+

WO2008025268A1 - Procédé et appareil de suppression d'interférence sur la base d'une décomposition de cholesky - Google Patents

Procédé et appareil de suppression d'interférence sur la base d'une décomposition de cholesky Download PDF

Info

Publication number
WO2008025268A1
WO2008025268A1 PCT/CN2007/070346 CN2007070346W WO2008025268A1 WO 2008025268 A1 WO2008025268 A1 WO 2008025268A1 CN 2007070346 W CN2007070346 W CN 2007070346W WO 2008025268 A1 WO2008025268 A1 WO 2008025268A1
Authority
WO
WIPO (PCT)
Prior art keywords
information symbol
semi
estimation
matrix
vector
Prior art date
Application number
PCT/CN2007/070346
Other languages
English (en)
Chinese (zh)
Inventor
Lei He
Original Assignee
Potevio Institute Of Technology 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.)
Filing date
Publication date
Application filed by Potevio Institute Of Technology Co., Ltd. filed Critical Potevio Institute Of Technology Co., Ltd.
Publication of WO2008025268A1 publication Critical patent/WO2008025268A1/fr

Links

Classifications

    • 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
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03012—Arrangements for removing intersymbol interference operating in the time domain

Definitions

  • the present invention relates to signal detection techniques in wireless communication systems, and more particularly to a method and apparatus for interference cancellation based on Cholesky decomposition. Background of the invention
  • ISI inter-symbol interference
  • MIMO multiple input multiple output
  • CDMA code division multiple access
  • the minimum mean squared linear block equalization (MMSE-BLE) algorithm and the zero-forcing algorithm are widely used in the overcoming of ISI in wireless communication systems, such as equalization algorithms, signal detection and time-division synchronization of MIMO communication systems. Joint detection of the site (TD-SCDMA) system.
  • MMSE-BLE minimum mean squared linear block equalization
  • TD-SCDMA Joint detection of the site
  • the following describes the specific process by taking the MMSE-BLE algorithm and the zero-forcing algorithm for signal detection in the MIMO communication system as an example.
  • ⁇ represents the autocorrelation matrix of the information symbol
  • R represents the autocorrelation matrix of the noise
  • ⁇ ( ⁇ ) represents the quantization process, that is, the hard decision operation, which is the estimated information symbol for the detection, that is, the final detection result.
  • the algorithm based on Cholesky decomposition is usually used to solve the above MMSE-BLE algorithm. Specifically, the method includes:
  • Step one solve M two! ⁇ ! ⁇ ! ! +! ⁇ 1 Cholesky decomposition.
  • the semi-equalization result is obtained according to the upper triangular matrix R, the system matrix ⁇ ⁇ and the noise autocorrelation matrix R hypo.
  • the semi-equalized results can be obtained by solving the above equations.
  • ⁇ , , ⁇ (2)
  • the information symbol is estimated by performing quantization processing; the signal component corresponding to the soft bit of the information symbol is removed from the semi-equalization result f by the formula (3), and then Subsequent information symbol detection is performed by using the eliminated semi-equalization result; c. detecting the next information symbol according to the operation of step b, and sequentially detecting subsequent signals Symbol, until the first information symbol is detected.
  • step three has obtained all the information symbol estimates.
  • the signal detection by the MMSE-BLE algorithm is completed from step one to step three.
  • the method obtains the information symbol estimation ⁇ 2 ,..., using the formula (2) in the third step, but does not use this information symbol estimation in the detection of the subsequent information symbols, but only through the formula ( 3) Achieving equalization, but failing to achieve interference cancellation, thus causing the semi-equalization result for subsequent detection to contain the signal component corresponding to the previous detection result, thereby increasing the error rate of the information symbol estimation obtained by subsequent detection, The detection performance of the receiving system is reduced.
  • H, xM [h 1 h 2 ... h M ] is the system matrix, X MX1 is the information symbol vector, ! ! Is the noise vector.
  • x (H H RH) H H R y ( ⁇ )
  • Rrust represents the autocorrelation matrix of noise
  • ⁇ ( ⁇ ) represents the quantization process, that is, the hard decision operation
  • the estimated information symbol for the detection that is, the final detection result.
  • the Cholesky decomposition based method is also used to solve the above zero-forcing algorithm. Specifically, the method includes:
  • Step two' according to the upper triangular matrix! ⁇ , system matrix 11 and the autocorrelation matrix of the noise, get the semi-equilibrium result ⁇
  • the semi-equalized results can be obtained by solving the above equations.
  • Step 3' sequentially detects the information symbols in the information symbol vector x, giving the detected information symbols and information symbol estimates.
  • the information symbol estimation is obtained by performing quantization processing; the signal component corresponding to the soft bit of the information symbol is eliminated from the semi-equilibrium result f by the formula (3), and the eliminated semi-equilibrium result is used.
  • Step 3' got all the information symbol estimates, 2 , .. . , ⁇ .
  • the signal detection by the zero-forcing algorithm is completed from step one to step three.
