WO2022016657A1 - 一种离散调制信号mimo传输方法 - Google Patents

一种离散调制信号mimo传输方法 Download PDF

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WO2022016657A1
WO2022016657A1 PCT/CN2020/111230 CN2020111230W WO2022016657A1 WO 2022016657 A1 WO2022016657 A1 WO 2022016657A1 CN 2020111230 W CN2020111230 W CN 2020111230W WO 2022016657 A1 WO2022016657 A1 WO 2022016657A1
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distribution
precoding matrix
source
channel
mutual information
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吴泳澎
冯杰
束锋
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Shanghai Jiao Tong University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0426—Power distribution
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/04—Transmission power control [TPC]
    • H04W52/38—TPC being performed in particular situations
    • H04W52/42—TPC being performed in particular situations in systems with time, space, frequency or polarisation diversity
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • the present invention relates to the field of communications, and in particular, to a method for MIMO transmission of discrete modulated signals.
  • the purpose of the present invention is to provide a method for MIMO transmission of discrete modulated signals, which can jointly optimize the coding matrix and the source symbol distribution under ASK modulation and a given MIMO coding matrix. Maximize the mutual information between the symbols of the transmitter and the receiver, thus approaching the Shannon limit theoretically and maximizing the MIMO transmission rate, thus solving the problem that the power gain needs to be further improved in the prior art because the PAS technology does not consider the characteristics of the MIMO itself. problem.
  • the precoding matrix G is adjusted by the gradient descent method to further maximize the mutual information I(x; y);
  • step (S4) judge whether the value of current constellation expansion factor ⁇ , source distribution P x and data coding matrix G converges, if not converge then jump to step (S2);
  • a further improvement of the present invention is that, in step (S2), for any given constellation expansion factor ⁇ , the maximum entropy optimization is performed on the multi-dimensional vector x of the source through Lagrangian multiplication, and finally the mutual information I(x is maximized; y) Determine the optimal constellation spreading factor ⁇ and the source distribution Px of the source multidimensional vector x .
  • step (S3) comprises the following steps:
  • the present invention has the following beneficial effects:
  • the present invention uses the non-uniform modulation technology to make the transmission rate closer to the Shannon limit.
  • the present invention further increases the gain brought by probability amplitude shaping under MIMO by jointly optimizing the precoding matrix and the signal distribution of each channel, aiming at the characteristics of multiple antennas in the MIMO system.
  • FIG. 1 is a structural diagram of a transmitter provided by the present invention.
  • FIG. 2 is a structural diagram of a receiver provided by the present invention.
  • an embodiment of the present invention provides a method for MIMO transmission of discrete modulated signals.
  • the transmitting end jointly optimizes the precoding matrix and the source distribution, theoretically maximizes the mutual information between the symbols at the transmitting end and the receiving end, and combines the existing single-channel probability amplitude shaping technology to realize a MIMO scenario non-uniformly distributed transmission.
  • the discrete modulation signal MIMO transmission method in this embodiment includes the following steps:
  • each ⁇ corresponds to a distribution P x such that H(x) is the largest at this ⁇ .
  • Different ⁇ corresponds to different maximum H(x), we choose the ⁇ that maximizes mutual information I(x, y) and the corresponding distribution P x that maximizes H(x) under this ⁇ .
  • the precoding matrix G is adjusted by the gradient descent method to further maximize the mutual information I(x; y);
  • step (S2) for any given constellation expansion factor ⁇ , the maximum entropy optimization is performed on the source multi-dimensional vector x through Lagrangian multiplication, and finally the optimal mutual information I(x; y) is maximized to determine the optimal The constellation spreading factor ⁇ and the source distribution P x of the source multidimensional vector x .
  • step (S3) comprise the following steps:
  • the present invention uses the existing probability amplitude shaping (PAS) technology to perform non-uniform modulation and identification operations on each channel of signals.
  • PAS probability amplitude shaping
  • the identified bit streams are sent to the channel after passing through modules such as channel coding, interleaving, modulation, and MIMO precoding.
  • each module of the receiver in this example is shown in Figure 2, and each module of the receiver is the inverse process of each module of the transmitter.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Radio Transmission System (AREA)

Abstract

本发明提供了一种离散调制信号MIMO传输方法，该方法的主要特征在于对信源分布和预编码矩阵的联合优化来最大化发送端与接收端符号向量的互信息，以此使传输速率逼近香农极限。在当前预编码矩阵G确定的情况下，对信源向量x的分布的优化通过拉格朗日数乘法来最大化信源熵；在当前信源向量分布确定的情况下，对预编码矩阵G的优化通过梯度下降法来最大化发送与接收向量的互信息。通过联合优化信源分布和预编码矩阵在MIMO场景下实现逼近香农极限的传输速率。发送端确定各路符号的边缘分布后采用概率幅度成型技术进行非均匀调制。本发明基于现有的单路概率幅度成型技术，结合了MIMO系统本身的特点，从理论上实现了针对MIMO场景的最大无差错传输速率。

