Patent Publication Number: US-2015085995-A1

Title: Selt and delt based diagnostic methods &amp; systems for twisted pair telephone lines

Description:
TECHNICAL FIELD 
     The subject matter described herein relates generally to the field of telecommunication, and more particularly to systems and methods for automated determinations of a physical configuration and diagnostics of twisted pair telephone lines in a digital subscriber line (DSL) network. 
     BACKGROUND 
     Digital subscriber line (DSL) technologies generally include digital subscriber line equipment and services using packet-based architectures, such as, for example, Asymmetric DSL (ADSL), High-speed DSL (HDSL), Symmetric DSL (SDSL), and/or Very high-speed/Very high-bit-rate DSL (VDSL). Such DSL technologies can provide extremely high bandwidth over a twisted pair line and offers great potential for bandwidth-intensive applications. DSL services in the 30K-30 MHz band are however more dependent on line conditions (for example, the length, quality and environment of the line) than is Plain Old Telephone Service (POTS) operating in the &lt;4K band. 
     While some lines (loops) are in good physical condition for implementing DSL (for example, having short to moderate lengths with operative micro-filters or splitters correctly installed and with no bridged taps and no bad splices), many lines are not as suitable. For example, line length varies widely, the wire gauge for a line may not be consistent over the length of the line (having two or more different gauges spliced together), micro-filters may be missing or inoperative, and many existing lines have one or more bridged taps (a length of wire pair that is tapped off a line at one end or anywhere along the length of line and is unconnected or poorly terminated). 
     Assessment of a line&#39;s physical configuration (referred to herein as “line diagnostics”) is an important step in the implementation of any DSL network. Physical line parameters characterized by line diagnostics includes: detection of any of the various faults listed above; localization of detected faults; and characterization of the fault with respect to one or more descriptors (e.g., a length of a bridged-tap). Such physical line diagnostics are important because the bit-rate that can be achieved for a given type of DSL technology is dependent on the physical configuration of the line. Spectrum management activities performed over a population of given lines, for example to minimize crosstalk problems, are also dependent on the physical configuration of a line. 
     Line diagnostics in the art generally include single-ended line testing (SELT) techniques estimating a line transfer function using equipment disposed one end of the line with any termination at the other end but without data collection at the second end, and double-ended line testing (DELT) techniques that directly measure a line transfer function with equipment disposed at both ends of the line. SELT techniques generally employ reflectometry, relying on the fact that as a signal propagates through a medium, part of it is reflected by discontinuities in that medium. Reflectometric techniques include frequency domain reflectometry (FDR) where a waveform of swept frequency (multi-tone) is sent down the line, and time domain reflectometry (TDR) where a pulsed waveform is sent down the line. In either form, an echo response is collected and analyzed with respect to one or more of at least frequency, amplitude, and polarity to estimate the line configuration (e.g., detect one or more of the line faults above). 
     While line diagnostics based on either SELT or DELT has been extensively studied, automated line diagnostic algorithms remain a subject of intense study. Accurate estimation of line configuration depends on avoiding misdetection resulting from either a first type of error where algorithm sensitivity to real features is too low, or a second type of error where sensitivity to spurious features is too high. Many TDR-based diagnostic algorithms rely on identifying from a bank of possible templates a line configuration template having the highest correlation with the echo response of the line under test. Accuracy of a TDR-based diagnostic algorithm relying on a template bank is therefore a function of the size of the bank. As larger banks increase processing complexity and processing time, diagnostic results are practically limited. 
     Techniques improving detection capability as well as accuracy of automated line diagnostics are therefore very useful. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Embodiments of the present invention are illustrated by way of example, and not by way of limitation, and can be more fully understood with reference to the following detailed description when considered in connection with the figures in which: 
         FIG. 1  illustrates an exemplary network architecture in which embodiments of the present invention may operate; 
         FIG. 2A  is a flow diagram illustrating a line diagnostics method including joint processing of SELT and DELT data, in accordance with an embodiment of the present invention; 
         FIG. 2B  is a flow diagram illustrating a method of joint processing SELT and DELT data to determine a physical configuration of a line, in accordance with an embodiment; 
         FIG. 3  is a functional block diagram illustrating a system configured to perform joint processing of SELT and DELT data collected from the exemplary network illustrated in  FIG. 1 , in accordance with an embodiment; 
         FIG. 4A  is a flow diagram illustrating an iterative SELT diagnostic method employing ratio tests, in accordance with an embodiment; 
         FIG. 4B  is a flow diagram illustrating exemplary peak/dip ratio tests performed on a time domain echo response, performed as a portion of the iterative SELT diagnostic method illustrated in  FIG. 4A , in accordance with an embodiment; 
         FIG. 4C  is a flow diagram further illustrating exemplary peak/dip ratio tests performed on a time domain echo response, performed as a portion of the iterative SELT diagnostic method illustrated in  FIG. 4A , in accordance with an embodiment; 
         FIG. 4D  is a flow diagram illustrating a method for adjusting the echo response based on the estimation of the physical configuration that is performed as a portion of the iterative SELT diagnostic method illustrated in FIG.  4 A, in accordance with an embodiment; 
         FIG. 5A  is an exemplary time domain echo response that may be operated on following the iterative SELT diagnostic method illustrated n  FIG. 4A ; 
         FIG. 5B  is an exemplary time domain echo response that has been adjusted following the method illustrated in  FIG. 4D , in accordance with an embodiment; 
         FIG. 6  is a functional block diagram illustrating a system configured to perform the iterative SELT diagnostic method illustrated in  FIG. 4A  on SELT data collected from the exemplary network illustrated in  FIG. 1 , in accordance with an embodiment; and 
         FIG. 7  is a diagrammatic representation of a machine in the exemplary form of a computer system that is configured to automatically perform at least one, and preferably all, of the functional blocks illustrated in  FIG. 3  and  FIG. 6 , in accordance with embodiments of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Described herein are methods and systems for twisted pair telephone line diagnostics. For brevity, the exemplary embodiments are described in the context of a DSL network. As used herein, “line diagnostics” refers to detection or determination of a physical line configuration parameter, such as, but not limited to, detection of a series fault, shunt fault, and bridged tap, localization of a fault, a characterization of the fault (e.g., bridged tap length). The diagnostic methods described herein, though illustrated for particular line configuration parameters, may be readily apply by those of ordinary skill in the art toward diagnosis of any other physical line configuration parameters which are known in the art to generate similar physical phenomena on a line. For example, it is envisioned that at least microfilter problems can also be detected and/or characterized by the diagnostics techniques described herein. Further extension of the methods and systems described herein may be made to improve detection of changes in wire gauge, for example. 
     Embodiments of the present invention improve accuracy and fault detection capability through at least one of: joint processing of SELT and DELT data; tests analyzing relative strengths of peaks and/or dips to envelope and peaks to dips in a time domain echo response; and iterative diagnostics whereby an echo response is adjusted through signal processing techniques between successive performance of a detection algorithm. In embodiments, more than one of the diagnostic systems and methods described herein are employed in combination to improve accuracy and fault detection capability. For example, in one embodiment where SELT and DELT data are jointly processed, analysis of the SELT data may employ the ratio tests described in the context of SELT diagnostics. Similarly, the SELT diagnostics employing ratio tests described herein are, in an embodiment, combined with iterative adjustment of the echo response. In further embodiments, iterative SELT diagnostics employing ratio tests are employed as the SELT analysis portion in joint processing of SELT and DELT data. 
     In the following description, numerous specific details are set forth such as examples of specific systems, languages, components, etc., in order to provide a thorough understanding of the various embodiments. It will be apparent, however, to one skilled in the art that these specific details need not be employed to practice the disclosed embodiments. In other instances, well known materials or methods have not been described in detail in order to avoid unnecessarily obscuring the disclosed embodiments. 
