Method and device for classification of network connections

FIELD: communications engineering, possible use for classification of connections.

SUBSTANCE: in method and device by means of computing block one or several distance coefficients are determined, while distance coefficients show efficient length of network connection depending on distance by air. On basis of known data about network connections, distribution coefficient of weak portions is determined, showing mutual relation to each other of weaker portions of network connection. Data transfer resource is determined to determine maximal for data transfer capacity for different types of modems. On basis of efficient length of network connection, weaker portions distribution coefficient and data transfer resources by means of computing block classification is performed (of subject network connection in accordance to its maximal data transfer capacity).

EFFECT: possible quick and flexible determining of service quality parameters.

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The present invention relates to a method and system for classifying network connections, and in the specified method and system of geographic coordinates at the beginning and end of the classified network connection between the transmitter and the receiver are known. In particular, the method relates to networks that use cable connections with copper conductors.

Traditional telephone services, such as denoted by the term POTS (plain telephone network), connect the traditional way accommodations and small companies with distribution station provider's telephone network via copper wires that suites each other and are called twisted pair. They were originally designed to transmit analog signals, in particular, tone and voice transmission. However, these requirements later with the advent of Internet technology and related data flows have changed and continue to change rapidly at the present time due to the need to provide opportunities to work in real time and multimedia applications both at home and at work.

Data networks, such as intranets and the Internet, are based largely on the so-called shared communication media, for example, on the technology counter is oriented local area network (LAN) or network coverage (WAN), as for broadband highways network between switches and gateways, and local network connections with bandwidths of less width. Widespread use of package management systems, such as bridges (device pairing local networks or routers, to ensure the connection of local networks to the Internet. The Internet router must be able to forward packets based on various protocols such as IP (Internet Protocol), IPX (internetwork packet exchange), DECNET (Protocol network architecture company DEC), ApplTALK (the network stack from Apple), OSI (open interaction systems), SNA (system network architecture IBM), etc. the Integration of such networks in order to route packets on a global scale is a problem for service providers (ISPs), and for manufacturers the necessary hardware.

The most common systems local area networks (LAN) work relatively well when the data rates of the order of 100 Mbit/s With transfer rates above 100 Mbps in most modern network resources network administrators, such as switches packets is not enough to control the distribution of bandwidth and user access. Of course, the usefulness of packet-oriented networks for transmission of the digital information, especially when a short pulse transmission, has long been recognized. Such networks usually have a structure "from point to point" (point-to-point structure of compounds), and the package is sent from a single sender to a single recipient, with each package includes at least a destination address (destination address). A typical example of this is known IP header of an IP data packet. The network responds to the data packet that sends the packet to the address of the corresponding header. Packet-oriented network can also serve to transmit the data types that require a steady stream of data, such as tone and audioproducer with high quality or video. Commercial use of networks makes it especially desirable for packet-oriented data transmission at the same time was possible and to many destinations. An example of this is the so-called batch transmission for transmitting video and audio data. Thus can be implemented with pay television, the pay broadcast transmission of video data over the network.

However, in next generation applications such as real-time applications and multimedia applications with more demanding in bandwidth, which should be guaranteed arowana in each moment of time, packet-oriented network Balk at the restrictions. So the next generation networks must be able to dynamically change the configuration of the networks in order to constantly guarantee the user a predefined bandwidth for the required or agreed quality parameters (QoS - quality of service). Such parameters include, for example, ensuring access, the access performance, tolerance for error, the reliability of data transmission, etc., among all possible target systems. New technologies, such as asynchronous transfer mode (ATM), should contribute to long-term development of networks to create the necessary preconditions for private intranets, and web open access Internet. These technologies promise more cost-effective and scalable solution for such guaranteed due to the QoS parameters of high-quality connections.

Change future systems will affect, in particular, the data flow. The flow data is currently based on the model of server-client, i.e. data from multiple clients are transferred to one or more or from one or more network servers. Customers usually do not create a direct data connection, and communicate with each other through network servers. This type connected what I was going to have its value in the future. Despite this, we should expect that the amount of data transmitted between peers, in the future will be greatly enhanced. Since the ultimate goal networks to meet the requirements, will be really a decentralized structure, in which all systems will have the ability to act as a server and as a client, the data flow connections between peers will increase. Thus, the network should be to create more direct connections to different peers, and, for example, desktop computers will direct connection through the backbone network of the Internet.

Thus, it is clear that for future applications, it is increasingly important to be able to guarantee the user the predefined QoS parameters and large values of the bandwidth.

Data to the end user, in particular, uses the traditional telephone network (PTSN) and/or mobile terrestrial network sharing (PLMN), which were originally developed for pure tones, and not to transfer such amounts of digital data. When determining the QoS parameters that the provider or the telephone service provider can guarantee the user, a crucial role is played by the so-called "Poslednyaya mile. This term is defined distance between the last distribution station telephone network of General use and the end user. That last mile in some cases formed high-performance bre-optic cables, but more often is based on the generic cables with copper conductors as, for example, a cable with a diameter lived 0.4 or 0.6 mm in addition, the cables are not everywhere is laid under the ground in a protected conduit, and there are lots of them laying above the ground on telephone poles, etc. the Result is more noise.

An additional problem with the definition of the maximum QoS parameter is the so-called problems of crosstalk. This problem occurs when the modulation signal on the plot, for example, from the end user prior to distribution station provider of telephone services and back. For the modulation of digital signals in the prior art, for example, xDSL (digital subscriber line), such as ADSL (asymmetric digital subscriber line), SDSL (symmetric digital subscriber line), HDSL (high speed digital subscriber line) or VDSL (ultra high performance digital subscriber line). Mentioned cross-interference is a physical phenomenon that occurs when the modulation data, re anaemic copper cable. Located close veins within a single copper cable are due to the electromagnetic interaction of the paired components of the signals, which are produced by the modem. This leads to the fact that the xDSL modems, transfer to adjacent cable conductors, create mutual interference. There are cross-crosstalk near end (NEXT), which refers to the unintentional input signals from the transmitter at one end to the signal receiver on the same end, and cross the far end crosstalk (FEXT), which refers to the unintentional input signals during transmission to the receiver at the other end, and the signals in the transmission signals are adjacent copper pairs and receiver appear as noise.

Although there are currently many studies xDSL crosstalk, as, for example, "Spectral management on metallic access networks; Part 1: Definitions and signal library", ETSI, TR 101 830, September 2000, due to the complexity of the phenomenon of crosstalk and other noise parameters at present, there is little practical and technically simple to use and cost-effective tools for the definition of QoS parameters for a particular end user in the network. In the prior art remote metering systems offered by different companies, for example, Acterna (WG SLK-11/12/22, Eningen U.A., Germany), Trend Communications (LT2000 Line Tester, www.trendcoms.com, Buckinghamshire, UK) and so the maximum data transfer rate on the last mile are determined through direct measurements via remote sensing: digital signal processor is installed on each local distribution station provider telephone communication network (for example, in Switzerland a few thousand). Through a digital signal processor is the so-called "asymmetric dimension, as the user on the other side of the last mile is not required to install any devices. But fundamentally also possible measurements on the principle of "symmetric measurement. But it requires the installation of measuring devices on both ends of the line. In published international application WO 01/41324 A1 (Qwest Communications International Inc.) the described method of classifying network connections. This is determined by the geographical length of individual lines, for example, by measuring the section of the route, and is the classification by comparing with the known dimensions of network connections.

The disadvantages of this prior art include, including high costs, due to the necessary installation of systems for remote measurement in each local distribution station, inaccurately known uncertainty or an unknown error if var is of, since the measurements are performed only on one side (single-ended measurement), and to determine the error would be required to implement a bilateral dimension. Bilateral dimension would be impractical because of the labor, time and cost. In addition, in the prior art is not known algorithms with hardware or software implementation to calculate or predict the maximum possible bit rate of the network connection. Installation of systems for remote measurement on a smaller number of Central distribution stations instead of the local target distribution stations shows that the dimensions peculiar to such a high degree of uncertainty that they are not suitable to determine the maximum possible data rate for a particular line to a target user.

