WO2012152020A1 - 一种信道均衡方法、基站和系统 - Google Patents

一种信道均衡方法、基站和系统 Download PDF

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Publication number
WO2012152020A1
WO2012152020A1 PCT/CN2011/084573 CN2011084573W WO2012152020A1 WO 2012152020 A1 WO2012152020 A1 WO 2012152020A1 CN 2011084573 W CN2011084573 W CN 2011084573W WO 2012152020 A1 WO2012152020 A1 WO 2012152020A1
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Prior art keywords
base station
matrix
autocorrelation matrix
frequency domain
channel response
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PCT/CN2011/084573
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English (en)
French (fr)
Inventor
周旭武
楼红伟
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中兴通讯股份有限公司
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Publication of WO2012152020A1 publication Critical patent/WO2012152020A1/zh

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    • 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
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/022—Channel estimation of frequency response
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0244—Channel estimation channel estimation algorithms using matrix methods with inversion
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/021—Estimation of channel covariance
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H04L25/0228—Channel estimation using sounding signals with direct estimation from sounding signals

Definitions

  • the present invention relates to channel processing technologies, and in particular, to a channel equalization method, a base station, and a system. Background technique
  • a new generation of wireless communication systems mostly employ antenna arrays composed of multiple dual-polarized antennas.
  • the dual-polarized antenna is composed of two antennas whose polarization directions are orthogonal to each other, and the two antennas operate in the duplex mode, which can greatly save the number of antennas in each cell; and, because of two antennas The polarization directions are orthogonal to each other, and the diversity reception is better.
  • dual-polarized antennas are divided into vertical and horizontal polarization modes, and +45. And -45.
  • Polarization mode Two types. Thanks to +45. And -45.
  • Polarized dual-polarized antennas outperform vertical and horizontally polarized dual-polarized antennas, so ⁇ 45 is currently widely used.
  • Polarized dual-polarized antenna is typically divided into vertical and horizontal polarization modes, and +45. And -45.
  • the process of acquiring the transmitted signal is as follows: First, the autocorrelation matrix is obtained according to the received signal, and then the inverse of the autocorrelation matrix is obtained to obtain the inverse of the autocorrelation matrix, and then the inverse of the autocorrelation matrix is adopted. Certain criteria, for example, the Minimum Mean Square Error (MMSE) criterion, the channel equalization process is used to obtain the optimal weight vector, and finally the transmitted signal is obtained according to the optimal weight vector.
  • MMSE Minimum Mean Square Error
  • one base station includes more and more dual-polarized antennas, and some communication systems use CoMP (Coordinated Multi-Point Transmission) technology, such as a long-term evolution system ( LTE (Long Term Evolution), multiple base stations work in the system, and each base station includes multiple antennas.
  • CoMP Coordinatd Multi-Point Transmission
  • LTE Long-term evolution
  • LTE Long Term Evolution
  • the main object of the present invention is to provide a channel equalization method, a base station, and a system, which can not only reduce the amount of calculation, but also reduce the loss of related information between antennas, thereby obtaining a better channel equalization effect.
  • the present invention provides a channel equalization method, the method comprising:
  • the transmitted signal is derived based on the inversion result, the channel response in the frequency domain, and the received signal.
  • the method further comprises: performing a diagonal loading process on the processed matrix.
  • the channel response in the frequency domain is obtained according to the received signal, and the reference signal is extracted from the received signal, and the channel is estimated according to the reference signal to obtain a channel response in the frequency domain.
  • the transmitting signal is obtained according to the inversion result, the channel response in the frequency domain, and the received signal
  • the optimal weight vector is obtained according to the inversion result and the channel response in the frequency domain, and then according to the optimal weight The value vector and the received signal result in a transmitted signal.
  • the invention also provides a channel equalization method, the method comprising:
  • Each base station obtains its own autocorrelation matrix and channel response in the frequency domain according to the received signals. Obtaining a multi-base station autocorrelation matrix according to an autocorrelation matrix of each base station;
  • the transmitted signal is derived based on the inversion result, the channel response in the frequency domain, and the received signal.
