WO2012051854A1 - 一种定点化软信息优化的方法和系统 - Google Patents

一种定点化软信息优化的方法和系统 Download PDF

Info

Publication number
WO2012051854A1
WO2012051854A1 PCT/CN2011/074782 CN2011074782W WO2012051854A1 WO 2012051854 A1 WO2012051854 A1 WO 2012051854A1 CN 2011074782 W CN2011074782 W CN 2011074782W WO 2012051854 A1 WO2012051854 A1 WO 2012051854A1
Authority
WO
WIPO (PCT)
Prior art keywords
soft information
information
bit
likelihood distance
likelihood
Prior art date
Application number
PCT/CN2011/074782
Other languages
English (en)
French (fr)
Inventor
严妙奇
董志峰
Original Assignee
中兴通讯股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 中兴通讯股份有限公司 filed Critical 中兴通讯股份有限公司
Publication of WO2012051854A1 publication Critical patent/WO2012051854A1/zh

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/06—Dc level restoring means; Bias distortion correction ; Decision circuits providing symbol by symbol detection
    • H04L25/067—Dc level restoring means; Bias distortion correction ; Decision circuits providing symbol by symbol detection providing soft decisions, i.e. decisions together with an estimate of reliability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/38—Demodulator circuits; Receiver circuits