Description

一种离散调制信号MIMO传输方法 技术领域
本发明涉及通信领域，具体地，涉及一种离散调制信号MIMO传输方法。
背景技术
根据香农公式，当发送功率限制为P，在单位噪声功率的加性高斯白噪声(AWGN)信道上进行可靠传输的成立条件是每个维度上的传输速率不超过容量-功率函数：C(P)＝1/2log 2(1+P)。根据信息论，为了达到加性高斯白噪声信道的信道容量，输入信号必须满足连续均匀的高斯分布。因此，传统的均匀分布的调制方式例如幅度位移键控(ASK)和正交幅度调制(QAM)都没有达到满足高斯分布的最优条件。
为了使无线传输速率能逼近香农极限，许多学者研究并发明了一些非均匀分布的调制方式。Georg
Figure PCTCN2020111230-appb-000001
等学者提出了基于两极幅度位移键控的非均匀分布调制。他们提出在发送功率受限制的条件下，符号分布应满足麦克斯韦—玻尔兹曼分布来最大化符号的信息熵。在次基础上，他们又最大化了发送端和接收端的信号互信息以此来得到次优的发送端符号分布。在已知符号分布后，均匀分布的信源比特通过固定成分分布匹配(Constant Composition Distribution Matching,CCDM)和LDPC编码来转变为服从麦克斯韦—玻尔兹曼分布的符号序列。这种技术被称为概率幅度成型(Probabilistic Amplitude Shaping,PAS)。实验证明在AWGN信道下，该技术相比于传统均匀分布，在8ASK调制时能节省1dB左右的能量以达到相同的误帧率。然而，上述技术只针对单天线无线传输的情况，并不能直接套用在MIMO下来得到最优的符号分布。
发明内容
针对现有技术中的缺陷，本发明的目的是提供一种离散调制信号MIMO传输方法，该方法在ASK调制下和给定的MIMO编码矩阵下，对编码矩阵和信源符号分布进行联合优化以来最大化发送端和接收端符号的互信息，由此从理论上逼近香农极限，最大化MIMO传输速率，从而解决现有技术中因PAS技术并不考虑MIMO本身特点而导 致功率增益有待进一步提高的问题。
本发明提供的技术方案是：
一种离散调制信号MIMO传输方法，其采用的离散调制信号的MIMO传输模型为y＝HGΔx+n，其中x是初始的多路ASK星座图符号，y是接收端得到的各路接收信号，H是已知的信道矩阵，G是MIMO的预编码矩阵，Δ是星座扩展因子。其包括以下步骤：
(S1)初始化预编码矩阵G；
(S2)对于任意星座扩展因子Δ，通过调整信源多维向量x的信源分布P x以最大化信源熵H(x)，并根据当前预编码矩阵G，选择使互信息I(x；y)＝H(x)-H(x|y)最大的Δ和P x，其中H(x|y)为条件熵；
(S3)根据当前的星座扩展因子Δ和信源分布P x，通过梯度下降法来调整预编码矩阵G来进一步最大化互信息I(x；y)；
(S4)判断当前的星座扩展因子Δ、信源分布P x和据编码矩阵G的取值是否收敛，如果不收敛则跳转至步骤(S2)；
(S5)根据x的分布得到x中各路符号的边缘分布，由单路概率幅度成型技术对各路信号进行非均匀调制。
本发明的进一步改进在于，步骤(S2)中，对于任意给定的星座扩展因子Δ，通过拉格朗日数乘法对信源多维向量x进行最大熵优化，最终通过最大化互信息I(x；y)确定最优的星座扩展因子Δ和信源多维向量x的信源分布P x。
本发明的进一步改进在于，步骤(S3)包括以下步骤：
(S31)计算互信息I(s；y)关于预编码矩阵G的梯度表达式；
(S32)基于梯度下降法，对当前预编码矩阵G内各元素取值进行调整；若调整后预编码矩阵G不符合功率限制，则在梯度调整的基础上通过对G乘以一个缩放倍数来达到功率要求。
与现有技术相比，本发明具有如下的有益效果：
1.相比于传统离散均匀调制的MIMO系统，本发明通过非均匀调制技术来使传输速率更逼近香农极限。
2.相比于单天线的PAS非均匀调制技术，本发明针对MIMO系统多天线的特点，通过联合优化预编码矩阵与各路信号分布来进一步增大MIMO下概率幅度成型带来 的增益。
附图说明
通过阅读参照以下附图对非限制性实施例所作的详细描述，本发明的其它特征、目的和优点将会变得更明显：
图1为本发明提供的发送机结构图；
图2是本发明提供的接收机结构图。
具体实施方式
下面结合具体实施例对本发明进行详细说明。以下实施例将有助于本领域的技术人员进一步理解本发明，但不以任何形式限制本发明。应当指出的是，对本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变化和改进。这些都属于本发明的保护范围。
如图1、2所示，本发明的实施例提供一种离散调制信号MIMO传输方法，其采用的离散调制信号的MIMO传输模型为y＝HGΔx+n，其中x是初始的多路ASK星座图符号，y是接收端得到的各路接收信号，H是已知的信道矩阵，G是MIMO的预编码矩阵，Δ是星座扩展因子。本实施例中，发送端联合优化了预编码矩阵与信源分布，从理论上最大化发送端与接收端符号之间的互信息，并结合现有的单路概率幅度成型技术，实现MIMO场景下的非均匀分布传输。
具体的，本实施例的离散调制信号MIMO传输方法包括以下步骤：
(S1)初始化预编码矩阵G；
(S2)对于任意星座扩展因子Δ，通过调整信源多维向量x的信源分布P x可以最大化信源熵H(x)；并根据当前预编码矩阵G，选择使互信息I(x；y)＝H(x)-H(x|y)最大的Δ和P x，其中H(x|y)为条件熵。在此过程中每一个Δ对应一种分布P x使得在这个Δ下H(x)是最大的。不同的Δ对应不同的最大H(x)，我们选择能让互信息I(x,y)最大的那个Δ以及对应的在这个Δ下让H(x)最大的那个分布P x。
(S3)根据当前的星座扩展因子Δ和信源分布P x，通过梯度下降法来调整预编码矩阵G来进一步最大化互信息I(x；y)；
(S4)判断当前的星座扩展因子Δ、信源分布P x和据编码矩阵G的取值是否收敛， 如果不收敛则跳转至步骤(S2)；
(S5)根据x的分布得到x中各路符号的边缘分布，由单路概率幅度成型技术(PAS)对各路信号进行非均匀调制。
在上述步骤(S2)中，对于任意给定的星座扩展因子Δ，通过拉格朗日数乘法对信源多维向量x进行最大熵优化，最终通过最大化互信息I(x；y)确定最优的星座扩展因子Δ和信源多维向量x的信源分布P x。
在上述步骤(S3)包括以下步骤：
(S31)计算互信息I(s；y)关于预编码矩阵G的梯度表达式；
(S32)基于梯度下降法，对当前预编码矩阵G内各元素取值进行调整；若调整后预编码矩阵G不符合功率限制，则在梯度调整的基础上通过对G乘以一个缩放倍数来达到功率要求。
在本实施例的发送端的后续步骤中(详见图1)，本发明采用现有的概率幅度成型(PAS)技术对各路信号进行非均匀调制和标识操作。经标识后的各路比特流又经过信道编码、交织、调制、MIMO预编码等模块后送入信道。
本实例接收机各模块如图2所示，接收机的各模块为发送器各模块的逆过程。
以上对本发明的具体实施例进行了描述。需要理解的是，本发明并不局限于上述特定实施方式，本领域技术人员可以在权利要求的范围内做出各种变化或修改，这并不影响本发明的实质内容。在不冲突的情况下，本申请的实施例和实施例中的特征可以任意相互组合。