The objective of the invention to provide a novel method and device for classifying network connections that do not have the above disadvantages. In particular, there should be created a quick and flexible way to define the parameters of quality of service (QoS) and specifically guaranteed maximum data rate for a specific user, without requiring disproportionate technical, human and financial cost. This must be provided in the case, to the Yes network includes only inaccurately known complex structures of compounds as, for example, the last mile.

In accordance with the invention this problem is solved in particular due to the characteristics of the independent claims. Preferred embodiments of result from the dependent claims and the description.

In particular, the above results are achieved in the invention by the fact that for classifying network connections, and the geographic coordinates of the transmitter and receiver are classified network connection is known, on the basis of known data network connection by means of the computing unit determines one or more coefficients of the distance and the received data associated with a defined probability, are transmitted to the data carrier of the computing unit, and the ratios of the distances indicate the effective length of a network connection, depending on the distance through the air, and determine the probability of whether a length of a network connection to a greater or lesser than its effective network length is determined by the reliability coefficient, on the basis of one or more ratios of distances, reliability coefficient and the geographic coordinates of the transmitter and receiver are classified network connection by using the computing unit determines the effective length of setevogo the connection and transmitted to the data carrier of the computing unit in accordance with the classified network connection, on the basis of known data network connection is defined by at least one distribution factor impairments and transmitted to the data carrier of the computing unit, with at least one distribution factor impairments indicates the ratio to each other impairments of various parts of the network connection, determine the resources necessary data to determine the maximum throughput of data transmission for various types of modems and stored on the storage medium of the computing unit in accordance with the physical length and thickness of cable network connections, and through the device power measurement measured energy spectra for the types of modems, by the computing unit on the basis of the energy spectra determined effective signal levels and the corresponding noise levels and using the Gaussian module conversion based on the signal levels and noise level for different modulation data and/or modulating codes are defined resources transfer to a pre-defined bit rate, and on the basis of the effective length of the network connection, the distribution coefficient of impairments and inventory resources data through computational unit is the classification class is peziraemje network connection in accordance with its maximum throughput of data. The advantage of the invention, including, is that the method and system for the first time provide a simple and rapid identification of reserves data without requiring large technical, labor and time costs. In particular, it is possible to adjust the uncertainty due to the mentioned correction without requiring, as in the known systems, remote sensing for the measurement of reserves data and/or bit rate, adjustments in each local distribution stations are different, not exactly known uncertainties or unknown error, which is due to the one-way measurements are difficult to assess, so as to determine the error would be required bilateral dimension.

In one embodiment, as the coefficients of the distance using the computing unit determines the ratio of the slope (slope coefficient) and the abscissa, when it is determined a linear relationship between the distance through the air and the effective length of the network connection. This option has run, including the advantage that it is sufficient for most dependency network structures and can give results within the required accuracy. For the specialist this is more than a surprise, as it was not expected that for such a complex dependent the child within the desired accuracy will be sufficient linear function. In particular, a linear relationship is easier and faster to identify and treat than non-linear.

In another embodiment, the computing unit determines the coefficients of the distance as parameters of a polynomial of at least the 2nd degree. This option is run, among other things, has the advantage that it provides any accuracy depending on the procedure used for the polynomial and the desired maximum deviation for the correlation between the distance in the air and the effective length of the network connection. Unexpected however was the fact that essentially does not require polynomials of very high order to satisfy the requirements of this method.

In another embodiment, the via reliability coefficient selected probability in the range from 0.85 to 0.95. The advantage of this variant is that the tolerance for error and the maximum deviation is limited by the precision required for this method and device.

In one embodiment of the reliability coefficient has a value in the range from 700 to 800. The unit of measurement for this option is the meter. The advantages of this option are the same as for the previous scenarios.

In yet another embodiment, the means of distribution coefficient of the impairments defined linear dependence of impairments on the relatively each other. This option has the advantage that it is sufficient for most dependency network structures and can provide results within the required accuracy. For the specialist this is more than a surprise, as it was not expected that for such complex dependencies within the desired accuracy will be sufficient linear function. In particular, a linear relationship is easier and faster to identify and treat than non-linear. This implementation is particularly suitable for networks with compounds composed of two different cables with different thicknesses lived, for example, cables with a diameter lived 0.4 mm and 0.6 mm

In another embodiment, the computing unit determines a corrected inventory resources data transmission through at least one correction factor based on the stored reserves data and stores them in accordance with the physical lengths and thicknesses of the wires of the cables of the network connection, the data medium of the computing unit, and a correction factor includes the average deviation of the saved resources data regarding the most effective resources data. This alternative implementation has the advantage, among other things, that can take into account factors that m is avleat additional deviation of the calculated reserves data regarding the most effective resources data. These include, for example, deviations due to quality or poor execution of the modem manufacturer or additional internal noise due to noise sampling or poor mutual agreement of the correction block.

In yet another embodiment, the noise levels are determined by the computing unit based at least on the parameters of the crosstalk and the number of interference sources on the basis of the energy spectra.

In another embodiment, the at least one correction factor plays a nonlinear relationship with respect to the physical lengths and/or thicknesses of the wires of the cables, that is, the adjustment factor may be a nonlinear function, for example, the function of the polynomial degree greater than 1. The advantage of this variant execution is the fact that thereby has an opportunity to address and correct more complex dependencies than the described linear correction coefficients.

In one embodiment, the energy spectrum is measured depending on the transmission frequency for the types of modems, ADSL and/or SDSL, and/or HDSL, and/or VDSL. Possible types of SDSL modems may include, at least, the type of modem G.991.2, and/or types of ADSL modems may include, at least, the type of modem G.992.2. Portstatus Gaussian transform can be defined resources data, at least for modulation data type 2B1Q (2 binary, 1 Quaternary), and/or CAP (amplitude/phase modulation without carrier), and/or DMT (digital multitenancy), and/or PAM (pulse amplitude modulation). Through module Gaussian transform can be defined resources data, at least for coding using lattice modulation code. This run has, among other things, the advantage consisting in the fact that the types of xDSL modems, when the above-mentioned modulation and data encoding using the modulation trellis code uses standard technologies, which are easily available in the market, and the use of which is widespread in Europe and in the USA.

In particular, the above objectives the present invention are achieved by the fact that for classifying network connections are known geographic coordinates of the transmitter and receiver are classified network connection, based on known data about the network connections through the computing unit determines one or more coefficients of the distance, and the received data is associated with a defined probability, are transferred to the data carrier of the computing unit, and the ratios of the distances indicate the effective length is a network connection, depending on the distance through the air, and determine the probability of whether a length of a network connection to a greater or lesser than its effective network length is determined by the reliability coefficient, based on the ratios of the distances of the safety factor and the geographic coordinates of the transmitter and receiver are classified network connection by using the computing unit determines the effective length of the network connection and transferred to the data carrier of the computing unit in accordance with the classified network connection, based on known data about the network connections is determined, at least one distribution factor impairments and transmitted to the data carrier of the computing unit, with at least one distribution factor impairments indicates the ratio to each other impairments of various parts of the network connection, determined bit rate to determine the maximum throughput of data transmission for various types of modems and stored on the storage medium of the computing unit in accordance with the physical length and thickness of cable network connections, and through the device power measurement measured energy spectra for the types of modems, by the computing unit on the basis of energy the definition of the spectra are determined by the effective signal levels and the corresponding noise levels, and with the help of the Gaussian transform based on the signal levels and noise level for different modulation data and/or modulating codes are determined by the bit rate for the predefined resource inventory transfer, and on the basis of the effective length of the network connection, the distribution coefficient of impairments and inventory resources data through computational unit is the classification of the classified network connection in accordance with its maximum throughput of data. The advantage of this option, perform, including, is that the method and system for the first time provide a simple and fast determination of the bit rate, without substantial technical, labor and time costs. In particular, it is possible to adjust the uncertainty due to the mentioned correction without requiring, as in the known systems, remote sensing for the measurement of reserves data and/or bit rate, adjustments in each local distribution stations are different, not exactly known uncertainties or unknown error, which is due to the one-way measurements are difficult to assess, so as to determine the error would be required bilateral dimension.

