Abstract:
A method is disclosed that enables the monitoring, evaluation, and adjustment of a telecommunications network&#39;s audio-signal loss plan. The method can be implemented at a data-collection server, in which the server accumulates voice-quality measurement statistics from various nodes in the network. Such nodes include telecommunications endpoints, media gateways, private-branch exchanges, teleconference bridges, and so forth. The different types of statistics that can be acquired include voice activity detection, average speech level, average noise level, and so forth. The server accumulates the statistical data from the various nodes for multiple calls and over an extended period of time. The server is also able to compare the statistics against a theoretical model that is a function of the loss plan, at least in part. For example, the comparisons that the data-collection server performs can be used to determine why certain calls have been reported as having unsatisfactory quality.

Description:
FIELD OF THE INVENTION 
     The present invention relates to telecommunications in general, and, more particularly, to managing the audio-signal loss plan of a telecommunications network. 
     BACKGROUND OF THE INVENTION 
     Traditionally, Public Switched Telephone Network (“PSTN”) telephony systems provided service by utilizing relatively homogeneous, centralized switching infrastructures. These infrastructures were homogeneous in the sense that a single service provider, such as the former Bell System in the United States, utilized a relatively limited, uniform group of telecommunications equipment in a voice-only network that provided “plain, old telephony service” (POTS). These traditional infrastructures were uniform in structure and composition, mainly because they were designed from the top on down. In part because they were centralized, these infrastructures generally had knowledge as to the signal transmission characteristics for every piece of equipment involved in each handled call. Based on this knowledge, the traditional PSTN could make adjustments for end-to-end audio-signal loss, thereby optimizing performance with respect to acoustical audio signal level, audio distortion, and echo. Furthermore, guidance as to the audio-signal loss across various telecommunications device types could be found in various standards and technical guidelines. 
     For example, in order to reduce the echo signals that were unavoidably present in each transmit path, the echo signals would be carried to the receive path of the line side equipment serving the far-end party and reduced there, based upon an audio-signal loss plan conventionally used by each service provider. The loss plan provided that a predetermined fixed amount of loss would be present in a receive path. The particular amount of fixed loss (e.g., 0 db, 3 dB, 6 dB, etc.) depended upon the type of call: intra-office, intra-exchange (local), intra-LATA (toll), or inter-LATA (toll). 
     In contrast, modern hybrid telecommunications systems typically must offer interconnectivity between disparate telecommunications networks such as datagram-based networks, the Internet being an example of this, and traditional circuit-switched networks. Additionally, a given network often must handle different types of media concurrently. For example, Voice over Internet Protocol (“VoIP”) systems provide voice telephony over the same networks that handle email, video, and other Internet traffic. Moreover, whereas before there were one or two service providers—that is, local providers and possibly long-distance providers—involved in a particular telephony call, now there can be several service providers involved in handling the media data packets of a given call or session. Finally, each provider&#39;s telecommunications network might comprise equipment from many more vendors than before. 
     A telecommunications system that comprises a business enterprise&#39;s network poses additional challenges in optimizing the call quality that is experienced by its users. In such a network, there are telecommunications endpoint devices interconnected with private-branch exchanges and teleconference bridges. To complicate the call-quality management, the audio signals passing through these components often continue on through media gateways to different, globally-reaching, service provider networks. There are techniques for managing the audio signals as they pass through the different components both within and outside of the enterprise network, such as automatic gain control (AGC). These techniques, however, often produce unwanted effects, such as “pumping up” background noise, and often mishandle certain types of signals, such as music-on-hold. 
     Consequently, the audio-signal loss plan in today&#39;s telecommunications networks is significantly more complex to manage than ever before. There are more situations in which the signal amplitude is too low or the noise is too high, or both. Therefore, it would be advantageous to provide a system and method for dynamic end-to-end loss compensation, particularly in an enterprise telecommunications network, with an ability to accommodate the characteristics of the various types of telecommunications devices present. 