Definitions

  • the invention relates to a soft information acquisition technology in Quadrature Amplitude Modulation (QAM), in particular to a method and system for fixed-point soft information optimization.
  • QAM Quadrature Amplitude Modulation
  • the channel encoder typically uses QAM for the encoding of signals, and this typical multi-level modulation can increase spectral efficiency.
  • the demodulator in the receiver calculates the maximum posterior probability ratio of the received signal, ie, the likelihood ratio, as the soft information, and outputs the translation signal.
  • the coder performs decoding.
  • the method of looking up the table will be used to find the likelihood ratio, and some similar algorithms will be obtained for the likelihood ratio.
  • the amplitude and phase of the modulated signal points can be different, and the constellation structure makes the Euclidean distance of some bits of the received signal larger.
  • the fixed-point decoder has a limited effective bit of the input soft information.
  • the soft information of these large-scale Bits will occupy too many valid bits, and the accuracy of the soft information of the Bit with a small Euclidean distance is suppressed.
  • the soft information of a bit with a large Euclidean distance the information provided to the decoder is already saturated. Therefore, how to suppress the saturation information occupying the bit bits of valid soft information is a problem that needs to be solved.
  • the output of the digital soft demodulator is the likelihood ratio of a certain bit, which can be expressed as:
  • R represents the possible value of the received signal and P represents the conditional probability for s.
  • the likelihood ratio is a monotonic function of the received signal r, in practice, the output of the demodulator is an approximation of the likelihood ratio, the so-called likelihood distance, represented by ⁇ .
  • equation (3) can be further approximated.
  • the soft information output of each bit further approximated by 16QAM modulation is shown in equation (4):
  • FIG. 57 3 real(r) ( 4 )
  • Figure 1 shows the constellation diagram of an example during 16QAM modulation.
  • a in equation (4) represents the distance from point A of the graph to the origin of the coordinate.
  • the distance of r from the abscissa is im 8 (H* )
  • the soft information of Bit3 and Bitl differs by about 3 squares, that is, 9 times, and in fact, the channel conditions experienced by Bit3 and Bitl are the same as the noise interference.
  • Bitl's soft information is only 1/9 of Bit3's soft information, which cannot be improved.
  • the present invention provides a method for fixed-point soft information optimization, the method comprising: obtaining a likelihood distance of the signal by using a channel estimation value and a frequency domain received signal of a baseband; and unifying a likelihood distance in the modulation coded block Calibration, and the optimized soft information is obtained according to the likelihood distance of the unified calibration.
  • the soft information obtained according to the likelihood distance of the unified calibration includes: a likelihood distance after uniform scaling under a high SNR condition, first removing redundant information, and then using soft information nonlinear mapping
  • the table performs the search to obtain the optimized soft information; and the optimized distance after the uniform scaling under the low SNR condition, the optimized soft information is obtained according to the likelihood distance.
  • the removing the redundant information includes: shifting the likelihood distance after the unified calibration to the left by two bits of saturation shift, and when there is an overflow, taking the maximum value, the symbol bit is retained, and then the data is taken.
  • Bit7 to Bitl5 are used as soft information after removing redundant information.
  • the searching by using the soft information non-linear mapping table is: extracting the sign bit of the soft information after removing the redundant information, and extracting the absolute value of the soft information after removing the redundant information as a soft information non-linear mapping
  • the index subscript of the table, according to the index subscript search to obtain the soft information value in the corresponding table, and then multiply the soft information value in the table by the sign bit to obtain the optimized soft information.
  • the unified calibration is: polling all the bits of the entire modulation coding block, finding the bit with the smallest sign bit of all Bit soft information, and recording the minimum bit of the Bit as Min _ Scale. Then poll the Bit of the entire modulation coding block, calculate the sign bit of the soft information of each bit, denote it as ⁇ raZe; and shift the soft information of each bit to the left by ⁇ '.
  • the present invention also provides a system for fixed-point soft information optimization, the system comprising: a likelihood distance determination module and a soft information optimization module;
  • the likelihood distance determining module is configured to obtain a likelihood distance of the signal by using a channel estimation value and a frequency domain received signal of a baseband, and send the likelihood distance to the soft information optimization module;
  • the soft information optimization module is configured to uniformly scale the likelihood distances in the modulation coded block, and obtain the optimized soft information according to the likelihood distance of the unified calibration.
  • the method and system for the fixed-point soft information optimization provided by the present invention obtains the likelihood distance of the signal by using the channel estimation value and the frequency domain received signal of the baseband; uniformly scaling the likelihood distance in the modulation coded block; The likelihood distance of the unified calibration is obtained by the optimized soft information.
  • the soft information is too large, the valid bits occupied by the redundant information can be released to protect the amount of information contained in the smaller soft information, so that the data bits of the limited soft information are fully utilized, thereby optimizing the QAM demodulation system. performance.
  • Figure 1 is a constellation diagram of an example of 16QAM modulation
  • FIG. 2 is a schematic flow chart of a method for determining a soft information optimization according to the present invention
  • FIG. 3 is a schematic diagram of a specific process of a method for determining a soft information optimization according to the present invention.
  • FIG. 4 is a schematic structural diagram of a system for fixed-point soft information optimization according to the present invention. detailed description
  • the basic idea of the present invention is: obtaining the likelihood distance of the signal by using the channel estimation value and the frequency domain received signal of the baseband; uniformly scaling the likelihood distance in the modulation coded block; obtaining the likelihood distance according to the uniform calibration Optimized soft information.
  • FIG. 2 is a schematic flowchart of a method for determining a soft information optimization according to the present invention. As shown in FIG. 2, the method for optimizing includes the following steps:
  • Step 201 Obtain a likelihood distance of the signal by using a channel estimation value and a frequency domain received signal of a baseband;
  • the likelihood distance of the received signal is obtained according to a maximum posterior probability criterion.
  • Step 202 Perform uniform calibration on the likelihood distance in each modulation code block.