In one embodiment, the Khujand the exercise as ratios of distance using the computing unit determines the ratio of the slope (slope coefficient) and the abscissa, when it is determined a linear relationship between the distance through the air and the effective length of the network connection. This option has run, including the advantage that it is sufficient for most dependency network structures and can give results within the required accuracy. For the specialist this is more than a surprise, as it was not expected that for such complex dependencies within the desired accuracy will be sufficient linear function. In particular, a linear relationship is easier and faster to identify and treat than non-linear.

In another embodiment, the computing unit determines the coefficients of the distance as parameters of a polynomial of at least the 2nd degree. This option is run, among other things, has the advantage that it provides any accuracy depending on the procedure used for the polynomial and the desired maximum deviation for the correlation between the distance in the air and the effective length of the network connection. Unexpected however was the fact that essentially does not require polynomials of very high order to satisfy the requirements of this method.

In another embodiment, the via reliability coefficient selected probability in the range from 0.85 to 0.95. The advantage of this option is the Ohm, the tolerance for error and the maximum deviation is limited by the precision required for this method and device.

In one embodiment of the reliability coefficient has a value in the range from 700 to 800. The unit of measurement for this option is the meter. The advantages of this option are the same as for the previous scenarios.

In yet another embodiment, the means of distribution coefficient of the impairments defined linear dependence impairments relative to each other. This option has the advantage that it is sufficient for most dependency network structures and can provide results within the required accuracy. For the specialist this is more than a surprise, as it was not expected that for such complex dependencies within the desired accuracy will be sufficient linear function. In particular, a linear relationship is easier and faster to identify and treat than non-linear. This implementation is particularly suitable for networks with compounds composed of two different cables with different thicknesses lived, for example, cables with a diameter lived 0.4 mm and 0.6 mm

In another embodiment, the computing unit determines a corrected bit rate by at least one corrective coeff what the patient should therefore be based on the saved bit rate and saves them, associated with the respective physical lengths and thicknesses of the wires of the cables of the network connection, the data medium of the computing unit, and a correction factor includes the average deviation of the stored bit rate with respect to the effective bit rate. This alternative implementation has the advantage, among other things, that can take into account factors that cause additional deviation of the calculated bit rate with respect to the effective bit rate. These include, for example, deviations due to quality or poor execution of the modem manufacturer or additional internal noise due to the noise sample rate (analog-to-digital conversion) or poor mutual agreement of the correction block.

In one embodiment, the energy spectrum is measured depending on the transmission frequency for the types of modems, ADSL and/or SDSL, and/or HDSL, and/or VDSL. Possible types of SDSL modems may include, at least, the type of modem G.991.2, and/or types of ADSL modems may include, at least, the type of modem G.992.2. Through module Gaussian transform can be defined resources data, at least for modulation data type is 2B1Q, and/or CAP, and/or DMT, and/or PAM. Through module Gaussian transform can be defined resources data, at least for coding using lattice modulation code. This run has, among other things, the advantage consisting in the fact that the types of xDSL modems, when the above-mentioned modulation and data encoding using the modulation trellis code uses standard technologies, which are easily available in the market, and the use of which is widespread in Europe and in the USA.

In another embodiment, the at least one correction factor plays a nonlinear relationship with respect to the physical lengths and/or thicknesses of the wires of the cables, that is, the adjustment factor may be a nonlinear function, for example, the function of the polynomial degree greater than 1. The advantage of this variant execution is the fact that thereby has an opportunity to address and correct more complex dependencies than the described linear correction coefficients.

In another embodiment, the through module Gaussian transformations define the bit rate for inventory resources data between 3 and 9 dB. This option is run, among other things, has the advantage, with toadie is the range between 3 and 9 dB provides reception with QoS parameters that satisfy the majority of requirements. In particular, the specified range of resources transfer data between 3 and 9 dB ensures optimization of bit rate in relation to other QoS parameters.

In another embodiment, the through module Gaussian transformations define the bit rate for the resource inventory data 6 dB. This option is run, among other things, has the same advantages as in the previous described embodiment. In particular, the supply of resources data 6 dB ensures optimization of bit rate in relation to other QoS parameters.

In addition, it should be noted that the claimed invention, along with a way consistent with the invention also relates to a device for implementing this method.

The following examples describe embodiments of the claimed invention. The examples illustrated by the drawings, which represent the following:

Fig. 1 is a block diagram showing the architecture scenarios corresponding to the invention of a system for determining the resources or data transmission speeds of bits for a network connection 12 with a certain physical length of 13 between the transmitter 10 and receiver 11.

Fig. 2 is a schematic representation of the crosstalk cross-interference of the near end (NEXT) 51, which refers to the unintentional input 50 of the transmitter 10 at one end in the signals 50 in the receiver 11 at the same end, and cross the far end crosstalk (FEXT) 52, which refers to the unintentional input signal 50 when transmitting to the receiver 11 at the other end, and the signal 50 when the transmission signals are 50 adjacent copper pairs and receiver 11 are manifested as noise.

Fig. 3 - schematic representation of the transmission path of the network connection, depending on the transmission speed (bit rate) for ADSL modems, as it can be obtained using the appropriate invention system. The reference position 60 and 61 represent different conditions of noise.

Fig. 4 - schematic representation of the so-called "last mile" telephone network (PSTN), existing in a typical case, between an end user's home network, which should be available through the telephone network of General use.

Fig. 5 - diagram of the sampling data for the existing network, and the data sample includes 200000 measured network last mile connections to the telephone network.

Fig. 6 is a chart of the average deviation of the effective length of the Dethe network connection from the calculated lengths of the D aa network connection. The X-axis indicates the average deviation ΔD in meters and the Y - axis value of the used data sample, i.e. the number N of known network connections.

Fig. 7 is a schematic representation of the relationship of R1copper cable t1diameter lived 0.4 mm copper cable t2diameter lived 0.6 mm on the last mile of telephone network of General use. The X-axis indicates the effective length of the Denetwork connection, i.e. its physical length, and the Y - axis the share of Rtthe appropriate type of cable in percent.

Fig. 8 is a diagram of example definition 2011/2012 one or more coefficients of the distance, as well as the reliability coefficient. By analogy with Fig. 5, the X-axis indicates the effective length of the Denetwork connection in meters and the Y - axis distance by air network connections Dandalso in meters.

Fig. 9 is a sequence diagram of operations of the claimed method. Four reference positions are related respectively to figs. 9.

