CN109495211A - A kind of channel coding and coding/decoding method - Google Patents
A kind of channel coding and coding/decoding method Download PDFInfo
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- H—ELECTRICITY
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Abstract
The present invention provides a kind of channel coding and coding/decoding methods, using the full probability coding based on probabilistic model, it added the debugging and error correction relation of symbol in coding, it realizes that debugging and error correction are androgynous, error correction or error detecing capability can be effectively improved, closer to entropy theory value, awgn channel is simulated from experiment is surveyed, start to decode in the 27th byte, less than 3 bit of mistake occur simultaneously in 27 bytes, is more than or equal to 3 bit situation energy error detections；In addition, method provided by the invention belongs to linear error correction, it is no-delay；Error correction rate and to adapt to the bit error rate high, in the case of the bit error rate is less than 0.00001, can disposable 100% correction decoding；Code rate bottom, conventional method needs 1/2 code rate, and this method only needs 1/1.5849625 code rate；Only need to retransmit a bit more than 100 for what can not be corrected, without retransmitting entire data packet, coding and decoding speed is faster.
Description
Technical field
The present invention relates to data transfer communications technical fields, more particularly to a kind of channel coding and coding/decoding method.
Background technique
Referring to Fig. 3, one classical digital carrier system generally includes, information source, letter according to the information theory of Shannon
Source encoder, channel encoder, modulator, channel, demodulator, channel decoder, source decoder, the stay of two nights.
Due to the presence of interference and the randomness of information code element, make receiving end can not predict can not also identify wherein have it is error-free
Mistake, while in the prior art, the coding method based on convolutional code or algebraic method is generallyd use, but all presence of these methods are entangled
Wrong or poor error detecing capability problem.
Summary of the invention
In view of the above situation, on the one hand the present invention, which provides, provides a kind of channel coding method, entangled with solving the prior art
Wrong or poor error detecing capability problem.
A kind of channel coding method, comprising:
Step 1 pre-processes random binary sequence, and the symbol 0 in random binary sequence is made to become symbol 1,
0,1, and the symbol 1 in random binary sequence is made to become 0,1；
Step 2, parameter initialization set the probability of symbol 0The probability of symbol 1 Single order is quiet
State coefficientH is obtained according to probabilistic model expression formula0=p0=1, L0=0, wherein L0、H0、p0It is respectively general
Lower limit initial value, upper limit initial value, the siding-to-siding block length initial value in rate section；Obtain the length Len of random binary sequence；Setting
Cyclic variable i=1, it is i-th of symbol that wherein i, which is currently processed, encodes and completes as i=Len；Setting encodes all symbols
The subscript V=0 of probability interval afterwards；xiFor etc. i-th of symbol to be encoded；p1=p2=p3=0；
Step 3: if i-th of symbol is symbol 0, enter step 4；If i-th of symbol is symbol 1, enter step 5；
Step 4: 3 symbols 1,0,1 are encoded respectively, steps are as follows:
For coded identification 1,V=V+p1；
For coded identification 0, p2=rp (0) p1, V=V+0；
For coded identification 1, p3=rp (1) p2, V=V+p3；
Into step 6；
Step 5: by being encoded respectively to 2 symbols 0,1, steps are as follows:
For coded identification 0,V=V+0；
For coded identification 1, p2=rp (1) p1, V=V+p2；
Into step 6；
Step 6: cyclic variable i adds 1, i.e. i=i+1；If judging i≤Len, next symbol is encoded back to step 3；
If i > Len, terminate coding, exports V and Len.
Providing method uses the full probability coding based on probabilistic model according to the present invention, added symbol in coding
Debugging and error correction relation realize that debugging and error correction are androgynous, can effectively improve error correction or error detecing capability, closer entropy theory value,
Awgn channel is simulated from experiment is surveyed, starts to decode in the 27th byte, less than 3 bit of mistake occurs simultaneously in 27 bytes,
More than or equal to 3 bit situation energy error detections；In addition, method provided by the invention belongs to linear error correction, it is no-delay；Error correction rate and suitable
Answer the bit error rate high, in the case of the bit error rate is less than 0.00001, can disposable 100% correction decoding；Code rate bottom, conventional method
1/2 code rate is needed, and this method only needs 1/1.5849625 code rate；Only need to retransmit more than 100 ratio for what can not be corrected
Spy, without retransmitting entire data packet, coding and decoding speed is faster.
