WO2006102792A1 - A method of channel estimate in tdd-cdma system - Google Patents
A method of channel estimate in tdd-cdma system Download PDFInfo
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- 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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- 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
- H04L25/0212—Channel estimation of impulse 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B1/00—Details 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
- H04B1/69—Spread spectrum techniques
- H04B1/707—Spread 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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Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2005800486485A CN101129007B (zh) | 2005-03-29 | 2005-03-29 | Tdd-cdma系统的信道估计方法 |
| PCT/CN2005/000404 WO2006102792A1 (en) | 2005-03-29 | 2005-03-29 | A method of channel estimate in tdd-cdma system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2005/000404 WO2006102792A1 (en) | 2005-03-29 | 2005-03-29 | A method of channel estimate in tdd-cdma system |
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| Publication Number | Publication Date |
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| WO2006102792A1 true WO2006102792A1 (en) | 2006-10-05 |
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| Application Number | Title | Priority Date | Filing Date |
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| PCT/CN2005/000404 Ceased WO2006102792A1 (en) | 2005-03-29 | 2005-03-29 | A method of channel estimate in tdd-cdma system |
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| Country | Link |
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| CN (1) | CN101129007B (zh) |
| WO (1) | WO2006102792A1 (zh) |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106789769B (zh) * | 2016-12-14 | 2020-04-21 | 北京邮电大学 | 信道预测方法及装置 |
Citations (3)
| 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 |
-
2005
- 2005-03-29 WO PCT/CN2005/000404 patent/WO2006102792A1/zh not_active Ceased
- 2005-03-29 CN CN2005800486485A patent/CN101129007B/zh not_active Expired - Fee Related
Patent Citations (3)
| 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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| Publication number | Publication date |
|---|---|
| CN101129007A (zh) | 2008-02-20 |
| CN101129007B (zh) | 2012-11-14 |
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