     In addition to various hardware components depicted in the figures and described herein, embodiments further include various operations which are described below. The operations described in accordance with such embodiments may be performed by hardware components or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the operations. Alternatively, the operations may be performed by a combination of hardware and software, including software instructions that perform the operations described herein via memory and one or more processors of a computing platform. 
     Embodiments also relate to a system or apparatus for performing the operations herein. The disclosed system or apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer or accessed through cloud storage. Such a computer program may be stored in a computer readable storage medium, such as, but not limited to, any type of disk including floppy disks, optical disks, flash, NAND, solid state drives (SSDs), CD-ROMs, magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any similar type of non-transitory media suitable for storing electronic instructions on a time scale that is sufficient to be considered non-transitory by one of ordinary skill in the art. In one embodiment, a non-transitory computer readable storage medium having instructions stored thereon, causes one or more processors within a Diagnostics Device to perform the diagnostic methods and operations described herein. In another embodiment, the instructions to perform such methods and operations are stored upon a non-transitory computer readable medium for later execution. 
       FIG. 1  illustrates an exemplary network architecture  100  in which embodiments may operate in compliance with the G.997.1 standard (also known as G.ploam). Asymmetric Digital Subscriber Line (ADSL) systems (one form of Digital Subscriber Line (DSL) systems), which may or may not include splitters, operate in compliance with the various applicable standards such as ADSL1 (G.992.1), ADSL-Lite (G.992.2), ADSL2 (G.992.3), ADSL2-Lite G.992.4, ADSL2+(G.992.5) and the G.993.x emerging Very-high-speed Digital Subscriber Line or Very-high-bitrate Digital Subscriber Line (VDSL) standards, as well as the G.991.1 and G.991.2 Single-Pair High-speed Digital Subscriber Line (SHDSL) standards, all with and without bonding. 
     The G.997.1 standard specifies the physical layer management for ADSL transmission systems based on the clear, Embedded Operation Channel (EOC) defined in G.997.1 and use of indicator bits and EOC messages defined in G.992.x standards. Moreover, G.997.1 specifies network management elements content for configuration, fault and performance management. In performing the disclosed functions, systems may utilize a variety of operational data (which includes performance data) that is available at an Access Node (AN). 
     In  FIG. 1 , a user&#39;s terminal equipment  102  (e.g., a Customer Premises Equipment (CPE) device or a remote terminal device, network node, LAN device, etc.) is coupled to a home network  104 , which in turn is coupled to a Network termination (NT) Unit  108 . DSL Transceiver Units (TU) are further depicted (e.g., a device that provides modulation on a DSL loop or line). In one embodiment, NT unit  108  includes a TU-R (TU Remote),  122  (for example, a transceiver defined by one of the ADSL or VDSL standards) or any other suitable network termination modem, transceiver or other communication unit. NT unit  108  also includes a Management Entity (ME)  124 . Management Entity  124  may be any suitable hardware device, such as a microprocessor, microcontroller, or circuit state machine in firmware or hardware, capable of performing as required by any applicable standards and/or other criteria. Management Entity  124  collects and stores, among other things, operational data, performance data (e.g., SELT and/or DELT data) in its Management Information Base (MIB), which is a database of information maintained by each ME capable of being accessed via network management protocols such as Simple Network Management Protocol (SNMP), an administration protocol used to gather information from a network device to provide to an administrator console/program or via Transaction Language 1 (TL1) commands, TL1 being a long-established command language used to program responses and commands between telecommunication network elements. 
     Each TU-R  122  in a system may be coupled with a TU-C (TU Central) in a Central Office (CO) or other central location. TU-C  142  is located at an Access Node (AN)  114  in Central Office  146 . A Management Entity  144  likewise maintains an MIB of operational data pertaining to TU-C  142 . The Access Node  114  may be coupled to a broadband network  106  or other network, as will be appreciated by those skilled in the art. TU-R  122  and TU-C  142  are coupled together by a line (loop)  112 , which in the case of ADSL may be a twisted pair line, such as a telephone line, which may carry other communication services besides DSL based communications. Either Management Entity  124  or Management Entity  144  may implement and incorporate a diagnostic/management device  170 , as described herein. The diagnostic/management device  170  may be operated by a service provider or may be operated by a third party, separate from the entity which provides DSL services to end-users. Thus, in accordance with one embodiment diagnostic/management device  170  is operated and managed by an entity which is separate and distinct from a telecommunications operator responsible for a plurality of digital communication lines. Management Entity  124  or Management Entity  144  may further store collected WAN information and collected LAN information within an associated MIB. 
     Several of the interfaces shown in  FIG. 1  are used for determining and collecting probe and/or operational data. The Q interface  126  provides the interface between the Network Management System (NMS)  116  of the operator and ME  144  in Access Node  114 . Parameters specified in the G.997.1 standard apply at the Q interface  126 . The near-end parameters supported in Management Entity  144  may be derived from TU-C  142 , while far-end parameters from TU-R  122  may be derived by either of two interfaces over the UA interface. Indicator bits and EOC messages may be sent using embedded channel  132  and provided at the Physical Medium Dependent (PMD) layer, and may be used to generate the required TU-R  122  parameters in ME  144 . Alternately, the Operation, Administration and Maintenance (OAM) channel and a suitable protocol may be used to retrieve the parameters from TU-R  122  when requested by Management Entity  144 . Similarly, the far-end parameters from TU-C  142  may be derived by either of two interfaces over the U-interface. Indicator bits and EOC message provided at the PMD layer may be used to generate the required TU-C  142  parameters in Management Entity  124  of NT unit  108 . Alternately, the OAM channel and a suitable protocol may be used to retrieve the parameters from TU-C  142  when requested by Management Entity  124 . 
     At the U interface, there are two management interfaces, one at TU-C  142  (the U-C interface  157 ) and one at TU-R  122  (the U-R interface  158 ). Interface  157  provides TU-C near-end parameters for TU-R  122  to retrieve over the line  112 . Similarly, U-R interface  158  provides TU-R near-end parameters for TU-C  142  to retrieve over the U interface/loop/line  112 . The parameters that apply may be dependent upon the transceiver standard being used (for example, G.992.1 or G.992.2). The G.997.1 standard specifies an optional Operation, Administration, and Maintenance (OAM) communication channel across the U interface. If this channel is implemented, TU-C and TU-R pairs may use it for transporting physical layer OAM messages. Thus, the TU transceivers  122  and  142  of such a system share various operational data maintained in their respective MIBs. 
     Generally, the diagnostic methods and systems described herein may be performed at any point with the network architecture  100 . As shown in  FIG. 1 , either or both ends of the line  112 , include SELT and DELT data collection. For example, in one embodiment, a signal generator and data collector for measuring a SELT parameter at one of the two ends of the line  112  is disposed at the CO side (TU-C  142 ). In an alternate embodiment, the signal generator and data collector for measuring a SELT parameter at one of the two ends of the line  112  is disposed at the CPE side (TU-R  122 ). A data collector for collecting a DELT line transfer function measurement performed by transmission from an opposite end of the line  112  may similarly be disposed at either or both ends of the line  112 . As further illustrated in  FIG. 1 , the SELT/DELT data generated for the line  112  is relayed from the measurement data collector to the diagnostic/management device  170 . The diagnostic/management device  170  then performs one or more of the methods described herein to analyze the SELT/DELT data received for a given line  112  to arrive at an estimation of one or more line parameters, such as but not limited to detection of one or more line faults. 
       FIG. 2A  is a flow diagram illustrating an automated line diagnostics method  201  including joint processing of SELT and DELT data, in accordance with an embodiment of the present invention. Generally, embodiments illustrated by  FIG. 2A  leverage the individual strengths of SELT and DELT data received at operations  205 ,  210 , and the respective analysis performed at operations  215  and  220 , to improve detection capability and accuracy. As such, three determinations are made via analysis of the SELT and DELT data with diagnostic results output at operation  225  based only on SELT data, diagnostic results output at operation  230  based only on DELT data, and diagnostic results are output at operation  250  based on joint processing of SELT and DELT data at operation  240 . 
     The joint processing of SELT and DELT data at operation  240  improves diagnostic capability first with improved fault detection capability. Recognizing that some faults are better detected through one or other of SELT and DELT data, at a minimum joint processing offers the benefit of additive detection capability. For example, because short bridged taps do not affect DELT data as much as they do SELT data, joint processing of SELT data with DELT data improves the detection capability for short bridged taps over that of DELT-based diagnostics alone. Similarly, fault localizing (the act of estimating the distance from an end of the line where a detected fault is) capability is improved beyond that of SELT if jointly processed with DELT data. 