  • the method obtains the information symbol estimation ⁇ using the formula (2)' in the step three', but does not use this information symbol estimation in the detection of the subsequent information symbols, but only uses the formula (3)' Zero forcing is achieved, which makes the remaining noise components no longer satisfy the white noise condition, and colorization noise occurs, which causes the zero-forcing algorithm to become the worst of many joint detection algorithms, which makes the information symbol estimation
  • the error rate is improved, and the detection performance of the receiving system is reduced.
  • the forced-zero algorithm based on Choleky decomposition the algorithm is often used in actual systems for signal detection.
  • the MMSE-BLE algorithm based on Cholesky decomposition the zero-forcing algorithm is used to overcome the ISI in the wireless communication system, and the joint algorithm in the TD-SCDMA system is the same as the above implementation process, so the same is true.
  • the problem is that the detection performance and the zero-forcing effect are reduced, and will not be described here. Summary of the invention
  • embodiments of the present invention provide a method and apparatus for implementing interference cancellation based on Cholesky decomposition, thereby improving detection performance of a receiving system.
  • the embodiment of the present invention adopts the following technical solutions:
  • a method for implementing interference cancellation based on Cholesky decomposition including:
  • the current information symbol estimate given in the sequence detection information symbol vector described in step c is used for the detection of the next information symbol.
  • the determining of the current information symbol to be used for the next information symbol is: removing the signal component corresponding to the given current information symbol from the semi-equalization result, and using the signal component after the signal is removed
  • the semi-equalization result detects the next information symbol.
  • the step C includes the following processing:
  • C2 according to the semi-equalization result and the upper triangular matrix, obtain the currently detected information symbol; c3, give an information symbol estimation according to the currently detected information symbol, and eliminate the corresponding signal component of the given information symbol estimation from the semi-equilibrium result And using the semi-equalization result after eliminating the signal component for the detection of the next information symbol;
  • the currently detected information symbol in step c2 is, where, is the currently detected information symbol, which is the i-th element in the semi-equalization result, and is the i-th column vector of the upper triangular matrix.
  • the i-th element in , i is the currently detected information symbol index.
  • the method further includes:
  • the step d includes the following processing:
  • the first information symbol estimates the interference of the previous information symbol estimation of the current information symbol estimation, and obtains the current information symbol estimation correction value
  • step D3. Determine whether the current information symbol estimate is the last information symbol estimate, and if yes, end the process; otherwise, set the next information symbol estimate to the current information symbol estimate, And return to step d2.
  • An apparatus for implementing interference cancellation based on Cholesky decomposition comprising: a decomposition unit, a semi-equalization unit, and an information symbol estimation unit,
  • the decomposing unit performs Cholesky decomposition on a specified matrix in the information symbol vector that needs to be sequentially detected, and obtains an upper triangular matrix, which is provided to the semi-equalization unit;
  • the semi-equalization unit obtains a semi-equalization result according to a system matrix, an autocorrelation matrix of the noise signal, and an upper triangular matrix provided by the decomposing unit, and provides the information symbol estimating unit;
  • the information symbol estimating unit sequentially detects information symbols in the information symbol vector according to the obtained semi-equalization result, and provides the detected current information symbol and the current information symbol estimation; and the sequence detection information symbol vector is given The current information symbol estimate is used for the detection of the next information symbol.
  • the information symbol estimating unit includes an estimating subunit and an interference canceling subunit,
  • the estimation subunit is configured to detect a current information symbol according to a semi-equilibrium result after interference cancellation by the interference cancellation subunit, and obtain a current information symbol estimate and send the information to the interference cancellation subunit.
  • the interference cancellation subunit is configured to remove, from the semi-equalization result obtained by the semi-equalization unit, a signal component corresponding to the current information symbol estimation obtained by the estimation subunit, and
  • the apparatus further comprises a parallel interference cancellation unit, configured to receive an information symbol estimate obtained by the information symbol estimation unit, and estimate the first information symbol included in the information symbol estimate to its own previous information symbol estimate. The interference is eliminated.
