CN109327227B - Channel coding method for wireless measurement while drilling transmission system - Google Patents

Abstract

The invention discloses a channel coding method for a wireless measurement while drilling transmission system, which comprises the following steps: carrying out BCH coding on underground transmitted information, modulating transmitted data on a carrier wave, amplifying power and then transmitting the data, demodulating the data from a received signal in a ground instrument, optimizing a hard decision algorithm of a BCH code by adopting a Berlecamp iterative algorithm, exciting the potential of the BCH code by an exhaustion method, and recovering the underground transmitted information with the error rate as low as possible. The main advantages are that: each exhaustive group of decoding results has instantaneity, at most, only two groups of data of hard decision decoding results need to be stored, and the storage space is not greatly influenced; the soft decision decoding brings at least 2dB of coding gain to the wireless measurement while drilling transmission system, so that the bit error rate of the measurement while drilling transmission system can be reduced, and the target of extending the transmission distance of the measurement while drilling system is achieved by reducing the signal-to-noise ratio on the premise of not changing the bit error rate.

Description

Channel coding method for wireless measurement while drilling transmission system

Technical Field

The invention relates to the technical field of measurement while drilling of petroleum, natural gas, coal mines and the like, in particular to a channel coding method for a wireless measurement while drilling transmission system.

Background

According to the difference of transmission media, the wireless measurement while drilling system is divided into three transmission modes of sound wave, mud pulse and electromagnetic wave. The sound wave transmission signal is greatly attenuated and seriously interfered by the environment; the mud pulse has high reliability, can be used for long-distance transmission and is convenient to operate, but has low signal transmission rate. The electromagnetic wave is not influenced by drilling fluid, can be applied to foam drilling and gas drilling, is improved in transmission rate to a certain extent, but is greatly influenced by signal attenuation, and the transmission distance is limited.

The wireless measurement while drilling system comprises an underground instrument and a ground instrument, wherein the underground instrument acquires engineering parameters from a sensor, a transmitting signal is formed after encoding, modulation and amplification, and the ground instrument receives, conditions, processes and demodulates/decodes signals. The system mainly transmits the engineering parameters of the drill bit, the information quantity needing to be transmitted is small, and a shorter code length is usually adopted.

The BCH code is an important subclass in linear block codes, is convenient to construct, simple to encode, easy to realize in decoding, and has better error rate performance under the condition of short code length, and the BCH code has complete algebraic theory support, and is the most thoroughly researched error correcting code at present. If the channel coding of the wireless electromagnetic measurement while drilling transmission system adopts a linear block code scheme, a soft decision decoding algorithm is necessary to be selected because the complexity of hard decision decoding is low but better error rate performance cannot be obtained.

Disclosure of Invention

The technical problem to be solved by the present invention is to provide a channel coding method for a wireless measurement while drilling transmission system to solve the above problems, aiming at the technical defects that the signal transmission rate of the existing wireless measurement while drilling transmission system is low or the signal transmission rate is increased, which is influenced by signal attenuation, and the transmission distance is limited.

A channel coding method for a wireless measurement while drilling transmission system comprises the following specific steps:

step 11, the underground instrument encodes the information M to be transmitted by adopting a BCH code encoding method to obtain a sequence E;

step 12, modulating and amplifying the coded sequence E by the underground instrument and then sending out the modulated and amplified sequence E;

step 13, demodulating the received signal in the ground instrument to obtain a received sequence r;

and step 14, decoding the received sequence r by adopting a soft decision decoding algorithm.

