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WO2003032545A1 - Procede de suppression d'interferences parallele a double ponderation - Google Patents

Procede de suppression d'interferences parallele a double ponderation Download PDF

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Publication number
WO2003032545A1
WO2003032545A1 PCT/CN2002/000711 CN0200711W WO03032545A1 WO 2003032545 A1 WO2003032545 A1 WO 2003032545A1 CN 0200711 W CN0200711 W CN 0200711W WO 03032545 A1 WO03032545 A1 WO 03032545A1
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WO
WIPO (PCT)
Prior art keywords
user
interference cancellation
decision
signal
weighted
Prior art date
Application number
PCT/CN2002/000711
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English (en)
French (fr)
Inventor
Limei Wei
Guolin Wang
Yu Jin
Original Assignee
Huawei Technologies Co., Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Huawei Technologies Co., Ltd filed Critical Huawei Technologies Co., Ltd
Priority to US10/492,096 priority Critical patent/US7321581B2/en
Priority to DE60218329T priority patent/DE60218329T2/de
Priority to EP02772004A priority patent/EP1443694B1/en
Publication of WO2003032545A1 publication Critical patent/WO2003032545A1/zh

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Classifications

    • 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
    • H04B1/7107Subtractive interference cancellation
    • H04B1/71075Parallel interference cancellation
    • 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
    • H04B1/7107Subtractive interference cancellation
    • H04B2001/71077Partial interference cancellation

Definitions

  • Double-layer weighted parallel interference cancellation method Double-layer weighted parallel interference cancellation method
  • the present invention relates to a multi-user detection (MUD) technology in a CDMA mobile communication system, and more particularly, to a double-layer weighted parallel interference cancellation method for a CDMA system.
  • MOD multi-user detection
  • the CDMA mobile communication system has become the development direction of the third generation mobile communication because of its high capacity, high service quality, and good confidentiality.
  • the multi-user detection technology is an enhanced technology that overcomes the multiple access interference (Multi Access Interference) limitation on the capacity of a CDMA system, thereby improving the capacity and performance of the CDMA system.
  • Multiple access interference Multi Access Interference
  • Multi-user detection technology uses the information of multiple users to jointly detect signals from multiple users, thereby minimizing the impact of multiple-access interference on the performance of the receiver and increasing the capacity of the system.
  • multi-user detection includes a maximum likelihood sequence detector as an optimal detector, a linear multi-user detector as a sub-optimal detector, and an interference cancellation multi-user detector.
  • the interference cancellation multi-user detection is to treat the signal of the desired user as a useful signal and the signal of other users as the interference signal; first eliminate the interference of other users from the received signal to obtain the signal of the desired user, and then Signals are detected to improve system performance.
  • Interference cancellation multi-user detection is divided into serial interference cancellation (Serial Interference Cancellation) and parallel interference cancellation (Parallel Interference Cancellation).
  • Serial interference cancellation is to sort user signals in descending order of power. This method uses serial de-interference. The performance of this method is better than single-user detection, but the delay is large, and power sequencing is required. Signal estimation is sensitive.
  • Parallel interference cancellation is to cancel the signal interference of all other users from the received signals in parallel for each user. This method has the advantages of small delay and small computational complexity. Interference cancellation method and weighted parallel interference cancellation method based on Bayes criterion.
  • the traditional parallel interference cancellation method has a large improvement in performance over a single-user detector at high signal-to-noise ratios, but at a low signal-to-noise ratio, the performance of this method decreases compared to the single-user detector.
  • the partial parallel interference cancellation method is to set a weight for each level of interference cancellation and weight the multiple-access interference received by the desired user.
  • multiple-access interference is only partially eliminated.
  • the traditional parallel interference cancellation method on the Gaussian channel completely eliminates the multiple-access interference received by the desired user from the received signal.
  • the estimation of the desired user signal is a biased estimate; part of the parallel interference cancellation method only partially eliminates multiple access. Interference can correct the deviation of the expected user signal estimation and make the decision result more reliable.
  • the performance of the partially parallel interference cancellation method is significantly better than the traditional parallel interference cancellation method.
  • a Bayesian criterion-based weighted parallel interference cancellation method is disclosed in US Patent No. 5,418,814. Although it is also a weighting method, the weighting principle is different from the partial parallel interference cancellation method. It is a symbol-level weighting method based on the smallest mean value of the decision cost. This method sets the cost function of the decision, uses the minimum value of the decision cost as a criterion, determines the reliability coefficient of the decision result of each symbol, and uses the coefficient to weight the signal at the symbol level by using this coefficient, so that in the elimination of multiple access interference It only partially eliminates the interference generated by the user for the symbol. Compared with the traditional parallel interference cancellation method, the performance of this method is improved, especially in the case of low signal-to-noise ratio, the performance is significantly improved.
  • the object of the present invention is to provide a two-layer weighted parallel interference cancellation method applied to a CDMA mobile communication system, which improves the multi-user detection performance under the condition of little increase in complexity, especially in the case of low signal-to-noise ratio. Improved performance.
  • a double-layer weighted parallel interference cancellation method applied to a CDMA mobile communication system includes the following steps:
  • the RAKE receiver performs multipath despreading, channel estimation and multipath combining on the user's input signal
  • the present invention combines partial parallel interference cancellation and weighted parallel interference cancellation based on Bayesian criterion, and proposes a two-layer weighted parallel interference cancellation method.
  • it has the advantage of partial weighting algorithm, which can make up for the deviation of the user signal estimation in the statistical sense.
  • the weighted parallel interference cancellation based on the Bayesian criterion when the amount of calculation is not increased, the gain at a low signal-to-noise ratio is greatly improved, so that the performance of the present invention is relatively Yes
  • the weighting of the guidelines has been greatly improved.