In addition, above-mentioned channel coding method according to the present invention, can also have the following additional technical features:
Further, in step 1, pretreatment is carried out to random binary sequence and is specifically included:
Increase by 1 symbol 1 behind each symbol 0, obtains sequence A；
Again to 1 symbol 0 is added behind each symbol 1 of sequence A, sequence B is obtained；
To sequence B step-by-step inverse, sequence C is obtained, i.e.,
Further, in step 1, pretreatment is carried out to random binary sequence and is specifically included:
It is practical successively to encode 1,0,1 three symbol if get symbol 0 from original string；If get symbol 1 from original string,
It is practical successively to encode 0,1 two symbols.
Further, the probabilistic model meets the following conditions:
Shrinkable or expansion a probabilistic model is constructed, moment t is definedn, n is natural number more than or equal to 1, symbol it is general
Rate is shunk or flare factor is ωn, and the probability of all symbols is defined in moment tnAccording to same coefficient ωnThe random mistake of variation
Journey is general process, and there are three types of elementary probability models for the general process tool: if any time tnThere is ωnWhen ≡ 1, it is defined as master pattern；
If there is 0 < ω in any timen≤ 1, and there are ωn< 1, then be defined as contracting model；If there is ω in any timen>=1, and exist
ωn> 1 is then defined as expansion model；
The fixation probability of symbol 0 and symbol 1 difference p (0) and p (1) in the random binary sequence are set, ifAnd the single order static coefficient r for expanding model meets:
If continuous 1 number in random sequenceThe distribution function for then expanding model can keep stochastic ordering columns
Rationality matter can be completely restored to random sequence；
The probability function and distribution function of the random binary sequence are as follows:
That is Hn(x1,x2,…,xn)=Ln(x1,x2,…,xn)+pn(x1,x2,…,xn), and have the Probability Region of lossless encoding/decoding
Between subordinate relation are as follows:
[Ln(x1,x2,…,xn),Hn(x1,x2,…,xn))
∈[Ln-1(x1,x2,…,xn-1),Hn-1(x1,x2,…,xn-1))∈…
∈[L1(x1),H1(x1))。
Further, it in the probabilistic model, satisfies the following conditional expression:
P ' (1)=rp (1)=1.
The present invention provide on the other hand a kind of channel decoding method is provided, with solve prior art error correction or error detecing capability compared with
The problem of difference.
A kind of channel decoding method, comprising:
Step 1: parameter initialization sets the probability of symbol 0The probability of symbol 1 Single order is quiet
State coefficientH is obtained according to probabilistic model expression formula0=p0=1, L0=0, wherein L0、H0、p0It is respectively general
Lower limit initial value, upper limit initial value, the siding-to-siding block length initial value in rate section；Obtain the length Len of random binary sequence；Setting
Cyclic variable i=1, it is i-th of symbol that wherein i, which is currently processed, encodes and completes as i=Len；Buffer Buff is set
[n], the n in [n] are buffer size, buffer counter lp=0；Temporary variable H=0 obtains V value；X is decoded symbol
Number；J is the jth position binary system of V value；
Step 2: i-th of symbol x is obtained according to probabilistic model expression formulaiPossible probability interval:
0 section of symbol are as follows:
1 section of symbol are as follows:
Into step 3；
Step 3: the affiliated section V is judged according to probabilistic model expression formula:
IfOrThen xi=0,
By xi=0 deposit buffer；
IfOrThen xi=1, it will
xi=1 deposit buffer；
Into step 4；
Step 4: error detection judges whether meet primitive character string in buffer, if satisfied, then determining that decoding is correct, enters
Step 6；If not satisfied, then determine to decode it is incorrect, into step 5 carry out error correction；
Step 5: current V is pressed into bit flipping from left to right, every overturning 1bit obtains new V, judges whether j is equal to V value
Binary length L return to step 2, and j=j+1 if j≤L；If j > L, output identification terminates decoding；
Step 6: judge whether occur following feature string in buffer from left to right: if substring for 101, output symbol 0；
If substring is 01, output symbol 1, and cyclic variable i adds 1, i.e. i=i+1, into step 7；
Step 7: judgement if i≤Len, returns to step 2 and carries out continuing to decode；If i > Len, decoding terminates.
