Using equalization coefficients of end devices in a cable television network to determine and diagnose impairments in upstream channels

Information

  • Patent Grant
  • 8526485
  • Patent Number
    8,526,485
  • Date Filed
    Wednesday, September 23, 2009
    15 years ago
  • Date Issued
    Tuesday, September 3, 2013
    11 years ago
Abstract
A system estimates impairment contributions for upstream communications in a cable television system. The system receives equalization coefficients used by end devices in the cable television system. The equalization coefficients are used by equalizers to mitigate distortion in upstream channels for the end devices. The system analyzes the coefficients based on impairment thresholds to determine whether impairment problems exist and to identify the types of impairment problems that exist.
Description
BACKGROUND

Cable television networks, including community antenna television (CATV), hybrid fiber-coaxial (HFC), and fiber networks, have been in widespread use for many years and are extensive. The extensive and complex cable networks are often difficult for a cable operator to manage and monitor. A typical cable network generally contains a headend which is usually connected to several nodes which provide bi-directional content to a cable modem termination system (CMTS). In many instances, several nodes may serve a particular area of a town or city. The CMTS contains several receivers, and each receiver connects to several modems of many subscribers. For instance, a single receiver may be connected to hundreds of modems at customer premises. Data may be transmitted downstream to the modems on different frequency bands. The modems communicate to the CMTS via upstream communications on a dedicated frequency band, referred to as a return band.


Cable networks are also increasingly carrying signals, which require a high quality and reliability of service, such as Voice over IP (VoIP) communications. Any disruption of voice or data traffic is a great inconvenience and often unacceptable to a customer. Various factors may affect the quality of service, including the quality of the upstream channels. One factor that affects the quality of upstream communications is the presence of up-stream channel impairments, such as micro-reflections (MRs) of communication signals, group delay variation (GDV), and amplitude distortion (AD).


AD is an undesirable variation in the channel's amplitude response. Common forms of AD include tilt, ripple, and roll-off. A common cause of AD is upper return band-edge carriers, aggravated by long reaches of a cable network plant. The long reaches accumulate diplex filters from devices including amplifiers and in-line equalizers. While individually contributing small attenuation versus frequency, the accumulated diplex filters can create appreciable response variation. In a QAM constellation, the amplitude roll-off causes the symbols to spread in a pattern similar in appearance to Additive White Gaussian Noise (AWGN) and causes received symbols to cross decision boundaries, resulting in errors.


GDV is an undesirable variation in the communication channel's phase response, resulting in distortion of the digital signal phase, or a variation in the propagation of frequency components of the signal across the channel. As is the case for AD, one major cause of GDV in the plant is upper-band-edge operation, combined with long reaches of cable network plant. The reasoning is the same as in the AD case. Note that filtering functions typically induce nonlinear phase responses as the band edges are approached, so the combination of AD and GDV in the same band region is perfectly expected, with the understanding that diplex filtering is the cause. Different filter functions induce different GDV responses, in a similar manner that different filter functions induce different stop-band characteristics. It is typical that the sharper the roll-off, such as would be the case for long cascades, the worse the GDV will be. In a QAM constellation, GDV causes the symbols to spread in a pattern similar to AWGN and AD and causes received symbols to cross decision boundaries, resulting in errors. 16-QAM is less sensitive to GDV than 64-QAM because of reduced decision boundary size of 64-QAM.


As seen by a receiver, a MR is a copy of the transmitted signal, arriving late and with reduced amplitude. The result of the additional copy is the typically seen by end users as image ghosting in analog video reception, whereas for digital communications the result is inter-symbol interference (ISI). MR sources are composed of pairs of hybrid fiber-coaxial (HFC) components separated by a distance of cable. The HFC components, also referred to as cable network components, facilitate the propagation of signal copies in a variety of ways including return loss, isolation, mixing, and combining. For instance, the MR may arise if a length of cable separates two devices with poor return loss, acting as signal reflectors. The reflector return loss and the loss between the reflectors determine the amplitude of the MR. Any HFC component, for instance a cable modem (CM), has the potential to act as a signal reflector. Note that the CM typically has as a design limit of 6 dB return loss, meaning it may reflect up to 25% of its incident power. In the cable network plant, components other then the CM typically reflect a lower percentage of incident power because the design limits are typically significantly better. However, as the cable network plant ages and elements that contribute to good RF matching degrade, for instance connectors, cable, splitters, and interfaces on printed circuit boards (PCBs), the reflected percentage of incident power increases.


These upstream channel impairments are known to be mitigated by the fundamental digital communications receiver function of equalization. During equalization, an equalizer generates coefficient information that is used to create an equalizing filter, with an inverse channel response, canceling distortion in the channel caused by the upstream channel impairments. The equalization coefficients in Data Over Cable Service Interface Specification (DOCSIS) 2.0 and DOCSIS 3.0 are 24 symbol-spaced coefficients (also referred to as taps). Equalization is part of virtually all modern telecommunications platforms, and is instrumental in proper return operation for all DOCSIS systems.


In order to offer higher data rates to subscribers in the competitive world of high-speed data and Internet access, operators must take advantage of the throughput benefits gained from leveraging more complex digital modulation schemes, such as 32-QAM and 64-QAM. Use of 32-QAM allows, for example, a 20 Mbps 16-QAM upstream to become a 25 Mbps upstream. On the other hand, for 64-QAM, it allows a 16-QAM, 20 Mbps upstream channel to become a 30 Mbps channel. This represents a 25-50% throughput improvement. Unfortunately, channels using these digital modulation schemes are also considerably more sensitive to digital communication channel impairments, including the upstream impairments described above, than the 16-QAM channels they are often replacing in the return band.


Given the potential problems that can be caused by the upstream impairments, upstream channels are one of the most challenging digital communication channels to manage and fully exploit. Operators prefer to ensure that capacity associated with the upstream channel, or as much of the capacity as possible, is realized for services and revenue. To do so requires a thorough understanding of a diverse set of HFC and digital communications variables. More importantly, variables that did not matter very much for 16-QAM operation now become not just relevant, but critical to understand for successful deployment of 64-QAM, and to a lesser extent, 32-QAM. Accurately diagnosing upstream issues typically requires technicians or engineers to be at multiple locations within a HFC plant and simultaneously inject test signals at the suspected device locations. This diagnostic process requires extensive manual effort, often requiring rolling trucks to remote locations within a plant or specialized test equipment. The diagnostic process is also time consuming and costly.


SUMMARY

According to an embodiment, a system estimates impairment contributions for upstream communications in a cable television system. The system receives equalization coefficients used by end devices in the cable television system. The equalization coefficients are used by equalizers to mitigate distortion in upstream channels for the end devices. The system analyzes the coefficients based on impairment thresholds to determine whether impairment problems exist in the upstream channels and to identify the types of impairment problems that exist. Other embodiments include computer-implemented methods estimating impairment contributions for upstream communications based on received equalization coefficients and impairment thresholds.