  • the purpose of uniformly scaling the likelihood distances in a modulation coded block is to make the significant bit of the largest data in each of the coded blocks the highest bit except the sign bit. It should be noted that, in the process of making the significant bit of the largest data in the coding block into the highest bit except the sign bit, the sign bit is to be reserved; wherein the modulation code block can be understood as a data packet.
  • Step 203 Obtain optimized soft information according to a likelihood distance of the unified calibration.
  • the optimized soft information according to the likelihood distance of the unified calibration includes: a likelihood distance after unified calibration under a high SNR condition, first removing redundant information, and then using soft information non- The linear mapping table is searched to obtain the optimized soft information.
  • the optimized soft information can be approximated according to the prior art.
  • FIG. 3 is a schematic flowchart of a method for optimizing soft information optimization according to the present invention. As shown in FIG. 3, the specific process includes the following steps:
  • Step 301 Perform channel estimation by using a priori information to obtain a channel estimation value.
  • the a priori information may be information obtained in a previous frame, or pilot information.
  • Step 302 Calculate a likelihood distance of each Bit soft information by using Equation (4) according to the channel estimation value and the frequency domain received signal of the baseband;
  • Step 303 Perform uniform calibration on the likelihood distance in the modulation coded block.
  • the performing unified calibration includes: polling all the bits of the entire modulation coding block, finding the bit with the smallest sign bit of all Bit soft information, and recording its sign bit as Min_Scale. Then The bit of the entire modulation coding block is polled, and the sign bit of the soft information of each bit is calculated, which is recorded as Scale, and the soft information of each bit is shifted to the left by - M bits, and the uniform calibration is completed.
  • Step 304 estimating the signal to noise ratio of the coded block according to the first risk information, when the signal to noise ratio is greater than a certain threshold, step 305 is performed, otherwise step 306 is performed;
  • the threshold of the signal to noise ratio may be set according to actual conditions of the network. Step 305, first removing redundant information, and then performing a search by using a soft information non-linear mapping table to obtain optimized soft information, and ending the processing flow;
  • the removing the redundant information is specifically: performing a saturation shift of the left bit by 2 bits after the unified scaling, that is, shifting 2 bits to the left, and if there is overflow, taking the maximum value, and the symbol bit is reserved. And taking the data of Bit7-Bitl 5, obtaining the soft information 5 after removing the redundant information, and searching according to the soft information 5 using the soft information non-linear mapping table to obtain the optimized soft information.
  • Step 306 Approve the optimized soft information according to the likelihood distance after the unified calibration and the prior art.
  • the method further includes sending to the decoder for decoding.
  • the soft information non-linear mapping table is preset in the QAM decoder, and the specific content is as shown in Table 1.
  • the method for searching is specifically: extracting a sign bit of the soft information S, the identifier is P, and extracting the absolute value of the soft information 5 as an index subscript of the table 1, that is, an index in the table 1; The soft information value Soft_Infor in the corresponding table is then multiplied by SofUnfor to obtain the optimized soft information.
  • FIG. 4 is a schematic structural diagram of a system for fixed-point soft information optimization according to the present invention. As shown in FIG. 4, the system is located in a QAM demodulator, and includes: a likelihood distance determining module 41 and a soft information optimization module 42, wherein
  • the likelihood distance determining module 41 is configured to obtain a likelihood distance of the signal by using a channel estimation value and a frequency domain received signal of the baseband, and send the likelihood distance to the soft information optimization module 42;
  • the likelihood distance determining module 41 uses the channel estimation value and the frequency domain received signal of the baseband to determine the likelihood distance of the received signal according to the maximum posterior probability criterion.
  • the soft information optimization module 42 is configured to uniformly scale the likelihood distances in each of the modulation coded blocks, and obtain the optimized soft information according to the likelihood distance of the unified calibration.
  • the purpose of the soft information optimization module 42 to uniformly scale the likelihood distance in each modulation code block is to: make the significant bit of the largest data in the code block into the highest bit except the sign bit.
  • the symbol bit is reserved; wherein the modulation coding block can be understood as a data packet.
  • the unified calibration includes: polling all Bits of the entire modulation coding block, finding the bit with the smallest sign bit of all Bit soft information, and recording its sign bit as Min_Scale. Then coding the entire modulation The bit of the block is polled, and the sign bit of the soft information of each bit is calculated, which is recorded as Scale, and the soft information of each bit is shifted to the left by ⁇ e_M bit to complete the unified calibration.
  • the soft information obtained according to the likelihood distance of the unified calibration specifically includes: a likelihood distance after unified calibration under a high SNR condition, first removing redundant information, and then using a soft information nonlinear mapping table Perform a search to obtain optimized soft information; for low SNR conditions
  • the likelihood distance after a certain standard can be approximated to obtain the optimized soft information according to the prior art.
  • the condition for distinguishing the high SNR and the low SNR is to set a threshold according to the actual situation of the network.
  • a value greater than the threshold belongs to a high SNR, and a value less than or equal to the threshold belongs to a low SNR.
  • the removing redundant information is specifically as follows: the likelihood distance after the unified calibration is shifted to the left by 2 bits, that is, the left shift is 2 bits, and if there is overflow, the maximum value is taken, the sign bit is reserved, and Bit7-Bitl5 of the data obtains the soft information with the redundant information removed, and then searches according to the soft information S by using the soft information non-linear mapping table, specifically: extracting the sign bit of the soft information S, and identifying it as ⁇ re-extracting the soft information S The absolute value of ⁇ (as the index subscript of Table 1, that is, the Index in Table 1; SofUnfor is obtained by index subscript search, and then the SofUnfor is multiplied by the sign bit to obtain the optimized soft
  • the QAM demodulator further includes a decoder for decoding the optimized soft information.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Error Detection And Correction (AREA)
  • Digital Transmission Methods That Use Modulated Carrier Waves (AREA)