  • a further object of the present invention is to provide a simplified two-layer weighted parallel interference cancellation method, which reduces the complexity of the algorithm while maintaining the performance of the above-mentioned two-layer weighted parallel interference cancellation method.
  • a double-layer weighted parallel interference cancellation method of a barreling algorithm according to the present invention includes the following steps:
  • the RAKE receiver performs multipath despreading, channel estimation and multipath combining on the user's input signal
  • the double-layer weighted parallel interference cancellation method of the barreling algorithm of the present invention changes the chip-level weighting to symbol-level weighting, while maintaining the double-layer weighted parallel interference cancellation performance, and reducing the complexity of the algorithm.
  • Figure 1 is a schematic diagram of the multi-level structure of a dual-layer weighted parallel interference cancellation receiver.
  • Figure 2 is a schematic diagram of the PIC structure of a two-layer weighted parallel interference cancellation method.
  • Figure 3 is a schematic diagram of the last-stage PIC structure.
  • FIG. 4 is a schematic diagram of a PIC structure of a simplified two-layer weighted parallel dry-four cancellation method.
  • the method of the present invention combines the idea of partial weighting and the idea of weighting based on Bayes' criterion.
  • the reliability coefficient of the decision result of the symbol is calculated according to the weighting algorithm formula based on the Bayesian criterion; the reliability signal of the user is used to weight the reproduced signal of the symbol.
  • the chip-level weighted reproduced signals of other users are used to obtain the multiple-access interference of other users on the desired user; then a weight is set, and the obtained multiple-access interference is performed using the weight. Weighted.
  • the weighted multiple access interference is subtracted from the received signal, that is, the multiple access interference of other users to the desired user is partially eliminated.
  • the above method is adopted for each level of PIC structure.
  • the multi-level structure of the double-layer weighted parallel interference cancellation method is the same as the traditional parallel interference cancellation method, as shown in Figure 1.
  • the first-stage PIC structure 1 processes the baseband signal zf of the received signal as an input signal of each user, and the output signal of each user obtained is the input signal of each user in the next-stage PIC structure;
  • the input signal of the user is processed, and the output signal of each user obtained is the input signal of each user in the next-stage PIC structure; in this way, it is processed step by step.
  • the user's output signal is the end result of a multi-stage PIC structure.
  • the PIC structure of the double-layer weighted parallel interference cancellation method is the same as the weighted parallel interference cancellation method based on the Bayesian criterion, as shown in Figure 2.
  • the final PIC structure of this method is the same as the traditional parallel interference cancellation method, as shown in Figure 3.
  • the baseband signal? Fj of the received signal enters the first-stage PIC structure 1 in parallel.
  • input signals that enter the PIC structure in parallel enter the RAKE receivers 3 of each user.
  • the RAKE receiver 3 first despreads the input signal, then performs channel estimation from the despread results, and finally performs multipath combining, and sends the multipath combined results to the hard decider 4 and the decision reliability calculator 7 at the same time.
  • the estimation results are sent to the verdict at the same time.
  • the hard decision unit 4 performs a hard decision on the input signal, and sends the hard decision result to the signal regenerator 5.
  • the baseband signal of the received signal can be expressed as:
  • the RAKE receiver performs multipath despreading on r, w (t), performs channel estimation from the despreading results, and then performs multipath combining.
  • the result of the despreading of the first path by the user's RAKE receiver is
  • the maximum ratio combining is used to obtain the multipath combining result of the RAKE receiver as: Is an estimate,.whoRepresents the channel fading value of the first user / path, and represents the power of the user ⁇ ⁇ .
  • the multipath combining result of the above RAKE receiver can be expressed as + «,., Where", is Gaussian white noise, obeying the normal distribution N (0, CT , 2 ), is the noise power of ",; a, () is the user's first symbol, and the value is +1 or- 1, is a real number related to channel fading.
  • the reliability calculator calculates the reliability of the hard decision result from the two input signals and sends the reliability coefficient to the signal regenerator 5.
  • w is a positive real number, which is used to compensate for the inaccuracy of the noise power estimation.
  • the signal regenerator obtains the user's reproduced signal from the three input signals, and sends the reproduced signal to the multiple-access interference estimation and partial interference cancellation device 6.
  • the baseband signal r (t) of the received signal also enters the multi-access interference estimation and partial interference cancellation device 6.
  • the device estimates the multiple-access interference received by each user from the reproduced signals of the users input in parallel, and eliminates the multiple-access interference received by a user from the baseband signal r (0 of the received signal).
  • r +1) (t) is the input signal of the user's RAKE receiver in the next-stage PIC structure.
  • Different weights p w can be set for different levels of interference cancellation, and preferably 1) ⁇ (2) ... ⁇ (/ ; ) ... ⁇ (5) , where is the interference cancellation at the first stage, and s is the number of stages of interference cancellation.
  • the next stage PIC structure performs the same processing on the signals input in parallel. This is processed step by step.
  • the signals input in parallel enter the RAKE receiver 3 of each user.
  • the user's RAKE receiver performs multipath despreading, channel estimation, and multipath combining on the input signal to obtain the user's soft output.
  • the soft output of each user is the final result of each user in the multi-stage PIC structure. That is, multi-path despreading is performed on the user's input signal according to formula (2), and multi-path combining is performed according to formulas (3) and (4).
  • the soft output of the user i obtained by the multipath combination is taken as the final result of the user ⁇ ⁇ in the multi-stage PIC structure.
  • the user's soft output is sent to the user's decoder for decoding.
  • the present invention combines a partial parallel interference cancellation with a weighted parallel interference cancellation based on the Bayesian criterion, and proposes a two-layer weighted parallel interference cancellation method.
  • the invention not only has the advantages of a weighting algorithm based on the Bayesian criterion, and has the smallest decision cost at the symbol level, but also has the advantages of a partial weighting algorithm, which can make up for the deviation of the user signal estimation in a statistical sense.