Embodiments interpret equalization coefficients for end devices and identify potential impairments of upstream channels for the end devices based on an analysis of the equalization coefficients. Also, a particular type of impairment problem can be identified based on the analysis of equalization coefficients. Determination of the type of impairment can be coupled with additional information, such as location of the end device or tap, to determine suspect cable network components that may be causing the impairment. Thus, identification of an impairment problem and potential solutions can be determined before a customer problem is experienced and without dispatching technicians to diagnose the problem.





BRIEF DESCRIPTION OF THE DRAWINGS

Features of the present invention will become apparent to those skilled in the art from the following description with reference to the figures, in which:



FIG. 1 illustrates a block diagram of a cable network, according to an embodiment of the invention;



FIG. 2 illustrates a CMTS architecture, according to an embodiment of the invention;



FIG. 3 illustrates a device for estimating impairment contributions and isolating defective network components, according to an embodiment of the invention; and



FIG. 4 illustrates a device for estimating impairment contributions and isolating defective network components, according to an embodiment of the invention;



FIG. 5 illustrates a method for estimating impairment contributions and isolating defective network components using a plurality of end devices, according to an embodiment of the invention; and



FIG. 6 shows a block diagram of a computer system that may be used for estimating impairment contributions and isolating defective network components, according to an embodiment of the invention.





DETAILED DESCRIPTION

For simplicity and illustrative purposes, the present invention is described by referring mainly to exemplary embodiments thereof. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that the present invention may be practiced without limitation to these specific details. In other instances, well known methods and structures have not been described in detail to avoid unnecessarily obscuring the present invention.


The abbreviation “decibels relative to a carrier (dBc)” refers to a measure of the power ratio of a signal to a carrier signal, and is expressed in decibels. Note “dB” refers to a decibel, “ns” refers to a nanosecond, and “MHz” refers to a megahertz.


The term “equalization coefficient” refers to complex tap values used to create an equalizing filter with an inverse channel response.


The term “impairment contribution” refers to causes of impairment in an upstream hybrid fiber coaxial (HFC) plant.


The term “micro-reflection (MR)” refers to an impairment contribution wherein a copy of a communication signal is reflected back onto itself, with a time delay. Significant MRs can degrade upstream HFC plant performance.


The term “group delay variation (GDV)” refers to an impairment contribution wherein different frequency components of a signal propagate through a network component with different time delays.


The term “cable network plant components” refers to any component that may cause impairment in an upstream channel in the cable network. The components may be components of an HFC network, and may be active or passive components. The upstream channel may be a channel between a modem and a CMTS or another upstream channel in the cable network.



FIG. 1 illustrates a network 100, such as an HFC network, including end devices 102. The end device 102 may be DOCSIS Terminal devices, such as cable modems (CMs), modem terminal adapters, MTAs, and embedded cable modems of DOCSIS set-top gateways (eCMs of DSGs), or any other like devices. The end devices 102 are connected to a headend 104 of the network 100 via nodes 106 and an RF cascade 103 comprised of multiple amplifiers and passive devices including cabling, taps, splitters, and in-line equalizers. A network tap is a hardware device providing access to data within the network 100. The network tap provides the ability to monitor data between two points, for instance components, in the network 100. An impairment contribution estimator 200, shown in FIG. 3, may be connected to the network 100 through any network access point including a tap. The headend 104 connects to an IP (Internet Protocol) and/or PSTN (Public Switched Telephone Network) network 108. Data, such as TV programs, audio, video and other data, which may be from the network 108, is sent from the headend 104 to the end devices 102. In addition, the end devices 102 may send data upstream towards the headend 104. Although not shown, each of the nodes 106 may be connected to multiple end devices.


As illustrated in FIG. 1, the headend 104 includes a CMTS 110 and optical transceivers 112 which provide optical communications to and from the CMTS 110 through optical fiber to the nodes 106. Typically, the nodes 106 connect to the headend 104, and the headend 104 contains a plurality of CMTS units 110. Each CMTS 110 contains a plurality of transceivers, which communicate with the plurality of end devices 102. For example, each CMTS 110 may have eight or more receivers (e.g., for DOCSIS 2.0), and each receiver may communicate with hundreds of end devices 102. The CMTS may have more than eight receivers (e.g., DOCSIS 3.0 may use 48 receivers).



FIG. 2 illustrates an architecture of the CMTS 110, according to an embodiment. As illustrated, the CMTS 110 includes a processing unit 114 having a microprocessor 116 that receives information, such as instructions and data, from a RAM 118 and a ROM 120. The processing unit 114 controls the operation of the CMTS 110 and RF communication signals to be sent by the end devices 102 to the CMTS 110. The processing unit 114 is connected to a display 122, which may display status information such as whether station maintenance (SM) is being performed, or a receiver is in need of load balancing. An input keypad 124 may also be connected to the processing unit 114 to permit an operator to provide instructions and process requests.


The CMTS 110 also includes an RF transceiver (transmitter/receiver) unit 126 having transmitters 128 and receivers 130 providing bi-directional communication capability with the end devices 102 through optical transceivers 112, nodes 106 and an RF cascade 103 comprised of multiple amplifiers and passive devices including cabling, taps, splitters, and in-line equalizers. The CMTS 110 may contain a plurality of RF receivers 130, such as eight RF receivers and a spare RF receiver. Each of the RF receivers 130 may provide support for a hundred or more end devices 102.


By way of example, the receivers 130 can be BROADCOM 3140 receivers that each includes a demodulator unit 132 and an equalizer 134 to which received RF signals are provided, for instance, for purposes of acquiring equalizer values and burst modulation error ratio (MER) measurements, packet error rate (PER) and bit error rate (BER). The equalizer 134 can be a multiple tap linear equalizer (e.g. a twenty-four tap linear equalizer), which also is known as a feed forward equalizer (FFE). The equalizer 134 can be integrally contained in the RF receiver, or alternatively, may be provided as a separate device. The communication characteristics of each receiver 130 may be stored on ROM 120 or RAM 118, or may be provided from an external source. Note that the equalizer 134 is in the upstream path, for example, from the end devices 102 towards the network 108.


The RF transceiver unit 126 also includes a modulator 136, which provides the modulated signals to RF transmitters 128. The modulator 136 and demodulator 132 are capable of modulation schemes of various levels of complexity. For example, some upstream DOCSIS 2.0 modulation schemes that may be used in order of level of complexity include, but are not limited to 16 QAM, 32 QAM, 64 QAM and 128 QAM. The microprocessor 116 may provide instructions to the end devices 102 as to which modulation scheme is to be used during communication.


The CMTS 110 also provides instructions for the end devices 102 using a transmit pre-equalization (PRE-EQ) feature in order to compensate for upstream channel impairments. The CMTS 110 receives an incoming signal from each of the end devices 102 and compares the incoming signal with an expected signal, which is an ideal response. If the incoming signal received by the CMTS 110 differs from the expected signal, the microprocessor 116 or other processing device performing a PRE-EQ function then determines a set of equalization coefficients (alternately referred to as transmit pre-equalization coefficients) for each of the end devices 102 and instructs the end devices 102 to set their transmit equalization coefficients to the transmit pre-equalization coefficients determined by the PRE-EQ function. The end devices 102 apply the pre-equalization coefficients and then continue to transmit. The CMTS 110 thereafter continues to monitor and compare the incoming signal against the expected signal.



