CN107733820B - DS-CDMA blind symbol estimation method under the conditions of multi-path channel environment - Google Patents

DS-CDMA blind symbol estimation method under the conditions of multi-path channel environment Download PDF

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CN107733820B
CN107733820B CN201710975637.6A CN201710975637A CN107733820B CN 107733820 B CN107733820 B CN 107733820B CN 201710975637 A CN201710975637 A CN 201710975637A CN 107733820 B CN107733820 B CN 107733820B
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toeplitz
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information code
cdma
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CN107733820A (en
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曾辉
张花国
刘莹
尤少钦
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0238—Channel estimation using blind estimation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods

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  • Power Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
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Abstract

The invention belongs to blind symbol estimation technical field, a kind of DS-CDMA blind symbol estimation method under the conditions of multi-path channel environment is particularly related to.The present invention is by the multipath DS-CDMA signal modeling received at matrix form, then according to the Toeplitz special construction of information code matrix and ± 1 characteristic, receipt signal matrix are decomposed using ILSP algorithm, obtain the estimated matrix of the combined channel matrix of the Sequence composition obtained by user's frequency expansion sequence and channel parameter convolutionIt finally de-spreads to obtain user information code matrix using combined channel matrix.The beneficial effects of the present invention are: the invention proposes a kind of DS-CDMA blind symbol estimation methods under the conditions of multi-path channel environment, even and if method of the invention still there is preferable performance under Low SNR.

