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WO2003047193A1 - Egaliseur d'estimation sequentielle de vraisemblance maximale (mlse) destine a des signaux d'interference correles - Google Patents

Egaliseur d'estimation sequentielle de vraisemblance maximale (mlse) destine a des signaux d'interference correles Download PDF

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Publication number
WO2003047193A1
WO2003047193A1 PCT/IB2002/004935 IB0204935W WO03047193A1 WO 2003047193 A1 WO2003047193 A1 WO 2003047193A1 IB 0204935 W IB0204935 W IB 0204935W WO 03047193 A1 WO03047193 A1 WO 03047193A1
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WIPO (PCT)
Prior art keywords
interference
state
signal
coefficients
equalizer
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PCT/IB2002/004935
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English (en)
Inventor
Juergen Petersen
Thomas Wagner
Original Assignee
Koninklijke Philips Electronics N.V.
Philips Corporate Intellectual Property Gmbh
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 Koninklijke Philips Electronics N.V., Philips Corporate Intellectual Property Gmbh filed Critical Koninklijke Philips Electronics N.V.
Priority to AU2002347491A priority Critical patent/AU2002347491A1/en
Publication of WO2003047193A1 publication Critical patent/WO2003047193A1/fr

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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
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03248—Arrangements for operating in conjunction with other apparatus

