WO2004043089A1 - Procede d'identification de canaux - Google Patents

Procede d'identification de canaux Download PDF

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Publication number
WO2004043089A1
WO2004043089A1 PCT/CN2003/000726 CN0300726W WO2004043089A1 WO 2004043089 A1 WO2004043089 A1 WO 2004043089A1 CN 0300726 W CN0300726 W CN 0300726W WO 2004043089 A1 WO2004043089 A1 WO 2004043089A1
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Prior art keywords
sample
threshold
power delay
identification method
channel
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PCT/CN2003/000726
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English (en)
French (fr)
Inventor
Xinxi Diao
Weifeng Wang
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Huawei Technologies Co., Ltd.
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Priority claimed from CN 02146694 external-priority patent/CN1260981C/zh
Priority claimed from CNB021501386A external-priority patent/CN1232061C/zh
Application filed by Huawei Technologies Co., Ltd. filed Critical Huawei Technologies Co., Ltd.
Priority to AU2003261580A priority Critical patent/AU2003261580A1/en
Publication of WO2004043089A1 publication Critical patent/WO2004043089A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements

Definitions

  • the present invention relates to the field of mobile communication technologies, and in particular, to a method for identifying a type of a wireless channel. Background of the invention
  • the existence of a non-visible propagation path causes an additional delay error to be included in the propagation delay between the mobile terminal and the base station. This additional delay error seriously affects the positioning accuracy of the mobile terminal.
  • the NLOS channel identification technology needs to be adopted.
  • the basic idea of the NLOS identification method is: (1) Long-term recording of the distance between the mobile terminal and the base station measured by each base station; (2) Smooth processing of a large amount of recorded data; (3) In the case of using NLOS The measurement variance (relative to the smoothed data, which is caused by the landform feature and the system measurement error) is much larger than the fact that the measurement variance (which is caused by the system measurement error) at LOS is used for LOS identification.
  • the recognition methods proposed in Documents 1 and 2 require the time correlation of the mobile terminal to track and smooth the trajectory of the mobile terminal in motion before it can output the NLOS recognition results, which requires a longer data accumulation time. Therefore, it is easy to generate a large delay and difficult To meet the FCC (Federal Communications Commission) requirements for response time, it does not have real-time nature, and is only suitable for visual path recognition when the mobile terminal is in motion.
  • FCC Federal Communications Commission
  • the local strongest diameter is detected and taken to determine whether the ratio of the strongest diameter to the local strongest diameter is greater than the threshold K;
  • An object of the present invention is to provide a channel identification method to identify a visible channel, a quasi-visible channel, and a non-visible channel in a complex channel environment, improve the real-time performance of channel identification, and Recognition rate.
  • a channel identification method includes the following steps:
  • A) Obtain multiple power delay profiles (PDP, Power Delay Profile) at the receiving end;
  • B) Obtain a path peak in each power delay profile as a sample, and obtain the entire sample;
  • the step of obtaining continuous multiple power delay distributions includes the following steps:
  • the receiving end receives signals transmitted by the transmitting end;
  • the receiving end performs matched filtering on the received signal
  • At least one non-coherent accumulation is performed on the result of the matched filtering obtained in step A12 to obtain a power delay distribution.
  • the acquiring multiple power delay distributions includes: acquiring, at a receiving end using an array antenna, a power delay distribution corresponding to a signal received by each antenna unit.
  • the obtaining a power delay distribution corresponding to a signal received by each antenna unit includes:
  • each antenna unit independently receives the same signal at the same time
  • step A23 Perform at least one non-coherent accumulation on the result of the matched filtering obtained in step A22 to obtain a power delay distribution.
  • step B includes the following steps:
  • the peak of the first path is selected as the sample population within each power delay distribution.
  • Step C includes,
  • Step D includes:
  • Dl preset decision threshold 1 and decision threshold 2, and set threshold 1 to be greater than decision threshold 2;
  • D12 Compare the sample variation coefficient with the decision threshold. 1 and decision threshold 2. If the sample variation coefficient is greater than threshold 1, it is judged as a non-visible channel; if the sample variation coefficient is less than threshold 2, it is judged as a visible channel; if If the sample coefficient of variation is greater than threshold 2 and smaller than threshold 1, it is judged as a quasi-visible channel.