     SUMMARY OF THE INVENTION 
     The present invention enables the monitoring, evaluation, and adjustment of a telecommunications network&#39;s audio-signal loss plan, such as the loss plan of an enterprise network. In accordance with the illustrative embodiment of the present invention, a data-collection server accumulates voice-quality measurement statistics from various nodes in the network. Such nodes include telecommunications endpoints, media gateways, private-branch exchanges, teleconference bridges, and so forth. The different types of statistics that can be acquired include voice activity detection, average speech level, average noise level, and so forth. These statistics can be acquired for multiple paths that pass through each reporting node, such as the receive path into an endpoint from the network and the transmit path of an endpoint user&#39;s speech signals from the endpoint into the network. The data-collection server accumulates the statistical data from the various nodes for multiple calls and over an extended period of time. 
     As the voice-quality measurement (VQM) statistics are accumulated, the server is also able to compare the statistics against a theoretical model that is a function of the loss plan, at least in part. For example, the comparisons that the data-collection server performs can be used to determine why certain calls have been reported (e.g., by customers, etc.) as having unsatisfactory quality. The important distinction between the data-collection server and some systems in the prior art is that whereas various prior-art techniques historically have been designed with traditional, homogeneous infrastructures in mind, the server advantageously makes use of the relatively new VQM-reporting capabilities that are becoming available in various types of telecommunications equipment—in particular, enterprise-oriented equipment such as packet-based endpoints, private-branch exchanges, teleconference bridges, and media gateways. By accumulating a large set of VQM statistics, which is made possible by enlisting a large number of reporting nodes possibly over an extended period of time, the data-collection server can pinpoint different types of loss-plan issues at different points in the monitored network. 
     For pedagogical purposes, three operating scenarios that involve the illustrative embodiment are disclosed herein. In the first operating scenario, the server accumulates voice-quality measurements from a predetermined endpoint and uses those accumulated statistics to adjust a parameter related to the audio loss plan and at a selected media gateway. In the second operating scenario, the server accumulates a first plurality and second plurality of voice-quality measurements from a first endpoint and second endpoint, respectively, where the two endpoints are collocated within the same acoustic environment (e.g., in a call center, etc.). In the second scenario, the server uses the accumulated statistics for the purpose of analyzing issues such as how to assign calls at a call center, whether to add acoustic suppression (e.g., ceiling tiles, etc.) to the acoustic environment, and so forth. And in the third operating scenario, the server accumulates a first plurality and second plurality of voice-quality measurements from a first set of endpoints and second set of endpoints, respectively. In the third scenario, the server uses those accumulated statistics for the purpose of analyzing issues such why the audio signals that are being received from one service provider&#39;s network might be consistently at a different signal level than those being received from another service provider&#39;s network. As those who are skilled in the art will appreciate, the data-collection server of the illustrative embodiment can be used for additional purposes than those explicitly disclosed herein. 
     A method is disclosed for managing an audio-signal loss plan of an enterprise network in a telecommunications system in accordance with the illustrative embodiment, the enterprise network serving telecommunications endpoints connected to the enterprise network, in which the method comprises: accumulating, at a data-processing system, a plurality of voice-quality measurements from a predetermined endpoint that is served by the enterprise network, the telecommunications endpoint being adapted to transmit and receive voice signals that pass through the enterprise network and a telecommunications gateway via a transmit path and a receive path, respectively; comparing the plurality of voice-quality measurements to a theoretical target that is a function of the audio-signal loss plan, resulting in a comparison result; and transmitting a signal from the data-processing system to a network node in the telecommunications system, in order to adjust a gain factor of at least one of the transmit path and the receive path, the amount of the adjustment being based on the comparison result. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  depicts a schematic diagram of telecommunications system  100  in accordance with the illustrative embodiment of the present invention. 
