1. Field of the Invention
This invention relates generally to T1/E1 type communications. More particularly, it relates to the implementation of a digital adaptive equalizer for a T1 or E1 long haul transceiver.
2. Background of Related Art
Telecommunications and more recently data communications commonly utilize T1 or E1 rate long haul transceivers for transmitting large amounts of data. A T1 type signal (1.544 Mb/s) is a standard 24 channel digital communication standard commonly used in North America. An E1 type signal (2.048 Mb/s) is a standard 30 voice channel or 32 payload channel digital communication standard commonly used in Europe. However, because of the similarities in the data structure and physical layer characteristics of T1 and E1 lines, many commercial components are capable of supporting either a T1 or an E1 standard, often with a bit setting or swap of a termination impedance.
As is known, data transmissions suffer dispersion and other debilitating degradations during transmission, particularly when transmitted over a twisted pair and/or cable.
In particular,
Conventional T1 or E1 equalizers 912 are analog devices included in the T1/E1 receiver 904 which are specifically adapted and designed to cancel the affects of the known transmission path 910 (e.g., twisted pair, coaxial cable, etc.) and a known length of that transmission path 910, by equalizing the received signal before processing. Thus, a conventional analog equalizer is chosen or designed based on the specific type of cable used, and on the specific length of the cable. Even given a same type cable, generally speaking the longer the cable, the more affected the received T1/E1 signal is by transmission through the path 910.
Conventional analog devices are typically designed with the specific cable type and sometimes even the length of the cable in mind. Thus, as cable length changes and/or as cable types change, conventional analog T1/E1 equalizers require physical changes to the circuit board containing the T1/E1 long haul transceiver to allow proper equalization of the received T1 or E1 signal. This poses delays and reliability issues when changes to a system are incurred, e.g., when increasing or decreasing the length of a T1/E1 cable.
There is a need for a more flexible T1/E1 equalizer which adapts to changes in T1/E1 cable type and/or length without requiring physical hardware changes to the receiving T1/E1 long haul device.
In accordance with the principles of the present invention, a digital adaptive equalizer for a data communication path comprises a first programmable filter capable of being programmed to implement any of a plurality of filter transfer functions. A filter selector selects any one of the plurality of filter transfer functions for the first programmable filter. A second digital filter receives an output from the first programmable filter.
A method of digitally equalizing a received T1/E1 data signal in accordance with another aspect of the present invention comprises firstly filtering the received T1/E1 data signal using a first digital filter. An output of the first digital filter is adaptively adjusted to accurately match an inverse response of a transmission channel used to transmit the received T1/E1 data signal.
Features and advantages of the present invention will become apparent to those skilled in the art from the following description with reference to the drawings, in which:
The present invention relates to the implementation of a digital adaptive equalizer for a T1/E1 long haul transceiver (i.e., the receiver portion) which is capable of adapting to a wide range of cable types, cable lengths, and/or other data transmission impairments. The digital adaptive equalizer corrects for or equalizes impairments caused in a T1 or E1 type signal which has presumably been degraded upon transmission, particularly where the cable type and/or length may be unknown (or have changed). The digital adaptive equalizer for T1/E1 long haul transceivers in accordance with the principles of the present invention can be implemented easily using low voltage digital technology. The invention has particular application when the T1/E1 signal has been received through an unknown channel (e.g., an unknown cable type, length, and/or other impediments to ideal transmission).
The digital adaptive equalizer contains two filter blocks, i.e., an IIR filter and a FIR filter, together with a filter selector block.
The IIR filter receives the digitized samples of a received analog signal (e.g., from a suitable analog-to-digital (A/D) converter). Preferably, the IIR includes a programmable set of coefficients, wherein each programmable set of coefficients represents a different IIR filter. Preferably, each set of coefficients is chosen to best represent the expected (or anticipated) cable types and/or lengths for which the T1/E1 long haul transceiver is specified. Only a few sets of coefficients are found to be necessary to allow proper digital equalization of a large number of cable types and/or lengths.
The particular set of coefficients to be programmed (and thus the particular IIR filter) is chosen, e.g., using an error estimation algorithm. The error estimation algorithm detects which IIR filter would be optimum for use given a current set of conditions. The error estimation algorithm may be operated as often as necessary, e.g., at start up of a communication system. Thus, whenever a cable type and/or length might be changed (e.g., whenever the system is moved or a cable is replaced), instead of requiring a physical change of analog components as in conventional analog equalizers, a digital adaptive equalizer for T1/E1 long haul applications need only be re-booted.
