CN110690934B - Constellation mapping method for reducing bit error rate of joint coding modulation system - Google Patents

Constellation mapping method for reducing bit error rate of joint coding modulation system Download PDF

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CN110690934B
CN110690934B CN201910953087.7A CN201910953087A CN110690934B CN 110690934 B CN110690934 B CN 110690934B CN 201910953087 A CN201910953087 A CN 201910953087A CN 110690934 B CN110690934 B CN 110690934B
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付芳
张志才
焦琦
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Abstract

The invention belongs to the technical field of communication. In particular, to a constellation mapping method for reducing bit error rate in a joint coded modulation system. The invention mainly solves the problem of high bit error rate in the prior joint coding modulation system adopting high-order APSK modulation. The invention discloses a constellation mapping method for reducing bit error rate in a joint coding modulation system, which comprises the following steps: firstly, establishing a joint coding modulation system model; taking an output signal which is interwoven by a sending end as an input signal of high-order APSK constellation mapping, and initializing parameters by using a novel bat algorithm; randomly generating a plurality of groups of solutions; calculating the bit error rate of each group of solutions, and taking a group of solutions corresponding to the minimum value of the bit error rate as an optimal solution; starting iteration to generate a new solution; generating a local solution around the optimal solution; and updating the current global optimal solution to reach the maximum iteration times, and outputting the optimal solution.

Description

Constellation mapping method for reducing bit error rate of joint coding modulation system
Technical Field
The invention belongs to the technical field of communication. In particular, to a constellation mapping method for reducing bit error rate in a joint coded modulation system.
Background
In the standards established in the satellite communication field, such as the second generation standard DVB-S2 of satellite digital video broadcasting, the council of spatial data system, etc., amplitude phase shift keying APSK modulation is commonly used because the non-linear characteristic of the satellite communication channel requires that the designed constellation structure can make the fluctuation of the signal amplitude smaller, and the characteristics of high spectrum utilization rate and small fluctuation of the signal amplitude of APSK modulation just meet the requirements of satellite communication. At present, a uniform pseudo gray mapping scheme is generally used in APSK modulation, and since different constellation structures have great influence on modulation performance, the conventional mapping scheme needs to be optimized to further improve system performance. In recent years, the constellation mapping optimization method has been studied both domestically and abroad.
On the one hand, most studies are aimed at reducing the floor effect of joint coded modulation systems, such as the TV mapping method proposed by d.torrieri et al, which, although reducing the floor effect, has the cost of severe performance loss in waterfall areas; the precoding method proposed by Hassan M et al has the advantage of reducing the floor effect, but has the disadvantage of not reducing the bit error probability as a whole.
On the other hand, in the field of satellite communication video broadcasting, MatteoAnedda et al propose a 64APSK mapping optimization method based on a genetic algorithm with a minimized bit error number as an optimization target, and Jon Barrueco et al propose a non-uniform QAM constellation mapping optimization method based on a particle swarm optimization with channel capacity as an optimization target. The two methods have the disadvantages that the two methods are based on the global optimal solution search algorithm, and both the channel capacity and the bit error number are used as optimization targets, so that more calculation amount is needed, and the complexity is slightly higher. Jordanova et al propose an alternative method for the 16APSK mapping method in the DVB-S2 standard, which is simply referred to as a (6,10) -16APSK constellation mapping method, wherein 6 constellation points are distributed in the inner ring, 10 constellation points are distributed in the outer ring, and the bit error rate performance is slightly better than that of the scheme in the DVB-S2 standard.
The bat algorithm is subjected to some approximate and ideal processing by simulating the principle of bat echo positioning and detection, is optimized by using an iteration mode, is initialized into a group of random solutions, then searches for an optimal solution by iteration, and generates a local solution around the optimal solution by random flight. The X.B.Meng et al provides a novel bat algorithm, embeds a self-adaptive local search strategy, and enhances the diversity of the population. It is worth noting that the bat algorithm has been used in control theory only, and not in constellation optimization.