Abstract

本发明公开了一种定点化软信息优化的方法，所述方法具体包括：利用信道估计值和基带的频域接收信号得到所述信号的似然距离；对调制编码块内的似然距离进行统一定标；根据统一定标的似然距离得到优化后的软信息。本发明还公开了一种定点化软信息优化的系统，通过上述方法和系统，能够在软信息过大时，释放被冗余信息占用的有效位，以保护较小的软信息包含的信息量，使有限的软信息的数据位得到充分的利用，进而优化了正交幅度调制解调系统的性能。

Description

种定点化软信息优化的方法和系统 技术领域
本发明涉及正交幅度调制 （ Quadrature Amplitude Modulation, QAM ) 中软信息的获取技术， 特别是指一种定点化软信息优化的方法和系统。 背景技术
在数据通信系统中， 信道编码器针对信号的编码通常釆用 QAM, 这种 典型的多级调制可以增加频谱效率。 为了通过软判决在接收机的信道译码 器中译码调制信号， 接收机中的解调器通过计算所接收的信号的最大后验 概率比， 即似然比， 作为软信息， 输出给译码器进行译码。 通常情况下为 了简化计算， 会釆用查表的方法来求似然比， 也会对似然比釆取一些近似 的算法。
针对釆用 QAM进行调制，调制信号点的幅度和相位可以各不相同，其 星座结构使得接收信号的某些比特（Bit ) 的欧氏距离会比较大。 但定点化 的译码器其输入软信息的有效位是有限的。 当信噪比较大时， 这些欧式距 离较大的 Bit的软信息会占用过多的有效位， 而抑制了欧式距离较小的 Bit 的软信息的精度。 实际上欧式距离较大的 Bit的软信息，提供给译码器的信 息却已经饱和。 因此， 如何抑制饱和信息占用有效的软信息的 Bit位是需要 解决的问题。
为了更好的理解本发明所解决的问题， 通过数学模型进行进一步的阐 述：
Figure imgf000002_0001
在模型公式（ 1 )中， "服从 ( V。 }的高斯分布； s表示所针对 Bit的信 源， 其中， 1代表 1, -1代表 0; r代表依次输出得到的接收信号的釆样， 代表信道衰落， 代表 s取该值的概率。
数字软解调器的输出就是某一个 Bit的似然比， 可以表示为：
P(s = l/R = r)
LLR =
P(s = -l/R = r)
2ΛΌ2 2W0 2 I
(2)
其中， R代表接收信号可能的值， P代表的是针对 s的条件概率。
这就是所谓的似然比， 由于似然比是接收信号 r的单调函数， 所以实际 上， 解调器的输出是取似然比的近似值， 即所谓的似然距离， 由 ^来表示，
SI=\n(LLR) = LLR
2Ni 2N,
(3)
对公式（3 ) 可以进一步近似， 下面给出 16QAM调制时进一步近似的 各 Bit的软信息输出如公式（4)所示：
SI0 = 2* A-img(r)
5丄 = img(r)
SI2 =2*A-real(r)
573 = real(r) ( 4 ) 图 1为 16QAM调制时一个实例的星座图， 如图 1所示， 公式（4)中 A表示图中 A点距离坐标原点的距离。针对接收信号的釆样 图 1中 为 r距离横坐标的距离 =im8(H* ) , 5/3为 r距离纵坐标的距离 = , 大小大概相差 3倍。由此，可以得出 Bit3和 Bitl的软信息相差约 3的平方， 即 9倍， 而实际上 Bit3和 Bitl经历的信道条件和所受的噪声干扰都是一样 的。 此时， 无论怎样提升发射功率， Bitl的软信息都只有 Bit3的软信息的 1/9, 无法得到改善， 译码器会认为 Bitl的软信息的这种损失是由噪声的干 扰引起的， 从而影响性能的提升。 进一步的， 在 64QAM调制下， 这种影响 更加明显， 某些 Bit的欧氏距离是其他 Bit欧氏距离的 49倍。 发明内容
有鉴于此， 本发明的主要目的在于提供一种定点化软信息优化的方法 和系统， 能够抑制饱和信息占用有效的软信息的 Bit位。
为达到上述目的， 本发明的技术方案是这样实现的：
本发明提供了一种定点化软信息优化的方法， 所述方法包括： 利用信道估计值和基带的频域接收信号得到所述信号的似然距离； 对调制编码块内的似然距离进行统一定标， 并根据统一定标的似然距 离得到优化后的软信息。
其中， 所述根据统一定标的似然距离得到优化后的软信息， 包括： 针对高信噪比条件下统一定标后的似然距离， 先去除冗余信息， 然后 利用软信息非线性映射表进行查找， 得到优化后的软信息； 针对低信噪比 条件下统一定标后的似然距离， 根据所述似然距离得到优化后的软信息。