  • the multi-base station autocorrelation matrix is obtained according to the autocorrelation matrix of each base station, and is: a matrix-to-multi-base station autocorrelation matrix according to each base station simplifies the respective autocorrelation matrix.
  • each of the base stations simplifies the respective autocorrelation matrix, and is: Preferably, after performing the zeroing process, the method further includes: each base station diagonally loading the processed matrix deal with.
  • the present invention further provides a base station, the base station includes at least one dual-polarized antenna, and the base station is configured to obtain, according to the received signal, an autocorrelation matrix and a matrix of the channel response in the frequency domain to invert the matrix;
  • the transmitted signal is derived based on the inversion result, the channel response in the frequency domain, and the received signal.
  • the present invention also provides a channel equalization system, the system comprising: an eNode B and a base station;
  • the base station is configured to obtain, according to the received signal, an autocorrelation matrix and a channel response in the frequency domain, and send the autocorrelation matrix and the channel response in the frequency domain to the eNodeB;
  • the eNode B is configured to obtain a multi-base station autocorrelation matrix according to an autocorrelation matrix sent by each base station; perform zero-zero processing on correlation between antennas in each base station in the multi-base station autocorrelation matrix, and process the correlation
  • the latter matrix is inverted; the transmitted signal is derived from the inverse result, the channel response in the frequency domain, and the received signal.
  • the channel equalization method, the base station and the system provided by the present invention are based on the received
  • the signal is obtained from the autocorrelation matrix and the channel response in the frequency domain; the correlation between the antennas in different polarization directions in the autocorrelation matrix is zeroed; the processed matrix is inverted; according to the inversion result, in the frequency domain
  • the channel response and the received signal result in a transmitted signal. Since the correlation between antennas with different polarization directions is low, even if they are ignored, the influence on the autocorrelation matrix is not large. In this way, the autocorrelation matrix can be simplified while reducing the loss of the correlation information between the antennas, and a better channel equalization effect can be obtained while reducing the amount of calculation.
  • FIG. 2 is a schematic diagram of an antenna array composed of a dual-polarized antenna in a polarization mode;
  • FIG. 2 is a schematic flowchart of an embodiment of a channel equalization method according to the present invention
  • Figure 3 shows the simplified matrix, autocorrelation matrix - &11 and the block diagonal matrix ⁇ . Comparison of the effects;
  • FIG. 4 is a schematic structural diagram of a communication system for multi-base station cooperative transmission work
  • FIG. 5 is a schematic flowchart diagram of an embodiment of a channel equalization method according to the present invention. detailed description
  • a certain base station is used by four ⁇ 45.
  • An antenna array consisting of a polarized dual-polarized antenna, wherein the antenna array has a total of eight antennas, and the first antenna to the fourth antenna are +45. Polarization, the fifth to eighth antennas are -45. Polarization, see Figure 1.
  • the channel equalization method in this embodiment is as shown in FIG. 2, and includes the following steps:
  • Step 201 Each antenna of the base station receives a signal y.
  • Step 202 The base station extracts a reference signal from the received signal y.
  • Step 203 Estimating the channel according to the extracted reference signal to obtain a channel response h in the frequency domain.
  • Step 204 The base station obtains an autocorrelation matrix &11 according to the received signal y.
  • the autocorrelation matrix - &u can be expressed as:
  • ⁇ is the correlation between the first antenna and the first antenna, that is, the autocorrelation information of the first antenna; the correlation between the first antenna and the fourth antenna is between the first antenna and the eighth antenna Relevance, and so on, will not be repeated here.
  • Step 205 The base station simplifies the autocorrelation matrix ⁇ to obtain a block diagonal matrix.
  • the antennas of different polarization directions for example, the first antenna and the fifth antenna in FIG. 1
  • sexual, but in reality, the multipath effect and noise of the channel will cause correlation between antennas with different polarization directions, and the correlation between antennas with different polarization directions is low. Therefore, different polarizations need to be adopted.
  • the correlation between the antennas in the direction is set to zero, and only the correlation between the antennas in the same polarization direction is retained, and the autocorrelation matrix ⁇ is simplified to obtain a block diagonal matrix ⁇ block :
  • the autocorrelation matrix is simplified by the above method, and the noise pair can also be reduced.