Further, the BCH code encoding method in step 12 specifically includes the following steps:

step 21, selecting an existing polynomial with the degree of m on the finite field GF (q) according to the total code length N, and constructing GF (q)^m) Where q is a prime number or prime power, usually 2, m is some positive integer, and m and N satisfy N2 when q is 2^m-1，GF(q^m) Together containN elements, optionally GF (q)^m) All contain the element 0, alphaⁱFor the power representation of the remaining N-1 elements, i preferably has a value of 0, 1,2, …, N-2;

step 22, GF (q)^m) Element alpha of (A)ⁱMinimum polynomial m of 1,3, … 2t-1_i(x) Where t represents the error correction capability of the BCH code, for any positive integer m and t, there must be a binary BCH code with α, α³，…，α^2t-1Is root, code length N is 2^m1, t errors can be corrected, and mt is larger than or equal to N-K between positive integers m and t and the total code length N and the information sequence length K;

step 23, constructing a generator polynomial g (x) m capable of correcting t errors₁(x)m₃(x)…m_2t-1(x)；

Step 24, constructing a matrix G according to the generator polynomial₁＝[x^k-1g(x) … x²g(x) xg(x) g(x)]^TMatrix G by line transformation₁Transforming a square matrix formed by K column vectors on the left side into an identity matrix, thereby obtaining an encoding matrix G, wherein K is K and is the length of the information sequence;

and step 25, completing encoding according to a formula E-MG, where M and E are the information to be transmitted and the sequence obtained after encoding in step 11, respectively, and G is the encoding matrix obtained in step 24.

Further, the specific steps of a soft-decision decoding algorithm in step 14 are as follows:

step 31, performing hard decision on the received sequence r to obtain a hard decision output hd _ r;

step 32, the specific method for determining the unreliable bit position set according to the received sequence r is as follows: searching the top P1 positions with the minimum confidence in the received sequence r, selecting 0 to P positions from the P1 positions, and traversing all the combinations to obtain all the possible positions

The selection lists out, constructs the unreliable position set T, and sets each group of unreliable position T in the unreliable position set T_iPerforming steps 33 to 36;

step 33, according to the set of unreliable positions T given in step 32_iAssuming that all the decoded positions in the hard decision output hd _ r are decoded in error to generate the test sequence set C ═ hd _ r + T_i；

Step 34, carrying out hard decision decoding on the test code word C to obtain an effective code word D, and temporarily storing the effective code word D as a decoding result in R_flagIn which R is_flagThe device comprises a memory, a data processing module and a data processing module, wherein the memory is used for storing valid code words D, and the initial value of a flag is 0;

step 35, calculating Euclidean distance between the valid code word D and the received sequence r and temporarily storing the Euclidean distance to Euc_flagWherein Euc_flagA storage for storing the calculated Euclidean distance;

step 36, if Euc_flagEuc _ min, making flag 1-flag, Euc _ min unchanged, otherwise, making Euc _ min Euc_flagFlag is constant, wherein Euc _ min is a floating-point variable with an initial value of + ∞, and in practice a larger positive number is generally taken, for example: + 1000.0;

step 37, adding R_1-flagThe decoding result in (2) is output as the result of the final soft-decision decoding.

Further, in the step 34, the hard decision decoding is performed on each test codeword C by using the following steps:

step 41, calculating syndrome S according to receiving code polynomial R (x)_i(x) I ∈ {1,2, … 2t }, where t is the error correction capability of BCH hard decoding, writing the received test codeword C in the form of a polynomial:

wherein k is₁,k₂,…,k_jE {1,2, …, N }, j is less than or equal to N, and then according to a formula

Calculating a corresponding syndrome;

step 42, constructing an n-order polynomial sigma (x) about x by using a Berleamp iterative algorithm, and iterating for 2t +1 times in total, wherein sigma (x) is an error position polynomial, and the previous two iterations are directly carried outAssigning initial values, updating new sigma (x) and d in each iteration, and obtaining the sigma (x) updated in the last iteration, wherein sigma (j +1) represents the sigma (x) updated in the jth iteration, and sigma (x) is updated in the jth iteration_k(j) Denotes x in σ (j)^kCorresponding coefficient, D (j) represents the highest order of x in σ (j), d_j+1Representing the updated d value in the j iteration; the following is a specific calculation method:

step 42(a), assigns σ (x) and d for j-1 and j-0 as follows: sigma (-1) 1, D (-1) 0, D_-1＝1，σ(0)＝1，D(0)＝0，d₀＝S₁(x) Then, starting iteration from j to 0, increasing j by 1 in each iteration until j to 2t-1, and continuously looping steps 42(b) to 42 (d);

step 42(b), selecting the appropriate i, i must satisfy i < j, d_iNot equal to 0, and the value of i-D (i) is maximum;

step 42(c), judgment of d_jWhether or not it is 0, if d_jDirectly let σ (j +1) ═ σ (j), otherwise according to the formula