     The joint processing SELT and DELT data at operation  240  however does not merely result in an additive effect because, as described further herein, the SELT and DELT data analysis may each be adjusted in view of their concurrent analysis of a same line to effectively increase the detection sensitivity of each analysis technique without sacrificing accuracy to the extent that would otherwise occur in lieu of joint processing. In one capacity therefore, joint processing entails employing SELT (DELT) data to prevent false positives (i.e., detecting a fault which is not real) which might happen if only DELT(SELT) data is employed with a similar detection threshold. With joint processing enabling greater detection sensitivity, faults not having a significant effect in either one SELT or DELT data also become detectable. 
       FIG. 2B  is a flow diagram illustrating a method  202  for joint processing SELT and DELT data to determine a physical configuration of a line, in accordance with an embodiment. The method  202  illustrates one embodiment of the joint processing performed at operation  204  in  FIG. 2A . As earlier introduced, SELT data is received at operation  205  and DELT data is received at operation  210 . For a given communication line (e.g., twisted pair line  112  in  FIG. 1 ), the SELT data at least includes a TDR echo response, or an FDR echo response, accuracy of the echo response (variance), and a scale factor from which the time domain response may be determined. The SELT data may be collected via any technique known in the art, such as, but not limited to TDR and FDR. The DELT data at least includes one or more parameter from which the transfer function (H) is measured. For example, the DELT data may include measures of line insertion loss and line attenuation, and other measures which are reported per-tone, such as, but not limited to, bit distribution, signal-to-noise ratio (SNR), power spectral density (PSD), quiet line noise (QLN), and fine gains. 
     At operation  255 , the SELT data is analyzed for the purpose of diagnosing physical line parameters. Likewise, at operation  260  physical line parameters are determined based on the DELT data. As shown in  FIG. 2B , the operations  255  and  260  are performed independently. Notably, at least one of the SELT data diagnostic algorithm and DELT data diagnostic algorithm employed at operations  255  and  260 , respectively, entail one or more line fault detection algorithms. Such algorithms generally include at least one analysis parameter that affects that algorithm&#39;s fault detection sensitivity. To further illustrate, where the SELT analysis algorithm entails analysis of a feature in an echo response (e.g., a peak), one exemplary analysis parameter is the detection criteria upon which a line fault is associated with the feature. 
     One exemplary SELT detection algorithm based on ratio tests to assess relative strengths of features in an echo response is further described elsewhere herein and each of the thresholds described for those ratio tests is another example of an analysis parameter. In other embodiments, where the SELT-based detection algorithm entails matching an echo response to a template stored in a bank of templates, the threshold upon which a particular template is determined to be a sufficient match is an exemplary analysis parameter. Similarly, any line fault detection criteria employed by the DELT data-based diagnostic algorithm is an example of an analysis parameter in the context of the present invention. Any SELT data-based diagnostic algorithm known in the art and having one or more analysis parameter that affects the algorithm&#39;s detection sensitivity may be utilized at operation  255 . Similarly, any DELT data-based diagnostic algorithm known in the art and having one or more analysis parameter that affects an algorithm&#39;s detection sensitivity may be utilized at operation  260 . 
     At operation  270 , the results generated by the SELT-based diagnostics operation  255  are compared to the results generated by the DELT-based diagnostics operation  260 . Operation  270  entails comparing line parameter estimates generated by operations  255  and  260  and classifying those attributes as compatible or incompatible with each other. Generally, this comparison is performed only for the subset of line parameters that are estimated by both SELT and DELT-based diagnostics. In other words, if the two diagnostics may potentially yield the same result, the comparison is to determine if a same or otherwise consistent result was yielded for a particular line. The line attributes that are to be compared at operation  270  are therefore dependent on the diagnostic algorithms employed at operations  260  and  270 . As such, any attribute known in the art to be discernible through both a SELT-based diagnostic and a DELT-based diagnostic may be compared at operation  270 . Such line attributes, include, but are not limited to, a line length, a detection of any of a series fault (e.g., bad splice); a shunt fault; a bridged-tap; a faulty microfilter, a location of the fault, and additional attributes of the fault, e.g., severity or length of a detected fault. 
     As one example, where two bridged taps are detected by SELT-based diagnostic operation  255  and one bridged tap of a certain length is estimated by the DELT-based diagnostic operation  260 , one bridged tap having been verified through both diagnostic techniques is declared to be a compatible attribute of the SELT-based and DELT-based line configuration estimates. In contrast, the second bridged tap not detected by the DELT-based diagnostics is identified as an incompatible attribute. 
     For any attributes identified as incompatible, such as the unverified detection of the second bridged tap described in the above example, the method  202  proceeds to determine if a subsequent iteration of one or both of the SELT-based and DELT-based diagnostic operations  255  and  260  is to be performed. This determination may be based on parameters controlling the automated execution of the method  202 . In one embodiment, the determination is based on a number of iterations thus far performed on a given set of SELT and DELT data for a line. For example, if less than a threshold number of iterations have been performed, the method  202  proceeds to operation  290  in preparation for performing an additional iteration. In another embodiment, the determination to proceed to operation  290  is based on a value of one or more of the analysis parameters employed in the SELT-based or DELT-based diagnostics performed at operations  255 ,  260 . For example, where a threshold controlling detection of the attribute identified as incompatible is not yet at the limit of a predetermined range, the method  202  proceeds to operation  290  for a further iteration of the method  202  with the detection threshold adjusted appropriately within the predetermined range. 
     Where the method  202  is to proceed to operation  290 , one or more analysis parameters employed in at least one of the SELT or DELT-based diagnostic algorithms is adjusted. Such adjustments may be made to address concurrently a plurality of line attributes identified as incompatible or such adjustments may be made to address a given one of the plurality so as to attempt to serially eliminate the attributes identified as incompatible. In either case, the iterative process may arrive at an estimation of the line configuration with relatively more compatible results and a higher confidence of a correct line diagnosis. 
     While an analysis parameter adjustment may take different forms dependent on the attribute identified as incompatible, the analysis parameter is in the exemplary embodiment adjusted toward eliminating the incompatible attribute identified during the prior iteration. For example, an adjustment may be made toward eliminating a potential type-I error where one of the SELT-based or DELT-based analyses failed to detect a true fault. In one such embodiment, a line fault detection threshold employed in the SELT or DELT analysis is adjusted so as to increase the detection sensitivity of a fault not detected by that analysis in a prior iteration. For the example where the DELT-based analysis at operation  260  did not detect the second bridged tap, bridged tap detection criteria employed by the DELT-based analysis are adjusted by a predetermined amount to increase bridged tap sensitivity. This increase may be performed incrementally with each iteration of the method  202  until either a limit in the bridged tap detection sensitivity is reached or a compatible result is obtained. 
     Alternatively, an adjustment may be made toward eliminating a potential type-II error where one of the analyses detected a non-existent fault. In one such embodiment, a line fault detection threshold employed in one of the SELT or DELT analysis is adjusted so as to decrease the detection sensitivity of a fault detected in a prior iteration. For the example, where the DELT-based analysis at operation  260  did not detect the second bridged tap, bridged tap detection criteria employed in the SELT-based analysis are adjusted by a predetermined amount to decrease bridged tap sensitivity. 
     In further embodiments, determination of how a SELT-based analysis or DELT-based analysis parameter is to be adjusted depends on a predetermined bias for one or the other with respect to a given incompatible attribute. For the example where the DELT-based analysis at operation  260  did not detect the second bridged tap, a bias that SELT-based data is better suited for detecting bridged taps of short length favors adjusting a parameter at operation  290  in a manner that will increase the bridged tap detection sensitivity of the DELT-based analysis rather than reduce the bridged tap detection sensitivity of the SELT-based analysis. 