Claims (3)

  1. 一种离散调制信号MIMO传输方法，其采用的离散调制信号的MIMO传输模型为y＝HGΔx+n，其中x是初始的多路ASK星座图符号，y是接收端得到的各路接收信号，H是已知的信道矩阵，G是MIMO的预编码矩阵，Δ是星座扩展因子；其特征在于包括以下步骤：
    (S1)初始化预编码矩阵G；
    (S2)对于任意星座扩展因子Δ，通过调整信源多维向量x的信源分布P x以最大化信源熵H(x)，并根据当前预编码矩阵G，选择使互信息I(x；y)＝H(x)-H(x|y)最大的Δ和P x，其中H(x|y)为条件熵；
    (S3)根据当前的星座扩展因子Δ和信源分布P x，通过梯度下降法来调整预编码矩阵G来进一步最大化互信息I(x；y)；
    (S4)判断当前的星座扩展因子Δ、信源分布P x和据编码矩阵G的取值是否收敛，如果不收敛则跳转至步骤(S2)；
    (S5)根据x的分布得到x中各路符号的边缘分布，由单路概率幅度成型技术对各路信号进行非均匀调制。
  2. 根据权利要求1所述的一种离散调制信号MIMO传输方法，其特征在于，步骤(S2)中，对于任意给定的星座扩展因子Δ，通过拉格朗日数乘法对信源多维向量x进行最大熵优化，最终通过最大化互信息I(x；y)确定最优的星座扩展因子Δ和信源多维向量x的信源分布P x。
  3. 根据权利要求1所述的一种离散调制信号MIMO传输方法，其特征在于，步骤(S3)包括以下步骤：
    (S31)计算互信息I(x；y)关于预编码矩阵G的梯度表达式；
    (S32)基于梯度下降法，对当前预编码矩阵G内各元素取值进行调整；若调整后预编码矩阵G不符合功率限制，则在梯度调整的基础上通过对G乘以一个缩放倍数来达到功率要求。
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