CN103166903B - The soft solution preprocess method of constellation mapping and soft solution method - Google Patents
The soft solution preprocess method of constellation mapping and soft solution method Download PDFInfo
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Abstract
本发明公开一种星座映射的软解预处理方法以及软解方法，解决了现有的Max-Log-MAP方法运算量大、系统资源占用多以及硬件实现成本高等问题。所述星座映射的软解预处理方法包括步骤：根据所采用的星座映射将包含有M个星座点的信号空间划分为N个区域；构建表B，在表B中记录有区域i内用于对数似然比计算的星座点集Si；i为不大于N的正整数；Si包括星座点子集以及星座点子集包含了第k比特位为0且与区域i内预设点距离最近的星座点；包含了第k比特位为1且与区域i内预设点距离最近的星座点；k为不大于log2M的正整数。星座映射的软解方法为：接收并判定信息符号所属的区域i；读取表B，并按预设方法对信息符号以及Si中的星座点进行对数似然比计算。
The invention discloses a soft-solution preprocessing method and a soft-solution method for constellation mapping, which solves the problems of the existing Max-Log-MAP method with large calculation amount, large system resource occupation, and high hardware implementation cost. The soft-solution preprocessing method of the constellation mapping includes the steps of: dividing the signal space containing M constellation points into N regions according to the adopted constellation mapping; Constellation point set S i calculated by logarithmic likelihood ratio; i is a positive integer not greater than N; S i includes a subset of constellation points and the constellation point subset Contains the constellation point whose k-th bit is 0 and is closest to the preset point in area i; Constellation points whose k-th bit is 1 and which are the closest to preset points in area i are included; k is a positive integer not greater than log 2 M. The soft-solution method of constellation mapping is: receive and determine the area i to which the information symbol belongs; read table B, and calculate the logarithmic likelihood ratio of the information symbol and the constellation points in S i according to the preset method.
Description
Technical Field
The invention relates to the field of digital information communication, in particular to a constellation mapping soft-solution preprocessing method and a constellation mapping soft-solution method.
Background
The currently most commonly used soft solution method for constellation mapping includes the following steps:
step 1: receiving an information symbol;
step 2: obtaining a Log-likelihood ratio through a formula (2) according to each bit in the information symbol and each constellation point in a signal space, wherein the method is called as a Max-Log-MAP algorithm;
a Log-Likelihood Ratio LLR (Log-likehood Ratio) is commonly used to express soft information for each bit in an information symbol;
for a certain bit b, its log-likelihood ratio is defined as:
the obtained sign of the log-likelihood ratio represents the decision result of the bit, the absolute value of the log-likelihood ratio is the confidence of the result, and soft demapping is completed after the log-likelihood ratio is obtained.
For example, in an additive White Gaussian noise awgn (additive White Gaussian noise) channel model, the mapping order is M, that is, in a constellation diagram including M constellation points:
wherein G isiEstimating channel fading (namely channel state information) of the ith information symbol obtained before demapping; for the ith received symbol yi;a set of constellation symbols (i.e. constellation points) representing the kth bit as 1,representing a set of constellation symbols with the k-th bit being 0.
As can be seen from the above, if the Max-Log-MAP method is used to obtain the Log likelihood ratio of each bit in the information symbol, o (M) times of addition, o (M) times of multiplication, and o (mlogm) times of comparison are required, so that it can be seen that when the mapping order M value in the constellation is large, the calculation amount is large, and thus, the consumed system resources are large, and the cost of hardware implementation is large.
Disclosure of Invention
Technical problem to be solved
The invention aims to provide a constellation mapping soft-solution preprocessing method and a constellation mapping soft-solution method, which can reduce the calculation amount and the calculation time of a log-likelihood ratio, reduce the system resource occupation and reduce the hardware implementation cost.
(II) technical scheme
In order to solve the above problems, the soft solution preprocessing method for constellation mapping of the present invention comprises the following steps:
dividing a signal space containing M constellation points into N areas according to the adopted constellation mapping;
constructing a table B in which a constellation point set S for log likelihood ratio calculation in a region i is recordedi(ii) a i is an integer no greater than N;
wherein,
said SiComprising a subset of constellation pointsAnd constellation point subsets
The above-mentionedThe constellation point which contains the kth bit position as 0 and is closest to the preset point in the area i;
the above-mentionedThe constellation point comprises a constellation point with the kth bit position being 1 and the nearest distance to a preset point in the area i;
k is not more than log2A positive integer of M.