  • the effect of the block diagonal matrix is such that the block diagonal matrix - bl . Ck has a high stability.
  • Step 206 The base station performs diagonal loading on the block diagonal matrix according to formula (1), and obtains adding Load block diagonal matrix _ bl ⁇ k _ d£ :
  • ⁇ -block-dc — block + a ⁇ traCe ( -blo i )
  • trace (.) represents the trace of the matrix, which is the diagonal loading coefficient, which can be obtained according to simulation or experimental tests.
  • the block diagonal matrix ⁇ Performing diagonal loading can make the loading block diagonal matrix A more stable.
  • Step 207 The base station inverts the loaded block diagonal matrix _ bl ⁇ k _ d £ to obtain an inverse bi ⁇ k — d of the loaded block diagonal matrix. .
  • Steps 202 and 203 in the above steps may be performed simultaneously with steps 204 to 207.
  • Step 208 The base station obtains an optimal weight vector w MMffi according to the inverse ⁇ 1 of the loaded block diagonal matrix ( ⁇ , the channel response h in the frequency domain and its conjugate symmetry h H , according to formula (2):
  • Step 209 The base station according to the optimal weight vector w Videos E w Videos conjugate symmetry E and H of the received signal y, according to equation (3) yields a transmission signal
  • Figure 3 is a comparison of the effects of the simplified matrix, the autocorrelation matrix, and the block diagonal matrix ⁇ , as shown in Figure 3, using the method of retaining only the diagonal metadata of the autocorrelation matrix. Simplifying the simplified matrix results in a large loss of related information between the antennas.
  • the channel equalization effect is the worst according to the simplified matrix y diag , that is, the block error rate is the highest in the case of the same SNR;
  • Channel equalization directly according to the autocorrelation matrix may result in poor channel equalization due to the influence of noise between antennas in different polarization directions, that is, the block error rate is higher in the case of the same signal to noise ratio;
  • Method to simplify the autocorrelation matrix v _ &11 Obtain a block diagonal matrix ⁇ . It can reduce the influence of noise between antennas with different polarization directions. Therefore, the channel equalization according to the block diagonal matrix is the best, that is, the block error rate is the lowest under the same signal-to-noise ratio.
  • FIG. 4 is a schematic structural diagram of a communication system for multi-base station cooperative transmission work.
  • the communication system in this example includes eight base stations, each base station includes multiple dual-polarized antennas, and eight base stations pass through an evolved base station. (eNodeB, Evolved Node B) Complete the collaborative work.
  • eNodeB Evolved Node B
  • Figure 5 The specific steps are as shown in Figure 5, including:
  • Step 501 According to the methods described in steps 201, 204, 205 and 206, each base station obtains a respective load block diagonal matrix.
  • the eNodeB obtains the channel response h in the frequency domain, and according to the loading block diagonal of each base station Multi-base station autocorrelation matrix
  • _ bl . ek _ de is the correlation between antennas in the first base station; _ bl ⁇ k _ de eighth inter-base station and a first base station correlation between antennas, and so is not repeated here.
  • Step 503 The eNodeB is connected to the multi-base station autocorrelation matrix e .
  • ⁇ Simplify to obtain a block multi-base station autocorrelation matrix: refrain.
  • the multi-base station autocorrelation matrix rnmn is simplified by the correlation between the antennas in the station: Obtaining a block multi-base station autocorrelation matrix ⁇ _ bl ⁇ k
  • the above method is used to simplify the multi-base station autocorrelation matrix 4, which can greatly reduce the computational complexity of the inverse and improve the efficiency of the channel equalization processing.
  • Step 504 The eNodeB inverts the block multi-base station autocorrelation matrix ⁇ bk to obtain an inverse ⁇ _ ⁇ ⁇ ⁇ of the block multi-base station autocorrelation matrix.
  • Step 505 The eNodeB obtains an optimal weight vector according to the formula (4) according to the inverse of the block multi-base station autocorrelation matrix, the channel response h in the frequency domain, and its conjugate symmetry. _ ⁇ £ :
  • Step 506 The eNode B obtains a transmission signal according to the optimal weight vector, the conjugate symmetry of the _MMffi , the leg SE, and the received signal y according to the formula (5).
