less than or equal to M, l and j are the positive integer less than or equal to N.

The plural discrete activation primitive σ that M=8 is corresponding _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 asynchronous work mode can be used formula (6) statement so.

$E(s,k):=-\frac{1}{2}\underset{l=1}{\overset{N}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{w}_{\mathrm{lj}}{s}_l*\left(k\right)s_j\left(k\right)---\left(6\right)$

Being write as quadratic form is

$E(s,k)=-\frac{1}{2}{s}^H\left(k\right)\mathrm{Ws}\left(k\right).---\left(7\right)$

The below illustrates the blind Detecting that how to realize the multi-system phase shift keying, and concrete steps are as follows:

1.. receiving terminal receives the unique user transmitted signal, through over-sampling, obtains the reception equation of discrete time channel:

X _N＝SΓ ^H，

In 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 less than or equal to M.Γ is by h _jj, jj=0,1 ..., the block Toeplitz matrix that P consists of, 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 random raised cosine pulse response that produces; ω _Rj, ω _IjBe equally distributed random weight coefficient between (0,1), t is 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.. because the need detection signal is the 8PSK signal, utilize the discrete unity-feedback neutral network kinetics equation

Carry out iteration, until s (k+1)=s (k), the signal that obtain this moment is exactly the extreme point of energy function in " equilibrium point ", also is the solution of required optimization problem; Activation primitive in formula

M=1 wherein, 2 ..., 8.L and j are the positive integer less than 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 plural discrete activation primitive ${\mathrm{\&sigma;}}_M\left(t\right)=e^{i\frac{2(m-1)}{M}\mathrm{\&pi;}},$ $\frac{2(m-1)}{M}\mathrm{\&pi;}\&le;\arg \left(t\right)<\frac{2m}{M}\mathrm{\&pi;},$ 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 the unique user transmitted signal, through over-sampling, obtains the reception equation of discrete time channel:

X _N＝SΓ ^H，

In 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 the transmitted signal battle array, P is channel exponent number, and L is the equalizer exponent number, and N is 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 less than or equal to M, and k is positive integer constantly,

Γ is by h _jj, jj=0,1 ..., the block Toeplitz matrix that P consists of, h _jj=[h ₀..., h _P] _{Q * (P+1)}It is channel impulse response; Q is 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)] ^TReceive data battle array, wherein x _L(k)=Γ s _L+P(k);

2.. according to performance function and the optimization problem of structure

Because the balance point of plural discrete unity-feedback neutral network energy function is exactly optimum point, the optimization problem of detection signal is mapped on 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 belongs to set A; During the full column rank of Γ, 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 $X_N=[U,U_c]\&CenterDot;\left[\begin{array}{c}D\\ 0\end{array}\right]\&CenterDot;V^H$ In basic matrix at the tenth of the twelve Earthly Branches; (0) _{(N-(L+P+1)) * (L+1) q}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) q}It is the singular value battle array;

Therefore, the blind Detecting problem just is converted into

The globally optimal solution problem;

3.. because the need detection signal is mpsk signal, utilize the discrete unity-feedback neutral network kinetics equation

Carry out iteration, until s (k+1)=s (k), the signal that obtain this moment is exactly the extreme point of energy function in " equilibrium point ", also is the solution of required optimization problem; Activation primitive in formula ${\mathrm{\&sigma;}}_M\left(t\right)=e^{i\frac{2(m-1)}{M}\mathrm{\&pi;}},$ $\frac{2(m-1)}{M}\mathrm{\&pi;}\&le;\arg \left(t\right)<\frac{2m}{M}\mathrm{\&pi;},$ M=1 wherein, 2 ..., M, e represents exponential function, and π represents angle, and t is function argument; Arg (t) is the angle computing, i.e. the phase angle of independent variable t, w _ljBe the element in plural weight matrix, the connection weights of expression from neuron l to neuron j, l and j are the positive integer less than or equal to N.

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