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WO2007030972A1 - Baseband processing method for improving signal-to-noise ratio based on multiple sampling - Google Patents

Baseband processing method for improving signal-to-noise ratio based on multiple sampling Download PDF

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Publication number
WO2007030972A1
WO2007030972A1 PCT/CN2005/001478 CN2005001478W WO2007030972A1 WO 2007030972 A1 WO2007030972 A1 WO 2007030972A1 CN 2005001478 W CN2005001478 W CN 2005001478W WO 2007030972 A1 WO2007030972 A1 WO 2007030972A1
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Prior art keywords
channel
channel estimation
signal
noise ratio
user
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English (en)
French (fr)
Inventor
Hai Jiang
Ping Li
Peng Geng
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ZTE Corp
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ZTE Corp
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Priority to PCT/CN2005/001478 priority Critical patent/WO2007030972A1/zh
Priority to KR1020087008740A priority patent/KR101041009B1/ko
Priority to HK07113355.5A priority patent/HK1108523B/zh
Priority to EP05785082.8A priority patent/EP1940041B1/en
Priority to CN200580049522XA priority patent/CN101167262B/zh
Publication of WO2007030972A1 publication Critical patent/WO2007030972A1/zh
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69Spread spectrum techniques
    • H04B1/707Spread spectrum techniques using direct sequence modulation
    • H04B1/7097Interference-related aspects
    • H04B1/7103Interference-related aspects the interference being multiple access interference
    • H04B1/7105Joint detection techniques, e.g. linear detectors
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0224Channel estimation using sounding signals
    • H04L25/0228Channel estimation using sounding signals with direct estimation from sounding signals
    • H04L25/023Channel estimation using sounding signals with direct estimation from sounding signals with extension to other symbols
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B1/00Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69Spread spectrum techniques
    • H04B1/707Spread spectrum techniques using direct sequence modulation
    • H04B1/7097Interference-related aspects
    • H04B1/7103Interference-related aspects the interference being multiple access interference
    • H04B1/7105Joint detection techniques, e.g. linear detectors
    • H04B1/71052Joint detection techniques, e.g. linear detectors using decorrelation matrix

Definitions

  • the present invention relates to a baseband processing method for improving signal-to-noise ratio based on multiple sampling in a mobile communication system.
  • shaping filters are typically used at the transceiver end to limit communication bandwidth.
  • the sampling time point at the receiving end affects the signal-to-noise ratio of the sampled signal, and the signal-to-noise ratio is maximized when sampling at a specific time point.
  • the multipath delay of the user is randomly changed, which makes the signal-to-noise ratio of the sampled signal also randomly changed, which will cause a certain loss to the system performance.
  • the Chinese patent No. 00105846.0 entitled “A Signal Processing Method for Terminal Devices in Code Division Multiple Access Mobile Communication Systems", proposes a multi-sampled signal processing method using joint detection, which is applied to a CDMA system. Its principle is that the receiving end performs multi-channel sampling in one chip, each channel performs channel estimation separately, and then participates in joint detection. The advantage of this is that under the condition of multipath delay random, the signal-to-noise ratio of the average sampled signal obtained by multi-channel sampling is higher than that of single-channel sampling, so as to improve the performance of the system.
  • the multipath noise in the multi-channel sampled signals within one chip is correlated, so the diversity gain brought about by the combination of the multiple signals is not the maximum ratio of the combined gain.
  • the signal-to-noise ratio after combining multiple signals is between the one with the largest signal-to-noise ratio and the one with the smallest signal-to-noise ratio, rather than the sum of the signal-to-noise ratios of the multiple signals (maximum ratio combining). That is to say, the signal-to-noise ratio after multiplexing of multiple signals is smaller than the maximum signal-to-noise ratio that can be obtained.
  • the simulation also verified this.
  • the technical problem to be solved by the present invention is to propose a new baseband processing scheme based on multi-sampling to improve the signal-to-noise ratio to resist the deterioration of the signal-to-noise ratio caused by the wireless random channel, and further improve the signal-to-noise ratio.
  • the idea of the present invention is as follows: Multi-channel sampling is performed on each chip of a received signal, and each channel is separately subjected to channel estimation, and the multi-channel channel estimation of each user is compared, and the power is relatively large. At the same time, the channel estimation tap with smaller noise correlation participates in the matched filtering in the joint detection.
  • the present invention provides a baseband processing method for improving signal-to-noise ratio based on multiple sampling, which includes the following steps:
  • step (b) the channel estimation is obtained by using a formula, where is the training sequence signal of the sth sampling, M is the training sequence matrix of the transmission, and ⁇ is the user of the current cell sampled by the sth channel The channel impulse response.
  • step (c) can be obtained by the following steps:
  • step (c4) Re-restoring the complete channel estimation sequence obtained after the processing of step (c3) into the channel estimation 3 ⁇ 4P of the N-channel samples.
  • step (c) can also be implemented by the following steps:
  • the method of the present invention participates in the matched filter interference cancellation in the joint detection by selecting the channel estimation tap with high power and uncorrelated noise in the multi-channel sampling, thereby achieving the purpose of improving the signal-to-noise ratio and improving the system performance.
  • the present invention is applicable to any mobile digital communication system, and is particularly applicable to systems employing a joint detection scheme.
  • the invention can be applied to both a base station and a terminal, and can be used in both a single antenna environment and a multi-antenna environment.
  • FIG. 1 is a schematic view showing a processing procedure of a method according to a first embodiment of the present invention
  • Figure 2 is a schematic illustration of the processing of the method of the second embodiment of the present invention.
  • a baseband processing method for improving signal-to-noise ratio based on multiple sampling uses the following steps: Step 101: Perform multi-channel sampling in each chip of the received signal;
  • the training sequence signal of the sth sample is denoted as ⁇ l, ..., N.
  • Step 102 Perform channel estimation on the sampling signals of the N channels respectively.
  • the received training sequence is a multi-user training sequence signal superimposed with noise interference after multi-path superposition, which can be expressed as:
  • M is the transmitted training sequence matrix, which is the channel impulse response of all users in the cell sampled by the sth channel, and is the noise of the S-th channel sample superimposed on the training sequence.
  • the channel estimate for each sample can be expressed as:
  • the channel impulse response of the S-th sample is assumed to have a dimension of [3 ⁇ 4 ⁇ 1].
  • Step 103 Perform channel post-processing on the channel estimation of each sampled signal to obtain a tap position of the user signal path;
  • the power of each tap is compared with a threshold.
  • the tap below the threshold is considered to be noise, and its value is set to zero.
  • the tap above the threshold is considered to be a signal, and its value is unchanged.
  • m is equal to 3
  • N is equal to 2
  • Step 105 Process the complete channel estimation, select a tap with a large power and no correlation between the noises, and set other taps to zero;
  • h total (I) is the complete channel estimation sequence before sorting. Then, for ⁇ ... ⁇ ⁇ , the operation of the pair is repeated, that is, the taps with high power and mutual noise are selected.
  • This step assumes that the noise of the multiple samples in one chip is correlated, so that the channel impulse response taps of the larger power are retained, and the tap values in the left and right chips are zeroed. Does not participate in matched filtering, because the combination of noise-correlated sampled signals does not bring gain.
  • Step ⁇ 106 the channel estimation obtained by the processing in the previous step 105 is reduced to N channel sampling, and is recorded as 3 ⁇ 4P, as follows:
  • Step 107 Generate a scrambling code and a spreading code of the local cell.
  • step 108 a system matrix is constructed using each user's spreading code, scrambling code, and channel estimate.
  • Step 109 Construct a matched filter matrix 4 by using a spreading code of each user, a scrambling code, and a channel estimation of the matched filtering participating in the joint detection.
  • Step 110 Perform joint detection on the user's signal to obtain symbols of each user.
  • the multiplexed sampled signal of the received data portion can be expressed as:
  • the system matrix of the S-th channel sampling which is composed of each user's spreading code, scrambling code and channel estimation.
  • the matched filtering system matrix 4 F sampled by the s-channel is composed of a spreading code and a scrambling code for each user.
  • the channel estimation involved in the matched filtering is composed of 3 ⁇ 4 ⁇ . Then the estimate of the user symbol d in (6) is: Zero-block linear equilibrium estimation:
  • the key point of the method in this embodiment is that the matched filtering in the joint detection is selected in the multi-channel sampling signal, and the noise-independent multipath is involved in the joint detection to obtain the diversity gain.
  • Step 201 Perform chip multipath sampling on the received signal
  • Step 202 Perform channel estimation on the N channel sampling signals respectively.
  • the received training sequence is a multi-user training sequence signal superimposed with noise interference after multi-path superposition, which can be expressed as:
  • M is the transmitted training sequence matrix, which is the channel impulse response of all users in the cell sampled by the sth channel, and is the noise of the s channel sample superimposed on the training sequence.
  • the channel estimate for each sample can be expressed as:
  • the dimension of the channel impulse response / ⁇ sampled by the sth channel is assumed to be ⁇
  • Step 204 Compare, for each channel sampled channel estimation, within one chip time, select a maximum value, and set other values to zero;
  • Step 205 Generate a scrambling code and a spreading code of the local cell.
  • Step 206 Form a system matrix by using a spreading code, a scrambling code, and a channel estimation of each user. After the steps 205 and 206 are performed in step 202, the steps 203 and 204 may be performed in parallel with steps 203 and 204. There is no succession in execution.
  • Step 207 Construct a matching filter matrix by using a spreading code of each user, a scrambling code, and a channel estimation of the matched filtering participating in the joint detection.
  • Step 208 Perform joint detection on the user's signal to obtain the symbol of each user ⁇
  • the multiplexed sampled signal of the received data portion can be expressed as:
  • is the system matrix of the sth channel sample, which consists of the spreading code, scrambling code and channel estimation of each user.
  • a matched filtering system matrix 4 F is constructed , which is composed of a spreading code of each user, a scrambling code and channel estimation participating in matched filtering. Then the estimate of the user symbol d in (12) is: Zero-block linear equilibrium estimation -
  • is the noise power
  • the key of the second embodiment is to compare the modes of the channel estimation of the N samples in one chip time, select the maximum value, participate in the matching filtering in the joint detection, and set other values to zero, and do not participate in the matching in the joint detection. Filtering. This is simpler than the solution. However, the noise between the taps with the highest channel estimation power in each chip in scheme 2 may still be correlated, so there may be some loss in performance.
  • the solution described in the present invention achieves the purpose of improving the signal-to-noise ratio by selecting the channel estimation taps with high power and uncorrelated noise in the multi-channel sampling, participating in the matching green and interference cancellation in the joint detection.
  • the invention can be applied to both a base station and a terminal, and can be used in a single antenna environment as well as in a multi-antenna environment.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Noise Elimination (AREA)
  • Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)
  • Mobile Radio Communication Systems (AREA)

Description

一种基于多倍采样的提高信噪比的基带处理方法
技术领域
本发明涉及移动通信系统中基于多倍采样的提高信噪比的基带处理方 法。
背景技术
在数字通信系统中, 为了限制通信带宽在收发端一般都会使用成形滤波 器。 在使用成形滤波器的情况下, 接收端采样时间点会影响采样信号的信噪 比,在特定的时间点采样,信噪比才得到最大。然而由于无线信道的随机性, 用户多径时延是随机变化的, 这使得采样信号的信噪比也是随机变化的, 这 会给系统性能带来一定的损失。
为了改善随机无线信道下的采样点信噪比, 一般采用提高采样速率的方 法。 申请号为 00105846.0, 名称为 "码分多址移动通信系统中终端设备端的 一种信号处理方法"的中国专利提出了一种使用联合检测的多倍采样信号处 理方法, 应用于 CDMA系统中。 它的原理是接收端在一个码片内进行多路 采样, 每路分别做信道估计, 然后都参加联合检测。 这样做的好处是在多径 时延随机的条件下, 多路采样得到的平均采样信号信噪比比单路采样的信噪 比要高, 从而达到改善系统性能的目的。
然而, 由于接收端成形滤波器的使用, 一个码片内的多路采样信号中的 多路噪声之间是相关的, 因此多路信号之间合并带来的分集增益并不是最大 比合并的增益, 实际上多路信号合并之后的信噪比是介于信噪比最大的一路 与信噪比最小的一路之间的,而不是多路信号的信噪比之和(最大比合并)。 也就是说, 多路信号合并之后的信噪比比可以获得的最大信噪比要小。 仿真 也验证了这一点, 当将无线信道设置成同步, 使得每个用户的每条多径的采 样点都保证最大信噪比时, 多倍采样后按照上述方法处理的性能要比单倍采 样的性能差。 发明内容
本发明要解决的技术问题是提出一种新的基于多倍采样的提高信噪比 的基带处理方案, 以抵抗无线随机信道带来的信噪比恶化, 进一步提高信噪 比。
为了解决上述技术问题, 本发明的思路如下: 对接收信号的每个码片内 进行多路采样, 每一路信号分别做信道估计, 对每个用户的多路信道估计进 行比较, 取功率较大同时噪声相关性又较小的信道估计抽头参与联合检测中 的匹配滤波。
为了实现本发明的思路, 本发明提供了一种基于多倍采样的提高信噪比 的基带处理方法, 包括以下步骤:
(a)对接收信号的每个码片内进行 N 次采样, 得到 N 路采样数据 em s, s = .,N;
(b)对接收到的每一路采样信号分别做信道估计 s = \,...,N;
(c)对每一路的信道估计 进行比较,确定功率较大同时噪声相关性较小 的信道估计 ,构成匹配滤波矩阵
(d)用系统矩阵 和匹配滤波矩阵 ^F, 对用户的信号做联合检测, 得到 各用户的符号 <ΐ。
进一步地, 步骤 (b) 中, 所述的信道估计 是利用公式 得到 的, 其中 为第 s次采样的训练序列信号, M是发射的训练序列矩阵, ^是 第 s路采样的本小区所有用户的信道冲激响应。
进一步地, 步骤 (c)中信道估计 可以采用如下步骤得到:
(cl)对每一路的信道估计 做信道后处理, 得出用户信号径的抽头位 置, 并得到信道后处理之后的信道估计/(0,z' = l,..., ,^l,...,N, 其中^是 每一路信道估计 的长度;
(c2)将信道估计 按照时间顺序合成一个完整的信道估计^ ^(), htola l) -. +s)=hps{i), i = H s = ...,N, l = l,...,N-Nm ; (c3)对 |^'"'( )|从大到小排序, 得到排序后的信道估计序列
Figure imgf000005_0001
然后从^开始依次到 ,执行以下运算:若 大于 0, 则保留排序前信道估计序列 中的该信道冲激响应抽头, 并将 htola' (l)中该抽头在左右各一码片内的其它抽头值置零;
(c4)将步骤 (c3 ) 处理后得到的完整的信道估计序列 再还原成 N 路采样的信道估计 ¾P。
进一步地, 步骤 (c)中 信道估计¾^还可以采用如下步骤实现:
(cl l)对每一路的信道估计 做信道后处理, 得出用户信号径的抽头位 置, 并得到信道后处理之后的信道估计 S ( ), = l,...,Nffl, ^l,...,N, 其中 ^是 每一路信道估计 的长度;
(cl2)对一个码片时间内的 N路采样的信道估计的模进行比较,选定最大 值, 其它值置为零, 得到 N路采样的信道估计 ¾^。
由上可知, 本发明方法通过选择多路采样中功率较大同时其噪声不相关 的信道估计抽头, 参与联合检测中的匹配滤波干扰消除, 从而达到提高信噪 比, 提高系统性能的目的。 本发明适用于任何移动数字通信系统, 尤其适用 于采用联合检测方案的系统。 本发明既可用于基站也可用于终端, 既可以用 于单天线环境, 也可以用于多天线环境。 附图概述
图 1 是本发明第一实施例方法的处理过程的示意图;
图 2是本发明第二实施例方法的处理过程的示意图。 本发明的最佳实施方式
下面结合附图对本发明的两个实施例作进一步的详细描述。
第一实施例 '
参考图 1, 一种基于多倍采样的提高信噪比的基带处理方法, 采用 如下步骤: 步骤 101: 在接收信号的每个码片内进行多路采样;
假设在接收信号的每个码片内进行 N次等时间间隔采样,第 s次釆 样的训练序列信号表示为^ l,...,N。
步骤 102: 对 N路的采样信号分别做信道估计;
接收到的训练序列是多用户的训练序列信号经过多径叠加之后, 与噪声 干扰再叠加, 可表示为:
=Mhs+nm s, s = l,...,N (1)
其中 M是发射的训练序列矩阵, 是第 s路采样的本小区所有用户的信 道冲激响应, 是第 S路采样的叠加在训练序列的噪声。 于是每路采样的信 道估计 可以表示为:
hs =M~lem s, s = l,...,N (2)
其中, 第 S路采样的信道冲激响应/ 的维数假设为]¾^1。
步骤 103: 对每一路采样信号的信道估计 做信道后处理, 得出用户信 号径的抽头位置;
也就是说, 将 的每个抽头的功率与一个门限进行比较, 低于门限的抽 头认为是噪声, 其值置为零, 高于门限的抽头认为是信号, 其值不变。,假设 信道后处理之后的信道估计记为 /(), =i,...,N„ =i,...,N。
步骤 104:将 N路采样的信道估计 ^ = l,...,N按照时间顺序排列,合成 为一个完整的信道估计 tal (l),l = l,...,N.Nm, 有:
^to,( IK(w +i)= ( 5 U m, s = \,...,N (3)
以一个实例说明, 假定: m等于 3, N等于 2, 信道估计序列 为
Figure imgf000006_0001
, 信道估计序列 为 (1), (2), (3) , 则组合后序列 ht0,al {l)=hl (1), h2 (1), h1 (2), h2 (2), hl (3), h2 (3)。
步骤 105, 对完整的信道估计^ ^进行处理, 选出功率较大且互相噪声 之间不相关的抽头, 其它抽头置为零;
对于序列^^ (/),/ = l,...,N.Nm,按 值的大小从大到小重新排序得到 序列 &ota! {k,),l=\,…… N.Nm, 即 | 。'。' (^)|≥ ψ°'α1 htota'[k ■N'Nm 对于 , 如果
Figure imgf000007_0001
, 则令:
ht1 •ot fal (/) = 0,/ = ¾ -(Ν-ί),^— (N一 2),..., —1, +1,^ + 2,^ + (N-1)
htotal (I)是排序前的完整的信道估计序列。然后对^^ ... Ν·Νη ,重复对 的操作, 即可选出功率较大且互相噪声之间不相关的抽头。
该过程用算法语言可以描述如下:
for /= 1 : N-N
|>0
hlotal{l) = Q,l = h-(N- ),h-(N-2),...,h-\,kl+\,kl+2,h + (N-\) (4) end if
end for
这一步是假设一个码片内的多路采样的噪声之间是相关的, 因此保留较 大功率的信道冲激响应抽头的同时, 将与之在左右各一码片内的抽头值置 零, 不参与匹配滤波, 因为噪声相关的各路采样信号的合并不能带来增益。
步^ 106, 将上一步骤 105中处理得到的 还原为 N路采样的信道 估计, 记为 ¾P, 如下式:
hM s F{i) = htotal {(i-\)N +s), i = \,...,Nm, s=l,...,N (5)
步骤 107, 产生本小区的扰码和扩频码。
步骤 108, 用每个用户的扩频码、 扰码和信道估计 构成系统矩阵 。 上述步骤 107和 108在步骤 102执行完成后, 即可与步骤 103-步骤 106 并行, 与步骤 103-步骤 106的执行没有先后关系。
步骤 109, 用每个用户的扩频码、 扰码和参与联合检测的匹配滤波的信 道估计 ¾Ρ构成匹配滤波矩阵 4。
步骤 110, 对用户的信号做联合检测, 得到各用户的符号
接收的数据部分的多路采样信号 可以表示为:
ed s =Asd + +nd s, s = l,...,N (6)
其中 是第 S路采样的系统矩阵, 由每个用户的扩频码、 扰码和信道估 计 构成。 第 s路采样的匹配滤波系统矩阵 4F由每个用户的扩频码、 扰码 和参与匹配滤波的信道估计 ¾^构成。 则对 (6) 中的用户符号 d的估计为: 迫零块线性均衡估计:
Figure imgf000008_0001
最小均方误差块线性均衡估计:
Figure imgf000008_0002
其中 是噪声功率。
本实施例方法的关键点在于在多路采样信号中挑出功率较大且噪声不 相关多径参与联合检测中的匹配滤波, 以获取分集增益。
第二实施例
第一实施例方法需要对各路信道估计进行排序, 复杂度较高。 本实施例 对此进行简化, 代价是性能可能有一定的损失。 参考图 2, 具体描述如下: 步骤 201 : 对接收信号做码片多路采样;
假设对接收信号每个码片内进行 Ν次等时间间隔采样,第 s次采样的训 练序列信号表示为^ s = U 。
步骤 202: 对 N路采样信号分别做信道估计;
接收到的训练序列是多用户的训练序列信号经过多径叠加之后, 与噪声 干扰再叠加, 可表示为:
em s = Mhs + nm s , s = l,...,N (9)
其中 M是发射的训练序列矩阵, 是第 s路采样的本小区所有用户的信 道冲激响应, 是第 s路采样的叠加在训练序列的噪声。 于是每路采样的信 道估计 可以表示为:
hs = M-xem s , s = l,...,N ( 10)
其中, 第 s路采样的信道冲激响应/^的维数假设为^^ ^
步骤 203 : 对每一路采样信号的信道估计 进行信道后处理, 得出用户 信号径的抽头位置; 也就是说, 将 的每个抽头的功率与一个门限进行比较, 低于门限的抽 头认为是噪声, 其值置为零, 高于门限的抽头认为是信号, 其值保留。 假设 信道后处理之后的信道估计记为 ft/ {i、,i = i,...,Nm,s = ..., N。
步骤 204: 对一个码片时间内的每一路采样的信道估计的模进行比较, 选出最大值, 其它值置为零;
该过程用算法语言可以描述如下:
for i= 1 : Nm
在^ s = l,..., 共 N个值, 选择最大值, 设其序号为 ^, 令:
¾7 (0 = 應 (0
F(i) = 0, s = l,...>Sm^-l,Smail +l,...,N (11)
end for。
步骤 205: 产生本小区的扰码和扩频码;
步骤 206: 用每个用户的扩频码、 扰码和信道估计 构成系统矩阵 上述步骤 205和 206在步骤 202执行完成后,即可与歩骤 203和步骤 204 并行, 与步骤 203和步骤 204的执行没有先后关系。
步骤 207: 用每个用户的扩频码、 扰码和参与联合检测的匹配滤波的信 道估计 ^构成匹配滤波矩阵 ;
步骤 208: 对用户的信号进行联合检测, 得到各用户的符号^
接收的数据部分的多路采样信号 可以表示为:
ed s =Asd + +nd s, s = l,...,N (12)
其中 ^是第 s路采样的系统矩阵, 由每个用户的扩频码、 扰码和信道估 计 构成。 同时构成匹配滤波系统矩阵 4F, 由每个用户的扩频码、 扰码和 参与匹配滤波的信道估计 构成。 则对 (12) 中的用户符号 d的估计为: 迫零块线性均衡估计-
Figure imgf000009_0001
最小均方误差块线性均衡估计-
Figure imgf000010_0001
其中 ^是噪声功率。
实施例二的关键是对一个码片时间内的 N路采样的信道估计的模进行 比较, 选出最大值, 参与联合检测中的匹配滤波, 其它值置为零, 不参与联 合检测中的匹配滤波。 这样做比方案一简单。 然而, 方案二中各个码片中的 信道估计功率最大的抽头之间的噪声仍然可能是相关的, 因此性能上可能有 一定的损失。
工业实用性 ,
本发明描述的方案, 通过选择多路采样中功率较大同时其噪声不相关的 信道估计抽头, 参与联合检测中的匹配绿和干扰消除, 从而达到提高信噪比 的目的。 本发明既可用于基站也可用于终端, 既可以用于单天线环境, 也可 以用于多天线环境。

Claims

权 利 要 求 书
1、 一种基于多倍采样的提高信噪比的基带处理方法,包括以下步骤:
(a)对接收信号的每个码片内进行 N 次采样, 得到 N 路采样数据 em s, s = \,...,N;
(b)对接收到的每一路采样信号分别做信道估计 , = 1,...,N;
(c)对每一路的信道估计 进行比较,确定功率较大同时噪声相关性较小 的信道估计 ¾^ 构成匹配滤波矩阵 F;
(d)用系统矩阵 和匹配滤波矩阵 4F, 对用户的信号做联合检测, 得到 各用户的符号 <ΐ。
2、 如权利要求 1所述的一种基于多倍采样的提高信噪比的基带处理 方法, 其特征在于, 步骤(b)中,所述的信道估计 是利用公式 得 到的, 其中 为第 s次采样的训练序列信号, M是发射的训练序列矩阵, 是第 s路采样的本小区所有用户的信道冲激响应。
3、 如权利要求 1所述的一种基于多倍采样的提高信噪比的基带处理 方法, 其特征在于, 步骤 (c)中信道估计 ¾^可以采用如下步骤得到:
(cl)对每一路的信道估计 做信道后处理,得出用户信号径的抽头位置, 并得到信道后处理之后的信道估计 » = 1,...,N^ = 1,...,N, 其中 N„是每一 路信道估计 的长度;
(c2)将信道估计 (i)按照时间顺序合成一个完整的信道估计
l,...,N-Nm
Figure imgf000011_0001
(c3)对 从大到小排序, 得到排序后的信道估计序列 Η,01α'( = ί,…… N.NW,然后从 开始依次到 ,执行以下运算:若
大于 0, 则保留排序前信道估计序列 中的该信道冲激响应抽头, 并将 h'ota! )中该抽头在左右各一码片内的其它抽头值置零;
(c4)将步骤 (c3) 处理后得到的完整的信道估计序列 再还原成 N 路采样的信道估计 ¾Ρ。
4、 如权利要求 1所述的一种基于多倍采样的提高信噪比的基带处理 方法, 其特征在于, 步骤 (C)中 信道估计^可以采用如下步骤得到:
(cl l)对每一路的信道估计 做信道后处理, 得出用户信号径的抽头位 置,
Figure imgf000012_0001
是 每一路信道估计 的长度;
(cl2)对一个码片时间内的 N路采样的信道估计的模进行比较,选定最大 值, 其它值置为零, 得到 N路采样的信道估计 ^。
5、 如权利要求 1所述的一种基于多倍采样的提高信噪比的基带处理 方法,其特征在于,步骤 (cl)和 (cl l)中,所述信道后处理之后的信道估计 是通过下述方法: 将 的每个抽头的功率与一个门限进行比较, 低于门限的 抽头认为是噪声, 其值置为零, 高于门限的抽头认为是信号, 其值保留。
6、 如权利要求 1所述的一种基于多倍采样的提高信噪比的基带处理 方法, 其特征在于, 步骤(d) 中, 所述系统矩阵 由每个用户的扩频码、 扰码和信道估计 构成。
7、 如权利要求 1所述的一种基于多倍采样的提高信噪比的基带处理 方法, 其特征在于, 步骤(d)中, 所述各用户的符号 是根据接收的数据部 分的多路采样信号 、 系统矩阵 和匹配滤波矩阵^ ^进行估计, 公式如下- ( ,
Figure imgf000012_0002
其中 为接收的数据部分的多路采样信号, = + , s = l, ... , N , σΐ 为噪声功率。
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