Definitions

  • the invention relates to a method and a device for suppressing interference signals in the case of a receiver with state-based equalization for detection of digital data signals received in time steps.
  • additive interference signals may occur, the adjacent values of which can be correlated more or less strongly with one another.
  • common-channel interference and adjacent-channel interference in particular exhibit correlations by virtue of the filtering in the transmitter and receiver.
  • state-based equalizers For the demodulation or equalization of a received signal, which may be interfered with as a result of strong pulse distortions, state-based equalizers are frequently used.
  • the principle of state-based equalizers of this kind is described in, for example, the publication G. David Forney, Jr.: Maximum Likelihood Sequence Estimation of Digital Sequences in the Presence of Intersymbol interference, IEEE Transactions on Information Theory, vol. IT-18: p. 363-378,1972, in the publication M. Vedat Eyuboglu, Shahid U.H. Qureshi: Reduced-State Sequence Estimation with Set Partitioning and Decision Feedback, IEEE Trans. Comm., vol. 36, No. 1, Jan. 1988, and in the textbook J.
  • the state transitions of a state-based equalizer can be visualized in a so-called trellis diagram (see J. Huber and G.D. Forney).
  • the principle of signal reconstruction presupposes that an estimation of the channel pulse response can be undertaken. An estimation of this kind may take place, for example, by means of a training sequence.
  • the power density spectrum of the interference In order to design a decorrelation filter, the power density spectrum of the interference must be known. Determination of this power density spectrum is difficult, particularly in the case of TDMA (Time Division Multiple Access) systems, since the type of interference, for example in the known frequency jumping method, can change from time slot to time slot, as a result of which the interval of the interference evaluation is restricted to one time slot.
  • TDMA Time Division Multiple Access
  • the above object is achieved according to the invention by the features as claimed in claim 1 as regards the method, and by the features as claimed in claim 10 as regards the device.
  • Fig. 1 is a simplified block diagram of a transmission system in baseband, in which symbols have the following meanings: " : Transmitted data symbols a " : Estimated data symbols in the receiver r n : Received-signal values after the receiving filter h,: i-th coefficient of total channel pulse response p,: i-th coefficient of interference prediction L: Length of total channel pulse response in symbol periods
  • Fig. 2 is a trellis diagram of a state-based equalizer with eight states and one binary symbol alphabet.
  • Fig. 3 shows a trellis step of a state-based equalizer with eight states and a binary symbol alphabet, with:
  • S n State in time step n.
  • Fig. 4 shows a recursive processing of the state trellis in a state-based equalizer, with:
  • Fig. 5 is a functional diagram of a branch metrics calculation with interference prediction.
  • a data source 1 transmits data symbols a n via a modulator 2 and a transmission channel 3 to a receiver 4.
  • a received-signal value r n occurs in the receiver 4, downstream of a receiving filter 5. This value is processed in a state-based equalizer 6 with interference prediction.
  • the coefficients ho... of the total channel pulse response are estimated by a block 7, and then passed on to the state-based equalizer 6 and to a block 8.
  • the coefficients Pi ... are estimated from the received signal (for example the training sequence) for interference prediction and also passed on to equalizer 6.
  • the coefficients pi ... correspond to the coefficients of a predictor filter.
  • the data symbols a " estimated in equalizer 6 are fed to a data sink.
  • the transmitted data sequence contains a training sequence which renders possible both the estimation of the total channel pulse response and the estimation of the coefficients for interference prediction.
  • the total channel pulse response thus also contains the pulse response of the receiving filter 5.
  • the coefficients h 0 ... of the total channel pulse response estimated in the receiver and the coefficients pi ... for interference prediction are passed on to the state-based equalizer 6.
  • the principle of the state-based equalizer 6 offers an opportunity of separating the hypothetical useful signal and interference signal, so that an individual processing of the hypothetical interference-signal values is possible. To calculate the coefficients pi ...
  • an initial estimate of the autocorrelation coefficients of the correlated interference signal u n is required.
  • An initial estimate of the autocorrelation coefficients of the correlated interference signal u n may take place, for example, by evaluation of the interference-signal values within the training sequence. These initial-estimate values can be further improved by the inclusion of the interference-signal values estimated during detection. If the autocorrelation coefficients of the interference signal u n are known and, from these, the coefficients of the interference prediction, the interference prediction can estimate the interference-signal value in the current time step for each state transition using the immediately preceding interference-signal values. This interference prediction value is subtracted from the received signal. The effective interference power is reduced thereby upon detection of the data symbols. It should be noted here that the corrected received-signal values are different for each state transition.
  • the interference prediction is an optimum when all linear statistical linkages of the interference process are taken account of by the interference prediction, which demands an interference prediction of a very high order.
  • a first or second order interference prediction frequently suffices for achieving a large proportion of the maximum possible gain.
  • the squared error signal In a state-based equalizer, the squared error signal, normalized where applicable with the variance of the error signal, is generally used as the similarity criterion or metrics.
  • the error signal corresponds to the difference between the particular received-signal value and the hypothetical, reconstructed signal values of the state transitions.
  • These metrics are an optimum in the case of additive white Gaussian noise (AWGN).
  • AWGN additive white Gaussian noise
  • the use of these metrics requires a calculation of the error signal.
  • the error signal is simultaneously used in the present case for interference prediction of correlated interference, as will be described in greater detail below.
  • N Variance of the error signal
  • M Number of coefficients of interference prediction.
  • G' Variance of error signal with interference prediction.
  • the interference prediction is a filtration of the past interference-signal values with the coefficients p, of the interference prediction.
  • the past error-signal values ⁇ n . may be of a state-dependent or state-independent form. State-dependent means that the past error- signal values originate from a sequence of past valid state transitions, i.e. they belong to a valid, selected path in the state trellis, which leads to the state S n under consideration in time step n.
  • the M past error-signal values can thus be assigned to a specific state and stored in a state-related memory (buffer). With a number Z of states, M . Z error-signal values must be stored. The error-signal values belonging to a selected state transition are each copied into the state-related memory of the subsequent state.
  • Fig. 2 is an example of a trellis diagram of a state-based equalizer with eight states (0 to 7) and one binary symbol alphabet. All possible state transitions and the fusion of the paths into the subsequent states are shown.
  • Fig. 3 shows, in greater detail than Fig. 2, a trellis recursion step using the example of a state-based equalizer with eight states and a binary symbol alphabet in time step n.
  • Three buffers 10, 11, 12, which store different variables, are assigned to each state. Buffer 10 stores the state metrics ⁇ n (Sschreib).
  • the number P of stored past data symbols depends on the equalization method.
  • a trellis step consists in the branch metrics ⁇ ' n (S n
  • Equation 4 shows how the state metrics ⁇ n (S n ) of the subsequent states S n are formed from the state metrics ⁇ n-1 (S n- ⁇ ) of the previous states S n- 1 and the branch metrics ⁇ 'n(Sn
  • the branch metrics of the state transition are added to the state metrics for all previous states S ⁇ - ⁇ for which a transition into the subsequent state S n exists, and the state transition with the smallest metrics is selected. Selection of the state transition implies simultaneously that the path memory and the state memory of the error-signal values of the previous state are adopted into the corresponding buffer of the subsequent state and supplemented by the data symbol a n and the error-signal value eix which belong to the state transition. Generally, the oldest value in each case is shifted out of the buffers.
  • Fig. 4 shows the recursive processing of the state trellis in a state-based equalizer.
  • Fig. 5 shows the determination of the error signal e' n with interference prediction and the branch metrics ⁇ ' n with interference prediction from the received-signal value r n and the data symbols a n- i and the past error-signal values ⁇ n -i, as corresponding to equation 3 above.
  • the possible use of state-independent error-signal values e n .j, in the interference prediction according to equation 3 above means that only one error-signal value per time step is stored, i.e. a total of M error-signal values for M past time steps, which are then used for all states.
  • One example of a possible criterion for the selection of the valid error-signal value is the selection of the error-signal value that leads to the smallest branch metrics with interference prediction.
  • the described method for interference prediction may be used for state-based equalization with a full state quantity as well as with a reduced state quantity, for example by set partitioning.
  • the described method forms a combination of a state-based equalization with an interference prediction for correlated interference.
  • the interference prediction in conjunction with the state-based equalization leads to a reduction of correlated interference without changing the useful signal, and thus also to a reduction in the bit and block error rate.
  • Interference suppression is all the more effective in proportion as the interference-signal values are correlated.
  • the method also has the advantage that it can be applied to any types of interference with low sensitivity to the parameters of the interference, and it causes only low loss levels in the case of uncorrelated interference. In the case of common-channel interference and adjacent-channel interference, the method brings about high gain.