In Fig. 1 presents the architecture that can be used to carry out the invention. In this example, the run method and device for classifying network connections geographic coordinates of the transmitter 10 and receiver 11 are classified network connection 12 is known (block 1000 of Fig. 9). Coordinates can, for example, indicated Iwate with sufficient accuracy the degrees of longitude and latitude, but you can use other coordinates or location data to indicate the relative geographical position of the transmitter 10 and receiver 11. For example, to be able to determine, does it work for a certain connection network connection, for example, the xDSL connection, you need to know the effective length of the cable with accuracy to a certain deviation. In practice, at an affordable cost (financial, time, human and material) can be determined only the distance through the air. Using the coordinate data or location data for the relative geographical location of the transmitter 10 and receiver 11 via the computing unit 30 determines the distance by air between the transmitter 10 and receiver 11, which may, for example, be stored on the storage medium of the computing unit 30. Computing unit 30 determines (3010) based on the sample data (4010) from known data (5000) about network connections, one or more of the coefficients of distance (2011). The execution process corresponding to the invention of the method shown in Fig. 9, which are driven by a four-digit reference position. Data 5000 can represent, for example, experimentally certain information known or otherwise data related to the network is soedinenijam, which include distance through the air and the effective physical length of these network connections. The coefficients 2011 distances are determined thereby, depending on the probability, and the probability can be determined, and describe effective length Denetwork connection depending on distance on air Da. Then the coefficients 2011 distances associated with a defined probability, can be transferred to the data carrier of the computing unit 30. As coefficients 2011 distance using the computing unit 30 can determine the coefficient of inclination (angular coefficient) and the abscissa, when it is determined a linear relationship between the distance by air Daand an effective length of Dea network connection. But you can also use the computing unit 30 to determine the coefficients 2011 distance as parameters of a polynomial of the 2nd or higher degree. Define the likelihood, which can be installed by a factor 2012 reliability indicates whether the calculated length of the Denetwork connection lesser or greater than the effective length Dea network connection. The probability can be selected by means of the safety factor in the range from 0.85 to 0.95. The reliability coefficient in the above-mentioned probability value in case ledney miles (described below) has, for example, a value in the range from 700 to 800, and the unit of measure is meters.

In Fig. 5 shows an example of sample data to an existing network, and the data sample includes 200000 measured network last mile connections to the telephone network. In this network there are connections, mainly from traditional telephone connections with copper cables with diameters lived 0.4 mm and 0.6 mm, the Example clearly illustrates the correlation, although due to the complexity of some network structures specialists would expect a more complex dependence. The X-axis indicates the effective length of the Denetwork connection in meters and the Y - axis distance by air network connections Dandalso in meters.

In Fig. 8 presents an example of determining one or more coefficients 2011 distance and factor 2012 reliability. By analogy with Fig. 5, the X-axis indicates the effective length of the Denetwork connection in meters and the Y - axis distance by air network connections Dandalso in meters. Data points can be selected (4010) from the sample data with the known data about 5000 network connections. Determination of the coefficients of 2011 distance and factor 2012 reliability can occur, for example, via the module fit. In this example we have defined a linear relationship between the distance by air Dandand eff the active length of D enetwork connections, and as coefficients 2011 distance using the computing unit 30 is determined by the angular coefficient a and the abscissa b. The abscissa b is determined for different locations of the connection (for example, city, suburb, rural, mountainous terrain), as well as for various areas of connection (for example, main valve, junction box, transition point, and so on). Effective distance is obtained then as follows: De=y=aDa+b. For y about 50% of the calculated network connection is shorter than the effective network connection, i.e. with probability 0.5. The coefficient of the 2012 reliability S were also chosen as linear, i.e. as a constant. Thereby it turns out De=ys=aDa+b+S. S can determine the probability of whether the length of the network connection is shorter or longer than its effective network length De. In the shown example, when ysaccording Fig. 8 the probability by a factor of 2012's reliability was set at 0.9. In this example, execution of the angular coefficient a=De/Dafor the last mile of the traditional telephone network were found to have the following values: urban-as=1,27, for a suburb of av=1,28, for rural conditions al=1.30 and for mountainous the terrain a g=130. For mixed data block (city, suburb, rural, mountainous area) is determined by the value of aall=1,30. Similarly obtained values for bs=200, bv=355, bl=372, bg=391 & ball=328, and b is specified in meters. Standard deviation σ for this example, perform the following: σs=333, σv=569, σl=682, σg=527 σall=598. Standard deviation σ determines the dispersion of the difference between the effective length of the network connection and the computed length of the network rejection. The average deviation in meters effective length Dethe network connection from the calculated length Danetwork deviations approximately regardless of the length of the network connection shown in Fig. 6 for this example run. The X-axis indicates the average deviation ΔD in meters and the Y - axis value of the used data sample, i.e. the number N of known network connections. To obtain a probability of 0.9, it is provided in this example, execution of the safety factor S, for example, Ss=360, Sv=640, Sl=850, Sg=670 and Sall=730. To obtain a probability of 0.95, it is provided in this example, execution of the safety factor S, respectively, Ss=490, Sv=1100, Sl=1330, Sg=930 and Sall=1210.

the and the one or more coefficients of 2011 and distance coefficients 2012 reliability using the geographic coordinates of the transmitter 10 and receiver 11 are classified network connection 12 computing unit 30 determines (1010) effective length of the network connection, that is, its physical length, and transfers it to a storage medium of the computing unit 30 in accordance with the classified network connection 12. The physical length refers to the effective length of the cable, and not, for example, the length of the air between the transmitter 10 and receiver 11. Network connection 12 may consist of an analog transmission medium, for example, cable with copper conductors. In this exemplary embodiment, for example, used copper cables with a diameter lived 0.4 or 0.6 mm, as they are typically used for last mile telephone network (PSTN). The last mile is schematically represented in Fig. 4. The reference position 70 denotes a router, which is connected, for example via 10BT Ethernet 77 and telephone network (PSTN) 72 c server 71 modem terminal. The server 71 modem terminal may be a DSL access multiplexer (DSLAM). As mentioned, the reference position 72 denotes telephone network (PSTN)to which the server 71 modem terminal is connected, for example, fibre optic cable 78. In addition, the telephone network 79 General use and, accordingly, the server 71 modem terminal in a typical case, through the cable 79 with copper conductors via the telephone box 73 is connected to the modem 74 personal computer is the software (PC) 75. The reference position 79 this refers to those so-called "last mile" from the distribution station provider's telephone network to the end user. The end user 76 thus, you can use your PC to directly access the router 70, through the described connections. The most common telephone wire can be, for example, of a pair of copper wires 2-2400. But can be used with other analog transmission medium, in particular copper cable, for example, with other diameters lived. It is necessary to indicate that a network connection 12 can not only have respectively different diameters or thickness 114, 142, 143, 144, and that a separate network connection may consist of a combination of cables with different diameters or thicknesses lived, that is, that the network connection includes several separate cables with different thicknesses lived.

If the network consists of a combination of cables with different diameters or thicknesses lived, based on the sample data 4020 selected from known data about 5000 network connection is determined (3020)at least one coefficient 2020 distribution of impairments, which is transferred to the data carrier of the computing unit 30, and at least one coefficient 2020 distribution of impairments indicates zootoxin the e impairments of various parts of the network connection. The coefficient 2020 distribution of impairments can be defined as a linear factor. At least one coefficient 2020 distribution of impairments may optionally include a non-linear dependence. In this example, the network connections include copper cables with a diameter lived 0.4 or 0.6 mm, as they are typically used for the last mile. As they use only two types of cables, it is sufficient to define only one factor 2020 distribution of impairments. The connecting cables are in accordance with their different diameters, different electrical properties and different attenuation. Therefore, for this method it is important that at least a proportion of copper cable with diameter lived 0.4 mm and copper cable with diameter lived 0.6 mm for a specific network connection was known with the required accuracy. The telephone network of General use are usually designed so that the total impedance for direct current (DC) lies within certain limits. This property is used to determine when the user is picking up the phone to make the call. If the phone is used, then the user has lifted the handset, the phone changes its impedance, and this change is detected at the Central station. So usually DL the long lines are used more cable diameter lived 0.6mm (as the resistance Ω less), and for short distances apply more cable diameter lived to 0.4 mm, thereby the ratio of the thicknesses of the wires of the cable can be determined approximately in accordance with the logic of the phenomena. In particular, the computing unit 30 using the module fit on the basis of known data about 5000 network connections may determine (2020) function of the distribution coefficient impairments depending on the length of the connection. In this exemplary embodiment was used, a linear coefficient as a coefficient 2020 distribution of impairments, thus:

De≤10:

And Lfor 0.4indicates the percentage of cable with diameter lived 0.4 mm in km, and Lfor 0.6indicates the percentage of cable with diameter lived 0.6 mm in km as a function of De(De- the effective length of the network connection). Fig. 7 schematically represents the dependence of Rtwhere t1- the proportion of copper cable with diameter lived 0.4 mm, and t2- copper cable with diameter lived 0,6 mm X-Axis indicates the effective length of the Denetwork connection, that is, its physical length, and the Y - axis the share of Rtthe appropriate type of cable in percent. You can see that the proportion of copper cable with diameter lived 0.6 mm for distances over 10 km increases to 100%, i.e. the network connection is essentially the exclusively consists of a copper cable with a diameter lived 0,6 mm. On the basis functions for the distribution coefficient of impairments for classified network connection is determined (1020) the distribution coefficient impairments depending on the length of the connection 2020 and the effective length of the network connection and transferred to the data carrier of the computing unit 30 in accordance with the classified network connection 12.

