EP1712012A1 - Procede et appareil d'estimation de variance de bruit, utilisables dans des systemes de communication sans fil - Google Patents

Procede et appareil d'estimation de variance de bruit, utilisables dans des systemes de communication sans fil

Info

Publication number
EP1712012A1
EP1712012A1 EP04801439A EP04801439A EP1712012A1 EP 1712012 A1 EP1712012 A1 EP 1712012A1 EP 04801439 A EP04801439 A EP 04801439A EP 04801439 A EP04801439 A EP 04801439A EP 1712012 A1 EP1712012 A1 EP 1712012A1
Authority
EP
European Patent Office
Prior art keywords
signal vector
noise
vector
impulse response
training sequence
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Withdrawn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
EP04801439A
Other languages
German (de)
English (en)
Inventor
Yan c/o Philips Electronics China LI
Luzbou c/o Philips Electronics China XU
Yucheng c/o Philips Electronics China LI
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.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips Electronics NV
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 Koninklijke Philips Electronics NV filed Critical Koninklijke Philips Electronics NV
Publication of EP1712012A1 publication Critical patent/EP1712012A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • 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
    • H04B1/7097—Interference-related aspects
    • H04B1/711—Interference-related aspects the interference being multi-path interference
    • 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
    • H04B1/7097—Interference-related aspects
    • H04B1/7103—Interference-related aspects the interference being multiple access interference
    • H04B1/7105—Joint detection techniques, e.g. linear detectors
    • H04B1/71057—Joint detection techniques, e.g. linear detectors using maximum-likelihood sequence estimation [MLSE]
    • 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
    • H04B1/06—Receivers
    • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
    • 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
    • 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
    • H04B1/7097—Interference-related aspects
    • H04B1/711—Interference-related aspects the interference being multi-path interference
    • H04B1/7115—Constructive combining of multi-path signals, i.e. RAKE receivers
    • 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