Disclosure of Invention
In order to solve the problem of high bit error rate in a joint coding modulation system adopting high-order APSK modulation, the invention provides a constellation mapping method for reducing the bit error rate of the joint coding modulation system.
In order to solve the above problem, the present invention provides a constellation mapping method for reducing bit error rate of a joint coding modulation system, and the method is implemented by the following steps:
step 1: establishing a joint coding modulation system model, randomly generating a long string of binary numbers as a signal sent by an information source, firstly, a transmitting end adopts a low-density parity check code (LDPC) encoder to encode the signal sent by the information source, the encoded signal passes through a bit interleaver to increase the Euclidean distance between codewords, high-order APSK constellation mapping is carried out on the interleaved signal, the mapped signal is transmitted to a receiving end through a wireless channel, the receiving end carries out soft demodulation and soft decoding joint iteration on the received signal, the iterated signal is sent to an information sink, and the establishment of the system model is completed;
step 2: taking the combined coding modulation system model built in the step 1 as a simulation platform, taking the output signal of the transmitting end bit interleaver in the step 1 after completing interleaving as an input signal of high-order APSK constellation mapping, wherein the output signal is a string of binary bit signals, and each log of the binary bit signals2M bit signals are mapped to a constellation point in a high-order APSK constellation diagram, wherein M represents an order; optimizing high-order APSK constellation mapping by utilizing a novel bat algorithm, initializing population and parameters, wherein the parameters comprise maximum repeated execution times of the bat algorithm, population size, pulse emissivity, frequency, loudness, update frequency and habitat selection probability P epsilon [0,1]Doppler compensation rate, inertial weight and coefficient of contraction and expansion;
and step 3: randomly generating N solutions of a D-dimensional search space, where D is the dimension of the solution space and N is the number of solutions, each solution using xijDenotes that i ∈ [1, 2.,. N.)]，j∈[1,2,...,D]Where i is the index for the number of the solution, j is the index for the number of the solution space dimension, xijComposed of a relative radius ratio and a phase value for each constellation point, xijIs obtained by the following formula:
xij＝xjmin+(xjmax-xjmin)*rand(0,1)
where rand (0,1) is a random number obeying uniform distribution, xjmaxAnd xjminRespectively representing the upper and lower bounds of the jth value in the search space, and being determined by a specific search target, wherein the step can generate a plurality of solutions;
and 4, step 4: solving each solution x in the plurality of solutions generated in the step 3ijSubstituting the formula to obtain the bit error rate Pb
Figure BDA0002226376000000033
In the formula
Figure BDA0002226376000000031
The variable y meansSubstitute for Chinese traditional medicine
Figure BDA0002226376000000032
hijRepresenting the Hamming distance, N, between signal points i and j0Is the noise power spectral density, dijRepresenting the Euclidean distance between signal points, wherein each solution in the step corresponds to a bit error rate value;
and 5: selecting the bit error rate P in the step 4bMinimum value, using the corresponding solution as global optimum solution
Figure BDA0002226376000000034
Represents;
step 6: randomly sampling between 0 and 1, comparing the sampling value with the habitat selection probability P in the step 2, and updating the solution x in the step 3ijDifferent updating methods are adopted according to the size relationship;
further, the step 6 updates the solution x in the step 3ijThe specific updating method is as follows:
randomly generating a random number between 0 and 1, which is represented by rand (0,1), if rand (0,1) < P, wherein P represents habitat selection probability, the updating method is as follows:
Figure BDA0002226376000000041
wherein
Figure BDA0002226376000000042
Representing a solution when step 5 is performed the t-th time,
Figure BDA0002226376000000043
represents the average of all solutions when step 5 is performed for the t-th time, N is the number of solutions in step 3, theta is the coefficient of contraction and expansion, uij∈[0,1]Uniform distribution is obeyed;
if rand (0,1) is not less than P, the updating method is as follows:
fij＝fmin+(fmax-fmin)*rand(0,1)
Figure BDA0002226376000000044
Figure BDA0002226376000000045
Figure BDA0002226376000000046
wherein f isijRepresenting the frequency, f, corresponding to the ith valueij' denotes the frequency after adaptive compensation of the Doppler Effect, fmin、fmaxFor the minimum and maximum values of frequency, depending on the specific search environment, c (c 340m/s) is the speed of sound in air, v ∈ [0,1]In order to obtain the flying speed of the aircraft,
Figure BDA0002226376000000047
indicates the flight speed at the time of execution of step 6 for the t-th time,
Figure BDA0002226376000000048
represents the flight speed corresponding to the global optimal solution when step 6 is executed the t-th time,
Figure BDA0002226376000000049
represents the flying speed at the time of t +1 th execution of step 6,
Figure BDA00022263760000000410
j-th value, C, representing the i-th solution from step 6 performed the t + 1-th timei∈[0,1]The doppler effect compensation rate is expressed as an infinitesimal number, and w ═ rand (0,1) represents the inertial weight.