Description

DS-CDMA blind symbol estimation method under the conditions of multi-path channel environment
Technical field
The invention belongs to the blind of DS-CDMA (Direct-Sequence Code-Division Multiple Access) Estimation technique field particularly relates to the DS- under the conditions of a kind of multi-path channel environment based on Toeplitz matrix structure CDMA blind symbol estimation method.
Background technique
Direct Sequence Spread Spectrum (DSSS, Direct Sequence Spread Spectrum) be in Modern Communication System most One of common communication technology.Information code sequence is multiplied with the spread spectrum code sequence of a high-speed in signal sending end, so that Signal spectrum extension, can reduce the power spectral density of transmission signal, have low probability of intercept characteristic.DSSS communication system cooperation connects Debit is de-spread to signal cooperation is received using known frequency expansion sequence, can inhibit and interfere and recover transmission information.For cooperation Recipient can expand the information code sequence of transmission from solution in signal is received with the frequency expansion sequence from sender, but for non-conjunction Make recipient then to need to handle received signal, therefrom extracts signal spread-spectrum sequence, the expansion then obtained with estimation Frequency sequence de-spreads to obtain transmission information code sequence.For DS-CDMA signal, different user uses different frequency expansion sequences, and each Spread spectrum code sequence between user is mutually orthogonal, makes it have multiple access property.DS-CDMA signal has intercept probability low, anti-dry The advantages that disturbing strong ability, CDMA, is widely used in the fields such as civilian, military communication and satellite communication.Therefore to DS- The blind estimate research of CDMA signal is more meaningful.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, propose a kind of based on the more of Toeplitz matrix structure DS-CDMA blind symbol estimation method under diameter channel environment condition, method proposed by the present invention are suitable for into multi-path channel environment The DS-CDMA blind symbol estimation problem of condition.
The technical scheme is that the DS-CDMA blind symbol estimation method under the conditions of multi-path channel environment, feature exist In, comprising the following steps:
S1, building DS-CDMA signal matrix model Y:
The DS-CDMA signal through multipath transmisstion received is indicated are as follows:
Wherein, R indicates the number of user, ArFor the signal amplitude of r-th of user, brFor the information code sequence of r-th of user Column, M are information code number, hrFor the spread spectrum code sequence of r-th user and the convolution sequence of multi-path channel parameters, v (n) is variance For σ2White Gaussian noise；
The matrix form of above-mentioned DS-CDMA signal are as follows:
Y=HAST+N (1)
Wherein, JR × JR ties up diagonal matrix A=diag (A1,...,A1,...,AR,...,AR), J is since multipath causes Intersymbol interference information code number, L × JR tie up matrix H be R user frequency expansion sequence and multi-path coefficients convolution after sequences h With matrix made of zero construction, (M+J-1) × JR dimension matrix S is constructed by the element of M × R dimension information code matrix B Toeplitz matrix, N be mean value be 0, variance σ2White Gaussian noise matrix；
The information code matrix of single userStructure are as follows:
S2, the estimated matrix for obtaining matrix H
According to step S1, matrix S is Toeplitz structure, and can obtain that matrix H is multiplied with matrix S can be with transformed matrix The Toeplitz structure of H is multiplied with the non-Toeplitz matrix form of matrix S, it may be assumed that
Wherein, H-matrix can be written as [H1 H2...HJR], HiFor the i-th column of H-matrix；
sr=[S(r-1)J+1 S(r-1)J+2...SJ(r-1)+J] indicate r-th of user information code character at Toeplitz matrix Structure；
For the Toeplitz form of H-matrix, B matrix is the multi-user information code matrix that signal transmitting terminal issues, specifically Form are as follows:
According to formula 3, can obtainThe size of matrix is (M+J-1) × MR dimension, the concrete form of Toeplitz structure are as follows:
Matrix can be divided into the Toeplitz matrix of R (M+J-1) × M dimensions, can be obtained according to formula 1:
Then obtain estimated matrixSpecific method include:
S21, i=0, random initializtion M × R is enabled to tie up matrixAnd byObtain Toeplitz formal matrices
S22, i=i+1 is enabled, calculatedEliminate scale shadow It rings；
S23, generalIt is rewritten as Toeplitz formIt calculatesAgain by matrixObtain Toeplitz formal matrices
S24, repetition step (2)~(3) until algorithmic statement or reach maximum number of iterations, algorithmic statement condition are as follows:
Wherein ε is convergent threshold value；
S25, step (1)~(4) are repeated repeatedly, selects best primary as final result of iteration effect；
S3, with the estimated matrix of finally obtained H-matrixIt is de-spread to obtain the estimated matrix of information matrix s-matrix
The total technical solution of the present invention, by the multipath DS-CDMA signal modeling received at matrix form, then according to letter Cease code matrix Toeplitz special construction and ± 1 characteristic, receipt signal matrix are decomposed using ILSP algorithm, obtain by The estimated matrix of the combined channel matrix for the Sequence composition that user's frequency expansion sequence and channel parameter convolution obtainFinally utilize connection Channel matrix is closed to de-spread to obtain user information code matrix.
The beneficial effects of the present invention are: the invention proposes the DS-CDMA signal under the conditions of a kind of multi-path channel environment is blind Estimation method, even and if method of the invention under Low SNR still have preferable performance.
Detailed description of the invention
Fig. 1 is a kind of specific reality for the DS-CDMA blind symbol estimation method propagated under the conditions of multi-path channel environment of the present invention Apply mode flow chart；
Fig. 2 is in present invention specific implementation 1, and the bit error rate of information code Matrix Estimation matrix when number of users is 3 is with noise The change curve of ratio and the contrast schematic diagram of CRB (Cramer-Rao Bound)；
