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Patent US20030128752 - Time domain equalization for discrete multi-tone systems - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsA multiple carrier communication system includes a primary impulse shortening filter that receives an output signal of an analog to digital converter and accepts coefficients. A secondary impulse shortening filter receives the output signal of the analog to digital converter, outputs an output signal,...http://www.google.com/patents/US20030128752?utm_source=gb-gplus-sharePatent US20030128752 - Time domain equalization for discrete multi-tone systemsAdvanced Patent SearchTry the new Google Patents, with machine-classified Google Scholar results, and Japanese and South Korean patents.Publication numberUS20030128752 A1Publication typeApplicationApplication numberUS 10/320,920Publication dateJul 10, 2003Filing dateDec 17, 2002Priority dateMay 29, 1998Also published asUS6526105, US6785328Publication number10320920, 320920, US 2003/0128752 A1, US 2003/128752 A1, US 20030128752 A1, US 20030128752A1, US 2003128752 A1, US 2003128752A1, US-A1-20030128752, US-A1-2003128752, US2003/0128752A1, US2003/128752A1, US20030128752 A1, US20030128752A1, US2003128752 A1, US2003128752A1InventorsGopal Harikumar, Daniel Marchok, Kenneth RudofskiOriginal AssigneeTellabs Operations, Inc. A Delaware CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (1), Referenced by (14), Classifications (8), Legal Events (7) External Links: USPTO, USPTO Assignment, EspacenetTime domain equalization for discrete multi-tone systems
US 20030128752 A1Abstract
A multiple carrier communication system includes a primary impulse shortening filter that receives an output signal of an analog to digital converter and accepts coefficients. A secondary impulse shortening filter receives the output signal of the analog to digital converter, outputs an output signal, and passes coefficients to the primary impulse shortening filter. A reference signal generator outputs a reference signal. A comparator compares the output signal and the reference signal and outputs a resulting error signal. An adaptive processor computes coefficients for the secondary impulse shortening filter based on the error signal. Images(11) Claims(35)
What is claimed is: 1. A method for adapting a primary impulse shortening filter in a multiple carrier communication system, the method comprising: providing a secondary impulse shortening filter, comparing an output signal of the secondary impulse shortening filter to a reference signal to compute an error signal, computing coefficients of the secondary impulse shortening filter in an adaptive processor based on the error signal, and replacing coefficients of the primary impulse shortening filter with coefficients of the secondary impulse shortening filter. 2. The method of claim 1, further comprising: decoding an output signal of the primary impulse shortening filter to form output data, and encoding the output data to form the reference signal. 3. The method of claim 2, further comprising applying a discrete Fourier transform to the output signal of the primary impulse shortening filter prior to decoding the output signal. 4. The method of claim 2, further comprising applying an inverse discrete Fourier transform to the encoded output data in forming the reference signal. 5. The method of claim 1, further comprising: receiving a digital signal from an output of an analog to digital converter, applying the digital signal to the primary impulse shortening filter, delaying the digital signal to produce a delayed digital signal, applying the delayed digital signal to the secondary impulse shortening filter, and applying the delayed digital signal to the adaptive processor. 6. The method of claim 2, further comprising scaling the encoded output data with a set of scaling factors in forming the reference signal. 7. The method of claim 6, wherein the scaling factors are determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, and computing the scaling factors so that the coefficients computed in the adaptive processor provide the secondary impulse shortening filter with a spectral response that matches the desired spectral response. 8. The method of claim 7, further comprising applying a discrete Fourier transform to the output signal of the primary impulse shortening filter prior to decoding the output signal and measuring the noise power spectral density at an output of the discrete Fourier transform. 9. The method of claim 6, further comprising applying an inverse discrete Fourier transform to the scaled, encoded output data. 10. A method for adapting an impulse shortening filter in a multiple carrier communication system having a spectrally constrained impulse shortening filter, the method comprising: comparing an output signal of the spectrally constrained impulse shortening filter to a reference signal to compute an error signal, and computing coefficients of the spectrally constrained impulse shortening filter in an adaptive processor based on the error signal. 11. The method of claim 10, wherein the reference signal comprises a predetermined signal stored in a memory in the communication system. 12. The method of claim 10, further comprising: scaling predetermined reference values with a set of scaling factors to form scaled values, and applying an inverse discrete Fourier transform to the scaled values to form the reference signal. 13. The method of claim 12, wherein the scaling factors are determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, and computing the scaling factors so that the coefficients computed in the adaptive processor provide the secondary impulse shortening filter with the desired spectral response. 14. The method of claim 10, further comprising: receiving a data signal from an output of an analog to digital converter, applying the data signal to the spectrally constrained impulse shortening filter, and applying the data signal to the adaptive processor. 15. A method for adapting an impulse shortening filter in a multiple carrier communication system having a spectrally constrained impulse shortening filter, the method comprising: receiving a digital signal, applying the digital signal to the spectrally constrained impulse shortening filter to obtain a first output signal, computing a reference signal from the first output signal, delaying the digital signal to produce a delayed digital signal, applying the delayed digital signal to the spectrally constrained impulse shortening filter to obtain a second output signal, comparing the second output signal to the reference signal to compute an error signal, and computing coefficients of the spectrally constrained impulse shortening filter in an adaptive processor based on the error signal. 16. The method of claim 15, wherein computing the reference signal comprises: decoding the first output signal to form output data, and encoding the output data to form the reference signal. 17. The method of claim 16, wherein computing the reference signal further comprises applying a discrete Fourier transform to the first output signal prior to decoding the first output signal. 