其中， 所述去除冗余信息， 包括： 将统一定标后的似然距离进行左移 两位的饱和移位， 有溢出时， 则取最大值， 符号位保留， 然后取该数据的
Bit7至 Bitl5作为去除冗余信息后的软信息。
其中， 所述利用软信息非线性映射表进行查找， 为： 提取去除冗余信 息后的软信息的符号位， 再提取所述去除冗余信息后的软信息的绝对值作 为软信息非线性映射表的索引下标， 根据索引下标查找得到对应的表中的 软信息值， 然后用表中的软信息值乘以符号位得到优化后的软信息。
其中， 所述利用信道估计值和基带的频域接收信号得到所述信号的似 然距离， 为： 利用信道估计值和基带的频域接收信号， 根据最大后验概率 准则求取所述接收信号的似然距离。
其中， 所述统一定标， 为： 对整个调制编码块的所有 Bit进行轮询， 找 到所有 Bit 的软信息的符号位最小的 Bit, 将最小的 Bit 的符号位记为 Min _ Scale . 然后对整个调制编码块的 Bit进行轮询， 计算每个 Bit的软信息 的符号位， 记为 ^raZe ; 并对每个 Bit的软信息左移 ^ ―^' 位。
本发明还提供了一种定点化软信息优化的系统， 所述系统包括： 似然 距离确定模块和软信息优化模块； 其中，
所述似然距离确定模块， 用于利用信道估计值和基带的频域接收信号 得到所述信号的似然距离， 将似然距离发送给软信息优化模块；
所述软信息优化模块， 用于对调制编码块内的似然距离进行统一定标， 并根据统一定标的似然距离得到优化后的软信息。
本发明所提供的定点化软信息优化的方法和系统， 利用信道估计值和 基带的频域接收信号得到所述信号的似然距离； 对调制编码块内的似然距 离进行统一定标； 根据统一定标的似然距离得到优化后的软信息。 能够在 软信息过大时， 释放被冗余信息占用的有效位， 以保护较小的软信息包含 的信息量，使有限的软信息的数据位得到充分的利用，进而优化 QAM解调 系统的性能。 附图说明
图 1为 16QAM调制时一个实例的星座图；
图 2为本发明定点化软信息优化的方法流程示意图；
图 3为本发明定点化软信息优化的方法的具体流程示意图；
图 4为本发明定点化软信息优化的系统结构示意图。 具体实施方式
本发明的基本思想是： 利用信道估计值和基带的频域接收信号得到所 述信号的似然距离； 对调制编码块内的似然距离进行统一定标； 根据统一 定标的似然距离得到优化后的软信息。
下面结合附图和具体实施例对本发明的技术方案进一步详细阐述。 图 2为本发明定点化软信息优化的方法流程示意图， 如图 2所示， 所 述优化的方法， 具体包括以下步骤：
步骤 201 ,利用信道估计值和基带的频域接收信号得到所述信号的似然 距离；
具体的， 利用信道估计值和基带的频域接收信号， 根据最大后验概率 准则求取所述接收信号的似然距离。
步骤 202, 对每一个调制编码块内的似然距离进行统一定标；
具体的， 对一个调制编码块内的似然距离进行统一定标的目的是： 使 每一个所述编码块内最大的数据的有效位成为除了符号位以外的最高位。 需要说明的是， 所述使编码块内最大的数据的有效位成为除了符号位以外 的最高位过程中符号位要保留； 其中， 所述调制编码块可以理解为一个数 据包。
步骤 203 , 根据统一定标的似然距离得到优化后的软信息。
具体的， 所述根据统一定标的似然距离得到优化后的软信息， 具体包 括： 针对高信噪比条件下统一定标后的似然距离， 先去除冗余信息， 然后 利用软信息非线性映射表进行查找， 得到优化后的软信息； 针对低信噪比 条件下统一定标后的似然距离， 可以根据现有技术近似得到优化后的软信 息。
进一步的， 在得到优化后的软信息之后还包括发送给译码器进行译码。 图 3为本发明定点化软信息优化的方法的具体流程示意图， 如图 3所 示， 所述具体流程包括以下步骤：
步骤 301 , 利用先验信息进行信道估计， 得到信道估计值；
具体的， 所述先验信息可以是前一帧得到的信息， 或导频信息等。 步骤 302, 根据信道估计值和基带的频域接收信号利用公式（4 )求取 每个 Bit的软信息的似然距离； 步骤 303, 对调制编码块内的似然距离进行统一定标；
具体的， 所述进行统一定标， 包括： 对整个调制编码块的所有 Bit进行 轮询， 找到所有 Bit 的软信息的符号位最小的 Bit, 将它的符号位记为 Min _ Scale . 然后对整个调制编码块的 Bit进行轮询， 计算每个 Bit的软信息 的符号位， 记为 Scale , 同时对每个 Bit的软信息左移 — M 位， 完 成统一定标。