  • the channel equalization method of the present invention is also applicable to other communication systems including a large number of dual-polarized antennas, such as MU-MIMO (Multi-User Multiple Input Multiple Output).
  • MU-MIMO Multi-User Multiple Input Multiple Output
  • the present invention provides a base station, the base station includes at least one dual-polarized antenna, and the base station is configured to obtain an autocorrelation matrix and a channel response in a frequency domain according to the received signal; and invert the self-phase matrix; Inversion result, channel response in the frequency domain, and received signal Shoot the signal.
  • the present invention also provides a channel equalization system, the system comprising an eNode B and at least one base station;
  • the base station is configured to obtain, according to the received signal, an autocorrelation matrix and a channel response in the frequency domain, and send the autocorrelation matrix and the channel response in the frequency domain to the eNodeB;
  • the eNode B is configured to obtain a multi-base station autocorrelation matrix according to an autocorrelation matrix sent by each base station, and perform zeroing processing on correlation between antennas in each base station in the multi-base station autocorrelation matrix, and process the correlation.
  • the latter matrix is inverted; the transmitted signal is derived from the inverse result, the channel response in the frequency domain, and the received signal.

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Abstract

本发明提供了一种信道均衡方法，该方法包括：根据接收到的信号得到自相关矩阵和频域内的信道响应；对自相关矩阵中不同极化方向的天线之间的相关性进行置零处理；对处理后的矩阵进行求逆；根据求逆结果、频域内的信道响应和接收到的信号得出发射信号。本发明还提供了一种基站和系统。本发明不仅能够减少对矩阵求逆的运算量，而且能减少天线间的相关信息的损失，从而获得较好的信道均衡效果。

Description

一种信道均衡方法、 基站和系统 技术领域
本发明涉及信道处理技术， 尤其涉及一种信道均衡方法、 基站和系统。 背景技术
新一代无线通信系统为追求更高的系统性能， 大多采用由多个双极化 天线组成的天线阵列。 所述双极化天线由两副极化方向相互正交的天线组 成， 所述两副天线都在收发双工模式下工作， 这样能大大节省每个小区的 天线数量； 而且， 由于两副天线的极化方向相互正交， 分集接收的效果更 好。