Further, in the soft solution preprocessing method for constellation mapping, one or more preset points are set in the region i according to the constellation mapping, the region division and the performance requirement.
Further, the constellation point set SiThe inner constellation points are calculated and obtained through a Monte Carlo algorithm or a greedy algorithm.
Further, the table B is stored in a random access memory, a read only memory, or a combinational logic circuit.
In order to solve the above problems, the soft solution method for constellation mapping of the present invention, after being used for the preprocessing performed by the soft solution preprocessing method for constellation mapping, comprises the following steps:
receiving an information symbol, and judging a region i to which the information symbol belongs;
obtaining constellation point set S of region i to which information symbol belongs for log likelihood ratio calculation from table BiAnd according to the preset method, the information symbol and SiThe constellation points in (1) are subjected to log likelihood ratio calculation.
Preferably, the preset method is a formula
wherein, LLR is a log-likelihood ratio; bkIs the kth bit of the information symbol, and k is not greater than log2A positive integer of M.
Preferably, the region to which the information symbol belongs is determined by a hard decision method.
Preferably, after receiving the information symbol and before determining the region to which the information symbol belongs, the method further includes performing normalization processing on the information symbol by using channel state information, so as to obtain a normalized information symbol.
(III) advantageous effects of the invention
In the soft solution process of constellation mapping, information symbols which are usually located at close positions in a signal space are discovered through repeated research and verification, when the Log-likelihood ratio of each bit is calculated, points which are closest to the constellation points with the same ordinal number of 0 or 1 are concentrated at certain special positions in the signal space, and in the traditional Max-Log-MAP method, when the Log-likelihood ratio of each bit in the information symbols is calculated, the calculation is carried out with all constellation points without screening;
the constellation mapping soft solution preprocessing method of the invention screens the special points by utilizing the rule, and the constellation mapping soft solution method of the invention utilizes the solved result obtained by the constellation mapping soft solution preprocessing method of the invention to carry out the operation of the log-likelihood ratio, thereby greatly reducing the operation amount, reducing the occupation of system resources and reducing the cost of hardware realization, and particularly for constellation mapping with large mapping order, the soft solution effect is particularly obvious.
Drawings
Fig. 1 is a schematic signal space diagram according to a first embodiment of the present invention;
fig. 2 is a flowchart of a soft solution method for constellation mapping according to a second embodiment of the present invention;
FIG. 3 is a signal space diagram according to a fourth embodiment of the present invention;
FIG. 4 is a schematic diagram of the signal space of FIG. 3 divided into a plurality of regions;
FIG. 5 is a graph comparing the performance of the soft solution method of constellation mapping according to the fourth embodiment of the present invention with the conventional Max-Log-MAP method under AWGN channel;
fig. 6 is a graph comparing the performance of the soft solution method for constellation mapping according to the fourth embodiment of the present invention with that of the conventional Max-Log-MAP method in the i.i.d.rayleigh channel.
Detailed Description
The soft solution preprocessing method for constellation mapping according to the present invention is further described with reference to the drawings and embodiments of the present disclosure.