  • the information symbol estimation obtained after the sequential detection may be corrected, and the first information symbol included in the information symbol estimation is estimated to be its own previous information symbol estimation.
  • the interference is eliminated to achieve parallel interference cancellation, thereby further reducing the bit error rate of the information symbol estimation and improving the detection performance of the receiving system.
  • FIG. 1 is a flowchart of a method according to Embodiment 1 of the present invention based on an MMSE-BLE algorithm.
  • FIG. 2 is a specific flowchart of the current information symbol estimation given in the first embodiment of the present invention for the next information symbol detection.
  • FIG. 3 is a detailed structural diagram of an interference cancellation apparatus according to Embodiment 1 of the present invention.
  • Embodiment 4 is a flow chart of a method according to Embodiment 2 of the present invention based on a zero-forcing algorithm.
  • FIG. 5 is a specific flowchart of the current information symbol estimation given in the second embodiment of the present invention for the next information symbol detection.
  • FIG. 6 is a specific flowchart of the third parallel interference cancellation according to the embodiment of the present invention based on the MMSE-BLE algorithm and the zero-forcing algorithm.
  • FIG. 7 is a detailed structural diagram of an interference cancellation apparatus according to Embodiment 3 of the present invention. Mode for carrying out the invention
  • the basic idea of the embodiment of the present invention is: performing Cholesky decomposition on a specified matrix in an information symbol vector that needs to be sequentially detected, obtaining an upper triangular matrix and a semi-equalization result; and sequentially detecting information symbols in the information symbol vector according to the semi-equalization result, The information symbol is estimated and the resulting information symbol estimates are used for the detection of subsequent information symbols.
  • the signal is detected by the MMSE-BLE algorithm as:
  • ⁇ represents the autocorrelation matrix of the information symbol
  • ⁇ represents the autocorrelation matrix of the noise signal
  • m is the index of the information symbol estimate.
  • each time after the detection is given a ⁇ the signal component is removed from the received data, that is, Y— y_ m h m
  • H to eliminate m corresponding channel impulse system matrix of the response, to eliminate the information symbol vector after the signal components corresponding to m, is the autocorrelation matrix, the above variables to the equation (4) to obtain formula (6) , that is, the calculation method of information symbol estimation after sequential interference cancellation:
  • ⁇ ( ⁇ ) represents a quantization process, that is, a hard decision operation.
  • Embodiment 1 is a diagrammatic representation of Embodiment 1:
  • FIG. 1 is a flowchart of a method according to Embodiment 1 of the present invention based on an MMSE-BLE algorithm. As shown in Figure 1, the method includes:
  • Step 101 Perform Cholesky decomposition according to the system matrix ⁇ , the autocorrelation matrix of the information symbol, and the autocorrelation matrix R mich of the noise signal to obtain an upper triangular matrix.
  • the so-called Cholesky decomposition is to decompose the specified matrix into the product of a certain upper triangular matrix and the conjugate transposed matrix of the upper triangular matrix.
  • the specified matrix is an autocorrelation matrix noise signal including the system matrix H and information symbols.
  • the matrix of the autocorrelation matrix ⁇ is M H H R ; 1 H + R- 1 , and the obtained upper triangular matrix is denoted as R, then
  • Step 102 ⁇ according to the upper triangular matrix R, the system matrix and the noise autocorrelation matrix R, obtain the semi-equalization result ⁇
  • the formula ⁇ ' ⁇ 1 is used. Perform matching filtering on the received data vector y to obtain the intermediate vector y' Mxl , and then obtain the semi-equilibrium result by the following equations.
  • the semi-equalized results can be obtained by solving the above equations.
  • Step 103 sequentially detect information symbols in the information symbol vector ⁇ x M XM-I . . . , give the detected information symbols and information symbol estimates, and use the information symbol estimates for subsequent information symbol detection. . In this step, using the equations to detect the letter
  • the symbol vector which in turn obtains an information symbol estimate, where v Mxl is equivalent to noise and its nature is white noise.
  • the specific processing flow of the information symbol estimation obtained by solving the above equations for information symbol detection is as shown in FIG. 2, and includes:
  • Step 103b detecting the current information symbol.
  • the element, i is the index of the currently detected information symbol.
  • the information symbol index, ⁇ ( ⁇ ) is a quantization process.
  • step 103d a semi-equalization result obtained by eliminating the signal component corresponding to the information symbol estimation is obtained.
  • Step 103e determining whether the currently detected information symbol is the first information symbol in the information symbol vector, and if yes, ending the signal detection process; otherwise, setting the previous information symbol in the information symbol vector to the current information symbol and returning to the step 103b.