通常， 双极化天线分为垂直和水平极化方式、 以及 +45。和 -45。极化方式 两种类型。由于 +45。和 -45。极化方式的双极化天线性能优于垂直和水平极化 方式的双极化天线， 因此， 目前普遍采用 ±45。极化方式的双极化天线。
当基站包括多个天线时， 获取发射信号的过程是这样的： 首先根据接 收信号得到自相关矩阵， 再对自相关矩阵进行求逆运算得到自相关矩阵的 逆，接着根据自相关矩阵的逆采用一定准则，例如，最小均方误差（MMSE, Minimum Mean Square Error ) 准则， 进行信道均衡处理得到最优的权值向 量， 最后根据最优的权值向量得到发射信号。
但是， 新一代无线通信系统中， 一个基站包括的双极化天线的数量越 来越多， 而且， 有些通信系统采用多基站协同传输（CoMP, Coordinated Multi-Point Transmission ) 技术， 如长期演进系统 （ LTE , Long Term Evolution ), 系统中多个基站协作工作， 每个基站都包括多个天线。 这就造 成自相关矩阵的数据量越来越多， 进而导致对自相关矩阵进行求逆的运算 量越来越大， 现有的计算设备很难完成上述运算任务。 目前， 为减少运算量通常采用只保留自相关矩阵的对角元数据的方法， 对自相关矩阵进行简化得到简化矩阵， 再对简化矩阵进行求逆。 但是， 由 于上述简化方法仅保留自相关矩阵的对角元数据， 造成了天线间的相关信 息的大量损失， 从而不能获得好的信道均衡效果。 发明内容
有鉴于此， 本发明的主要目的在于提供一种信道均衡方法、 基站和系 统， 不仅能够减少运算量， 而且能减少天线间相关信息的损失， 进而获得 较好的信道均衡效果。
为达到上述目的， 本发明的技术方案是这样实现的：
本发明提供了一种信道均衡方法， 该方法包括：
根据接收到的信号得到自相关矩阵和频域内的信道响应； 对处理后的矩阵进行求逆；
根据求逆结果、 频域内的信道响应和接收到的信号得出发射信号。 较佳的， 所述进行置零处理之后， 该方法还包括： 对处理后的矩阵进 行对角加载处理。
较佳的， 所述根据接收到的信号得到频域内的信道响应为， 从接收到 的信号中提取参考信号， 根据所述参考信号对信道进行估计， 得到频域内 的信道响应。
较佳的， 所述根据求逆结果、 频域内的信道响应和接收到的信号得出 发射信号为， 根据求逆结果、 频域内的信道响应得出最优权值向量， 再根 据最优权值向量和接收到的信号得出发射信号。
本发明还提供了一种信道均衡方法， 该方法包括：
各基站根据接收到的信号得到各自的自相关矩阵和频域内的信道响 根据各基站的自相关矩阵得到多基站自相关矩阵；
对多基站自相关矩阵中的各基站间的各天线之间的相关性进行置零处 理， 并对处理后的矩阵进行求逆；
根据求逆结果、 频域内的信道响应和接收到的信号得出发射信号。 较佳的， 所述根据各基站的自相关矩阵得到多基站自相关矩阵， 为： 根据各基站对各自的自相关矩阵进行简化处理后的矩阵到多基站自相关矩 阵。
较佳的， 所述各基站对各自的自相关矩阵进行简化处理， 为： 各基站 较佳的， 所述进行置零处理之后， 该方法还包括， 各基站对处理后的 矩阵进行对角加载处理。
本发明还提供了一种基站， 所述基站至少包括一个双极化天线； 所述基站， 用于根据接收到的信号得到自相关矩阵和频域内的信道响 对处理后的矩阵进行求逆； 根据求逆结果、 频域内的信道响应和接收到的 信号得出发射信号。
本发明还提供了一种信道均衡系统， 该系统包括： eNode B和基站； 其 中，
所述基站， 用于根据接收到的信号得到自相关矩阵和频域内的信道响 应， 将自相关矩阵和频域内的信道响应发送给 eNodeB;
所述 eNode B,用于根据各基站发来的自相关矩阵得到多基站自相关矩 阵； 对多基站自相关矩阵中的各基站间的各天线之间的相关性进行置零处 理， 并对处理后的矩阵进行求逆； 根据求逆结果、 频域内的信道响应和接 收到的信号得出发射信号。
由上可知， 本发明提供的信道均衡方法、 基站和系统， 根据接收到的 信号得到自相关矩阵和频域内的信道响应； 对自相关矩阵中不同极化方向 的天线之间的相关性进行置零处理； 对处理后的矩阵进行求逆； 根据求逆 结果、 频域内的信道响应和接收到的信号得出发射信号。 因不同极化方向 的天线之间的相关性较低， 即使将其忽略， 对自相关矩阵的影响也不大。 如此， 能够在满足减少天线间的相关信息的损失的前提下， 对自相关矩阵 进行简化， 在减少运算量的同时获得较好的信道均衡效果。 附图说明
图 1为由 ±45。极化方式的双极化天线组成的天线阵列的示意图； 图 2为本发明信道均衡方法的一实施例的流程示意图；
