CN105812300A - Long code DSSS signal blind estimation method for eliminating information code hopping - Google Patents

Long code DSSS signal blind estimation method for eliminating information code hopping Download PDF

Info

Publication number
CN105812300A
CN105812300A CN201610292502.5A CN201610292502A CN105812300A CN 105812300 A CN105812300 A CN 105812300A CN 201610292502 A CN201610292502 A CN 201610292502A CN 105812300 A CN105812300 A CN 105812300A
Authority
CN
China
Prior art keywords
code
information code
signal
long code
matrix
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201610292502.5A
Other languages
Chinese (zh)
Other versions
CN105812300B (en
Inventor
夏文龙
郭庆功
周渊平
马雪莲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sichuan University
Original Assignee
Sichuan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sichuan University filed Critical Sichuan University
Priority to CN201610292502.5A priority Critical patent/CN105812300B/en
Publication of CN105812300A publication Critical patent/CN105812300A/en
Application granted granted Critical
Publication of CN105812300B publication Critical patent/CN105812300B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H04B1/707—Spread spectrum techniques using direct sequence modulation

Abstract

The invention discloses a long code direct sequence spread spectrum (DSSS) signal blind estimation method for eliminating information code hopping, and relates to the field of spread-spectrum signal processing during signal processing. Technical key points of the long code DSSS signal blind estimation method are as follows: in consideration that a long code is interfered by multiple different information code elements during one period, an interference reason is: random time varying of an information code causes existence of hopping between a front code element and a next code element, and a hopping point varies the polarity of a spread-spectrum code, so that long code spread spectrum signal estimation generates errors; and according to the long code DSSS signal blind estimation method for eliminating the information code hopping, a hopping point compensation matrix is constructed to a receiving signal, and influence of a hopping point is eliminated, so that a long code spread spectrum sequence is estimated by directly utilizing a principal component decomposition method under an condition of not needing of segmentation. The long code DSSS signal blind estimation method for eliminating the information code hopping is especially suitable for performing blind detection and blind estimation of long code spread spectrum signals in non-cooperative communication, and processing and detecting software radio signals of a spread spectrum system.