FIG. 3 illustrates an architecture of an impairment contribution estimator 200. The impairment contribution estimator 200 may be connected to the network 100 through any network access point, for instance through a network access terminal. The impairment contribution estimator 200 is configured for estimating impairment contributions and isolating defective network components in the system 100 according to the method 300 below. As such, the impairment contribution estimator 200 includes a data storage device 201, and a testing module 202. The testing module 202 includes an equalization coefficient receiving (ECRC) module 203, an equalization coefficient resolution (ECRS) module 204, an impairment level determination (ILD) module 205, and a cable network plant components isolation (CPCI) module 206. The testing module 201 may also include a modulation configuration (MC) module (not shown).


The data storage device 201 is configured to store an impairment threshold for at least one impairment contribution. The ECRC module 203 is configured to receive equalization coefficients from the end devices 102. The equalization coefficients are thereafter stored in the data storage device 201. The ECRS module 204 is configured to resolve the equalization coefficients into the at least one impairment contribution. The ILD module 205 is configured to determine whether each of the end devices 102 exceeds the impairment threshold and to group each of the end devices 102 into sets that exceed impairment thresholds as impaired sets or sets that do not exceed impairment thresholds as unimpaired sets. The CPCI module 206 is configured to identify cable network plant components associated with each of the ILD sorted sets wherein the cable network plant components are designated as suspect components. cable network plant components are correlated with each set of end devices, for example, based on whether they are used in an upstream or downstream path for an end device.


The components 202-206 are configured to perform the method 300 described with respect to FIG. 5. The components 202-206 may comprise software modules, hardware modules, and a combination of software and hardware modules. Thus, in one embodiment, one or more of the modules 202-206 comprise circuit components. In another embodiment, one or more of the modules 202-206 comprise software code stored on a computer readable storage medium, which is executable by a processor. It should be understood that the impairment contribution estimator 200 depicted in FIG. 3 may include additional components and that some of the components described herein may be removed and/or modified without departing from a scope of the impairment contribution estimator 200. According to an embodiment, the impairment contribution estimator 200 comprises a part of a network device such as a RF-Sentry application. According to another embodiment, the impairment contribution estimator 200 comprises a part an edge router, such as a part of the advanced spectrum management function of the BSR64000 edge router.



FIG. 4 illustrates an embodiment of one of the end devices 102 (shown as 102a), such as a cable modem. The end device 102a contains a processor 181 which communicates with a RAM 182 and ROM 183 and which controls the general operation of the end device 102, including applying the pre-equalization coefficients and controlling preamble lengths of communications sent by the end device 102a in accordance with instructions from the CMTS 110. The end device 102a also contains a transceiver 186 which provides bidirectional RF communication with the CMTS 110. A demodulator 185 demodulates signals received by the transceiver 186, and an equalizer 187 biases communications transmitted to the CMTS 110. For example, the equalizer 187 is connected in the upstream path between a transmitter in the transceiver 186 and the CMTS 110. The microprocessor 181 configures the equalizer 187 using the coefficients received from the CMTS 110 to compensate for upstream impairments. The end device 102a also contains a modulator 188, which modulates signals to be transmitted upstream to the CMTS 110 according to a modulation scheme, which the end device 102a has been instructed to use by the CMTS 110. In addition, the end device 102a has an attenuator 189 controlled by microprocessor 181 to attenuate signals to be transmitted by the RF transmitter to be within a desired power level. Those of skill in the art will appreciate that the components of end device 102a have been illustrated separately only for discussion purposes and that various components may be combined in practice.


By way of example, the end device 102a may be a DOCSIS network element, such as a cable modem, to generate a variety of test signals. Accordingly, the test signals may be implemented using one of the available upstream DOCSIS bandwidths, e.g. 200 kHz, 400 kHz, 800 kHz, 1600 kHz, 3200 kHz or 6400 kHz.


Accurate knowledge of the available and/or optimum modulation schemes of the network 100 enables the operator to utilize available resources of their network more efficiently, such as by adding additional end devices to improve portions of the network with the least complex modulation schemes so that those portions may be able to use more complex modulation schemes.


It will be apparent that the system 100 may include additional elements not shown and that some of the elements described herein may be removed, substituted and/or modified without departing from the scope of the system 100. It should also be apparent that one or more of the elements described in the embodiment of FIG. 1 may be optional.


An example of a method in which the system 100 and the impairment contribution estimator 200 may be employed for estimating impairment contributions and isolating defective network components using the end devices 102 will now be described with respect to the following flow diagram of the method 300 depicted in FIG. 5. It should be apparent to those of ordinary skill in the art that the method 300 represents a generalized illustration and that other steps may be added or existing steps may be removed, modified or rearranged without departing from the scopes of the method 300. In addition, the method 300 is described with respect to the system 100 by way of example and not limitation, and the method 300 may be used in other systems.


Some or all of the operations set forth in the method 300 may be contained as one or more computer programs stored in any desired computer readable medium and executed by a processor on a computer system. Exemplary computer readable media that may be used to store software operable to implement the present invention include but are not limited to conventional computer system RAM, ROM, EPROM, EEPROM, hard disks, or other data storage devices.


At step 301, as shown in FIG. 5, the impairment contribution estimator 200 retrieves at least one impairment threshold corresponding to an impairment contribution from the data storage 201. The impairment contribution may be selected from the group including GDV, AD, MR and any impairment contribution that may be isolated by analysis of the coefficients as described in detail at step 303 below. At least one impairment threshold corresponding to the impairment contribution may be selected from the group comprising an industry standard specification, a customer preferred limit, a PRE-EQ failure limit, a PRE-EQ failure limit less acceptable system margin and, where applicable, a function of signaling characteristics. Signaling characteristics include, for instance, RF frequency, QAM modulation level, bandwidth, symbol rate, forward error correction (FEC) settings, and other properties related to signaling.


To illustrate, where the impairment contribution is GDV, the impairment threshold may be selected from the group comprising the industry standard specification (for GDV), the customer preferred limit, the PRE-EQ failure limit, the PRE-EQ failure limit less acceptable system margin and a function of a radio frequency (RF) cascade. The function of the RF cascade may comprise a to-be-determined (TBD) value in ns/MHz per RF Amplifier. For instance, a DOCSIS assumption for GDV is 200 ns/MHz.


Next, where the impairment contribution is AD, the impairment threshold may be any of the industry standard specification. For instance any of a DOCSIS assumption for amplitude ripple of ≦0.5 dB per MHz, the customer preferred limit, the PRE-EQ failure limit, the PRE-EQ failure limit less acceptable system margin and a function of RF frequency and RF amplifier cascade length.


Similarly, where the impairment contribution is MR, the impairment threshold may be any of the industry standard specification. For instance a DOCSIS assumption of −10 dBc@<=0.5 μsec (alternately −20 dBc@<=1.0 μsec, or −30 dBc@>1.0 μsec) for a single dominant MR, the customer preferred limit, the PRE-EQ failure limit, the PRE-EQ failure limit less acceptable system margin, and a function of RF frequency. Simulation and tests may be performed to determine the highest MR impairment level that is correctable using DOCSIS 2.0/3.0 PRE-EQ. The results of these simulations may be used to define the PRE-EQ failure limit.