图 3为简化矩阵 、 自相关矩阵 — &11和分块对角矩阵 ω。 的效果 比较图；
图 4为多基站协同传输工作的通信系统的结构示意图；
图 5为本发明信道均衡方法的一实施例的流程示意图。 具体实施方式
下面参考图 1和图 2对本发明的一具体实施例进行详细的介绍。
本实施例中， 某一基站使用由四个 ±45。极化方式的双极化天线组成的 天线阵列， 其中， 此天线阵列共八根天线， 第一天线至第四天线是 +45。 极 化， 第五天线至第八天线是 -45。 极化， 参考图 1所示。
本实施例的信道均衡方法如图 2所示， 包括以下步驟：
步驟 201： 基站的各天线分别接收信号 y。
步驟 202: 基站从接收到的信号 y中提取参考信号。
步驟 203:根据提取的参考信号对信道进行估计得到频域内的信道响应 h。
步驟 204: 基站根据接收到的信号 y得到自相关矩阵 &11。 这里， 所述自相关矩阵 — &u可以表示为:
rU … r\ … ·
R -foil
Γ81 … Γ88
其中， ^为第一天线与第一天线之间的相关性 即体现第一天线的自 相关信息； 为第一天线与第四天线之间的相关性 为第一天线与第八 天线之间的相关性， 以此类推， 此处不再赘述。
步驟 205:基站对自相关矩阵^ 进行简化，得到分块对角矩阵 这里， 不同极化方向的天线 （例如， 图 1 中的第一天线和第五天线） 之间在理想状态下是没有相关性的， 但现实中信道的多径效应及噪声会造 成不同极化方向的天线之间产生相关性， 而且不同极化方向的天线之间的 相关性较低， 因此， 需要采用将不同极化方向的天线之间的相关性置零， 仅保留相同极化方向的天线之间的相关性的方式， 对自相关矩阵 ω进行 简化， 得到分块对角矩阵^ block：
0 · ·· 0
¾ι · " Γ44 0 · ·· 0
Figure imgf000007_0001
0 · ·· 0 · " r%%
通常， 将不同极化方向的天线之间的相关性置零， 即意味着消除了不 同极化方向的天线之间的噪声， 因此， 采用上述方法对自相关矩阵 进 行简化， 还可以降低噪声对分块对角矩阵 造成的影响， 使得分块对角 矩阵 —bl。ck具有较高的稳定性。
步驟 206: 基站对分块对角矩阵 按公式 (1)进行对角加载， 得到加 载分块对角矩阵 _bl∞k_d£：
^-block-dc = — block + a · traCe( -blo i )
其中， trace (.)表示矩阵的迹， 为对角加载系数， 所述 可以根据仿 真或实验测试获得。对分块对角矩阵 ω。 进行对角加载可以使加载分块对 角矩阵 A 具有更高的稳定性。
步驟 207: 基站对加载分块对角矩阵 _bl∞k_d£进行求逆， 得到加载分块 对角矩阵的逆 bi∞k— d。。
上述步驟中步驟 202和 203可以与步驟 204 ~ 207同时执行。
步驟 208: 基站根据加载分块对角矩阵 的逆 Λ1(ϋ、 频域内的 信道响应 h和其共轭对称 hH , 按公式 (2)得出最优权值向量 wMMffi：
WMMSE
Figure imgf000008_0001
步驟 209：基站根据最优权值向量 w画 E的共轭对称 w画H E和接收到的信 号 y, 按公式 (3)得出发射信号
X = WMMSE - y (3) 图 3为简化矩阵 、 自相关矩阵 和分块对角矩阵 ^的效果 比较图， 如图 3所示， 采用只保留自相关矩阵 的对角元数据的方法进 行简化得到简化矩阵 ，会造成了天线间的相关信息的大量损失， 因此， 根据所述简化矩阵 y diag进行信道均衡的效果最差， 即在相同信噪比情形 下， 块误码率最高； 而直接根据自相关矩阵 进行信道均衡， 会因不同 极化方向的天线间噪声的影响， 导致信道均衡的效果较差， 即在相同信噪 比情形下， 块误码率较高； 采用本发明的方法对自相关矩阵 v_&11进行简化 得到分块对角矩阵 ω。 , 可以减少不同极化方向的天线之间的噪声的影 响， 因此， 根据分块对角矩阵 进行信道均衡的效果最好， 即相同信噪 比情形下， 块误码率最低。
下面参考图 4和图 5对本发明信道均衡方法应用于多基站协同工作的 情况进行介绍。
图 4为多基站协同传输工作的通信系统的结构示意图， 如图 4所述， 本例中的通信系统包括八个基站， 每个基站包括多个双极化天线， 八个基 站通过演进型基站（eNodeB, Evolved Node B ) 完成协同工作， 具体步驟 如图 5所示， 包括：。
步驟 501 : 按照步驟 201、 204、 205和 206所述的方法， 各基站分别获 得各自的加载分块对角矩阵。