And 7: randomly sampling between 0 and 1, and if the sampling value is larger than the pulse emissivity in the step 2, solving the global optimal solution in the step 6
Figure BDA00022263760000000411
Substituting into the following formula to obtain local new solution
Figure BDA00022263760000000412
Figure BDA00022263760000000413
Wherein randn (0, σ)2) Is a mean of 0 and a variance of σ2The distribution of the gaussian component of (a) is,
Figure BDA00022263760000000414
is an infinite fraction, t is the number of executions,
Figure BDA00022263760000000415
indicating the loudness of the ith solution the t-th time step 7 is performed,
Figure BDA00022263760000000416
represents the average loudness of all solutions the t time step 7 is performed; if the sampling value is less than or equal to the pulse emissivity in the step 2, skipping the step and executing a step 8;
and 8: the global optimal solution obtained in the step 5 is used
Figure BDA0002226376000000051
The updated solution x in step 6ijAnd the local new solution obtained in step 7
Figure BDA0002226376000000052
Substituting into the formula in step 4 to obtain the bit error rate value P of each solutionb；
And step 9: updating the global optimal solution in the step 5, namely selecting the minimum value of the bit error rate in the step 8, and taking the corresponding solution as the updated global optimal solution;
step 10: updating the loudness in step 7, and comparing the loudness in step 7
Figure BDA0002226376000000053
Substituting the following formulaUpdating:
Figure BDA0002226376000000054
alpha epsilon (0,1) is a constant,
Figure BDA0002226376000000055
representing the updated loudness, the updated loudness for use the next time step 7 is performed;
step 11: updating the pulse emissivity in the step 7, and substituting the pulse emissivity in the step 7 into the following formula for updating: r isi t+1＝ri 0(1-e-γt)，ri t+1Is the updated pulse emissivity, ri 0The pulse emissivity is the pulse emissivity when the parameter is initialized and set in the step 1, gamma is a constant more than 0, and the updated pulse emissivity is used for the next time when the step 7 is executed;
step 12: and (5) repeatedly executing the steps 5 to 11 until the maximum repeated execution times set in the step 1 is reached, outputting the global optimal solution updated in the step 9, and finishing the optimization of the high-order APSK constellation mapping chart.
Particularly, the constellation mapping method for reducing the bit error rate in the joint coding modulation system is a high-order APSK constellation mapping method based on a novel bat algorithm, is only suitable for APSKs with dimensions of 16 th order and 32 th order, namely 16APSK and 32APSK, and is not suitable for the situation that the dimensions exceed 32 th order.