  • formula (6) involves a hyperbolic tangent operation, which cannot be directly implemented under the existing hardware conditions.
  • a new computing chip needs to be developed, and the cost is high; in formula (9), £ ⁇ is a chip-level multiplication, which requires a large amount of calculation.
  • the present invention further proposes a double-layered weighted parallel interference cancellation method for a canned algorithm.
  • the multi-level structure is shown in FIG. 1, and the PIC structure of the canned algorithm is shown in FIG. 4.
  • the level PIC structure is shown in Figure 3.
  • the received baseband signal 3 ⁇ 4 enters the first-stage PIC structure 1 in FIG. 1 in a parallel manner.
  • the input signals r that enter the PIC structure in parallel enter the RAKE receivers 3 of each user.
  • the RAKE receiver 3 first despreads the input signal, then performs channel estimation, and finally performs multipath combining.
  • the RAKE receiver 3 sends the multipath combining result to the soft decision unit 8 and sends the channel estimation result to both the soft decision unit 8 and the signal regenerator.
  • the multipath combining result of the user ⁇ ⁇ can be expressed Is: Gaussian white noise, obeying the normal distribution ⁇ , ⁇ , 2 ); a, (m) is the user's first symbol, and the value is +1 or -1, which is a real number related to channel fading.
  • (X) is defined as a line segment connecting points ( ⁇ and point /.), Where the coordinates of C q are (3 ⁇ 4 )). Use this line segment ( ⁇ 1) 9 to approximate the interval [tanhO 'on the curve of ⁇ ⁇ — g).
  • the equation for the line segment C q D q is:
  • the soft decision device 8 sends the soft decision result to the soft decision weighting device 9.
  • the soft decision weighting device 9 weights the soft decision result according to formula (14), and sends the weighted result to the signal regenerator 5. This weighting is a symbol-level weighting.
  • the signal regenerator 5 obtains the user's reproduced signal from the two input signals according to the following formula, and sends the reproduced signal to the multiple-access interference estimation and partial interference cancellation device 6.
  • the chip-level weighted reproduced signal of the user can Expressed as:
  • the baseband signal r of the received signal also enters the multiple-access interference estimation and partial interference cancellation device 6.
  • This device estimates the multiple-access interference received by each user from the reproduced signals of the users input in parallel.
  • the estimation of the multiple access interference suffered by the user ⁇ ⁇ is:
  • the multiple-access interference received by user ⁇ is eliminated from the baseband signal r () of the received signal, and the multiple-access interference is canceled according to formula (17):
  • the signal obtained by eliminating the multiple access interference received by the user from the baseband signal r (t) of the received signal is used as the output signal of the user in the PIC structure at this stage and the input signal of the user in the PIC structure at the next stage.
  • the next stage PIC structure performs the same processing on the signals input in parallel.
  • the signals input in parallel enter the RAKE receiver 3 of each user.
  • the user's RAKE receiver performs despreading, channel estimation, and multipath combining on the input signal to obtain the user's soft output.
  • the soft output of each user is the end result of the multi-stage PIC structure. In the receiver, the user's soft output is sent to the user's translation
  • the encoder performs decoding.
  • the baseband signal r (i) of the received signal enters the first-stage PIC structure 1 in the figure in parallel.
  • the input signals 7 that enter the PIC structure in parallel enter the RAKE receivers 3 of each user.
  • the RAKE receiver 3 first despreads the input signal, then performs channel estimation, and finally performs multipath combining.
  • the RAKE receiver sends the multipath combining result to the soft decision device 8, and sends the channel estimation result to the soft decision device 8 and the signal regenerator 5 at the same time.
  • the user's multipath merge result can be expressed as:
  • the soft decision unit 8 performs a soft decision on the input signal.
  • the soft decision unit 8 sends the soft decision result to the soft decision weighting device 9.
  • the soft decision weighting means 9 performs symbol-level weighting on the soft decision result according to formula (22), and sends the weighted result to the signal reproducer 5.
  • the signal regenerator 5 obtains the user's reproduced signal from the two input signals according to the following formula, and sends the reproduced signal to the multiple-access interference estimation and partial interference cancellation device 6, user ⁇
  • the baseband signal r (t) of the received signal also enters the multiple access interference estimation and partial interference cancellation device. 6.
  • This device estimates the multiple access interference experienced by each user from the reproduced signals of each user input in parallel.
  • the estimated multiple access interference received by the user ⁇ ⁇ is:
  • the multiple-access interference received by the user is eliminated from the baseband signal r (t) of the received signal, and the above-mentioned multiple-access interference is canceled according to formula (25):
  • r strict is the output signal of user i in the k-th PIC structure, and it is also the input signal of the user's RAKE receiver in the next-level HC structure.
  • the signal obtained by eliminating the multiple access interference received by the user from the baseband signal r ⁇ t) of the received signal is used as the output signal of the user in the PIC structure of this stage and the input signal of the user in the PIC structure of the next stage.
  • the next stage PIC structure performs the same processing on the signals input in parallel. This is processed step by step.
  • the signals input in parallel enter the RAKE receiver 3 of each user.
  • the user's RAKE receiver performs despreading, channel estimation, and multipath combining on the input signal to obtain the user's soft output.
  • the soft output of each user is the end result of the multi-stage PIC structure. In the receiver, the user's soft output is sent to the user's decoder for decoding.