  • step 103 the operation in step 103c completes the process of sequential interference cancellation in equation (5), and then returns the interference-eliminated semi-equalization result obtained in step 103c to step 103b again, that is, the information symbol is made.
  • the value is equivalent to the solution result of equation (6).
  • Fig. 3 is a detailed structural diagram of the interference canceling device. As shown in FIG. 3, the apparatus includes: a decomposition unit, a semi-equalization unit, and an information symbol estimation unit.
  • the decomposing unit performs Cholesky decomposition on the specified matrix in the information symbol vector that needs to be sequentially detected, and obtains an upper triangular matrix, which is supplied to the semi-equalization unit.
  • the semi-equalization unit obtains a semi-equalization result according to the system matrix, the autocorrelation matrix of the noise signal, and the upper triangular matrix provided by the decomposition unit, and provides the information to the information symbol estimating unit.
  • the information symbol estimating unit sequentially detects the information symbols in the information symbol vector according to the obtained semi-equalization result, gives the detected current information symbol and the current information symbol estimation, and uses the given current information symbol estimation for the next one. Detection of information symbols. Specifically, the current information symbol estimation is used for the next information symbol detection as shown in FIG. 2. Specifically, the information symbol estimating unit may include an estimation subunit and an interference cancellation subunit.
  • the estimation subunit is configured to detect the current information symbol according to the semi-equilibrium result after the interference cancellation sub-unit performs interference cancellation, and obtain the current information symbol estimate and send the interference to the interference cancellation sub-unit.
  • An interference cancellation sub-unit configured to remove, from the semi-equalization result obtained by the semi-equalization unit, a signal component corresponding to a current information symbol estimation obtained by the estimation sub-unit, and as seen by the foregoing technical solution,
  • the method is applied to the MMSE-BLE algorithm for signal detection, when an information symbol estimation is detected, the signal component corresponding to the information symbol estimation is eliminated in the semi-equalization result, and then the half of the signal component is eliminated.
  • the equalization results are used for subsequent testing.
  • the obtained information symbol estimation eliminates the interference of the signal component corresponding to the previous detection result, thereby realizing the sequential interference cancellation, and the algorithm complexity and the original Some MMSE-BLE algorithms based on Cholesky decomposition are the same, but the error rate of information symbol estimation is reduced, which can effectively improve the detection performance of the receiving system.
  • the signal is detected by a zero-forcing algorithm:
  • ⁇ represents the autocorrelation matrix of the noise signal and m is the index of the information symbol estimate.
  • ⁇ represents the autocorrelation matrix of the noise signal and m is the index of the information symbol estimate.
  • H is the system matrix after eliminating the channel impulse response corresponding to ⁇ , in order to eliminate the information symbol vector after the signal component corresponding to m , the above variable is substituted into the formula (4) 'Getting expression
  • ⁇ ( ⁇ ) represents a quantization process, that is, a hard decision operation.
  • Embodiment 2 is a diagrammatic representation of Embodiment 1:
  • FIG. 4 is a flow chart of a method according to Embodiment 2 of the present invention based on a zero-forcing algorithm. As shown in Figure 4, The method includes:
  • Step 10 Perform Cholesky decomposition according to the system matrix H and the autocorrelation matrix R wh of the noise signal to obtain an upper triangular matrix.
  • the so-called Cholesky decomposition is to decompose the specified matrix into the product of a certain upper triangular matrix and the conjugate transposed matrix of the upper triangular matrix.
  • the obtained upper triangular matrix is denoted as R, then there is
  • Step 102' according to the upper triangular matrix! ⁇ , the system matrix and the noise autocorrelation matrix R, get the semi-equilibrium result.
  • the formula ⁇ ' ⁇ 1 is used.
  • the semi-equalized results can be obtained by solving the above equations.
  • ⁇ , ⁇ ,- ⁇ 1 1 is:
  • Step 103' sequentially detecting the information symbol of the information symbol vector ⁇ x M XM-I ?? xj ⁇ , giving the detected information symbol and the information symbol estimate, and estimating the information symbol for the subsequent information symbol Detection.
  • this step using the equations to detect the letter
  • Step 103b' detecting the current information symbol.
  • the information symbol index, ⁇ ( ⁇ ) is a quantization process.
  • step 103d' the semi-equalization result obtained by eliminating the signal component corresponding to the information symbol estimation is obtained to eliminate the colorization noise.
  • Step 103e' determining whether the currently detected information symbol is the first information symbol in the information symbol vector, and if so, ending the signal detection process; otherwise, setting the previous information symbol in the information symbol vector to the current information symbol and returning Step 103b'.
