阅读说明：本技术 一种实现信号高误码率下的编码识别方法 (Code identification method for realizing high error rate of signal ) 是由 姚慰 杜健 王志 龚珊 耿世磊 蒋天立 梁京生 于 2021-04-16 设计创作，主要内容包括：本发明公开一种实现信号高误码率下的编码识别方法,包括步骤：对输入的信号利用同步码集合对解调码流实现同步码搜索,若搜索成功,则对分组码TPC码或LDPC码进行识别；若搜索失败,则对序列码、Viterbi码或TCM码进行识别；在步骤S10中相应码下识别成功后,对该码进行相应的译码；所有译码完成后,进行扰码识别。本发明能够使编码增益得到充分利用,能够实现整个信道编码全过程的识别,实现信号高误码率下的编码识别。(The invention discloses a coding identification method for realizing high signal error rate, which comprises the following steps: the method comprises the steps that synchronous code searching is achieved on a demodulation code stream of an input signal through a synchronous code set, and if the searching is successful, a TPC code or an LDPC code of a block code is identified; if the search fails, identifying a sequence code, a Viterbi code or a TCM code; after the identification is successful under the corresponding code in step S10, the code is decoded correspondingly; and after all decoding is finished, carrying out scrambling code identification. The invention can make full use of coding gain, realize the identification of the whole channel coding process and realize the coding identification under the high error rate of signals.)

1. A coding identification method for realizing high bit error rate of signals is characterized by comprising the following steps:

s10, using synchronous code set to realize synchronous code search for demodulation code stream for input signal, if search is successful, identifying TPC code or LDPC code of grouped code; if the search fails, identifying a sequence code, a Viterbi code or a TCM code;

s20, after the identification is successful under the corresponding code in the step S10, the code is decoded correspondingly;

and S30, after all decoding is finished, carrying out scrambling code identification.

2. The method as claimed in claim 1, wherein the synchronization code search comprises the steps of: setting an error code threshold, and sequentially searching a synchronous head by using synchronous codes in a synchronous code set; if the error code threshold is exceeded, the synchronous code is considered to be successfully searched, and the search is finished; otherwise, the search is continued until the traversal of the whole synchronous code set is completed and the search is still unsuccessful, and the synchronous code search is regarded as failed.

3. The method as claimed in claim 1, wherein the TPC code identification procedure comprises the following steps: respectively checking row codes and column codes of the TPC, and if the passing rate exceeds a threshold, judging that the verification is successful; and decoding after successful verification, and if the decoding is successful, considering that the encoding is correct and entering scrambling code identification.

4. The method for identifying codes under high bit error rate of signals according to claim 1, wherein the LDPC code identification process comprises the steps of: the LDPC codes are subjected to trial decoding, if the trial decoding is successful, the coding identification is correct, and if the trial decoding is failed, the coding identification is completed through coding structure analysis, and then the decoding is carried out; and after the decoding is successful, checking the BCH code, if the decoding is successful, entering scrambling code identification after the decoding is performed again, and if not, directly entering the scrambling code identification.

5. The method as claimed in claim 4, wherein the code structure analysis comprises the steps of:

step 1: the received M code vectors are arranged in an M × n matrix by row arrangement:

；

step 2: performing row transformation on C to obtain a matrix of a system formAnd expressed in decomposed form:

；

wherein the content of the first and second substances,a rank of C, i.e., the number of received linearly independent codewords; p isA matrix;to representAn identity matrix of order;is a sub-matrixEach column in a matrixA set of middle column labels;

and step 3: using matricesThereby constructing a matrix；To representIdentity matrix in matrixThe set of column labels is,is a transpose of the P matrix,to representAn identity matrix of order;

and 4, step 4: when in useWhen the temperature of the water is higher than the set temperature,andgenerating a matrix and a check matrix for a pair of codes to be solved; when in useWhen the temperature of the water is higher than the set temperature,anda pair of generator matrix and check matrix which is not the code to be solved; in any case, the step 5 needs to be carried out for further solving;

and 5: by usingFind out all sparse check vectorsAll ofThe set of the LDPC codes forms a sparse check matrix of the LDPC codes to be identified.