Description

Eliminate the long code DSSS blind symbol estimation method of information code saltus step
Technical field
The present invention relates to the spread-spectrum signal process field in signal processing, be the long code DSSS blind symbol estimation method eliminating information code saltus step concretely.
Background technology
DSSS (DirectSequenceSpreadSpectrum；DSSS) modulation technique utilizes the pseudo-random sequence of two-forty to carry out spread information signal, feature at frequency domain shows as the broadening of frequency spectrum, direct sequence spread spectrum skill has the feature of secrecy, anti-multipath, anti-interference and Anti TBIgG, is widely used in civil and military communication.Under collaboration communication scene, receiving terminal utilizes the parameter that receiving-transmitting sides is known to carry out the despreading of signal thus identifying the information of transmission.And in non-cooperating communicates, as under the situations such as radio investigation, location, information reverting, it is necessary to Direct Sequence Spread Spectrum Signal carries out blind process, and most important of which parameter is exactly obtain the pseudo-random sequence that spread spectrum adopts.
Under normal circumstances Direct Sequence Spread Spectrum Signal is classified as according to the information code element number that a spreading code cycle (pseudo-random sequence cycle) modulates short code direct sequence signal and the big class of long code direct sequence signal two.For short code direct sequence signal, its information code duration is just equal to a spreading code cycle, and namely a spreading period modulates an information code element；For long code direct sequence signal, its information code duration less than the spreading code cycle, namely spreading period modulation K (K is the positive rational number more than 1, it is possible to can also be mark for integer, respectively correspondence cycle long code and aperiodic long code) individual information code.The interference that long code Direct Sequence Spread Spectrum Signal is modulated due to information code so that long code Direct Sequence Spread Spectrum Signal is estimated that relatively short code is more difficult.Chinese patent (publication number: CN101237250A, publication date on August 6th, 2008) disclose a kind of frequency spreading wave blind estimation method based on odd value analysis, the method is that the spread-spectrum signal received is carried out segmentation, estimate the spreading code waveform in each segment data, more each section of spreading code waveform is connected the frequency expansion sequence obtaining a cycle.The method needs to be divided into spreading code the section less than spreading period, and the selection of segmentation parameter can affect the performance of estimation, and to carry out repeatedly Eigenvalues Decomposition computing, adds the complexity of calculating.Chinese patent (publication number: CN103414670A, publication date on November 27th, 2013) discloses a kind of long code DSSS signal blind despread method based on Semidefinite Programming, by constructing symmetrical matrix and adopting interior-point algohnhm to estimate spreading code waveform.The method computation complexity relatively first method is bigger, consuming time longer.
Summary of the invention
The technical problem to be solved, it is simply that provide a kind of long code DSSS blind symbol estimation method eliminating information code saltus step, solves the problem that prior art computing is complicated.
The present invention solves that the technical scheme that problem above provides is, the long code DSSS blind symbol estimation method eliminating information code saltus step comprises the following steps:
A. signal down coversion of eating dishes without rice or wine obtains baseband sampling signal, and blind estimate obtains long code spread spectrum DSSS signal period P, width Q when spreading rate and information code element, and intercepting N segment length in sampled signal is the digital signal of P, can obtain following expression
y ( n ) = A Σ i = 0 M - 1 b i q ( n - j Q ) Σ j = 0 N - 1 h ( n - j P ) + w ( n )
h ( n ) = Σ k = 0 P - 1 c k p ( n - k )
Wherein bi(bi∈ ± 1}, i=0 ..., M-1) and ck(ck∈ ± 1}, k=0 ..., and P-1) distinguish representative information code sequence and spread spectrum code sequence, the amplitude of A representation signal, M represents the number of information code in NP sample of signal, and q (n) is rectangular function and meetsP (n) represents the convolution of emission filter, channel and receiving filter, and h (n) is spread spectrum code sequence ckWith the shock response of p (n), w (n) represents additive white Gaussian noise；
B. width Q and spreading code cycle P time according to the information code element estimated, calculates the information code element number comprised in the spreading code cycle This mathematical symbolism rounds up, then in a long code spreading period, information code element is up to β trip point, constructs Hopping Pattern matrix
Wherein, Hk(k=0 ..., β) represent have the Hopping Pattern matrix that k trip point is corresponding；