Compared with the prior art, the invention can achieve the following beneficial effects:
1) steps 4-5 and steps 8-9 show that the method takes the bit error rate minimization as the optimization target of the high-order APSK constellation mapping, and the search process of the global optimal solution is simple, namely, a new solution is generated by utilizing random flight around the global optimal solution, and then the bit error rate values of all solutions mentioned in step 8 are compared to select the solution corresponding to the minimum one, so that the search time of the global optimal solution is greatly reduced; 6-7 show that the solution updating method has low calculation complexity; steps 10-11 show that to realize the solution update, only two parameters of loudness and pulse emissivity need to be updated, excessive parameters do not need to be adjusted, and the parameters and steps are simplified for the high-dimensional and complex optimization problems of high-order APSK constellation mapping.
2) Parameter NminRepresenting the average number of different bits between two adjacent constellation points in the constellation diagram, the closer the parameter is to 1.0, the better the bit error rate performance theoretically. For the 16APSK mapping scheme, the parameter value of the precoding method is 2.25, the parameter value of the DVB-S2 standard is 1.0, the parameter value of the (6,10) -16APSK method is 1.1667, and the parameter value of the constellation mapping method adopting the present patent is 1.0, so that it is theoretically proved that the bit error rate of the joint coding modulation system can be effectively reduced and the reliability of the wireless communication can be improved by adopting the 16APSK constellation mapping method of the present patent. From the experimental simulation results of example 2, it can be seen that the signal-to-noise ratio E is the sameb/N0When the bit error rate is 7dB, the bit error rate obtained by the constellation mapping method is 10-7The bit error rate is reduced by 1 order of magnitude compared with the bit error rate obtained by adopting the (6,10) -16APSK constellation mapping method, is reduced by 2 orders of magnitude compared with the bit error rate obtained by adopting the constellation mapping method in the DVB-S2 standard, and is reduced by 5 orders of magnitude compared with the bit error rate obtained by adopting the precoding method.
3) For the 32APSK mapping scheme, the parameter N of the precoding methodminThe value is 2.5625, the parameter value of the constellation mapping method in the DVB-S2 standard is 1.125, and the parameter value of the constellation mapping method in the patent is 1.0, so that the 32APSK constellation mapping method in the patent is theoretically proved to be capable of effectively reducing the bit error rate of the joint coding modulation system and improving the reliability of wireless communication. From the experimental simulation results, it can be seen that when the bit error rate of the system is 10-5When the method is used, the signal-to-noise ratio required by the constellation mapping method is 8.73dB, the gain is improved by 0.09dB compared with the constellation mapping method in the DVB-S2 standard, and the gain is improved by 1.88dB compared with the precoding method.
4) Aiming at the high-dimensionality and complex optimization problems of high-order constellation mapping, the novel bat algorithm is embedded with a self-adaptive local search strategy, the diversity of the population is enhanced, and the limitation of the basic bat algorithm is avoided.
5) The bat algorithm is only used in the control theory, the novel bat algorithm is innovatively used in the APSK constellation mapping optimization problem, the problem of high bit error rate when high-order APSK modulation is adopted in a combined coding modulation system is solved, the minimum bit error rate is used as an optimization target to optimize constellation mapping, and the theory and experimental simulation prove that the bit error rate performance obtained by adopting the constellation mapping method of the invention is superior to that of the existing precoding method and the constellation mapping method in the DVB-S2 standard.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a diagram of a joint coded modulation system model;
fig. 2 is a bit error rate curve comparison of 16APSK multiple mapping methods according to embodiment 2 of the present invention;
fig. 3 is a comparison of bit error rate curves of multiple 32APSK mapping methods according to embodiment 3 of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
Example 1:
in the joint coded modulation system model shown in fig. 1, the simulation is specifically set as follows: the channel coding uses LDPC codes with code length 2304 and code rate 5/6, the interleaver is random interleaving, the channel model is a Gaussian white noise channel, the LDPC decoder is an LLR-BP decoding algorithm, the soft demodulator is an MAX-log-Map decoding algorithm, the soft demodulation soft decoding joint iteration time is set to be 4, and the LDPC code decoding internal iteration time is set to be 10.
