SYMMETRY BASED SUBBAND ACOUSTIC ECHO CANCELLATION

Abstract: Processing complexity in an acoustic echo canceller can be reduced by partitioning the input near-end and far-end signals into respective pluralities of frequency subband signals. Also, due to the complex conjugate symmetry of conventional Discrete Fourier Transform matrices, not all of the subband signals of each plurality need be subjected to echo cancellation processing. The subband signals that would have otherwise been produced by echo cancellation processing are instead provided by producing complex conjugates of selected ones of the subband signals that have been subjected to echo cancellation processing.

Description: SYMMETRY BASED SUBBAND ACOUSTIC ECHO CANCELLATION This application claims the priority under 35 USC 119(e) (1) of copending U.S. Provisional Application No. 60/137,537, filed on June 4, 1999. FIELD OF THE INVENTION The invention relates generally to bidirectional audio communications and, more particularly, to echo cancellation in such communications. BACKGROUND OF THE INVENTION FIGURE 1 illustrates a conventional communication device in which echo cancellation techniques are utilized. The device of FIGURE 1 could be, for example, a telephone (fixed or mobile) including a hands -free speaker/microphone arrangement at 14. A signal x far from a far-end source is reproduced at loudspeaker 11. When the sound emerges from loudspeaker 11, it bounces off of surrounding structures and back into a microphone 13 that also receives a sig —'nal x-n,e,,a--r. from a near-end source. Because of this echo phenomenon, a listener at the far end can actually perceive an echo of the sound produced at the far end. To eliminate such echos, a filter with adjustable filter taps is conventionally applied as illustrated at 17 and 19 in FIGURE 1. The values of the filter taps are controlled by an adaptive algorithm (e.g., a Least Mean Squares algorithm) illustrated at 17 such that the echo canceller filter at 19 resembles as closely as possible the echo path between the loudspeaker 11 and the microphone 13. The estimated echo produced by the echo canceller filter 19 is subtracted at 15 from the signal output from the microphone 13, such that, ideally, only the near-end signal x near remains as the resulting signal 12. Conventional techniques of eliminating acoustical echos in communication devices such as illustrated in FIGURE 1 have heretofore employed algorithms that operate on the entire frequency range supported by the communication device, for example 300-3400 Hz for a typical conventional telephone. According to the present invention, improved echo cancellation performance is achieved by dividing the audio signal into subbands, and applying echo cancellation techniques in the subbands. Advantageously, by applying echo cancellation techniques in subbands, the adaptive filter used for echo cancellation can be simplified. BRIEF DESCRIPTION OF THE DRAWINGS FIGURE 1 illustrates a conventional communication device including an echo canceller. FIGURE 2 diagrammatically illustrates pertinent portions of an exemplary communication device including echo cancellation according to the present invention. FIGURE 3 diagrammatically illustrates an exemplary embodiment of the analysis filter banks of FIGURE 2. FIGURE 4 diagrammatically illustrates an exemplary embodiment of the synthesis filter bank of FIGURE 2. FIGURE 5 illustrates an exemplary DFT matrix which can be used in the DFT filters of FIGURES 3 and 4. FIGURE 6 diagrammatically illustrates an exemplary echo canceller calculation example according to the invention. FIGURE 7 diagrammatically illustrates an exemplary echo canceller calculation simplification according to the invention. FIGURE 8 diagrammatically illustrates pertinent portions of an exemplary embodiment of the echo canceller of FIGURE 2. FIGURE 9 illustrates exemplary operations which can be performed by the echo canceller embodiments of FIGURES 2 and 8. DETAILED DESCRIPTION FIGURE 2 illustrates pertinent portions of an exemplary embodiment of a communication device including an echo canceller 20 according to the present invention. The communication device could be, for example, a telephone (fixed or mobile) including a hands-free arrangement as described above. The far-end acoustic signal x far passes through an acoustic echo path H(z) illustrated generally at 22, and is added at 26 (for example at a microphone) to the near-end acoustical signal x near . The resulting signal d is applied to an analysis filter bank A at 23. The filter bank 23 splits the signal d into a plurality of frequency