按上文描述的方法分别获得第一基站至第八基站的加载分块对角矩阵 、 、 、 、 、 、 和 步驟 502: eNodeB获得频域内的信道响应 h, 并根据各基站的加载 块对角矩阵得到多基站自相关矩阵
Figure imgf000009_0001
其中， _bl。ek_de为第一基站内各天线之间的相关性； _bl∞k_de为第一基 站和第八基站间各天线之间的相关性， 以此类推， 此处不再赘述。
步驟 503 : eNodeB对多基站自相关矩阵 e。^进行简化， 得到分块多基 站自相关矩阵 :。„。 。
鉴于各基站间的各天线之间的相关性明显弱于基站内各天线之间的相 关性， 因此， 需要采用将各基站间的各天线之间的相关性置零， 仅保留基 站内各天线之间的相关性的方式， 对多基站自相关矩阵 rnmn进行了简化: 得到分块多基站自相关矩阵 ^_bl∞k
Com/?— block
Figure imgf000010_0001
采用上述方法对多基站自相关矩阵 4，进行简化， 可以大大降低求逆 的运算量， 提高信道均衡处理的效率。
步驟 504: eNodeB对分块多基站自相关矩阵^ ^^b k求逆， 得到分块 多基站自相关矩阵的逆 ^ _bl∞k。
步驟 505: eNodeB根据分块多基站自相关矩阵的逆 ^^^、 频域内 的信道响应 h和其共轭对称 , 按公式（ 4 )得出最优权值向量 。 _ΜΜ £：
Figure imgf000010_0002
步驟 506: eNode B根据最优权值向量 ，_MMffi的共轭对称 ―腿 SE 和接收的信号 y, 按公式（5 )得出发射信号
Figure imgf000010_0003
本发明信道均衡方法也适用于其他包括大量双极化天线的通信系统， 例如多用户多入多出系统（ MU-MIMO, Multiple User-Multiple Input Multiple Output )。
本发明提供了一种基站， 所述基站至少包括一个双极化天线； 所述基 站， 用于根据接收到的信号得到自相关矩阵和频域内的信道响应； 对自相 矩阵进行求逆； 根据求逆结果、 频域内的信道响应和接收到的信号得出发 射信号。
本发明还提供了一种信道均衡系统， 该系统包括一个 eNode B和至少 一个基站；
所述基站， 用于根据接收到的信号得到自相关矩阵和频域内的信道响 应， 将自相关矩阵和频域内的信道响应发送给 eNodeB;
所述 eNode B ,用于根据各基站发来的自相关矩阵得到多基站自相关矩 阵， 对多基站自相关矩阵中的各基站间的各天线之间的相关性进行置零处 理， 并对处理后的矩阵进行求逆； 根据求逆结果、 频域内的信道响应和接 收到的信号得出发射信号。
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。

Claims

权利要求书
1、 一种信道均衡方法， 其特征在于， 该方法包括：
根据接收到的信号得到自相关矩阵和频域内的信道响应； 对处理后的矩阵进行求逆；
根据求逆结果、 频域内的信道响应和接收到的信号得出发射信号。
2、根据权利要求 1所述的方法，其特征在于， 所述进行置零处理之后， 该方法还包括： 对处理后的矩阵进行对角加载处理。
3、 根据权利要求 1所述的方法， 其特征在于， 所述根据接收到的信号 得到频域内的信道响应为： 从接收到的信号中提取参考信号， 根据所述参 考信号对信道进行估计， 得到频域内的信道响应。
4、 根据权利要求 1所述的方法， 其特征在于， 所述根据求逆结果、 频 域内的信道响应和接收到的信号得出发射信号为： 根据求逆结果、 频域内 的信道响应得出最优权值向量， 再根据最优权值向量和接收到的信号得出 发射信号。
5、 一种信道均衡方法， 其特征在于， 该方法包括：
各基站根据接收到的信号得到各自的自相关矩阵和频域内的信道响 应；
根据各基站的自相关矩阵得到多基站自相关矩阵；
对多基站自相关矩阵中的各基站间的各天线之间的相关性进行置零处 理， 并对处理后的矩阵进行求逆；
根据求逆结果、 频域内的信道响应和接收到的信号得出发射信号。
6、 根据权利要求 5所述的方法， 其特征在于， 所述根据各基站的自相 关矩阵得到多基站自相关矩阵， 为： 根据各基站对各自的自相关矩阵进行 简化处理后的矩阵到多基站自相关矩阵。
7、 根据权利要求 6所述的方法， 其特征在于， 所述各基站对各自的自 相关矩阵进行简化处理为： 各基站对自相关矩阵中不同极化方向的天线之 间的相关性进行置零处理。
8、根据权利要求 7所述的方法，其特征在于， 所述进行置零处理之后， 该方法还包括： 各基站对处理后的矩阵进行对角加载处理。
9、 一种基站， 其特征在于， 所述基站至少包括一个双极化天线； 所述基站， 用于根据接收到的信号得到自相关矩阵和频域内的信道响 对处理后的矩阵进行求逆； 根据求逆结果、 频域内的信道响应和接收到的 信号得出发射信号。