Further, the impairment contribution may comprise any impairment contribution that may be isolated by analysis of the coefficients, for instance as described at step 303 below. After the impairment contribution has been isolated, the at least one impairment threshold corresponding to the impairment contribution may be thereafter selected in a similar manner as described above with regard to the impairment threshold for AD, MR, and GDV.


At step 302, the impairment contribution estimator 200 determines the equalization coefficients currently being used by the end devices 102 for upstream communication. The equalization coefficients may be received from the end devices 102 or the CMTS 110. The end devices 102 may comprise at least one of the group comprising DOCSIS terminal devices, including cable modems (CMs), modem terminal adapters, (MTAs), and embedded cable modems of DOCSIS set-top gateways, (eCMs of DSGs). The resolution of the 24-tap equalizer of DOCSIS 2.0 more effectively identifies impairments, compared to the 8-tap equalizer of DOCSIS 1.1. In a current HFC plant, in order to more effectively identify impairments, the majority of the end devices 102 are required to support at least DOCSIS 2.0 with the pre-equalization feature enabled.


The ECRC module 203 may be configured to query the end devices 102 (preferably a DOCSIS 2.0 CM population) using a simple network management protocol (SNMP) query tool such as a modem PRE-EQ response tool. The modem PRE-EQ response tool, developed by MOTOROLA, is operable to query multiple DOCSIS terminal devices based on an Internet protocol (IP) address list. The modem PRE-EQ response tool is operable to conduct periodic polls of coefficient values and other relevant physical layer (PHY) metrics and to subsequently display the results of the periodic polls and/or to store the results of the periodic polls into a log file for post processing. The modem PRE-EQ response tool also provides users with a graphical view of the impulse response or alternately the amplitude response for each CM poll. The modem PRE-EQ response tool is operable to establish a baseline of performance, and may be used to identify defective network components based on CM IP addresses of the plurality of end devices.


At step 303, the impairment contribution estimator 200 determines whether an impairment problem exists for upstream communications from the end devices 102. The determination is based on an analysis of the coefficients determined from step 302 and may be based on the impairment thresholds determined from step 301. There may be multiple techniques for determining whether an impairment problem exists. In one embodiment, the coefficients are analyzed to determine whether any of the impairment thresholds are exceeded. For example, based on experience, certain coefficient values are associated with certain impairment problems and exceeded impairment thresholds. A table may be stored that includes sets of coefficient values (e.g., impairment coefficient signatures) and the type of impairment problem associated with each set of values. This tables of signatures is compared against each of the coefficients determined at step 302. If an impairment coefficient signature is found in coefficients determined at step 302, then the end device using those coefficients is determined to have the particular type of impairment associated with the signature as indicated in the table. Thus, at least two determinations may be made. One determination is whether an impairment problem exists, such as unsatisfactory GDV, AR, MR, etc. Then, if an impairment problem exists, at step 304, a second determination is made which identifies the type of impairment.


According to an embodiment, at step 303, to determine if an impairment problem exists, the ECRS module 204 performs a Fast Fourier Transform (FFT) function on the equalization coefficients for the end devices 102 (e.g. a set of 24 complex coefficients in DOCSIS 2.0), and determines frequency domain information, including a frequency response. For instance, the ECRS module 204 may use a 1024-point FFT to arrange the equalization coefficients for the PRE-EQ baseline and determine the optimal translation of the equalization coefficients. The frequency domain information may be interpreted in multiple ways including in terms of magnitude versus frequency, phase versus frequency, and group delay versus frequency. Based on these magnitudes, a determination is made as to the type of impairment problem that exists, if any exists. For example, negligible amplitude correction but increased correction for phase and group delay is indicative of a GDV impairment. Similarly, other types of impairments can be determined. For example, the end devices 102 are sorted into sets, on increasing levels that sum the DOCSIS PRE-EQ regions for each of the end devices 102, according to the impairment that the ECRS module 204 is configured to determine. For example, the ECRS module 204 may determine which of the end devices 102 experiences the greatest amount of MR impairment contribution by sorting on the levels which result from summing the taps located in the post-tap region of each tap of the 24-tap equalizer of DOCSIS 2.0.


At step 304, the ILD module 205 determines the type of impairment for each end device, for example, if the impairment threshold is exceeded for the end device. In one embodiment, the ILD module 205 groups each of the end devices 102 into impairment level determined (ILD) sets. The ILD sets include impaired sets comprising end devices that exceed impairment thresholds and unimpaired sets comprised of end devices that do not exceed impairment thresholds as unimpaired sets. Furthermore, the impairment sets may include sets by type of impairment and may indicate the level of impairment for each end device. In one embodiment, the ILD module 205 determines the relation of the measured impairment contribution to the impairment threshold for each of the impairment contributions. If the impairment contribution exceeds the impairment threshold, the upstream impairments may be at a level at which a customer problem is experienced. Alternately, if the impairment threshold has an acceptable system margin, the ILD module 205 is configured to provide information so that an end user may perform preventive maintenance. The ILD module 205 may also be configured to determine a dominant impairment contribution. For instance, the ILD module 205 may analyze the translation of the equalization coefficients of the end devices 102, and an expected translation of the equalization coefficients for each of the impairment contributions in order to determine the dominant impairment contribution. The expected translation of the equalization coefficients for each of the impairment contributions comprises a translation of equalization coefficients for a channel with a single impairment, for instance AD.


The operation of the ILD module 205 may be enhanced by application of an increased understanding of the different impairment contributions and how they originate in HFC plant. For example, although an MR source has been discussed in the preceding section regarding MRs, combining an understanding of other probable permutations of MR sources with the location of the ILD sets increases the probability of successful isolation of the MR sources. The understanding of probable sources may be used to eliminate possible sources of the impairment contribution and to therefore isolate the source of the impairment contribution. The results may be used to define what impairment levels will likely result in service calls, and thereafter impairment thresholds as defined at step 301 may be determined. Further, the ILD module 205 may be configured to prioritize the impaired sets or prioritize end devices in each set according to level of impairment.


At step 305, suspect cable network components are identified that are probable causes for the type of impairment being experienced by an end device. Identification of the suspect components may be based on experience or historical analysis of past impairments and their fixes. For example, the CPCI module 206 identifies cable network plant components associated with each of the impaired sets. This process of identification may be enhanced by consulting data regarding the end devices 102 and network components between each of the plurality of end devices and the CMTS 110. The CPCI module 206 identifies the cable network components associated with impaired sets as suspect components. The CPCI module 206 then leverages the end devices 102 to isolate those experiencing an impairment problem related to a specific impairment contribution. For example, a query of the end devices 102 may reveal that all of the end devices 102 located off a particular node are reporting a MR impairment contribution above the impairment threshold for MR, while the other end devices 102, unimpaired sets are not reporting a problem.