         FIG. 2  depicts a flowchart of the salient tasks performed by data-collection server  103 , as part of a first operating scenario. 
         FIG. 3  depicts a flowchart of the salient tasks performed by data-collection server  103 , as part of a second operating scenario. 
         FIG. 4  depicts a flowchart of the salient tasks performed by data-collection server  103 , as part of a third operating scenario. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  depicts a schematic diagram of telecommunications system  100  in accordance with the illustrative embodiment of the present invention. System  100  comprises enterprise telecommunications network  101 ; telecommunications endpoints  102 - 1  through  102 -M, wherein M is a positive integer; data-collection server  103 ; gateways  104 - 1  through  104 -N, wherein N is a positive integer; and service provider network  105 - 1  through  105 -N. The depicted elements in system  100  are interconnected as shown. 
     Enterprise telecommunications network  101  enables the transport and control of communications signals among endpoints such as endpoints  102 - 1  through  102 -M. The communications signals convey media signals, such as audio, video, and so forth. To this end, network  101  comprises one or more interconnected data-processing systems such as private-branch exchanges, switches, servers, routers, gateways, and teleconference bridges, as are well-known in the art. 
     In accordance with the illustrative embodiment, network  101  comprises an Internet Protocol-based (IP-based) network, as is known in art, for the purpose of transmitting bitstreams of encoded voice signals. Although network  101  in the illustrative embodiment comprises a Voice-over-IP (VoIP) enterprise network, network  101  could alternatively or additionally comprise another type of network such as the Internet, some other type of IP-based network, or some other type of packet-based network (e.g., asynchronous transfer mode, multiprotocol label switching [MPLS], etc.), as those who are skilled in the art will appreciate. Furthermore, although network  101  is a business enterprise&#39;s telecommunications network in the illustrative embodiment, it will be clear to those skilled in the art how to make and use alternative embodiments in which network  101  is a different type of network. 
     Telecommunications endpoints  102 - 1  through  102 -M are end-user telephony devices, such as speakerphones, desksets, cellular phones, soft phones resident in computers, personal digital assistants, and so forth. Each being equipped with a loudspeaker and/or microphone, endpoints  102 - 1  through  102 -M enable their users to communicate at least audibly with one other, or with users of other endpoints supported by network  101  that are not depicted. Accordingly, endpoints  102 - 1  through  102 -M interoperate with network  101  and with one other in well-known fashion. 
     In accordance with the illustrative embodiment, endpoint  102 - m , wherein m has a value of 1 through M, is capable of taking voice-quality measurements (VQM) and of providing VQM statistics to a requesting node such as data-collection server  103 . The set of statistics include, but are not limited to, one or more of the following: 
     i. speech envelope, 
     ii. background-noise envelope, 
     iii. voice activity detection, 
     iv. average speech level, 
     v. average peak-speech level, and 
     vi. average noise level. 
     As those who are skilled in the art will appreciate, endpoint  102 - m  might be capable of providing other types of VQM statistics. The VQM statistics include statistics about the receive path, which represent the data packets arriving at endpoint  102 - m  from enterprise network  101 . The VQM statistics also include statistics about the transmit path, which represent the data packets that are first generated by endpoint  102 - m  from the audio signals received from endpoint  102 - m &#39;s user (i.e., via the endpoint&#39;s microphone) and then transmitted into network  101 . Each endpoint  102 - m  can provide receive path statistics or transmit path statistics, or both. 
     Although endpoints  102 - 1  and  102 -M are described above as providing VQM statistics, other nodes throughout system  101  are capable of providing similar statistics, as those who are skilled in the art will appreciate. For example, one or more of gateways  104 - 1  through  104 -N, private-branch exchanges within network  101 , and teleconference bridges within network  101  measure voice quality and provide VQM statistics to data-collection server  103 . 