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

Description

双层加权并行干扰抵消方法
技术领域
本发明涉及 CDMA移动通信系统中'的多用户检测 (MUD )技术, 尤其涉及一种 CDMA系统的双层加权并行干扰抵消方法。 发明背景
CDMA移动通信系统因其高容量、 高服务质量以及保密性好等优点 已经成为第三代移动通信的发展方向。 其中多用户检测技术是克服多址 干扰( Multiple Access Interference )对 CDMA系统容量的限制, 从而提 高 CDMA系统容量和性能的一种增强型技术。
多用户检测技术是利用多个用户的信息, 对多个用户信号进行联合 检测, 从而尽可能地减小多址干扰对接收机性能的影响, 提高系统的容 量。 目前, 多用户检测包括作为最佳检测器的最大似然序列检测器, 作 为次最佳检测器的线性多用户检测器和干扰抵消多用户检测器。 其中, 干扰抵消多用户检测是将期望用户的信号视为有用信号, 将其他用户的 信号视为千扰信号; 先从接收信号中消除其他用户的干扰, 得到期望用 户的信号, 然后对期望用户的信号进行检测, 从而提高系统的性能。
干扰抵消多用户检测分为串行干扰抵消 ( Serial Interference Cancellation )和并行干扰抵消 ( Parallel Interference Cancellation )。 串行 干扰抵消是按照功率降序对用户信号进行排序, 采用串行的去干扰方 式, 该方法性能优于单用户检测, 但是延时较大, 而且需要进行功率排 序, 计算量较大以及对初始信号估计敏感。 并行干扰抵消是从接收信号 中并行地为每个用户消除所有其他用户的信号干扰, 该方法具有延时 小、 计算复杂性小的优点。 扰抵消方法以及基于贝叶斯准则的加权并行干扰抵消方法等。
传统并行干扰抵消方法在高信噪比下相对于单用户检测器性能提高 较大, 但是在低信噪比下, 该方法相对于单用户检测器性能提高的幅度 降低。
与传统并行干扰抵消方法的从接收信号中完全地消除期望用户受到 的多址干扰不同, 部分并行干扰抵消方法是给每级干扰抵消设置一个权 值, 对期望用户受到的多址干扰进行加权, 在干扰抵消过程中, 只是部 分地消除多址干扰。 高斯信道下传统的并行干扰抵消方法从接收信号中 完全地消除期望用户受到的多址干扰, 这种情况下对期望用户信号的估 计是有偏估计; 部分并行干扰抵消方法只是部分地消除多址干扰, 可以 纠正对期望用户信号估计的偏差,使判决结果更可靠。在较低信噪比下, 部分并行干扰抵消方法的性能明显优于传统的并行干扰抵消方法。
基于贝叶斯准则的加权并行干扰抵消方法由美国专利 US 5418814 公开。 虽然也是一种加权方法, 但加权基理不同于部分并行干扰抵消方 法, 是一种基于判决代价的均值最小的符号级加权方法。 该方法设置判 决的代价函数, 以判决代价的均值最小作为准则, 确定每个符号判决结 果的可靠性系数, 并用该系数对该符号再生的信号进行符号级加权, 这 样在多址干扰的消除中只是部分地消除该用户该符号产生的干扰。 该方 法的性能相对于传统的并行干扰抵消方法有提高, 尤其在低信噪比情况 下, 性能提高较明显。
以上两种方法虽然都有效地提高了传统并行干扰抵消方法在较低信 噪比下的性能, 但是提高的幅度有限。 发明内容
本发明的目的在于提供一种应用于 CDMA移动通信系统的双层加 权并行干扰抵消方法, 在复杂度增加不大的情况下, 使多用户检测性能 得到提高, 尤其在低信噪比情况下, 性能提高较大。
本发明一种应用于 CDMA移动通信系统的双层加权并行干扰抵消 方法, 包括以下步骤:
( a ) 由 RAKE接收机对用户的输入信号进行多径解扩、 信道估计 和多径合并;
( b ) 对多径合并的结果进行硬判决;
( c ) 由多径合并结果和信道估计值计算每个符号的硬判决结果的 可靠性系数;
( d ) 由硬判决结果、 可靠性系数及信道估计值再生用户的码片级 加权信号;
( e ) 由并行输入的各用户的码片级加权再生信号估计各用户受到 的多址干扰, 并对不同级别的干扰抵消设置权值, 对期望用户受到的多 址干扰进行加权;
( f ) 从用户总的输入信号中减去期望用户受到的加权的多址干 扰, 得到该期望用户的输出信号, 即下一级并行干扰^ ^消中该用户的输 入信号。
本发明将部分并行干扰抵消和基于贝叶斯准则的加权并行干扰抵消 相结合, 提出双层加权并行干扰抵消方法 , 不仅具有基于贝叶斯准则的 加权算法的优点, 在符号级判决代价最小, 而且具有部分加权算法的优 点, 可以弥补统计意义上对用户信号估计的偏差。 同时, 与基于贝叶斯 准则的加权并行干扰抵消相比, 在计算量增加不大的情况下, 大大提高 了在低信噪比时的增益, 使本发明的性能相对于部分加权和基于贝叶斯 准则的加权都有很大提高。
本发明的进一步的目的在于提供一种筒化的双层加权并行干扰抵消 方法, 在保持上述双层加权并行干扰抵消方法性能的同时, 降低了算法 的复杂度。
本发明一种筒化算法的双层加权并行干扰抵消方法,包括以下步骤:
( a ) 由 RAKE接收机对用户的输入信号进行多径解扩、 信道估计 和多径合并;
( b ) 由多径合并结果和信道估计值进行软判决;
( c ) 对不同级别的软判决设置权值, 并对软判决进行符号级加权;
( d ) 由加权的软判决结果及信道估计值再生用户的码片级加权信 号;
( e ) 由并行输入的各用户的码片级加权再生信号估计各用户受到 的多址干扰;
( f) 从用户总的输入信号中减去期望用户受到的多址干扰, 得到 该期望用户的输出信号, 即下一级并行干扰抵消中该用户的输入信号。