In addition, above-mentioned channel decoding method according to the present invention, can also have the following additional technical features:
Further, in step 4, judge in the step of whether meeting primitive character string in buffer, including two criterions:
Criterion 1: the number of continuous symbol 1 cannot be greater than 2 in buffer binary string；
Criterion 2: the number of continuous symbol 0 cannot be greater than 1 in buffer binary string,
If meeting criterion 1 and criterion 2 simultaneously, determine that decoding is correct, into step 6；If at least a criterion is discontented
Foot, then determine to decode it is incorrect, into step 5 carry out error correction.
Further, the probabilistic model meets the following conditions:
Shrinkable or expansion a probabilistic model is constructed, moment t is definedn, n is natural number more than or equal to 1, symbol it is general
Rate is shunk or flare factor is ωn, and the probability of all symbols is defined in moment tnAccording to same coefficient ωnThe random mistake of variation
Journey is general process, and there are three types of elementary probability models for the general process tool: if any time tnThere is ωnWhen ≡ 1, it is defined as master pattern；
If there is 0 < ω in any timen≤ 1, and there are ωn< 1, then be defined as contracting model；If there is ω in any timen>=1, and exist
ωn> 1 is then defined as expansion model；
The fixation probability of symbol 0 and symbol 1 difference p (0) and p (1) in the random binary sequence are set, ifAnd the single order static coefficient r for expanding model meets:
If continuous 1 number in random sequenceThe distribution function for then expanding model can keep stochastic ordering columns
Rationality matter can be completely restored to random sequence；
The probability function and distribution function of the random binary sequence are as follows:
That is Hn(x1,x2,…,xn)=Ln(x1,x2,…,xn)+pn(x1,x2,…,xn), and have the Probability Region of lossless encoding/decoding
Between subordinate relation are as follows:
[Ln(x1,x2,…,xn),Hn(x1,x2,…,xn))
∈[Ln-1(x1,x2,…,xn-1),Hn-1(x1,x2,…,xn-1))∈…
∈[L1(x1),H1(x1))。
Further, in step 5, V value is finite length or indefinite length by bit flipping.
Additional aspect and advantage of the invention will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Fig. 1 is the flow chart of the channel coding method of the embodiment of the present invention；
Fig. 2 is the flow chart of the channel decoding method of the embodiment of the present invention；
Fig. 3 is the structural schematic diagram of traditional digital carrier system.
Specific embodiment
To facilitate the understanding of the present invention, a more comprehensive description of the invention is given in the following sections with reference to the relevant attached drawings.In attached drawing
Give several embodiments of the invention.But the invention can be realized in many different forms, however it is not limited to this paper institute
The embodiment of description.On the contrary, purpose of providing these embodiments is make it is more thorough and comprehensive to the disclosure.
Unless otherwise defined, all technical and scientific terms used herein and belong to technical field of the invention
The normally understood meaning of technical staff is identical.Term as used herein in the specification of the present invention is intended merely to description tool
The purpose of the embodiment of body, it is not intended that in the limitation present invention.Term " and or " used herein includes one or more phases
Any and all combinations of the listed item of pass.