The first embodiment is as follows:
as shown in fig. 1, the soft solution preprocessing method for constellation mapping in this embodiment includes the following steps:
dividing a signal space containing 16 constellation points into 4 regions according to the adopted constellation mapping; each region is distinguished by different shades, the number at the center of each region represents the number of the region, and each region comprises 4 constellation points; each information symbol comprises 4 bits;
constructing a table B; in table B, a constellation point set S for log likelihood ratio calculation in the region i is recordedi(ii) a i is an integer no greater than 4, i is 1, 2, 3 or 4; specifically, region 1, region 2, region 3, and region 4 as described in fig. 1;
wherein,
said SiComprising a subset of constellation pointsAnd constellation point subsets
The above-mentionedThe constellation point which has the kth bit position of 0 and is closest to a preset point in the region i, namely a point p is included;
the above-mentionedThe constellation point which has the kth bit position of 1 and is closest to a preset point, namely a point p, in the region i is included;
k is not more than log2A positive integer of M, i.e., 4 or less;
constructing a table B; a constellation point set used for calculating the log likelihood ratio in each region is recorded in the table B;
for example, in the region 1, when the preset point is one and is the central point of the region 1, the constellation point set includes a subset of constellation points whose first high bit is 0 And a subset of constellation points with a high first bit of 1Therefore, in the calculation process, the information symbols only need to be operated with 4 constellation points with the high-order first bit being 0 and 2 constellation points with the high-order first bit being 1, and compared with the traditional Max-Log-MAP method, the information symbols are operated with 8 constellation points with the high-order first bit being 0 and 8 constellation points with the high-order first bit being 1, the calculation amount is saved, and the calculation amount is reducedThe consumption of system resources and the hardware implementation cost are lower.
In the traditional Max-Log-MAP method, a soft solution preprocessing process of constellation mapping is not adopted, wherein each operation comprises the calculation of M/2 constellation points with the same sequence position as an information symbol being 0 or 1; in the soft solution preprocessing method for constellation mapping of the present embodiment, the closest point that may occur in the subsequent log-likelihood ratio calculation is firstly determined through preprocessing, so that not only are the multiplication and addition operations between the information symbols and the constellation points reduced; and the comparison operation is also reduced, and the optimization effect is particularly obvious when the method is applied to the soft solution process of high-order constellation mapping.
In a specific implementation process, the preset points are distributed at different positions of the region i according to one or more requirements of constellation mapping, region division and performance; the higher the accuracy requirement, the more the preset points should be taken. As in the area 1, when the preset points include the center position of the area 1 and two edge points, and one of the edge points is located at the center point of the edge line bordering on the area 2, and the other edge point is located at the center point of the edge line bordering on the area 3; said set of constellation points comprises a subset of constellation points with a high first bit of 0 And a subset of constellation points with a high first bit of 1
As can be seen from the above, the number and the positions of the preset points are related to the composition of the constellation point subsets, and also related to the accuracy of the final operation result, so in the specific implementation process, the positions and the numbers of the preset points are determined according to the region division, the constellation mapping and the performance requirements, and when the number of the preset points is 1, the preset points are usually selected as the center of the constellation point in the region.
In a specific implementation process, the areas should be divided according to different types of constellation mapping, the precision requirement on the solving result and the size of the calculation amount, and the divided areas should not be too large.
Example two:
on the basis of the above embodiment, the soft solution preprocessing method for constellation mapping in this embodiment provides two methods for obtaining a constellation point set,
the constellation point set SiThe inner constellation points are calculated by a Monte Carlo algorithm or a greedy algorithm.
The method comprises the following steps: the Monte Carlo algorithm finds:
repeatedly verifying the constellation point set on the basis of statistics and probability to obtain the constellation point set;
the second method comprises the following steps: greedy algorithm solving:
a: defining the distance of a point in the information symbol signal space to the region i,
b: then calculateAndn is the nth bit of the information symbol, and n is not more than log2The distance from all points in M (M is the mapping order of the constellation diagram) to the region i, and a plurality of shortest points are taken asDenoted as the ith region, u is denoted as the u-th bit of the received information symbol; w is 0 or 1; wherein the distance from the constellation point in the signal space to the region i can beIn a different way of definition. In particular, when there is one and only one constellation point in the region i, the euclidean distance to this point can be taken as the distance to the region i.
In this embodiment, two methods for obtaining each region to solve log-likelihood ratios of each bit of an information symbol are specifically provided, which have the advantages of simple and convenient implementation.
In summary, the number of constellation point subsets included in the constellation point set is at most 2 × log2M。
In the soft solution preprocessing method for constellation mapping of this embodiment, two preferable methods for solving constellation point sets are provided, and both the two methods are mature in technology and simple and convenient to apply, so that the soft solution preprocessing method for constellation mapping of this embodiment has the characteristics of simplicity and convenience in use.