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

Abstract

L'invention concerne un égaliseur effectuant une estimation MLSE (algorithme de Viterbi) en présence de bruit coloré. Pour chaque état (Sn) dans le treillis, une séquence d'erreur (e) est stockée. Cette séquence d'erreur est déterminée à partir de la différence entre les séquences de signal estimée et reçue. Pour chaque état, la séquence d'erreur est alimentée dans un filtre de prévision de bruit correspondant dont la sortie est soustraite de la séquence reçue. La métrique de branche globale (μ) est, par conséquent, calculée à partir de la différence entre la somme du signal estimé et du bruit prévu et le signal reçu (rn). Les coefficients (pi) du filtre de prévision de bruit sont obtenus à partir de la fonction d'auto-corrélation du bruit pouvant être estimée dans la séquence d'entraînement. L'invention concerne également une version simplifiée n'utilisant, par exemple, qu'un filtre de prévision de bruit pour tous les états.
PCT/IB2002/004935 2001-11-27 2002-11-26 Egaliseur d'estimation sequentielle de vraisemblance maximale (mlse) destine a des signaux d'interference correles WO2003047193A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2002347491A AU2002347491A1 (en) 2001-11-27 2002-11-26 Mlse equalizer for correlated interference signals

Applications Claiming Priority (2)

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DE10158056.8 2001-11-27
DE2001158056 DE10158056A1 (de) 2001-11-27 2001-11-27 Verfahren und Einrichtung zur Unterdrückung korrelierter Störsignale

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003088240A3 (fr) * 2002-04-18 2004-02-05 Infineon Technologies Ag Procede et appareil pour le calibrage de la prediction du bruit lie aux donnees
DE10354557A1 (de) * 2003-11-21 2005-07-14 Infineon Technologies Ag Verfahren und Vorrichtung zur Prädiktion von in einem Empfangssignal enthaltenen Rauschen

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CAROSELLI J ET AL: "Improved Detection For Magnetic Recording Systems With Media Noise", MAGNETICS CONFERENCE, 1997. DIGESTS OF INTERMAG '97., 1997 IEEE INTERNATIONAL NEW ORLEANS, LA, USA 1-4 APRIL 1997, NEW YORK, NY, USA,IEEE, US, 1 April 1997 (1997-04-01), pages CR - 7-CR-7, XP010230108, ISBN: 0-7803-3862-6 *
CHEVILLAT P R ET AL: "Noise-predictive partial-response equalizers and applications", DISCOVERING A NEW WORLD OF COMMUNICATIONS. CHICAGO, JUNE 14 - 18, 1992. BOUND TOGETHER WITH B0190700, VOL. 3, PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, NEW YORK, IEEE, US, vol. 4, 14 June 1992 (1992-06-14), pages 942 - 947, XP010062033, ISBN: 0-7803-0599-X *
PIPON F ET AL: "Multichannel receivers performance comparison in the presence of ISI and CCI-application to a GSM link", DIGITAL SIGNAL PROCESSING PROCEEDINGS, 1997. DSP 97., 1997 13TH INTERNATIONAL CONFERENCE ON SANTORINI, GREECE 2-4 JULY 1997, NEW YORK, NY, USA,IEEE, US, 2 July 1997 (1997-07-02), pages 371 - 374, XP010250986, ISBN: 0-7803-4137-6 *
RANTA P A ET AL: "CO-CHANNEL INTERFERENCE CANCELLING RECEIVER FOR TDMA MOBILE SYSTEMS", COMMUNICATIONS - GATEWAY TO GLOBALIZATION. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMMUNICATIONS. SEATTLE, JUNE 18 - 22, 1995, PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), NEW YORK, IEEE, US, vol. 1, 18 June 1995 (1995-06-18), pages 17 - 21, XP000532964, ISBN: 0-7803-2487-0 *
WESOLOWSKI K: "ML sequence estimation for data signals corrupted by intersymbol interference and colored noise", PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, 1996. PIMRC'96., SEVENTH IEEE INTERNATIONAL SYMPOSIUM ON TAIPEI, TAIWAN 15-18 OCT. 1996, NEW YORK, NY, USA,IEEE, US, 15 October 1996 (1996-10-15), pages 472 - 476, XP010209215, ISBN: 0-7803-3692-5 *
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003088240A3 (fr) * 2002-04-18 2004-02-05 Infineon Technologies Ag Procede et appareil pour le calibrage de la prediction du bruit lie aux donnees
DE10354557A1 (de) * 2003-11-21 2005-07-14 Infineon Technologies Ag Verfahren und Vorrichtung zur Prädiktion von in einem Empfangssignal enthaltenen Rauschen
DE10354557B4 (de) * 2003-11-21 2007-11-29 Infineon Technologies Ag Verfahren und Vorrichtungen zur Prädiktion von in einem Empfangssignal enthaltenen Rauschen sowie ein digitaler Empfänger
US7616714B2 (en) 2003-11-21 2009-11-10 Infineon Technologies Ag Process and device for the prediction of noise contained in a received signal

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DE10158056A1 (de) 2003-06-05

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