6. The method as claimed in claim 5, wherein in step 5, the modified Canteaut-Chabaud algorithm is usedFind out all sparse check vectorsThe method comprises the following steps:

initialization: set of column labelsAnd a matrixWeight thresholdSpace, spaceSet of medium and small weight vectorsThe counter is set to zero;

step 51: adding 1 to the counter; randomly divide I into two subsetsAndrespectively compriseAndan element; will be provided withAndviewed as a matrixLine marked with numeralsSet, matrixIs divided intoAndtwo parts, each being assigned a line reference numberAndthe row composition of (2);

step 52: randomly selecting the number of elements asIs set L of column labels, satisfies；Representing a set of elements left after removing the elements of the set I in the matrix column label set S;

step 53: computingAll ofSum of lines vectorTaking its value on LIs recorded in a tablePerforming the following steps; computingAll ofSum of lines vectorTaking its value on LIs recorded in a tablePerforming the following steps;

step 54: according to the tableAndexamine all the satisfactionIs/are as followsIn combination with, if anyWt denotes the Hamming weight of the vector, w is the weight threshold, and h is the vectorAnda sum vector of, i.e.And then:

(a) order toThe counter is set to zero;

(b) if it isThen give an orderThen order；

Step 55: if the counter value reaches a positive integer T, namely a new small weight vector cannot be found in T iterations, the algorithm is ended, and when the algorithm is ended, all the small weight vectors found out are stored in the setThe LDPC code is regarded as a sparse check vector of the LDPC code to be identified; if the value is less than T, then randomly selectingAndset of notesAnd through line conversion willIntoLet us orderAnd isAnd returns to step 51.

7. The method of claim 1, wherein the step S10 of identifying the sequence code, the Viterbi code or the TCM code comprises the steps of: firstly, trial decoding is carried out on a sequence code, a Viterbi code or a TCM code, and coding identification is carried out after the trial decoding is successful;

in step S30, after the decoding of the sequence code, the Viterbi code, or the TCM code is successful, the RS synchronization code is first searched, if the decoding is successful, the decoding is performed again, and then the scrambling code identification is performed, if not, the scrambling code identification is directly performed.

8. The method of claim 7, wherein the sequence code check comprises: verifying the data, counting the verification passing rate, and if the verification passing rate exceeds a threshold, judging that the verification is successful;

the Viterbi code trial translation: and (3) performing trial decoding on the data, re-encoding the decoding result, comparing the decoding result with the data before decoding, solving the error rate, and if the error rate is lower than a threshold, considering that the verification is successful, otherwise, failing to verify.

9. The method as claimed in claim 7, wherein the identification process of the TCM code comprises the steps of:

performing timing demodulation on an input signal;

carrying out modulation discrimination on the demodulated signal, and extracting a constellation diagram;

and establishing a multi-stage state transition distribution system diagram of the constellation diagram, and judging whether the signal is a TCM signal according to the multi-stage state transition distribution system diagram.

10. The method of claim 1, wherein the scrambling code identification is performed by: the method comprises the following steps of carrying out self-synchronization and pseudo-random identification, and sequentially carrying out trial identification on the two modes until an identification result is obtained;

for self-synchronizing scrambling codes, carrying out descrambling on data according to an assumed polynomial, counting 0/1 unbalance degrees of result data, and if the unbalance degrees are greater than a threshold, determining that the scrambling codes are contained;

for pseudo-random scrambling code, the length of the former block code, i.e. the scrambling period, is set a polynomial, different initial states are set to descramble the data, 0/1 degrees of unbalance of the result data are counted and a decision is made.

Technical Field

The invention belongs to the technical field of signal processing, and particularly relates to a code identification method for realizing high error rate of signals.

Background

At present, the encoding and identifying technology of mainstream signals is generally realized by identifying and judging certificates under the condition of no error codes, but in an actual satellite receiving system, a higher error rate generally exists after demodulation, and meanwhile, a receiving object generally has links of scrambling codes, cascade codes, constellation point mapping, phase ambiguity and the like after demodulation, so that the purpose of encoding and identifying can be realized only by peeling off the scrambling codes, the difference codes, the outer codes, the inner codes, the constellation point mapping and the phase ambiguity layer by layer. The current mainstream signal coding identification technology cannot complete the identification of codes and restore decoding information under a certain error rate condition.

Disclosure of Invention

In order to solve the problems, the invention provides a coding identification method for realizing the high error rate of signals, which can fully utilize coding gain, realize the identification of the whole channel coding process and realize the coding identification of the high error rate of signals.