subbands, and downsamples the subband signals. Similarly, the far-end signal x far is applied to an analysis filter bank A at 21 which, in one embodiment, is identical to the analysis filter bank at 23. An echo cancellation operator including a Least Mean Squares (LMS) operator 24 and a summation operator 29 is coupled to the analysis filter banks 21 and 23 such that the LMS operator 24 receives the output x of the filter bank 21, and the summation operator 29 receives the output d of the filter bank 23. The output of the summation operator 29 is fed back to the LMS operator 24 and is also applied to a complex conjugate operator 27 of the echo canceller, whose output is in turn coupled to a synthesis filter bank S at 25. FIGURE 3 illustrates an exemplary embodiment of the FIGURE 2 analysis filter banks 21, operating on x(n) , and 23, operating on d(n) . The digitized far-end signal x(n) (or digitized near-end signal d(n)) in FIGURE 3 is input to a bank of analysis filters 31, for example a bank of conventional polyphase bandpass filters, which split the far-end signal into M frequency subbands. The subband signals are then downsampled by a factor of K by a downsampler 33, and the resulting downsampled subband signals are applied to a Discrete Fourier Transform (DFT) filter W* at 35. The arrangement of FIGURE 3 provides for lower computational complexity, because the signal is down- sampled in each of the M subbands by a factor of K. Thus, the number of filter tap computations for each output sample of each subband is reduced by a factor of K. Also, the arrangement of FIGURE 3 will provide for faster convergence of the adaptive echo cancellation algorithm, because the signal in each subband is "whiter" and has a smoother energy level than would the input signal x(n) (or d(n)) . In one embodiment, the values of M and K are chosen such that M/K = 4/3. Analysis filters, DFT filters and downsamplers are well-known in the art, and can be implemented in any suitable conventional manner in the embodiment of FIGURE 3. FIGURE 4 illustrates an exemplary embodiment of the synthesis filter bank 25 of FIGURE 2. As shown in FIGURE 4, and as further discussed below, an error signal eM formatted in M frequency subbands is applied to an inverse DFT filter W* INV at 41. This filter performs an inverse DFT operation on the subband error signals. The output of the filter 41 is applied to an upsampler 43 which upsamples the subband signals by a factor of K. The upsampled subband signals are then input to respective synthesis filters at 45. The synthesis filters have their outputs coupled together in conventional fashion (not explicitly shown in FIGURE 4) to produce the desired, echo-cancelled, output signal e (n) (see also FIGURE 2). Inverse DFT filters, upsamplers and synthesis filters are well-known in the art, and can be implemented in any suitable conventional manner in the FIGURE 4 embodiment . FIGURE 5 illustrates an exemplary DFT modulation matrix W* which can be used by the filter 35 of FIGURE 3 , and the transpose of which can be used as W* INV by the filter 41 of FIGURE 4. (In this example the transpose is identical to the FIGURE 5 matrix) . This matrix illustrates a fundamental principle of all DFT matrices, namely that such matrices include rows which are complex conjugates of one another. For example, in the DFT matrix of FIGURE 5, rows 2 and 4 are complex conjugates of each other. This in turn means that, when a plurality of subband signals are applied to the DFT matrix, at least two of the resulting output signals will be complex conjugates of each other. Referring again to FIGURE 2, and ignoring for now the M and M' nomenclature, it can be seen generally that, by operation of the summing operator 29, Equation 1 e = d - y, where y is generally the output of the LMS filter 24. The signal e includes a real component e r , and an imaginary component e 1# given by Equation 2 e r = d r - y r Equation 3 e, = d. - y. where d r and d. are the real and imaginary components of the signal d, and y r and y. are the real and imaginary components of the signal y. The real and imaginary components y r and y l respectively, are given by Equation 4 y r = x r h r τ - x.h. τ Equation 5 y. = x r h. τ + x.h r τ where h r and h are the respective real and imaginary adaptive filter coefficient matrices conventionally used by the LMS operator 24, and x r and x 1 are the real and imaginary components of the signal x. Combining Equations 2 and 4 yields Equation 6 = cL x h + x,h. and combining Equations 3 and 5 yields Equation 7 = d. x,h. x,h„ As mentioned above, the multiple subband output of