EP0963642A1 - Estimation de la reponse impulsionnelle d'un canal au moyen de la decomposition d'une valeur singuliere - Google Patents

Estimation de la reponse impulsionnelle d'un canal au moyen de la decomposition d'une valeur singuliere

Info

Publication number
EP0963642A1
EP0963642A1 EP98904204A EP98904204A EP0963642A1 EP 0963642 A1 EP0963642 A1 EP 0963642A1 EP 98904204 A EP98904204 A EP 98904204A EP 98904204 A EP98904204 A EP 98904204A EP 0963642 A1 EP0963642 A1 EP 0963642A1
Authority
EP
European Patent Office
Prior art keywords
cir
matrix
eigenvalues
present
diagonal matrix
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
EP98904204A
Other languages
German (de)
English (en)
Inventor
Peter John White
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nokia Oyj
Original Assignee
Nokia Telecommunications Oy
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 Nokia Telecommunications Oy filed Critical Nokia Telecommunications Oy
Publication of EP0963642A1 publication Critical patent/EP0963642A1/fr
Withdrawn legal-status Critical Current

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
    • H04L25/0202—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
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0248—Eigen-space methods

Definitions

  • the present invention relates to the estimating of CIR (channel impulse response) and SINR (signal-to-i ⁇ terference-plus-noise ratio) in CDMA receivers.
  • the present invention is directed to a method of determining the channel impulse response (CIR) of a communication system, such as the CIR of radio channels of a digital mobile radio network (GSM network).
  • the present invention relates to determining the CIR based on the reception of a known training sequence.
  • the present invention also has application in interference cancellation and use in CDMA receivers.
  • Synchronisation bursts (S3) are a useful portion of the signal.
  • the SB are transmitted on at least one channel from every base station, and they are transmitted in a regular pattern. Decoding of the GSM protocols is not necessary. Both the data in the SB and the pattern with which they occur is fixed and substantially identical for all base stations.
  • the advantage of using SB for determining the CIR is that they represent a relatively long, noise-like predetermined transmitted signal. Typically, 64 bits are transmitted over a period of 237 ⁇ sec. The determination of the CIR thus requires sufficient synchronisation to the bursts in the received signal to enable the extraction of the SB which is then processed to determine the CIR.
  • the processing is done by using estimation techniques.
  • a known training sequence is transmitted S (t), and this is corrupted by a communications channel producing the received signal S ra (t).
  • the problem in estimating the CIR is to determine tap-weights ⁇ of a FIR filter (which is used to approximate the CIR), so that the known S tx (t) after passing through the filter is as close as possible to the received signal S, x (t).
  • the tap weights ⁇ i are determined by simple correlation as
  • This algorithm relies on the noise-like properties of the transmitted signal whereby its autocorrelation function should have low time sidelobes.
  • the sidelobe performance of this algorithm has been found to be limited due to the correlation properties of the "clean" part of the training sequence and the fact that only partial correlations are performed for later weights.
  • US 5,473,632 produces a matrix.
  • the problem really relates to what is done to the matrix to calculate the CIR.
  • a "factor ⁇ " is added to the matrix before the matrix is inverted, and then after the
  • factor ⁇ is added, the matrix is inverted. In practice it has been found that the inversion of the matrix causes problems in calculating the CIR.
  • the present invention seeks to alleviate the problems experienced in determining CIR and SINR with prior art techniques.
  • the present invention stems from the realisation that the problems associated with the prior art can be alleviated by initially transforming the matrix obtained by virtue of network analysis into a 'diagonal matrix' and then inverting the resultant diagonal matrix. Thus there is no "factor ⁇ " added.
  • An advantage of using a diagonal matrix is that it is possible to remove or ignore some eigenvalues (such as some" of the small problematic eigenvalues) and in this way avoid the magnified errors and noise of US 5,473,632 when the matrix is inverted.
  • Another advantage of using a diagonal matrix is attributable to the nature of a diagonal matrix and that is, the matrix can be inverted by inverting only the diagonal elements. This exposes the difficulty caused by small eigenvalues - they lead to very large elements in the inverse.
  • the present application discloses a still further invention which is directed to alleviating the problem of the production of large side lobes.
  • This further invention is considered an improvement on the invention noted above and is based on, not discarding small eigenvalues (which is the approach noted above) but instead to multiply the reciprocal of the eigenvalue in the inverse matrix by a decreasing number until the sidelobes are removed or so small that they have little effect.
