Adaptive echo cancellation method and device for implementing said method

Abstract: The echo cancellation method includes starting with an arbitrary set of echo filter coefficients. The coefficients are first sequentially re-estimated using a fast converging method. These operations are repeated a predefined number of times, and then the coefficients estimation is switched to a low converging but more precise method. In addition, an adaptive threshold is being defined and readjusted and all filter coefficients lower than said threshold are being discarded. Finally, sampling time boundaries are adaptively defined based on non-discarded filter coefficients with reference to said threshold, and in such a way the final echo cancelation algorighm is adaptive to echo variations (backtracking algorithm).

Description: The present invention deals with digital signal transmission over telephone lines in networks including two-to-four wire conversions, and it deals more particularly with a method and device for cancelling echo signals inherent to this kind of networks. Background of the invention Everyone in the communications technology area is aware of the increasing interest in multi-media networks and systems. As far as communications are concerned, multi-media processing means merging and distributing, without impairment, text, images, and speech over a same high speed network covering very long distances. This implies efficiently converting all three kinds of information into digitally encoded data and then vehiculating those data over a common network. Needless to mention that several important technical problems have to find solutions prior to one being able to provide acceptable networks. Echo is one of those problems, and echo cancellation the solution. Several echo cancelers are already available. They, however, are not yet fully satisfactory from a cost/efficiency standpoint, particularly when multiple echoes are involved. To make the above statements clearer, one should remind the basic principles. Speech signals issuing from the telephone set are first transmitted, at least over a short distance, in their analog form and through a bi-directional two-wire line. Said line is then split into two mono-directional lines (four wires overall). One mono-directional line for incoming signals, the other for outgoing signals. Analog-to-Digital (A/D) conversion of the signal are operated over the outgoing speech signal, to enable further transmission over a high speed digital network. Then correlative Digital-to-Analog (D/A) conversion need being performed at the receiving end prior to the signal being vehiculated to the destined telephone set over a bi-directional 2-wire line. Therefore, at least at both ends of the network, two-to-four and four-to-two wire conversions must be performed. These are conventionally achieved through so-called hybrid transformers. Due to unavoidable hybrid load mismatching throughout the voice frequency bandwidth parts of outgoing speech are fedback to their originating telephone user. These are the so-called echoes which do disturb significantly the communication between end-users. Obviously, each hybrid transformer on the speech path may generate an echo, which worsens the situation. Simple echoes are already difficult to track and cancel, therefore, needless to insist on the complexity of the problem when dealing with multiple echoes and/or when dealing with variable environments due to PBX's. Echo cancelers are made using adaptive digital filters monitoring the digital signals over both mono-directional lines, processing said signals to generate an echo replica and subtracting said replica from the actual echo polluted signal. The echo replica generating filter (so-called echo filter) coefficients are dynamically estimated and adjusted to tune the filter. The coefficients estimation computing load is fairly heavy, which is a main drawback with current signal processors. The higher the number of required coefficients, the higher the filter complexity. In addition, one should remember that the echo filter should be designed to dynamically synthesize the echo path impulse response h(t). The filter coefficients may be defined as samples of said impulse response. The longer the impulse response, or more particularly the significant portion of said impulse response, the higher the number of coefficients to be considered. In addition, and especially in a variable network environment, the coefficients computation should be fast enough to render the system operable satisfactorily. This could be achieved, at least partially, by increasing the signal processor power. But in practice, to optimize efficiency versus complexity, one needs optimizing the coefficients computation. Otherwise, the computing workload involved might render the whole echo canceler cost prohibitive. Different methods have been proposed for tracking the significant portions of echo path impulse response, or for computing echo filter coefficients. They all either lack efficiency on adaptiveness or lack efficiency in their convergence toward the right