Definitions

  • the present invention relates generally to a method and apparatus of noise variance estimation for use in wireless communication systems, a nd more particularly, to a method and apparatus of noise variance estimation by exploiting the training sequence.
  • CDMA Code Division Multiple Access
  • FDMA Frequency Di vision Multiple Access
  • TDMA Time Division Multiple Access
  • different UEs user equipments
  • signals spread by different UEs with different spreading codes ca n be transferred on the same frequency band.
  • a CDMA downlink transmission model is put forward in the paper entitled “Data Detection Algorithms Specially Designed For The Downlink of CDMA Mobile Radio Systems", VTC, 1997, by A. Klein, as shown in Fig.1.
  • Equation (1) indicates that the received signal vector e d ( ⁇ ) contains UEk's desired signal vector d°° , as well as signal vectors sent to other UEs by the base station and the noise vector.
  • noise estimation methods in which noise variance is computed by convolving the training sequence. These noise estimation methods can meet the precision requirement of 2G wireless communication systems. But in 3G wireless communication systems, more accurate noise variance is needed for signal reception, for example, the key technologies of multiuser detection and turbo -code both have high requirement for accurate noise variance. Current noise estimation methods can 't satisfy the precision requirement for noise variance of 3G wireless communication systems.
  • An object of the present invention is to provide a method and apparatus of noise variance estimation for use in wireless communication systems, in which the training sequence is exploited to compute noise variance to obtain more accurate noise variance.
  • a method of noise variance estimation is proposed in the present invention for use in wireless communication systems, comprising steps of: receiving a signal vector containing training sequence and noise vector transmitted via at least one propagation path f rom the base station; estimating, according to the signal vector, the channel impulse response of each propagation path to construct a channel impulse response matrix; calculating the noise variance of the signal vector according to the channel impulse response matrix and the signal vector if the channel impulse response remains primarily unchanged during the special time duration of the training sequence.
  • Fig.1 illustrates conventional CDMA downlink transmission model
  • Fig.2 is a flow chart illustrating the noise variance estimation method in the present invention
  • Fig.3 is a block diagram illustrating the UE equipped with the noise variance estimation apparatus in an embodiment of the present invention
  • Fig.4 is a block diagram illustrating the noise variance estimation apparatus in an embodiment of the present invention.
  • TD-SCDMA Detailed Description of the Invention
  • the base station transmits signal vector to each UE in corresponding timeslot.
  • the signal vector sent to each UE by the base station in corresponding timeslot is composed of the training sequence and the s pread user signal.
  • the base station first combines the signal vectors to be transmitted to each UE into a combined signal vector, and then transmits this combined signal vector in the timeslot to each UE.
  • Said combined signal vector is also composed of user signal and training sequence, wherein the user signal in the combined signal vector is obtained by combining the spread user signal in the signal vector to be transmitted to each UE, and the training sequence in the combined signal vector is obtained by combing the training sequence in the signal vector to be transmitted to each UE.
  • the training sequence allocated to each UE in a cell is obtained through performing different shift operation on the sam e basic training sequence, so the training sequence of the combined signal vector can be considered as the basic training sequence.
  • Each UE has acquired the basic training sequence used by its cell during cell search procedure, so the training sequence sent by the base station in the timeslot is known beforehand to each UE. Let's suppose that the training sequence included in the signal vector sent by the base station in a timeslot reaches a UE through at least one propagation path, the signal vector receiv ed by the UE in the timeslot is r, composed of said training sequence and noise vector n, and the known value of said training sequence is s.
  • H the CIR matrix constructed by the CIR of each propagation path between the UE and the base station.
  • the maximum likelihood estimated value s of the training sequence included in signal vector r can be expressed as fol lows: wherein superscript H represents complex conjugate transposition.
  • ⁇ 2 (n 'H n ' ) I trace ⁇ ( H ⁇ H ) - 1 ⁇ ( 7 )
  • ⁇ 2 (n 'H n ' ) I trace ⁇ ( H ⁇ H ) - 1 ⁇ ( 7 )
  • the UE receives a signal vector containing training sequence and noise vector in a timeslot transferred through at least one propagation path from the base station (step S10).
  • the UE estimates the CIR of each propagation path according to the received signal vector, and constructs a CIR matrix H by using the estimated CIR of each propagation path (step S20).
  • the UE estimates the maximum likelihood es timated value s of the training sequence included in said signal vector using equation (3), according to said signal vector and said CIR matrix (step S30).
  • the UE computes the estimated value n ' of the noise vector contained in said signal vector by using equation (4), according to the MLE (maximum likelihood estimate) value s of the training sequence included in said signal vector and the known value of the training sequence (step S40).
  • the known value of the training sequence contained in said signal vector is acquired by the UE in cell search procedure.
  • the UE computes the noise variance ⁇ 2 of said signal vector by using equation (7), according to the estimated value n ' of the noise vector contained in said signal vector and said CIR matrix H (step S50).
  • the UE sums and averages the noise variance ⁇ 2 calculated from equation (7) in the timeslot and the noise variance ⁇ 2 calculated from equation (7) in each previous timeslot, and takes the mean of different ⁇ 2 as the noise variance ⁇ 2 of signal vector r in the timeslot (step S60).
  • Fig.3 is a block diagram illustrating the UE equipped with the proposed noise variance estimation apparatus.
  • cell searching means 40 acquires the basic training sequence s used by the cell where the UE is camping.
  • the antenna of the UE first sends the sign al vector Rx received in a timeslot to multiplier 10, and multiplier 10 multiplies the received signal vector Rx by the
  • ADC 30 converts the baseband signal vecto r outputted from multiplier 10 into digital baseband signal vector r.
  • cell searching means 40 synchronizes the digital baseband signal vector r outputted from ADC 30, and channel estimating means 50 computes the CIR of each propagation channel for the synchronized digital baseband signal vector r by using conventional channel estimation methods, and constructs CIR matrix with the computed CIR of each propagation path.
  • noise variance estimating means 60 computes the noise variance of the di gital baseband signal vector r according to the CIR matrix computed by channel estimating means 50, the digital baseband signal vector r outputted by ADC 30 and the basic training sequence s acquired by cell searching means 40.
  • data detecting mean s 70 acquires the desired user signal from the digital baseband signal vector r according to the noise variance computed by noise variance estimating means 60, by using conventional data detection methods, such as multiuser detection method, turbo -code decoding and etc.
  • Fig.4 is a block diagram illustrating noise variance estimating means 60. Referring to Fig.4, noise variance estimating means 60 comprises: equalizing means 601 , for estimating the MLE value s of the training sequence contained in said digital baseband signal vector r according to the

