Method for adaptive hybrid selection during ADSL modem training

Information

  • Patent Grant
  • 7194024
  • Patent Number
    7,194,024
  • Date Filed
    Wednesday, January 29, 2003
    21 years ago
  • Date Issued
    Tuesday, March 20, 2007
    17 years ago
Abstract
The methodology accomplishes adaptive hybrid selection during ADSL modem training. The adaptive hybrid selection method maximizes performance for ADSL modems in the presence of various impairments on the line by optimally selecting the appropriate hybrid based on line conditions. Specifically, the adaptive hybrid selection method is based on a measure directly coupled to the channel capacity.
Description
BACKGROUND

1. Field


This invention relates generally to Asymmetric Digital Subscriber Line (ADSL) modems, and more particularly to a method of adaptive hybrid selection during ADSL modem training.


2. Description of the Prior Art


The hybrid is an analog electrical network (part of the analog front end-AFE) in the modem that is responsible for 2 to 4 wire conversion i.e., the hybrid allows the transmit signal from one pair of the 4-wire side (transmit) to pass directly on to the 2-wire side (subscriber loop) and at the same time suppresses the transmit signal component on the other pair of the 4-wire side (receive). Ideally, the hybrid should completely suppress the transmit energy on the receive wire pair. However, in reality since the line impedance changes from one loop to the next, the hybrid can only be designed to match an “average” loop impedance. In many cases, with bridge taps, HPNA devices and other devices on the line, the loop impedance can change substantially from the nominal value. In these cases, the hybrid is mismatched to the line and the transmit energy can completely dominate the receive signal and receive performance suffers. In order to reduce the effect of hybrid mismatch on receive performance, often multiple hybrids are designed into the modem. The important task then becomes one of selecting the hybrid that maximizes receive performance.


It would therefore be desirable and advantageous in view of the foregoing to provide a methodology for adaptive hybrid selection based on the estimated noise floor during regular ADSL modem initialization.


SUMMARY OF THE INVENTION

The present invention is directed to a methodology for adaptive hybrid selection during ADSL modem training based on the estimated noise floor during regular ADSL modem initialization. The adaptive hybrid selection method maximizes performance for ADSL modems in the presence of various impairments on the line by optimally selecting the appropriate hybrid based on line conditions. Specifically, the adaptive hybrid selection method is based on a measure directly coupled to the channel capacity.


A method according to one embodiment of the invention comprises the steps of determining a set of N representative test loops; defining a first parametric cost function directly coupled to channel capacity; evaluating the first cost function in terms of the cost function parameters for each hybrid in response to estimated noise floors associated with each hybrid for each representative test loop; determining the optimum values of the cost function parameters to maximize the data rate for each test loop by selecting the hybrid resulting in the minimum first cost function value associated with a selected subscriber loop; and using the optimum parameters estimated as above in the cost function during ADSL modem training to determine the best hybrid to select for each training attempt by choosing the hybrid that results in the minimum value for the cost function.





BRIEF DESCRIPTION OF THE DRAWINGS

Other aspects and features of the present invention and many of the attendant advantages of the present invention will be readily appreciated as the same become better understood by reference to the following detailed description when considered in connection with the accompanying drawing wherein:



FIG. 1 is a flowchart depicting a method for adaptively selecting a hybrid based on a measure (cost function) ‘J’ during ADSL modem training and that is directly coupled to the channel capacity according to one embodiment of the present invention; and



FIG. 2 is a flowchart depicting a method of determining the empirical constant parameters of the cost function ‘J’ shown in FIG. 1.





While the above-identified drawing figure sets forth particular embodiments, other embodiments of the present invention are also contemplated, as noted in the discussion. In all cases, this disclosure presents illustrated embodiments of the present invention by way of representation and not limitation. Numerous other modifications and embodiments can be devised by those skilled in the art which fall within the scope and spirit of the principles of this invention.


DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

A method 10 is shown in the FIG. 1 for adaptively selecting the hybrid based on a measure ‘J’ during ADSL modem training and that is directly coupled to the channel capacity. During ADSL modem training the cost function J is evaluated for each hybrid position as seen in block 12, and the hybrid corresponding to the minimum value of J is selected as seen in block 14. According to the most preferred embodiment that is discussed herein, the cost function ‘J’ is given by,







J
=


A
*




i

ɛ

S









log
2



(

nf_quiet


(
i
)


)




+

B
*

f


(
nf_echo
)





,





where


A and B are empirical constants estimated based on the performance of the different hybrids over a set of representative test loops. An exact procedure for determining these constants is described later with reference to FIG. 2.