C. long code baseband signal of the band received being made an uproar carries out segmentation by cycle P, obtains the vectorial y that N number of length is Pl(l=0 ..., N-1), wherein
Wherein,Represent the information symbol sequence pressing spreading rate sampling；
D. calculate?In certainly exist group hopping pattern and a blThe Hopping Pattern of middle information code is identical, namely It is the matrix of a Γ × P, thenCan be expressed as
s.t.||bl(1:P) | |2=P
| b l ( i ) | = 1 , ∀ i ∈ { 0 , 1 , ... P - 1 }
E. basisCalculate covariance matrixRightCarry out principal component decomposition, obtain characteristic of correspondence vector wmax, thus obtaining the spread spectrum code sequence estimated
c ^ = s i g n ( w max )
Wherein sign () represents sign function.
Consider that long code is subject to the interference of multiple different information code element within a cycle, the reason of interference is owing to the randomness of information code causes there is saltus step between the code element of front and back, trip point changes the polarity of spreading code, so that long code spread-spectrum signal is estimated to bring mistake, and the present invention is by structure trip point compensation matrix to received signal, reduce the impact even eliminating trip point, thus directly use principal component decomposition method to estimate frequency expansion sequence when not needing segmentation.
Further, in step a, blind estimate long code spread spectrum DSSS signal period P estimates to adopt Second spectrum, correlated fluctuations spectrometry, Cepstrum Method, circulation spectrometry or auto-correlation calculus of finite differences.
Further, in step b, Hopping Pattern matrix neutron matrix HkA jump position is represented with 1 to-1 or-1 to 1.K=0 represents does not have trip point, corresponding is length is complete 1 row vector of P, k=1 represents only one of which trip point, during one trip point can there is the position in P chip between the adjacent chip in any front and back in jump position, P-1 row vector is had under worst case, by that analogy, so that it is determined that whole information code saltus step matrix
Further, in step b, Hopping Pattern matrix can also adopt the matrix that the Hopping Pattern of the maximum trip point of jumping probability is constituted to carry out approximate representation, namely can use information code saltus step matrixSubset be similar to, thus reducing the dimension of matrix.
Further, in step d, operatorRepresenting matrixIn every a line in element and ylCorresponding element in vector carries out point multiplication operation.
Further, in step e, principal component decomposition adopts singular value decomposition or Eigenvalues Decomposition to realize.
The invention has the beneficial effects as follows, by tectonic information code Hopping Pattern matrix, eliminate the information code destruction to the spread spectrum code sequence cycle in long code spread spectrum, the blind estimate of long code frequency expansion sequence is realized by principal component analytical method, achieving with relatively low complexity and estimate performance preferably, particularly when low signal-to-noise ratio, more existing method has bigger performance boost.The present invention is especially suitable for the blind Detecting of long code spread-spectrum signal in non-cooperating communication and blind estimate, and the Software Radio for spread spectrum system processes and detection.
Below in conjunction with accompanying drawing, the present invention is further described, so that those skilled in the art are capable of the present invention.
Accompanying drawing explanation
Fig. 1 is the flow chart of the long code DSSS blind symbol estimation method eliminating information code saltus step；
The performance comparison curve chart that Fig. 2 is the present invention and traditional characteristic value decomposition method changes with sample period lengths；
Fig. 3 is the spreading code despreading correlation coefficient correlation curve figure that the present invention and traditional characteristic value decomposition method change with signal to noise ratio；
Fig. 4 is the present invention and the decomposition of traditional characteristic value and the cooperation despreading information code ber curve figure with signal to noise ratio change；
Detailed description of the invention
As it is shown in figure 1, eliminate the flow chart of the long code DSSS blind symbol estimation method of information code saltus step, the long code DSSS blind symbol estimation method eliminating information code saltus step comprises the following steps:
Step 100: process from eating dishes without rice or wine and obtain baseband sampling signal；
Step 101: blind estimate obtains long code spread spectrum DSSS signal period P, width Q when spreading rate and information code element.The estimation of P and Q can adopt secondary power spectrum, correlated fluctuations spectrum, cepstrum, Cyclic Spectrum or auto-correlation calculus of finite differences to realize, and then intercepting N segment length in sampled signal is the digital signal of P
y ( n ) = A Σ i = 0 M - 1 b i q ( n - i Q ) Σ j = 0 N - 1 h ( n - j P ) + w ( n )
h ( n ) = Σ k = 0 P - 1 c k p ( n - k )