  • step 103' the operation in step 103c' completes the process of sequential interference cancellation in equation (5)', and then returns the interference-eliminated semi-equalization result obtained in step 103c' to step 103b'. That is, the value of the information symbol is equivalent to the solution result of the equation (6)'.
  • the remaining noise component is still white noise, thereby overcoming the shortcoming that the zero-forcing algorithm will color the noise.
  • the obtained information symbol estimation eliminates the interference of the signal component corresponding to the previous detection result, so that the remaining noise component satisfies the condition of white noise, no coloring noise occurs, thereby implementing sequential interference cancellation, and the algorithm thereof
  • the complexity is the same as the original zero-forcing algorithm based on Cholesky decomposition, but it reduces the bit error rate of information symbol estimation and can effectively improve the detection performance of the receiving system.
  • the method in the first embodiment and the second embodiment of the present invention can implement sequential interference cancellation, and at the same time,
  • the embodiment of the invention can further increase the step of parallel interference cancellation, thereby further improving the detection performance of the system.
  • the specific implementation is as shown in the third embodiment.
  • Embodiment 3 is a diagrammatic representation of Embodiment 3
  • the operation in the first embodiment or the second embodiment is performed first, and finally all the information symbol estimates are obtained. Then, the parallel interference cancellation processing is further increased.
  • the specific processing flow is as shown in FIG. 6, and includes:
  • Step 301 Set the second information symbol to be estimated as the current information symbol estimate.
  • Step 302 correcting the current information symbol estimation.
  • the i-th column vector is the first element in 1 ⁇
  • i is the index of the current information symbol estimation
  • ⁇ is the semi-equalization result before the signal component is eliminated
  • ⁇ ( ⁇ ) is the quantization process.
  • the process of the third embodiment of the present invention is completed, and the correction of the information symbol estimation is completed.
  • the interference of the first information symbol included in the information symbol estimation to the estimation of the previous information symbol of its own is eliminated, that is, the parallel interference cancellation is completed, the error rate of the information symbol estimation is further reduced, and the receiving system is improved. Detection performance.
  • FIG. 7 is a detailed structural diagram of the device.
  • the apparatus includes: a decomposition unit, a semi-equalization unit, an information symbol estimation unit, and a parallel interference cancellation unit.
  • the device adds a parallel interference cancellation unit, which can further eliminate interference in parallel, thereby further reducing the error rate of information symbol estimation and improving the detection performance of the receiving system.
  • the decomposing unit performs Cholesky decomposition on the specified matrix in the information symbol vector that needs to be sequentially detected, and obtains an upper triangular matrix, which is supplied to the semi-equalization unit.
  • the semi-equalization unit obtains a semi-equalization result according to the system matrix, the autocorrelation matrix of the noise signal, and the upper triangular matrix provided by the decomposition unit, and provides the information symbol estimating unit.
  • the information symbol estimating unit sequentially detects the information symbols in the information symbol vector according to the obtained semi-equalization result, gives the detected current information symbol and the current information symbol estimation, and uses the given current information symbol estimation for the next one.
  • the detection of the information symbols sends all the obtained information symbol estimates to the parallel interference cancellation unit.
  • the parallel interference cancellation unit is configured to receive the information symbol estimate obtained by the information symbol estimating unit, and estimate the interference of the first information symbol included in the information symbol estimation to the interference of its own previous information symbol.
  • the method in the embodiment of the present invention can fully utilize the obtained information symbol estimation in the detection of subsequent information symbols, thereby implementing sequential interference cancellation on the basis of not increasing the complexity of the algorithm, and reducing The error rate of the information symbol estimation; in addition, if the processing capability allows, it may further include parallel interference cancellation.
  • the operation further eliminates the ISI existing in the information symbol estimation, and effectively improves the detection performance of the receiving system.
  • the above is a specific implementation manner of the embodiment of the present invention by taking signal detection in the MIMO communication system as an example.
  • the joint detection and the application method are the same, and the same effect can be obtained, and the receiving system can be improved.
  • the detection performance, improve the balance effect, will not repeat them here.