“nf_quiet(i)” is the estimated quiet noise floor for tone index-i with no transmit signal. It is estimated as








nf_quiet


(
i
)


=


1
N






f
=
1

N











Y
f



(
i
)




2




,





where Yf is the Fast Fourier Transform (FFT) of the fth received Discrete Multi-Tone (DMT) frame and Yf (i) is the value of Yf at tone index-i. The quiet noise floor for an ADSL Customer Premises Equipment (CPE) modem can be reliably estimated over 64 DMT frames during the first 512 frames of R-REVERB1 during which the CPE modem is transmitting the REVERB signal and receiving a QUIET signal. The hybrid selection importantly must be done early on in the training before the Automatic Gain Control (AGC) settings are decided. Since the transmit and receive of the modem are completely synchronized, estimating “nf_quiet(i)” over the non-overlapping receive band while transmitting the REVERB signal is equivalent to estimating it while transmitting a QUIET signal.


The set “S” for summation of the “nf_quiet” noise floor is a part of the receive band. For an ADSL CPE modem, this can be chosen to be S={37, 38, . . . , 119}.


The “nf_echo” term is the sum of the echo signal power over the transmit band. It is determined as follows:






nf_echo
=




i
=
TX_start

TX_end







nf_echosignal


(
i
)








and







nf_echosignal


(
i
)


=


1
N






f
=
1

N











Y
f



(
i
)




2




,





where TX_start and TX_end are the start and end of the transmit signal. For an ADSL CPE modem, this could be TX start=6 and TX end=31.


As in the case of “nf_quiet”, “nf_echo” can be reliably estimated over 64 received DMT frames during the first 512 frames of R-REVERB1 for an ADSL CPE modem.


The function “f(nf_echo)” is the effect of the transmit signal echo on the channel capacity. According to one embodiment of the present invention, this can be chosen to be the “log” function.


The cost function ‘J’ is evaluated for each hybrid (based on the estimated noise floors for each hybrid). As stated herein above for an ADSL CPE modem, 64 DMT frames are sufficient for a reliable estimate of the “nf_quiet” and “nf_echo” noise floors for each hybrid. Further, some amount of “settle” time for the relay/switch to settle must be given, where 5 milliseconds of settle time is believed by the present inventor to be sufficient in most cases. The hybrid that results in the minimum value of ‘J’ is then chosen for that particular loop.


An important task is to determine the weighting constants “A” and “B” of the cost function ‘J’, as one method 100 shows in FIG. 2, for best performance across all possible loops for the particular switchable hybrid architecture. As seen in block 102, a set of representative test loops is first determined. Next, the cost function ‘J’ is estimated in terms of the parametric constants for each hybrid and for each test loop as shown in block 104. Finally, as shown in block 106, the parametric constants are selected such that for each test loop, the cost function ‘J’ is minimized for the hybrid that results in the maximum data rate for that test loop. A more detailed methodology for doing this according to one embodiment comprises the following steps:


First, determine a set of N representative test loops. For example, the test loops specified in the ADSL standards can be chosen.


Second, for each test loop, estimate the values of






J1
=





i

ɛ

S










log
2



(

nf_quiet


(
i
)


)







and





J2


=

f


(
nf_echo
)








for each hybrid (assume M hybrids). In order to do this, nf_quiet(i) and nf_echo(i) must be estimated. This can be done as specified in the previous section.


Third, for each test loop#k, determine the modem connect rate R(n,k) with each hybrid#n. Based on the connect rate, determine the best hybrid n0=n0(k) for each test loop.


Fourth, let J1(n,k) denote the value of J1 for hybrid#n and test loop#k. Similarly, define J2(n,k) as the value of J2 for hybrid#n and test loop#k.


Fifth, form the following cost function:










H


(

A
,
B

)


=





k










n
!=
n0









Sign


[


J


(

n
,
k

)


-

J


(

n0
,
k

)



]


*


(


R


(

n0
,
k

)


-

R


(

n
,
k

)



)


R


(

n0
,
k

)












=





k










n
!=
n0








Sign
[


A
*

(


J1


(

n
,
k

)


-

J1


(

n0
,
k

)



)


+

B
*















(


J2


(

n
,
k

)


-

J2


(

n0
,
k

)



)

]

*


(


R


(

n0
,
k

)


-

R


(

n
,
k

)



)


R


(

n0
,
k

)









=




Sign


(
A
)


*



k










n
!=
n0








Sign
[


(


J1


(

n
,
k

)


-

J1


(

n0
,
k

)



)

+

C
*
















(


J2


(

n
,
k

)


-

J2


(

n0
,
k

)



)

]

*


(


R


(

n0
,
k

)


-

R


(

n
,
k

)



)


R


(

n0
,
k

)











where only the sign of A is important and C=B/A.