coefficients value. The PCT Application published on April 7, 1988, with the Publication Number WO 88/02582, for instance, discloses a method for cancelling echo noises in a digital network, particularly oriented toward multiple echoes conditions. To that end, an impulse signal can be applied to the transmission line and the corresponding echo signal be measured in response to that impulse. The measured impulse response enables then conventionally generating and storing the required echo filter coefficients. The number of coefficients is then optimized by discarding coefficients having an amplitude which is lower than a predefined threshold. While improving known methods for performing noise cancellation for both simple and multiple echo conditions, this method, based on the use of a training sequence, lacks efficiency in a fast varying network environment, and this, obviously, could be a main drawback for most present applications, including multimedia network applications. One object of this invention is to provide a fully adaptive method to track and compute the most significant echo filter coefficients directly through dynamic thresholding operations, to adapt to changing network environment as required. And in order to be particularly efficient in a fast varying network environment, said method is made to combine a fast converging gradient method with a more precise sign method. These and other objects, characteristics and advantages of the present invention will be explained in more detail in the following, with reference to the enclosed figures, which represent a preferred embodiment thereof. Brief Description of the Figures. Figure 1 is a schematic representation of a single echo path Figure 2 shows a block diagram of a network with an echo canceler Figure 3 shows a double echo representation Figure 4-8 are flow-charts for implementing the echo cancellation features of this invention. Description of Preferred Embodiment Figure 1 shows a schematic representation of a single echo path. The speech signal issuing from speaker A over a 2-wire bi-directional facility, is vehiculated through hybrid transformer (HA) as a signal x t over the upper unidirectional line. Said signal is normally sampled and digitally coded into a flow of data x(n) (n standing for the n th sample), and transmitted over a digital network, toward speaker B. Prior to reaching the hybrid transformer (HB), the signal is converted into analog form. Due to impedance loading mismatching throughout the speech frequency spectrum, a portion of the signal x(t) reaching hybrid transformer HB, is fed back toward speaker A. This is a primary echo, and one may easily understand how disturbing this echo may be to speaker A. Actually, even more disturbing are multiple echoes (see echo 1 and echo 2 in figure 2). Figure 2 shows a block diagram of a conventional Echo Canceler (echo-filter) architecture. The system includes a transversal digital filter (20) fed with the signal samples x(n) (which might be referred to as signal x(n)). The filter (20) is an adaptive filter the coefficients of which are computed in a so-called coefficients estimation device (22) fed with both the x(n) signal and the residual signal e(n). The filter (20) is made to provide an estimated echo replica signal (n). In theory, subtracting (n) from y(n) in a subtractor (24) should cancel the echo. The remaining signal is an error signal e(n). The essential problem to be solved here, lies with the coefficients estimation no matter whether the echo is simple or multiple. A double echo impulse response is shown in figure 3. The main problem lies with determining the significant (amplitudewise) coefficients without knowing the real shape of the impulse response they should be derived from. The method of this invention includes dynamically computing both, threshold values to distinguish significant over insignificant coefficient values, and setting correlative limits (see : first, left, right and last for a double echo situation, in figure 3). Permanently adjusting said limits enable saving a lot of processing load and therefore considerably improving over known methods, including over so-called flat delay determining methods (see European Application n° 854300381 filed on 10.30.1985). Assuming speaker B is not active, which is determined using a conventional voice activity detector (not shown in the figures provided in this application), then the overall process may be summarized as shown in the flow-chart of figure 4. A coefficient threshold value (Thrshld) is initialized to zero, and so-called relative sampling time limits or coefficient boundaries parameters are respectively initially set to the following values : First = 0 Last = D, with D being a predefined large number Left = D/2 Right = Left + 1 In other words, the original transversal filter will cover the whole distance zero to D. The transversal filter is set to operate with an arbitrary set of coefficients defined conventionally and provide an estimated echo replica (n). The error e(n) is derived therefrom. A new set of coefficients is estimated (computed) providing for each previous coefficient (n), a new estimated coefficient (n+1). These operations are repeated for a number of sampling times up to a predefined number T (e.g. T=1000). Once T=1000, boundaries computations are performed and followed by Threshold computation. The whole process may start again with the newly computed Thrshld, First, Last, Left and Right parameters. Any filter coefficient outside those limits is simply dropped. One may also notice one of the flexibilities of this method, enabling redefining dynamically even the number of coefficients itself. Represented in figure 5 is a flow-chart of the transversal filter operation. It should first be reminded that, conventionally, if one let be the estimation at time n of the set of filter coefficients : {h i , i=0, ..., D-1} Then, the transversal filtering providing the echo replica estimation ( (n) ) is according to : The above operations are performed initially with the initial set of coefficients (technique already used with equalizers) and subsequently with the sets defined through coefficients estimation operations, as disclosed further in this description. But one should already note that only those coefficients located between First and Left and between Right and Last will be considered. This also will be described later on. This explains why the flow-chart of Figure 5 implementing equation (1) has been split into two main steps (50) and (52). Each finally estimated echo replica (n) is subtracted from the echo spoiled (or polluted) signal y(n) to generate the estimation error signal e(n). Represented in Figure 6 is a flow-chart for performing the coefficients estimation step of the invention (see Figure 4). The coefficients estimation combines two known methods, i.e. the gradient method and the sign method, generally used separately. The gradient method enables estimating a given filter coefficient h i at sampling time n+1, using the previous h i estimated value, through the following expression : and repeating these operations for the whole set of filter coefficients. µ = mu, is a predefined constant defining a convergence rate. The sign method enables performing filter coefficient computation operations according to : Wherein γ = gamma, is a predefined constant and the expression Sign [X] stands for the sign of X. It has been noticed that while the gradient method usually starts rapidly as far as Signal/Noise ratio (S/N) of the process is concerned, it, then, rapidly saturates to a low (S/N). On the contrary, the sign method may start slowly but goes up to high S/N ratios. The method implemented in the flow-chart of Figure 6, combines both methods to take full advantage of both qualities. It starts with the gradient method (see steps 62 and 64), up to a predefined number N of sampling times n (e.g. 10,000) and then switches to the sign method (see steps 66 and 68). The above combination of methods also provides permanent adjustments to the varying hybrid and network conditions. Also, should the coefficients variations become higher than a given threshold, then the whole coefficients estimation process may start back with the gradient method. Every multiple of a predefined time interval T (e.g. T = n.1000), the boundaries significant parameters (First, Left, Right and Last) are redefined. This is accomplished according to the flow-chart of figure 7. The boundaries are tracked and adjusted through an adaptive scheme based on thresholding considerations over the coefficients magnitudes. The threshold is also adaptively set and permanently adjusted as will be disclosed later. But, assume a threshold value is set, the boundaries tracking is performed as follows : the First and Last boundaries first, and then the Left and Right ones. To begin with, a computing index i is set equal to the last value of First, the magnitude of coefficient is compared to the Threshold value (Thrshld). As long as is lower than said Threshold, the index i is incremented by one, is set to zero and the process goes on. As soon as the test is negative ( > Thrshld), the new value First is set equal to i-1 (to allow algorithm backtracking) and stored as a pointer (see 70). Then, the process starts with i = Last (previously computed Last value), and i is decremented as long as keeps being smaller than Thrshold. When this test becomes negative, Last is set to i-1 (see 72). This is the aim to allow algorithm backtracking. A similar process is used for setting Left (see 74) and Right (see 76). Represented in Figure 8 is a flow-chart for computing the Thrshld value. It is based on the formula : Wherein 0 < α ≤ 1 and | (n)| stands for magnitude (or abs) of (n). Different approaches could be used. For instance, one may use different thresholds, one between First and Left and the other between Right and Last, therefore taking into consideration the fact that secondary echoes are generally lower than primary echoes. Given the above described flow-charts, a man skilled in the art will have no difficulty writing the required (micro) programs for implementing the echo cancellation operations.