The method comprises the following steps:
step 1: establishing a joint coding modulation system model, randomly generating a long string of binary numbers as a signal sent by an information source, firstly, a transmitting end adopts a low-density parity check code (LDPC) encoder to encode the signal sent by the information source, the encoded signal passes through a bit interleaver to increase the Euclidean distance between code words, the interleaved signal is subjected to high-order APSK constellation mapping, the mapped signal is transmitted to a receiving end through a wireless channel, the receiving end performs soft demodulation and soft decoding joint iteration on the received signal, the iterated signal is sent to an information sink, and the establishment of the system model is completed;
step 2: taking the combined coding modulation system model built in the step 1 as a simulation platform, taking the output signal of the transmitting end bit interleaver in the step 1 after completing interleaving as an input signal of high-order APSK constellation mapping, wherein the output signal is a string of binary bit signals, and each log of the binary bit signals2M bit signals are mapped to a constellation point in a high-order APSK constellation diagram, wherein M represents an order; optimizing high-order APSK constellation mapping by using an improved bat algorithm, initializing population and parameters, wherein the parameters are shown in table 1 and comprise maximum repeated execution times of the bat algorithm, population size, pulse emissivity, frequency, loudness, updating frequency and habitat selection probability P ∈ [0,1 ]]Doppler compensation rate, inertial weight and coefficient of contraction and expansion;
TABLE 1 parameters of the novel bat algorithm
Figure BDA0002226376000000081
And step 3: randomly generating N solutions of a D-dimensional search space, where D is the dimension of the solution space and N is the number of solutions, each solution using xijDenotes that i ∈ [1, 2.,. N.)]，j∈[1,2,...,D]Where i is the index for the number of the solution, j is the index for the number of the solution space dimension, xijComposed of a relative radius ratio and a phase value for each constellation point, xijIs obtained by the following formula:
xij＝xjmin+(xjmax-xjmin)*rand(0,1)
where rand (0,1) is a random number obeying uniform distribution, xjmaxAnd xjminRespectively representing the upper and lower bounds of the jth value in the search space, and being determined by a specific search target, wherein the step can generate a plurality of solutions;
and 4, step 4: solving each solution x in the plurality of solutions generated in the step 3ijSubstituting the formula to obtain the bit error rate Pb
Figure BDA0002226376000000091
In the formula
Figure BDA0002226376000000092
Variable y denotes
Figure BDA0002226376000000093
hijRepresenting the Hamming distance, N, between signal points i and j0Is the noise power spectral density, dijRepresenting the Euclidean distance between signal points, wherein each solution in the step corresponds to a bit error rate value;
and 5: selecting the bit error rate P in the step 4bMinimum value, using the corresponding solution as global optimum solution, and gjt represents;
step 6: randomly sampling between 0 and 1, comparing the sampling value with the habitat selection probability P in the step 2, and updating the solution x in the step 3ijDifferent updating methods are adopted according to the size relationship, and the specific updating method is as follows:
randomly generating a random number between 0 and 1, which is represented by rand (0,1), if rand (0,1) < P, wherein P represents habitat selection probability, the updating method is as follows:
Figure BDA0002226376000000094
wherein
Figure BDA0002226376000000095
Representing a solution when step 5 is performed the t-th time,
Figure BDA0002226376000000096
represents the average of all solutions when step 5 is performed for the t-th time, N is the number of solutions in step 3, theta is the coefficient of contraction and expansion, uij∈[0,1]Uniform distribution is obeyed;
if rand (0,1) is not less than P, the updating method is as follows:
fij＝fmin+(fmax-fmin)*rand(0,1)
Figure BDA0002226376000000101
Figure BDA0002226376000000102
Figure BDA0002226376000000103