At step 306, corrective action is taken. For example, the operator physically inspects all suspect components isolated at step 305 and repairs and replaces as necessary the defective components. The impairment contribution estimator 200 may provide guidance helping cable operators decide the significance of the information that they are analyzing. The impairment contribution estimator 200 may contain a checklist of possible sources of the impairment contribution, preferably sorted in order of probability. For instance, inspection of the suspect components may show that the MR impairment contribution source is a combination of tap-to-output port isolation loss and an improperly terminated cable splice at the end of a feed amplifier. By properly terminating the splice, the operator may reduce the MR to negligible amplitudes. Alternately, the impairment contribution estimator 200 may sort the impaired sets into a less impaired set of devices and a more impaired set of devices according to a level of impairment and route traffic to another channel that the impairment contribution estimator 200 indicates is less impaired.


The steps of the method 300 may be repeated periodically and for each of the end devices 102 or groups of end devices to detect future impairment problems and to ensure that detected impairment problems are eliminated and the improvements are sustainable. If the operator is preparing to upgrade the network 100 to a higher modulation scheme, for instance upgrading from 16-QAM to 64-QAM, the operator may perform the method 300 in order to determine potential problem components. In order to test the network 100, the operator may configure the network at the higher modulation scheme. Thereafter, the operator may perform the testing process of the method 300, designating the suspect components as potential upgrade components.


Although described specifically throughout the entirety of the instant disclosure, representative embodiments of the present invention have utility over a wide range of applications, and the above discussion is not intended and should not be construed to be limiting, but is offered as an illustrative discussion of aspects of the invention.


Embodiments of the present invention interpret equalization coefficients for end devices and identify potential impairments of upstream channels for the end devices based on an analysis of the equalization coefficients. Also, a particular type of impairment problem can be identified based on the analysis of equalization coefficients. Determination of the type of impairment can be coupled with additional information, such as location of the end device or tap, to determine suspect cable network components that may be causing the impairment. Thus, identification of an impairment problem and potential solutions can be determined before a customer problem is experienced and without dispatching technicians to diagnose the problem.


What has been described and illustrated herein are embodiments of the invention along with some of their variations. The terms, descriptions and figures used herein are set forth by way of illustration only and are not meant as limitations. Those skilled in the art will recognize that many variations are possible within the spirit and scope of the invention, wherein the invention is intended to be defined by the following claims—and their equivalents—in which all terms are meant in their broadest reasonable sense unless otherwise indicated.