In order to achieve the purpose, the invention adopts the technical scheme that: a coding identification method for realizing high bit error rate of signals comprises the following steps:

s10, the input signal utilizes the synchronous code set to realize synchronous code search for the demodulation code stream, if the search is successful, the TPC code or LDPC code of the block code is identified; if the search fails, identifying a sequence code, a Viterbi code or a TCM code;

s20, after the identification is successful under the corresponding code in the step S10, the code is decoded correspondingly;

and S30, after all decoding is finished, carrying out scrambling code identification.

Further, the sync header search includes the steps of: setting an error code threshold, and sequentially searching a synchronous head by using synchronous codes in a synchronous code set; if the error code threshold is exceeded, the synchronous code is considered to be successfully searched, and the search is finished; otherwise, the search is continued until the traversal of the whole synchronous code set is completed and the search is still unsuccessful, and the synchronous code search is regarded as failed.

Further, the TPC code identification and processing procedure includes the steps of: respectively checking row codes and column codes of the TPC, and if the passing rate exceeds a threshold, judging that the verification is successful; and decoding after successful verification, and if the decoding is successful, considering that the encoding is correct and entering scrambling code identification.

Further, the LDPC code identification and processing procedure includes the steps of: the LDPC codes are subjected to trial decoding, if the trial decoding is successful, the coding identification is correct, and if the trial decoding is failed, the coding identification is completed through coding structure analysis, and then the decoding is carried out; and after the decoding is successful, checking the BCH code, if the decoding is successful, performing decoding again, and then entering scrambling code identification, otherwise, directly entering scrambling code identification. The error control performance of the system is improved, and the code identification under high bit error rate is realized.

Further, the coding structure analysis comprises the steps of:

step 1: the received M code vectors are arranged in an M × n matrix by row arrangement:

；

step 2: performing row transformation on C to obtain a matrix of a system formAnd expressed in decomposed form:

；

wherein the content of the first and second substances,a rank of C, i.e., the number of received linearly independent codewords; p isA matrix;to representAn identity matrix of order;is a sub-matrixEach column in a matrixA set of middle column labels;

and step 3: using matricesThereby constructing a matrix；To representIdentity matrix in matrixThe set of column labels is,is a transpose of the P matrix,to representAn identity matrix of order;

and 4, step 4: when in useWhen the temperature of the water is higher than the set temperature,andgenerating a matrix and a check matrix for a pair of codes to be solved; when in useWhen the temperature of the water is higher than the set temperature,anda pair of generator matrix and check matrix which is not the code to be solved; in any case, the step 5 needs to be carried out for further solving;

and 5: by usingFind out all sparse check vectorsAll ofThe set of the LDPC codes forms a sparse check matrix of the LDPC codes to be identified.

Further, in step 5, a modified Canteaut-Chabaud based algorithm is utilizedFind out all sparse check vectorsThe method comprises the following steps:

initialization: set of column labelsAnd a matrixWeight thresholdSpace, spaceSet of medium and small weight vectorsThe counter is set to zero;

step 51: adding 1 to the counter; randomly divide I into two subsetsAndrespectively compriseAndan element; will be provided withAndviewed as a matrixSets of row labels, matricesIs divided intoAndtwo parts, each being assigned a line reference numberAndthe row composition of (2);

step 52: randomly selecting the number of elements asIs set L of column labels, satisfies；Representing a set of elements left after removing the elements of the set I in the matrix column label set S;

step 53: computingAll ofSum of lines vectorTaking its value on LIs recorded in a tablePerforming the following steps; computingAll ofSum of lines vectorTaking its value on LIs recorded in a tablePerforming the following steps;

step 54: according to the tableAndexamine all the satisfactionIs/are as followsIn combination with, if anyWt denotes the Hamming weight of the vector, w is the weight threshold, and h is the vectorAnda sum vector of, i.e.And then:

(a) order toThe counter is set to zero;

(b) if it isThen give an orderThen order；

Step 55: if the counter value reaches a positive integer T, namely a new small weight vector cannot be found in T iterations, the algorithm is ended, and when the algorithm is ended, all the small weight vectors found out are stored in the setThe LDPC code is regarded as a sparse check vector of the LDPC code to be identified; if the value is less than T, then randomly selectingAndset of notesAnd through line conversion willIntoLet us orderAnd isAnd returns to step 51.