wherein f isijRepresenting the frequency, f, corresponding to the ith valueij' denotes the frequency after adaptive compensation of the Doppler Effect, fmin、fmaxFor the minimum and maximum values of frequency, depending on the specific search environment, c (c 340m/s) is the speed of sound in air, v ∈ [0,1]In order to obtain the flying speed of the aircraft,
Figure BDA0002226376000000104
indicates the flight speed at the time of execution of step 6 for the t-th time,
Figure BDA0002226376000000105
represents the flight speed corresponding to the global optimal solution when step 6 is executed the t-th time,
Figure BDA0002226376000000106
represents the flying speed at the time of t +1 th execution of step 6,
Figure BDA0002226376000000107
j-th value, C, representing the i-th solution from step 6 performed the t + 1-th timei∈[0,1]Represents the doppler effect compensation rate as an infinitesimal number, w ═ rand (0,1) represents the inertial weight;
and 7: randomly sampling between 0 and 1, and if the sampling value is larger than the pulse emissivity in the step 2, solving the global optimal solution in the step 6
Figure BDA0002226376000000108
Substituting into the following formula to obtain local new solution
Figure BDA0002226376000000109
Figure BDA00022263760000001010
Wherein randn (0, σ)2) Is a mean of 0 and a variance of σ2The distribution of the gaussian component of (a) is,
Figure BDA00022263760000001011
is an infinite fraction, t is the number of executions,
Figure BDA00022263760000001012
indicating the loudness of the ith solution the t-th time step 7 is performed,
Figure BDA00022263760000001013
represents the average loudness of all solutions the t time step 7 is performed; if the sampling value is less than or equal to the pulse emissivity in the step 2, skipping the step and executing a step 8;
and 8: the global optimal solution obtained in the step 5 is used
Figure BDA00022263760000001014
The updated solution x in step 6ijAnd the local new solution obtained in step 7
Figure BDA00022263760000001015
Substituting into the formula in step 4 to obtain the bit error rate value P of each solutionb；
And step 9: updating the global optimal solution in the step 5, namely selecting the minimum value of the bit error rate in the step 8, and taking the corresponding solution as the updated global optimal solution;
step 10: updating the loudness in step 7, and comparing the loudness in step 7
Figure BDA0002226376000000111
Updating is performed by substituting the following formula:
Figure BDA0002226376000000112
alpha epsilon (0,1) is a constant,
Figure BDA0002226376000000113
representing the updated loudness, the updated loudness for use the next time step 7 is performed;
step 11: updating the pulse emissivity in the step 7, and substituting the pulse emissivity in the step 7 into the following formula for updating: r isi t+1＝ri 0(1-e-γt)，ri t+1Is the updated pulse emissivity, ri 0The pulse emissivity is the pulse emissivity when the parameter is initialized and set in the step 1, gamma is a constant more than 0, and the updated pulse emissivity is used for the next time when the step 7 is executed;
step 12: and (5) repeatedly executing the steps 5 to 11 until the maximum repeated execution times set in the step 1 is reached, outputting the global optimal solution updated in the step 9, and finishing the optimization of the high-order APSK constellation mapping chart.
Example 2:
fig. 2 is a bit error rate curve comparison of multiple constellation mapping methods for 16APSK according to the system model shown in fig. 1, where the constellation mapping method in fig. 2 includes: the constellation mapping method, the precoding method, the (6,10) -16APSK constellation mapping method in the DVB-S2 standard, and the constellation mapping method adopting the patent. Since the patent is based on the novel bat algorithm pair in the embodiment 2The (6,10) -16APSK constellation mapping method is optimized, so the bit error rate curve obtained by the constellation mapping method of the present patent in fig. 2 is marked as "(after 6,10) -16APSK bat algorithm is optimized"). As can be seen from the figure, when the signal-to-noise ratio E isb/N0When the bit error rate is 7dB, the bit error rate obtained by the constellation mapping method is 10-7The bit error rate obtained by adopting the (6,10) -16APSK constellation mapping method is 10-6Order of magnitude, the bit error rate obtained using the DVB-S2 standard is 10-5Order of magnitude, the bit error rate obtained by using the pre-coding method is 10-2An order of magnitude.