A filter selector block selects a desired set of coefficients corresponding to the best IIR filter. The coefficients may be programmed into volatile memory (e.g., RAM) or non-volatile memory (e.g., Flash). Alternatively, the coefficients may be hardwired into the IIR filter.
The back end of the digital adaptive equalizer contains an adaptive finite impulse response (FIR) filter. In the disclosed embodiment, the FIR filter uses a least mean square (LMS) algorithm for adaptation to the unknown or changed T1 or E1 transmission channel or medium. The adaptive FIR filter adjusts the output from the IIR filter to accurately match the inverse response of the unknown channel used to transmit the received T1/E1 signal.
Preferably, the adaptive LMS FIR filter is modified to work under the main problems a T1/E1 signal presents for digital adaptive algorithms, i.e., the fact that the source is correlated and the periodic patterns that the signal might contain.
A restored T1 or E1 signal is output from the FIR filter, and thus from the digital adaptive equalizer, in accordance with the principles of the present invention.
In particular, in
An automated gain control (AGC) in the analog portion 171a of the front end 171 receives the raw data signal in analog form, and appropriately couples the received signal to an analog-to-digital (A/D) converter 110 (e.g., an 8-bit A/D converter in the disclosed embodiment). In the disclosed embodiment, the PGA 112 maximizes the dynamic range of the received raw data signal to provide the A/D converter 110 with a constant envelope (e.g., +1 to −1).
The principles of the present invention relate equally to data transmission techniques and data rates other than those specifically at T1 or E1 rates. In the example of the disclosed embodiment using T1 and E1 data rates, the A/D converter 110 is an 8-bit converter which is sampled at a rate of four samples per symbol (i.e., 4×f). In the case of a T1 (i.e., 1.544 Mb/s) digital adaptive equalizer, the input data signal is sampled at four times the T1 rate, or 6.176 MHz. Similarly, in the case of an E1 (i.e., 2.048 Mb/s) digital adaptive equalizer, the input data signal is sampled at four times the E1 rate, or 8.192 MHz.
In the digital portion 171b of the front end 171, the equalizer 100 receives the 8-bit samples from the A/D converter 110, equalizes the digitized input data signal, and outputs 8-bit samples. Of course, the present invention relates equally to sample sizes other than those of the disclosed exemplary embodiment, e.g., 10 bits, 12 bits, 16 bits, etc.
An interpolator 102 in the digital portion 171b of the front end 171 interpolates the signals from the equalizer 100 into an interpolated output signal having a much faster output sampling rate. For example, the exemplary interpolator 102 interpolates and outputs samples at 96 times the T1 or E1 rate (i.e., 148.224 MHz or 196.608 MHz, respectively). The output of the interpolator 102 is passed to a timing recovery stage to achieve the requirements (e.g., telecommunications standards such as jitter specifications) of a recovered T1/E1 signal.
In particular, the digital adaptive equalizer 100 includes an infinite impulse response (IIR) filter 202, followed by a filter selector 204, and then by a finite impulse response (FIR) filter 206.
The IIR filter 202 in the disclosed embodiment is a 7th order filter. The IIR filter 202 effectively opens the signal eye-diagram of the received digitized data signal.
The filter selector 204 selects the optimum IIR filter, and programs the related coefficients into the IIR filter 202 based on that selection. The filter selector 204 also performs timing and process control for the equalizer 100, and converts the 9-bit output from the IIR filter 202 into 8-bit samples for use by the FIR filter 206.
The adaptive FIR filter 206 includes a finite impulse response filter having, e.g., 16 taps. In the disclosed embodiment, the adaptive FIR filter 206 utilizes a least mean squares (LMS) fit, and completes the equalization of the input data samples.
In a specific application, four separate sets of coefficients are available for use by the IIR filter 202, effectively transforming the IIR filter 202 into any one of four different IIR filters without requiring a physical hardware change. The four sets of coefficients are established to represent the IIR filters 202 that best fit to the overall conditions of a wide set of cable types and/or lengths.
The filter selector 204 tests each of the possible IIR filters, and selects at that time the particular IIR filter which yields the least error in the filter selector 204. The output of the selected IIR filter 202 is passed to the adaptive FIR filter 206, which improves the total equalization of the received data signal.
In particular, in
Preferably, the available sets of coefficients for the IIR filter 202 are loaded into the coefficients register area 304 prior to startup of the equalization process.