Wherein A, bi(bi∈ ± 1}, i=0 ..., M-1 and ck(ck∈ ± 1}, k=0 ..., and P-1) distinguish the amplitude of representation signal, information code sequence and spread spectrum code sequence, M represents the number of information code in NP sample of signal.Q (n) is rectangular function and meetsP (n) represents the convolution of emission filter, channel and receiving filter, and h (n) is spread spectrum code sequence ckWith the shock response of p (n), w (n) represents additive white Gaussian noise.
Step 102: calculate the information code element number comprised in the spreading code cycle Expression rounds up, then in a long code spreading period, information code element is up to β trip point, constructs Hopping Pattern matrix
Wherein Hk(k=0 ..., β) represent have the Hopping Pattern matrix that k trip point is corresponding.Hopping Pattern matrix neutron matrix HkA jump position is represented with 1 to-1 or-1 to 1.K=0 represents does not have trip point, corresponding is length is complete 1 row vector of P, k=1 represents only one of which trip point, during one trip point can there is the position in P chip between the adjacent chip in any front and back in jump position, P-1 row vector is had under worst case, by that analogy, so that it is determined that whole information code saltus step matrixHopping Pattern matrix can also adopt the matrix that the Hopping Pattern of the maximum several trip points of jumping probability is constituted to carry out approximate representation, namely can use information code saltus step matrixSubset be similar to, thus reducing the dimension of matrix.
Step 103: long code baseband signal that the band received is made an uproar carries out segmentation by cycle P, obtains the vectorial y that N number of length is Pl(l=0 ..., N-1)
Wherein,Represent the information symbol sequence pressing spreading rate sampling.
OperatorRepresenting matrixIn every a line in element and ylCorresponding element in vector carries out point multiplication operation, and ⊙ represents that the element of correspondence position carries out point multiplication operation.?In certainly exist group hopping pattern and a blThe Hopping Pattern of middle information code is identical, namely It is the matrix of a Γ × P, thenCan be expressed as:
s.t.||bl(1:P) | |2=P
| b l ( i ) | = 1 , ∀ i ∈ { 0 , 1 , ... P - 1 }
Step 104: according toCalculate covariance matrixRightCarry out Eigenvalues Decomposition, obtain characteristic of correspondence vector wmax, thus obtaining the spread spectrum code sequence estimated
c ^ = s i g n ( w max )
Wherein sign () represents sign function.
Step 105: the spread spectrum code sequence that estimation is obtainedMake related operation with sample sequence y (n), recover information symbol sequence bi(bi∈ ± 1} ,=0 ..., M-1).
As shown in Figure 2, the performance comparison curve chart that the present invention and traditional characteristic value decomposition method change with sample period lengths, spreading code cycle P=127 in embodiment, information code element width Q=60, sample of signal length N is set as between spreading period 20 to 200, signal to noise ratio is-10dB, carries out 200 Monte Carlo simulations, by the present invention with do not eliminate the traditional characteristic value decomposition method of information code saltus step and carried out the performance comparison of error sign ratio.Embodiment from Fig. 2 is it can be seen that the sample size that needs under identical performance of the present invention is less, and the frequency expansion sequence being highly suitable for intercepting and capturing under the less occasion of sample number is estimated.
As shown in Figure 3, the spreading code despreading correlation coefficient correlation curve figure that the present invention and traditional characteristic value decomposition method change with signal to noise ratio, under different signal to noise ratios, sample of signal length N is set as 100, signal to noise ratio presses 1dB stepping from-15dB to 0dB, spreading code cycle P and information code element width Q respectively 127 and 60. present invention and do not eliminate information code saltus step traditional characteristic value decomposition method estimate spreading code parameter performance contrasted, performance assessment by define estimate spread spectrum code sequenceNormalizated correlation coefficient with actual spreading code cCharacterize.From figure 3, it can be seen that the performance boost that the present invention estimates spreading code is obvious.
As shown in Figure 4, the information code ber curve figure that the present invention and traditional characteristic value are decomposed and cooperation despreading changes with signal to noise ratio, under different signal to noise ratios, the present invention and do not eliminate the bit error rate of the information code that the traditional characteristic value decomposition method of information code saltus step recovers, and and performance when collaboration communication contrasted.Parameter setting is consistent with the embodiment of Fig. 3, from fig. 4, it can be seen that the present invention faster converges on the performance of collaboration communication.