In particular, the table B is stored in a random access memory, a read only memory or a combinational logic circuit. The number of constellation points in the constellation point set is different according to the region, the constellation mapping mode and the implementation mode, and is usually much smaller than the mapping order M of the constellation mapping.
The soft solution method of constellation mapping according to the present invention is further described with reference to the drawings and embodiments of the present disclosure.
The first embodiment:
the soft solution method for constellation mapping in this embodiment is applied to the preprocessing performed by the soft solution preprocessing method for constellation mapping, and specifically includes the following steps:
receiving an information symbol, and judging a region i to which the information symbol belongs;
obtaining constellation point set S of region i to which information symbol belongs for log likelihood ratio calculation from table BiAnd according to the preset method, the information symbol and SiThe constellation points in (1) are subjected to log likelihood ratio calculation.
In the soft solution method for constellation mapping in this embodiment, the table B for Log likelihood ratio calculation is obtained by the soft solution preprocessing method for constellation mapping as described in the first embodiment or the second embodiment, and the number of constellation points recorded in the table B is much smaller than the number of constellation points for which the Max-Log-MAP method needs to perform Log likelihood ratio calculation, so that the amount of calculation is reduced, meanwhile, the occupation of system resources is reduced, and the cost for hardware implementation is reduced. Particularly, in high-order constellation mapping, one information symbol carries a large number of bits, and a large number of constellation points are provided in an information space, however, when points closest to any point in the area i are concentrated at some special positions and calculated by adopting a traditional Max-Log-MAP method, a large number of calculations which are obviously not beneficial to a final result are performed, and in the embodiment, useless points are screened out by a preprocessing method, so that the purpose of reducing the calculation amount is achieved.
As a further improvement of this embodiment, the soft solution method of constellation mapping of this embodiment further provides a solution method of log likelihood ratio of each bit in the information symbol, specifically by the following formula
The preset method is a formula
Calculating a log-likelihood ratio for each bit in the information symbol;
wherein, LLR is a log-likelihood ratio; bkIs the kth bit of the information symbol, and k is not greater than log2A positive integer of M.
E.g., 16-order constellation mapping, each information symbol and constellation point in the signal space are composed of 4 bits (e.g., 0000, 1111, etc.). With 256-order constellation mapping, each information symbol in the signal space and the constellation point are composed of 8 bits (e.g., 00010010, etc.).
By the formula, the constellation mapping method has the advantages of direct and simple operation when soft solution of constellation mapping is performed, the solving of the log-likelihood ratio of each bit of the information symbol by adopting the constellation mapping soft solution method is convenient and quick, the operand is small, the occupied resource of the system is less, and the realization cost is low in the specific hardware realization process.
Second embodiment:
as shown in fig. 2, the soft solution method for constellation mapping in this embodiment includes the following steps:
a preprocessing step implemented by the constellation mapping soft solution preprocessing method according to the first embodiment or the second embodiment;
step S1: receiving an information symbol;
step S2: and carrying out normalization processing on the received information symbols by utilizing the channel state information so as to obtain normalized information symbols. When the state of the channel changes, normalization processing is usually performed on the received information symbols according to the attenuation estimation of the signal, so as to obtain information symbols with the same strength and weakness for subsequent processing;
step S3: judging the area i to which the information symbol belongs;
step S4: and acquiring a constellation point set of the information symbol region i for calculating the log-likelihood ratio from the table B, and calculating the log-likelihood ratio of the information symbols and the constellation points in the constellation point set according to a preset method.
By adopting the constellation mapping soft solution method described in this embodiment, the log-likelihood ratio of each bit of the information symbol is solved to obtain a final soft solution result, and the method has the multiple advantages of less calculation amount, less system resources, less operation time and the like.