Further, in step S10, the identifying the sequence code, the Viterbi code or the TCM code includes: firstly, trial decoding is carried out on a sequence code, a Viterbi code or a TCM code, and coding identification is carried out after the trial decoding is successful;

in step S30, after the decoding of the sequence code, the Viterbi code, or the TCM code is successful, the RS synchronization code is first searched, if successful, the decoding is performed again, and then the scrambling code identification is performed, if not, the scrambling code identification is directly performed. The error control performance of the system is improved, and the code identification under high bit error rate is realized.

Further, the sequence code check: verifying the data, counting the verification passing rate, and if the verification passing rate exceeds a threshold, judging that the verification is successful;

the Viterbi code trial translation: and (3) performing trial decoding on the data, re-encoding the decoding result, comparing the decoding result with the data before decoding, solving the error rate, and if the error rate is lower than a threshold, considering that the verification is successful, otherwise, failing to verify.

Further, the identification process of the TCM code includes the steps of:

performing timing demodulation on an input signal;

carrying out modulation discrimination on the demodulated signal, and extracting a constellation diagram;

and establishing a multi-stage state transition distribution system diagram of the constellation diagram, and judging whether the signal is a TCM signal according to the multi-stage state transition distribution system diagram.

The operation method is adopted to carry out template matching, and when the template matching fails, the identification is carried out so as to improve the success rate of TCM identification.

Further, the scrambling code identifies: the method comprises the following steps of carrying out self-synchronization and pseudo-random identification, and sequentially carrying out trial identification on the two modes until an identification result is obtained;

for self-synchronizing scrambling codes, carrying out descrambling on data according to an assumed polynomial, counting 0/1 unbalance degrees of result data, and if the unbalance degrees are greater than a threshold, determining that the scrambling codes are contained;

for pseudo-random scrambling code, the length of the former block code, i.e. the scrambling period, is set a polynomial, different initial states are set to descramble the data, 0/1 degrees of unbalance of the result data are counted and a decision is made.

The beneficial effects of the technical scheme are as follows:

the invention realizes synchronous code search for the demodulation code stream by using the synchronous code set, and uniformly performs scrambling code identification after respectively performing identification, matching decoding and other operations on the TPC code, the LDPC code, the sequence code, the Viterbi code or the TCM code in a distributed manner, so that the coding gain can be fully utilized, and the identification of the whole channel coding process can be realized. The invention carries out matching identification on TPC codes, LDPC codes, sequence codes, Viterbi codes, TCM and the like respectively, and comprises a check matching method and a trial decoding matching method, which have strong fault-tolerant performance and can realize code identification under high error rate.

The invention fully considers the existence of possible cascade codes, including cascade of LDPC codes and BCH codes, cascade of sequence codes and RS codes, and improves the accuracy of code identification under high bit error rate.

The invention also integrates an identification method based on coding structure analysis aiming at the LDPC code, can realize the identification of the LDPC code when the template matching fails or the template information is insufficient, and improves the accuracy of the coding identification under high error rate.

Drawings

Fig. 1 is a schematic flow chart of a method for identifying codes under a high signal error rate according to the present invention.

FIG. 2 is a diagram illustrating a state transition profile of a stage of TCM signals according to an embodiment of the present invention.

FIG. 3 is a diagram illustrating two-stage state transition profiles of TCM signals according to an embodiment of the present invention.

FIG. 4 is a diagram illustrating three-level state transition profiles of TCM signals according to an embodiment of the present invention.

FIG. 5 is a diagram illustrating a one-stage state transition distribution of a non-TCM signal according to an embodiment of the present invention.

FIG. 6 is a diagram of a two-level state transition profile of a non-TCM signal according to an embodiment of the present invention.

FIG. 7 is a three-level state transition distribution diagram of a non-TCM signal according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described with reference to the accompanying drawings.

In this embodiment, referring to fig. 1, the present invention provides a method for identifying codes under a high signal error rate, including the steps of:

s10, the input signal utilizes the synchronous code set to realize synchronous code search for the demodulation code stream, if the search is successful, the TPC code or LDPC code of the block code is identified; if the search fails, identifying a sequence code, a Viterbi code or a TCM code;

s20, after the identification is successful under the corresponding code in the step S10, the code is decoded correspondingly;

and S30, after all decoding is finished, carrying out scrambling code identification.