Updating a new sigma (j + 1);

step 42(d), according to the formula

Update out a new d_j；

And 43, calculating the solution of the equation sigma (x) to 0 by adopting a Chien search algorithm, wherein the possible values of x are 0, alpha and alpha²,…,α^N-1Substituting each possible value into an equation sigma (x) 0 to search, and finding out all solutions of the equation sigma (x) 0;

and 44, if the number of the equation solutions in the step 43 is equal to the highest order number of x in the polynomial sigma (x), passing the hard decision check, otherwise, failing to pass the hard decision check, and if the check passes, determining the solution of the equation as the error position in the test code word C, and correcting the information of the error position in the test code word C to obtain the effective code word D.

The algorithm has the advantages that: the hard decision algorithm of the BCH code is optimized by adopting a Berleamp iterative algorithm; the soft decision decoding algorithm brings at least 2dB of coding gain to a transmission system; each exhaustive group of decoding results has instantaneity, at most, only the data of two groups of decoding results need to be stored, and the storage space is not greatly influenced.

Drawings

The invention will be further described with reference to the accompanying drawings and examples, in which:

FIG. 1 is a schematic diagram of a channel coding method for a wireless measurement-while-drilling transmission system according to the present invention;

FIG. 2 is a flow chart of a soft decision decoding algorithm of the present invention;

fig. 3 is a graph of error rate curves corresponding to different parameters P1 selected by BCH soft-decision decoding when the total code length N is 31, the information sequence length K is 16, and the parameter P is 2 according to the present invention;

fig. 4 is a graph of error rate curves corresponding to different parameters P selected by BCH soft decision decoding when the total code length N is 31 and the information sequence length K is 16 according to the present invention;

fig. 5 is a comparison graph of the error rate curves of BCH hard-decision decoding and soft-decision decoding when the total code length N is 31, the information sequence length K is 16, the total code length N is 63, and the information sequence length K is 36.

Detailed Description

For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

A flow of a channel coding method for a wireless measurement while drilling transmission system is shown in fig. 1, the wireless measurement while drilling transmission system is divided into a downhole instrument and a surface instrument, and the following methods are specifically adopted to receive and transmit information:

step 11, the underground instrument encodes the information M to be transmitted by adopting a BCH code encoding method to obtain a sequence E;

step 12, modulating and amplifying the coded sequence E by the underground instrument and then sending out the modulated and amplified sequence E;

step 13, demodulating the received signal in the ground instrument to obtain a received sequence r;

and step 14, decoding the received sequence r by adopting a soft decision decoding algorithm.

The BCH code encoding method in step 11 specifically comprises the following steps:

step 21, selecting an existing polynomial with the degree of m on the finite field GF (q) according to the total code length N, and constructing GF (q)^m)；

Where q is a prime number or prime power, usually 2, m is a positive integer, m and N satisfy N2^m-1。

Step 22, GF (q)^m) Element alpha of (A)ⁱMinimum polynomial m of 1,3, … 2t-1_i(x)；

Where t denotes the error correction capability of the BCH code.

Step 23, constructing a generator polynomial g (x) m capable of correcting t errors₁(x)m₃(x)…m_2t-1(x)；

The step of calculating the generator polynomial g (x) is cumbersome and is generally obtained directly by looking up a table.

The common generator polynomials for the binary BCH code length N-63 and N-31 are shown in table 1.