本发明一种筒化算法的双层加权并行干扰^ ^消方法, 变码片级加权 为符号级加权, 在保持双层加权并行干扰抵消性能的同时, 降低了算法 的复杂度。 附图简要说明
图 1是双层加权并行干扰抵消接收机的多级结构示意图。
图 2是双层加权并行干扰抵消方法的 PIC结构示意图。
图 3是最后一级 PIC结构示意图。
图 4是简化的双层加权并行干 4尤抵消方法的 PIC结构示意图。 实施本发明的方式
下面结合附图和具体实施例对本发明做进一步详细说明。
本发明方法是结合部分加权的思想和基于贝叶斯准则的加权思想。 在对用户的每个符号进行判决时, 按照基于贝叶斯准则的加权算法公式 计算该符号判决结果的可靠性系数; 用该可靠性系数对该用户该符号的 再生信号进行加权。 在多址干扰的估计与消除过程中, 由其他用户的码 片级加权再生信号求得其他用户对期望用户的多址干扰; 然后设置一个 权值, 用该权值对得到的多址干扰进行加权。 最后, 从接收信号中减去 经过加权的多址干扰, 即部分地消除其他用户对期望用户的多址干扰。 对每级 PIC结构都采用上述方法。
双层加权并行干扰抵消方法的多级结构同传统的并行干扰抵消方 法, 如图 1所示。 第一级 PIC结构 1把接收信号的基带信号 zf 作为各 用户的输入信号, 进行处理, 得到的各用户的输出信号是下一级 PIC结 构中各用户的输入信号;第二级 PIC结构对各用户的输入信号进行处理, 得到的各用户的输出信号是下一级 PIC结构中各用户的输入信号; 这样 逐级处理, 最后一级 PIC结构 2对各用户的输入信号进行处理, 得到的 各用户的输出信号是多级 PIC结构的最终结果。
双层加权并行干扰抵消方法的 PIC结构同基于贝叶斯准则的加权并 行干扰抵消方法, 如图 2所示。 该方法的最后一级 PIC结构同传统的并 行干扰抵消方法, 如图 3所示。
参见图 1所示,接收信号的基带信号? f j以并行方式进入第一级 PIC 结构 1。 参见图 2所示, 并行进入 PIC结构的输入信号分別进入各用户 的 RAKE接收机 3。 RAKE接收机 3先对输入信号进行解扩, 然后由解 扩结果进行信道估计, 最后进行多径合并, 并将多径合并结果同时送给 硬判决器 4和判决可靠性计算器 7, 将信道估计结果同时送给判决可靠 性计算器 7和信号再生器 5。 硬判决器 4对输入信号进行硬判决, 并将 硬判决结果送给信号再生器 5。
在衰落信道环境下, 接收信号的基带信号 可以表示为:
Figure imgf000008_0001
= ¾ - τη . 一 ½ ) + Z(t) 其中, j表示接收信号的基带信号; 表示第 个用户第 /径的信 道衰落值, L为径数; 表示第 ζ·个用户第 /径的时延; 表示用户 i 的发送信号, 表示用户总数; 表示用户 ζ·的功率; 表示用户 的 符号流, =∑ (^ 0, ^表示第 个用户的第 个符号, 表示周期为 Γ¾的信号脉冲,在不妨碍算法推导结论的情况下,设 p(t) 是矩形脉冲 (当 te[0,rj时, p(t) = 1; 当 tg[0,rj时, p(t) = 0); 表示 用户 ζ·的扩频码; Ζ (^表示信道噪声。
在第 级 PIC结构中,用户 的 RAKE接收机 3的输入信号为, 当 =l时, r,.(')(t) = r(t)。
RAKE接收机对 r,w (t)进行多径解扩 , 并由解扩结果进行信道估计, 然后进行多径合并。 用户 ζ·的 RAKE接收机对第 I径的解扩结果为:
Figure imgf000008_0002
其中, /=1, ...... ,L。
采用最大比合并, 得到 RAKE接收机的多径合并结果为:
Figure imgf000008_0003
是 的估计值, 。„表示第 个用户第 /径的信道衰落值, 表 示用户 ζ·的功率。
上述 RAKE接收机的多径合并结果可以表示为
Figure imgf000009_0001
+ «,. , 其 中《,为高斯白噪声, 服从正态分布 N(0,CT,2), 是《,的噪声功率; a,( )是 用户 的第 个符号, 值为 +1或 -1 , 是与信道衰落相关的实数。
对第 ζ·个用户第 个符号的判决结果为:
Figure imgf000009_0002
可靠性计算器由两个输入信号计算硬判决器判决结果的可靠性系 并将可靠性系数送给信号再生器 5。 的可靠性系数计算如下: j = (6)
Figure imgf000009_0003
其中, w是正实数, 用来弥补噪声功率估计的不准确。 可以通过实 验确定不同信噪比下 w的数值, 在信噪比较高时, 可以取 w=l。
信号再生器由输入的三个信号得到用户的再生信号, 并将再生信号 送入多址干扰的估计与部分干扰抵消装置 6。 用户 的码片级加权再生 信号为: gf](t) = tAa ; (")( ") (卜 ― r,7)c, ― ) (7) 其中, (^表示周期为 Γ6的信号脉沖。
从图 2中可以看到,接收信号的基带信号 r(t)也进入多址干扰的估计 与部分干护 ύ抵消装置 6。 该装置由并行输入的各用户的再生信号估计各 用户受到的多址干扰, 从接收信号的基带信号 r(0中消除某个用户受到 的多址干 4尤得到的信号作为本级 PIC结构中该用户的输出信号、 下一级 PIC结构中该用户的输入信号。
第 级 PIC结构中, 用户 ί的多址干扰(ΜΆΙ ) 的估算为: ,w= g t) (8) 设第 k级 PIC结构的权值为 pW, 按照公式( 9 )对公式( 8 )中得到 的 MAI进行加权干扰抵消, 得到第 k級 PIC结构中用户 i的输出信号 r/i+1)(t)。 r +1)(t)是下一级 PIC结构中用户 的 RAKE接收机的输入信号。