步骤 304,才艮据先险信息估计该编码块的信噪比， 当信噪比大于某一门 限值时， 执行步骤 305, 否则执行步骤 306;
具体的， 所述信噪比的门限值可以根据网络的实际情况进行设置。 步骤 305, 先去除冗余信息， 然后利用软信息非线性映射表进行查找， 得到优化后的软信息， 结束处理流程；
具体的， 所述去除冗余信息， 具体为： 将统一定标过后的似然距离进 行左移 2位的饱和移位， 即左移 2位， 若有溢出， 则取最大值， 符号位保 留， 并取该数据的 Bit7-Bitl 5， 得到去除冗余信息后的软信息 5， 依据软信 息5利用软信息非线性映射表进行查找， 得到优化后的软信息。
步骤 306,根据统一定标后的似然距离， 结合现有技术近似得到优化后 的软信息。
进一步的， 在得到优化后的软信息之后还包括发送给译码器进行译码。 在步骤 305中， 所述软信息非线性映射表预先设置在 QAM解码器中， 具体内容如表 1所示。 所述查找的方法， 具体为： 提取软信息 S的符号位， 标识为 P , 再提取软信息 5的绝对值 作为表 1的索引下标， 即表 1中 的 Index; 根据索引下标查找得到对应的表中的软信息值 Soft_Infor, 然后 用 SofUnfor乘以符号位 得到优化后的软信息。
Index (索引） SofUnfor (软信息）
0 1
1 1
2 1
Figure imgf000008_0001
1^8IS0 Z OAV
Figure imgf000009_0001
8
1^8IS0 Z OAV
Figure imgf000010_0001
6
1^8IS0 Ζ OAV
Figure imgf000011_0001
01
1^8IS0 Z OAV
Figure imgf000012_0001
II
1^8IS0 Ζ OAV 254 127
255 127 表 1
图 4为本发明定点化软信息优化的系统结构示意图， 如图 4所示， 所 述系统位于 QAM解调器中， 包括： 似然距离确定模块 41和软信息优化模 块 42, 其中，
所述似然距离确定模块 41 , 用于利用信道估计值和基带的频域接收信 号得到所述信号的似然距离， 将似然距离发送给软信息优化模块 42;
具体的， 所述似然距离确定模块 41利用信道估计值和基带的频域接收 信号， 根据最大后验概率准则求取所述接收信号的似然距离。
所述软信息优化模块 42 , 用于对每一个调制编码块内的似然距离进行 统一定标， 根据统一定标的似然距离得到优化后的软信息。
具体的， 所述软信息优化模块 42对每一个调制编码块内的似然距离进 行统一定标的目的是： 使所述编码块内最大的数据的有效位成为除了符号 位以外的最高位。
需要说明的是， 所述使所述编码块内最大的数据的有效位成为除了符 号位以外的最高位过程中符号位要保留； 其中， 所述调制编码块可以理解 为一个数据包。 所述进行统一定标， 包括： 对整个调制编码块的所有 Bit 进行轮询， 找到所有 Bit的软信息的符号位最小的 Bit, 将它的符号位记为 Min _ Scale . 然后对整个调制编码块的 Bit进行轮询， 计算每个 Bit的软信息 的符号位， 记为 Scale , 同时对每个 Bit的软信息左移 ^^e— M 位， 完 成统一定标。
所述根据统一定标的似然距离得到优化后的软信息， 具体包括： 针对 高信噪比条件下统一定标后的似然距离， 先去除冗余信息， 然后利用软信 息非线性映射表进行查找， 得到优化后的软信息； 针对低信噪比条件下统 一定标后的似然距离， 可以根据现有技术近似得到优化后的软信息。
其中， 区分高信噪比和低信噪比的条件为根据网络的实际情况设置一 个门限值， 大于门限值的属于高信噪比， 小于等于门限值的属于低信噪比。 所述去除冗余信息， 具体为： 将统一定标过后的似然距离进行左移 2位的 饱和移位， 即左移 2位， 若有溢出， 则取最大值， 符号位保留， 并取该数 据的 Bit7-Bitl5 , 得到去除了冗余信息的软信息 然后依据软信息 S利用 软信息非线性映射表进行查找，具体为：提取软信息 S的符号位，标识为^ 再提取软信息 S的绝对值 Ω ( 作为表 1的索引下标， 即表 1 中的 Index; 根据索引下标查找得到 SofUnfor, 然后用 SofUnfor乘以符号位 得到优 化后的软信息。
进一步的，所述 QAM解调器中还包括译码器，用于对优化后的软信息 进行译码。
以上所述， 仅为本发明的较佳实施例而已， 并非用于限定本发明的保 护范围， 凡在本发明的精神和原则之内所作的任何修改、 等同替换和改进 等， 均应包含在本发明的保护范围之内。