Channel coding method provided in this embodiment and corresponding channel decoding method are established with interference
On the basis of probabilistic model, general process is change procedure of the probability of symbol in timing, and the probability of symbol exists in random process
It is then master pattern not by external disturbance in timing.Master pattern is a kind of ideal model, if the probability of symbol in timing by
External disturbance, then there are three types of basic scenarios: standard, and making probability, there is no variations；It shrinks, probability is made to become smaller；Expansion, makes probability
Become larger.Based on this, probabilistic model meets the following conditions:
Shrinkable or expansion a probabilistic model is constructed first, defines moment tn, n is the natural number more than or equal to 1, symbol
Probability Contract or flare factor be ωn, and the probability of all symbols is defined in moment tnAccording to same coefficient ωnVariation with
Machine process is general process, and there are three types of elementary probability models for the general process tool: if any time tnThere is ωnWhen ≡ 1, it is defined as standard
Model；If there is 0 < ω in any timen≤ 1, and there are ωn< 1, then be defined as contracting model；If there is ω in any timen>=1, and
There are ωn> 1 is then defined as expansion model；
The fixation probability of symbol 0 and symbol 1 difference p (0) and p (1) in the random binary sequence are set, ifAnd the single order static coefficient r for expanding model meets:
If continuous 1 number in random sequenceThe distribution function for then expanding model can keep stochastic ordering columns
Rationality matter can be completely restored to random sequence；
The probability function and distribution function of the random binary sequence are as follows:
That is Hn(x1,x2,…,xn)=Ln(x1,x2,…,xn)+pn(x1,x2,…,xn), and have the Probability Region of lossless encoding/decoding
Between subordinate relation are as follows:
In the effective range of interference effect, therefore the symbol that distribution function can correctly restore each moment is based on
Above-mentioned distribution function and subordinate relation construct lossless decoding method.
Referring to Fig. 1, the channel coding method of an embodiment mainly comprises the steps that
Step 1 pre-processes random binary sequence, and the symbol 0 in random binary sequence is made to become symbol 1,
0,1, and the symbol 1 in random binary sequence is made to become 0,1；
Wherein, it is illustrated by taking the binary sequence of certain completely random to be encoded as an example, the completely random to be encoded
Binary sequence specifically:
1100101000111101011111110000001010110111110
When it is implemented, can be pre-processed using following two mode to random binary sequence:
The first: increasing by 1 symbol 1 behind each symbol 0, obtain sequence A；
A=110101101101010111110110111111110101010101011011011101 1111101
Again to 1 symbol 0 is added behind each symbol 1 of sequence A, sequence B is obtained；
B=101001001010010100100100101010101001010010101010101010 10010010010
010010010100101001010100101010101010010
To sequence B step-by-step inverse, sequence C is obtained, i.e.,
C=010110110101101011011011010101010110101101010101010101 01101101101
101101101011010110101011010101010101101。
Second: practical successively to encode 1,0,1 three symbol if get symbol 0 from original string；If getting symbol from original string
When number 1, practical successively to encode 0,1 two symbols, after processing, obtained result is identical as the first, second of pretreatment mode
Compared to the first, it can be realized optimization and accelerate.
Step 2, parameter initialization set the probability of symbol 0The probability of symbol 1 Single order is quiet
State coefficientAccording to the H in probabilistic model expression formulan(x1,x2,…,xn), Ln(x1,x2,…,xn) and pn(x1,
x2,…,xn) obtain H0=p0=1, L0=0, wherein L0、H0、p0Respectively the lower limit initial value of probability interval, upper limit initial value,
Siding-to-siding block length initial value；Obtaining the length Len of random binary sequence, (Len=43 in the present embodiment, Len is to be compressed here
The length of string is not the length of sequence C)；Cyclic variable i=1 is set, it is i-th of symbol that wherein i, which is currently processed, works as i=
It encodes and completes when Len；Setting encode the probability interval after all symbols subscript V=0 (wherein, in the present embodiment, V=L43
(x1,x2,…,x43))；xiFor etc. i-th of symbol to be encoded；p1=p2=p3=0；
Step 3: if i-th of symbol is symbol 0, enter step 4；If i-th of symbol is symbol 1, enter step 5；
Step 4: 3 symbols 1,0,1 are encoded respectively, steps are as follows:
For coded identification 1,V=V+p1；
For coded identification 0, p2=rp (0) p1, V=V+0；
For coded identification 1, p3=rp (1) p2, V=V+p3；
Into step 6；
Step 5: by being encoded respectively to 2 symbols 0,1, steps are as follows:
For coded identification 0,V=V+0；
For coded identification 1, p2=rp (1) p1, V=V+p2；
Into step 6；
Step 6: cyclic variable i adds 1, i.e. i=i+1；If judging i≤Len, next symbol is encoded back to step 3；
If i > Len, terminate coding, exports V and Len.