= r(t)-pwik (9) 对不同级別的干扰抵消可以设置不同的权值 pw , 且较佳地取 1) <^(2)...<^(/)...<^(5),其中 为第 级干扰抵消, s为干扰抵消的级数。
下一級 PIC结构对并行输入的信号进行同样的处理。这样逐级处理, 当处理到最后一级 PIC 结构时, 并行输入的信号分别进入各用户的 RAKE接收机 3。 用户的 RAKE接收机对输入信号进行多径解扩、 信道 估计和多径合并, 得到用户的软输出。 各用户的软输出就是多级 PIC结 构中各用户的最终结果。 即: 按照公式(2)对用户 的输入信号进行多 径解扩, 按照公式 (3)、 (4)进行多径合并。 将多径合并得到的用户 i 的软输出作为多级 PIC结构中用户 ζ·的最终结果。 在接收机中, 用户的 软输出被送给该用户的译码器进行译码。
本发明将部分并行干扰抵消和基于贝叶斯准则的加权并行干扰抵消 相结合, 提出双层加权并行干扰抵消方法。 本发明不仅具有基于贝叶斯 准则的加权算法的优点, 在符号级判决代价最小, 而且具有部分加权算 法的优点, 可以弥补统计意义上对用户信号估计的偏差。 同时, 与基于 贝叶斯准则的加权并行干扰抵消相比, 在计算量增加不大的情况下, 大 大提高了在低信噪比时的增益, 使本发明的性能相对于部分加权和基于 贝叶斯准则的加权都有很大提高。
通过对上述双层加权并行干扰抵消方法计算公式的分析可以发现, 公式(6) 涉及双曲正切运算, 该运算在现有硬件条件下无法直接实现, 需要开发新的运算芯片, 成本较高; 公式(9 ) 中 £ ^为码片级乘法, 运算量较大。
针对上述问题, 本发明进一步提出一种筒化算法的双层加权并行干 扰抵消方法,其多级结构如图 1所示,筒化算法的 PIC结构如图 4所示, 筒化算法的最后一级 PIC结构如图 3所示。
本发明筒化算法的一个实施例为:
如图 1所示, 接收信号的基带信号 ¾)以并行方式进入图 1 中的第 一级 PIC结构 1。如图 4所示,并行进入 PIC结构的输入信号 r 分别进 入各用户的 RAKE接收机 3。 RAKE接收机 3先对输入信号进行解扩, 然后进行信道估计, 最后进行多径合并。 RAKE接收机 3将多径合并结 果送给软判决器 8, 将信道估计结果同时送给软判决器 8和信号再生器 在第 /c级 PIC结构中, 用户 ζ·的多径合并结果可以表示为: 为高斯白噪声,服从正态分布 Λφ,σ,2); a,(m)是用户 的第 个符号, 值为 + 1或 -1 , 是与信道衰落相关的实数。
软判决器 8对输入信号进行软判决, 用户 ζ·的 RAKE接收机的多径 合并结果的软判决为 = 且/; 满足下式:
Figure imgf000011_0001
其中, 是用户 ζ·的第 个符号的判决结果, ^m)W = Sgn ww } , WW为 ^WW的可靠性系数。 用分段线性判决代替上述双层加权并行干扰抵消方法中的双曲正切 判决, 设分段线性判决函数为 (X), 用分段线性判决代替双曲正切判决 就是用分段线性判决函数 逼近双曲正切函数 tanh(x) , 分段线性判决 函数的推导过程如下:
① .定义分段线性判决函数 Ζ(Χ)
由于双曲正切函数是奇函数: tanh(- ) = -tanh(x); 所以, 定义
= - (x)。
② .确定阔值
由于双曲正切函数具有特点: 当 x→oo时, tanh(x)~ l; 因此, 取 阈值 >0, 当 >6>时, 令 (x)=l;
③ .确定线性化参数 Q
当 0≤x≤6>时, 将区间 [0, ]等分为 Q个小区间, 第 个小区间为
Figure imgf000012_0001
④.在第 个小区间内 的表达式为:
在区间 [χ^, ], 将 (X)定义为连接点(^和点/ 的线段。 其中, Cq 的坐标为 (¾
Figure imgf000012_0002
))。 用该线段 (^1)9近似区间 [χγ— g上的 tanhO')曲线。 线段 CqDq的方程为:
Figure imgf000012_0003
⑤ .利用 L(~x) = - L(x), 区间 上 (χ)的表达式为:
(X) = - Lq{-x)
⑥ .分段线性判决的函数 (X)的表达式为: τ(
Figure imgf000012_0004
-\,χ<-θ
软判决器 8将软判决结果送给软判决加权装置 9。软判决加权装置 9 对软判决结果以公式( 14)进行加权, 并将加权结果送给信号再生器 5。 该加权为符号级加权。
) (14) 信号再生器 5按照下述公式由两个输入信号得到用户的再生信号, 并将再生信号送入多址干扰的估计和部分干扰抵消装置 6, 用户 的码 片级加权再生信号可以表示为:
Figure imgf000013_0001
从图 4 中可以看到, 接收信号的基带信号 r (^也进入多址干扰的估 计与部分干扰抵消装置 6。 该装置由并行输入的各用户的再生信号估计 各用户受到的多址干扰, 第 级 PIC算法中, 用户 ζ·受到的多址干扰的 估计为:
Figure imgf000013_0002
计算得到用户 i的多址干扰后,从接收信号的基带信号 r( )中消除用 户 ί受到的多址干扰, 按照公式(17 )对上述多址干扰进行干扰抵消:
Figure imgf000013_0003
是第 级 PIC结构中用户 i的输出信号, 也是下一级 PIC结 构中用户 ζ·的 RAKE接收机的输入信号。