     In accordance with the illustrative embodiment, each endpoint  102 - m  is a wired, Ethernet-based deskset. In some alternative embodiments, as those who are skilled in the art will appreciate, endpoints  102 - 1  through  102 -M interface with network  101 &#39;s infrastructure through any of a variety of link protocols (e.g., IEEE 802.11, CDMA, GSM, UMTS, etc.), wired or otherwise. 
     Data-collection server  103  is a data-processing system that accumulates the voice-quality measurement statistics collected by endpoints  102 - 1  through  102 -M, as well as possibly other nodes. Server  103  performs the tasks of the illustrative embodiment that are described below and with respect to  FIGS. 2 through 4 . As those who are skilled in the art will appreciate, the techniques of the illustrative embodiment can be implemented at a data-processing system other than a server, in some alternative embodiments. 
     Gateway  104 - n , for n=1 through N, is a data-processing system that comprises media gateway functionality that is known in the art, acting as a translator between two types of networks in well-known fashion. As depicted, gateway  104 - n  acts as a translator between Internet-Protocol-based network  101  and service provider network  105 - n , which is described below. Gateway  104 - n  enables telecommunications over multiple transport protocols from one endpoint in one network to another endpoint in another network, in part by working in concert with one or more gateway controllers to set up, maintain, and terminate calls. For pedagogical purposes, the gateway controller functionality is incorporated into one or more of the depicted gateways. 
     Because gateway  104 - n  connects two different types of networks with each other, one of its main functions is to convert between the different transmission and coding techniques uses across the two different networks. In accordance with the illustrative embodiment, gateway  104 - n  is a Voice-over-Internet-Protocol-capable (VoIP-capable) media gateway that performs the conversion between i) time-division multiplexed (TDM) voice signals that originate at a telecommunications endpoint associated with network  105 - n  and ii) VoIP signals that are intended for an Internet Protocol network endpoint, such as one of endpoints  102 - 1  through  102 -M. Gateway  104 - n  performs the conversion in the reverse direction as well (i.e., from an IP endpoint to a TDM endpoint) and is able to perform bidirectional conversion for multiple calls concurrently. 
     Service provider networks  105 - 1  through  105 -N are portions of the Public Switched Telephone Network (PSTN), where each network  105 - n  is operated by a different service provider, such as Verizon and AT&amp;T in the United States. The Public Switched Telephone Network, as is well-known in the art, comprises access paths, switches, and transmission paths, in a combination of analog and digital technology, which enable associated endpoints to communicate with other endpoints, including endpoints  102 - 1  through  102 -M. In accordance with the illustrative embodiment, enterprise telecommunications network  101  is interconnected with at least two service provider networks (e.g., networks  105 - 1  and  105 - 2 , etc.), via the corresponding gateways (e.g., gateways  104 - 1  and  104 - 2 , etc.). Using multiple service providers to provide users with access to outside the enterprise network is a common practice followed by many larger business enterprises. 
     In accordance with the illustrative embodiment, each of service provider networks  105 - 1  through  105 -N provides the same type of service to enterprise network  101  (e.g., voice telephony, etc.). In some alternative embodiments, the type of service provided by one service provider network might be different from that provided by another service provider network. Furthermore, each network  105 - n  might comprise a vastly different complement of wireline equipment, wireless equipment, or both wireline and wireless equipment, from one network to another. 
       FIGS. 2 ,  3 , and  4  depict flowcharts of the salient tasks performed by data-collection server  103 , as part of managing the audio-signal loss plans of enterprise network  101 , and in accordance with the illustrative embodiment of the present invention. Each of the three figures relates to a different operating scenario that is related to the management of loss plans. As those who are skilled in the art will appreciate, some or all of the individual tasks depicted in  FIGS. 2 ,  3 , and  4  can be performed simultaneously or performed in a different order from that depicted. 