Fig. 3 is in present invention specific implementation 2, and the normalization of combined channel Matrix Estimation matrix when user's number is fixed is equal Square error is with the change curve of signal-to-noise ratio and the contrast schematic diagram of CRB；
Fig. 4 is in present invention specific implementation 3, and the normalization of combined channel Matrix Estimation matrix when user's number is fixed is equal Square error is with the change curve of signal length and the contrast schematic diagram of CRB.
Specific embodiment
With reference to the accompanying drawing with example in detail technical solution of the present invention.
Embodiment 1
Fig. 1 is a kind of specific embodiment stream of the DS-CDMA blind symbol estimation under the conditions of multi-path channel environment of the present invention Cheng Tu.As shown in Figure 1, DS-CDMA blind symbol estimation method includes following step under the conditions of the present embodiment realizes multi-path channel environment It is rapid:
Step 1: the DS-CDMA signal through multipath transmisstion received is represented by
Wherein, R indicates the number of user, this is embodied as R=3, arFor the signal amplitude of r-th of user, this implementation In be random number, brFor the information code sequence of r-th of user, information code sequence and spread spectrum code sequence are all ± 1 in this implementation Sequence, M be information code number, this implement M=100, spreading gain L=31, the multi-path channel parameters of a user be all [1, 0.9,0.7,0.5,0.3,0.15], hrFor the spread spectrum code sequence of r-th user and the convolution sequence of multi-path channel parameters, noise Than arriving 0dB for -5dB, n (n) is that variance is σ2White Gaussian noise.
Step 2: by step 1 it is found that the matrix form of the DS-CDMA signal through multipath transmisstion can be written as
Y=HAST+N
Wherein JR × JR ties up diagonal matrix A=diag (A1,...,A1,...,AR,...,AR), J is due to caused by multipath The information code number of intersymbol interference, L × JR tie up the sequences h after frequency expansion sequence and the multi-path coefficients convolution that matrix H is R user and Matrix made of zero construction, (M+J-1) × JR dimension matrix S are by the Toeplitz of the element construction of M × R dimension information code matrix B Matrix, N be mean value be 0, variance σ2White Gaussian noise matrix.
The information code matrix of single userStructure be shown below
Step 3: for the DS-CDMA signal matrix model Y of above-mentioned introduction, since the Toeplitz matrix of matrix S is special Structure and ± 1 characteristic, fuzzy matrix can destroy the Toeplitz structure of matrix S if it exists, and matrix A is diagonal matrix, i.e., only Matrix H can respectively be arranged and generate scale influence, only H each column need to be normalized and can be eliminated, therefore can directly utilized ILSP algorithm decomposes matrix Y to obtain the estimated matrix of s-matrix and H-matrixWith
Implement step:
(1) enables i=0, random initializtion M × R tie up matrixAnd byObtain Toeplitz formal matrices
(2) enables i=i+1, calculatesEliminate scale shadow It rings；
(3) willIt is rewritten as Toeplitz formIt calculatesAgain by matrixObtain Toeplitz formal matrices
(4) repetition step (2)~(3) until algorithmic statement or reach maximum number of iterations, algorithmic statement condition are as follows:
Wherein ε is convergent threshold value, is usually taken to be 1 × 10-9.In this algorithm, maximum number of iterations is set as 50.
(5) repeats step (1)~(4) repeatedly (this method is selected as 40 times), selects iteration effect to improve algorithm performance Fruit it is best it is primary be used as final result.
Step 4: with the estimated matrix of finally obtained H-matrixIt is de-spread to obtain the estimation square of information matrix s-matrix Battle array
Obtained estimated matrix is compared with former data matrix, counts the bit error rate, at the same with the CRB under same case It compares, and draws the curve that the bit error rate changes with signal-to-noise ratio.This implements to carry out 100 Monte Carlo Experiments, final to obtain The information code matrix bit error rate arrived is as shown in Figure 2 with SNR (Signal Noise Rate, signal-to-noise ratio) change curve.It can from figure To find out blind despread method proposed by the present invention excellent performance in low signal-to-noise ratio, and gradually approached with signal-to-noise ratio increase CRB curve, is consistent with theory.
Embodiment 2
The purpose of the present embodiment is under conditions of user's number is certain, to the normalized mean squared error of joint channel matrix Rate is emulated with SNR variation.This implementation condition is identical as implementing 1, and signal-to-noise ratio is that -5dB arrives 5dB, the normalizing of combined channel Change mean square error to be calculated by following formula:
100 Monte Carlo experiments are carried out, finally obtained combined channel matrix normalization mean square error changes bent with SNR Line is as shown in Figure 3 compared with CRB.As can be seen from the figure blind despread method proposed by the present invention performance in low signal-to-noise ratio Well, the normalized mean squared error of combined channel reduces with the increase of signal-to-noise ratio, and gradually approaches CRB, is consistent with theory.
Embodiment 3
The purpose of the present embodiment is under conditions of user's number is certain, to the normalized mean squared error of joint channel matrix Rate is emulated with signal length variation.The fixed SNR of this implementation condition is -3dB, and signal length changes to 500 from 100, Remaining condition is identical as implementing 2, and the normalized mean squared error of combined channel is calculated by following formula:
100 Monte Carlo experiments are carried out, finally obtained combined channel matrix normalization mean square error is with signal length Change curve is as shown in Figure 4 compared with CRB.As can be seen from the figure the combined channel that blind despread method proposed by the present invention obtains Normalized mean squared error reduce with the increase of signal length, and gradually approach CRB, be consistent with theory.