The next step is to define (1030) resources 2030 data to determine the maximum throughput and data stored on the storage medium of the computing unit 30 according to different types of modems and the physical length of the cable 13 and the thickness of the cable 141, 142, 143, 144 network connection 12. This measured energy spectrum PSDModem(f) depending on the frequency f of the transmission for possible types of modems 101, 102, 103, 104 through the device 20 power measurement and is transferred to the data carrier of the computing unit 30. The energy spectrum is also indicated with the term "power spectral density" (PSD) and plays for a certain bandwidth continuous range of frequencies, i.e. full capacity in a given bandwidth, divided by a certain bandwidth. Divide by the width of the strip corresponds to the normalization. Thus, the power spectral density PSD is a function that freezes the soup from the frequency f, and is usually given in watts per Hertz. To measure the power through the device 20 power measurement in the receiver 11 can be used a simple analog-to-digital Converter, and the voltage applied to the resistance. For the modulation of digital signals in lines 12, for example, from the end user to the distribution station provider's telephone network and back can be applied to various types of modulation. In the prior art, for example, known techniques xDSL (digital subscriber line), the two main representatives of which are ADSL (asymmetric digital subscriber line) and SDSL (symmetric digital subscriber line). Other members of the xDSL technologies are HDSL (high speed digital subscriber line) or VDSL (ultra high performance digital subscriber line). XDSL technologies are highly developed schemes of modulation used to modulate the data transmitted in the transmission line on the copper wires or other analog media. The xDSL technology is sometimes referred to as last mile access technology, in particular, due to the fact that they usually are used to connect the last distribution station telephone network with the end user in the office or at home, and does not apply to connections between the individual distribution t the telephone network. XDSL is similar to the network (ISDN Digital network integrated services) in the sense that it can work on existing transmission lines on the copper wires, and they both require a relatively short distance to the next junction station provider's telephone network. XDSL provides, however, a higher data transfer speeds than ISDN. xDSL reaches speeds of up to 32 Mbps for speed downstream (transmission speed when receiving data, that is, when the modulation) and speeds from 32 kbps to 6 Mbps for speed upstream (the transfer rate during data transfer, that is, when demodulation), while ISDN supports data transfer rate per channel of 64 kbit/s ADSL recently become a very popular technology for data modulation in the transmission line on the copper wires. ADSL supports data transfer speeds from 0 to 9 Mbit/s for velocities in the downstream direction of the flow and from 0 to 800 kbit/s for velocities in the upward direction of flow. ADSL is called asymmetric DSL, as it supports various transmission speed in an upward and downward direction of flow. SDSL or symmetric DSL, called, in contrast, symmetric because it supports the same speed for upstream and downstream flows Yes the data. SDSL provides the ability to transmit data at speeds up to 2.3 Mbit/s ADSL transmits the digital pulses in the high frequency range of copper cable. Since these high frequency in normal transmission of tone signals in the audible range (e.g., voice) are not used, ADSL can act to transmit telephone calls over the same copper cable. The ADSL technology is most common in North America, while SDSL technology primarily developed in Europe. ADSL and SDSL require specially equipped for this modem. HDSL is a representative for symmetric DSL (SDSL). Standard for symmetric HDSL (SDSL) is currently the G.SHDSL, known as G.991.2 developed as an international standard by the Committee CCITT the International telecommunications Union (ITU). G.991.2 supports reception and transmission of symmetric data flow for a simple pair copper cables with transmission speeds from 192 kbps to 2,31 MB/s Standard G.991.2 was designed in such a way that it includes the features of ADSL and SDSL and supports standard protocols such as IP (Internet Protocol), in particular modern version of IPv4 and IPv6 or IPng (Working group on the development of the Internet IETF), and TCP/IP (transmission control Protocol), ATM (asynchronous transfer mode), T1, E1 and ISDN. As for ledney of xDSL technologies mentioned here VDSL technology (ultra high performance digital subscriber line). VDSL transmits data in the range 13-55 Mbps over short distances (usually in the range 300-1500 m) copper cable twisted pair. For VDSL true value lies in the fact that the shorter the distance, the higher the transmission rate. As the final section of the VDSL network used to connect the office or home user with neighboring optical network unit, called an optical network unit (ONU), which is typically associated with the main bre-optic network (backbone), for example, firms. VDSL provides user access to the network with the maximum bandwidth for normal telephone wires. The VDSL standard is not yet fully defined. So, there VDSL technologies that have the encoding scheme of the line based on the DMT (discrete multitoning signal), and DMT is a system with many bearing, which is very similar to ADSL technology. Other technologies have VDSL encoding line, based on quadrature amplitude modulation (QAM), which in contrast to DMT is more economical and requires less energy. For this example, perform the types of modems may include the types of modems (101, 102, 103, 104) ADSL and/or SDSL, and/or HDSL, and/or VDSL. In particular, the possible types SDSL modems (101, 102, 103, 104) may include at least one type of modem G.991.2, and/or types of ADSL fashion is s (101, 102, 103, 104) may include at least one type of modem G.992.2. However, it is clear that this list in no way should be considered as limiting the scope of protection of the invention, and in contrast, other types of modems.

Using the computing unit 30 is determined by the weakening of N for different physical lengths 13 and the thickness of the wires of the cables 141, 142, 143, 144, as, for example, 0.4 mm and 0.6 mm network connection 12, and the effective level of the signal S(f) in the receiver 11, based on the weakening of H(f) and the energy spectrum of PSD(f)associated with the respective physical lengths L13 and the thickness of the wires of the cables D 141, 142, 143, 144, stored in the first list on the media data computing unit 30. The weakening of H(f,L,D)as of the effective level of the signal S(f)is a function that depends on the frequency f. Sent from the transmitter 10, the signal corresponds to PSDModem(f), while in the receiver is made effective level of the signal S(f)=PSD(f)H2(f,L,D). The second list on the media data computing unit 30 is stored noise N(f), associated with the respective physical lengths 13 and the thickness of the wires of the cable 141, 142, 143, 144 network connection, and the noise N(f) 40 is determined by the computing unit 30 depending on at least the parameter crosstalk Xtalktype and the number And sources of interference on the basis of the energy spectra is RA PSD. That is:

The sum is taken over the index i for all palehovym modulation (SModem) depending on their parameter crosstalk Xtalktype that operate on parallel connections of this network connection. PSDSModem(i)represents the energy spectrum of the i-th modem. NHR is weakening, depending on crosstalk. As mentioned, the problems of crosstalk associated with a physical phenomenon that occurs when the modulation data transmitted over copper cable. Neighboring copper cable wires inside the copper cable are due to the electromagnetic interaction of the paired components of the signals, which are produced by the modems. This leads to the fact that xDSL modems that perform transmission by neighboring wires, create mutual interference. Cross-interference as a physical effect is negligible for ISDN (range of frequencies up to 120 kHz), but is significant, for example, ASDL (frequency range up to 1 MHz) and is a decisive factor for VDSL (range of frequencies up to 12 MHz). As described, used telephone lines consist of copper conductors number from 2 to 2400. So, for example, to be able to use four pairs, the data stream in the transmitter is divided into multiple parallel data streams, and the receiver is again restored, th is increases effective bandwidth 4 times. This would allow to transfer data at speeds up to 100 Mbit/S. Additionally, in the case of 4 pairs of copper wires of the same four pairs of wires are used for the same volume of data at a time to pass in the opposite direction. Bilateral data transmission on each of the copper wire pair doubles the data capacity that can be transmitted. In this case, the data rate increases eight times compared to conventional transmission, in which two pairs are used only for one direction. For data transmission, as described above, the crosstalk noise are strongly limiting factor. As types of crosstalk (Xtalktype) distinguish cross-crosstalk near end (NEXT) 51, which refers to the unintentional input 50 of the transmitter 10 at one end in the signals 50 in the receiver 10 at the same end, and cross the far end crosstalk (FEXT) 52, which refers to the unintentional input signal 50 when transmitting to the receiver 11 at the other end, and the signal 50 when the transmission signals are 50 adjacent copper pairs and receiver 11 are manifested as noise (see Fig. 1). Usually proceed from the fact that the NEXT obstacle 51 is the only source of interference near the end. Parameter Xtalktype, thus, depends on the location and flow (upward/NIS is odasi), that is, this dependence can be written as Xtalktype (stream, position). If you have more than two copper conductors, as it usually takes place (in a typical scenario, there are from 2 to 2400 lived), then the above pairwise link is no longer valid. For example, for the case when both used the four pairs of conductors, then, consequently, there are three unintentional sources of interference that its energy acting on the signal 50. For And in this case the relation is valid : A=3. The same is true for crosstalk type FEXT 52.

Computing unit 30 determines the reserves data by module 31 of the Gaussian transform based on the effective level of the signal S(f) from the first list and the corresponding level of the noise N(f) from the second list for different modulation data and/or modulating codes for a pre-defined bit rate and saves resources data associated with the respective physical lengths 13 and the thickness of the wires of the cable 141, 142, 143, 144 network connection 12, the data medium in the computing unit 30. On the basis of the effective levels of the signal S(f) from the first list and the corresponding level of the noise N(f) from the second list by using the computing unit 30 to determine the ratio of the signal S and noise N (SNR) in the following form:

This expression is true only for modulation type CAP, 2B1Q and FRAMES, but not applicable for modulation type DMT. Modulation type DMT is described below in more detail. T thus denotes the symbol interval or half the inverse of the magnitude of the Nyquist frequency. The Nyquist frequency is the maximum frequency which can be accurately taken sample. The Nyquist frequency is half the value of the sampling frequency, so as the unintended frequency is generated when the sampled signal, whose frequency is higher than half the value of the sampling frequency. The index n is the index of summation. In practice, it is usually enough, when n takes values from -1 to +1. If that's not enough, you can use the extra highs 0, ±1/T, ±2/T and so on until, until you reach the required accuracy. Resources data-dependent modulation data and/or modulating codes, as noted above. In this exemplary embodiment shows the dependence for 2B1Q modulation used for HDSL modems and modulation of ATS as an example for ADSL modulation type DMT, as well as for modulating codes using signals of trellis coding. However, it is clear that corresponding to the invention the method and system can also be applied to other modulation data and/or delirously codes such as PAM (pulse amplitude modulation), etc. As the modulation type 2B1Q, and modulation type of ATS are used for HDSL modems and are characterized by a predefined bit rate. Modulation type DMT is used for ADSL modems and has in contrast a variable bit rate. The modulation of the cap and DMT use the same fundamental technology modulation: quadrature amplitude modulation (QAM), although this technology is used in different ways. QAM provides the possibility that two digital carrier signal have the same bandwidth transmission. Thus there are two independent, so-called message signal to modulate two carrier signal having the same carrier frequency, but different amplitude and phase. Receivers of QAM signals can distinguish whether low or high number of amplitude and phase States, to overcome the effect of noise and interference, for example, in one pair of copper conductors. Modulation type 2B1Q also known as 4-level amplitude modulation (PAM). It uses two levels of voltage pulse signals, not one level, as, for example, in the case of modulation type (AMI coding with alternating polarity items). Since the applied positive and negative RA the differences in the levels get a 4-level signal. The bits are then estimated in pairs, a pair corresponds to a specific voltage level (hence the name 2-bit modulation). Due to this, you can halve the required transmission frequency to broadcast with the same bit rate as in the case of bipolar modulation type AMI. For HDSL modem that uses the modulation type 2B1Q or cap, there is the following dependence of resource inventory data from SNR:

where the parameter ξ can be determined depending on the frequency error (frequency error symbol) εs. For local area networks the Internet Protocol is usually sufficient frequency error εs=10-7that is every 107bit in the middle is transmitted distortion. Firms require in a typical case for their corporate networks εs=10-12. If the value of εsbecomes of the order of magnitude of the transmitted data packet (for example, 10-3), is, by contrast, would mean that each package in the middle must be transmitted twice, until it is received correctly. For modulation type 2B1Q for parameter εstrue, for example, the following:

for unencrypted signals

for signals trellis encoding

at the time for both modulation types RAA fair the following relations:

for unencrypted signals

for signals trellis encoding

Parameter Gcfor both types of encoding is the complementary Gaussian function:

M stands for the modulation type 2B1Q torque number, and M=4 for 2B1Q, while for the modulation type of the SAR parameter grouping equal MHM. T denotes, as above, the symbol interval or half the inverse of the magnitude of the Nyquist frequency. For ADSL modems using modulation types DMT addiction is different. As noted above, ADSL has a variable bit rate. This is also apparent in the parameter definition Mwith. In this case we have the following relation:

when it ξ(f) denotes the signal-to-noise S(f)/N(f). xrefdenotes a reference stock of resources, which in this example is run in a typical case was chosen equal to 6 dB, that is, xref=100,6. However, for xrefcan be selected and the other values as reference resources. Δf - all bandwidth or the frequency band used for transmission. The integration is performed on the frequency. D is the bit rate, for example, in bits per second (bps). Mr. correctitude the coefficient. In this example, the run D has a value of, for example, equal of 9.55. Integrating this example the frequency f. Similarly, it may, however, also be carried out by time or another physical magnitude, and the above expression should be consistent.

In the General case the above resources data do not coincide with the experiment. Therefore, the computing unit 30 determines effective resources data transmission through at least one correction factor based on the stored reserves resource data. The adjustment factor was selected for this example was run in such a way that ensures sufficient consistency between the obtained resources data and effective resources data. As of sufficient magnitude in this case was made, for example, ±3 dB, and can be used and other values. To get the maximum deviation ±3 dB, determined by two parameters. Mimptake into account good or poor implementation of the modem manufacturer. The parameter Mimpwas introduced on the basis of the fact that the same modems with similar hardware and the same modulation data and/or modulation codes, which, however, produced by different manufacturers, when converting an analog signal into a digital signal and back gave different results that influenced their maximum data transfer rate or the maximum range for a particular network connection. This should be adjusted in relation to inventory resources data. As a second option was introduced with Nint. Ninttakes into account the quantization noise in the modem (analog-to-digital conversion), and possible bad configuration error correction block in the transmission. If the transfer takes place between the transmitter 10 and receiver 11, the error correction block in the modem will negotiate speed data transfer with the terms of the network connection, for example, the weakening line, phase distortion, etc. through the test sequence, which is sent between the two leading information exchange modems in both directions. Poor alignment caused by the correction block, leads to distortion of the results and should be adjusted. For linear error correction block may be used, for example, the following expression:

where

When SNRLinearEqdenotes the ratio of signal/noise, Sethe signal received by the error correction block, Ne- noise and f is the frequency. For blockarray with adaptive decision feedback (DFE) may be used, for example, the following expression:

where

In this re-SNRThe DFEdenotes the ratio of signal/noise, Se- as above, the signal received by the error correction block, Ne- noise and f is the frequency. Computing unit 30 for determining SNRThe DFEcan be used, for example, the following approximation:

Thus, for effective inventory resources data we get: S(f)= PSDModem(f)H2(f,L,D)as before. Noises are adjusted as follows:

Correction can be implemented in the computing unit 30 by the hardware or software in a single module. It should be noted that using such a module based on the correction of Nintintroduces a variable noise factor, which, for example, can take into account the setting of the error correction block, etc. the solution is not known from the prior art and is owned by, among other things, substantial advantages of the invention. Effective resources data Meffaccounted for by the ratios of Meff=Mc-Mimpthat is taken into account in addition to Nintas referred to above. Valid values for Mcand Nintcan be obtained by the computing unit 30 is compared with the experimental data. In a typical case, the computing unit 30 should then have access to the data of different experiments, to be able to correctly identify the parameters within desired tolerances. By means of correction factors, which, therefore, include the average deviation of the saved resources data in relation to effective resources data, determined as described above, effective resources data and also in comparison with the respective physical lengths L (13) and the thickness D of the wires of the cables 141, 142, 143, 144 network connection are stored on the media data computing unit 30. It should be noted that correction factors are not necessarily linear coefficients, that is, it must be permanent, but with the same success can include corrective functions with nonlinear dependence. Thus you can, depending on the application, be considered more complex deviations of the experimental data. Through the saved array data resources data computing unit 30 determines on the basis of the stored effective resources data using known physical length 13 network connection 12 between the transmitter 10 and receiver 11 reserves data the La specific network connection 12. The reserves data are indicated, as repeatedly mentioned above, in decibels. For values of >0, the modem operates in a generic manner, while for values of <0, it does not work. In order to guarantee reliable operation, it may be useful, as the lower bound to choose, for example, 6 dB. However, in General suitable for use and other values inventory resources data for the lower bound, for example, values in the range from 3 dB to 9 dB. Due to the similar configuration for ADSL modems also possible, as shown in the above data, instead of data arrays with the reserves data respectively to define arrays of data with the bit rate for different network connections, for example, to inventory resources data 6 dB. Thereby to define arrays of data with a bit rate of 6 dB = Meff. For HDSL modems that don't make sense in this respect, as in the case of HDSL is used to encode, for example, 2B1Q or cap c constant data rate, in this case 2,048 Mbit/S. the Reason for this difference in relation to the ADSL modems is that HDSL system was designed only to connect with a higher bit rate, and interest only reliability before the Chi ratio (SNR). In Fig. 3 presents a plot of transmission network connection, depending on the bit rate for ADSL modems. Reference positions 60 and 61 are indicated by different noise conditions. Bit rate, as described above, are presented on the basis of the stored data arrays or lists 2030.

On the basis of the stored data arrays or lists 2030 inventory resources data/bit rate are determined (1030) the reserves data/bit rate for classified network connection and transferred to the data carrier of the computing unit 30 in accordance with the classified network connection 12.

On the basis of the effective length of the network connection, the coefficient 2020 distribution of impairments and resources 2030 data using the computing unit 30 may be implemented classification (1040) classified connection in accordance with the maximum bandwidth for data. Classification may, in particular, to include the maximum possible data rate for classified network connection. The classification results can be provided (1050) to the user by the screen module printing or other output device. In particular, it is possible, for example, through the device through a graphical interface in order to connect to the Internet, moreover, any telephone subscriber provider of telephone services easy to determine whether a connection (for example, in his residential premises) for a particular network connection.

1. The classification method of network connections, and the geographic coordinates of the transmitter (10) and receiver (11) classified network connection (12) is known, characterized in that

on the basis of known data (5000) network connections via a computing unit (30) determine one or more coefficients (2010) distance and the received data associated with a defined probability, is transferred onto the storage medium of the computing unit (30), and coefficients (2010) distances indicate the effective length of a network connection, depending on the distance through the air, and determine the probability of whether a length of a network connection to a greater or lesser than its effective network length, determined by the factor (2012) reliability

on the basis of one or more coefficients (2010) distance factor (2012) reliability and geographic coordinates of the transmitter (10) and receiver (11) classified network connection (12) using a computing unit (30) define (1010) effective length of the network connection and transferred to the data carrier of computing the Loka (30) in accordance with the classified network connection (12),

on the basis of known data (5000) about network connections define (3020)at least one coefficient (2020) distribution of impairments and transferred to the data carrier of the computing unit (30)with at least one coefficient (2020) distribution of impairments indicates the ratio to each other impairments of various parts of the network connection,

define (3030) supply of resources (2030) data to determine the maximum throughput of data transmission for various types of modems and save on the storage medium of the computing unit (30) in accordance with the physical length (13) and the thickness of the cable (141, 142, 143, 144) network connection (12), and through the device (20) power measurement measured energy spectra for the types of modems, via a computing unit (30) on the basis of the energy spectra define the effective signal levels and the corresponding noise levels and module (31) Gaussian transformation on the basis of the signal levels and noise levels for different modulation data and/or modulating codes determine the supply of resources (2030) transmission for a pre-defined bit rate and

on the basis of the effective length of the network connection, factor (2020) distribution of impairments and reserves resources (2030) transmission d is the R by means of the computing unit (30) are classification (1040) classified network connection in accordance with its maximum throughput of data.

2. The method according to claim 1, characterized in that as coefficients (2011) distances by computing unit (30) determines the angular coefficient and the abscissa, thus define a linear relationship between the distance through the air and the effective length of the network connection.

3. The method according to claim 1, characterized in that by means of the computing unit determines the coefficients (2011) distance as parameters of a polynomial of at least 2nd class.

4. The method according to claim 1, characterized in that by means of the factor (2012) reliability choose a probability in the range from 0.85 to 0.95.

5. The method according to claim 1, characterized in that the reliability coefficient (2012) is set in the range from 700 to 800.

6. The method according to claim 1, characterized in that by means of the coefficient (2020) distribution of impairments determine linear dependence impairments relative to each other.

7. The method according to any one of claims 1 to 6, characterized in that the computing unit (30) determines the adjusted reserves data by at least one correction factor based on the stored resources (2030) data and stores them correlated with the respective physical lengths (13) and the thickness of the wires of the cables (141, 142, 153, 144) network connection (12) on the media data of the computing unit (30), and, at least, is in the adjustment factor includes the average deviation of the saved resources transfer data on effective resources data and/or coefficient correction unit for setting error correction block.

8. The method according to claim 7, characterized in that the correction factor plays a nonlinear relationship with respect to the physical lengths (13) and/or thickness of the wires of the cables(141, 142, 143, 144).

9. The method according to claim 1, characterized in that the noise levels are determined by the computing unit (30) based at least on the parameters of the crosstalk and the number of interference sources on the basis of the energy spectra.

10. The method according to claim 1 or 9, characterized in that the energy spectrum is measured depending on the transmission frequency for the types of modems (101, 102, 103, 104) ADSL and/or SDSL, and/or HDSL, and/or VDSL.

11. The method according to claim 10, characterized in that the possible types of modems (101, 102, 103, 104) SDSL include at least the type of modem G.991.2 and/or types of modems (101, 102, 103, 104) ADSL include at least the type of modem G.992.2.

12. The method according to claim 1, characterized in that the module (31) Gaussian transformations define resources data, at least for modulation data type 2B 1Q (2 binary, 1 Quaternary), and/or CAP (amplitude/phase modulation without carrier), and/or DMT (digital multitenancy), and/or PAM (pulse amplitude modulation).

