Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L25/00—Baseband systems
  • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
  • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
  • H04L25/03006—Arrangements for removing intersymbol interference
  • H04L25/03343—Arrangements at the transmitter end
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B3/00—Line transmission systems
  • H04B3/02—Details
  • H04B3/32—Reducing cross-talk, e.g. by compensating
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L5/00—Arrangements affording multiple use of the transmission path
  • H04L5/0001—Arrangements for dividing the transmission path
  • H04L5/0003—Two-dimensional division
  • H04L5/0005—Time-frequency
  • H04L5/0007—Time-frequency the frequencies being orthogonal, e.g. OFDM(A), DMT
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L5/00—Arrangements affording multiple use of the transmission path
  • H04L5/02—Channels characterised by the type of signal
  • H04L5/023—Multiplexing of multicarrier modulation signals
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L25/00—Baseband systems
  • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
  • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
  • H04L25/03006—Arrangements for removing intersymbol interference
  • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
  • H04L2025/03426—Arrangements for removing intersymbol interference characterised by the type of transmission transmission using multiple-input and multiple-output channels
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L5/00—Arrangements affording multiple use of the transmission path
  • H04L5/003—Arrangements for allocating sub-channels of the transmission path
  • H04L5/0044—Arrangements for allocating sub-channels of the transmission path allocation of payload
  • H04L5/0046—Determination of how many bits are transmitted on different sub-channels

Definitions

• the invention relates to a method and to a device for data processing, in particular to reduce interference and/or crosstalk, and to a communication system comprising such a device .
• DSL or xDSL is a family of technologies that provide digital data transmission over the wires of a local telephone network .
• Asymmetric Digital Subscriber Line is a form of DSL, a data communications technology that enables faster data transmission over copper telephone lines than a conventional voice band modem can provide. Such fast transmission is achieved by utilizing frequencies that are normally not used by a voice telephone call, in particular, frequencies higher than normal human hearing.
• VDSL Very High Speed DSL
• xDSL technology providing faster data transmission over a single twisted pair of wires.
• High bit rates are achieved at a range of about 300 meters (1000 ft), which allows for 26 Mbit/s with symmetric access or up to 52Mbit/s in downstream - 12Mbit/s in upstream with asymmetric access.
• VDSL uses up to 4 different frequency bands, two for upstream (from the client to the telecom provider) and two for downstream.
• the underlying modulation technique is DMT (discrete multitone modulation) , wherein each tone carries a specified number of bits that are incor- porated into a complex QAM (quadrature amplitude modulation) symbol .
• DMT discrete multitone modulation
• QAM quadrature amplitude modulation
• VDSL is capable of supporting applications like HDTV, as well as telephone services (e.g., Voice over IP) and general Internet access, over a single connection.
• VDSL2 Very High Speed Digital Subscriber Line 2
• POTS plain old telephone service
• VDSL2 is designed to support the wide deployment of Triple Play services such as voice, video, data, high definition television (HDTV) and interactive gaming.
• VDSL2 enables operators and carriers to gradually, flexibly, and cost efficiently upgrade existing xDSL infrastructure.
• VDSL2 ITU-T G.993.2
• VDSL G.993.1
• the xDSL wide band modulation approaches are problematic re- lating to crosstalk interference that is introduced to the twisted pair transmission line and received by the modem.
• Crosstalk occurs when wires are coupled, in particular between wire pairs of the same or a nearby bundle that are used for separate signal transmission. Hence, data signals from one or more sources can be superimposed on and contaminate a data signal.
• the crosstalk comprises a near-end crosstalk (NEXT) and a far-end crosstalk (FEXT) .
• idle data sent induce crosstalk interference and hence disturb user data sent via other lines of, e.g., a multi-core cable. As there are typically 50 lines within one multi-core cable, such crosstalk could significantly impair the overall performance of the transmitting capability.
• Processing of a pre-coding matrix at the central office (CO) results in processing a 50*50 matrix thereby consuming a significant region on a chip and leading to a high power consumption .