As an optimization scheme of the above embodiment, the synchronization header search includes the steps of: setting an error code threshold, and sequentially searching a synchronous head by using synchronous codes in a synchronous code set; if the error code threshold is exceeded, the synchronous code is considered to be successfully searched, and the search is finished; otherwise, the search is continued until the traversal of the whole synchronous code set is completed and the search is still unsuccessful, and the synchronous code search is regarded as failed.

As an optimization scheme of the above embodiment, the TPC code identifying and processing procedure includes the steps of: respectively checking row codes and column codes of the TPC, and if the passing rate exceeds a threshold, judging that the verification is successful; and decoding after successful verification, and if the decoding is successful, considering that the encoding is correct and entering scrambling code identification.

As an optimization scheme of the above embodiment, the LDPC code identification and processing procedure includes the steps of: the LDPC codes are subjected to trial decoding, if the trial decoding is successful, the coding identification is correct, and if the trial decoding is failed, the coding identification is completed through coding structure analysis, and then the decoding is carried out; and after the decoding is successful, checking the BCH code, if the decoding is successful, performing decoding again, and then entering scrambling code identification, otherwise, directly entering scrambling code identification. The error control performance of the system is improved, and the code identification under high bit error rate is realized.

Wherein the coding structure analysis comprises the steps of:

step 1: the received M code vectors are arranged in an M × n matrix by row arrangement:

；

step 2: performing row transformation on C to obtain a matrix of a system formAnd is shown in decomposed formFormula (II):

；

wherein the content of the first and second substances,a rank of C, i.e., the number of received linearly independent codewords; p isA matrix;to representAn identity matrix of order;is a sub-matrixEach column in a matrixA set of middle column labels;

and step 3: using matricesThereby constructing a matrix；To representIdentity matrix in matrixThe set of column labels is,is a transpose of the P matrix,to representAn identity matrix of order;

and 4, step 4: when in useWhen the temperature of the water is higher than the set temperature,andgenerating a matrix and a check matrix for a pair of codes to be solved; when in useWhen the temperature of the water is higher than the set temperature,anda pair of generator matrix and check matrix which is not the code to be solved; in any case, the step 5 needs to be carried out for further solving;

and 5: by usingFind out all sparse check vectorsAll ofOf the set constituting the LDPC code to be identifiedAnd (5) sparse check matrix.

In step 5, the improved Canteaut-Chabaud based algorithm is utilizedFind out all sparse check vectorsThe method comprises the following steps:

initialization: set of column labelsAnd a matrixWeight thresholdSpace, spaceSet of medium and small weight vectorsThe counter is set to zero;

step 51: adding 1 to the counter; randomly divide I into two subsetsAndrespectively compriseAndan element; will be provided withAndviewed as a matrixSets of row labels, matricesIs divided intoAndtwo parts, each being assigned a line reference numberAndthe row composition of (2);

step 52: randomly selecting the number of elements asIs set L of column labels, satisfies；Representing a set of elements left after removing the elements of the set I in the matrix column label set S;

step 53: computingAll ofSum of lines vectorTaking its value on LIs recorded in a tablePerforming the following steps; computingAll ofSum of lines vectorTaking its value on LIs recorded in a tablePerforming the following steps;

step 54: according to the tableAndexamine all the satisfactionIs/are as followsIn combination with, if anyWt denotes the Hamming weight of the vector, w is the weight threshold, and h is the vectorAnda sum vector of, i.e.And then:

(a) order toThe counter is set to zero;

(b) if it isThen give an orderThen order；

Step 55: if the counter value reaches a positive integer T, namely a new small weight vector cannot be found in T iterations, the algorithm is ended, and when the algorithm is ended, all the small weight vectors found out are stored in the setThe LDPC code is regarded as a sparse check vector of the LDPC code to be identified; if the value is less than T, then randomly selectingAndset of notesAnd through line conversion willIntoLet us orderAnd isAnd returns to step 51.