     Upon adjusting one or more of the analysis parameters, the method  202  returns to either or both of the analysis operation  255 ,  260  to repeat the analysis with the adjusted parameters. If only SELT-based analysis parameters were adjusted, the iteration of the method  202  entails performing only operation  255  (not operation  260 ), and vice versa if only DELT-based analysis parameters were adjusted. If both SELT-based analysis and DELT-based analysis parameters were adjusted, the iteration of the method  202  entails performing again both operations  255  and  260 . Iteration of the method  202  then continues with repeating the comparison at operation  270 . 
     Iteration of the method  202  may proceed to incrementally adjust the analysis parameters within a predetermined range. In embodiments, this predetermined range spans detection criteria threshold that exceeds what could be tolerated if the individual analyses were not compared at operation  270 . If the comparison at operation  270  yields any compatible attributes, those attributes are ultimately to be declared as part of a line configuration estimate at operation  280 . Though embodiments of the present invention are not particular to the mechanics of the reporting operation  280 , it is noted such reporting may be performed in substantial real time as the method  202  identifies attributes as compatible, or may be reported at some time subsequent to the completion of the method  202  when no incompatible attributes remain, or when it is determined that no further iteration is to be done. 
     Where no further iteration is to be done and one or more incompatible analysis result (e.g., line attribute) remains, a determination is made whether to report out an incompatible result as part of operation  280 , or instead discard the result at operation  285 . In the exemplary embodiment, at operation  275  an accuracy associated with each of the first or second line configuration estimates is determined with respect to a given incompatible attribute. If one of the SELT data analysis or DELT data analysis is considered to have a sufficiently high accuracy for the incompatible attribute, or if a difference in the accuracies of the SELT and DELT data analysis is sufficiently large, the attribute value having the superior accuracy is reported along with compatible results. Of course, the report of any incompatible result may be distinguished from that of compatible results through a measure of confidence proscribed to each of the results reported. 
       FIG. 3  is a functional block diagram illustrating a system  300  configured to perform joint processing of SELT and DELT data collected from the exemplary network illustrated in  FIG. 1 , in accordance with an embodiment. Generally, the system  300  is to perform one or more of the methods  201  or  202 , described elsewhere herein, in an automated fashion. In the illustrated embodiment, system  300  includes a memory  395  and a processor or processors  396 . For example, memory  395  may store instructions to be executed and processor(s)  396  may execute such instructions. Processor(s)  396  may also implement or execute implementing logic  360  to implement the diagnostic algorithms discussed herein. System  300  includes communication bus(es)  315  to transfer transactions, instructions, requests, and data within system  300  among a plurality of peripheral devices communicably interfaced with one or more communication buses  315  (e.g., as further illustrated in  FIG. 7 ). System  300  further includes management interface  325 , for example, to receive analysis requests, return diagnostic results, and otherwise interface with the network elements illustrated in  FIG. 1 . 
     In embodiments, management interface  325  communicates information via an out-of-band connection separate from DSL line based communications, where “in-band” communications are communications that traverse the same communication means as payload data (e.g., content) being exchanged between networked devices. System  300  further includes DSL line interface  330  to communicate information via a LAN based connection, to monitor connected lines (e.g., line  112  in  FIG. 1 ). System  300  may further include multiple management events  355 , any of which may be initiated responsive to analysis of the vectored and non-vectored lines. For example, additional diagnostics, SELT and DELT measurement probes, and the like may be specified and triggered as management events  355 . Stored historical information  350  (e.g., SELT/DELT line data) and management events  355  may be stored upon a hard drive, a persistent data store, a database, or other memory/storage location within system  300 . 
     Within system  300  is a line diagnostic and management device  301  which includes a data collection module  370  to collect SELT and DELT data received for a line, a SELT analysis module  375 , a DELT analysis module  376 , and a diagnostics module  380 . The line diagnostic and management device  301  may be installed and configured in a compatible system  300  as is depicted by  FIG. 3 , or provided separately so as to operate in conjunction with appropriate implementing logic or other software (such as system  600 ). In any configuration the diagnostic and management device  301  may be implemented within the network architecture  100  ( FIG. 1 ), for example as component of the management device  170 . 
     In accordance with one embodiment, collection module  370  collects SELT and DELT data from interfaced digital communication lines over the interface  330  or from other network elements via management interface  325 . Analysis modules  375 ,  376  analyze the information retrieved via collection module  570  with each of the SELT analysis module  375  and DELT analysis module  376  to apply at least one line fault detection algorithm to output line configuration estimates based on the SELT data or the DELT data, respectively. 
     The diagnostics module  380  is further coupled to the analysis modules  375 ,  376  to receive and compare the results of the SELT and DELT analysis, for example comparing attributes of the respective line configurations to determine at least one attribute to be either compatible or incompatible. Where incompatible attributes are identified, at least one of the analysis modules is to modify at least one of the SELT or DELT analysis (e.g., by modifying a detection threshold or other analysis parameter in a predetermined manner substantially as described elsewhere herein), toward eliminating the incompatible attribute. The analysis module may be instructed to adjust one or more of their parameters where the SELT and DELT analysis modules  375 ,  376  arrive at a different estimate of one or more of: a line length; a location or length of a detected fault; or a different detection/categorization of a fault such as: a series fault; a shunt fault; a bridged-tap; a bad splice; or a faulty microfilter. In further embodiments, where the SELT analysis module  375  processes an echo response, the SELT analysis module is to perform the signal processing of the echo response substantially as described elsewhere herein to cancel an effect of a line attribute, such as a straight length of line, identified in a line configuration estimate. 
     Where a line attribute is identified by both the SELT and DELT analysis modules  375 ,  376  (e.g., the line configuration estimates output by each include an estimation that a same fault is present), the diagnostic module is to identify that compatible attribute in an estimation of the physical configuration of the line. This estimation may then be output as a diagnostic report or otherwise made accessible at one or more node in the network architecture  100  ( FIG. 1 ). 
     In further embodiments, the diagnostics module  380  is to compare an accuracy associated with each of the first or second analysis output by the analysis modules  375 ,  376  with respect to an incompatible attribute. For example, accuracies may be compared to each other or to a threshold to substantially as described elsewhere herein as part of a determination whether to further identify any attributes deemed incompatible as a line estimation published to one or more node of the network architecture  100 , or otherwise made externally available. 
       FIG. 4A  is a flow diagram illustrating an iterative SELT diagnostic method  401  assessing relative strengths of features in a time domain echo response to detect a large number of line configurations with multiple faults without the complexity of methods employing banks of configuration templates. In a first embodiment, the SELT diagnostic method  401  is employed as a stand-alone line diagnostic which may be applied to any SELT data collected from the CO-side or CPE-side of a line. In the exemplary embodiment, the SELT diagnostic method  401  is performed at the SELT diagnostic operation  255  in the method  202  of  FIG. 2B . 
     As one input, the SELT diagnostic method  401  receives transmission line data at operation  405 . The transmission line data may be derived from any transmission line parameters, such as, but not limited to ABCD parameters determined for the line through any conventional measurement technique. The transmission line data includes, but is not limited to characteristic impedance and propagation constant and/or RLCG characterization of the transmission line from which an envelope function of the line is to be calculated at operation  415 . Notably, the envelope function may also be determined based on ABCD parameters estimated for a line given certain line characteristics known from field data (e.g., a wire gauge of 26, etc.). 
     The envelope function is a relationship of the line propagation constant with respect to line distance and is to serve as a reference in the method  401 . The reference envelope function may be a reflection expected if an open loop, a short, or a known fault was present in the line at a certain distance from the measure point. In one embodiment where the envelope function represents a reflection expected if an open loop was present in the line at a certain distance from the measurement point, calculation of the envelope proceeds as: 
       envelope( d )= ifft ( e   −2γd )  (Eq. 1)
 