Claims
  • 1. A system for identifying suspect cable network plant components causing an upstream impairment, the system comprising: a data storage device configured to store an impairment threshold for at least one impairment contribution; anda testing module configured to perform a testing process, the testing module including an equalization coefficient receiving module (ECRC) configured to receive equalization coefficients from a plurality of end devices; andan impairment level determination (ILD) module configured to determine whether an impairment exists for each of the end devices and to determine a type of impairment using the received equalization coefficients and the impairment threshold.
  • 2. The system of claim 1, wherein the at least one impairment contribution comprises at least one of group delay variation (GDV), amplitude distortion (AD), micro-reflection (MR), and an impairment contribution isolated by analysis of the equalization coefficients.
  • 3. The system of claim 1, wherein the at least one impairment contribution includes a plurality of impairment contributions and the ILD module is further configured to compare the plurality of impairment contributions to determine a dominant impairment contribution.
  • 4. The system of claim 1, further comprising: an ECRC module configured to receive a set of equalization coefficients after corrective action for the suspect components is performed and to inform an operator whether the corrective action was effective.
  • 5. The system of claim 1, wherein the equalization coefficients are translated into frequency domain information to determine whether an impairment exists.
  • 6. The system of claim 1, further comprising: an impairment contribution estimator configured to provide a checklist of possible sources of the impairment contribution.
  • 7. The system of claim 1, further comprising: a modulation configuration (MC) module operable to configure the system to a more advanced modulation scheme; andwherein the testing module is further configured to perform a test on the system at the more advanced modulation scheme and to designate the suspect components as potential upgrade components.
  • 8. A method for estimating impairments for a plurality of end devices, the method comprising: retrieving an impairment threshold for at least one impairment contribution from a data storage device;receiving equalization coefficients for the plurality of end devices;determining whether an impairment exists for each of the plurality of end devices using the equalization coefficients and a determination of whether the impairment threshold for the at least one impairment contribution is exceeded; andif an impairment exists for one or more of the plurality of end devices, then determining a type of impairment for each existing impairment.
  • 9. The method of claim 8, wherein the type of impairment is determined from the impairment contribution for the exceeded threshold.
  • 10. The method of claim 8, further comprising: identifying suspect cable network components causing each impairment at least from the determined type of impairment.
  • 11. The method of claim 10, further comprising: inspecting the suspect components to identify defective components;performing a corrective action on the defective components;receiving a corrected set of equalization coefficients; anddetermining whether the corrective action was not effective.
  • 12. The method of claim 8, wherein the impairment contributions are taken from the group comprising GDV, AD, MR and other impairment contributions that may be isolated by analysis of the equalization coefficients.
  • 13. The method of claim 8, wherein the impairment threshold for the at least one impairment contribution comprises one of an industry standard specification, a customer preferred limit, a PRE-EQ failure limit, a PRE-EQ failure limit less acceptable margin, and a function of signaling characteristics.
  • 14. The method of claim 8, wherein the plurality of end devices comprises at least one of the group comprising DOCSIS terminal devices, including cable modems (CMs), modem terminal adapters, (MTAs), and embedded cable modems of DOCSIS set-top gateways (eCMs of DSGs).
  • 15. The method of claim 8, further comprising: sorting the plurality of end devices into sets that exceed the impairment contribution threshold, wherein end devices are grouped by similar communication channel characteristics and shared common path through a cable network plant components to a CMTS.
  • 16. The method of claim 15, further comprising: prioritizing the suspect components according to level of impairment.
  • 17. The method of claim 15, further comprising: sorting impaired sets into a less impaired set of end devices and a more impaired set of end devices according to a level of impairment; androuting a modulation scheme through the more impaired set of end devices and a more advanced modulation scheme through the less impaired set of end devices.
  • 18. A computer readable storage device storing at least one computer program that when executed by a computer system performs a method comprising: retrieving an impairment threshold for at least one impairment contribution from a data storage device;receiving equalization coefficients for a plurality of end devices;determining whether an impairment exists for each of the plurality of end devices using the equalization coefficients and a determination of whether the impairment threshold for the at least one impairment contribution is exceeded; andif an impairment exists for one or more of the plurality of end devices, then determining the type of impairment for each existing impairment.
  • 19. The computer readable storage device of claim 18, wherein the type of impairment is determined from the impairment contribution for the exceeded threshold.
  • 20. The computer readable storage device of claim 18, wherein the method comprises: identifying suspect cable network components causing each impairment at least from the determined type of impairment.
US Referenced Citations (275)
Number Name Date Kind
3838221 Schmidt et al. Sep 1974 A
4245342 Entenman Jan 1981 A
4385392 Angell et al. May 1983 A
4811360 Potter Mar 1989 A
4999787 McNally et al. Mar 1991 A
5228060 Uchiyama Jul 1993 A
5251324 McMullan, Jr. et al. Oct 1993 A
5271060 Moran et al. Dec 1993 A
5278977 Spencer et al. Jan 1994 A
5347539 Sridhar et al. Sep 1994 A
5390339 Bruckert et al. Feb 1995 A
5463661 Moran et al. Oct 1995 A
5532865 Utsumi et al. Jul 1996 A
5557603 Barlett et al. Sep 1996 A
5606725 Hart Feb 1997 A
5631846 Szurkowski May 1997 A
5692010 Nielsen Nov 1997 A
5694437 Yang et al. Dec 1997 A
5732104 Brown et al. Mar 1998 A
5790523 Ritchie et al. Aug 1998 A
5867539 Koslov Feb 1999 A
5870429 Moran et al. Feb 1999 A
5886749 Williams et al. Mar 1999 A
5939887 Schmidt et al. Aug 1999 A
5943604 Chen et al. Aug 1999 A
6032019 Chen et al. Feb 2000 A
6061393 Tsui et al. May 2000 A
6108351 Hardy et al. Aug 2000 A
6154503 Strolle Nov 2000 A
6229792 Anderson et al. May 2001 B1
6230326 Unger et al. May 2001 B1
6233274 Tsui et al. May 2001 B1
6240553 Son et al. May 2001 B1
6272150 Hrastar et al. Aug 2001 B1