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Noise Elimination (AREA)

Abstract

La présente invention concerne un procédé de suppression d'interférence basé sur une décomposition de Cholesky. Ce procédé consiste à effectuer une décomposition de Cholesky sur la matrice indiquée dans un vecteur de symboles d'information à détecter de manière séquentielle, de manière à obtenir une matrice triangulaire supérieure (101), à obtenir un résultat semi-égalisé sur la base de la matrice du système, de la matrice d'autocorrélation du signal de bruit et de la matrice triangulaire supérieure (102), à détecter de manière séquentielle les symboles d'information dans le vecteur de symboles d'information, de manière à obtenir une évaluation de symboles d'information, puis à utiliser cette évaluation de symboles d'information dans l'étape de détection suivante (103).
PCT/CN2007/070346 2006-08-23 2007-07-24 Procédé et appareil de suppression d'interférence sur la base d'une décomposition de cholesky WO2008025268A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN200610111546.X 2006-08-23
CN200610111546XA CN1913390B (zh) 2006-08-23 2006-08-23 一种基于Cholesky分解实现干扰消除的方法

Publications (1)

Publication Number Publication Date
WO2008025268A1 true WO2008025268A1 (fr) 2008-03-06

Family

ID=37722186

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2007/070346 WO2008025268A1 (fr) 2006-08-23 2007-07-24 Procédé et appareil de suppression d'interférence sur la base d'une décomposition de cholesky

Country Status (2)

Country Link
CN (1) CN1913390B (fr)
WO (1) WO2008025268A1 (fr)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1913390B (zh) * 2006-08-23 2011-04-06 普天信息技术研究院 一种基于Cholesky分解实现干扰消除的方法
CN101068116B (zh) * 2007-06-15 2011-07-27 北京邮电大学 一种多用户多天线码分多址系统的检测方法
CN102594737B (zh) * 2011-01-05 2015-04-01 中兴通讯股份有限公司 一种邻区干扰检测方法及系统
CN102129420B (zh) * 2011-03-07 2013-03-20 哈尔滨工业大学 基于Cholesky分解解决最小二乘问题的FPGA实现装置
US8731028B2 (en) * 2011-12-02 2014-05-20 Futurewei Technologies, Inc. Method and apparatus for modulation and coding scheme adaption in a MIMO system
CN104348518B (zh) * 2013-07-26 2018-07-31 马维尔国际有限公司 信号的联合检测方法和装置