• the problem to be solved is to overcome the disadvantage as stated before and to provide an approach for processing data in particular in an xDSL field such that crosstalk interference is reduced and/or minimized.
• a method for data processing in particular for processing a channel to reduce interference and/or crosstalk, said method comprising the following steps:
• the crosstalk matrix has substantially a block diagonal structure, which stems from the fact that the cable is separated into sub-bundles comprising a higher crosstalk, while crosstalk in-between sub-bundles is reduced by a (special) drilling of each sub-bundle.
• Pre-coding techniques like "zero-forcing” or minimum means squared error (MMSE) are discussed to overcome the crosstalk, which is in particular investigated as a DSL layer 3 technology.
• MMSE minimum means squared error
• said data comprise coefficients of a pre- coding matrix.
• pre-coding relates to both alternatives, i.e. pre-coding and equalization.
• said data may comprise information to describe a channel, in particular a channel comprising several lines that may connect a central office with several customer-premises equipments (e.g., (at least) one line per customer-premises equipment) .
• the clustering of the matrix comprises the steps:
• Clustering the matrix along said region.
• the clustered matrix can be pre- coded.
• the clustering of data comprises a co- ordination.
• the coordination may further be based on at least one of the following criteria:
• said clustering of the data comprises a provider and/or operator connecting lines to a central office (CO) and/or to a digital subscriber line access multiplexer (DSLAM) such that a crosstalk and/or interference is reduced or minimized.
• CO central office
• DSLAM digital subscriber line access multiplexer
• connecting of the lines can be done according to a predetermined scheme that reduces the crosstalk and/or interference effects.
• the central office (CO) and/or the digital subscriber line access multiplexer (DSLAM) comprises a distribution unit that allows switching and/or connecting lines between the CO and/or the DSLAM on the one side and customer-premises equipments (CPEs) on the other side .
• CO central office
• DSLAM digital subscriber line access multiplexer
• the distribution unit may be an auto- matic distribution unit that can be realized separately or, e.g., on a line card.
• a processing scheme may use a connection to all ports of a line card or of a DSLAM, but an internal distribution means and/or clusters may be used in order to reduce a number of modem correlations.
• the data represent a channel that is described as a multiple-input-multiple-output (MIMO) system comprising first coefficients associated with transmission lines and second coefficients in particular associated with crosstalk and/or interference.
• MIMO multiple-input-multiple-output
• the clustering of data comprises a clustering into groups.
• the data clustering into groups comprises the steps:
• the data may be grouped together according to cross-spectra values. Such values may be of a predefined range for grouping purposes. Several groups may be set up, preferably each such group providing a predetermined range. According to a further embodiment, a cross-spectra matrix is determined. Next, the cross-spectra matrix may be permuted to obtain a strong block-diagonal structure. Advantageously, the cross-spectra matrix may be inverted in a subsequent step.
• the channel matrix that results from the MIMO system is permuted according to the cross- spectra matrix.
• the inversion of the blocks of the permuted clustered channel matrix can be utilized for a partial crosstalk canceller performing pre-coding in order to reduce or cancel crosstalk and/or interference.
• the cross-spectra matrix may be utilized to find these clusters that enable appropriate permutation of the channel matrix.
• a bitloading for a multi-user scenario is calculated on a per-cluster or on a per-group basis, using the information obtained from said clustering.
• the methods set forth may be used for crosstalk and/or interference reduction and/or cancellation .
• the methods can be used in a digital subscriber line environment (DSL, xDSL) .
• DSL digital subscriber line environment
• the methods may be used in a communication network, in particular in a central office (CO) or in a digital sub- scriber line access multiplexer (DSLAM) .
• CO central office
• DSLAM digital sub- scriber line access multiplexer
• a device for data processing in particular for interference and/or crosstalk reduction and/or cancellation
• a processor unit that is arranged and/or equipped such that the method as described herein is executable on said processor.