In the disclosed embodiment, the IIR filter 202 implements the following equations:
In particular, in
Input samples are loaded into 8-bit registers 402–410 constituting an input delay line. The input samples are shifted through the 8-bit registers 402–410 every ¼ T.
Output samples are loaded into output 9-bit registers 448–454 constituting an output feedback delay line.
Multiplication operations are performed in the various multipliers 422–438, and the results are appropriately summed in summer 460, to ultimately arrive at the desired equations for the IIR filter 202.
In particular, as shown in
The PGA 502 converts the 9-bit input signal from the IIR filter 202 into an 8-bit output signal, the error estimator 506 calculates the total absolute error of the current IIR filter, and the peak detector 504 detects the maximum value of the input IIR filtered data signal.
In particular, the PGA 502 includes a multiplexer 612 which selects eight bits from the 9-bit input IIR filtered data samples, depending upon on the value of the maximum data sample detected by the peak detector 504. The PGA 502 includes a divide by 2 block 608, and a least significant bit block, each fed into and selected by the multiplexer 612.
The peak detector 504 stores the value of the maximum data sample detected in the 9-bit register 604. The peak detector 504 includes a comparator 602 to compare an input 9-bit data sample to a currently established maximum data value maintained in a 9-bit register 604. The most significant 8 bits of the maximum value are selected in block 606, which is divided by 2 in divider 630.
The error estimator 506 includes a slicer 614, a summer 616, an absolute value determiner 618, another summer 620, a 24-bit register 624, a comparator 626, and another 24-bit register 628.
The error estimator 506 calculates the total absolute error by comparing the input IIR filtered data sample to a sliced version of the same signal as follows.
where x[n] is the input signal, and a[n] is the sliced signal.
The slicer 614 in the error estimator 204 creates the sliced signal from the maximum value detected. The threshold of the slicer 614 is equal to the maximum value divided by two (i.e., T=M/2).
if—x[n]>T,a[n]=M
if—−T<x[n]<T,a[n]=0
if—x[n]<−T,a[n]=−M
The error estimator 506 stores the total absolute error detected using each of the available IIR filters (e.g., each of the 4 IIR filters in the given example). After each of the available IIR filters are tested, the error estimator 506 and the control block 508 outputs the selection of the IIR filter providing the least absolute error.
In operation, the filter selector 204 waits 256 samples for the IIR filter transient to be completed. The next 16128 data samples are used by the peak detector 504 to find the maximum value of the input IIR filtered data, and the last 16384 data samples are used by the error estimator 506 to calculate the total absolute error.
In particular, as shown in
In the implementation of
The FIR filter 206 preferably includes an adaptive algorithm, e.g., a least mean squares algorithm. A least mean squares algorithm was chosen in the given example because of the properties of a T1/E1 signal, e.g., correlated source, periodic patterns, etc. The FIR filter 206 outputs 8-bit samples, and implements the following equations.
FIR equation:
y[n]=c1x[n]+c2x[n−1]+ . . . +c15x[n−14]+c16x[n−15]
Coefficients correction (LMS algorithm):
Ci(new)=Ci(old)−k·x[n−i]·(y[n]−r[n])
where r[n] is the reference signal used to measure the error of the output signal, and k is the step size.
The signal output from the adaptive FIR filter 206 is sliced using a slicer 822 as shown in
if—y[n]>0.5,r[n]=1
if—y[n]<−0.5,r[n]=−1
otherwise, r[n]=0
The coefficients (712–716 in
The step size in the adaptive FIR filter 206 is a number always lower than one, e.g., ½, ¼, 1/16, etc. The step size is reduced as the algorithm converges, and can be set equal to zero (i.e., no coefficients correction).
In order to accomplish fast convergence of the least mean square algorithm, the initial value of the coefficients is set to the autocorrelation function of an AMI-RZ (amplitude mark inversion, return to zero) signal, characteristic in the transmission of a T1/E1 signal. It is common to transmit periodic signals in a T1/E1 transmission. Some alarms to be transmitted have this characteristic. A periodic pattern causes a major problem to equalization algorithms.
This issue is solved, e.g., by using a periodic pattern detector 113 as shown in
A digital, adaptive equalizer in accordance with the principles of the present invention provides adaptation to a much larger range of cable types and/or lengths, particularly with automatic reprogramming of coefficients for the IIR filter.
While the invention has been described with reference to the exemplary embodiments thereof, those skilled in the art will be able to make various modifications to the described embodiments of the invention without departing from the true spirit and scope of the invention.
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