6278730 Tsui et al. Aug 2001 B1
6308286 Richmond et al. Oct 2001 B1
6310909 Jones Oct 2001 B1
6321384 Eldering Nov 2001 B1
6330221 Gomez Dec 2001 B1
6334219 Hill et al. Dec 2001 B1
6377552 Moran et al. Apr 2002 B1
6385773 Schwartzman et al. May 2002 B1
6389068 Smith et al. May 2002 B1
6434583 Dapper et al. Aug 2002 B1
6445734 Chen et al. Sep 2002 B1
6456597 Bare Sep 2002 B1
6459703 Grimwood et al. Oct 2002 B1
6477197 Unger Nov 2002 B1
6480469 Moore et al. Nov 2002 B1
6483033 Simoes et al. Nov 2002 B1
6498663 Farhan et al. Dec 2002 B1
6512616 Nishihara Jan 2003 B1
6526260 Hick et al. Feb 2003 B1
6546557 Ovadia Apr 2003 B1
6556239 Al-Araji et al. Apr 2003 B1
6556562 Bhagavath et al. Apr 2003 B1
6556660 Li et al. Apr 2003 B1
6559756 Al-araji et al. May 2003 B2
6563868 Zhang et al. May 2003 B1
6570394 Williams May 2003 B1
6570913 Chen May 2003 B1
6574797 Naegeli et al. Jun 2003 B1
6588016 Chen et al. Jul 2003 B1
6606351 Dapper Aug 2003 B1
6611795 Cooper Aug 2003 B2
6646677 Noro et al. Nov 2003 B2
6662135 Burns et al. Dec 2003 B1
6662368 Cloonan et al. Dec 2003 B1
6671334 Kuntz et al. Dec 2003 B1
6687632 Rittman Feb 2004 B1
6690655 Miner et al. Feb 2004 B1
6700875 Schroeder et al. Mar 2004 B1
6700927 Esliger et al. Mar 2004 B1
6711134 Wichelman et al. Mar 2004 B1
6741947 Wichelman et al. May 2004 B1
6748551 Furudate et al. Jun 2004 B2
6757253 Cooper et al. Jun 2004 B1
6772388 Cooper et al. Aug 2004 B2
6772437 Cooper et al. Aug 2004 B1
6775840 Naegel et al. Aug 2004 B1
6816463 Cooper et al. Nov 2004 B2
6839829 Daruwalla et al. Jan 2005 B1
6853932 Wichelman et al. Feb 2005 B1
6877166 Roeck et al. Apr 2005 B1
6895043 Naegeli et al. May 2005 B1
6895594 Simoes et al. May 2005 B1
6906526 Hart et al. Jun 2005 B2
6928475 Schenkel et al. Aug 2005 B2
6944881 Vogel Sep 2005 B1
6961314 Quigley et al. Nov 2005 B1
6961370 Chappell Nov 2005 B2
6967994 Boer et al. Nov 2005 B2
6973141 Isaksen et al. Dec 2005 B1
6985437 Vogel Jan 2006 B1
6999408 Gomez Feb 2006 B1
7002899 Azenkot et al. Feb 2006 B2
7010002 Chow et al. Mar 2006 B2
7032159 Lusky et al. Apr 2006 B2
7039939 Millet et al. May 2006 B1
7050419 Azenkot et al. May 2006 B2
7054554 McNamara et al. May 2006 B1
7058007 Daruwalla et al. Jun 2006 B1
7072365 Ansley Jul 2006 B1
7079457 Wakabayashi et al. Jul 2006 B2
7099412 Coffey Aug 2006 B2
7099580 Bulbul Aug 2006 B1
7139283 Quigley et al. Nov 2006 B2
7142609 Terreault et al. Nov 2006 B2
7152025 Lusky et al. Dec 2006 B2
7158542 Zeng et al. Jan 2007 B1
7164694 Nodoushani et al. Jan 2007 B1
7177324 Choudhury et al. Feb 2007 B1
7197067 Lusky et al. Mar 2007 B2
7222255 Claessens et al. May 2007 B1
7227863 Leung et al. Jun 2007 B1
7242862 Saunders et al. Jul 2007 B2
7246368 Millet et al. Jul 2007 B1
7263123 Yousef Aug 2007 B2
7274735 Lusky et al. Sep 2007 B2
7295518 Monk et al. Nov 2007 B1
7315573 Lusky et al. Jan 2008 B2
7315967 Azenkot et al. Jan 2008 B2
7400677 Jones Jul 2008 B2
7421276 Steer et al. Sep 2008 B2
7451472 Williams Nov 2008 B2
7492703 Lusky et al. Feb 2009 B2
7554902 Kim et al. Jun 2009 B2
7573884 Klimker et al. Aug 2009 B2
7573935 Min et al. Aug 2009 B2
7584298 Klinker et al. Sep 2009 B2
7616654 Moran et al. Nov 2009 B2
7650112 Utsumi et al. Jan 2010 B2
7672310 Cooper et al. Mar 2010 B2
7684315 Beser Mar 2010 B1
7684341 Howald Mar 2010 B2
7693090 Kimpe Apr 2010 B1
7716712 Booth et al. May 2010 B2
7739359 Millet et al. Jun 2010 B1
7742697 Cooper et al. Jun 2010 B2
7742771 Thibeault Jun 2010 B2
7760624 Goodson et al. Jul 2010 B1
7778314 Wajcer et al. Aug 2010 B2
7787557 Kim et al. Aug 2010 B2
7792183 Massey et al. Sep 2010 B2
7856049 Currivan et al. Dec 2010 B2
7876697 Thompson et al. Jan 2011 B2
7953144 Allen et al. May 2011 B2
7970010 Denney et al. Jun 2011 B2
8000254 Thompson et al. Aug 2011 B2
8037541 Montague et al. Oct 2011 B2
8040915 Cummings Oct 2011 B2
8059546 Pai et al. Nov 2011 B2
8081674 Thompson et al. Dec 2011 B2
8116360 Thibeault Feb 2012 B2
8265559 Cooper et al. Sep 2012 B2
8284828 Cooper et al. Oct 2012 B2
8345557 Thibeault et al. Jan 2013 B2
20010055319 Quigley et al. Dec 2001 A1
20020038461 White et al. Mar 2002 A1
20020044531 Cooper et al. Apr 2002 A1
20020091970 Furudate et al. Jul 2002 A1
20020116493 Schenkel et al. Aug 2002 A1
20020154620 Azenkot et al. Oct 2002 A1
20020168131 Walter et al. Nov 2002 A1
20020181395 Foster et al. Dec 2002 A1
20030028898 Howald Feb 2003 A1
20030043732 Walton et al. Mar 2003 A1
20030067883 Azenkot et al. Apr 2003 A1
20030101463 Greene et al. May 2003 A1
20030108052 Inoue et al. Jun 2003 A1
20030120819 Abramson et al. Jun 2003 A1
20030138250 Glynn Jul 2003 A1
20030149991 Reidhead et al. Aug 2003 A1
20030158940 Leigh Aug 2003 A1
20030179768 Lusky et al. Sep 2003 A1
20030179770 Reznik et al. Sep 2003 A1
20030179821 Lusky et al. Sep 2003 A1
20030181185 Lusky et al. Sep 2003 A1
20030182664 Lusky et al. Sep 2003 A1
20030185176 Lusky et al. Oct 2003 A1
20030188254 Lusky et al. Oct 2003 A1
20030200317 Zeitak et al. Oct 2003 A1
20030212999 Cai Nov 2003 A1
20040015765 Cooper et al. Jan 2004 A1
20040042385 Kim et al. Mar 2004 A1
20040047284 Eidson Mar 2004 A1
20040062548 Obeda et al. Apr 2004 A1
20040073937 Williams Apr 2004 A1
20040096216 Ito May 2004 A1
20040109661 Bierman et al. Jun 2004 A1
20040139473 Greene Jul 2004 A1
20040163129 Chapman et al. Aug 2004 A1
20040181811 Rakib Sep 2004 A1
20040208513 Peddanarappagari et al. Oct 2004 A1
20040233234 Chaudhry et al. Nov 2004 A1
20040233926 Cummings Nov 2004 A1
20040248520 Miyoshi Dec 2004 A1
20040261119 Williams et al. Dec 2004 A1
20050010958 Rakib et al. Jan 2005 A1
20050025145 Rakib et al. Feb 2005 A1
20050034159 Ophir et al. Feb 2005 A1
20050039103 Azenko et al. Feb 2005 A1
20050058082 Moran et al. Mar 2005 A1
20050064890 Johan et al. Mar 2005 A1
20050097617 Currivan et al. May 2005 A1
20050108763 Baran et al. May 2005 A1
20050122996 Azenkot et al. Jun 2005 A1
20050163088 Yamano et al. Jul 2005 A1
20050175080 Bouillett Aug 2005 A1
20050183130 Sadja et al. Aug 2005 A1
20050198688 Fong Sep 2005 A1
20050226161 Jaworski Oct 2005 A1
20050281200 Terreault Dec 2005 A1
20060013147 Terpstra et al. Jan 2006 A1
20060121946 Walton et al. Jun 2006 A1
20060250967 Miller et al. Nov 2006 A1
20060262722 Chapman et al. Nov 2006 A1
20070002752 Thibeault et al. Jan 2007 A1
20070058542 Thibeault Mar 2007 A1
20070076592 Thibeault et al. Apr 2007 A1
20070076789 Thibeault Apr 2007 A1
20070076790 Thibeault et al. Apr 2007 A1
20070086328 Kao et al. Apr 2007 A1
20070094691 Gazdzinski Apr 2007 A1
20070097907 Cummings May 2007 A1
20070133672 Lee et al. Jun 2007 A1
20070143654 Joyce et al. Jun 2007 A1
20070147489 Sun et al. Jun 2007 A1
20070177526 Siripunkaw et al. Aug 2007 A1
20070184835 Bitran et al. Aug 2007 A1
20070189770 Sucharczuk et al. Aug 2007 A1
20070206600 Klimker et al. Sep 2007 A1
20070206625 Maeda Sep 2007 A1
20070211618 Cooper et al. Sep 2007 A1
20070223920 Moore et al. Sep 2007 A1
20070245177 Cooper et al. Oct 2007 A1
20080056713 Cooper et al. Mar 2008 A1
20080062888 Lusky et al. Mar 2008 A1
20080075157 Allen et al. Mar 2008 A1
20080101210 Thompson et al. May 2008 A1
20080125984 Skendzic et al. May 2008 A1
20080140823 Thompson et al. Jun 2008 A1
20080193137 Thompson et al. Aug 2008 A1
20080200129 Cooper et al. Aug 2008 A1