The principle of above-mentioned channel coding method is illustrated below:
Due to needing to pre-process to binary sequence, then addition supervision member, sets binary system sequence to be transmitted first
Column are completely randoms, and the number of the number equal symbol 1 of symbol 0, i.e.,According to the above method,
The preprocess method of feature random sequence is as follows:
To 1 symbol 1 is increased behind each symbol 0, sequence A is obtained；
Again to 1 symbol 0 is added behind each symbol 1 of sequence A, sequence B is obtained；
Then it allows sequence B step-by-step inverse again, obtains sequence C, i.e.,
If original random sequence total length is Len, by above three step, the number of symbol 0 in sequence C are as follows: Len, symbol
Number 1 number are as follows:Total length isThe probability of symbol 0 and symbol 1 at this time are as follows:
It is then fed into encoder to be encoded, be had according to comentropy formula:
It is obvious that the sequence length after coding is 2.42737639 times of original length, 1/2 code rate is not accomplished.In analysis
Probabilistic model is stated, k is positive integer, then distributes the probability of symbol 0 are as follows:Distribute the probability of symbol 1 are as follows:At this timeSo continuous 1 number is up to 2 in sequence C, meet the condition of k < 3.SimultaneouslySo the probability currently distributed meets above-mentioned probabilistic model, then obtainSo
Afterwards it can be concluded that the probabilistic model satisfies the following conditional expressionP ' (1)=rp (1)=1.By p ' (0)
It is updated in entropy formula and obtains with p ' (1)；
It is obvious that H ' (X) is small than H (X), and reduces 65.2953% bit, so being based on above-mentioned probabilistic model structure
The channel coding for building out has compression.If desired accomplish 1/2 code rate, supervision member can be further added by or by symbol
0 and symbol 1 probability setting are as follows:P ' (1)=1；So that coding method has higher error correcting capability, and p '
(0) smaller error correcting capability is also higher.Next, set be not further added by supervision member in the case where, analyze error correction thinking.Based on sequence
Column C can obtain two features:
Feature one: continuous 1 number is up to 2；
Feature two: continuous 0 number only has 1.
Then there are continuous 3 or 3 or more during can use the two characteristics, such as decoding in the method for error correction
Symbol 1, or the symbol 0 for continuous 2 or 2 occur or more, then it is assumed that have decoding error.Decoder can pass through the two
Characteristic, the data that Lai Xiufu is received, and sequence C is decoded out, original binary sequence can be restored using following steps:
1), by sequence C step-by-step inverse, sequence B is obtained, i.e.,
2), remove the subsequent symbol 0 of sequence B symbol 1, obtain sequence A；
3), remove the subsequent symbol 1 of sequence A symbol 0, be then completely restored to out binary sequence.