• said device is a communication device, in particular a Central Office (CO) or a Digital Subscriber Line Access Multiplexer (DSLAM) .
• CO Central Office
• DSLAM Digital Subscriber Line Access Multiplexer
• the problem is also solve by a communication system comprising said device as describe herein.
• Fig.l shows user signals and crosstalk signals in a DSL system, wherein a central office is connected to several customer-premises equipments;
• Fig.2 shows a concept for interference pre-distortion comprising a channel transfer function, a pre-distorted transmit signal and a signal for pre-distortion;
• Fig.3A shows a 9*9 channel matrix comprising diagonal ele- ments and elements with crosstalk values higher than a predetermined threshold
• Fig.3B shows the 9*9 channel matrix of Fig.3A further comprising off-diagonal elements that have been reduced below a predetermined threshold by a coordination function;
• Fig.4 shows a processing structure for crosstalk cancellation by pre-coding with and without coordination
• Fig.5 shows a scenario comprising a communication network allowing to send data from a server to a client in particular via an xDSL connection;
• Fig.6 shows a multiple-input-multiple-output (MIMO) system modeling near-end crosstalk (NEXT) and far-end crosstalk (FEXT) ;
• Fig.7A shows a section of a ground-bundle with ten wire pairs of copper wires;
• Fig.7B shows a section of a main bundle with fifty pairs of copper wires.
• the approach presented herewith combines interference coordination by linear optimization with crosstalk cancellation by pre-coding.
• Coordination in multi-user systems has the advantage of a low processing effort and very small control signal overhead. Co- ordination may result on measurements together with static or semi-static adaptation of signal powers for the transmit signals or it may be based on other criteria, e.g., on a sub- bundle structure of the cable itself and/or the length of the individual lines, e.g., from a central office (CO) or digital subscriber line access multiplexer (DSLAM) to at least one customer-premises equipment (CPE) .
• CO central office
• DSLAM digital subscriber line access multiplexer
• CPE customer-premises equipment
• a interference level within a sub-bundle and between sub-bundles of a multi-core cable can be utilized.
• Semi-static coordination can be used to adapt more precisely to the actual channel (described by a matrix) thereby providing higher gains. However, such coordination may also require some control signaling.
• Fig.l shows user and crosstalk signals in a DSL system.
• a central office CO is connected via lines Sl, S2, S3 with customer-premises equipments CPEl, CPE2, CPE3.
• Interference that may comprise crosstalk and general interference is caused by any line Sl to S3 towards an adjacent line, e.g., the respective other lines of Fig.l.
• the coordination utilizes the fact that crosstalk levels IFxy (i.e. interference between lines x and y) are different between different lines x any y.
• varying constrained linearly solvable optimization criteria can be defined, e.g., like an overall throughput maximization or a maximization of a minimum throughput.
• Said criteria can be solved by linear optimization tools (e.g., available for the MATLAB software package) .
• Additional constraints may be defined, like a maximum transmitting power for each line and/or a sum power constraint in case of optimization over all single carriers of a multi carrier system.
• Coordination gains stem from the fact that a first group of lines may transmit data at a higher transmitting power than other lines without generating significant crosstalk while a second group of lines may reduce the overall throughput due to strong crosstalk effects to at least one adjacent line so that the overall transmitting capacity of the system increases, if such lines of the second group operate at a reduced power level.
• a lin- ear optimization can be performed for each sub-carrier individually. This may have a significant impact on the processing effort.
• a graph 201 shows a pre-distorted transmit signal
• a graph 202 shows a channel transfer function
• a graph 203 shows a signal used for pre-distortion.
• the received power level for several adjacent sub-carriers is set to a single value by pre-equalization of power levels.
• the linear optimization can be done for several sub-carriers to- gether. This would also be helpful for reducing the control signal overhead in case of bitloading, i.e. such bitloading can be completed for several adjacent sub-carriers with the same number of bits.