20080242339 Anderson Oct 2008 A1
20080250508 Montague et al. Oct 2008 A1
20080274700 Li Nov 2008 A1
20080291840 Cooper et al. Nov 2008 A1
20090031384 Brooks et al. Jan 2009 A1
20090103557 Hong et al. Apr 2009 A1
20090103669 Kolze et al. Apr 2009 A1
20090109877 Murray et al. Apr 2009 A1
20090249421 Liu et al. Oct 2009 A1
20090252234 Samdani et al. Oct 2009 A1
20100083356 Steckley et al. Apr 2010 A1
20100095360 Pavlovski et al. Apr 2010 A1
20100154017 An et al. Jun 2010 A1
20100157824 Thompson et al. Jun 2010 A1
20100158093 Thompson et al. Jun 2010 A1
20100185391 Lee et al. Jul 2010 A1
20100223650 Millet et al. Sep 2010 A1
20100251320 Shafer et al. Sep 2010 A1
20110026577 Primo et al. Feb 2011 A1
20110030019 Ulm et al. Feb 2011 A1
20110069745 Thompson et al. Mar 2011 A1
20110072127 Gerber et al. Mar 2011 A1
20110110415 Cooper et al. May 2011 A1
20110153683 Hoskinson Jun 2011 A1
20110194418 Wolcott et al. Aug 2011 A1
20110194597 Wolcott et al. Aug 2011 A1
20110197071 Wolcott et al. Aug 2011 A1
20110243214 Wolcott et al. Oct 2011 A1
20120054312 Salinger Mar 2012 A1
20120084416 Thibeault et al. Apr 2012 A1
20120147751 Ulm Jun 2012 A1
Foreign Referenced Citations (21)
Number Date Country
0905998 Mar 1999 EP
1235402 Aug 2002 EP
1341335 Sep 2003 EP
1956782 Aug 2008 EP
55132161 Oct 1980 JP
04208707 Jul 1992 JP
6120896 Apr 1994 JP
6177840 Jun 1994 JP
09008738 Jan 1997 JP
9162816 Jun 1997 JP
10247893 Sep 1998 JP
11230857 Aug 1999 JP
2001044956 Feb 2001 JP
2003530761 Oct 2003 JP
2004172783 Jun 2004 JP
2004343678 Dec 2004 JP
0192901 Jun 2001 WO
0233974 Apr 2002 WO
2004062124 Jul 2004 WO
2007046876 Apr 2007 WO
2009146426 Dec 2009 WO
Non-Patent Literature Citations (37)
Entry
Motorola, “White Paper: Expanding Bandwidth Using Advanced Spectrum Management”, pp. 1-12, Sep. 25, 2003.
Cable Television Laboratories, Inc., “Pre-Equalization based pro-active network maintenance process model”, Invention Disclosure 60177, Jun. 2008.
Campos, L.A., et al., “Pre-equalization based Pro-active Network Maintenance Methodology”, Cable Television Laboratories, Inc., (presentation), 2008.
Shelke, Y.R., “Knowledge Based Topology Discovery and Geo-localization”, Thesis, Master of Science, Ohio State University, 2010.
Cable Television Laboratories, Inc., “A Simple Algorithm for Fault Localization Using Naming Convention and Micro-reflection Signature,” Invention Disclosure 60193, Jun. 2008.
Cable Television Laboratories, Inc., “Pre-Equalization Based Pro-active Network Maintenance Process Model for CMs Transmitting on Multiple Upstream Channels,” Invention Disclosure 60203, May 2009.
Y. Morishita, et al., “An LMS adaptive equalizer using threshold in impulse noise environments”, IEEE, ICT 2003 10th International Conference on Telecommunications, vol. 1, pp. 578-582, Feb. 2003.
PCT Search Report & Written Opinion, RE: Application #PCT/US2012/049685, Mar. 1, 2013.
Cable Television Laboratories, Inc., “Data-Over-Cable Service Interface Specifications DOCSIS 3.0: MAC and Upper Layer Protocols Interface,” CM-SP-MULPIv3.0-I16-110623, section 8, pp. 242-266, Jun. 2011.
Cable Television Laboratories, Inc., “Data-Over-Cable Service Interface Specifications DOCSIS® 3.0—Mac and Upper Layer Protocols Interface Specification,” CM-SP-MULPIv3.0-I17-111117, Nov. 2011.
Cable Television Laboratories, Inc., “DOCSIS® Best Practices and Guidelines: Proactive Network Maintenance Using Preequalization,” CM-GL-PNMP-V01-100415, Apr. 2010.
Cable Television Laboratories, Inc., “DOCSIS® Best Practices and Guidelines: Proactive Network Maintenance Using Pre-equalization,” CM-GL-PNMP-V02-110623, Jun. 2011.
Cable Television Laboratories, Inc., Data-Over-Cable Service Interface Specifications—DOCSIS 2.0: Radio Frequency Interface Specification, CM-SP-RFIv2.0-I06-040804, Aug. 2004.
R.L. Howald, et al., “Customized Broadband—Analysis Techniques for Blended Multiplexes,” NCTA Technical Papers, 2002.
R. Howald, “Access Networks Solutions: Introduction to S-CDMA,” Presentation to Society of Cable Telecommunications Engineers (SCTE) South Florida Chapter, 2009.
R. Howald, “Upstream Snapshots & Indicators (2009),” Regional Samples, Presentation to Society of Cable Telecommunications Engineers (SCTE) South Florida Chapter, Jan. 2010.
R.L. Howald, et al., “Characterizing and Aligning the Hfc Return Path for Successful DOCSIS 3.0 Rollouts”, SCTE Cable-Tec Expo, Oct. 2009.
R. Howald, et al., “DOCSIS 3.0 Upstream: Readiness & Qualification,” SCTE Cable-Tec Expo, Oct. 2009.
R. Howald, et al., “The Grown-Up Potential of a Teenage PHY”, NCTA Convention and Exposition, May 2012.
R. Howald, “DOCSIS 3.0 Upstream: Technology, RF Variables & Case Studies,” Access Networks Solutions, 2009, presentation to Society of Cable Telecommunications Engineers (SCTE) South Florida Chapter, 23 pages, Jan. 2010.
R. Hranac, “Linear Distortions, Part 1,” Communication Technology, Jul. 2005.
X. Liu, et al., “Variable Bit Rate Video Services in DOCSIS 3.0 Networks,” NCTA Technical Papers, 2008.
H. Newton, Newton's Telecom Dictionary, Flatiron Publishing, 9th ed., pp. 216 and 1023 (definitions of “carrier to noise ratio” and “signal to noise ratio”), Sep. 1995.
M. Patrick, et al., “Delivering Economical IP Video over DOCSIS by Bypassing the M-CMTS with DIBA,” SCTA 2007 Emerging Technologies, NCTA Technical Papers, 2007.
A. Popper, et al, “An Advanced Receiver with Interference Cancellation for Broadband Cable Networks,” International Zurich Seminar on Broadband Communications Access 2002, pp. 23-1 to 23-6, IEEE, 2002.
A. Popper, et al., “Ingress Noise Cancellation for the Upstream Channel in Broadband Cable Access Systems,” International Conference on Communications 2002, vol. 3, pp. 1808-1812, IEEE, 2002.
S.U.H. Qureshi, “Adaptive Equalization,” Proceedings of the IEEE, vol. 73, No. 9, pp. 1349-1387, Sep. 1985.
S. Ramakrishnan, “Scaling the DOCSIS Network for IPTV,” SCTE Conference on Emerging Technologies, NCTA Cable Show, Apr. 2009.
R. Thompson, et al., “256-QAM for Upstream HFC,” NCTA 2010 Spring Technical Forum Proceedings, pp. 142-152, May 2010.
R. Thompson, et al., “256-QAM for Upstream HFC Part Two”, SCTE Cable-Tec Expo 2011, Technical Paper, Nov. 2011.
R. Thompson, et al., “Multiple Access Made Easy,” SCTE Cable-Tec Expo 2011, Technical Paper, Nov. 2011.
R. Thompson, et al., “Optimizing Upstream Throughput Using Equalization Coefficient Analysis”, National Cable & Telecommunications Association (NCTA) Technical Papers, Apr. 2009.
R. Thompson, et al., “Practical Considerations for Migrating the Network Toward All-Digital”, Society of Cable Telecommunications Engineers (SCTE) Cable-Tec Expo, Oct. 2009.
R. Thompson, et al., “64-QAM, 6.4MHz Upstream Deployment Challenges,” SCTE Canadian Summit, Toronto, Canada, Technical Paper, Mar. 2011.
B. Volpe, et al., “Cable-Tec Expo 2011: Advanced Troubleshooting in a DOCSIS© 3.0 Plant,” Nov. 2011.
L. Wolcott, “Modem Signal Usage and Fault Isolation,” U.S. Appl. No. 61/301,835, filed Feb. 5, 2010.
F. Zhao, et al., “Techniques for minimizing error propagation in decision feedback detectors for recording channels,” IEEE Transactions on Magnetics, vol. 37, No. 1, pp. 592-602, Jan. 2001.
Related Publications (1)
Number Date Country
20110069745 A1 Mar 2011 US