Example 3:
fig. 3 is a bit error rate curve comparison of the system model shown in fig. 1 for multiple 32APSK constellation mapping methods, where the constellation mapping method shown in fig. 3 includes: a constellation mapping method and a precoding method in DVB-S2 standard, and a constellation mapping method adopting the patent. Since the present patent optimizes the constellation mapping method in the existing DVB-S2 standard based on the novel bat algorithm in embodiment 3, the bit error rate curve obtained by using the constellation mapping method of the present patent in fig. 3 is labeled as "after the constellation mapping method in the standard is optimized". It can be seen from the figure that when the bit error rate of the system is 10-5In the process, the signal-to-noise ratio required by the constellation mapping method is 8.73dB, the signal-to-noise ratio required by the constellation mapping method in the DVB-S2 standard is 8.82dB, and the signal-to-noise ratio required by the precoding method is 10.61 dB.

Claims (2)

1. A constellation mapping method for reducing bit error rate of a joint coding modulation system is characterized by comprising the following steps:
step 1: establishing a joint coding modulation system model, randomly generating a long string of binary numbers as a signal sent by an information source, firstly, a transmitting end adopts a low-density parity check code (LDPC) encoder to encode the signal sent by the information source, the encoded signal passes through a bit interleaver to increase the Euclidean distance between codewords, high-order APSK constellation mapping is carried out on the interleaved signal, the mapped signal is transmitted to a receiving end through a wireless channel, the receiving end carries out soft demodulation and soft decoding joint iteration on the received signal, the iterated signal is sent to an information sink, and the establishment of the system model is completed;
step 2: taking the combined coding modulation system model built in the step 1 as a simulation platform, taking the output signal of the transmitting end bit interleaver in the step 1 after completing interleaving as an input signal of high-order APSK constellation mapping, wherein the output signal is a string of binary bit signals, and each log of the binary bit signals2M bit signals are mapped to a constellation point in a high-order APSK constellation diagram, wherein M represents an order; optimizing high-order APSK constellation mapping by utilizing a novel bat algorithm, initializing population and parameters, wherein the parameters comprise maximum repeated execution times of the bat algorithm, population size, pulse emissivity, frequency, loudness, update frequency and habitat selection probability P epsilon [0,1]Doppler compensation rate, inertial weight and coefficient of contraction and expansion;
and step 3: randomly generating N solutions of a D-dimensional search space, where D is the dimension of the solution space and N is the number of solutions, each solution using xijDenotes that i ∈ [1, 2.,. N.)]，j∈[1,2,...,D]Where i is the index for the number of the solution, j is the index for the number of the solution space dimension, xijComposed of a relative radius ratio and a phase value for each constellation point, xijIs obtained by the following formula:
xij＝xjmin+(xjmax-xjmin)*rand(0,1)
where rand (0,1) is a random number obeying uniform distribution, xjmaxAnd xjminRespectively representing the upper and lower bounds of the jth value in the search space, and being determined by a specific search target, wherein the step can generate a plurality of solutions;
and 4, step 4: solving each solution x in the plurality of solutions generated in the step 3ijSubstituting the formula to obtain the bit error rate Pb
Figure FDA0002643187080000021
In the formula
Figure FDA0002643187080000022
Variable y denotes
Figure FDA0002643187080000023
hijDenotes xijHamming distance, N, between intermediate signal points i and j0Is the noise power spectral density, dijRepresenting the Euclidean distance between signal points, wherein each solution in the step corresponds to a bit error rate value;
and 5: selecting the bit error rate P in the step 4bMinimum value, using the corresponding solution as global optimum solution
Figure FDA0002643187080000024
Represents;