On this basis, referring to Fig. 2, the channel decoding method of an embodiment mainly comprises the steps that
Step 1: parameter initialization sets the probability of symbol 0The probability of symbol 1 Single order is quiet
State coefficientH is obtained according to the expression formula of probabilistic model0=p0=1, L0=0, wherein L0、H0、p0Respectively
Lower limit initial value, upper limit initial value, the siding-to-siding block length initial value of probability interval；Obtain length Len (this of random binary sequence
In embodiment, Len=43 can be obtained from coding result)；Cyclic variable i=1 is set, wherein to be currently processed be i the
I symbol is encoded as i=Len and is completed；It is arranged buffer Buff [n], the n in [n] is that (buffer stores n to buffer size
A binary character), buffer counter lp=0；Temporary variable H=0 is (for recording the section subscript of each moment symbol 0
Value), obtain V value；X is decoded symbol；J is the jth position binary system of V value；
Step 2: i-th of symbol x is obtained according to probabilistic model expression formula (with specific reference to formula 1.2,1.3,1.4)iIt may
Probability interval:
0 section of symbol are as follows:
1 section of symbol are as follows:
Into step 3；
Step 3: the affiliated section V is judged according to probabilistic model expression formula (with specific reference to formula 1.4):
IfOrThen xi=0,
By xi=0 deposit buffer；
IfOrThen xi=1, it will
xi=1 deposit buffer；
Into step 4；
Step 4: error detection judges whether meet primitive character string in buffer, if satisfied, then determining that decoding is correct, enters
Step 6；If not satisfied, then determine to decode it is incorrect, into step 5 carry out error correction；
Wherein, as the above analysis, judge in the step of whether meeting primitive character string in buffer, including two are sentenced
According to:
Criterion 1: the number of continuous symbol 1 cannot be greater than 2 in buffer binary string；
Criterion 2: the number of continuous symbol 0 cannot be greater than 1 in buffer binary string,
If meeting criterion 1 and criterion 2 simultaneously, determine that decoding is correct, into step 6；If at least a criterion is discontented
Foot, then determine to decode it is incorrect, into step 5 carry out error correction.
Step 5: it by current V (V is with binary expression in any digital display circuit) from left to right by bit flipping, often turns over
Turn 1bit and obtain new V, judge whether j is equal to the binary length L of V value, if j≤L, returns to step 2, and j=j+1；If j >
L, then explanation can not correct V value, then output identification, terminate decoding；
Wherein, V value can be finite length by bit flipping, or indefinite length.
Step 6: judge whether occur following feature string in buffer from left to right: if substring for 101, output symbol 0；
If substring is 01, output symbol 1, and cyclic variable i adds 1, i.e. i=i+1, into step 7；
Step 7: judgement if i≤Len, returns to step 2 and carries out continuing to decode；If i > Len, decoding terminates.
To sum up, the debugging and error correction relation of symbol added in coding according to the method that invention provides, realize debugging and
Error correction is androgynous, can effectively improve error correction or error detecing capability, closer to entropy theory value, simulates awgn channel from experiment is surveyed,
27th byte starts to decode, and less than 3 bit of mistake occurs simultaneously in 27 bytes, is more than or equal to 3 bit situation energy error detections；
In addition, method provided by the invention belongs to linear error correction, it is no-delay；Error correction rate and the adaptation bit error rate are high, and the bit error rate is less than
In the case of 0.00001, can disposable 100% correction decoding；Code rate bottom, conventional method needs 1/2 code rate, and this method is only
Need 1/1.5849625 code rate；Only need to retransmit a bit more than 100 for what can not be corrected, without retransmitting entire number
According to packet, coding and decoding speed is faster.