     where d is the distance, γ is the propagation constant for a given line, and ifft(.) represents the inverse Fourier transform. 
     In further embodiments, frequency windowing and/or normalization is further applied to adjust Eq. 1. Generally, the windowing filer and/or normalization scale is to be the same as that applied in calculation of the time domain echo response at operation  430 . Filtering the transmission line data smoothens out ripples when transformed into the time domain, reducing inverse Fourier transform artifacts. Generally, any frequency filter design known in the art may be employed to this end. Normalization is performed, for example, to adjust dynamic range of the envelope function to match that of the time domain echo response at operation  430  (e.g., to be between 0 and 1) and thereby facilitate the ratio tests subsequently performed in method  401 . 
     As a second input to the SELT diagnostic method  401 , chip-set dependent calibration parameters are received as an input at operation  410 . Such calibration parameters describe the frequency behavior of the measurement device (e.g., a CO-modem) and fixed front end (e.g., test leads or bus) coupling the measurement device to the line at the measurement point. Techniques for determining such calibration parameters, for example through shorted, loaded, and opened measurements, are known in the art and embodiments of the present invention are not limited in this respect. 
     As a third input to the SELT diagnostic method  401 , a frequency domain echo response is received as measurement data collected at operation  420  in response to excitation signals applied to the line at the measurement point. The received calibration parameters are utilized to arrive at a calibrated time domain echo response at operation  430 . In the time domain, impedance changes associated with features of a line can be detected. Many techniques for arriving at a calibrated time domain echo response from a frequency domain echo response are known in the art. A time domain echo response may also be directly provided as an input to the method  401 . 
     In embodiments, frequency windowing and/or normalization is applied to a frequency domain echo response (e.g., as received at operation  420 ) to arrive at the calibrated time domain echo response at operation  430 . In the exemplary embodiment, the windowing filter and normalization scale is the same as those applied in calculation of the reference envelope function at operation  430 . 
     At operation  440 , the line configuration is estimated based on a comparison of strengths of peaks and dips detected in the calibrated time domain echo response relative to the envelope function evaluated at the distances associated with the peaks and dips, and relative to each other. As described further elsewhere herein in the context of  FIGS. 4A and 4B , relative strengths of peaks and dips, peaks and envelope, and dips to envelope are analyzed at operation  440  to detect and/or classify of a variety of faults in a line as an estimate of a line&#39;s configuration. 
     As illustrated in  FIG. 4A , upon detection of at least one fault at operation  440 , a decision is made to either report out the fault(s) as a part of a SELT-based line configuration estimate at operation  445  or to adjust the echo response based on the currently detected line configuration at operation  450  so as to remove an effect of an attribute from the line through signal processing. As is further described elsewhere herein in the context of  FIG. 4D , the signal processing performed at operation  450  is an effort to improve fault detectability in a subsequent iteration of the operation  440  where peak, dip, envelope assessment is repeated for the adjusted echo response. In the exemplary embodiment, the decision to perform an iteration is based on whether a first detected line condition (i.e. fault) is located at a distance further than a pre-defined threshold. If so, the echo response is adjusted, and if not no further iteration is performed. 
       FIG. 4B  is a flow diagram illustrating a method  402  for performing peak and dip strength assessments on a time domain echo response. The method  402  begins with receiving the calibrated time domain echo response at operation  435 , for example as was determined at operation  430  ( FIG. 4A ). A predetermined number of detection attempts (e.g., 2-3) are then performed on the same time domain echo response, one or more of which may, but not necessary result in detection and classification of a line condition (fault). Where the number of detection attempts i has reach the predetermined maximum, the method  402  proceeds to operation  492  for return to operation  445  ( FIG. 4A ) for reporting of results. 
     Where the number of detection attempts i has reach a predetermined maximum, the method  402  proceeds to operation  455 . At operation  455 , a peak and a dip of largest magnitude are identified from a subset of peaks and dips in the calibrated time domain echo response that have not already been associated with line faults identified in prior iterations of the method  402 .  FIG. 5A  is an exemplary time domain echo response plotting a time-domain normalized reflection as a function of distance from the measurement point. The point  510  represents amplitude of the lowest dip and the point  515  represents amplitude of a highest peak for an iteration of the method  402 . 
     In embodiments, a strength of a peak relative to that of a dip is determined for the peak/dip pair identified at operation  455 . A physical configuration of the line may then be determined based on a thresholding of the relative strengths of the peak and dip amplitude. For example, if the peak or dip is sufficiently dominant and/or large, the peak or dip is associated with a particular line fault. In the illustrated embodiment, relative strengths of a peak and dip pair are assessed on the basis of a “peak-to-dip ratio,” referred to herein as a “PDR,” which is a useful quantity independent of amplitude. For example, in the threshold operation  458  ( FIG. 4B ), a first PDR is calculated as the magnitude of the amplitude of the peak divided by the amplitude of the dip which may be expressed mathematically as: 
     