从接收信号的基带信号 r(t)中消除用户受到的多址干扰得到的信号 作为本级 PIC结构中该用户的输出信号、 下一级 PIC结构中该用户的输 入信号。 下一级 PIC结构对并行输入的信号进行同样的处理。 这样逐级 处理, 当处理到最后一级 PIC结构时, 如图 3所示, 并行输入的信号分 别进入各用户的 RAKE接收机 3。用户的 RAKE接收机对输入信号进行 解扩、 信道估计和多径合并, 得到用户的软输出。 各用户的软输出就是 多级 PIC结构的最终结果。 在接收机中, 用户的软输出被送给用户的译 码器进行译码。
本发明简化算法的另一个实施例为:
如图 1所示, 接收信号的基带信号 r(i)以并行方式进入图中的第一 级 PIC结构 1。 如图 4所示, 并行进入 PIC结构的输入信号 7 )分别进 入各用户的 RAKE接收机 3。 RAKE接收机 3先对输入信号进行解扩 , 然后进行信道估计, 最后进行多径合并。 RAKE接收机将多径合并结果 送给软判决器 8, 将信道估计结果同时送给软判决器 8和信号再生器 5。 在第 A级 PIC结构中, 用户 的多径合并结果可以表示为:
+ (18) ζϊ,.为高斯白噪声,服从正态分布 Λ ,σ; 2); ",(m)是用户 的第 个符 号, 值为 +1或 -1。 是与信道衰落相关的实数。
软判决器 8对输入信号进行软判决, 用户 ζ·的 RAKE接收机的多径 合并结果的软判决为 ζί" = , 且 y.WW^W满足下式:
Figure imgf000014_0001
其中, 是用户 的第 个符号的判决结果, s ^ sgn^ " } , . 为 的可靠性系数。
用查表法代替上述双层加权并行干扰抵消方法中的双曲正切判决, 设查表法的判决函数为 Γ (; c) , 用查表法代替双曲正切判决就是用查表法 的判决函数 Γ(χ)逼近双曲正切函数 tanh(x) , 查表法的判决函数的推导过 程如下:
①.定义查表法的判决函数
由于双曲正切函数是奇函数: tan (- ) = -tan (x) , 所以, 定义
T(- x) = -T(x) ; ② .确定阈值 <
由于双曲正切函数具有特点: 当 χ→οο时, tan ( )→l; 因此, 本发 明中取阈值 0>0, 当; c>0时, 令 r(;c) = l;
③ .确定线性化参数 Q
当 O≤ c≤ 时, 将区间 [0 等分为 Q 个小区间, 第 q 个小区间为
Figure imgf000015_0001
④ .在第 个小区间内: )的表达式为: 在区间 [ _15 ], 取区间的中点^ 将 Γ(χ)定义如下:
2 r(x) = tan ( " (20)
⑤ .利用 Γ (- c) = -r(c), 可以得到区间 [- 0]上 Γ(χ)的表达式;
⑥ .查表法的判决函数 的表达式为:
\,χ>θ
χ„ , +χ„
tanh( ' '), χ e [xq_ , xq J
Τ(χ) = 2 (21)
- tan ( g"2 "),x e [- xg,-一' j
Figure imgf000015_0002
软判决器 8将软判决结果送给软判决加权装置 9。软判决加权装置 9 对软判决结果以公式(22)进行符号级加权, 并将加权结果送给信号再 生器 5。
AW(' = ') ) (22) 信号再生器 5按照下述公式由两个输入信号得到用户的再生信号, 并将再生信号送入多址干扰的估计和部分干扰抵消装置 6, 用户 ζ·的码 片级加权再生信号可以表示为: gf]i ) = tAu f^„ — nTb -rM - u) (23) 从图 4中可以看到,接收信号的基带信号 r(t)也进入多址干扰的估计 与部分干扰抵消装置 6。 该装置由并行输入的各用户的再生信号估计各 用户受到的多址干扰, 第 级 PIC算法中, 用户 ζ·受到的多址干扰的估 计为:
Ψ = gf t) (24)
=',·/≠'■
计算得到用户 的多址干扰后,从接收信号的基带信号 r(t)中消除用 户 受到的多址干扰, 按照公式(25 )对上述多址干扰进行干扰抵消:
Figure imgf000016_0001
r严 )是第 k级 PIC结构中用户 i的输出信号, 也是下一级 HC结 构中用户 的 RAKE接收机的输入信号。
从接收信号的基带信号 r{t)中消除用户 受到的多址干扰得到的信号 作为本级 PIC结构中该用户的输出信号, 下一级 PIC结构中该用户的输 入信号。 下一级 PIC结构对并行输入的信号进行同样的处理。 这样逐级 处理, 当处理到最后一级 PIC结构时, 如图 3所示, 并行输入的信号分 别进入各用户的 RAKE接收机 3。用户的 RAKE接收机对输入信号进行 解扩、 信道估计和多径合并, 得到用户的软输出。 各用户的软输出就是 多级 PIC结构的最终结果。 在接收机中, 用户的软输出被送给用户的译 码器进行译码。

Claims

权利要求书
1、 一种应用于 CDMA移动通信系统的双层加权并行干扰抵消方 法, 包括以下步骤:
(a) 由 RAKE接收机对用户的输入信号进行多径解扩、 信道估计 和多径合并;
(b) 对多径合并的结果进行硬判决;
( c ) 由多径合并结果和信道估计值计算每个符号的硬判决结果的 可靠性系数;
(d) 由硬判决结果、 可靠性系数及信道估计值再生用户的码片级 加权信号;
( e ) 由并行输入的各用户的码片级加权再生信号估计各用户受到 的多址干扰, 并对不同级别的干扰抵消设置权值, 对期望用户受到的多 址干扰进行加权;
( f ) 从用户总的输入信号中减去期望用户受到的加权的多址干 扰, 得到该期望用户的输出信号, 即下一级并行干扰抵消中该用户的输 入信号。
2、 根据权利要求 1 所述的双层加权并行干扰抵消方法, 如果用 户 ζ·的第 1级并行干扰抵消的输入信号表示为 r/"(t) , 则