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1307414A (zh) * 1999-11-08 2001-08-08 三菱电机株式会社 联合探测方法
CN1457568A (zh) * 2001-02-07 2003-11-19 摩托罗拉公司 使用有限脉冲响应矩阵滤波器的多用户检测
WO2004073197A1 (fr) * 2003-02-11 2004-08-26 University Of Bristol Procede et appareil de detection de signaux
CN1913390A (zh) * 2006-08-23 2007-02-14 普天信息技术研究院 一种基于Cholesky分解实现干扰消除的方法

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU2005203278A1 (en) * 2004-08-12 2006-03-02 Nec Australia Pty Ltd Method for calculating filter coefficients for an equaliser in a communication receiver
CN100399717C (zh) * 2005-11-25 2008-07-02 重庆重邮信科股份有限公司 一种联合检测中双重递归的均衡实现方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1307414A (zh) * 1999-11-08 2001-08-08 三菱电机株式会社 联合探测方法
CN1457568A (zh) * 2001-02-07 2003-11-19 摩托罗拉公司 使用有限脉冲响应矩阵滤波器的多用户检测
WO2004073197A1 (fr) * 2003-02-11 2004-08-26 University Of Bristol Procede et appareil de detection de signaux
CN1913390A (zh) * 2006-08-23 2007-02-14 普天信息技术研究院 一种基于Cholesky分解实现干扰消除的方法

Also Published As

Publication number Publication date
CN1913390A (zh) 2007-02-14
CN1913390B (zh) 2011-04-06

Similar Documents

Publication Publication Date Title
KR100874507B1 (ko) 슬롯 코드분할 다중접속 시스템의 멀티 셀 결합 검출방법
JP2008532354A (ja) 向上されたブロック等化を提供する無線通信装置及び関連する方法
WO2007095697A1 (fr) Procédé et système de communication dans un réseau sans fil
US7944903B2 (en) Multi-cell joint-detection method in time-slotted CDMA system
JP2008530906A (ja) 過去、現在及び／又は将来の自己相関マトリクスの予測値に基づいてブロック等化を実行する無線通信装置及び関連する方法
WO2008025268A1 (fr) Procédé et appareil de suppression d'interférence sur la base d'une décomposition de cholesky
JP2003512759A (ja) Ｃｄｍａ信号のマルチユーザ検出のための受信機
CN100496031C (zh) 接收机、发送机和无线通信系统及信道估计方法
KR101220717B1 (ko) 채널 이퀄라이제이션을 위한 방법 및 시스템
WO2012059058A1 (fr) Procédé et dispositif de suppression des interférences dans un système de communication mobile
WO2007090868A1 (fr) Procédé et dispositif permettant de déterminer la réponse d'un canal
CN110855593B (zh) 一种单码循环移位多址接入系统的下行链路通信方法
WO2007135400A1 (fr) Affinage d'une estimation de canal doté d'une batterie de filtres
CN101170366B (zh) 基于最小均方差线性块均衡实现信号联合检测的方法
EP1714449B1 (fr) Procede et appareil pour effectuer une estimation de canaux pour un systeme de communication
JP4213747B2 (ja) 複雑度を低減したスライディングウィンドウベースの等化器
US7412000B1 (en) Maximum likelihood block decision feedback estimation for CCK demodulation apparatus and method
WO2004079927A2 (fr) Egaliseur base sur une fenetre glissante a complexite reduite
JPH08509343A (ja) 非同期ｃｄｍａチャネル用の相関解除受信機
WO2000077942A1 (fr) Detection commune de complexite mettant en oeuvre peu de calculs destinee a des systemes mixtes td-cdma
WO2007095775A1 (fr) Procédé et système d'évaluation de canal au moyen d'une antenne réseau
JP4675255B2 (ja) マルチユーザー検出装置
JP2008521308A (ja) 無線受信機における干渉抑圧
CN101036318A (zh) 用于具有天线阵列的无线通信系统的联合检测方法及基站
TWI463809B (zh) 通訊系統及執行通訊系統中聯合偵測之方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 07764272

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

NENP Non-entry into the national phase

Ref country code: RU

122 Ep: pct application non-entry in european phase

Ref document number: 07764272

Country of ref document: EP

Kind code of ref document: A1

点击 这是indexloc提供的php浏览器服务，不要输入任何密码和下载