filter bank 21 will include at least two subbands which are complex conjugates, as will the multiple subband output of analysis filter bank 23. Accordingly, the error signal attributable to a given subband which is a complex conjugate of another subband will have a real component given by Equation 8 rcc — rcc -T ree ' where d rcc is the real component of the complex conjugate subband signal output from analysis filter bank 23, and y rcc is the real component of the subband signal output from LMS filter 24 in response to the complex conjugate subband signal output from analysis filter bank 21. Similarly, the imaginary component e lcc attributable to the complex conjugate signals output from analysis filter banks 21 and 23 is given by Equation 9 Yx Also , Equation 10 Yr x rcc h rcc X ιcc n ιcc Equation 11 where x rcc and x lcc are the real and imaginary components of the complex conjugate subband signal output from analysis filter bank 21, and h rcc and h lcc are the respective real and imaginary adaptive filter coefficient matrices computed by the LMS filter algorithm in response to x rcc and x lcc . By the definition of complex conjugates, we have Equation 12 Equation 13 X ιcc _ X ι Equation 14 d rcc = d r Equation 15 d ICC = -d 1 Due to the linearity of the LMS algorithm, the filter coefficients h respectively associated with input subband signals that are complex conjugates of each other will themselves be complex conjugates of each other. Accordingly, applying the definition of complex conjugates, Equation 16 Equation 17 h ιcc = - Combining Equations 8, 10, 12-14, 16 and 17, yields Equation 18 e rcc = d r X l. χ, . = e r . Similarly, combining Equations 9, 11-13, and 15-17 yields Equation 19 e. cc = -d. + x r h. τ + Xι h r τ = - e ι. Accordingly, and referring again to FIGURE 2, if a first subband signal x from filter bank 21 and a first subband signal d from filter bank 23 are applied to the echo cancellation operator, the resulting subband signal e will be the complex conjugate of a subband signal e cc (including real part e rcc and imaginary part e ιcc ) that would be produced by the echo cancellation operator in response to second subband signals x cc and d cc , where x cc and d cc are respectively output from filter banks 21 and 23, and are respective complex conjugates of the first subband signals x and d output from filter banks 21 and 23. Thus, any complex conjugate subband signals need not be forwarded from the filter banks 21 and 23 to the echo cancellation operator, because the associated output signal e cc is easily determined by obtaining the complex conjugate of the signal e associated with the first signals x and d. This is illustrated in FIGURES 2 and 3 wherein, although the analysis filters 31 produce M subbands, only M' subbands are output from the DFT filter 35, wherein M' is less than M, but at least M/2 + 1 in some embodiments. For example, if M = 4, and the matrix of FIGURE 5 is implemented in the DFT filter 35, then M' = 3, because one of the subband signals produced by the filter 35 will be the complex conjugate of another of the subband signals produced by the filter 35, and therefore need not be applied to the echo cancellation operator at 24 and 29 in FIGURE 2. A further advantage according to the invention of applying echo cancellation in subbands is illustrated by the following example. In a telecommunications application, if the input signal is band-limited to 3400 Hz, the sampling frequency is 8000 Hz, and 8 subbands are used, then one of the frequency subbands will be between 3500 and 4000 Hz. Because this frequency band has no spectral energy in it, this band can be advantageously discarded without any distortion occurring. Noting also that, for this example, M/2 + 1 = 8/2 + 1 = 5, it can be seen that three additional subbands can be discarded due to the complex conjugate symmetry of the DFT matrix. Accordingly, using the present invention, the total number of subbands to be input to the echo cancellation operator is reduced in this example from M = 8 subbands to M' = 4 subbands. Similarly, with M = 16 subbands, M/2 + 1 = 16/2 + 1 = 9, and 2 subbands will have no spectral energy therein, so echo cancellation filtering is applied to only M' = 7 subbands . The reduction in subbands from M to M' is designated generally in FIGURE 2 by the signal xM' (n) output from filter bank 21, the signal yM' (n) output from the LMS operator 24, and the signal dM' (n) output from the filter bank 23. Similarly, the signal eM' (n) output from summation operator 29 includes M' subbands. This signal is input to a complex conjugate operator 27 which