       
         
           
             
               
                 
                   PDR 
                   ≡ 
                   
                     
                        
                       
                         
                           Amplitude 
                            
                           
                             ( 
                             peak 
                             ) 
                           
                         
                         
                           Amplitude 
                            
                           
                             ( 
                             dip 
                             ) 
                           
                         
                       
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                     . 
                   
                 
               
               
                 
                   Eq 
                   . 
                   
                       
                   
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     The PDR determined at operation  458  for the peak/dip pair  515 / 510  ( FIG. 5 ) is ˜0.88. 
     In embodiments, one of the peak/dip pair deemed sufficiently dominant is compared to the envelope function of the line, for example as was determined at operation  415  in  FIG. 4A , evaluated at the distance of the peak/dip. In the embodiment illustrated by  FIG. 4B , a first threshold (i.e., “threshold 1”) is applied to the PDR. Where the PDR satisfies the first predetermined threshold (e.g., exceeds the threshold 1), the peak is deemed sufficiently dominant and compared to the envelop at the distance d of the peak. If the PDR does not satisfy the first threshold, a second assessment is made to determine if the dip is sufficiently dominant (i.e., sufficiently larger than the peak). For example, the PDR is compared to a second predetermined threshold (i.e., “threshold 2”). Where the PDR satisfies the second threshold (e.g., is below threshold 2), the dip is deemed sufficiently dominant over the peak and the dip is then compared to the envelope at the distance d of the dip. In the exemplary embodiment, the dominant member of the peak/dip pair is compared by thresholding a second ratio. This second ratio is calculated by dividing the dominant member of the peak/dip pair by the envelope to generate either a peak-to-envelope ratio (“PER”) or a dip-to-envelope ratio (“DER”). A PER may be mathematically expressed as: 
     
       
         
           
             
               
                 
                   
                     PER 
                     ≡ 
                     
                        
                       
                         
                           Amplitude 
                            
                           
                             ( 
                             peak 
                             ) 
                           
                         
                         
                           Envelope 
                            
                           
                             ( 
                             
                               distance 
                                
                               
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                                 peak 
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                   , 
                 
               
               
                 
                   Eq 
                   . 
                   
                       
                   