     In the first operating scenario, which is represented by  FIG. 2 , data-collection server  103  accumulates voice-quality measurements from a predetermined endpoint chosen among endpoints  102 - 1  through  102 -M and uses those accumulated statistics to adjust a parameter related to the audio loss plan and at a selected gateway (i.e., one of gateways  104 - 1  through  104 -N). As those who are skilled in the art will appreciate, the disclosed technique can be applied to accumulating and analyzing voice-quality measurements from more than one endpoint. 
     In the second operating scenario, which is represented by  FIG. 3 , data-collection server  103  accumulates a first plurality and second plurality of voice-quality measurements from a first endpoint and second endpoint, respectively, which endpoints are chosen among endpoints  102 - 1  through  102 -M. The two endpoints are collocated within the same acoustic environment. For example, endpoints  102 - 1  and  102 - 2  can be spatially-adjacent endpoints at the same call center. In the second scenario, server  103  uses those accumulated statistics to output a parameter value that characterizes the acoustic environment that is common to both endpoints. Based on the statistics, server  103  can be used to analyze issues such as how to assign calls at a call center, whether to add acoustic suppression (e.g., ceiling tiles, etc.) to the acoustic environment, and so forth. As those who are skilled in the art will appreciate, the disclosed technique can be applied to accumulating and analyzing voice-quality measurements from more than two endpoints in the same acoustic environment. 
     In the third operating scenario, which is represented by  FIG. 4 , data-collection server  103  accumulates a first plurality and second plurality of voice-quality measurements from a first set of endpoints and second set of endpoints, respectively, the endpoints within each set being chosen from endpoints  102 - 1  through  102 -M. The first set of endpoints is served by a first gateway, and the second set of endpoints is served by a second gateway, where the gateways are chosen from gateways  104 - 1  through  104 -N. In some alternative embodiments, collection server  103  accumulates first and second pluralities of voice-quality measurements from the first and second gateways themselves, instead of from the first and second sets of endpoints served by those gateways. In the third scenario, server  103  uses those accumulated statistics to output a parameter value that characterizes a signal path associated with one of the gateways. Based on the statistics, server  103  can be used to analyze issues such why the audio signals being received from one service provider&#39;s network might be consistently at a different signal level than those being received from another service provider&#39;s network. As those who are skilled in the art will appreciate, the disclosed technique can be applied to accumulating and analyzing voice-quality measurements associated with more than two sets of endpoints or with more than two service provider networks, or both. 
     In each scenario, as those who are skilled in the art will appreciate, server  103  may obtain the voice-quality measurements in one or more of various different ways, such as transmitting a single request to a measuring node to start transmitting measurements, transmitting a one-for-one request for each measurement to be transmitted, or accepting whatever measurements are transmitted by a sending node. In other words, server  103  might pull information from one or more sending nodes, both receive pushed information from the sending nodes, or both. 
       FIG. 2 , now to be described in detail, depicts a flowchart of the salient tasks performed by data-collection server  103 , as part of the first operating scenario described above. At task  201 , server  103  accumulates a plurality of voice-quality measurements from a predetermined endpoint that is served by enterprise network  101 , in this case endpoint  102 - 1 . Telecommunications endpoint  102 - 1  is capable of transmitting and receiving voice signals that pass through enterprise network  101  and a selected telecommunications media gateway, in this case gateway  104 - 2 , via a transmit path and a receive path, respectively. As those who are skilled in the art will appreciate, in some alternative embodiments, server  103  instead accumulates a plurality of voice-quality measurements from a predetermined network node that is not an endpoint. 
     In some embodiments, server  103  is able to select not only the gateway to analyze and the endpoint or endpoints to use in the analysis, but also specific pathways through intermediate nodes within network  101  itself. For example, some of the voice-quality measurements that are selected for use can represent a path that passes through a private-branch exchange or a teleconference bridge in network  101 . Server  103  might or might not be accumulating statistics from the intermediate nodes, depending in part on the measuring capability of each intermediate node selected. 