produces from the subband signals in eM' (n) the complex conjugate subband signals that would otherwise have been produced by the echo cancellation operator, thereby producing the signal eM(n) including M subbands . FIGURE 6 illustrates diagrammatically a calculation example in view of Equations 8-19 above. More specifically, if the signal inputs to a first LMS echo cancellation operator 63 are complex conjugates of the signals input to a second LMS echo cancellation operator 61, then the output of the LMS echo cancellation operator 63 will be the complex conjugate of the output of the LMS echo cancellation operator 61. FIGURE 7 diagrammatically illustrates a calculation simplification example in view of FIGURE 6 and Equations 8-19 above. More particularly, the signals e rcc and e lcc associated with the signals x rcc , x lcc , d rcc and d lcc of FIGURE 6 can be produced directly from the signals x r , x., d r and d lA by performing a complex conjugate operation on the signals e r and e.^ FIGURE 8 diagrammatically illustrates pertinent portions of an exemplary embodiment of the echo canceller of FIGURE 2. The embodiment of FIGURE 8 is illustrative of the aforementioned example of a telecommunications application wherein the input signal is band-limited to 3400 Hz, the sampling frequency is 8000 Hz, and M = 8 subbands. As mentioned above, one of the subbands has no spectral energy therein, and may therefore be discarded (note subband signals x 4 and d 4 have already been discarded in FIGURE 8) , so that M is effectively equal to 7. Furthermore, as described above, 3 more subbands can be discarded due to the symmetry of the DFT matrices in the filters 35, such that the signals xM' (n) and dM' (n) include only 4 subbands (M' = 4) . In the example of FIGURE 8, the echo cancellation operator utilizes conventional Complex Normalized Least Mean Squares (CNLMS) techniques to produce the 4 -subband output signal eM' (n) , 3 of whose subbands are used to produce complex conjugates in the complex conjugate section 27, thereby producing a 7-subband signal to be input to the filter 41. FIGURE 9 illustrates exemplary operations which can be performed by communication devices including echo cancellation according to the invention. At 91, the input signals x(n) and d(n) are received. At 92, the signals x(n) and d(n) are filtered in M bandpass filters to produce respective signals including M frequency subbands, and the M subband signals are downsampled K times. At 94, the downsampled signals are multiplied by the DFT matrix W* . At 95, the unnecessary subband signals, including complex conjugate subband signals and subband signals having no spectral energy, are discarded. At 96, adaptive echo cancellation filtering is performed on the remaining subband signals. At 97, the missing components of the signal e are produced by obtaining complex conjugates of the existing subband signals of signal e. At 98, the resulting signal e including M subbands is multiplied by the inverse DFT matrix. At 93, the M- subband signal is upsampled by a factor of K, and then applied to M polyphase filters to obtain the desired, echo-cancelled signal e(n). As is clearly evident from the foregoing description, the present invention reduces the number of calculations needed to provide echo cancellation in a communication device. For example, if the LMS operator includes a finite impulse response (FIR) filter with 256 taps, an 8 band system with complex signals would require 2 x 256 x 8 filter calculations. This number can be divided by a factor close to 2 by applying the principles of the present invention. Alternatively, the performance of the system can be enhanced. For example, if L taps are used in each LMS operator in a system with M subbands, then the (M/2 - 1) x L taps that are saved according to the principles of the invention can be distributed as desired to the other bands, thus enhancing the performance of the remaining bands . It will evident to workers in the art that the embodiments of the present invention described above with respect to FIGURES 2-9 can be implemented, for example, by a suitably programmed data processing device such as a digital signal processor (DSP) provided in a communication device according to the invention. Alternatively, the above-described embodiments can be provided in a suitably programmed data processing device in combination with external components coupled thereto. Although exemplary embodiments of the present invention have been described above in detail, this does not limit the scope of the invention, which can be practiced in a variety of embodiments.