Claims

权利要求书
1、 一种定点化软信息优化的方法， 其特征在于， 所述方法包括： 利用信道估计值和基带的频域接收信号得到所述信号的似然距离； 对调制编码块内的似然距离进行统一定标， 并根据统一定标的似然距 离得到优化后的软信息。
2、 根据权利要求 1所述的方法， 其特征在于， 所述根据统一定标的似 然距离得到优化后的软信息， 包括：
针对高信噪比条件下统一定标后的似然距离， 先去除冗余信息， 然后 利用软信息非线性映射表进行查找， 得到优化后的软信息； 针对低信噪比 条件下统一定标后的似然距离， 根据所述似然距离得到优化后的软信息。
3、 根据权利要求 2所述的方法， 其特征在于， 所述去除冗余信息， 包 括： 将统一定标后的似然距离进行左移两位的饱和移位， 有溢出时， 则取 最大值， 符号位保留， 然后取该数据的 Bit7至 Bitl5作为去除冗余信息后 的软信息。
4、 根据权利要求 2或 3所述的方法， 其特征在于， 所述利用软信息非 线性映射表进行查找， 包括： 提取去除冗余信息后的软信息的符号位， 再 提取所述去除冗余信息后的软信息的绝对值作为软信息非线性映射表的索 引下标， 根据索引下标查找得到对应的表中的软信息值， 然后用表中的软 信息值乘以符号位得到优化后的软信息。
5、 根据权利要求 1或 2所述的方法， 其特征在于， 所述利用信道估计 值和基带的频域接收信号得到所述信号的似然距离， 包括： 利用信道估计 值和基带的频域接收信号， 根据最大后验概率准则求取所述接收信号的似 然距离。
6、 根据权利要求 1或 2所述的方法， 其特征在于， 所述统一定标， 包 括： 对整个调制编码块的所有 Bit进行轮询， 找到所有 Bit的软信息的符号 位最小的 Bit, 将最小的 Bit的符号位记为 '"- 然后对整个调制编码 块的 Bit进行轮询， 计算每个 Bit的软信息的符号位， 记为 Scale 并对每个 Bit的软信息左移 M 位。
7、 一种定点化软信息优化的系统， 其特征在于， 所述系统包括： 似然 距离确定模块和软信息优化模块； 其中，
所述似然距离确定模块， 用于利用信道估计值和基带的频域接收信号 得到所述信号的似然距离， 将似然距离发送给软信息优化模块；
所述软信息优化模块， 用于对调制编码块内的似然距离进行统一定标， 并根据统一定标的似然距离得到优化后的软信息。
8、 根据权利要求 7所述的系统， 其特征在于， 所述软信息优化模块根 据统一定标的似然距离得到优化后的软信息， 包括：
针对高信噪比条件下统一定标后的似然距离， 先去除冗余信息， 然后 利用软信息非线性映射表进行查找， 得到优化后的软信息； 针对低信噪比 条件下统一定标后的似然距离， 根据所述似然距离得到优化后的软信息。
9、 根据权利要求 8所述的系统， 其特征在于， 所述软信息优化模块去 除冗余信息， 包括： 将统一定标过后的似然距离进行左移两位的饱和移位， 有溢出时， 则取最大值， 符号位保留， 然后取该数据的 Bit7-Bitl5作为去除 冗余信息后的软信息。
10、 根据权利要求 8或 9所述的系统， 其特征在于， 所述软信息优化 模块中利用软信息非线性映射表进行查找， 包括： 提取去除冗余信息后的 软信息的符号位， 再提取所述去除冗余信息后的软信息的绝对值作为软信 息非线性映射表的索引下标， 根据索引下标查找得到对应的表中的软信息 值， 然后用表中的软信息值乘以符号位得到优化后的软信息。
PCT/CN2011/074782 2010-10-22 2011-05-27 一种定点化软信息优化的方法和系统 WO2012051854A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201010516704.6 2010-10-22
CN201010516704.6A CN102457471B (zh) 2010-10-22 2010-10-22 一种定点化软信息优化的方法和系统