  • the method of the present invention judges the visibility of a path based on a path's sample variation coefficient, it can effectively distinguish NLOS, LOS, and quasi-LOS propagation, and has a high recognition rate in a complex channel environment.
  • the array antenna is used to receive and transmit signals, and matching filtering is performed to obtain the power delay distribution corresponding to the signal received by each antenna, it is not necessary to perform long-term measurements on each mobile terminal, and it is possible to quickly and accurately identify non-visible channels.
  • the quasi-visible channel and the visible channel improve the real-time performance, the implementation method is simple, and the recognition rate is high.
  • the non-visible channel, the quasi-visible channel, and the visible channel can be effectively distinguished. Due to the difference of the first-path fading characteristics of the present invention under the non-visible channel, the quasi-visible channel, and the visible channel, not only It is applicable to the case where the mobile terminal is moving, and also applicable to the case where the mobile terminal is stationary. Brief description of the drawings
  • Figure 1 is the fading characteristic curve on the visible channel power delay distribution
  • Figure 2 is the fading characteristic curve on the power delay distribution of the invisible channel
  • FIG. 3 is a flowchart of the method of the present invention.
  • Figure 4 shows the distribution characteristics of the signal strength received by each antenna in the array antenna. Differences in the NLOS environment.
  • Figure 4a is the signal strength curve received by different antenna units at the same time in the LOS environment
  • Figure 4b is the signal strength curve received by different antenna units at the same time in the NLOS environment.
  • FIG. 5 is a flowchart of receiving by an array antenna to implement channel identification.
  • Figure 1 shows the fading curve of a single channel with Rice's fading characteristics, and the channel showing this fading is the visible channel
  • Figure 2 shows the fading curve of a single channel with Rayleigh fading characteristics.
  • a fading channel is an invisible channel.
  • the channel identification method of the present invention includes the following steps:
  • Step 301 Obtain multiple power delay profiles (PDP, Power Delay Profile) at the receiving end.
  • PDP Power Delay Profile
  • Step 302 Obtain a peak of a path as a sample in each power delay distribution, and obtain a total sample;
  • Step 303 Calculate the average and standard deviation of all sample values in the above sample population, and use the ratio of the standard deviation to the average as the sample coefficient of variation;
  • Step 304 Identify the non-visible channel, the quasi-visible channel, and the visible channel according to the sample variation coefficient. Obtaining continuous multiple power delay distributions described in step 301 may include the following steps:
  • Step A1 The receiving end receives a signal transmitted by the transmitting end
  • Step A2 the receiving end performs matched filtering on the received signal
  • Step A3 Perform at least one non-coherent accumulation on the result of the matched filtering obtained in step A2 to obtain a power delay distribution. After matched filtering and multiple non-coherent accumulation, the influence of noise can be effectively eliminated.
  • the receiving end and the transmitting end of the present invention include two cases, that is, the receiving end is a mobile station, the transmitting end is a base station; the receiving end is a base station, and the transmitting end is a mobile station.
  • step 302 obtaining a sample value in each power delay distribution is performed by using the peak diameter of the first path as a sample, and includes the following steps:
  • Step B11 Select the first-path peak in the first multi-path power delay distribution as a sample;
  • Step B21 For subsequent power delay distributions, according to the first power delay distribution, the first detected near the peak position of the first-path peak The peak diameter is used as a sample.
  • step 303 the calculation of the standard deviation in step 303 is replaced by an approximate algorithm with the standard formula, and the approximate algorithm is calculated according to the following steps:
  • Step Cl Find the absolute value of the difference between each sample value and the average value
  • Step C2 Take the average of each absolute value of Step C1 as the standard deviation.
  • the non-visible channel, the quasi-visible channel, and the visible channel are determined according to the sample variation coefficient.
  • the double threshold can be used in the specific implementation. The determination includes the following steps: Step D1. If the sample discrete variation coefficient is greater than the threshold 1, the preaching is a non-visible channel;
  • Step D2 If the sample variation coefficient is less than the threshold 2, the channel is a visible channel; Step D3, if the sample variation coefficient is greater than the threshold 2 and less than the threshold 1, the channel is a quasi-visible channel; Among them, the threshold 1 is greater than the threshold 2. For example, when the number of non-coherent accumulations of the outdoor channel is 10, the threshold 1 is taken as 0.4, and the threshold 2 is taken as 0.1. The larger the threshold 1 is, the higher the accuracy of the non-visual propagation path judgment is, but the higher the missed judgment rate is. On the contrary, the accuracy rate decreases, and the false alarm rate increases. The smaller the threshold 2 is, the higher the accuracy of judging the visible propagation path is, but the higher the rate of missed judgment is. On the contrary, the accuracy is reduced and the false alarm rate is increased.
  • the non-visible and visible paths are determined according to the sample variation coefficient, and a single threshold may also be used. The determination includes the following steps:
  • the channel is an invisible channel; otherwise, the propagation channel is a visible channel or a quasi-visible channel.
  • the threshold can be any value between 0.0 and 1.0 when the number of non-coherent accumulations of the outdoor channel is 10. For example, if 0.4 is selected, the larger the threshold, the higher the accuracy of the judgment of the non-visible channel, but The lower the accuracy of the judgment of the channel and the quasi-visible channel, the higher the accuracy of the judgment of the visible channel, but the lower the accuracy of the judgment of the non-visual channel.
  • FIG. 4 shows a difference between a signal strength distribution characteristic received by each antenna in the array antenna under the LOS and LOS environments.
  • Figure 4a is a signal strength curve received by different antenna units of an array antenna at the same time in the LOS environment
  • Figure 4b is a signal strength curve received by different antenna units of the array antenna at the same time in the LOS environment.
  • the signal intensity distribution characteristic curve 101 in the LOS environment obeys Rice fading characteristics
  • the signal intensity distribution characteristic curve 102 in the NLOS environment Fading characteristics. This difference in fading characteristics is mainly caused by channel fading.
  • FIG. 5 is a process of implementing invisible and visible channel identification by using an array antenna receiving, which is divided into 4 steps:
  • multiple power delay distributions are obtained by using multiple signals received by an array antenna.
  • Each antenna unit of the array antenna receives the same signal independently, and the matched filter bank performs matched filtering on the signals independently received by each antenna unit to obtain multiple power delay distributions corresponding to the same signal.
  • the power delay distribution may be obtained through multiple non-coherent accumulations or a single non-coherent accumulation.
  • the matched filter bank may perform matched filtering on the signals received by each antenna unit in parallel to obtain each
  • the power delay distribution corresponding to the antenna unit may also be processed one by one. After matching filtering on the received signal of one antenna unit to obtain a power delay distribution, then perform matching filtering on the received signal of the other antenna unit to obtain another Power delay distribution.
  • a sample is selected from each power delay distribution obtained in the first step.
  • a sample is selected, and a first path judgment is performed for each power delay distribution, and a peak (power or amplitude) of the first path is stored.
  • the peak of the first path on each power delay distribution is used as the sample population needed to calculate the sample coefficient of variation.
  • the third step 503 is to calculate the average value and standard deviation of these samples according to the statistical method, based on the sample population obtained in the second step, that is, the peaks (power or amplitude) of multiple first paths. ratio. You can also first calculate the difference between each sample value and their average, and find the sum of the absolute values of these differences, then average the sum to get the approximate standard deviation, and divide the approximate standard deviation by the average to get the approximate sample variation coefficient.
  • the sample variation coefficient output in the third step 503 is compared with the decision threshold obtained from the empirical data.
  • a single threshold can be used for comparison, such as taking a threshold of 0.4, or a dual threshold, and setting the threshold 1> threshold 2 For example, if threshold 1 is 0.4, threshold 2 is 0.1.
  • the sample variation coefficient is compared with the single threshold. If the sample variation coefficient is greater than or equal to the threshold, it is judged as LOS, and if the sample variation coefficient is less than the threshold, it is judged as LOS or Quasi-LOS.
  • the double threshold if the sample variation coefficient is greater than threshold 1, it is judged as NLOS; if the sample variation coefficient is less than threshold 2, it is judged as LOS; if it is between two thresholds, it is judged as quasi-LOS.

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Description

一种信道识别的方法
技术领域
本发明涉及移动通信技术领域， 尤其涉及一种无线信道种类的识別 方法。 发明背景
在移动通信系统中， 非可视传播路径的存在使得移动终端和基站之 间的传播时延中包含了一项附加时延 ( Excess Delay )误差， 这项附加时 延误差严重影响移动终端定位精度， 为了有效地抑制非可视传播路径 ( NLOS ) 引入的附加时延误差对定位精度的影响， 需要采用 NLOS信 道识別技术。
移动终端定位系统中的 NLOS 识别技术首先由 M.RWylie在题为 "Non-Line of Sight Problem in Mobile Location Estimation" (以下称文 献 1 ) 的论文中讨论， 在 1997年 9月， MJP.Wylie 向美国专利局递交了 一份矫正移动终端定位中 NLOS误差的专利申请 US 5,974,329 (以下称 文献 2 ), 该专利将 NLOS识別技术作为构成其发明的一个要素， 文献 1 和文献 2中所述的 NLOS识别方法的基本思路是： ( 1 )对各个基站测量 得到的移动终端到该基站间的距离进行长时间的记录； （2 )对记录的大 量数据进行平滑处理； （3 )利用 NLOS情况下测量方差（相对于平滑后 的数据，该方差由地貌特怔和系统测量误差造成 )远大于 LOS时的测量 方差 （该方差由系统测量误差造成）这个事实， 进行 LOS识别。
文献 1和文献 2中提出的识别方法需要利用移动终端的时间相关性， 对运动中的移动终端的轨迹进行较长时间的跟踪和平滑才可以输出 NLOS识别结果， 需要较长的数据积累时间， 因此易产生大的时延， 难 以满足 FCC (联邦通信委员会）对响应时间的要求， 不具备实时性， 只 适用于移动终端运动时的可视路径识别。
本申请人在申请号为 CN01145H3.0、名称为 "CDMA移动通信系统 中可视与非可视信道的识别方法"的专利申请 (以下筒称文献 3)中，提出 了一种利用同一个功率时延分布上的可视路径功率强度和非可视路径 功率强度之间的差异进行识别的基本方法， 包括以下步骤：
A、 读入功率时延分布；
B、 从整个功率时延分布中挑选出幅度最大的最强径；
C；、 确定平均噪声功率， 并确定第 1 径的到达时间和最强径的到达 时间；
D、 在局部最强径的搜索窗宽度内， 检测到局部最强径并取值， 判 断最强径与局部最强径的比值是否大于门限 K;
E、 判断第 1 径的到达时间与最强径的到达时间之差是否小于一时 间定值 T;
F、在同时满足最强径与局部最强径的比值大于门限 K,和第 1径的 到达时间与最强径的到达时间之差小于时间定值 T时，判定为可视信道， 否则判定为非可视信道。
这种基于径间功率 （或幅度）差别的识别方法的缺点是： 由于这种 方法是基于形状匹配的， 当信道环境复杂时识别率会下降， 而且难以区 分 LOS和具有小的传播路径误差的准 LOS, 限制了移动台定位精度的 进一步提高。 发明内容
本发明的目的在于提供一种信道的识别方法， 以在复杂信道环境下 识别出可视信道、 准可视信道、 非可视信道， 提高信道识别的实时性和 识别率。
本发明通过以下技术方案实现：
一种信道识别方法， 包括如下步骤：
A )在接收端获取多个功率时延分布 ( PDP, Power Delay Profile ); B )在每个功率时延分布中分別取得一个径的峰值作为一个样本,获 得样本总体；
C )根据样本总体计算样本变异系数；
D )根据样本变异系数识别非可视信道、 准可视信道和可视信道。 较佳地， 所述获取连续的多个功率时延分布包括如下步骤：
All )接收端对发射端发射的信号进行接收；
A12 )接收端对接收到的信号进行匹配滤波；
A13 )对步骤 A12所得匹配滤波的结果进行至少一次非相干累加，得 到功率时延分布。
较佳地， 所述获取多个功率时延分布包括: 在使用阵列天线的接收 端获取每个天线单元所接收信号对应的功率时延分布。 所述获取每个天 线单元所接收信号对应的功率时延分布包括 ,
A21 )每个天线单元独立地同时接收同一路信号；
A22 ) 匹配滤波每个天线单元所接收的信号；
A23 )对步骤 A22所得匹配滤波的结果进行至少一次非相干累加， 得到功率时延分布。
较佳地， 步驟 B包括如下步骤：
在每个功率时延分布内挑选出首径的峰值作为样本总体。
步骤 C包括，
C11)根据样本总体计算样本平均值和标准差;
C12) 求取标准差与样本平均值的比值， 将该比值作为样本变异系 数。
步骤 D包括：
Dl 1 )预先设置判决门限 1和判决门限 2， 并设置门限 1大于判决门 限 2;
D12 )将样本变异系数与判决门限 . 1和判决门限 2相比较， 如果样 本变异系数大于门限 1 , 则判为非可视信道； 如果样本变异系数小于门 限 2, 则判为可视信道； 如果样本变异系数大于门限 2并且小于门限 1， 则判为准可视信道。
由于本发明方法基于径的样本变异系数判断路径的可视性， 能够有 效的区分 NLOS、 LOS和准 LOS传播，并且在复杂信道环境下具有较高 识别率。
由于采用阵列天线接收发射信号， 并分别进行匹配滤波以获取每个 天线接收到的信号对应的功率时延分布， 不需对各个移动终端进行长时 间的测量， 能够快速准确地识别非可视信道、 准可视信道和可视信道， 提高了实时性， 实现方法筒单， 识别率高。
通过采用双门限判决， 能够有效区分非可视信道、 准可视信道和可 视信道； 由于本发明根据首径衰落特性在非可视信道、 准可视信道和可 视信道下的差异， 不仅适用于移动终端运动的情况, 也适用于移动终端 静止的情况。 附图简要说明
图 1是可视信道功率时延分布上的衰落特性曲线；
图 2是非可视信道功率时延分布上的衰落特性曲线；
图 3是本发明方法的流程图。
图 4表示了阵列天线中各天线接收到的信号强度分布特性在 LOS和 NLOS环境下的差异。 图 4a为 LOS环境下同一时刻不同天线单元接收 到的信号强度曲线， 图 4b为 NLOS环境下同一时刻不同天线单元接收 到的信号强度曲线。
图 5为利用阵列天线接收以实现信道识別的流程。 实施本发明的方式
下面结合附图对本发明进行详细描述。
实施例 1
通过大量样本采集和分析，得出如图 1和图 2所示的功率（或幅度） 的衰落特性曲线。图 1给出的是呈莱斯衰落特性的单个信道的衰落曲线， 呈这种衰落的信道就是可视信道； 图 2给出的是呈瑞利衰落特性的单个 信道的衰落曲线， 呈这种衰落的信道就是非可视信道。 通过对图 1和图 2 的比较可以看出， 两种衰落曲线的重要差异之一表现为样本变异系数 σ / μ的不同。 显然样本变异系数 σ / μ在 NLOS信道下显著大于 L0S信 道下的值，本发明方法就是利用这种样本变异系数 σ / μ的差异来实现非 可视信道、 准可视信道和可视信道识别的。
参照图 3 , 本发明的信道识别方法， 包括如下步骤：
步骤 301、 在接收端获取多个功率时延分布 （PDP, Power Delay Profile );
步骤 302、 在每个功率时延分布中分别取得一个径的峰值作为一个 样本,获得样本总体；
步驟 303、 计算上述样本总体中所有样本值的平均值和标准差， 并 将标准差与平均值的比值作为样本变异系数；
步驟 304、 根据样本变异系数识别非可视信道、 准可视信道和可视 信道。 执行步骤 301 所述的获取连续的多个功率时延分布可包括如下步 骤：
步骤 A1、 接收端接收发射端发射的信号；
步驟 A2、 接收端对接收到的信号进行匹配滤波；
步骤 A3、对步骤 A2所得匹配滤波的结果进行至少一次非相干累加， 得到功率时延分布。 经过匹配滤波和多次非相干累加可有效地消除噪声 影响。
本发明所说接收端与发射端包括两种情形， 即接收端为移动台， 则 发射端为基站； 接收端为基站， 则发射端为移动台。
步驟 302中， 所述在每个功率时延分布中取得一个样本值是以首径 峰值作为样本进行， 包括如下步驟：
步骤 B11、在第一个多径功率时延分布内挑选出首径峰值作为样本； 步骤 B21、 对后续的功率时延分布， 根据第一个功率时延分布首径 峰值位置附近检测出的首径峰值作为样本。
为提高运算效率， 作为本发明的进一步改进， 将步骤 303中标准差 的计算以近似算法代替标准公式， 近似算法依如下步骤计算:
步骤 Cl、 求每个样本值与平均值的差的绝对值；
步骤 C2、 对步骤 C1的各绝对值取平均值作为标准差。
本发明方法在步骤 304中根据样本变异系数判断非可视信道、 准可 视信道和可视信道，具体执行中可以采用双门限，其判断包括如下步骤： 步骤 Dl、 如果样本离散变异系数大于门限 1 , 则传 道为非可视 信道；
步骤 D2、 如果样本变异系数小于门限 2, 则传 道为可视信道； 步驟 D3、 如果样本变异系数大于门限 2且小于门限 1 , .则传 道 为准可视信道； 其中， 门限 1大于门限 2。 例如， 在室外信道非相干累加次数为 10 时， 门限 1取 0.4, 门限 2取 0.1。 门限 1越大， 则对非可视传播路径判 断的准确率越高， 但漏判率也越高， 反之准确率降低， 虚警率增加。 门 限 2越小， 则对可视传播路径判断的准确率越高但漏判率也越高， 反之 准确率降低， 虚警率增加。 ― . 步骤 304中根据样本变异系数判断非可视与可视路径， 也可以采用 单门限， 其判断包括如下步骤：
如果样本变异系数大于或等于门限， 则传 道为非可视信道； 否 则传播信道为可视信道或准可视信道。 例如， 其中门限在室外信道非相 干累加次数为 10时可以取 0.0〜1.0之间的任意值， 如选 0.4， 该门限越 大， 对非可视信道的判断准确率越高， 但对可视信道和准可视信道的判 断准确率越低， 反之对可视信道的判断准确率越高， 但对非可视信道的 判断准确率越低。
实施例 2
参见图 4所示， 图 4表示了阵列天线中各天线接收到的信号强度分 布特性在 LOS和 LOS环境下的差异。图 4a为 LOS环境下同一时刻阵 列天线不同天线单元接收到的信号强度曲线， 图 4b为 LOS环境下同 一时刻阵列天线不同天线单元接收到的信号强度曲线。 从图 4可见， 同 一时刻阵列天线不同天线单元上的信号强度分布特性的差异， 在 LOS 环境下信号强度分布特性曲线 101服从莱斯衰落特性， 在 NLOS环境下 信号强度分布特性曲线 102 良从瑞利衰落特性， 这种衰落特性的差异主 要是由信道的衰落造成的， 这种差异最直接的表现就是样本变异系数 σ/μ在 NLOS环境下的值显著大于 LOS环境下的值。 本发明也可利用阵 列天线中各天线单元接收到的信号强度的样本变异系数的差异性进行 非可视信道、 准可视信道和可视信道的识别。 参见图 5所示， 图 5为利用阵列天线接收实现非可视和可视信道识 别的流程， 分为 4步：
第一步 501 , 利用阵列天线接收到的多路信号得到多个功率时延分 布。 阵列天线的每个天线单元独立地接收同一路信号， 匹配滤波器组对 每个天线单元独立地接收到的信号分别进行匹配滤波以得到同一路信 号对应的多个功率时延分布。 上述功率时延分布可以是经过多次非相干 累加的， 也可以是单次非相干累加结果； 上述匹配滤波器组可以对每个 天线单元接收到的信号并行进行匹配滤波， 同时地得到每个天线单元对 应的功率时延分布， 也可以是逐个处理， 在对一个天线单元的接收信号 进行匹配滤波获取一个功率时延分布后， 再对另一个天线单元的接收信 号进行匹配滤波以获取另一个功率时延分布。
第二步 502， 从第一步得到的每个功率时延分布中挑.选样本， 对每 个功率时延分布进行首径判决， 并存储首径的峰值（功率或幅度）， 将 存储的每个功率时延分布上首径的峰值作为计算样本变异系数所需要 的样本总体。
第三步 503 , 根据第二步得到的样本总体即多个首径的峰值（功率 或幅度）， 按统计方法计算这些样本的平均值和标准差， 样本变异系数 为标准差与样本平均值的比值。 也可以首先计算每个样本值与它们平均 值的差，并求这些差的绝对值之和，然后将该和值平均得到近似标准差, 将该近似标准差除以平均值得到近似的样本变异系数。
第四步 504, 将第三步 503输出的样本变异系数与从经验数据获取 的判决门限比较， 比较时可以使用单门限， 如门限取 0.4, 也可以使用 双门限， 并设置门限 1〉门限 2, 如门限 1取 0.4, 门限 2取 0.1。 当采 用单门限， 将样本变异系数与单门限进行比较， 如果样本变异系数大于 或等于门限， 就判为 LOS， 如果样本变异系数小于门限， 判为 LOS或 准 LOS。 当采用双门限， 如果样本变异系数大于门限 1 , 就判为 NLOS， 如果样本变异系数小于门限 2, 就判为 LOS， 如果在两个门限之间， 就 判为准 LOS。
除了利用径的功率 （或幅度） 的样本变异系数之外， 还可以利用径 的信干比的样本变异系数进行 NLOS识别。

Claims

权利要求书
1、 一种信道识别方法， 其特征在于， 包括如下步驟：
A )在接收端获取多个功率时延分布；
B )在每个功率时延分布中分别取得一个径的峰值作为一个样本,获 得样本总体；
C )根据样本总体计算样本变异系数；
D )根据样本变异系数识别非可视信道、 准可视信道和可视信道。
2、 如权利要求 1所述的识别方法， 其特征在于， 步骤 A包括如 下步驟：
Al l )接收端对发射端发射的信号进行接收；
A12 )接收端对接收到的信号进行匹配滤波；
A13 )对步骤 A12所得匹配滤波的结果进行至少一次非相干累加，得 到功率时延分布。
3、 如权利要求 2所述的识别方法， 其特征在于， 接收端为移动 台， 发射端为基站。
4、 如权利要求 2所述的传播路径可视性识别方法， 其特征在于： 接收端为基站， 发射端为移动台。
5、 如权利要求 1所述的识别方法， 其特征在于， 步驟 B包括如 下步骤：
B21 )在第一个功率时延分布上挑选出首径的峰值作为样本； B22 )对后续的功率时延分布， 根据第一个功率时延分布首径峰值 位置附近检测出的首径峰值作为样本。
6、 如权利要求 1 所述的识别方法， 其特征在于， 所述获取的多 个功率时延分布包括： 在使用阵列天线的接收端获取每个天线单元所接 收信号对应的功率时延分布。
7、 如权利要求 6所迷的识别方法， 其特征在于， 所述获取每个 天线单元所接收信号对应的功率时延分布包括，
A21 )每个天线单元独立地同时接收同一路信号；
A22 ) 匹配滤波每个天线单元所接收的信号； . A23 )对步骤 A22所得匹配滤波的结果进行至少一次非相干累加， 得到功率时延分布。
8、 如权利要求 Ί所述的识别方法， 其特征在于， 所述步骤 A22 包括， 对每个天线单元接收的信号并行地进行匹配滤波， 同时地得到每 个天线单元对应的功率时延分布。
9、 如权利要求 7所述的识别方法， 其特征在于， 所述步骤 A22 包括， 对每个天线单元接收的信号逐个地进行匹配滤波， 逐一地得到每 个天线单元对应的功率时延分布。
10、 如权利要求 7所述的识别方法， 其特征在于， 步骤 B包括， 在每个天线单元时延分布内挑选出首径峰值作为样本。
11、 如权利要求 1所述的传播路径可视性识别方法， 其特征在于， 步骤 C包括，
C11)根据样本总体计算样本平均值和标准差；
C12) 求取标准差与样本平均值的比值， 将该比值作为样本变异系 数。
12、 如权利要求 1所述的识别方法， 其特征在于， 步骤 C包括， C21 )根据样本总体计算样本平均值；
C22 ) 求每个样本值与样本平均值差的绝对值， 并计算该绝对值的 平均值， 作为近似标准差； .
C23 ) 求取近似标准差与样本平均值的比值， 将该比值作为样本变 异系数。
13、 如权利要求 1所述的识别方法， 其特征在于， 所述步骤 D包 括: 判断样本变异系数是否不小于预定的判决门限， 如果是， 则判决为 非可视信道， 否则， 判决为可视信道。
14、 如权利要求 1所述的识别方法， 其特征在于， 所述步骤 D包 括：
D11 )预先设置判决门限 1和判决门限 2， 并设置门限 1大于判决门 限 2;
D12 )将样本变异系数与判决门限 1和判决门限 2相比较， 如果样 本变异系数大于门限 1 , 则判决为非可视信道； 如果样本变异系数小于 门限 2, 则判决为可视信道； 如果样本变异系数大于门限 2并且小于门 限 1， 则判决为准可视信道。
PCT/CN2003/000726 2002-11-05 2003-08-28 Procede d'identification de canaux WO2004043089A1 (fr)

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