Claims (6)

1. eliminate the long code DSSS blind symbol estimation method of information code saltus step, it is characterised in that comprise the following steps:
A. signal down coversion of eating dishes without rice or wine obtains baseband sampling signal, and blind estimate obtains long code spread spectrum DSSS signal period P, width Q when spreading rate and information code element, and intercepting N segment length in sampled signal is the digital signal of P, can obtain following expression
y ( n ) = A Σ i = 0 M - 1 b i q ( n - i Q ) Σ j = 0 N - 1 h ( n - j P ) + w ( n )
h ( n ) = Σ k = 0 P - 1 c k p ( n - k )
The wherein amplitude of A representation signal, bi(bi∈ ± 1}, i=0 ..., M-1) and ck(ck∈ ± 1}, k=0 ..., and P-1) distinguish representative information code sequence and spread spectrum code sequence, M represents the number of information code in NP sample of signal, and q (n) is rectangular function and meetsP (n) represents the convolution of emission filter, channel and receiving filter, and h (n) is spread spectrum code sequence ckWith the shock response of p (n), w (n) represents additive white Gaussian noise；
B. width Q and spreading code cycle P time according to the information code element estimated, calculates the information code element number comprised in the spreading code cycle This mathematical symbolism rounds up, then in a long code spreading period, information code element is up to β trip point, constructs Hopping Pattern matrix
Wherein, Hk(k=0 ..., β) represent have the Hopping Pattern matrix that k trip point is corresponding；
C. long code baseband signal of the band received being made an uproar carries out segmentation by cycle P, obtains the vectorial y that N number of length is Pl(l=0 ..., N-1), wherein
Wherein,Represent the information symbol sequence pressing spreading rate sampling；
D. calculate?In certainly exist group hopping pattern and a blThe Hopping Pattern of middle information code is identical, namely It is the matrix of a Γ × P, thenCan be expressed as
s.t.||bl(1:P) | |2=P
| b l ( i ) | = 1 , ∀ i ∈ { 0 , 1 , ... P - 1 }
E. basisCalculate covariance matrixRightCarry out principal component decomposition, obtain characteristic of correspondence vector wmax, thus obtaining the spread spectrum code sequence estimated
c ^ = s i g n ( w m a x )
Wherein sign () represents sign function.
2. eliminate the long code DSSS blind symbol estimation method of information code saltus step according to claim 1, it is characterized in that: in described step a, blind estimate long code spread spectrum DSSS signal period P adopts Second spectrum, correlated fluctuations spectrometry, Cepstrum Method, circulation spectrometry or auto-correlation calculus of finite differences.
3. eliminate the long code DSSS blind symbol estimation method of information code saltus step according to claim 1, it is characterised in that: in described step b, Hopping Pattern matrix neutron matrix HkA jump position is represented with 1 to-1 or-1 to 1, k=0 represents does not have trip point, corresponding is length is complete 1 row vector of P, k=1 represents only one of which trip point, during one trip point can there is the position in P chip between the adjacent chip in any front and back in jump position, P-1 row vector is had under worst case, by that analogy, so that it is determined that whole information code saltus step matrix
4. eliminate the long code DSSS blind symbol estimation method of information code saltus step according to claim 3, it is characterized in that, in described step b, Hopping Pattern matrix can adopt the matrix that the Hopping Pattern of the maximum several trip points of jumping probability is constituted to carry out approximate representation, namely can use information code saltus step matrixSubset be similar to, thus reducing the dimension of matrix.
5. eliminate the long code DSSS blind symbol estimation method of information code saltus step according to claim 1, it is characterised in that in described step d, operatorRepresenting matrixIn every a line in element and ylCorresponding element in vector carries out point multiplication operation.
6. eliminating the long code DSSS blind symbol estimation method of information code saltus step according to claim 1, it is characterised in that in described step e, principal component decomposition adopts singular value decomposition or Eigenvalues Decomposition to realize.
CN201610292502.5A 2016-05-05 2016-05-05 Eliminate the long code DSSS blind symbol estimation method of information code jump Expired - Fee Related CN105812300B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610292502.5A CN105812300B (en) 2016-05-05 2016-05-05 Eliminate the long code DSSS blind symbol estimation method of information code jump

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610292502.5A CN105812300B (en) 2016-05-05 2016-05-05 Eliminate the long code DSSS blind symbol estimation method of information code jump

Publications (2)

Publication Number Publication Date
CN105812300A true CN105812300A (en) 2016-07-27
CN105812300B CN105812300B (en) 2019-01-11

Family

ID=56456284

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610292502.5A Expired - Fee Related CN105812300B (en) 2016-05-05 2016-05-05 Eliminate the long code DSSS blind symbol estimation method of information code jump

Country Status (1)

Country Link
CN (1) CN105812300B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107682041A (en) * 2017-10-19 2018-02-09 杭州电子科技大学 A kind of multiple antennas LC DS CDMA signal spread-spectrum code blind estimating methods
CN112702080A (en) * 2020-12-16 2021-04-23 中国人民解放军国防科技大学 Direct sequence spread spectrum signal and pseudo code estimation method based on K-means algorithm
CN115940992A (en) * 2022-11-16 2023-04-07 中国人民解放军战略支援部队航天工程大学 BL-DSSS signal code tracking method based on frequency domain subspace principle

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006082546A1 (en) * 2005-02-05 2006-08-10 Southeast University Method and device for channel estimation in cdma communication system
CN101237250A (en) * 2008-03-03 2008-08-06 黄知涛 Frequency spreading wave blind estimation method based on odd value analysis
CN103414670A (en) * 2013-08-21 2013-11-27 电子科技大学 Long code DSSS signal blind dispreading method based on semi-definite programming
CN105553506A (en) * 2015-12-15 2016-05-04 中国电子科技集团公司第二十九研究所 Fast acquisition method and device of long code spread spectrum signal