Publications (1)

Publication Number Publication Date
WO2012051854A1 true WO2012051854A1 (zh) 2012-04-26

Family

ID=45974657

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2011/074782 WO2012051854A1 (zh) 2010-10-22 2011-05-27 一种定点化软信息优化的方法和系统

Country Status (2)

Country Link
CN (1) CN102457471B (zh)
WO (1) WO2012051854A1 (zh)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105071820A (zh) * 2015-07-14 2015-11-18 曹明伟 双流通信系统及其接收端和该接收端的信号解调方法

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101471749A (zh) * 2007-12-28 2009-07-01 三星电子株式会社 为qam-ofdm调制信号产生对数似然比的方法
US20100098194A1 (en) * 2008-10-16 2010-04-22 Andres Reial Method and Apparatus for Simplified Expected Symbol Value Computation and Interference Cancellation in Communication Signal Processing

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1773867B (zh) * 2004-11-08 2012-01-11 华为技术有限公司 Turbo码译码方法
KR101106682B1 (ko) * 2005-10-31 2012-01-18 삼성전자주식회사 다중 안테나 로그 우도 율 생성 장치 및 방법
US8229013B2 (en) * 2008-09-17 2012-07-24 Qualcomm Incorporated Methods and systems for maximum-likelihood detection using post-squaring compensation

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101471749A (zh) * 2007-12-28 2009-07-01 三星电子株式会社 为qam-ofdm调制信号产生对数似然比的方法
US20100098194A1 (en) * 2008-10-16 2010-04-22 Andres Reial Method and Apparatus for Simplified Expected Symbol Value Computation and Interference Cancellation in Communication Signal Processing

Also Published As

Publication number Publication date
CN102457471A (zh) 2012-05-16
CN102457471B (zh) 2015-09-16

Similar Documents

Publication Publication Date Title
CN106911374B (zh) 一种低复杂度软输出空间调制检测方法
JP5579851B2 (ja) 結合ｌｌｒ抽出および優先的確率を使用する統一反復復号アーキテクチャ
JP4563455B2 (ja) 移動通信システムの受信器におけるデコーディングのためのログ近似率演算方法及び装置
US8811548B2 (en) Hypotheses generation based on multidimensional slicing
US9106470B2 (en) Enhanced decoding and demapping method and apparatus for QAM data signals
EP2564535A1 (en) Using a joint decoding engine in a wireless device
EP2281376B1 (en) Method and digital communication device for calculating soft information for received QAM symbols
US9088400B2 (en) Hypotheses generation based on multidimensional slicing
CN101764773A (zh) 格雷编码m-qam调制的并行软比特信息计算的实现方法
KR101704096B1 (ko) 연판정 준 ｍｌ 검출기에서 로그 우도율 클리핑을 수행하는 프로세스 및 그 검출기
CN101938333B (zh) 格雷编码π/M-MPSK调制软比特信息计算方法
JP2009212586A (ja) データ通信システム、ｌｌｒ算出装置及び方法
CN109639301B (zh) 一种基于置信度估计的ftn均衡方法
WO2012051854A1 (zh) 一种定点化软信息优化的方法和系统
CN101518002A (zh) 解调方法
CN106534037B (zh) 一种高阶调制信号的软解调方法
EP2950493B1 (en) Bit likelihood calculation device and bit likelihood calculation method
WO2011101753A1 (en) Blind sir estimation using soft bit values
CN109639618B (zh) 一种适用于高阶正交幅度调制信号的低复杂度软输出解调方法
KR101268751B1 (ko) 수신단에서의 복조 및 디코딩 시스템 및 그 방법
TWI593257B (zh) 處理序列估測的裝置及方法
KR100636372B1 (ko) 위상 오차 추정 장치 및 그를 이용한 위상 오차 보정시스템
CN113055319A (zh) 一种信号均衡方法和装置
CN112332948B (zh) 多业务的传输发送、接收方法、系统、介质及装置
CN111294125B (zh) 信噪比估计方法及装置、计算机可读存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 11833760

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 11833760

Country of ref document: EP

Kind code of ref document: A1