Sixth, find “A=+/−1” and “C=real number” to maximize the value of H(A,C). Each term in the above maximization is weighted by the percent difference in data rate. This guarantees that incorrect decisions that result in a substantially lower data rate from the optimal are minimized; and


Seventh, for each of the above terms






C
=


C


(

n
,
k

)


=

-


(


J1


(

n
,
k

)


-

J1


(

n0
,
k

)



)


(


J2


(

n
,
k

)


-

J2


(

n0
,
k

)



)









will result in that term equal to zero. Hence, sorting the values C(n,k) for all n and k will give (M−1)*N sorted values or (M−1)*N+1 intervals over which the value of the above cost function H is constant (since H is dependent only on the sign of the terms). Evaluate the value of H over each of the (M−1)*N+1 intervals and choose the interval that gives the maximum of the absolute value of H. Then A=(Sign of H) and C=(the mid-point) for the corresponding interval.


As an example for an ADSL CPE modem with multiple hybrids tuned to match the ADSL standard bridged tap test loops, the values of A and B can be chosen to be: A=1, B=3.847.


In summary explanation, a methodology has been described to accomplish adaptive hybrid selection during ADSL modem training. The adaptive hybrid selection process maximizes performance for ADSL modems in the presence of various impairments on the line by optimally selecting the appropriate hybrid based on line conditions.


This invention has been described in considerable detail in order to provide those skilled in the ADSL hybrid art with the information needed to apply the novel principles and to construct and use such specialized components as are required. In view of the foregoing descriptions, it should be apparent that the embodiments of the invention represent a significant departure from the prior art in construction and operation. However, while particular embodiments of the invention have been described herein in detail, it is to be understood that various alterations, modifications and substitutions can be made therein without departing in any way from the spirit and scope of the invention, as defined in the claims which follow. For example, embodiments of the invention shall be understood to using software implementations of the methods set forth in the claims.

Claims
  • 1. A method of adaptive hybrid selection during modem training, the method comprising: determining a set of N representative test loops;defining a first parametric cost function directly coupled to channel capacity as
  • 2. The method according to claim 1 wherein selecting the hybrid that results in minimum ‘J’ comprising: estimating the optimum values of the cost function parameters to maximize the data rate for each test loop by selecting the hybrid resulting in the minimum cost function value associated with a selected subscriber loop; andusing the optimum values estimated as above in the cost function during modem training to determine the best hybrid to select for each training attempt by choosing the hybrid that results in the minimum value for the cost function.
  • 3. The method according to claim 1 further comprising estimating nf_quiet(i) as
  • 4. The method according to claim 1 further comprising estimating nf_echo as
  • 5. The method according to claim 1 further comprising: estimating for each representative test loop, the values of
US Referenced Citations (28)
Number Name Date Kind
4246582 Kondo et al. Jan 1981 A
4785465 Lang et al. Nov 1988 A
4805215 Miller Feb 1989 A
5416776 Panzarella et al. May 1995 A
5506868 Cox et al. Apr 1996 A
5572517 Safadi Nov 1996 A
5623514 Arai Apr 1997 A
5696765 Safadi Dec 1997 A
5764694 Rahamim et al. Jun 1998 A
5802169 Frantz et al. Sep 1998 A
5999540 McGhee Dec 1999 A
5999565 Locklear, Jr. et al. Dec 1999 A
6021158 Schurr et al. Feb 2000 A
6101216 Henderson et al. Aug 2000 A
6160843 McHale et al. Dec 2000 A
6163579 Harrington et al. Dec 2000 A
6185280 Jarboe et al. Feb 2001 B1
6192109 Amrany et al. Feb 2001 B1
6208732 Moschytz et al. Mar 2001 B1
6295343 Hjartarson et al. Sep 2001 B1
6385203 McHale et al. May 2002 B2
6385252 Gradl et al. May 2002 B1
6400772 Chaplik Jun 2002 B1
6483870 Locklear, Jr. et al. Nov 2002 B1
6724890 Bareis Apr 2004 B1
6795405 Mladenovic et al. Sep 2004 B1
6996200 Schubert et al. Feb 2006 B2
20010048716 Gough et al. Dec 2001 A1
Related Publications (1)
Number Date Country
20040146096 A1 Jul 2004 US