     At task  202 , server  103  compares the plurality of accumulated voice-quality measurements to a theoretical target. The theoretical target is a function of the audio-signal loss plan of enterprise network  101 . In some embodiments, the theoretical target is also a function of a signal model of the predetermined endpoint (i.e., endpoint  102 - 1 ). The comparing task that is performed at task  202  results in a comparison result. 
     The theoretical target is calculated in well-known fashion. For example, if the theoretical target is to be calculated with respect to average peak-speech level, the target would ideally be at a value at which the full digital representation of a speech signal is utilized in each virtual channel used by calls throughout enterprise network  101 . In other words, the objective in setting the audio levels would be to maximize the signal-to-quantization-noise ratio in each communications link from one network node to the next. A goal for achieving such an objective might be to maintain a target speech root-mean-square (RMS) level at approximately −15 dBm relative to the maximum digitally representable signal level, so as to maximize use of the available digital signal representation without reaching the saturation, or overload, point. As another example, if the theoretical result is to be calculated with respect to noise, recognizing that lower levels of noise are better than higher levels, an objective along this line would be to maximize the ratio of average speech level to average noise level. A goal for achieving such an objective might be to maintain the speech-to-noise ratio at 40 dB or greater. 
     As those who are skilled in the art will appreciate, there might be other considerations that are needed to be made when calculating the theoretical target. Furthermore, the calculation of theoretical target will vary from one voice-quality measurement type (e.g., peak-speech level, noise, etc.) to another. 
     At task  203 , server  103  transmits a signal to selected gateway  104 - 2  to adjust a gain factor of at least one of the transmit communication path and the receive communication path, the amount of the adjustment being based on the comparison result. In some alternative embodiments, the result is instead provided to a technician who can then make the appropriate adjustment to the gain factor, or the result is instead transmitted to a network node other than the gateway. 
       FIG. 3  depicts a flowchart of the salient tasks performed by data-collection server  103 , as part of the second operating scenario described above. At task  301 , server  103  accumulates i) a first plurality of voice-quality measurements from a first endpoint, in this case endpoint  102 - 1 , and ii) a second plurality of voice-quality measurements from a second endpoint, in this case endpoint  102 - 2 . Endpoints  102 - 1  and  102 - 2  are capable of transmitting and receiving voice signals. Furthermore, endpoints  102 - 1  and  102 - 2  are collocated within the same acoustic environment, such as being spatially-adjacent to each other at a call center. As those who are skilled in the art will appreciate, in some alternative embodiments, server  103  instead accumulates pluralities of voice-quality measurements from network nodes that are not endpoints. 
     In some embodiments, server  103  is able to select not only the particular acoustic environment to analyze and the endpoint or endpoints common to that environment to use in the analysis, but also specific pathways through intermediate nodes within network  101  itself. For example, some of the voice-quality measurements that are selected for use can represent a path that passes through a private-branch exchange or a teleconference bridge in network  101 . Server  103  might or might not be accumulating statistics from the intermediate nodes, depending in part on the measuring capability of each intermediate node selected. 
     At task  302 , server  103  compares the first plurality of voice-quality measurements to a first theoretical target. The first theoretical target is a function of the audio-signal loss plan of enterprise network  101 . In some embodiments, the first theoretical target is also a function of a signal model of the first predetermined endpoint (i.e., endpoint  102 - 1 ). The calculation of the theoretical target is described above and with respect to task  202 . The comparing task that is performed as part of task  302  results in a first comparison result. 
     At task  303 , server  103  compares the second plurality of voice-quality measurements to a second theoretical target. The second theoretical target is a function of the audio-signal loss plan of enterprise network  101 , where the function representing the second theoretical target might be the same as or might be different from the function represent the first theoretical target. In some embodiments, the second theoretical target is also a function of a signal model of the second predetermined endpoint (i.e., endpoint  102 - 2 ). The comparing that is performed as part of task  303  results in a second comparison result. 