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     with the envelope function in Eq. (1), for example, evaluated to determine the reflection expected if an open loop was at the distance of the peak being evaluated. For the case where the dip is sufficiently dominant (e.g., threshold 1 is not satisfied but threshold 2 is satisfied), an analogous function for the dip is evaluated to calculate the DER. 
     As further illustrated in  FIG. 4B , where the PER satisfies a predetermined threshold, for example, where the PER is greater than a third threshold (“threshold 3”), the peak is associated with a series fault in the line, such as, but not limited to, a bad splice, a corroded connection, or a gauge change to a higher impedance. The series fault is then available for output as a parameter of the diagnosed line configuration, for example to be reported out as a SELT-based line configuration estimate at operation  445  ( FIG. 4A ). The method  402  then returns to operation  455  for location of a next largest peak/trough pair until the maximum detection iteration count is reached, or until analysis of the next largest peak/trough satisfies another loop exit criteria. 
     Where the peak is of insufficient strength (e.g., the first PDR fails to satisfy the first threshold) and the dip is also of insufficient strength (e.g., first PDR fails to satisfy the second threshold, or DER fails to satisfy the fourth threshold), the method  402  triggers a further analysis for bridged taps at operation  475  on the basis of the peak/dip pair that was identified at operation  455 . 
     Alternatively, where the PDR comparisons indicate the dip is sufficiently dominant (e.g., threshold 1 is not satisfied but threshold 2 is satisfied), the method  402  proceeds to operation  470  if the DER satisfies a predetermined threshold, for example where the DER is greater than a fourth threshold (“threshold 4”), and the line is diagnosed as having a potential shunt fault such as, but not limited to, a short on the line, poor isolation, water in the cable, or gauge change to lower impedance. In the exemplary embodiment, the association of the dip with a shunt fault at operation  470  is provisional pending a further analysis for bridged taps at operation  475 , as described elsewhere herein in the context of  FIG. 4C . 
       FIG. 4C  is a flow diagram further illustrating exemplary relative comparisons of peaks and dips performed on a time domain echo response. Such comparisons are performed as a portion of the iterative SELT diagnostic method illustrated in  FIG. 4A , in accordance with an embodiment. After being triggered at operation  475 , the method  403  proceeds to operation  480 , with locating in the time domain echo response a first peak after the dip identified at operation  455  (i.e., the first trailing peak). For the particular echo response shown in  FIG. 5A , the point  515  is the amplitude of the peak following the dip associated with point  510  and so operation  480  locates the same peak/dip pair as was identified at operation  455 . However, operation  480  may of course identify a new peak as the first trailing peak, different than the main peak that was located at operation  455 , as dependent on a given echo response. 
     In embodiments, the strength of the dip is then assessed relative to the first trailing peak. If the relative strength of the dip falls within a predetermined range, then the line is diagnosed as having a bridged tap and the dip/first trailing peak pair are associated with the bridged tap. In the exemplary embodiment illustrated in  FIG. 4C , the strength of the dip is assessed relative to the first trailing peak by first determining a second peak-to-dip ratio (PDR) in the same manner as the first PDR was calculated. This second PDR is then compared to a fifth predetermined threshold (“threshold 5”) and a six predetermined threshold (“threshold 6”). Where the second PDR falls between the fifth and six thresholds, the DER is compared to another predetermined threshold (“threshold 7”). Where DER threshold is satisfied, the dip/first trailing peak pair is associated with a bridged tap on the line at operation  485 . If not, no bridged tap determination is made for the ith detection iteration and any provisional association made between the dip and a shunt fault at operation  470  becomes non-provisional and processing returns to method  401  ( FIG. 4A ) with at least one iteration of  440  now completed. Results from operation  440  are then ready for reporting at operation  445  or the echo response is adjusted at operation  450 . In either event, the method  403  then completes at operation  486  by incrementing the iteration count and returning to operation  444  for a subsequent iteration of the method  402  ( FIG. 4B ). 
     Alternatively, where the second PDR falls outside of the range defined by the fifth and six thresholds, the method  403  proceeds to operation  490  where the largest trailing peak is detected. For the particular echo response shown in  FIG. 5A , the point  515  is the maximum of the largest peak following the dip associated with point  510  and so operation  490  locates the same peak/dip pair as was identified at operation  455  and at operation  490 . However, operation  490  may of course identify a new peak as the largest trailing peak, different than the largest peak that was located at operation  455  and different than the first trailing peak that was located at operation  490 , as a dependent on a given echo response. 
     In embodiments, the strength of the dip is then assessed relative to the largest trailing peak. If the relative strength of the dip falls within a predetermined range, then the line is diagnosed as having a bridged tap and the dip/largest trailing peak pair are associated with the bridged tap. In the exemplary embodiment illustrated in  FIG. 4C , the strength of the dip is assessed relative to the largest trailing peak by first determining a third peak-to-dip ratio (PDR) in the same manner as the first and second PDR. This third PDR is then compared to an eighth predetermined threshold (“threshold 8”) and eighth ninth predetermined threshold (“threshold 9”). Where the third PDR falls between the seventh and eighth thresholds, the DER is compared to another predetermined threshold (“threshold 10”). Where DER threshold is satisfied, the dip/largest trailing peak pair is associated with a bridged tap on the line at operation  491 . If not, no bridged tap determination is made for the ith detection iteration and any provisional association made between the dip and a shunt fault at operation  470  becomes non-provisional and processing returns to method  401  ( FIG. 4A ) with at least one iteration of  440  now completed. Results from operation  440  are then ready for reporting at operation  445  or the echo response is adjusted at operation  450 . In either event, the method  403  then completes at operation  486  by incrementing the iteration count and returning to operation  444  for a subsequent iteration of the method  402  ( FIG. 4B ). 
     Alternatively, where the third PDR falls outside of the range defined by the seventh and eighth thresholds, and the strength of the dip relative to the largest trailing peak is sufficient, the dip is compared to the envelope (potentially a second time). If the dip is sufficiently dominant, the line is diagnosed with a shunt fault. For example, as shown in  FIG. 4C , the third PDR is compared to another predetermined threshold (“threshold 11”) and if the dip is sufficiently dominant, the ninth threshold is satisfied (e.g., PDR is smaller than the ninth threshold). A dip-to-envelope ratio (DER) is then calculated, substantially as described elsewhere in the context of a PER, and compared to another threshold (“threshold 12”). If the dip satisfies this threshold (e.g., DER exceeds threshold 12), the dip is associated with a shunt fault on the line at operation  493 . If not, no bridged tap determination is made for the particular detection iteration and any provisional association made between the dip and a shunt fault at operation  470  becomes non-provisional and processing returns to method  401  ( FIG. 4A ) with at least one iteration of  440  now completed. Results from operation  440  are then ready for reporting at operation  445  or the echo response is adjusted at operation  450 . In either event, the method  403  then completes at operation  486  by incrementing the iteration count and returning to operation  444  for a subsequent iteration of the method  402  ( FIG. 4B ). 
       FIG. 4D  is a flow diagram illustrating a method  404  for adjusting the echo response based on the estimation of the physical configuration that is performed. The method  404  may be applied within the context of any line diagnostic based on SELT. Generally, the method  404  is useful for improving detectability of faults dynamically as a line is diagnosed. As such, in the exemplary embodiment the method  404  is implemented to process the time domain echo response between iterations of the method  404  ( FIG. 4A ). With the method  404 , an effect of a line attribute identified in a previous estimation of the physical configuration, or derived from the previous estimation of the physical configuration, is removed. Generally, the effect of any attribute of the line configuration may be removed, such as but not limited to lengths of straight line and detected faults (e.g., any of the faults detected in methods  402 ,  403 ). Removal of detected faults however poses relatively more risk of propagating a detection error. 
     The method  404  begins with the received calibrated time domain echo response input at operation  431 . In the exemplary embodiment where the attribute to be removed is a length of straight line, a distance (D) of a first reflection is identified at operation  496 . In the exemplary embodiment where the method  404  is performed at operation  450  ( FIG. 4A ), the first reflection has been identified at operation  440  for the current iteration of method  401 . For example, as shown in  FIG. 5A , the first reflection is the dip  515  with the distance D being approximately 2950 feet (ft). 
     At operation  497 , if the distance D is greater than a predetermined threshold (e.g., 500 ft) a distance D_Zoom, that is no greater than the distance D, is selected at which the first reflection is desired to appear (e.g., at the threshold distance of 500 ft). At operation  498 , the effect of a straight line having a length equal to D-D_Zoom is subtracted from the time domain echo response under the assumption that over this distance D-D_Zoom, the line is straight (i.e., faultless). Generally, any known signal processing technique for removing a length of straight line may be applied. For example, in the exemplary embodiment, the echo response is processed to compensate for the effect of the straight line as follows: 
       echo( f )=echo( f )*(1+tan  h (γΔ))/(1−tan  h (γΔ)),  Eq. (4)
 