  • S/N OdB
  • Figure 2 illustrates CIR estimated using the algorithm disclosed in US
  • Figure 3 illustrates CIR estimated using SVD and including 10 largest eigenvalues
  • Figure 4 illustrates CIR estimated using SVD and including 16 largest eigenvalues
  • Figure 5 illustrates CIR estimated using SVD and including 25 largest eigenvalues
  • Figure 6 illustrates CIR estimated using SVD and including 36 largest eigenvalues
  • n 2 25 S/N - OdB
  • Figure 10 illustrates CIR estimated using SVD and using ramping function with n-
  • One method of estimating the tap weights is to determine the weights which predict a received signal most closely matching the measured signal.
  • the desired FIR tap weights (ot ⁇ ) are estimated by requiring that the cumulative square error between the measured received signal and the estimate of the received signal (i.e. the known transmitted signal passed through the FIR approximating the channel) is minimised, i.e. minimise
  • T is the MxN matrix of conjugated delayed signals t jj -T j j O ⁇ i ⁇ M O ⁇ j ⁇ N (2 , 6)
  • US 5,473,632 discloses an algorithm which stabilises the inversion of the matrix and produces results reasonably resilient to noise.
  • US 5,473,632 estimates the CIR by c - ((A + e!)-rT)R (2.9) where I is the identity matrix and ⁇ is a constant (they call a noise term). This equation equates to the equation disclosed in US 5,473,632 at col. 6, line 44. The results of using this algorithm follow:
  • the matrix A (which is positive definite) may be represented by where U and V are orthogonal and S is diagonal. In fact the diagonal elements of S are the eigenvalues (all positive) of A and these are arranged in decreasing order: s 1>1 > s 2 , 2 .>s n , ⁇ (2.1 1 ) If the matrix is singular, some of these are zero. The inverse of A is then
  • A-1 VS-1U' (2.12) where S- 1 is formed by inverting the (diagonal) elements of S. The effects of a poorly conditioned matrix are clear here, the (almost zero) eigenvalues are inverted and produce an extremely large contribution to the inverse. These amplify the noise.
  • Figures 16 and 17 illustrate the results for some more complex CIR's. It has also been found that the present embodiment has the ability to enable the algorithm to discriminate between peak, and Figure 18 shows close peaks split with time separations greater than about 5 ⁇ s.
  • Matrix inversion as described above is also required when estimating the channel impulse response vector h.
  • ⁇ h ⁇ (2.14)
  • ⁇ is the crosscorrelation matrix between locally generated signals
  • ⁇ is the crosscorrelation matrix between locally generated signals and the received signal.
  • the principles and method as described above are equally applied in this situation.
  • CDMA is applied usually using optimum combining of signals received from multiple sensors (antenna array). Optimum combining maximises the signal-to-interference-plus-noise ratio (SINR).
  • w the weight vector for antenna elements
  • ⁇ a constant
  • R the received interference-plus-noise correlation matrix
  • u d * is the conjugate of the desired signal vector.
  • the preferred implementation of the inventions disclosed is to generate a CIR using the matrix multiplication as specified in equation (2.8) and to then use SVD to determine the inverse of the matrix A.

Landscapes

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

Abstract

Cette invention concerne l'estimation de la réponse impulsionnelle d'un canal (RIC) et du rapport signal/brouillage plus bruit (RSPBPB) dans des récepteurs à accès multiple par code de répartition (AMCR). Plus précisement il s'agit d'un procédé permettant de déterminer la réponse impulsionnelle d'un canal (RIC) d'un système de télécommunications, telle que la RIC de canaux radioélectriques d'un réseau numérique de radiotéléphonie mobile (réseau GSM). Cette invention concerne plus particulièrement la détermination de la RIC fondée sur la réception d'une séquence d'apprentissage connue. Elle s'applique également à l'annulation des interférences et à des récepteurs AMCR. L'invention se fonde sur l'idée que les problèmesassociés à l'art antérieur peuvent être partiellement résolus si on transforme au départ la matrice obtenue par l'analyse du réseau en une 'matrice diagonale' et qu'on inverse ensuite la matrice diagonale résultante. Une autre invention consiste à multiplier la réciproque de la valeur propre de l'inverse par un nombre décroissant jusqu'a ce que les lobes latéraux soient éliminés ou si petits que leur effet est faible.
EP98904204A 1997-02-25 1998-02-23 Estimation de la reponse impulsionnelle d'un canal au moyen de la decomposition d'une valeur singuliere Withdrawn EP0963642A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
AU14889/97A AU688228B1 (en) 1997-02-25 1997-02-25 A system and method of estimating CIR
AU1488997 1997-02-25
PCT/FI1998/000159 WO1998038772A1 (fr) 1997-02-25 1998-02-23 Estimation de la reponse impulsionnelle d'un canal au moyen de la decomposition d'une valeur singuliere