N	K	t	g (x) octal form
				31	26	1	45
	21	2	3551
					16	3	107657
	11	5	5423325
					6	7	313365047
63	45	3	1701317
					39	4	166623567
	36	5	1033500423
					30	6	157464165547
	24	7	17323260404441
					18	10	1363026512351725
	16	11	6331141367235453

TABLE 1

Step 24, constructing a matrix G according to the generator polynomial₁＝[x^k-1g(x)…x²g(x)xg(x)g(x)]^TMatrix G by line transformation₁Transforming a square matrix formed by the k column vectors on the left side into an identity matrix, thereby obtaining a coding matrix G;

wherein K is the information sequence length.

And step 25, finishing coding according to the formula C-MG.

The decoding part adopts a soft decision algorithm for decoding, the flow chart of the algorithm is shown in figure 2, and the specific steps are as follows:

step 31, performing hard decision on the received sequence r to obtain a hard decision output hd _ r, wherein flag is initialized to 0, and Euc _ min is + ∞;

step (ii) of32, determining a set of unreliable bit positions, searching the top P1 positions with the minimum confidence in the received sequence r, selecting 0 to P positions from the P1 positions, and combining all the possible positions

The selection of the categories is listed by constructing a set of unreliable locations T, for each group of unreliable locations T_iPerforming steps 33 to 36;

step 33, according to the set of unreliable positions T given in step 32_iAssuming that all the decoded positions in the hard decision output hd _ r are decoded in error to generate the test sequence set C ═ hd _ r + T_i；

Step 34, carrying out hard decision decoding on the test code word C to obtain an effective code word D, and temporarily storing the effective code word D as a decoding result in R_flagPerforming the following steps;

step 35, calculating Euclidean distance between the valid code word D and the received sequence r and temporarily storing the Euclidean distance to Euc_flagPerforming the following steps;

step 36, if Euc_flagEuc _ min, making flag 1-flag, Euc _ min unchanged, otherwise, making Euc _ min Euc_flagFlag is unchanged;

step 37, adding R_1-flagThe decoding result in (2) is output as the result of the final soft-decision decoding.

The hard decision decoding in step 34 comprises the following specific steps:

step 41, calculating syndrome S according to receiving code polynomial R (x)_i(x),i∈{1,2,…2t}；

Wherein t is the error correction capability of BCH hard decoding, and the received test code word is written into a polynomial form:

wherein k is₁,k₂,…,k_jE {1,2, …, N }, j ≦ N, and then write the corresponding syndrome

Step 42, constructing an n-order polynomial sigma (x) about x by using a Berleamp iterative algorithm, and iterating for 2t +1 times in total, wherein the former two iterations are directly assigned with initial values, new sigma (x) and new d are updated in each iteration, and the sigma (x) updated in the last iteration is the obtained value;

the following is a specific calculation method, where σ (j +1) denotes σ (x), σ updated at the jth iteration_k(j) Denotes x in σ (j)^kCorresponding coefficient, D (j) represents the highest order of x in σ (j), d_j+1Representing the updated d value at the jth iteration.

In step 42(a), the parameters when j is-1 and j is 0 are assigned as follows: sigma (-1) 1, D (-1) 0, D_-1＝1，σ(0)＝1，D(0)＝0，d₀＝S₁(x) Then, starting iteration from j to 0, increasing j by 1 in each iteration until j to 2t-1, and continuously looping steps 42(b) to 42 (d);

step 42(b), selecting the appropriate i, i must satisfy i < j, d_iNot equal to 0, and the value of i-D (i) is maximum;

step 42(c), judgment of d_jWhether or not it is 0, if d_jDirectly let σ (j +1) ═ σ (j), otherwise according to the formula

Updating a new sigma (j + 1);

step 42(d), according to the formula

Update out a new d_j。

Step 43, calculating a solution of equation σ (x) to 0 by using a Chien search algorithm;

wherein x may take the values 0, alpha²,…,α^N-1Substituting each possible value into an equation sigma (x) 0 to search, and finding out all solutions of the equation sigma (x) 0;

and 44, if the number of the equation solutions in the step 43 is equal to the highest order number of x in the polynomial sigma (x), the hard decision check is passed, otherwise, the hard decision check is not passed.