10、 一种信道均衡系统， 其特征在于， 该系统包括： 演进型基站 eNode B和基站； 其中，
所述基站， 用于根据接收到的信号得到自相关矩阵和频域内的信道响 应， 将自相关矩阵和频域内的信道响应发送给 eNodeB;
所述 eNode B,用于根据各基站发来的自相关矩阵得到多基站自相关矩 阵； 对多基站自相关矩阵中的各基站间的各天线之间的相关性进行置零处 理， 并对处理后的矩阵进行求逆； 根据求逆结果、 频域内的信道响应和接 收到的信号得出发射信号。
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CN104348518B (zh) * 2013-07-26 2018-07-31 马维尔国际有限公司 信号的联合检测方法和装置
CN112468194B (zh) * 2019-09-06 2023-04-07 中兴通讯股份有限公司 一种抵消信号的生成方法、装置、基站以及存储介质
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1439184A (zh) * 2000-06-21 2003-08-27 艾利森电话股份有限公司 在无馈电电缆相干性情况下在多波束中同时传输信号的系统和方法
CN1512697A (zh) * 2002-12-30 2004-07-14 �ʼҷ����ֵ��ӹɷ����޹�˾ 基于cdma系统的多用户检测的简化去相关的方法及其装置
CN1564494A (zh) * 2004-04-01 2005-01-12 上海交通大学 波束空间正交频分复用调制系统自适应波束形成方法
CN101039305A (zh) * 2007-04-23 2007-09-19 北京天碁科技有限公司 一种基于均衡技术的接收机和接收方法
US20090247086A1 (en) * 2008-03-31 2009-10-01 Xintian Eddie Lin Reducing co-channel interference

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20080073624A (ko) * 2007-02-06 2008-08-11 삼성전자주식회사 다중 편파 다중 입출력 시스템을 위한 코드북 생성 방법 및그 장치
CN101459457B (zh) * 2007-12-12 2013-01-16 鼎桥通信技术有限公司 一种波束赋形方法
CN101465683B (zh) * 2007-12-18 2012-10-10 中兴通讯股份有限公司 基于双极化天线的上行接收方法及下行发射方法
CN101754362B (zh) * 2008-12-09 2012-04-18 鼎桥通信技术有限公司 一种双极化智能天线系统中的doa估计方法
US8743941B2 (en) * 2009-12-01 2014-06-03 Telefonaktiebolaget L M Ericsson (Publ) Spatial and temporal pre-equalization
CN101729486B (zh) * 2009-12-24 2015-04-29 北京韦加航通科技有限责任公司 一种单载波频域均衡系统中双天线接收分集方法及系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1439184A (zh) * 2000-06-21 2003-08-27 艾利森电话股份有限公司 在无馈电电缆相干性情况下在多波束中同时传输信号的系统和方法
CN1512697A (zh) * 2002-12-30 2004-07-14 �ʼҷ����ֵ��ӹɷ����޹�˾ 基于cdma系统的多用户检测的简化去相关的方法及其装置
CN1564494A (zh) * 2004-04-01 2005-01-12 上海交通大学 波束空间正交频分复用调制系统自适应波束形成方法
CN101039305A (zh) * 2007-04-23 2007-09-19 北京天碁科技有限公司 一种基于均衡技术的接收机和接收方法
US20090247086A1 (en) * 2008-03-31 2009-10-01 Xintian Eddie Lin Reducing co-channel interference

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