     At task  304 , server  103  outputs a value of a parameter that characterizes the first acoustic environment. In accordance with the illustrative embodiment, the value is based on the first and second comparison results. In some embodiments, server  103  can transmit the parameter to a node that is more closely associated with the acoustic environment being analyzed, such as a monitoring node at a call center that is used by the local technician. 
       FIG. 4  depicts a flowchart of the salient tasks performed by data-collection server  103 , as part of the third operating scenario described above. At task  401 , server  103  accumulates a first plurality of voice-quality measurements from a first set of one or more endpoints, in this case endpoints  102 - 1  through  102 - 10 . Server  103  also accumulates a second plurality of voice-quality measurements from a second set of one or more endpoints, in this case endpoints  102 - 11  through  102 - 20 . Endpoints  102 - 1  through  102 - 10  are capable of at least receiving voice signals that pass through a first telecommunications gateway, in this case gateway  104 - 7 , via a first receive path. Furthermore, endpoints  102 - 11  through  102 - 20  are capable of at least receiving voice signals that pass through a second telecommunications gateway, in this case gateway  104 - 8 , via a second receive path. In the example, gateway  104 - 7  provides access to the Verizon network, and gateway  104 - 8  provides access to the AT&amp;T network. As those who can appreciate, the gateways that are selected for the analysis alternatively can be those which provide access to the same service provider&#39;s network. 
     In accordance with the illustrative embodiment, server  103  accumulates voice-quality measurements from sets of endpoints. As those who are skilled in the art will appreciate, in some alternative embodiments, server  103  can instead accumulate pluralities of voice-quality measurements from network nodes that are not endpoints, such as the first and second telecommunications gateways. 
     In the example provided, the first set and second set of endpoints are mutually exclusive. As those who are skilled in the art will appreciate, however, the first and second sets of endpoints can comprise at least one endpoint that is common to both sets, or can even have the same exact endpoints in both sets. 
     In some embodiments, server  103  is able to select not only the gateways to analyze and the endpoints to use in the analysis, but also specific pathways through intermediate nodes within network  101  itself. For example, some of the voice-quality measurements that are selected for use can represent a path that passes through a private-branch exchange or a teleconference bridge in network  101 . Server  103  might or might not be accumulating statistics from the intermediate nodes, depending in part on the measuring capability of each intermediate node selected. 
     At task  402 , server  103  compares the first plurality of voice-quality measurements to a first theoretical target. The first theoretical target is a function of the audio-signal loss plan of enterprise network  101 . In some embodiments, the first theoretical target is also a function of a signal model of one or more of the endpoints in the first set (i.e., endpoints  102 - 1  through  102 - 10 ). The calculation of the theoretical target is described above and with respect to task  202 . The comparing task that is performed as part of task  402  results in a first comparison result. 
     At task  403 , server  103  compares the second plurality of voice-quality measurements to a second theoretical target. The second theoretical target is a function of the audio-signal loss plan of enterprise network  101 , where the function representing the second theoretical target might be the same as or might be different from the function represent the first theoretical target. In some embodiments, the second theoretical target is also a function of a signal model of one or more of the endpoints in the second set (i.e., endpoint  102 - 11  through  102 - 20 ). The comparing that is performed as part of task  403  results in a second comparison result. 
     At task  404 , server  103  outputs a value of a parameter that characterizes the first receive path (i.e., through gateway  104 - 7 ). In accordance with the illustrative embodiment, the value is based on at least one of the first and second comparison results. In some embodiments, server  103  also outputs a value of a parameter that characterizes the second receive path (i.e., through gateway  104 - 8 ). In accordance with the illustrative embodiment, this value is also based on at least one of the first and second comparison results. 
     It is to be understood that the disclosure teaches just one example of the illustrative embodiment and that many variations of the invention can easily be devised by those skilled in the art after reading this disclosure and that the scope of the present invention is to be determined by the following claims.