• clustering allows to further reduce the complexity of the linear optimization problem for calculating the optimal bitloading in a multi-user scenario. Because of the limited mutual influence of bitloadings of users belonging to different clusters, it may suffice optimizing the bitloading on a per-cluster basis, possibly for several adjacent subcar- riers . This procedure reduces the complexity of the linear optimization problem significantly, thus improving adaptation to real-world applications.
• the pre-equalization can be carried out without changing the overall transmit power, because power variations average over the sub-carriers.
• Typical gains may depend on the actual channel matrices for each sub-carrier.
• Crosstalk cancellation by pre-coding establish an improved performance at the cost of a high processing power and a particular control signaling required. It further leads to a high number of pilot signals and a lot of feedback information to be transmitted and processed in order to achieve an accurate channel measurement.
• the advantages of coordination as set forth may be combined with cancellation (i.e., significant performance gain) .
• cancellation i.e., significant performance gain
• One possibility to achieve the desired result is to cancel off-block diagonal elements in a channel matrix (i.e., elements of the channel matrix that are not located at or in a region around the diagonal of such matrix) if the respective element's value is below a given threshold value.
• Fig.3A shows a 9*9 channel matrix comprising diagonal element "o" and elements with crosstalk values above a predetermined threshold "x".
• the 9*9 channel matrix is clustered into a block diagonal structure comprising squares 301, 302 and 303 indicated by three 3*3 squares with solid lines comprising the diagonal of the 9*9 channel matrix (i.e. covering a region around said diagonal of the 9*9 channel matrix) .
• Fig.3B is based on Fig.3A, but the off-diagonal elements that have been reduced below a predetermined threshold by said coordination are indicated by encircled elements 304, 305, 306, 307 and 308.
• Fig.4 shows different processing structures 401 and 402 for a pre-coding system with and without coordination.
• the structure 401 shows a 50*50 matrix that may have to be estimated by the customer-premises equipment, fed back to the central office and processed by the central office.
• Another advantage is the combined effects of the strength of coordination - small implementation effort with low control overhead - combined with the cancellation, i.e. large gains are suitably exploited. This allows realizing similar performance gains as for full cancellation (processing the overall matrix with tremendous processing efforts) at a considerably smaller processing complexity, which is in particular important for practical realization.
• the reduced complexity has the advantage that a reduced number of calculations for matrix inversion and much less multiplications with the weighting coefficients are required. This is in particular crucial as such weighting has to be done for all data symbols.
• the processing can be done in blocks that are arranged in a region along the diagonal of the channel matrix, thereby simplifying the hardware structure, because such processing can be passed to different chips, e.g. if the number of lines which can be attached to a single chip is not sufficient.
• the number of weighting matrices can be significantly reduced, as such weighting can be used for several sub carriers .
• the processing can be reduced to the remaining lines, while a few lines only are handled by coordination. This is helpful if only a few lines for cancellation are missing at the processing chip.
• the lines that are not pre-coded may have to be selected so that throughput degradation is minimized.
• FIG.5 A particular scenario of a communication network is shown in Fig.5. Downstream Traffic is conveyed from the Server via a Network to a Central Office or Digital Subscriber Line Access Multiplexer CO/DSLAM.
• the CO/DSLAM is further connected via a digital subscriber line xDSL to a Customer-Premises Equipment CPE.
• the digital subscriber line connection can be in particular of the following type:
• VDSL Very High Speed Digital Subscriber Line
• the customer can be connected to the Customer-Premises Equipment CPE via a set-top box and a television or via a personal computer PC/TV. Data that is sent from the PC/TV towards the Server is referred to as Upstream Traffic.
• an operator or provider wants to efficiently use the xDSL downstream direction from the CO/DSLAM to the CPE by employing high data rate with low crosstalk effects.
• crosstalk i.e. mutual interference between xDSL systems transmitting data over the same cable-bundle, i.e. via different lines of a multi-core cable.