Claims: WHAT IS CLAIMED IS: 1. A filter bank for use in an acoustic echo canceller, comprising: an input for receiving a digital acoustical signal; an integer number M of filters coupled to said input for partitioning the digital acoustical signal into M frequency subband signals; M downsamplers respectively coupled to said filters for reducing the sampling rate of said M frequency subband signals to produce M downsampled frequency subband signals; and a further filter implementing an MxM modulation matrix, said further filter coupled to said M downsamplers for applying said modulation matrix to said M downsampled frequency subband signals to produce further frequency subband signals, said further filter having an output for providing said further frequency subband signals to an acoustic echo cancellation operator. 2. The filter bank of Claim 1, wherein said digital acoustical signal is a near-end signal. 3. The filter bank of Claim 1, wherein said digital acoustical signal is a far-end signal. 4. The filter bank of Claim 1, wherein said modulation matrix is a DFT matrix having at least one pair of complex conjugated rows. 5. A filter bank for use in an acoustic echo canceller, comprising: an input for receiving a digitized acoustical error signal produced by an acoustic echo cancellation operator and formed as an integer number M of frequency subband error signals; a filter implementing an MxM modulation matrix, said filter coupled to said input for applying said modulation matrix to said M frequency subband error signals to produce M further frequency subband error signals; M upsamplers having respective inputs coupled to said filter for respectively receiving said M further frequency subband error signals and increasing the sampling rate of said M further frequency subband error signals to produce M upsampled frequency subband error signals; and M synthesis filters respectively coupled to said M upsamplers for receiving said M upsampled frequency subband error signals and producing therefrom an echo- cancelled near-end signal. 6. The filter bank of Claim 5, wherein said modulation matrix is a DFT matrix. 7. An acoustic echo canceller, comprising: a first input for receiving a digitized near-end acoustical signal formed as a plurality of near-end frequency subband signals; a second input for receiving a digitized far-end acoustical signal formed as a plurality of far-end frequency subband signals; an acoustic echo cancellation operator coupled to said first and second inputs for producing in response to said near-end frequency subband signals and said far-end frequency subband signals an error signal formed as a plurality of frequency subband error signals; and said acoustic echo cancellation operator having an output for providing said plurality of frequency subband error signals to a synthesis filter bank capable of producing therefrom an echo-cancelled near- end signal. 8. The acoustic echo canceller of Claim 7, wherein said acoustic echo cancellation operator includes a Least Mean Squares operator. 9. The acoustic echo canceller of Claim 8, wherein said acoustic echo cancellation operator includes a Complex Normalized Least Mean Squares operator. 10. An acoustic echo canceller, comprising: a first input for receiving a far-end digitized acoustical signal; a second input for receiving a near-end digitized acoustical signal; a first analysis filter bank coupled to said first input for partitioning said far-end signal into M frequency subband far-end signals and producing from said M frequency subband far-end signals M' further frequency subband far-end signals where M' is less than M; a second analysis filter bank coupled to said second input for partitioning said near-end signal into M frequency subband near-end signals and for producing from said M frequency subband near-end signals M' further frequency subband near-end signals; an acoustic echo cancellation operator coupled to said first and second analysis filter banks for receiving from said first analysis filter bank said M' further frequency subband far-end signals, and for receiving from said second analysis filter bank said M' further frequency subband near-end signals, said acoustic echo cancellation operator operable in response to said M' further frequency subband far-end signals and said M' further frequency subband near-end signals to produce M' frequency subband error signals; a complex conjugate operator coupled to said acoustic echo cancellation operator for receiving therefrom M - M' of said frequency subband error signals and producing complex conjugates of said M - M' frequency subband error signals; and a synthesis filter bank coupled to said complex conjugate operator for receiving said M - M' complex conjugates and also coupled to said acoustic echo cancellation operator for receiving therefrom said M' frequency subband error signals, said synthesis filter bank responsive to said M' frequency subband error signals and said M - M' complex conjugates for producing an echo-cancelled near-end signal. 