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)

Abstract

Procédé d'estimation de variance de bruit, destiné à être mis en oeuvre par un matériel utilisateur et comportant les étapes consistant à: recevoir un vecteur signal contenant une séquence d'apprentissage et un vecteur de bruit transmis via au moins un trajet de transmission; estimer la réponse impulsionnelle de voie de chaque trajet de transmission en vue d'élaborer une matrice de réponse impulsionnelle de voie en fonction du vecteur signal; et calculer la variance de bruit du vecteur signal en fonction de la matrice de réponse impulsionnelle de voie et du vecteur signal si ladite réponse impulsionnelle reste sensiblement inchangée au cours de la durée spécifique de la séquence d'apprentissage.
EP04801439A 2003-12-05 2004-12-02 Procede et appareil d'estimation de variance de bruit, utilisables dans des systemes de communication sans fil Withdrawn EP1712012A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CNA2003101197841A CN1625075A (zh) 2003-12-05 2003-12-05 一种用于无线通信体系的噪声方差估算方法及装置
PCT/IB2004/052631 WO2005055456A1 (fr) 2003-12-05 2004-12-02 Procede et appareil d'estimation de variance de bruit, utilisables dans des systemes de communication sans fil

Publications (1)

Publication Number Publication Date
EP1712012A1 true EP1712012A1 (fr) 2006-10-18

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Family Applications (1)

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EP04801439A Withdrawn EP1712012A1 (fr) 2003-12-05 2004-12-02 Procede et appareil d'estimation de variance de bruit, utilisables dans des systemes de communication sans fil

Country Status (5)

Country Link
EP (1) EP1712012A1 (fr)
JP (1) JP2007513564A (fr)
KR (1) KR20060123263A (fr)
CN (2) CN1625075A (fr)
WO (1) WO2005055456A1 (fr)

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GB0519051D0 (en) * 2005-09-19 2005-10-26 Nokia Corp Search algorithm
US8265209B2 (en) 2005-10-28 2012-09-11 Qualcomm Incorporated Method and apparatus for channel and noise estimation
CN101427506B (zh) 2006-04-17 2013-07-17 高通股份有限公司 用于无线通信的噪声估计
US7693231B2 (en) * 2006-05-15 2010-04-06 Qualcomm Incorporated System and method of calculating noise variance
GB0615292D0 (en) * 2006-08-01 2006-09-06 Ttp Communications Ltd Signal evaluation and adjustment
CN101174854B (zh) * 2007-12-06 2011-07-06 华为技术有限公司 噪声估计方法及装置
WO2009118700A1 (fr) * 2008-03-26 2009-10-01 Nxp B.V. Système et procédé d’estimation de variance du bruit à hautes performances sur la base d’échantillons finis en td-scdma
JP5206251B2 (ja) * 2008-09-05 2013-06-12 株式会社ニコン 利用対象推薦装置、利用対象推薦方法およびプログラム
KR101152808B1 (ko) * 2010-03-16 2012-06-12 서강대학교산학협력단 잡음 분산 추정 방법 및 이를 이용하는 수신기
CN114268352B (zh) * 2022-03-01 2022-05-20 四川创智联恒科技有限公司 一种nr上行控制信道格式1的检测方法
CN115560795B (zh) * 2022-12-02 2023-07-04 小米汽车科技有限公司 适用于充电设备的风道阻塞检测方法及装置

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ATE270482T1 (de) * 1998-07-21 2004-07-15 Nokia Corp Schätzung der kanalimpulsantwort mittels der streuung vom empfangenen signal
JP2003500897A (ja) * 1999-05-17 2003-01-07 ノキア コーポレイション Ｔｄｍａシステムにおけるノイズエネルギー推定方法
US6947502B2 (en) * 2002-04-16 2005-09-20 Taylor Matthew A Parameter estimator for a multiuser detection receiver

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Also Published As

Publication number Publication date
CN1625075A (zh) 2005-06-08
KR20060123263A (ko) 2006-12-01
WO2005055456A1 (fr) 2005-06-16
JP2007513564A (ja) 2007-05-24
CN1890891A (zh) 2007-01-03

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