It should be pointed out that in practical applications, due to Computer Precision problem, because of the meeting of probability interval length when coding
The very little of reduction, so the probability interval contracting of infinite precision can be realized with the probability interval iteration reduction of a finite accuracy
Subtract；Similarly, limited position (such as 32 bit, because the variable digit of an int type is in computer of V value can be taken when decoding
32) it is decoded in the probability interval of finite accuracy.So when needing to carry out error correction, it is impossible to pass through a unlimited essence
The V value of degree by bit flipping and carries out pre decoding judgement from left to right.But by caching multiple adjacent finite length (such as 32)
V value, by pre decoding judgement is carried out after bit flipping again.But this is an accommodation on concrete methods of realizing, judgment mode and
Coding and decoding process meets this algorithm flow, can not be not understood as new method invention, illustrate hereby.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (9)
1. a kind of channel coding method characterized by comprising
Step 1 pre-processes random binary sequence, and symbol 0 in random binary sequence is made to become symbol 1, and 0,1,
And the symbol 1 in random binary sequence is made to become 0,1；
Step 2, parameter initialization set the probability of symbol 0The probability of symbol 1 Single order static state system
NumberH is obtained according to the expression formula of probabilistic model0=p0=1, L0=0, wherein L0、H0、p0Respectively probability
Lower limit initial value, upper limit initial value, the siding-to-siding block length initial value in section；Obtain the length Len of random binary sequence；Setting follows
Ring variable i=1, it is i-th of symbol that wherein i, which is currently processed, encodes and completes as i=Len；After setting encodes all symbols
Probability interval subscript V=0；xiFor etc. i-th of symbol to be encoded；p1=p2=p3=0；
Step 3: if i-th of symbol is symbol 0, enter step 4；If i-th of symbol is symbol 1, enter step 5；
Step 4: 3 symbols 1,0,1 are encoded respectively, steps are as follows:
For coded identification 1,V=V+p1；
For coded identification 0, p2=rp (0) p1, V=V+0；
For coded identification 1, p3=rp (1) p2, V=V+p3；
Into step 6；
Step 5: by being encoded respectively to 2 symbols 0,1, steps are as follows:
For coded identification 0,V=V+0；
For coded identification 1, p2=rp (1) p1, V=V+p2；
Into step 6；
Step 6: cyclic variable i adds 1, i.e. i=i+1；If judging i≤Len, next symbol is encoded back to step 3；If i
> Len terminates coding, exports V and Len.
2. channel coding method according to claim 1, which is characterized in that in step 1, carried out to random binary sequence
Pretreatment specifically includes:
Increase by 1 symbol 1 behind each symbol 0, obtains sequence A；
Again to 1 symbol 0 is added behind each symbol 1 of sequence A, sequence B is obtained；
To sequence B step-by-step inverse, sequence C is obtained, i.e.,
3. channel coding method according to claim 1, which is characterized in that in step 1, carried out to random binary sequence
Pretreatment specifically includes:
It is practical successively to encode 1,0,1 three symbol if get symbol 0 from original string；It is practical if get symbol 1 from original string
Successively encode 0,1 two symbols.
4. channel coding method according to claim 1, which is characterized in that the probabilistic model meets the following conditions:
Shrinkable or expansion a probabilistic model is constructed, moment t is definedn, n is the natural number more than or equal to 1, and the probability of symbol is received
Contracting or flare factor are ωn, and the probability of all symbols is defined in moment tnAccording to same coefficient ωnThe random process of variation is
General process, there are three types of elementary probability models for the general process tool: if any time tnThere is ωnWhen ≡ 1, it is defined as master pattern；If appointing
0 is carved with when meaningn≤ 1, and there are ωn< 1, then be defined as contracting model；If there is ω in any timen>=1, and there are ωn> 1, then
It is defined as expansion model；
The fixation probability of symbol 0 and symbol 1 difference p (0) and p (1) in the random binary sequence are set, if
And the single order static coefficient r for expanding model meets:
If continuous 1 number in random sequenceThe distribution function for then expanding model can keep random sequence mathematics
Matter can be completely restored to random sequence；
The probability function and distribution function of the random binary sequence are as follows:
That is Hn(x1,x2,…,xn)=Ln(x1,x2,…,xn)+pn(x1,x2..., xn), and have the probability interval of lossless encoding/decoding from
Category relationship are as follows:
[Ln(x1,x2,…,xn),Hn(x1,x2,…,xn))
∈[Ln-1(x1,x2,…,xn-1),Hn-1(x1,x2,…,xn-1))∈…
∈[L1(x1),H1(x1))。
5. channel coding method according to claim 4, which is characterized in that in the probabilistic model, meet the following conditions
Formula:
6. a kind of channel decoding method characterized by comprising
Step 1: parameter initialization sets the probability of symbol 0The probability of symbol 1 Single order static coefficientH is obtained according to the expression formula of probabilistic model0=p0=1, L0=0, wherein L0、H0、p0Respectively Probability Region
Between lower limit initial value, upper limit initial value, siding-to-siding block length initial value；Obtain the length Len of random binary sequence；Setting circulation
Variable i=1, it is i-th of symbol that wherein i, which is currently processed, encodes and completes as i=Len；It is arranged buffer Buff [n],
N in [n] is buffer size, buffer counter lp=0；Temporary variable H=0 obtains V value；X is decoded symbol；J is
The jth position binary system of V value；
Step 2: i-th of symbol x is obtained according to probabilistic model expression formulaiPossible probability interval:
0 section of symbol are as follows:
1 section of symbol are as follows:
Into step 3；
Step 3: the affiliated section V is judged according to probabilistic model expression formula:
IfOrThen xi=0, by xi=
0 deposit buffer；
IfOrThen xi=1, by xi=
1 deposit buffer；
Into step 4；
Step 4: error detection judges whether meet primitive character string in buffer, if satisfied, then determining that decoding is correct, into the 6th
Step；If not satisfied, then determine to decode it is incorrect, into step 5 carry out error correction；
Step 5: current V is pressed into bit flipping from left to right, every overturning 1bit obtains new V, judges whether j is equal to the two of V value
System length L returns to step 2, and j=j+1 if j≤L；If j > L, output identification terminates decoding；
Step 6: judge whether occur following feature string in buffer from left to right: if substring for 101, output symbol 0；If sub
String is 01, then output symbol 1, and cyclic variable i adds 1, i.e. i=i+1, into step 7；
Step 7: judgement if i≤Len, returns to step 2 and carries out continuing to decode；If i > Len, decoding terminates.
7. channel decoding method according to claim 6, which is characterized in that in step 4, judge whether meet in buffer
In the step of primitive character string, including two criterions:
Criterion 1: the number of continuous symbol 1 cannot be greater than 2 in buffer binary string；
Criterion 2: the number of continuous symbol 0 cannot be greater than 1 in buffer binary string,
If meeting criterion 1 and criterion 2 simultaneously, determine that decoding is correct, into step 6；If at least a criterion is unsatisfactory for,
Determine that decoding is incorrect, carries out error correction into step 5.
8. channel decoding method according to claim 6, which is characterized in that the probabilistic model meets the following conditions:
Shrinkable or expansion a probabilistic model is constructed, moment t is definedn, n is the natural number more than or equal to 1, and the probability of symbol is received
Contracting or flare factor are ωn, and the probability of all symbols is defined in moment tnAccording to same coefficient ωnThe random process of variation is
General process, there are three types of elementary probability models for the general process tool: if any time tnThere is ωnWhen ≡ 1, it is defined as master pattern；If appointing
0 < ω is carved with when meaningn≤ 1, and there are ωn< 1, then be defined as contracting model；If there is ω in any timen>=1, and there are ωn>
1, then it is defined as expansion model；
The fixation probability of symbol 0 and symbol 1 difference p (0) and p (1) in the random binary sequence are set, if
And the single order static coefficient r for expanding model meets:
If continuous 1 number in random sequenceThe distribution function for then expanding model can keep random sequence mathematics
Matter can be completely restored to random sequence；
The probability function and distribution function of the random binary sequence are as follows:
That is Hn(x1,x2,…,xn)=Ln(x1,x2,…,xn)+pn(x1,x2,…,xn), and have the probability interval of lossless encoding/decoding from
Category relationship are as follows:
[Ln(x1,x2,…,xn),Hn(x1,x2,…,xn))
∈[Ln-1(x1,x2,…,xn-1),Hn-1(x1,x2,…,xn-1))∈…
∈[L1(x1),H1(x1))。
9. channel decoding method according to claim 6, which is characterized in that in step 5, V value is to have limit for length by bit flipping
Degree or indefinite length.
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