Publications (1)

Publication Number Publication Date
EP0963642A1 true EP0963642A1 (fr) 1999-12-15

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
EP98904204A Withdrawn EP0963642A1 (fr) 1997-02-25 1998-02-23 Estimation de la reponse impulsionnelle d'un canal au moyen de la decomposition d'une valeur singuliere

Country Status (6)

Country Link
EP (1) EP0963642A1 (fr)
JP (1) JP2001513954A (fr)
CN (1) CN1248370A (fr)
AU (1) AU688228B1 (fr)
NO (1) NO994072D0 (fr)
WO (1) WO1998038772A1 (fr)

Cited By (1)

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CN100539557C (zh) * 2004-10-18 2009-09-09 威盛电子股份有限公司 全球移动通信系统预测信道脉冲响应的装置及方法

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IT1314344B1 (it) * 1999-12-30 2002-12-09 Telit Mobile Terminals Spa Metodo ricevitore e sistema di trasmissione wcdma-utra/fdd
JP3805205B2 (ja) * 2000-04-06 2006-08-02 株式会社エヌ・ティ・ティ・ドコモ Ｃｄｍａセルラ方式における通信品質測定方法およびその装置
GB2365715B (en) * 2000-05-15 2004-04-28 Univ Bristol Circuit
KR100651962B1 (ko) 2000-09-02 2006-11-30 엘지전자 주식회사 적응 안테나 어레이 시스템에서의 신호처리 방법
GB2370469B (en) * 2000-09-07 2004-10-27 Nec Corp Improvements in CDMA receivers
US7035353B2 (en) * 2001-10-24 2006-04-25 Zenith Electronics Corporation Channel estimation method blending correlation and least-squares based approaches
US20040081131A1 (en) * 2002-10-25 2004-04-29 Walton Jay Rod OFDM communication system with multiple OFDM symbol sizes
CN1300962C (zh) * 2002-12-31 2007-02-14 上海贝尔阿尔卡特股份有限公司 正交频分复用系统中均衡快衰落信道的方法及装置
CN101218517B (zh) * 2005-07-13 2012-05-30 埃克森美孚上游研究公司 预测非唯一解集合中的最佳和最坏解的方法
CN104950326B (zh) * 2015-03-04 2016-09-28 中石化石油工程技术服务有限公司 基于目的层频谱的可控震源非线性扫描信号的设计方法
CN114018250B (zh) * 2021-10-18 2024-05-03 杭州鸿泉物联网技术股份有限公司 惯性导航方法、电子设备、存储介质和计算机程序产品

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US4945502A (en) * 1988-12-27 1990-07-31 Eastman Kodak Company Digital image sharpening method using SVD block transform
US5209237A (en) * 1990-04-12 1993-05-11 Felix Rosenthal Method and apparatus for detecting a signal from a noisy environment and fetal heartbeat obtaining method
DE4135953A1 (de) * 1991-10-31 1993-05-06 Rohde & Schwarz Gmbh & Co Kg, 8000 Muenchen, De Verfahren zum bestimmen der komplexen impulsantwort eines funkkanals

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN100539557C (zh) * 2004-10-18 2009-09-09 威盛电子股份有限公司 全球移动通信系统预测信道脉冲响应的装置及方法

Also Published As

Publication number Publication date
AU688228B1 (en) 1998-03-05
WO1998038772A1 (fr) 1998-09-03
CN1248370A (zh) 2000-03-22
NO994072L (no) 1999-08-24
JP2001513954A (ja) 2001-09-04
NO994072D0 (no) 1999-08-24

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