Echo canceller having an adaptive filter with a dynamically adjustable step size

• US 6,950,842 B2
• Filed: 01/23/2002
• Issued: 09/27/2005
• Est. Priority Date: 01/23/2002
• Status: Active Grant

• Current Assignee: Analog Devices, Inc.
• Original Assignee: Analog Devices, Inc.
• Inventors: Lis, Fabian
• Primary Examiner(s): Ngo, Chuong D
• Application Number:
  US10/055,447
• Publication Number:
  US 20030140075A1
• Time in Patent Office: 1,343 Days
• Field of Search: 708/310, 708/314, 708/322, 708/323, 379/406.08, 379/406.09
• US Class Current: 708/322
• CPC Class Codes: H04B 3/23 using a replica of transmitted signal in the time domain, e.g. echo cancellers

Abstract

The present invention is directed to an echo canceller adapted for use in a communication system that includes a hybrid circuit. The echo canceller comprises an adaptive digital filter that generates an estimated echo signal {circumflex over (z)}[k] in response to: (i) a sampled input data sequence x[k] and (ii) an error signal sequence e[k] indicative of the difference between a near end signal sequence y[k] and the estimated echo signal {circumflex over (z)}[k]. The adaptive digital filter computes filter coefficients based upon the error signal sequence e[k] using a stochastic quadratic descent estimator, such as for example a least mean square (LMS) estimator, that employs a dynamically adjustable step size vector μ[k]. The adaptive digital filter computes the dynamically adjustable step size vector μ[k] of the form $\underset{\_}{\mu }\left[k+1\right]=\underset{\_}{\mu }\left[k\right]+\alpha \underset{\_}{\varphi }\left[k\right]·\underset{\_}{x}\left[k\right]e\left[k\right]{|}_{{\mu }_{\min }}^{{\mu }_{\max }},$
where φ[k+1]=φ[k]•(1−μ[k]•x²[k])+e[k])+e[k]x[k] and α is a scalar. In an open loop embodiment, the dynamically adjustable step size vector μ[k] equals to μ[k]=μ[k]1, that is, all elements of the vector take the same value collapsing to the particular case of a scalar. The step size is computed using an expression of the form μ[k+1]=μ[k]+ξ[k], where ξ[k] is an empirically derived set of values.

Claims

1. An echo canceller adapted for use in a communication system that includes a hybrid circuit, said echo canceller comprising:

an adaptive digital filter that generates an estimated echo signal {circumflex over (z)}[k] in response to (i) a sampled input data sequence x[k] and (ii) an error signal sequence e[k] indicative of the difference between a near end signal sequence y[k] and the estimated echo signal {circumflex over (z)}[k], wherein said adaptive digital filter computes filter coefficients based upon said error signal sequence e[k] using a stochastic quadratic descent estimator that employs a dynamically adjustable step size vector μ

[k] and said adaptive digital filter comprises means for computing said dynamically adjustable step size vector μ

[k] of the form $\underset{\_}{\mathrm{\mu <br><br>}}<br><br>\left[k+1\right]=\underset{\_}{\mathrm{\mu <br><br>}}<br><br>\left[k\right]+\mathrm{\alpha <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\underset{\_}{\mathrm{\varphi <br><br>}}<br><br>\left[k\right]·<br><br>\underset{\_}{x}<br><br>\left[k\right]<br><br>e<br><br>\left[k\right]<br><br>{|}_{{\mathrm{\mu <br><br>}}_{\min }}^{{\mathrm{\mu <br><br>}}_{\max }},$

where φ

[k+1]=φ

[k]•

(1−

μ

[k]•

x²[k])+e[k]x[k] and α

is a scalar.

2. The echo canceller of claim 1, wherein said stochastic quadratic descent estimator comprises a least mean square (LMS) estimator that includes said dynamically adjustable step size.

3. An integrated circuit that includes an echo canceller adapted for use in a communication system that includes a hybrid circuit that provides a return signal, said echo canceller comprising:

an adaptive digital filter that generates an estimated echo signal {circumflex over (z)}[k] in response to (i) a sampled input data sequence x[k] and (ii) an error signal sequence e[k] indicative of the difference between a near end signal sequence y[k] and the estimated echo signal {circumflex over (z)}[k], wherein said adaptive digital filter computes filter coefficients based upon said error signal sequence e[k] using a stochastic quadratic descent estimator that employs a dynamically adjustable step size vector μ

[k] and said adaptive digital filter comprises means for computing said dynamically adjustable step size vector μ

[k] of the form $\underset{\_}{\mathrm{\mu <br><br>}}<br><br>\left[k+1\right]=\underset{\_}{\mathrm{\mu <br><br>}}<br><br>\left[k\right]+\mathrm{\alpha <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\underset{\_}{\mathrm{\varphi <br><br>}}<br><br>\left[k\right]·<br><br>\underset{\_}{x}<br><br>\left[k\right]<br><br>e<br><br>\left[k\right]<br><br>{|}_{{\mathrm{\mu <br><br>}}_{\min }}^{{\mathrm{\mu <br><br>}}_{\max }},$

where φ

[k+1]=φ

[k]•

(1−

μ

[k]•

x²[k])+e[k]x[k] and α

is a scalar.

4. The integrated circuit of claim 3, wherein said stochastic quadratic descent estimator comprises a least mean square (LMS) estimator that includes said dynamically adjustable step size.

5. A digital signal processor that includes executable program instructions to provide an echo canceller adapted for use in a communication system which includes a hybrid circuit that provides a return signal, said echo canceller comprising:

an adaptive digital filter that generates an estimated echo signal {circumflex over (z)}[k] in response to (i) a sampled input data sequence x[k] and (ii) an error signal sequence e[k] indicative of the difference between a near end signal sequence y[k] and the estimated echo signal {circumflex over (z)}[k], wherein said adaptive digital filter computes filter coefficients based upon said error signal sequence e[k] using a stochastic quadratic descent estimator that employs a dynamically adjustable step size vector μ

[k] and said adaptive digital filter comprises means for computing said dynamically adjustable step size vector μ

[k] of the form $\underset{\_}{\mathrm{\mu <br><br>}}<br><br>\left[k+1\right]=\underset{\_}{\mathrm{\mu <br><br>}}<br><br>\left[k\right]+\mathrm{\alpha <br><br>}<br><br>\text{\hspace{1em}<br><br>}<br><br>\underset{\_}{\mathrm{\varphi <br><br>}}<br><br>\left[k\right]·<br><br>\underset{\_}{x}<br><br>\left[k\right]<br><br>e<br><br>\left[k\right]<br><br>{|}_{{\mathrm{\mu <br><br>}}_{\min }}^{{\mathrm{\mu <br><br>}}_{\max }},$

where φ

[k+1]=φ

[k]•

(1−

μ

[k]•

x²[k])+e[k]x[k] and α

is a scalar.