Comparing the method with the original Canteaut-Chabaud algorithm flow, the difference is that the storage of the sparse vector h and the updating of the parameter w are added in step 54, and the ending criterion in step 55 is changed (the counter does not count the total number of iterations any more). According to step 54, each time a vector h is found, if anyUpdate the threshold value w to. This is because the sum of the two sparse check vectors of weight wt (h) is still the check vector of the LDPC code, with a minimum value of weight of 2wt (h) -2 (assuming no ring of length 4 exists). The step 54 can avoid finding out such check vectors, and is also suitable for the requirements of irregular LDPC codes, and can find out all sparse check vectors whose weights are within a certain range. For some LDPC codes, there may be a ring of length 4, then the change in step 45 should be "ifThen give an order". In step 55, the meaning of the parameter T is: if no new low weight vector can be found in T consecutive iterations, the algorithm ends. When the algorithm is finished, all the found small weight vectors are stored in a setI.e. they are considered as sparse check vectors of the LDPC code to be identified.

Identifying sparse check vectors, i.e., spaces, of LDPC codes by the above methodMedium small weight vector. The original Canteaut-Chabaud algorithm needs to give the maximum weight w of a vector to be solved in advance, and the process is finished immediately when a small weight vector meeting the requirement is found out; but the maximum weight w is unknown and the small weight vectors that need to be found are r in total. Therefore, the original algorithm needs to be optimized to some extent: firstly, the value of w is gradually determined in the searching process, the determining process of the maximum weight w of the vector to be found is modified, under the condition that the maximum weight w is unknown and the number of small weight vectors to be found is r, the storage of a sparse vector h and the updating of a parameter w are increased, the condition that the sum of two sparse check vectors with the weight of wt (h) is still the check vector of the LDPC code is avoided being found, meanwhile, the method is also suitable for the requirement of the irregular LDPC code, and all sparse check vectors with the weight in a certain range can be found. Secondly, a new ending criterion is adopted, the original algorithm needs to give the maximum weight w of the vector to be solved in advance, the small weight vector meeting the requirement is found out and then immediately ended, and the algorithm is judged to be ended after the modified ending rule does not find a new small weight vector in the continuous T iterations. When the algorithm is finished, all the sparse check vectors of the LDPC code to be identified can be found out. The sparse check vector of the LDPC code is identified through the improved Canteaut-Chabaud algorithm, so that the identification accuracy of the sparse check vector can be improved, and the identification process is simplified.

As an optimization solution of the above embodiment, in step S10, the identifying the sequence code, the Viterbi code or the TCM code includes the steps of: firstly, trial decoding is carried out on a sequence code, a Viterbi code or a TCM code, and coding identification is carried out after the trial decoding is successful; in step S30, after the decoding of the sequence code, the Viterbi code, or the TCM code is successful, the RS synchronization code is first searched, if successful, the decoding is performed again, and then the scrambling code identification is performed, if not, the scrambling code identification is directly performed. The error control performance of the system is improved, and the code identification under high bit error rate is realized.

And the sequence code check: verifying the data, counting the verification passing rate, and if the verification passing rate exceeds a threshold, judging that the verification is successful;

the Viterbi code trial translation: and (3) performing trial decoding on the data, re-encoding the decoding result, comparing the decoding result with the data before decoding, solving the error rate, and if the error rate is lower than a threshold, considering that the verification is successful, otherwise, failing to verify.

The identification process of the TCM code comprises the following steps:

performing timing demodulation on an input signal;

carrying out modulation discrimination on the demodulated signal, and extracting a constellation diagram;

and establishing a multi-stage state transition distribution system diagram of the constellation diagram, and judging whether the signal is a TCM signal according to the multi-stage state transition distribution system diagram.

As shown in fig. 2 to fig. 7, the state transition profiles of TCM signals are clearly distinguished in three-level state transition that not all state transition paths are present, and the state transition profiles of non-TCM signals are very even because there is no coded information at symbol level, and by this feature, TCM signals can be identified.

The operation method is adopted to carry out template matching, and when the template matching fails, the identification is carried out so as to improve the success rate of TCM identification.

As an optimization scheme of the above embodiment, the scrambling code identifies: the method comprises the following steps of carrying out self-synchronization and pseudo-random identification, and sequentially carrying out trial identification on the two modes until an identification result is obtained;

for self-synchronizing scrambling codes, carrying out descrambling on data according to an assumed polynomial, counting 0/1 unbalance degrees of result data, and if the unbalance degrees are greater than a threshold, determining that the scrambling codes are contained;

for pseudo-random scrambling code, the length of the former block code, i.e. the scrambling period, is set a polynomial, different initial states are set to descramble the data, 0/1 degrees of unbalance of the result data are counted and a decision is made.

The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.