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006082546A1 (en) * 2005-02-05 2006-08-10 Southeast University Method and device for channel estimation in cdma communication system
CN101237250A (en) * 2008-03-03 2008-08-06 黄知涛 Frequency spreading wave blind estimation method based on odd value analysis
CN103414670A (en) * 2013-08-21 2013-11-27 电子科技大学 Long code DSSS signal blind dispreading method based on semi-definite programming
CN105553506A (en) * 2015-12-15 2016-05-04 中国电子科技集团公司第二十九研究所 Fast acquisition method and device of long code spread spectrum signal

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
H.G. ZHANG,ET.AL: "Estimating spreading waveform of long-code direct sequence spread spectrum signals at a low signal to noise ratio", 《IET SIGNAL PROCESSING》 *
P.-Y. QUI,ET.AL: "Improved blind spreading sequence estimation algorithm for direct sequence spread spectrum signals", 《IET SIGNAL PROCESSING》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107682041A (en) * 2017-10-19 2018-02-09 杭州电子科技大学 A kind of multiple antennas LC DS CDMA signal spread-spectrum code blind estimating methods
CN107682041B (en) * 2017-10-19 2019-12-10 杭州电子科技大学 Multi-antenna LC-DS-CDMA signal spreading code blind estimation method
CN112702080A (en) * 2020-12-16 2021-04-23 中国人民解放军国防科技大学 Direct sequence spread spectrum signal and pseudo code estimation method based on K-means algorithm
CN115940992A (en) * 2022-11-16 2023-04-07 中国人民解放军战略支援部队航天工程大学 BL-DSSS signal code tracking method based on frequency domain subspace principle
CN115940992B (en) * 2022-11-16 2023-10-03 中国人民解放军战略支援部队航天工程大学 BL-DSSS signal code tracking method based on frequency domain subspace principle

Also Published As

Publication number Publication date
CN105812300B (en) 2019-01-11

Similar Documents

Publication Publication Date Title
CN105791184B (en) Aperiodic long code direct sequence signal frequency expansion sequence blind estimating method based on similarity
Kaddoum et al. Theoretical performance for asynchronous multi-user chaos-based communication systems on fading channels
US9467201B2 (en) Transmission signal generating/detecting method using code sequences, communication system using the same and measurement system using the same
CN104168233A (en) DSSS/UQPSK signal pseudo code sequence estimation method based on characteristic decomposition and Messay algorithm
CN105812300A (en) Long code DSSS signal blind estimation method for eliminating information code hopping
Peña et al. Implementation of Code Shift Keying signalling technique in GALILEO E1 signal
CN103490860A (en) Iterative demodulating and decoding method for high-performance shortwave orthogonal spectrum spreading
CN111953380B (en) Non-periodic long code direct sequence spread spectrum signal time delay estimation method and system based on norm fitting
CN104038249A (en) Method of estimating pseudorandom code of cycle long code direct sequence spread spectrum signals
EP3748897B1 (en) Quantum chaotic wave packet digital signal generating method
Vlok et al. Non-cooperative detection of weak spread-spectrum signals in additive white Gaussian noise
CN102035770A (en) Method for estimating channel by means of correlation
CN105245247A (en) Adaptive threshold controller and control method, direct sequence spread spectrum signal detection method and circuit
EP3258609B1 (en) Clear channel assessment
CN109951406B (en) Blind estimation method for number of users and scrambling codes of real-time acquisition signals of Unicom asynchronous WCDMA (wideband code division multiple Access)
Michaels et al. Quantization effects in digital chaotic communication systems
Sha et al. Blind spreading sequence estimation based on hill-climbing algorithm
Qiu et al. Blind classification of the short-code and the long-code direct sequence spread spectrum signals
Sheng et al. An improved power spectrum reprocessing method for DS-SS signal on spreading code period estimation
CN102946287A (en) Error code performance evaluating method of compressed domain direct spread receiver
Zhao et al. Blind Estimation of PN Codes in Multi-user LSC-DSSS Signals.
EP1428338A2 (en) Method and apparatus for interference signal code power and noise variance estimation
CN113411177B (en) Signal type detection method, device, equipment and storage medium
RU126541U1 (en) COMMUNICATION SYSTEM USING STOCHASTIC MULTI-FREQUENCY BROADBAND CODED RADIO SIGNALS
RU2669507C1 (en) Method of determination of optimal part of frequency band affected by intentional interference in communication systems with broadband signals

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20190111

CF01 Termination of patent right due to non-payment of annual fee