Claims (1)

1. the DS-CDMA blind symbol estimation method under the conditions of multi-path channel environment, which comprises the following steps:
S1, building DS-CDMA signal matrix model Y:
The DS-CDMA signal through multipath transmisstion received is indicated are as follows:
Wherein, R indicates the number of user, ArFor the signal amplitude of r-th of user, brFor the information code sequence of r-th of user, M is Information code number, hrFor the spread spectrum code sequence of r-th user and the convolution sequence of multi-path channel parameters, v (n) is that variance is σ2's White Gaussian noise, L are spreading gain；
The matrix form of above-mentioned DS-CDMA signal are as follows:
Y=HAST+N (1)
Wherein, JR × JR ties up diagonal matrix A=diag (A1,...,A1,...,AR,...,AR), J is the intersymbol due to caused by multipath The information code number of interference, L × JR tie up the frequency expansion sequence and sequences h and zero structure after multi-path coefficients convolution that matrix H is R user Matrix made of making, (M+J-1) × JR dimension matrix S are the Toeplitz matrixes constructed by the element of M × R dimension information code matrix B, N be mean value be 0, variance σ2White Gaussian noise matrix；
The information code matrix of single userStructure are as follows:
S2, the estimated matrix for obtaining matrix H
According to step S1, matrix S is Toeplitz structure, and can obtain that matrix H is multiplied with matrix S can be with transformed matrix H's Toeplitz structure is multiplied with the non-Toeplitz matrix form of matrix S, it may be assumed that
Wherein, H-matrix can be written as [H1 H2 ... HJR], HiFor the i-th column of H-matrix；
sr=[S(r-1)J+1 S(r-1)J+2 … SJ(r-1)+J] indicate r-th of user information code character at Toeplitz matrix structure；
For the Toeplitz form of H-matrix, B matrix is the multi-user information code matrix that signal transmitting terminal issues, concrete form Are as follows:
According to formula (3), can obtainThe size of matrix is (M+J-1) × MR dimension, the concrete form of Toeplitz structure are as follows:
Matrix can be divided into the Toeplitz matrix of R (M+J-1) × M dimensions, can be obtained according to formula (1):
Then obtain estimated matrixSpecific method include:
S21, i=0, random initializtion M × R is enabled to tie up matrixAnd byObtain Toeplitz formal matrices
S22, i=i+1 is enabled, calculated1≤r≤R, eliminating scale influences；
S23, generalIt is rewritten as Toeplitz formIt calculatesAgain by matrix To Toeplitz formal matrices
S24, repetition step S21~S23 until algorithmic statement or reach maximum number of iterations, algorithmic statement condition are as follows:
Wherein ε is convergent threshold value；
S25, it repeats step S21~S24 more times, selects best primary as final result of iteration effect；
S3, with the estimated matrix of finally obtained H-matrixIt is de-spread to obtain the estimated matrix of information matrix s-matrix
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