11. The acoustic echo canceller of Claim 10, wherein said acoustic echo cancellation operator includes a Least Mean Squares operator. 12. The acoustic echo canceller of Claim 11, wherein said acoustic echo cancellation operator includes a Complex Normalized Least Mean Squares operator. 13. The acoustic echo canceller of Claim 10, wherein said analysis filter banks each include a filter implementing an MxM modulation matrix having at least one pair of complex conjugated rows, said filter producing the associated M' further frequency subband signals . 14. The acoustic echo canceller of Claim 13, wherein said modulation matrix is a DFT matrix having at least one pair of complex conjugated rows. 15. A method of processing a digital acoustical signal in an acoustic echo canceller, comprising: receiving the digital acoustical signal; partitioning the digital acoustical signal into M frequency subband signals; reducing the sampling rate of said M frequency subband signals to produce M downsampled frequency subband signals; and applying an MxM modulation matrix to said M downsampled frequency subband signals to produce further frequency subband signals; and applying said further frequency subband signals to an acoustical echo cancellation operator. 16. The method of Claim 15, wherein said digital acoustical signal is a near-end signal. 17. The method of Claim 15, wherein said digital acoustical signal is a far-end signal. 18. A method of processing a digitized acoustical error signal produced by an echo cancellation operator in an acoustic echo canceller, comprising: receiving the digitized acoustical error signal formed as an integer number M of frequency subband error signals; applying an MxM modulation matrix to said M frequency subband error signals to produce M further frequency subband error signals; increasing the sampling rate of said M further frequency subband error signals to produce M upsampled frequency subband error signals; and using M synthesis filters to produce from said M upsampled frequency subband error signals an echo- cancelled near-end signal. 19. A method of performing acoustic echo cancellation, comprising: receiving a digitized near-end acoustical signal formed as a plurality of near-end frequency subband signals; receiving a digitized far-end acoustical signal formed as a plurality of far-end frequency subband signals ; producing in response to said near-end frequency subband signals and said far-end frequency subband signals an error signal formed as a plurality of frequency subband error signals; and providing said plurality of frequency subband error signals to a synthesis filter bank capable of producing therefrom an echo-cancelled near-end signal. 20. The method of Claim 19, wherein said producing step includes using a Least Mean Squares technique to produce said frequency subband error signals from said near-end and far-end frequency subband signals. 21. A method of performing acoustic echo cancellation, comprising: receiving a far-end digitized acoustical signal; receiving a near-end digitized acoustical signal; partitioning said far-end signal into M frequency subband far-end signals; partitioning said near-end signal into M frequency subband near-end signals; producing from said M frequency subband far-end signals M' further frequency subband far-end signals where M' is less than M; producing from said M frequency subband near-end signals M' further frequency subband near-end signals; producing M' frequency subband error signals in response to the M' further frequency subband far-end signals and the M' further frequency subband near-end signals; producing complex conjugates of M - M' of the frequency subband error signals; and producing an echo-cancelled near-end signal in response to said M' frequency subband error signals and the M - M' complex conjugates. 22. The method of Claim 21, wherein said first- mentioned and second-mentioned producing steps each include applying to the associated M frequency subband signals an MxM modulation matrix having at least one pair of complex conjugated rows. 23. The method of Claim 22, wherein said modulation matrix is a DFT matrix having at least one pair of complex conjugated rows. 24. The method of Claim 21, wherein said third- mentioned producing step includes using a Least Mean Squares technique to produce the M' frequency subband error signals.

Inventors: EHRENSTRAALE FREDRIK, GRUNDSTROEM PATRIK, EHRENSTRAALE, FREDRIK, GRUNDSTROEM, PATRIK
Applicants: ERICSSON TELEFON AB L M, TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)
Application year: 2000
Main classification: H04M9
IPC codes: H04B3, H04M1, H04M9, H04R3