If the check is passed, the solution of the equation is the error position in the test code word C, and the information of the error position in the test code word C is corrected to obtain the valid code word D.

According to the flow chart of the soft-decision decoding algorithm shown in fig. 2, the algorithm has two parameters, P and P1, and in order to obtain the best possible error rate performance of the BCH code, the two parameters, P and P1, are selected by a controlled variable method, and the limit of the error rate performance is found by simulation.

The following describes the process of parameter selection specifically by taking the code length N as 31 and the information bit length K as 16 as examples:

first, the control parameter P is constant at 3, and the parameter P1 is continuously increased. It can be seen from fig. 3 that P1-5 has a gain of less than 0.1dB compared to the block error rate performance of P1-4, and therefore it is considered that P1 takes 5 for best performance when P is 2.

As shown in fig. 4, the performance of the algorithm is not improved significantly when P is 5, so that the performance of the algorithm when P is 5 and P1 is 8 is selected as the limit performance of the algorithm when the code length N is 31 and K is 16.

Fig. 5 is a comparison graph of error rate curves of BCH hard decision decoding and soft decision decoding when the total code length N is 31, the information sequence length K is 16, the total code length N is 63, and the information sequence length K is 36, and it can be seen from the graph that the soft decision method brings more than 2dB gain to the system.

While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (4)

1. A channel coding method for a wireless measurement while drilling transmission system is characterized by comprising the following specific steps:

step 11, the underground instrument encodes the information M to be transmitted by adopting a BCH code encoding method to obtain a sequence E;

step 12, modulating and amplifying the coded sequence E by the underground instrument and then sending out the modulated and amplified sequence E;

step 13, demodulating the received signal in the ground instrument to obtain a received sequence r;

step 14, decoding the received sequence r by adopting a soft decision decoding algorithm; wherein, when decoding, the method comprises determining an unreliable bit position set according to a received sequence r, and comprises the following steps: searching the top P1 positions with the minimum confidence in the received sequence r, selecting 0 to P positions from the P1 positions, and traversing all the combinations to obtain all the possible positions

The selection lists out, constructs the unreliable location set T.

2. The channel coding method for the wireless measurement-while-drilling transmission system according to claim 1, wherein the coding method of the BCH code in step 12 specifically comprises the following steps:

step 21, selecting an existing polynomial with the degree of m on the finite field GF (q) according to the total code length N, and constructing GF (q)^m) Where q is a prime number or prime power, usually 2, m is some positive integer, and m and N satisfy N2 when q is 2^m-1，GF(q^m) Containing a total of N elements, optionally GF (q)^m) All contain the element 0, alphaⁱFor the power representation of the remaining N-1 elements, i preferably has a value of 0, 1,2, …, N-2;

step 22, GF (q)^m) Element alpha of (A)ⁱA minimum polynomial m of 1,3_i(x) Where t represents the error correction capability of the BCH code, for any positive integer m and t, there must be a binary BCH code with α, α³，…，α^2t-1Is root, code length N is 2^m1, t errors can be corrected, and mt is larger than or equal to N-K between positive integers m and t and the total code length N and the information sequence length K;

step 23, constructing a generator polynomial g (x) m capable of correcting t errors₁(x)m₃(x)...m_2t-1(x)；

Step 2Constructing a matrix G from the generator polynomial₁＝[x^k-1g(x)...x²g(x) xg(x) g(x)]^TMatrix G by line transformation₁Transforming a square matrix formed by K column vectors on the left side into an identity matrix, thereby obtaining an encoding matrix G, wherein K is K and is the length of the information sequence;

and step 25, completing encoding according to a formula E-MG, where M and E are the information to be transmitted and the sequence obtained after encoding in step 11, respectively, and G is the encoding matrix obtained in step 24.