• This problem can be modeled by a MIMO (Multiple Input Multiple Output) transmission, in which each binder can be util- ized as a single MIMO channel, on which many xDSL systems may operate .
• MIMO Multiple Input Multiple Output
• Fig.6 shows a multiple-input-multiple-output (MIMO) system modeling near end crosstalk (NEXT) and far end crosstalk (FEXT) .
• MIMO multiple-input-multiple-output
• NEXT near end crosstalk
• FXT far end crosstalk
• the Loop Plant Model LPM represents the complete channel structure including (but not limited to) a main dis- tribution frame, optional branching devices and crosstalk interferences of various kind.
• Loop Plant Model LPM can be used to model upstream (from a customer-premises equipment CPE to a central office CO) and downstream (traffic from the CO towards the CPE) traffic via separate ports.
• Loop Plant Model LPM comprises a matrix of pulse responses comprising pulse responses of the transmission lines in its diagonal and crosstalk interference outside of the matrix' diagonal:
• h k , k (t) is associated with the respective transmission line and hence represents the pulse response of said transmission line and h k ,i(t) (k ⁇ l) represents the crosstalk interference outside of the matrix' diagonal, i.e. crosstalk interference between a port with an index k and another port with an index 1.
• the channel is modeled by a complex matrix H k .
• An input of the channel is a vector x k formed by x t
• the output of the channel is a vector y k , comprising y k/1 symbols.
• x k ,i is the QAM symbol transmitted on the k-th sub-carrier from the i-th xDSL system
• y k/1 is the corre- sponding symbol received at the other end of the cable from the i-th receiver.
• the QAM symbols x k ,i are sent by the CPEs and the symbols y k ,i are received by the DSLAM and/or the CO. In the case of downstream data transmission, this scheme applies vice versa.
• a vector n k contains noise samples n k/1 .
• Data transmission over a single sub-carrier can be modeled by
• crosstalk may be reduced by equalization and/or by pre-equalization on a per-carrier basis.
• the objective set forth herewith is in particular to partially cancel crosstalk and/or interference thereby taking only a sub-set of systems and carriers into account for (pre- ) equalization purposes.
• the partial crosstalk cancellation may be based on a clustering of signals.
• multi-core cables such as, e.g., telephone cable bundles (formed by star-quads, ground-bundles and main-bundles as shown in Fig.7A and Fig.7B)
• the cable is formed by near-independent groups of mutual interferers (e.g. those in the same ground- bundle) .
• This has an impact on cross-spectra of the signals as well as on the relating cross-spectra matrix, which can be calculated as :
• signals that are within the same group have strong cross-spectra (and the corresponding entries in the cross-spectra matrix will show high absolute values), while signals in different groups will have less cross-spectra (and the corresponding entries in the cross-spectra matrix will show low absolute values) .
• the reason for permuting the matrix stems from the fact that physically adjacent wire-pairs may be "logically" distant (i.e., the numbering of the signals in the logical representation does not necessarily match the physical sequence within the cable-bundle) . Therefore a clustering procedure is necessary in order to identify the groups of mutually- dependent signals, and to calculate the permutation that leads to a (nearly) block-diagonal cross-spectra matrix.
• a vector b can be obtained comprising indices of the last signals belonging to each group.
• S k ' it is possible to apply the same permutation to the signals and to the MIMO channel-matrix, thus obtaining a logical representation of signals belonging to the same "physical" group.
• a dimension of the blocks to be inverted is indicated by the elements of the vector b.
• the inverse matrices obtained are the partial crosstalk cancellers for the permuted signals contained in y k ' of equation (5) .

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• Engineering & Computer Science (AREA)
• Signal Processing (AREA)
• Computer Networks & Wireless Communication (AREA)
• Power Engineering (AREA)
• Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)

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• 2007
  • 2007-05-29 EP EP07010646A patent/EP1998464A1/de not_active Withdrawn
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  • 2008-05-15 WO PCT/EP2008/055974 patent/WO2008145537A1/en active Application Filing

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