     where echo(f) denotes the echo response at frequency f, Δ=D−D_Zoom denotes the length of the straight line effect of which will be cancelled, and γ denotes the propagation constant. 
       FIG. 5B  is the exemplary calibrated time domain echo response illustrated in  FIG. 5A  after having an effect of approximately 1500 feet of straight line removed. As shown, the dips and peaks corresponding to points  510 ,  515  are now more prominent and in better condition for further analysis. For example, as shown in  FIG. 4D , the method  404  completes by returning the revised echo response to the method  401  ( FIG. 4A ) for the peak/dip strength assessments and based on ratio tests. 
       FIG. 6  is a functional block diagram illustrating a system  600  configured to characterize a physical configuration of a twisted pair telephone line based on analysis of SELT data collected from the exemplary network illustrated in  FIG. 1 , in accordance with an embodiment. Generally, the system  600  is to perform one or more of the methods  401 ,  402 ,  403  or  404 , described elsewhere herein, in an automated fashion. In further embodiments, the system  600  may be incorporated with the system  300 , described elsewhere herein, as an integrated line diagnostic system. 
     In the illustrated embodiment, system  600  includes a memory  695  and a processor or processors  696 . For example, memory  695  may store instructions to be executed and processor(s)  696  may execute such instructions. Processor(s)  696  may also implement or execute implementing logic  660  to implement the diagnostic algorithms discussed herein. System  600  includes communication bus(es)  615  to transfer transactions, instructions, requests, and data within system  600  among a plurality of peripheral devices communicably interfaced with one or more communication buses  615  (e.g., as further illustrated in  FIG. 7 ). System  600  further includes management interface  625 , for example, to receive analysis requests, return diagnostic results, and otherwise interface with the network elements illustrated in  FIG. 1 . 
     In embodiments, management interface  625  communicates information via an out-of-band connection separate from DSL line based communications, where “in-band” communications are communications that traverse the same communication means as payload data (e.g., content) being exchanged between networked devices. System  600  further includes DSL line interface  630  to communicate information via a LAN based connection, to monitor connected lines (e.g., line  112  in  FIG. 1 ). System  600  may further include multiple management events  655 , any of which may be initiated responsive to analysis of the vectored and non-vectored lines. For example, additional diagnostics, SELT and line transmission measurement probes, and the like may be specified and triggered as management events  655 . Stored historical information  650  (e.g., SELT/DELT line data) and management events  655  may be stored upon a hard drive, a persistent data store, a database, or other memory/storage location within system  600 . 
     Within system  600  is a line diagnostic and management device  601  which includes a data collection module  670  to collect SELT data and line transmission data received for a line, an analysis module  675 , and a diagnostics module  680 . The line diagnostic and management device  601  may be installed and configured in a compatible system  600  as is depicted by  FIG. 6 , or provided separately so as to operate in conjunction with appropriate implementing logic or other software (such as system  300 ). 
     In accordance with one embodiment, collection module  670  collects SELT data and line transmission data from interfaced digital communication lines over the interface  630  or from other network elements via management interface  625  and stores the data to a memory. The analysis module  675  communicatively coupled to the collection module  670  analyzes the information retrieved via collection module  670 . For example, in an embodiment the analysis module  675  is to determine a calibrated time domain echo response from a frequency domain echo response received from the collection module  670  for the line under analysis. In further embodiments, the analysis module  675  is to calculate an envelope function from transmission line data received for the line under analysis. The diagnostics module  680  is further coupled to the analysis module  675 , to receive a characterization of features and/or parameters identified by processing the data for a line and to compare a size of at least one peak relative to that of at least one dip in the time domain echo response; and to determine a physical configuration of the line based on the size comparison between the peak and dip. 
     In embodiments, the diagnostics module  680  is to compare a size of at least one peak or at least one dip to the envelope function determined by the analysis module  675  and to determine a physical configuration of the line based on the size comparison between the envelope and the peak or dip, substantially as described elsewhere herein. For example, in one embodiment the diagnostics module  680  is to identify a highest peak from a set of peaks in the time domain echo response not yet associated with a line attribute, identify a lowest dip from a set of dips in the echo response not yet associated with a line attribute, and the distinguish between a series fault and a shunt fault based on a size of the highest peak relative to that of the lowest dip. As another example, the diagnostics module  680  may be further configured to identify, in the time domain echo response, a first trailing peak after the lowest dip not yet associated with a line fault and compare a size of the lowest dip to a size of the first trailing peak, substantially as described elsewhere herein. The diagnostics module  380  may then output a determination of a bridge tap or a shunt fault based on the size comparison between the first trailing peak and the lowest dip. 
     In still other embodiments, the diagnostics module  380  is to identify, in response to determining the first trailing peak relative to the lowest dip is not within a first predetermined range, a highest trailing peak after the lowest dip. The diagnostics module  380  may further be configured to determine a size of the largest trailing peak relative to the lowest dip and where the relative size of the largest trailing peak relative to the lowest dip is within a predetermined range, the highest trailing peak and the lowest dip is identified by the diagnostics module  380  as corresponding to a bridged-tap. Any such diagnostic results may then be stored or forwarded to a location accessible one or more mode of the network architecture  100 . 
     In further embodiments, the analysis module  675  is to iteratively adjust the calibrated time domain echo response based on an estimation of the physical configuration of the line output from the diagnostics module  680 . For example where the diagnostics module  680  is executing the method  401 , and identifies a fault at a given distance, the analysis module  675  may subject the SELT data to single processing techniques to cancel an effect of a length of straight line from the time domain echo response as determined based on the distance of a reflection in the echo response corresponding to the identified fault. The time domain echo response, as processed by the analysis module  675  is then output again to the diagnostics module  380  for a subsequent iteration of peaks and dips, for example using the ratio tests described herein. 
       FIG. 7  illustrates a diagrammatic representation of a computer system  700  in the exemplary form of a computer system, in accordance with one embodiment, within which a set of instructions, for causing the computer system  700  to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine may be connected, networked, interfaced, etc., with other machines in a Local Area Network (LAN), a Wide Area Network, an intranet, an extranet, or the Internet. The computer system  700  may operate in the capacity of a server or a client machine in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. Certain embodiments of the machine may be in the form of a personal computer (PC), a set top box (STB), a web appliance, a server, or any machine known in the art capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines (e.g., computers) that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. 
     The exemplary computer system  700  includes a processor  702 , a main memory  704  (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM), etc., static memory such as flash memory, static random access memory (SRAM), volatile but high-data rate RAM, etc.), and a secondary memory  718  (e.g., a persistent storage device including hard disk drives and persistent data base implementations), which communicate with each other via a bus  730 . Main memory  704  includes information and instructions and software program components necessary for performing and executing the functions with respect to the various embodiments of the systems, methods, and DSM server as described herein. Optimization instructions  723  may be triggered based on, for example, analysis of neighborhood information, SNR data, PSD data, noise levels with mitigation active and noise levels with mitigation inactive, and so forth. Collected SELT/DELT, and line transmission data and calculations  724  are stored within main memory  704 . Line configuration results as well as optimization instructions  723  may be stored within main memory  704 . Main memory  704  and its sub-elements (e.g.  723  and  724 ) are operable in conjunction with processing logic  726  and/or software  722  and processor  702  to perform the methodologies discussed herein. 
     Processor  702  represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. Processor  702  may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or the like. Processor  702  is configured to execute the processing logic  726  for automatically performing the operations and functionality which is discussed elsewhere herein (e.g., as methods  201 ,  202 ,  401 ,  402 ,  403 ,  404 , etc.). 
     The computer system  700  may further include one or more network interface cards  708  to communicatively interface the computer system  700  with one or more networks  720  from which information may be collected for analysis. The computer system  700  also may include a user interface  710  (such as a video display unit, a liquid crystal display (LCD)), an alphanumeric input device  712  (e.g., a keyboard), a cursor control device  714  (e.g., a mouse), and a signal generation device  716  (e.g., an integrated speaker). The computer system  700  may further include peripheral device  736  (e.g., wireless or wired communication devices, memory devices, storage devices, audio processing devices, video processing devices, etc.). 
     The computer system  700  may perform the functions of a line analyzer  705  capable interfacing with digital communication lines in vectored and non-vectored groups, monitoring, collecting SELT/DELT data  724 , analyzing, and reporting detection results  723 , and initiating, triggering, and executing various instructions including the execution of commands and instructions to diagnose a line based on collected SELT/DELT data  724 , perform ratio tests on a time domain echo response calculated from SELT data  724 , etc. 
     The secondary memory  718  may include at least one non-transitory machine-readable storage medium (or more specifically a non-transitory machine-accessible storage medium)  731  on which is stored one or more sets of instructions (e.g., software  722 ) embodying any one or more of the methodologies or functions described herein. Software  722  may also reside, or alternatively reside within main memory  704 , and may further reside completely or at least partially within the processor  702  during execution thereof by the computer system  700 , the main memory  704  and the processor  702  also constituting machine-readable storage media. The software  722  may further be transmitted or received over a network  720  via the network interface card  708 . 
     The above description is illustrative, and not restrictive. For example, while flow diagrams in the figures show a particular order of operations performed by certain embodiments of the invention, it should be understood that such order may not be required (e.g., alternative embodiments may perform the operations in a different order, combine certain operations, overlap certain operations, etc.). Furthermore, many other embodiments will be apparent to those of skill in the art upon reading and understanding the above description. Although the present invention has been described with reference to specific exemplary embodiments, it will be recognized that the invention is not limited to the embodiments described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.