步骤(a) 中用户 的多径合并结果由公式: y;('")w=Re "')w}计算, 可以表示为 其中, 其中 为高斯白噪声, 服从正态分 布 N(0, ,2), ex2是 的噪声功率, α«是用户 的第 个符号, 值为 +1 或 -1, 是与信道衰落相关的实数;
步骤 (b ) 中用户 i 的第 m 个符号的硬判决结果由公式: ,w
Figure imgf000017_0001
计算; 步骤(C) 中用户 ζ·的第 m个符号的判决结果的可靠性系数由公式: 计算, 其中, W是正实数;
Figure imgf000018_0001
步骤(d) 中用户 ζ·的码片级加权再生信号由公式: 的估
Figure imgf000018_0002
计值, 表示用户 ζ·第 /径的信道衰落值, 表示用户 ζ·的功率; 步骤(e) 中用户 ζ·受到的多址干扰的估计由公式: ,w= | (t)计
JO' 算;
设第 级并行干扰抵消的权值为 则步骤(f)中用户 ζ·的输出信 号由公式: r,(/i+1)(t) = )-„)计算, 其中, r 是接收信号的基带信号。
3、 居权利要求 2所述的双层加权并行干扰抵消方法, 其中步 骤(c)中用户 的第 个符号的判决结果的可靠性系数计算中, 用分段 线性判决代替双曲正切判决, 即用分段线性判决函数 (^逼近双曲正切 函数 tm (x), 分段线性判决函数 的表达式为:
Figure imgf000018_0003
-\,χ<-θ
4、 根据权利要求 2所述的双层加权并行干扰抵消方法, 其中步 驟( c )中用户 的第 个符号的判决结果的可靠性系数计算中, 用查表 法代替双曲正切判决, 即用查表法的判决函数 rfxj逼近双曲正切函数 tanhf , 查表法的判决函数 7¾)的表达式为: 1,χ>θ
J
Figure imgf000019_0001
-\,χ<-θ
5、 根据权利要求 1、 2、 3或 4所述的双层加权并行干扰抵消方 法, 其中步骤(e) 中对不同级别的干扰抵消设置不同的权值 ), 且 ^(1)<^(2)...<^(/£)...<^(5),其中 为第 级干扰抵消, S为干扰抵消的级数。
6、 一种应用于 CDMA移动通信系统的双层加权并行干扰抵消方 法, 包括以下步骤:
( a ) 由 RAKE接收机对用户的输入信号进行多径解扩、 信道估计 和多径合并;
(b) 由多径合并结果和信道估计值进行软判决;
(c) 对不同级别的软判决设置权值, 并对软判决进行符号级加权;
(d) 由加权的软判决结果及信道估计值再生用户的码片级加权信 号;
( e ) 由并行输入的各用户的码片级加权再生信号估计各用户受到 的多址干扰;
(f) 从用户总的输入信号中减去期望用户受到的多址干扰, 得到 该期望用户的输出信号, 即下一级并行干扰抵消中该用户的输入信号。
7、 根据权利要求 6所述的双层加权并行干扰抵消方法, 如果用 户 的第 k级并行干扰抵消的输入信号表示为 ,.w(t), 则
步驟(a) 中用户 的多径合并结果由公式: y;(m)("=Re^,(m)("}计算, 可以表示为
Figure imgf000019_0002
为高斯白噪声, 服从正态分 布 ;ν(0,σ,2), σ2是 的噪声功率, β«是用户 i的第 m个符号, 值为 +1 或 -1, 是与信道衰落相关的实数;
步骤(b ) 中用户 i的多径合并结果的软判决为 ^t'^ - .WH 'w, 且由公式: /;·(»')( ;»*) 计算, 其中, W是正实数, )(")是
Figure imgf000020_0001
用户 ζ·的第 个符号的硬判决结果, ^为^ 的可靠性系数;
设第 /C级软判决的权值为 则步骤(C ) 中用户 i的符号级加权 软判决由公式: Aww = ww · 计算得到;
步骤(d) 中用户 的码片级加权再生信号由公式: § ) =∑Αη t^„ -nTb - k.(t- ½)计算, 其中 ' 4,是", 的估
/=1 ιι=—∞
计值, 表示用户 第 /径的信道衰落值, A.表示用户 ζ·的功率; 步骤(e) 中用户 i受到的多址干扰的估计由公式:
Figure imgf000020_0002
算;
步骤(f) 中用户 Ζ·的输出信号由公式: „t) = r(t)— )计算, 其中, 是接收信号的基带信号。
8、 根据权利要求 Ί所述的双层加权并行干扰抵消方法, 其中步 骤(b)中用户 i的多径合并结果的软判决计算中, 用分段线性判决代替 双曲正切判决, 即用分段线性判决函数 逼近双曲正切函数 tanhf , 分段线性判决函数 W的表达式为:
Figure imgf000020_0003
-\,χ<-θ
9、 根据权利要求 7所述的双层加权并行干扰抵消方法, 其中步 骤(b)中用户 的多径合并结果的软判决计算中, 用查表法代替双曲正 切判决, 即用查表法的判决函数吖 逼近双曲正切函数 tanhf^, 查表法 的判决函数 Γ「χ的表达式为:
\,χ>θ
Figure imgf000021_0001
Λ,χ<-Θ
10、 根据权利要求 6、 7、 8或 9所述的双层加权并行干扰抵消方 法, 其中步骤 (c) 中对不同级别的软判决设置不同的权值 且
P < ...^...<^,其中 A为第 A级干扰抵消, 为干扰抵消的级数。
PCT/CN2002/000711 2001-10-09 2002-10-09 Procede de suppression d'interferences parallele a double ponderation WO2003032545A1 (fr)

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