3. The channel coding method for the wireless measurement-while-drilling transmission system according to claim 1, wherein the step 14 of a soft-decision decoding algorithm comprises the following steps:

step 31, performing hard decision on the received sequence r to obtain a hard decision output hd _ r;

step 32, determining an unreliable bit position set T according to the received sequence r, and determining each group of unreliable positions T in the unreliable position set T_iPerforming steps 33 to 36;

step 33, according to the set of unreliable positions T given in step 32_iAssuming that all the decoded positions in the hard decision output hd _ r are decoded in error to generate the test sequence set C ═ hd _ r + T_i；

Step 34, carrying out hard decision decoding on the test code word C to obtain an effective code word D, and temporarily storing the effective code word D as a decoding result in R_flagIn which R is_flagThe device comprises a memory, a data processing module and a data processing module, wherein the memory is used for storing valid code words D, and the initial value of a flag is 0;

step 35, calculating Euclidean distance between the valid code word D and the received sequence r and temporarily storing the Euclidean distance to Euc_flagWherein Euc_flagA storage for storing the calculated Euclidean distance;

step 36, if Euc_flagEuc _ min, making flag 1-flag, Euc _ min unchanged, otherwise, making Euc _ min Euc_flagFlag is unchanged, wherein Euc _ min is a floating point type variable taking a positive number, and the initial value thereof is preset to + ∞;

step 37, adding R_1-flagThe decoding result in (2) is output as the result of the final soft-decision decoding.

4. The channel coding method for the wireless measurement-while-drilling transmission system according to claim 3, wherein the step 34 of hard decision decoding of each test codeword C comprises the following steps:

step 41, calculating syndrome S according to receiving code polynomial R (x)_i(x) i ∈ {1,2,. 2, 2t }, where t is the error correction capability of BCH hard decoding, writing the received test codeword C in the form of a polynomial:

wherein k is₁,k₂,...,k_jE {1, 2., N } j is less than or equal to N, and then according to a formula

Calculating a corresponding syndrome;

step 42, constructing an n-order polynomial σ (x) about x by using a Berleamp iterative algorithm, and iterating for 2t +1 times in total, wherein σ (x) is an error position polynomial, the first two iterations are directly provided with initial values, new σ (x) and new d are updated in each iteration, σ (x) updated in the last iteration is obtained, wherein σ (j +1) represents σ (x) updated in the jth iteration, and σ (x) is updated in the jth iteration_k(j) Denotes x in σ (j)^kCorresponding coefficient, D (j) represents the highest order of x in σ (j), d_j+1Representing the updated d value in the j iteration; the following is a specific calculation method:

step 42(a), assigns σ (x) and d for j-1 and j-0 as follows: sigma (-1) 1, D (-1) 0, D_-1＝1，σ(0)＝1，D(0)＝0，d₀＝S₁(x) Then, starting iteration from j to 0, increasing j by 1 in each iteration until j to 2t-1, and continuously looping steps 42(b) to 42 (d);

step 42(b), selecting the appropriate i, i must satisfy i<j，d_iNot equal to 0, and the value of i-D (i) is maximum;

step 42(c), judgment of d_jWhether or not it is 0 or not,if d is_jDirectly let σ (j +1) ═ σ (j), otherwise according to the formula

Updating a new sigma (j + 1);

step 42(d), according to the formula

Update out a new d_j；

And 43, calculating the solution of the equation sigma (x) to 0 by adopting a Chien search algorithm, wherein the possible values of x are 0, alpha and alpha²,...,α^N-1Substituting each possible value into an equation sigma (x) 0 to search, and finding out all solutions of the equation sigma (x) 0;

and 44, if the number of the equation solutions in the step 43 is equal to the highest order number of x in the polynomial sigma (x), passing the hard decision check, otherwise, failing to pass the hard decision check, and if the check passes, determining the solution of the equation as the error position in the test code word C, and correcting the information of the error position in the test code word C to obtain the effective code word D.

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