The third embodiment:
the soft solution method for constellation mapping in the embodiment comprises the following steps:
step S1: receiving an information symbol, and judging the region to which the information symbol belongs; in a specific implementation process, a hard decision (i.e., comparing with a region division boundary) may be adopted to determine a region to which an information symbol belongs; hard decision is a technically mature decision method applied to decoding, and is not described herein in detail;
step S2: obtaining a constellation point set of a region where the information symbol belongs for calculating a log-likelihood ratio from the table B, and calculating the log-likelihood ratio of the information symbol and the constellation point in the constellation point set according to a preset method;
wherein, the table B is obtained by a soft solution preprocessing method of constellation mapping; the soft solution preprocessing method of the constellation mapping further comprises the following steps:
s0.1, dividing a signal space containing M constellation points into N areas according to the adopted constellation mapping;
s0.2, constructing a table B; in table B, a constellation point set S for log likelihood ratio calculation in the region i is recordedi(ii) a i is an integer no greater than N;
in the embodiment, hard decision is preferred, and by adopting the mature decision method, on one hand, the realizability of decision is ensured, and simultaneously, the simplicity and the rapidness of realization are ensured, and meanwhile, the table B generated in the preprocessing process is adopted to solve the subsequent log-likelihood ratio, so that the computation amount is small, the result acquisition time is short, the system resources are few, and the hardware realization cost is low.
The fourth embodiment:
as shown in fig. 3-6, the soft solution method for constellation mapping in this embodiment applies an environment in which the constellation mapping is Gray-APSK (Amplitude-Phase Shift Keying) of 256 steps; the channel coding adopts LDPC Code in DVB-S2 standard, Low Density Parity Check Code Low Density Parity Check Code; the LDPC decoding algorithm adopts an improved minimum sum algorithm, and the maximum iteration number is 50; the transmission channel is an AWGN (additive White Gaussian noise) channel or an i.i.d.Rayleigh channel, namely an independent Rayleigh channel;
wherein the signal space shown is a circular signal space as shown in fig. 3;
first, the preprocessing of the constellation mapping to the table B is performed as follows:
dividing a signal space containing 256 constellation points into 256 regions according to the adopted constellation mapping, wherein the divided signal space is shown in fig. 4;
constructing a table B; in table B, a constellation point set S for log likelihood ratio calculation in the region i is recordedi(ii) a i is an integer no greater than 256;
wherein,
said SiComprising a subset of constellation pointsAnd constellation point subsets
The above-mentionedThe constellation point which contains the kth bit position as 0 and is closest to the preset point in the area i;
the above-mentionedThe constellation point which has the kth bit position of 1 and is closest to the preset point in the area i is included; in this embodiment, the preset points are points at positions where constellation points are located in each region;
k is not more than log2Positive integer of M
Receiving information symbols and channel state information;
carrying out normalization processing on the information symbol by using the channel state information to obtain a processed normalized information symbol;
judging the area to which the normalized information symbol belongs;
and obtaining a constellation point set of the region where the information symbol belongs for calculating the log-likelihood ratio from the table B, and calculating the log-likelihood ratio of the information symbol and the constellation point in the constellation point set according to a preset method.
The soft solution method for constellation mapping according to this embodiment is applied to the following table compared with the operation speed and operation amount of the conventional Max-Log-MAP method in the communication with the above parameters:
in addition, the performance of the soft solution method for constellation mapping described in this embodiment is also very small compared to the difference in the system error rate of the conventional Max-Log-MAP method, which is specifically shown in fig. 5 to 6:
fig. 5 is a comparison diagram of the soft solution method of constellation mapping according to this embodiment and the Max-Log-MAP method when the transmission channel is an AWGN channel (Additive White Gaussian Noise) channel.
Fig. 6 is a comparison diagram of the soft solution method of constellation mapping according to the present embodiment and the Max-Log-MAP method when the transmission channel is an i.i.d. rayleigh channel, i.e. an independent rayleigh channel.
From the above, it can be seen that the soft solution method for constellation mapping according to this embodiment greatly reduces the computation amount of the log-likelihood ratio of each bit of the information symbol under the condition of almost no performance loss, and especially has an especially obvious effect in high-order constellation mapping such as 256-order constellation mapping, thereby reducing the system resources occupied during the decision in the soft solution process and also reducing the cost of hardware implementation.
The above embodiments are only for illustrating the invention and are not to be construed as limiting the invention, and those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention, therefore, all equivalent technical solutions also belong to the scope of the invention, and the scope of the invention is defined by the claims.
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| CN104506479B (en) * | 2014-12-23 | 2017-11-10 | 湖南基石通信技术有限公司 | The soft de-mapped implementation method and device of a kind of modulated signal |
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