18. The method of claim 16, wherein computing the reference signal further comprises applying an inverse discrete Fourier transform to the encoded output data. 19. The method of claim 16, wherein computing the reference signal further comprises scaling the encoded output data with a set of scaling factors. 20. The method of claim 19, wherein the scaling factors are determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, and computing the scaling factors so that the coefficients computed in the adaptive processor provide the spectrally constrained impulse shortening filter with a spectral response that matches the desired spectral response. 21. The method of claim 20, further comprising applying a discrete Fourier transform to the first output signal prior to decoding the first output signal and measuring the noise power spectral density at an output of the discrete Fourier transform. 22. The method of claim 19, further comprising applying an inverse discrete Fourier transform to the scaled, encoded output data. 23. A multiple carrier communication system comprising: a primary impulse shortening filter connected to receive a digital signal and to accept coefficients, a secondary impulse shortening filter connected to receive the digital signal, output an output signal, and pass coefficients to the primary impulse shortening filter, a reference signal generator configured to output a reference signal, a comparator connected to compare the output signal and the reference signal and output a resulting error signal, and an adaptive processor that computes coefficients for the secondary impulse shortening filter based on the error signal. 24. The multiple carrier communication system of claim 23, further comprising: a discrete Fourier transform connected to receive an output signal of the primary impulse shortening filter, and a decoder connected to receive the transformed output signal from the discrete Fourier transform. 25. The multiple carrier communication system of claim 24, wherein the reference signal generator comprises an encoder connected to receive output data from the decoder. 26. The multiple carrier communication system of claim 25, wherein the reference signal generator further comprises a scaling filter connected to scale the output data from the encoder using a set of scaling factors. 27. The multiple carrier communication system of claim 26, wherein the scaling factors are determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, computing the scaling factors so that the coefficients computed in the adaptive processor provide the secondary impulse shortening filter with the desired spectral response. 28. The multiple carrier communication system of claim 26, further comprising an inverse discrete Fourier transform connected to receive the scaled output signal from the scaling filter. 29. A multiple carrier communication system comprising: a spectrally constrained impulse shortening filter connected to receive a digital signal and to accept coefficients, a reference signal generator configured to output a reference signal, a comparator connected to compare the digital signal and the reference signal and output a resulting error signal, and an adaptive processor that computes coefficients for the spectrally constrained impulse shortening filter based on the error signal. 30. The multiple carrier communication system of claim 29, further comprising a memory that stores the reference signal as a predetermined signal. 31. The multiple carrier communication system of claim 30, further comprising: a discrete Fourier transform connected to receive the reference signal from the memory, a scaling filter connected to scale the reference signal using a set of scaling factors, and an inverse discrete Fourier transform connected to receive the scaled reference signal. 32. The multiple carrier communication system of claim 31, wherein the scaling factors are determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, computing the scaling factors so that the coefficients computed in the adaptive processor provide the spectrally constrained impulse shortening filter with the desired spectral response. 33. A method for adapting a primary impulse shortening filter in a multiple carrier communication system, the method comprising: selecting a first cyclic prefix length for the communication system from a set of candidate lengths, transmitting data having a cyclic prefix of the first selected length to a receiver, computing a first maximum bit rate value in the receiver for the first selected length, and sending the first maximum bit rate value to the transmitter. 34. The method of claim 33, wherein computing the maximum bit rate value comprises measuring received signal power and received noise power of the transmitted data. 35. The method of claim 33, further comprising: selecting a second cyclic prefix length for the communication system from the set of candidate lengths, transmitting data having a cyclic prefix of the second selected length to a receiver, computing a second maximum bit rate value in the receiver for the second selected length, sending the second maximum bit rate value to the transmitter, comparing the first maximum bit rate value to the second maximum bit rate value, and selecting the cyclic prefix length corresponding to the greater of the first and second maximum bit rate values. Description
CROSS REFERENCE TO RELATED APPLICATIONS [0001] This application claims priority from U.S. Provisional Application No. 60/087,336, filed May 29, 1998 and entitled “Time Domain Equalization in DMT Systems”, which is incorporated herein by reference. This application is related to U.S. application Ser. No. 09/054,468, filed Apr. 3, 1998 and entitled “Spectrally Constrained Impulse Shortening Filter for a Discrete Multi-tone Receiver”, which is incorporated herein by reference.
BACKGROUND [0002] The invention relates to time-domain equalization in a discrete multi-tone (DMT) receiver. [0003] Conventional single carrier modulation techniques translate data bits for transmission through a communication channel by varying the amplitude and/or phase of a single sinusoidal carrier. By contrast, DMT, which is also referred to as Orthogonal Frequency Division Multiplexing (OFDM) or Multicarrier Modulation (MCM), employs a large number of sinusoidal subcarriers, e.g., 128 or 256 subcarriers. The available bandwidth of the communication channel is divided into subchannels and each subchannel communicates a part of the data. A DMT system may employ quadrature amplitude modulation (QAM) for each of the subcarriers. [0004] OFDM-based systems transmit blocks of information bits. The time required to transmit one such block is called the symbol period. The time domain waveform that corresponds to one such block of bits is called a symbol. [0005] Intersymbol interference (ISI) arises from the characteristics of practical communication channels and limits the rate at which information can be transmitted through them. Specifically, communication channels typically have an Effective Discrete-Time Impulse Response (EDIR) that is greater than one sample time in length, which causes ISI. ISI is a well-known phenomenon in single-carrier communication systems and there are many techniques for reducing it. The process of such ISI reduction is called equalization. ISI is discussed, for example, in Proakis, Digital Communications, McGraw Hill, 2nd Edition, 1989. [0006] