WO2006102792A1 - A method of channel estimate in tdd-cdma system - Google Patents

A method of channel estimate in tdd-cdma system Download PDF

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Publication number
WO2006102792A1
WO2006102792A1 PCT/CN2005/000404 CN2005000404W WO2006102792A1 WO 2006102792 A1 WO2006102792 A1 WO 2006102792A1 CN 2005000404 W CN2005000404 W CN 2005000404W WO 2006102792 A1 WO2006102792 A1 WO 2006102792A1
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user
noise
channel
time slot
tap
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French (fr)
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Junfeng Guo
Zhaohua Zeng
Hu Liu
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ZTE Corp
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    • 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
    • H04L25/0212Channel estimation of impulse response
    • 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
    • H04L25/024Channel estimation channel estimation algorithms
    • 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

Definitions

  • the present invention relates to a channel estimation method for a TDD-CDMA (Time Division Duplex-Code Division Multiple Access) system, and more particularly to a channel of a TDD-CDMA system using a training sequence for channel estimation.
  • the estimation method is applicable to all systems in the TDMA/CDMA using the training sequence for channel estimation, and is particularly applicable to the TD-SCDMA and WCDMA TDD systems in the third generation mobile communication system. Background technique
  • the following types of interference and noise exist in the TD-SCDMA system As an example, as a cellular mobile communication system, the following types of interference and noise exist in the TD-SCDMA system: 1. Since the same time slot may exist simultaneously Multiple code division channel transmission, under the condition of mobile channel, the orthogonality between code division channels is partially destroyed, and multiple access interference, ie, MAI (Multiple Access Interference), is formed between the code division channels at the receiving end; Due to the multipath propagation of the signal, inter-symbol interference is formed at the receiving end, that is, ISI (Inter-Symbol Interference); 3. Thermal noise of the receiver; 4. Interference from other cells; 5. Other interference.
  • MAI Multiple Access Interference
  • the demodulation performance of the TD-SCDMA system is generally SIR (Signal to Interference Ratio) or SNR (Signal to Noise Ratio) required by the receiver when a certain QOS (Quality of Service) is satisfied. ) indicates that, since in cellular CDMA (Code Division Multiple Access) systems, interference has statistical characteristics similar to white noise, interference and noise are generally not strictly distinguished.
  • the demodulation algorithm is required to have good interference suppression capability. The stronger the suppression of interference, the better the system performance, and the The utilization of the spectrum is more efficient. Therefore, interference suppression technology has become a key factor in improving the performance of TD-SCDMA.
  • the code design, frame structure, and chip rate of the TD-SCDMA system provide feasibility for interference suppression techniques.
  • Joint detection technology is one of the key technologies of TD-SCDMA.
  • the joint detection technology in TD-SCDMA system can effectively suppress MAI and ISI.
  • the joint detection technology is based on channel estimation, and the effect of channel estimation is combined. Detection performance has a very important impact, and good channel estimation techniques become a necessary condition for determining joint detection.
  • the wireless mobile environment is modeled as a finite-length impulse response model, and the task of channel estimation is to estimate the amplitude and phase of each time-delay tap.
  • the multipath propagation of signals in a wireless mobile environment requires very high channel estimation. How to obtain accurate channel estimation under complex channel propagation conditions becomes the key to TD-SCDMA technology.
  • the existing estimation methods of TD-SCDMA systems mainly include the following:
  • the training sequence of all users of the same cell is generated by cyclic shifting through a basic training sequence midamble of period P, and the corresponding channel impulse estimation is performed.
  • the method generally uses the Steiner estimation method.
  • the channel estimation method using this method is generally called Steiner estimator, and the estimation principle is to calculate the channel impulse response of all users at one time by solving the linear equations by using the least squares method. Since the training sequence of the TD-SCDMA system has a cyclic shift characteristic, a correlator can be used in calculating the channel impulse response of each user, and an efficient and fast implementation method such as FFT (Fas t Fourier Transfer, etc.) can be used in the specific implementation.
  • FFT Fast t Fourier Transfer
  • the performance of the Steiner estimator is affected by the additive noise at the receiving end, and the resulting channel impulse response contains a noise component compared to the ideal channel impulse response. That is, the reason for the channel estimation error is generated; at the same time, the noise power is expanded, resulting in a certain loss of the signal-to-noise ratio at the output relative to the input terminal, so that the channel impulse response estimation performance is degraded.
  • the Ste iner estimator calculates the user channel impulse response estimate for a time slot. Due to the limitation of transmission overhead, the training sequence in one time slot cannot be too long, and its performance is affected by the additive noise of the receiving end, which leads to loss of channel estimation accuracy. If no processing is used directly, the estimation result will inevitably lead to system performance. decline.
  • This method filters out the channel impulse response taps obtained by the Steiner estimator based on the Ste iner estimator without a signal and is completely a noise component.
  • Each tap of the channel impulse response obtained by the Steiner estimator corresponds to each multipath component when the signal propagates through the mobile radio channel and arrives at the receiver. If the tap contains no signal and only noise, the tap should be filtered out. Do not participate in the multipath combination, otherwise the noise is combined, and the detection of the useful signal will cause interference.
  • this method still does not overcome the shortcomings of the prior method 1 using only one slot of instantaneous estimation, so there are two disadvantages: First, the noise in the tap containing the signal in the channel impulse response is not suppressed, superimposed on The noise on the signal causes the signal detection performance to deteriorate. Second, the noise tap filtering method is too simple, it is ineffective for instantaneous strong noise, and the strong noise is not filtered out. The sound is misjudged as a signal, which interferes with signal detection and causes performance degradation.
  • the method proposed by the method uses a zero correlation window code to replace the midamble code specified by the current TD-SCDMA standard as a training sequence, and uses a code group of different zero correlation length according to the number of users in the system, and can perform pilot in the user time slot.
  • a small number of shift operations if using a smart antenna, can also be configured according to the user's position and the angle of arrival of the signal, so that the configuration of the neighboring users of the arrival angle has a code sequence with a wider zero correlation window, which reduces the intrinsic channel estimation of the system. Interference.
  • the method adopts a zero-correlation window code different from the current TD-SCDMA standard as a training sequence, the influence of the cross-correlation property existing between the user training sequences on the channel estimation is reduced, thereby improving the channel estimation performance.
  • this method has two disadvantages. First, it requires a complex training sequence allocation algorithm and multiple parallel correlators, which is costly and cannot be implemented using efficient and fast algorithms. Second, this technical solution The existing TD-SCDMA standard is not compatible. Summary of the invention
  • the object of the present invention is to provide a channel estimation method for a TDD-CDMA system, which can reduce the interference of noise on a signal in a TDD-CDMA system, can effectively suppress the interference of instantaneous strong noise, and can realize TDD- efficiently, quickly and at low cost.
  • CDMA high-performance channel estimator and enhances the suppression of frequency offset capability of TDD-CDMA systems, and is compatible with current standards, without the need to modify existing standards.
  • the present invention provides a channel estimation method for a TDD-SCDMA system, which is characterized by comprising the following steps:
  • Step 1 Using the Ste iner estimator to perform simultaneous estimation of the channel impulse response of one time slot of each user, and obtain the original time domain discrete channel impulse response H, H], k - ⁇ , 2, ⁇ of all users.
  • K "is the time slot number, is the user number, is the user The number is the channel impulse response length;
  • f, k ⁇ , 2,...,K , all taps get t nk ⁇ ,. nt W .
  • Step 3. Perform a variable length multi-slot sliding average for each tap of the slot n of each user k, and obtain an average value.
  • Step 4 Filter out the noise tap processing for each user's time slot n, get / step 5, output a user k in the time slot letter n channel estimation value h'". Step 6. Repeat steps 1 - 5 until the channel estimates for all users are obtained.
  • step 3 J is the number of time slots for weighted moving average
  • J is between 1 and 16. ⁇ ⁇ . When it is stationary or walking communication, the value is 0.2 ⁇ 0.5; when it is high-speed mobile communication, the value is 0.5 0.9.
  • the step 4 is specifically:
  • Step 4.1 Calculate the noise threshold ⁇ ; Step 4.2: Filter the noise tap processing for each user's time slot. If the channel estimation of one tap is squared and lower than the noise threshold, the tap is set to 0, otherwise it is reserved.
  • the tap n i A noise is
  • the Boltzmann constant is the absolute temperature
  • S is the signal bandwidth
  • the receiver noise figure is the sum of the parameters
  • the present invention has the following advantages: 1.
  • the interference of noise on the signal is reduced, and the interference of instantaneous strong noise can be effectively suppressed.
  • a high-performance channel estimator can be implemented using an efficient, fast, and low-cost method.
  • FIG. 1 is a flow chart of a method for channel estimation of a TDD-SCDMA system according to the present invention.
  • Fig. 2 is a schematic diagram showing the process of calculating the decision metric of each tap of the original channel impulse response of the user in the channel estimation method of the TDD-SCDMA system of the present invention.
  • FIG. 3 is a schematic diagram of a user of the channel estimation method of the TDD-SCDMA system of the present invention * performing variable length multi-slot averaging processing on the original instantaneous channel estimation of the time slot.
  • FIG. 4 is a flow chart of calculating a channel impulse response of a user in a time slot according to a channel estimation method of a TDD-SCDMA system according to the present invention.
  • the inventive idea of the present invention is to provide a novel TDD-CDMA channel estimation method for extracting training sequence symbols from received digital spread spectrum signals from a plurality of mobile stations or base stations superimposed with a plurality of user signals and noise and interference. Using the training sequence symbols of each user generated locally by the base station receiver or the mobile station receiver, estimating the channel impulse response of each user in one time slot, and then performing channel impulse response on multiple time slots of the same user. Processing to reduce the effects of noise and improve the accuracy of channel impulse response estimation.
  • Step 1 Using the S tei ne r estimator to perform simultaneous estimation of the channel impulse response of one time slot of each user, and obtain the original time domain discrete channel impulse response of one user:
  • Equation (1) "is the slot number, is the user number, is the number of users, is the channel impulse response length, depends on the multipath delay spread of the mobile radio channel, such as TD-SCDMA system, the typical value of W The range is 4 ⁇ 32 chips.
  • Step 2 Calculate the individual tap decision metrics for each user slot:
  • FIG. 2 it is a schematic diagram of a method for calculating a decision metric of each channel of a user of a channel estimation method of the present invention in a channel estimation method of the present invention.
  • the method includes: modulo and square operator 202-1 ⁇ 202 - W; multipliers 203-1 ⁇ 203-W; multipliers 204-1 ⁇ 204-W; adders 205-1 205-W; delays 206-1 ⁇ 206- W, delay
  • the output is delayed by one time slot than the input.
  • Input 201-1 ⁇ 201- W ⁇ ".”, ⁇ "", ⁇ , ⁇ is the original channel of the user* in the time slot obtained by the Steiner estimator Impulse response. This figure contains the same process.
  • the first process is used as an example to describe its process.
  • the other processes are identical.
  • the modulo and square operator 202-1 modulates the first tap of the original channel estimate of the time slot And the square operation is performed to obtain l wl 2 , the multiplier 203-1 multiplies a coefficient to obtain ⁇ ) .*, ⁇
  • Step 3 Perform a variable length multi-slot sliding average for each tap of each user * time slot ⁇ : (5)
  • the moving average length is the number of time slots in which the weighted moving average is performed, which is a coronation.
  • the sliding average length J contains two possible cases: single-slot service and multi-slot service.
  • is equal to the number of moving average subframes.
  • J is related to the number of moving average subframes and the number of slots allocated by the multi-slot service in one subframe.
  • the value of J depends on the speed of the channel change. For users with low speed movement, such as static or walking communication, a large value can obtain good noise suppression capability. For high-speed mobile users, such as communication in a moving vehicle.
  • the smaller value of J can adapt to the rapid change of the channel while obtaining satisfactory noise suppression capability.
  • The range of values can be unlimited, but it is usually 1 to 16.
  • the value of the channel is also related to the fast change of the channel. For example, one possible value is as follows:
  • O ⁇ for users moving at low speed, such as stationary or walking communication, P The value is 0. 5 ⁇ 0. 9.
  • the value is 0. 5 ⁇ 0. 9.
  • variable length multi-slot averaging processing of the original instantaneous channel estimation of the user in the time slot of the present invention.
  • the variable length multi-slot averaging processing is performed on the original instantaneous channel estimation of the user in the time slot, including : Multipliers 302-0 ⁇ 302-J; J delays 303-1 ⁇ 303-J, the output of the delay is one time slot than the input delay; 1 adder 304.
  • Step 4 Perform noise filtering processing on the time slot n of each user.
  • is the noise filtering threshold. According to the actual working environment settings, for example, one can be used as follows:
  • Equation (11) it is the Boltzmann constant.
  • is the absolute temperature, is the signal bandwidth, is the receiver noise figure.
  • the unit is Coke/Open (J/K), : The unit of ⁇ is open ( ⁇ ), the unit is Hertz (Hz), and the unit is decibel (dB).
  • Step 5 Output the user in the time slot "channel estimation value h '".* :
  • FIG. 4 it is a flow chart of calculating a channel impulse response of a user in a time slot according to the present invention.
  • “Channel Estimation Step Step 6 the above steps are operations for one user, and the channel estimates of all users are obtained repeatedly.
  • the invention is an efficient, fast and low-cost joint channel estimation method suitable for the TDD-SCDMA standard.
  • a multi-slot processing combined with non-coherent accumulation is used to overcome the problem.
  • the defects of the prior art reduce the interference of noise on the signal, can effectively suppress the interference of the instantaneous strong noise, and also have good anti-frequency offset performance.
  • the channel estimation method of the present invention adds a small amount of computation to the S teiner estimator, enabling a high performance channel estimator to be implemented using an efficient, fast, and low cost method.
  • the method has the following advantages: First, the interference of the noise on the signal is reduced and the interference of the instantaneous strong noise can be effectively suppressed; Second, the frequency offset performance is good; Third, the high frequency can be used. An efficient, fast, and low-cost way to implement a high-performance channel estimator. Fourth, compatibility with current standards does not require modifications to existing standards.
  • the present invention is also applicable to all systems in TDMA/CDMA using training sequences for channel estimation, especially for TD-SCDMA and WCDMA TDD systems in third generation mobile communication systems, although the technical solution of the present invention is mainly directed to TDD-SCDMA.
  • the wireless communication system but also applies to CDMA, TDMA systems using similar transmission structures, both for base station receivers and mobile station receivers. In combination with the relevant measurement process of the receiver, this aspect can adaptively adjust the parameters according to the working environment.

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Description

TDD-CDMA系统的信道估计方法 技术领域
本发明涉及一种 TDD-CDMA ( Time Division Duplex-Code Division Multiple Access, 时分双工-码分多址) 系统的信道估计方法, 尤其涉及一 种采用训练序列进行信道估计的 TDD- CDMA 系统的信道估计方法, 适用于 TDMA/CDMA中采用训练序列进行信道估计的所有系统,尤其适用第三代移动通 信系统中的 TD-SCDMA和 WCDMA TDD系统。 背景技术
以 TD-SCDMA ( Time Division ― Synchronous Code Division Multiple Access) 系统为例, 作为一种蜂窝移动通信系统, TD-SCDMA系统中存在以下 几种干扰和噪声: 1、 由于同一个时隙中可能同时存在多个码分信道传输, 在 移动信道条件下,码分信道之间的正交性被部分破坏, 在接收端码分信道之间 会形成多址干扰, 即 MAI (Multiple Access Interference); 2、 由于信号的 多径传播,在接收端会形成符号间干扰,即 ISI( Inter-Symbol Interference); 3、 接收机的热噪声; 4、 来自其它小区的千扰; 5、 其它干扰。
TD-SCDMA系统的解调性能一般由满足一定的 QOS (Quality of Service, 服务质量) 时接收机所需要的 SIR (Signal to Interference Ratio, 信干比) 或 SNR( Signal to Noise Ratio,信噪比)表示., 由于蜂窝 CDMA ( Code Division Multiple Access, 码分多址) 系统中, 干扰具有类似白噪声的统计特性, 因 此一般不严格区分干扰和噪声。 为了获得良好的解调性能, 就要求解调算法 具有很好的干扰抑制能力。 对干扰的抑制能力越强, 系统性能越好, 所能提 供的频谱的利用效率就越高。 因此, 干扰抑制技术成为提高 TD- SCDMA性能的 关键因素。
TD-SCDMA系统的码设计、 帧结构、 码片速率等为干扰抑制技术提供了可 行性。 联合检测技术是 TD- SCDMA的关键技术之一, 在 TD- SCDMA系统中应用联 合检测技术, 可以有效抑制 MAI和 ISI , 联合检测技术是建立在信道估计的基 础上的, 信道估计的效果对联合检测性能有着极为重要的影响, 良好的信道 估计技术成为决定联合检测的必要条件。 通常, 无线移动环境被建模为有限 长度沖激响应模型, 信道估计的任务就是估计出各个时延抽头的幅度和相位。 无线移动环境下信号的多径传播对信道估计的要求非常高, 如何在复杂的信 道传播条件下获得准确的信道估计成为 TD-SCDMA技术的关键。
现有的 TD-SCDMA系统的估计方法主要有以下几种:
1、 斯坦纳 (Steiner )估计方法
在现有的 TD-SCDMA 系统中, 同一个小区的所有用户的训练序列都是通过 一个基本的、 周期为 P的训练序列 midamble, 通过循环移位的方式产生的, 而 对应的信道冲激估计方法一般都是运用 Steiner估计方法。 采用这种方法的信 道估计方法一般被称为 Steiner 估计器, 其估计原理是采用最小二乘法通过 解线性方程组一次计算所有用户的信道冲激响应。 由于 TD-SCDMA系统的训练 序列具有循环移位特性, 因此在计算各个用户的信道沖激响应时可以使用一 个相关器, 具体实现时可以使用高效、 快速的实现方法如 FFT ( Fas t Fourier Transfer,快速傅里叶变换)和 IFFT ( Inverse Fas t Four ier Transfer,快速 傅里叶逆变换), 将复杂的线性卷积转化为简单的循环卷积, 可以降低信道估 计的算法复杂度和成本。 但是, Steiner 估计器的性能受接收端加性噪声的 影响, 其得到的信道沖激响应和理想信道冲激响应相比, 包含噪声分量, 这 也就是信道估计误差产生的原因; 同时会扩大噪声功率, 导致输出端信噪比 相对输入端有一定量的损失, 使得信道沖激响应估计性能下降。 Ste iner 估 计器计算的是一个时隙的用户信道沖激响应估计值。 受传输开销的限制, 一 个时隙内的训练序列不能太长, 其性能受接收端加性噪声的影响而导致信道 估计精度损失, 如果不做任何处理直接使用其估计结果必然会导致系统性能 的下降。
2、 过门限判决的降噪的处理方法
参见文献《Impact of Channel Est imat ion on the 3GPP- TD - CDMA》, Ol iver Prator等著, GLOBECOM 'Ol IEEE: 3365-3369 vol. 6和 《TD-SCDMA 系统中 低代价信道估计方法的改进》康绍莉, 袭正定等著, 《 通信学报》, 2002 , 23 (10): 125-130。 其基本思想是先用 Steiner 估计方法估计出原始信道沖 激响应, 然后用一个门限, 滤除估计得到的信道冲激响应抽头中没有信号而 完全是噪声成分的抽头。 用这种方法只增加了很小的计算量, 能使信道估计 性能获得一定的改善。
这种方法在 Ste iner 估计器基础上通过设置的门限滤除 Steiner估计器 得到的信道沖激响应抽头中没有信号而完全是噪声成分的抽头。 Steiner估计 器得到的信道沖激响应的各个抽头对应的是信号通过移动无线信道传播后到 达接收机时的各个多径成份, 如果抽头中不含信号而只有噪声, 则这个抽头 就应该被滤除而不参加多径的合并, 否则被合并的是噪声, 对有用信号的检 测将产生干扰。 但是这种方法仍然没有克服现有方法 1只使用了一个时隙的瞬 时估计的缺陷, 因此存在两个缺点: 第一, 信道冲激响应中含有信号的抽头 中的噪声没有得到抑制, 叠加在信号上的噪声引起信号检测性能的恶化; 第 二, 噪声抽头的滤除方法过于简单, 对瞬时的强噪声无效, 未被滤除的强噪 声会被误判为信号, 从而干扰信号检测, 引起性能恶化。
3、 零相关窗码法
本方法提出的方法采用零相关窗码取代现行 TD- SCDMA标准规定的 midamble码作为训练序列, 根据系统中用户的数目多少使用不同零相关长度 的码组, 可以对用户时隙中的导频进行少量的移位操作, 若使用智能天线, 还可以根据用户的位置, 信号的到达角配置, 使到达角相邻用户的配置互相 关具有较宽零相关窗的码序列, 减少系统内在的信道估计的干扰。
由于本方法采用了不同于现行 TD-SCDMA标准的零相关窗码作为训练序 列, 降低用户训练序列之间存在的互相关特性对信道估计造成的影响, 从而 达到提高信道估计性能的目的。 但是这种方法有两个缺点'. 第一, 需要复杂 的训练序列分配算法、 多个并行的相关器, 成本很高, 并且无法使用高效、 快速的算法实现; 第二, 这种技术方案与现有的 TD- SCDMA标准不兼容。 发明内容
本发明的目的是提供一种 TDD- CDMA系统的信道估计方法, 可以降低 TDD - CDMA系统中噪声对信号的干扰, 能够有效抑制瞬时强噪声的干扰, 能够高 效、快速和低成本的实现 TDD-CDMA高性能的信道估计器, 并且增强 TDD- CDMA 系统的抑制频偏能力, 而且与现行标准兼容, 无需对现有标准修改。
为实现上述目的, 本发明提供了一种 TDD-SCDMA 系统的信道估计方法, 其特征在于包括以下步骤:
步骤 1、利用 Ste iner估计器完成各个用户的一个时隙的信道沖激响应的 同 时估计, 得到所有用 户 的原始的 时域离散信道冲激响应 H ,H ] , k - \, 2,〜, K , "是时隙编号, 是用户编号, 是用户 数, 是信道沖激响应长度;
步骤 2、 对每一个用户计算时隙 n 的各个抽头判决量度 = - +(1-«)| f, k=\,2,...,K , 所有抽头得到 tnk^,. nt W . 步骤 3、对每一个用户 k的时隙 n的各个抽头进行变长度多时隙滑动平均, 得到平均值
Figure imgf000007_0001
k = l,2,-,K. 步骤 4、 对每一个用户的时隙 n进行滤除噪声抽头处理, 得到/ 步骤 5、 输出一个用户 k在时隙信 n道估计值 h'". ; 步骤 6、 重复步骤 1 -5, 直到得到所有用户的信道估计值。
所述步骤 3中
Figure imgf000007_0002
, J是进行加权滑动平均的时隙个数,
J的取值在 1 - 16之间,。〈 ^。当静止或者步行通信时, 取值为 0.2~ 0.5; 高速移动通信时, 取值为 0.5 0.9。
所述步骤 4具体为:
步骤 4.1、 计算噪声门限 Γ; 步骤 4.2、对每一用户的时隙进行滤除噪声抽头处理,如果一个抽头的信 道估计取模求平方后低于噪声门限则该抽头被置为 0, 否则保留该抽头 ni A噪 功 是
Figure imgf000007_0003
波尔兹曼常数, 是绝对温度, S是信号带宽, 是接收机噪声系数。
因此, 本发明具有以下优点: 1、 降 ^了噪声对信号的干扰, 能够有效抑制瞬时强噪声的干扰。
2、 能够使用高效、 快速、 低成本的方法实现高性能的信道估计器。
3、 抑制频偏能力强。
4、 兼容现行标准, 无需对现有标准修改。
下面结合附图和实施例, 对本发明的技术方案做进一步的详细描述。 附图说明
图 1为本发明 TDD-SCDMA系统的信道估计方法的方法流程图。
图 2为本发明 TDD-SCDMA系统的信道估计方法的用户 在时隙 "的原始信 道沖激响应各个抽头计算判决度量处理示意图。
图 3为本发明 TDD- SCDMA系统的信道估计方法的用户 *在时隙 "的原始瞬 时信道估计进行变长度多时隙平均处理的示意图。
图 4为本发明 TDD-SCDMA系统的信道估计方法的计算用户 在时隙 "的信 道沖激响应流程图。 具体实施方式
本发明的发明思想是提供一种新型的 TDD-CDMA信道估计方法,从接收的 来自多个移动台或者基站的叠加有多个用户信号和噪声以及干扰的数字扩频 信号中提取出训练序列符号, 利用基站接收机或者移动台接收机本地产生的 各个用户的训练序列符号, 估计出每个用户在一个时隙的信道冲激响应, 然 后对同一个用户多个时隙的信道沖激响应进行处理, 以降低噪声的影响, 提 高信道沖激响应估计的精度。
如图 1所示, 为本发明的方法流程图, 本发明所述信道沖激响应估计的 方法如下: 步骤 1、使用 S t e i ne r估计器完成各个用户的一个时隙的信道冲激响应的 同时估计, 得到 Κ个用户的原始的时域离散信道冲激响应:
Figure imgf000009_0001
式(1)中, "是时隙编号, 是用户编号, 是用户数, 是信道沖激响 应长度, 取决于移动无线信道的多径时延扩展, 例如 TD- SCDMA系统, W的 典型取值范围是 4 ~ 32码片。
步骤 2、 对每一个用户计算时隙"的各个抽头判决度量:
t„,* 2" ",^] , k = l,2,...,K (2) 式 (2)中,
,,=<^"— +G— i=\,2,...,W ? k=\,2,...,K (3)
(4)
Figure imgf000009_0002
式(3)中, "是遗忘因子, 0<"<1, —般取值为 0.1 ~ 0.95。 由于本步骤 采用了非相干累加的处理方法, 能够提高信道估计抗频偏的能力。
参见图 2所示, 为本发明系统的信道估计方法的用户 *在时隙 "的原始信 道冲激响应各个抽头计算判决度量处理示意图。 包括: 个取模并求平方运 算器 202-1 ~ 202- W; 个乘法器 203- 1 ~ 203- W; 个乘法器 204-1 ~ 204-W; 个加法器 205- 1 205-W; 个延时器 206-1 ~ 206- W, 延时器的输出是比输 入延时一个时隙。 输入 201-1 ~ 201- W Α".",Α"",··Α,^是由 Steiner估计器得 到的用户 *的在时隙 "的原始信道沖激响应。 本图中含有 个相同的处理过 程, 以第一个处理过程为例描述其处理过程, 其它的过程与之完全相同。 取 模并求平方运算器 202-1对时隙 "的原始信道估计的第一个抽头 进行取模 并求平方运算得到 l wl2 , 乘法器 203-1 对 乘一个系数 得到 α) .*,ι|,另一方面,延时器 206-1输出的前一个时隙的 乘法器 204-1 对 w乘一个系数"得到 , 加法器 205-1将乘法器 203-1的输出与乘法 器 204-1 的输出相加得到用户 *的在时隙"的第一个抽头判决度量
1=α^·' + (1"α) ·*·1Ι ,最后,上述 个相同的处理过程输出用户 在时隙 "的 信道沖激响应的 个抽头判决度量 =[ί",",^.2,·· ^]
步骤 3、对每一个用户 *的时隙 η的各个抽头进行变长度多时隙滑动平均: (5)
Figure imgf000010_0001
hn-j,k,i = 0^ "~j≤0 , i = \,2,...,W ? k = \,2,...,K (6)
L;*
Figure imgf000010_0002
, k = \,2,...,K (7) 式(5)中, 滑动平均长度 是进行加权滑动平均的时隙个数, 是加杈系 教。 滑动平均长度 J包含了两种可能的情况: 单时隙业务和多时隙业务。 对于 单时隙业务, ■ 就等于参与滑动平均子帧个数, 对于多时隙业务, J与滑动平 均子帧个数和多时隙业务在一个子帧内所分配的时隙数有关。 J的取值根据信 道变化的快慢而定, 对于低速移动的用户, 例如静止或者步行时通信, 取值 较大可以获得良好的抑制噪声能力; 对于高速移动的用户, 例如行驶的车辆 中的通信, J取值较小可以在获得满意的抑制噪声能力的同时适应信道的快速 变化。 · 的取值范围可以不受限制, 但是通常情况下其取值为 1~ 16。 的取 值也与信道变化的快^曼有关, 例如一种可能的取值如下:
Figure imgf000010_0003
式(8)中, O ^, 对于低速移动的用户, 例如静止或者步行时通信, P 取值为 0. 2 ~ 0. 5; 对于高速移动的用户, 例如高速行 ¾^车辆中的通信, 取 值为 0. 5 ~ 0. 9。
参见图 3所示, 为本发明用户 *在时隙 "的原始瞬时信道估计进行变长度 多时隙平均处理的示意图。 对用户 在时隙 "的原始瞬时信道估计进行变长度 多时隙平均处理, 包括: 个乘法器 302-0 ~ 302-J; J个延时器 303-1 ~ 303-J , 延时器的输出是比输入延时一个时隙; 1 个加法器 304。 输入 101 = [^ ,^2,···^是由 ste iner估计器得到的各个用户 的在一个时隙 "的 原始信道冲激响应, 对时隙 "的原始信道估计 h".*的所有抽头 ^^, "",… , 乘法器 302-0 ~ 302- J把每一个抽头 ζ· ( = 1'2'-'^ )的信道估计 .'以及 个延 时器 303-1 ~ 303-J 输出的抽头 的前 J个时隙的原始信道估计 A-W,"A-w与相应的加权系数 相乘, 得到 Cj - j , 7' = 1,2,"',J, 然后 加法器 304把
Figure imgf000011_0001
, i = U 2,..., W ^ 最终得用户 *在时隙 "的多时隙平均后的信道估计 305 h„,k
Figure imgf000011_0002
k = l, 2, ..., K。
步骤 4、 对每一个用户的时隙 n进行滤除噪声抽头处理
Figure imgf000011_0003
式(9)中, : Γ是噪声滤除门限, 根据实际的工作环境设置, 例如一种可 的取值方法如下:
T = \0logl0(Pnoise) + offset 式(10)中, "。-·是底噪功率, 通过测量接收机在不接收信号时测量得到, 也可以根据下述公式(11)计算得到。 Ρ——经确定一般不需要调整。 ^是相 对于底噪功率的偏移量, 其取值范围不受限制, 通常可以通过计算机仿真或 者实验得到最优值。
Pnoise = KTB + NF (1 1)
式(11)中, 是波尔兹曼常数,
Figure imgf000012_0001
, Γ是绝对温度, 是信号 带宽, 是接收机噪声系数。 的单位是焦 /开 ( J/K ), : Γ的单位是开(Κ ), 的单位是赫兹 (Hz ), 的单位是分贝 (dB )。
步骤 5、 输出用户 在时隙 "信道估计值 h'".* :
h'",t =[ w'A,* 〗 (12)
参见图 4所示, 为本发明计算用户 在时隙"的信道冲激响应流程图。 根 据式(8)计算噪声过滤门限 , 从抽头 = 1起, 判断用户 在时隙 "的信道沖激 响应的各抽头! '是否满足 1QlDgl。(U> :r, 如果判断成立, 则保留该抽头的信道 估计, 即 = , 否则将抽头置为 0, 一个抽头处理完毕后抽头计数器 递 增, 直到所有 个抽头处理完毕, 最后输出用户 在时隙 "信道估计值 步骤 6、 以上步骤是对一个用户的操作,重复 次得到所有用户的信道估 计。
本发明是一种适用 TDD-SCDMA标准的高效、 快速、 低成本的联合信道估 计方法, 在 Steiner估计器基础上, 釆用了一种多时隙处理与非相干累加相 结合的处理方法, 克服了现有技术的缺陷, 降低了噪声对信号的干扰, 能够 有效抑制瞬时强噪声的干扰, 同时还具有良好的抗频偏性能。 本发明的信道 估计方法在 S teiner估计器基础上增加了很小的计算量, 能够使用高效、 快 速、 低成本的方法实现高性能的信道估计器。
因此本方法有如下优点: 第一, 降低了噪声对信号的干扰 而且能够有效 抑制瞬时强噪声的干扰; 第二, 具有良好的抗频偏性能; 第三, 能够使用高 效、 快速、 低成本的方法实现高性能的信道估计器。 第四, 兼容现行标准, 无需对现有标准修改。
本发明也适用于 TDMA/CDMA 中采用训练序列进行信道估计的所有系统, 尤其是适用于第三代移动通信系统中的 TD-SCDMA和 WCDMA TDD系统, 虽然本 发明的技术方案主要针对 TDD-SCDMA 的无线通信系统, 但是也同样适用于采 用类似传输结构的 CDMA、 TDMA系统, 既适用于基站接收机, 也适用于移动台 接收机。 结合接收机的相关测量过程, 本方面可以自适应地才艮据工作环境动 态调整参数。
最后所应说明的是, 以上实施例仅用以说明本发明的技术方案而非限制, 尽管参照较佳实施例对本发明进行了详细说明, 本领域的普通技术人员应当 理解, 可以对本发明的技术方案进行修改或者等同替换, 而不脱离本发明技 术方案的精神和范围, 其均应涵盖在本发明的权利要求范围当中。

Claims

权利要求
1、 一种 TDD-SCDMA系统的信道估计方法, 其特征在于包括以下步骤: 步骤 1、利用 Steiner估计器完成各个用户的一个时隙的信道冲激响应的 同 时估计, 得到所有用 户 的原始的时域离散信道冲激响应 ,k
Figure imgf000014_0001
l,2,〜,K , "是时隙编号, A:是用户编号, 是用户 数, 是信道沖激响应长度;
步骤 2、 对每一个用户计算时隙 n 的各个抽头判决量度 tn, i
Figure imgf000014_0002
, k = \,2,...,K, 所有抽头得到 tn,k *,2,...υ ; 步骤 3、对每一个用户 k的时隙 η的各个抽头进行变长度多时隙滑动平均, 得到平均值 Ι ,, =^ Α- w , = 1,2,..., , 所有抽头得到!^^ , ^,… ^],
7=0 ' , k = \,2,...,K\
步骤 4、 对每一个用户的时隙 n进行滤除噪声抽头处理, 得到 4; 步骤 5、 输出一个用户 k在时隙信 n道估计值 h'„,t;
步骤 6、 重复步骤 1 -5, 直到得到所有用户的信道估计值。
2、 根据权利要求 1所述的 TDD-SCDMA系统的信道估计方法,其特征在于 所述步骤 3中 C/ = ,...,J , J是进行加权滑动平均的时隙个数,
Figure imgf000014_0003
的取值在 1 - 16之间, 0<^<1o
3、 根据权利要求 2所述的 TDD-SCDMA系统的信道估计方法,其特征在于: 当静止或者步行通信时, 取值为 0.2 ~ 0.5;高速移动通信时, 取值为 0.5 - 0.9。
4、 根据权利要求 1所述的 TDD-SCDMA系统的信道估计方法,其特征在于 所述步骤 4具体为:
步骤 4. 1、 计算噪声门限 Γ ;
步骤 4. 2、对每一用户的时隙进行滤除噪声抽头处理,如果一个抽头的信 道估计取模求平方后低于噪声门限则该抽头被置为 0, 否则保留该抽头
Figure imgf000015_0001
5、 根据权利要求 4所述的 TDD-SCDMA系统的信道估计方法,其特征在于: 所述噪声门限?^^^^ ^^ + ^^", P„。,.re是底噪功率, o 是相对于底噪功率 的偏移量。
6、 根据权利要求 5所述的 TD-SCDMA系统的信道估计方法,其特征在于: 所迷的 噪功率 P„。ise = KTB + NF, 是波尔兹曼常数, : Γ是绝对温度, 是信号 带宽, NF是接收机噪声系数。
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WO2000064113A1 (de) * 1999-04-16 2000-10-26 Siemens Aktiengesellschaft Verfahren zur kanalschätzung in einem tdma-mobilfunksystem
WO2003044975A1 (en) * 2001-11-21 2003-05-30 D.S.P.C. Technologies Ltd. Low complexity multiuser detector
US20040203812A1 (en) * 2003-02-18 2004-10-14 Malladi Durga Prasad Communication receiver with an adaptive equalizer that uses channel estimation

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Publication number Priority date Publication date Assignee Title
WO2000064113A1 (de) * 1999-04-16 2000-10-26 Siemens Aktiengesellschaft Verfahren zur kanalschätzung in einem tdma-mobilfunksystem
WO2003044975A1 (en) * 2001-11-21 2003-05-30 D.S.P.C. Technologies Ltd. Low complexity multiuser detector
US20040203812A1 (en) * 2003-02-18 2004-10-14 Malladi Durga Prasad Communication receiver with an adaptive equalizer that uses channel estimation

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