step 6: randomly sampling between 0 and 1, comparing the sampled value with the habitat selection probability P in the step 2, and updating the solution x in the step 3ijDifferent updating methods are adopted according to the size relationship;
and 7: randomly sampling between 0 and 1, and if the sampling value is larger than the pulse emissivity in the step 2, solving the global optimal solution in the step 5
Figure FDA0002643187080000025
Substituting into the following formula to obtain local new solution
Figure FDA0002643187080000026
Figure FDA0002643187080000027
Wherein randn (0, σ)2) Is a mean of 0 and a variance of σ2The distribution of the gaussian component of (a) is,
Figure FDA0002643187080000028
is an infinite fraction, t is the number of executions,
Figure FDA0002643187080000029
indicating the loudness of the ith solution the t-th time step 7 is performed,
Figure FDA00026431870800000213
represents the average loudness of all solutions the t time step 7 is performed;
and 8: the global optimal solution obtained in the step 5 is used
Figure FDA00026431870800000210
The updated solution x in step 6ijAnd the local new solution obtained in step 7
Figure FDA00026431870800000211
Substituting into the formula in step 4 to obtain the bit error rate value P of each solutionb；
And step 9: updating the global optimal solution in the step 5, namely selecting the minimum value of the bit error rate in the step 8, and taking the corresponding solution as the updated global optimal solution;
step 10: updating the loudness in step 7, and comparing the loudness in step 7
Figure FDA00026431870800000212
Updating is performed by substituting the following formula:
Figure FDA0002643187080000031
alpha epsilon (0,1) is a constant,
Figure FDA0002643187080000032
representing the updated loudness, the updated loudness for use the next time step 7 is performed;
step 11: updating the pulse emissivity in the step 7, and substituting the pulse emissivity in the step 7 into the following formula for updating: r isi t+1＝ri 0(1-e-γt)，ri t+1Is the updated pulse emissivity, ri 0Is the pulse emissivity at the time of parameter initialization setting in step 2, and gamma > 0 isA constant, the updated pulse emissivity is ready for use when step 7 is executed next time;
step 12: and (5) repeatedly executing the steps 5 to 11 until the maximum repeated execution times set in the step 2 is reached, outputting the global optimal solution updated in the step 9, and finishing the optimization of the high-order APSK constellation mapping chart.
2. The constellation mapping method for reducing bit error rate of joint coded modulation system according to claim 1, wherein:
the step 6 updates the solution x in the step 3ijThe specific updating method is as follows:
randomly generating a random number between 0 and 1, which is represented by rand (0,1), if rand (0,1) < P, wherein P represents habitat selection probability, the updating method is as follows:
Figure FDA0002643187080000033
wherein
Figure FDA0002643187080000034
Representing a solution when step 5 is performed the t-th time,
Figure FDA0002643187080000035
represents the average of all solutions when step 5 is performed for the t-th time, N is the number of solutions in step 3, theta is the coefficient of contraction and expansion, uij∈[0,1]Uniform distribution is obeyed;
if rand (0,1) is not less than P, the updating method is as follows:
fij＝fmin+(fmax-fmin)*rand(0,1)
Figure FDA0002643187080000036
Figure FDA0002643187080000041
Figure FDA0002643187080000042
wherein f isijRepresents the frequency, f 'corresponding to the ith value'ijRepresenting the frequency, f, after adaptive compensation of the Doppler effectmin、fmaxFor the minimum and maximum values of frequency, depending on the specific search environment, c (c 340m/s) is the speed of sound in air, v ∈ [0,1]In order to obtain the flying speed of the aircraft,
Figure FDA0002643187080000043
indicates the flight speed at the time of execution of step 6 for the t-th time,
Figure FDA0002643187080000044
represents the flight speed corresponding to the global optimal solution when step 6 is executed the t-th time,
Figure FDA0002643187080000045
represents the flying speed at the time of t +1 th execution of step 6,
Figure FDA0002643187080000046
j-th value, C, representing the i-th solution from step 6 performed the t + 1-th timei∈[0,1]The doppler effect compensation rate is expressed as an infinitesimal number, and w ═ rand (0,1) represents the inertial weight.
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