Claims: An adaptive digital echo canceling method for canceling from a transmission network, the echo to a periodically sampled (period T) input signal x(n) by synthesizing an echo replica (n), using a digital filter the coefficients of which are to be adaptively generated, and subtracting said replica from an echo spoiled returning signal y(n), to derive therefrom a minimal error signal e(n),said method including : a) setting a coefficient threshold (Thrshld) to a predefined initial value ; b) setting initial relative sampling time limits whereby coefficient boundaries are being defined ; c) setting initial echo filter with initial coefficients set conventionally ; d) generating, based on said initially set filter, an echo replica and subtracting said echo replica from said echo spoiled returning signal, and deriving therefrom an updated error signal e(n); e) deriving a new set of estimated coefficients, said deriving including: generating a set of estimated filter coefficients for the (n+1) th sample time, using a gradient method as a fast converging method ; repeating said fast converging method for a predefined number of times ; and then, switching to a more precise coefficient generating method including a so-called sign method f) repeating steps d) and e) for a predefined number of periods T ; g) redefining after said predefined number of periods said coefficient boundaries based on said coefficient threshold value and dropping filter coefficients out of said threshold thereby defining an updated coefficient set ; h) computing a new coefficient threshold value, based on said updated coefficient set; and, repeating steps d) through h). An adaptive digital echo canceling method according to claim 1, wherein said coefficient boundaries redefining includes: testing the magnitude of each estimated coefficient with respect to the threshold until said estimated coefficient is higher than the threshold and then backtracking to previous estimated coefficient for boundary defining. An adaptive digital echo canceling method according to claim 1 or 2, wherein said deriving of a new set of estimated coefficients is performed only for coefficients within said redefined coefficient boundaries. An adaptive digital echo canceling method according to claim 1, wherein said initial coefficients boundaries includes : setting four boundaries initially as follows : First boundary = zero, Last boundary = D, with D being a predefined large number, Left boundary = D/2, and Right boundary = (D/2) + 1, periodically redefining said boundaries based on current filter coefficient values, with respect to current threshold. An adaptive digital echo canceling method according to claim 4, wherein said redefining coefficient boundaries includes : a) setting a computing index i to be equal to last value of First boundary ; b) comparing the magnitude of last estimated coefficient value to current threshold ; c) setting said as long as its magnitude is lower than said current threshold ; d) incrementing i and repeating steps b and c ; e) setting First boundary equal to i when becomes higher than said current threshold; f) setting i equal to last value of Last boundary ; g) comparing to current threshold, setting to zero if it is lower than said current threshold, and decrementing i until becomes higher than said threshold, then setting Last boundary equal to i ; h) setting Left = First + (Last-First)/2 and Right = Left+1 ; i) repeating steps f) and g) for Left boundary ; j) repeating steps a) through e) for Right boundary. An adaptive digital echo canceling method according to claim 5, wherein said new threshold coefficient value computing is made according to : Wherein 0 < α ≤ 1 | (n)| is the magnitude of coefficient (n). An adaptive digital echo canceling method according to claim 5, wherein said new coefficient threshold value computing includes : computing the coefficients energy ; setting said threshold to be proportional to said energy. An adaptive echo canceling device for canceling from a transmission network, the echo to a periodically sampled input signal x(n), by synthesizing an echo replica '(n) by using a digital filter the coefficients hi of which are to be adaptively generated, and by subtracting said replica from an echo polluted returning signal y(n) to minimize resulting error signal e(n)=y(n) - (n), said device including : a) means for setting an initial set of filter coefficients ; b) means for setting a coefficient threshold (Thrshld) to a first predefined value ; c) means for generating a set of estimated filter coefficients hi for the (n+1) sample time using for i=0 to D-1 D being a predefined limit and µ being a predefined convergence constant ; d) means for running said coefficient generation for a first predefined number of sampling periods ; e) means for comparing, at said first predefined number of sampling periods, the last computed set of coefficients and discarding any coefficient lower than said threshold ; f) means for readjusting the threshold value based on values of at least one set of filter coefficients; g) means for repeating steps c) through f) up to a second predefined number of sampling rates ; and, h) means for switching the filter coefficient generating operation to : for i=0 to D-1, gamma being a constant and Sign[X] standing for the sign of [X].

Inventors: MENEZ JEAN, ROSSO MICHELE, SCOTTON PAOLO, MENEZ, JEAN, ROSSO, MICHELE, SCOTTON, PAOLO, Rosso, Michèle
Applicants: IBM, INTERNATIONAL BUSINESS MACHINES CORPORATION
Application year: 1991
Main classification: H04B3
IPC codes: H04B3, H03H15, H03H17, H03H21