13. The method according to any one of claims 1 to 6, 11 and 12, characterized in that the module (31) Gaussian transformations define resources data at measures which, for coding using lattice modulation code.

14. The classification method of network connections, and the geographic coordinates of the transmitter (10) and receiver (11) classified network connection (12) is known, characterized in that

on the basis of known data (5000) about network connectivity by computing unit (30) determine one or more coefficients (2011) distances and in accordance with the determined probability is transferred onto the storage medium of the computing unit (30), and coefficients (2011) distances indicate the effective length of a network connection, depending on the distance through the air, and determine the probability of whether a length of a network connection to a greater or lesser than its effective network length, determined by the factor (2012) reliability

based on the coefficients (2010) distance factor (2012) reliability and geographic coordinates of the transmitter (10) and receiver (11) classified network connection (12) using a computing unit (30) define (1010) effective length of the network connection and transferred to the data carrier of the computing unit in accordance with the classified network connection (12),

on the basis of known data (5000) about network connections define (3020)at least one coefficient (2020) distribution of impairments and transferred to the data carrier of the computing unit (30), in this case, at least one coefficient (2020) distribution of impairments indicates the ratio to each other impairments of various parts of the network connection,

determine the transfer rate (2030) bits to determine the maximum throughput of data transmission for various types of modems and save on the storage medium of the computing unit (30) in accordance with the physical length (13) and the thickness of the cable (141, 142, 143, 144) network connection (12), and through the device (20) power measurement measured energy spectra for the types of modems, via a computing unit (30) on the basis of the energy spectra define the effective signal levels and the corresponding noise levels and module (31) of the Gaussian transform-based signal levels and the noise level for different modulation data and/or modulating codes determine the transfer rate (2030) bits for the predefined resource inventory data and

on the basis of the effective length of the network connection, factor (2020) distribution of impairments and reserves resources (2030) data by the computing unit (30) are classification (1040) classified network connection in accordance with its maximum throughput of data.

15. With the royals by 14 characterized in that, as the coefficients (2011) distances by computing unit (30) determines the angular coefficient and the abscissa, thus define a linear relationship between the distance through the air and the effective length of the network connection.

16. The method according to 14, characterized in that by means of the computing unit (30) determines the coefficients (2011) distance as parameters of a polynomial of at least 2nd class.

17. The method according to 14, characterized in that by means of the factor (2012) reliability choose a probability in the range from 0.85 to 0.95.

18. The method according to 14, characterized in that the factor (2012) reliability has a value in the range from 700 to 800.

19. The method according to 14, characterized in that the module (31) Gaussian transformations define the bit rate for inventory resources data between 3 and 9 dB.

20. The method according to 14, characterized in that the module (31) Gaussian transformations define the bit rate for the resource inventory data 6 dB.

21. The method according to any of PP-20, characterized in that the computing unit (30) determines the adjusted bit rate by at least one correction factor based on the stored transmission speeds (2030) bits and stores them in accordance with the physical lengths 13) and the thickness of the wires of the cables (141, 142, 143, 144) network connection (12) on the media data of the computing unit (30), and a correction factor includes the average deviation of the stored bit rate with respect to the effective bit rate and/or ratio correction block for setting the correction block.

22. The method according to item 21, wherein the at least one correction factor plays a nonlinear relationship with respect to the physical lengths (13) and/or thickness of the wires of the cables(141, 142, 143, 144).

23. The method according to 14, characterized in that the noise levels are determined by the computing unit (30) based at least on the parameters of the crosstalk and the number of interference sources on the basis of the energy spectra.

24. The method according to 14 or 23, characterized in that the energy spectrum is measured depending on the transmission frequency for the types of modems (101, 102, 103, 104) ADSL and/or SDSL, and/or HDSL, and/or VDSL.

25. The method according to paragraph 24, wherein the possible types of modems (101, 102, 103, 104) SDSL include at least the type of modem G.991.2 and/or types of modems (101, 102, 103, 104) ADSL include at least the type of modem G.992.2.

26. The method according to 14, characterized in that the module (31) Gaussian transformations determine the bit rate, at least for modulation data type 2B 1Q, and/or CAP, or DMT, and/or FRAMES.

27. The method according to any of PP-20, 25 and 26, characterized in that the module (31) Gaussian transformations determine the bit rate, at least for coding using lattice modulation code.

28. Device for classifying network connections, and the geographic coordinates of the transmitter (10) and receiver (11) classified network connection (12) is known, characterized in that

the device comprises a computing unit (30) to define and store one or more coefficients (2011) distances in accordance with the determined probability based on known data (5000) about network connections, and the coefficients (2011) distances indicate the effective length of a network connection, depending on the distance through the air, and determine the probability of whether a length of a network connection to a greater or lesser than its effective network length is determined by the factor (2012) reliability

computing unit (30) includes means for determining and storing, at least one factor (2020) distribution of impairments on the basis of known data (5000), with at least one coefficient (2020) distribution of impairments indicates the ratio to each other impairments of various sections of setev the th connection

the device also includes a device (20) power measurement to measure the energy spectra for different types of modems, means (30) for calculating the effective signal levels and the corresponding noise levels on the basis of the energy spectra, and the module (31) of the Gaussian transform for the identification and conservation of resources (2030) transmission based on the signal levels, noise levels for different modulation data and/or modulating codes for a pre-defined bit rate.



 

Same patents:

FIELD: method and device for measuring quality of signal shape.

SUBSTANCE: real signal, representing shape of signal, divided on separate channels by time and codes, is produced, for example, by means of standard communication system for high speed data transfer. Controlling-measuring equipment produces ideal signal shape, matching real signal shape. This equipment produces estimate of shifts between parameters of real signal shape and ideal signal shape, then performs estimation of different measurements of quality of signal shape using quality measurements of compensated real shape of signal. Examples of processing real signal shape and appropriate ideal signal shape by means of controlling-measuring equipment are given. Provided method and devices can be utilized with any shape of signal, separated on channels by time and codes, not depending on equipment, which produces signal shape.

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3 cl, 3 dwg

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4 cl, 2 dwg

FIELD: systems for determining amount of available data transfer resources.

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3 cl, 4 dwg

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1 cl, 1 dwg

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5 dwg

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2 cl, 1 dwg

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3 cl, 1 dwg

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1 cl, 1 dwg

The invention relates to measuring technique and can be used to build electrical measuring parameters of a two-wire data lines

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33 cl, 4 dwg

The invention relates to systems division multiplexing wavelengths (MRDV)

The invention relates to a single-mode optical fiber with a controlled negative full dispersion and a relatively large effective area

The invention relates to optical circuit for attenuating optical noise

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FIELD: fiber-optic and open digital and analog communication lines.

SUBSTANCE: proposed method involves concurrent transfer of two optical data signals over optical communication line, their reception and comparison, and noise suppression. Optical data signals are shaped across output of nonlinear optical element by supplying at least one optical beam to element input and varying input power or phase, or frequency of one optical beam supplied to input of nonlinear optical element, or by varying electric or acoustic field applied to this element. In this way optical change-over between two unidirectional distributed and coupled waves propagating through nonlinear optical element is ensured. Each of these waves at output of nonlinear optical element corresponds to optical data signal. These data signals are supplied to differential amplifier designed for subtracting electric signals and/or to correlator which separates coinciding part of amplitude of these signals as function of time. As an alternative, optical data signals are shaped across output of tunnel-coupled optical waveguides of which at least one functions as nonlinear optical element.

EFFECT: enhanced noise immunity of line, eliminated impact of photodetector noise onto data signal reception.

33 cl, 4 dwg

FIELD: communications engineering, possible use for classification of connections.

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3 cl, 9 dwg

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EFFECT: expanded area of possible use.

6 dwg

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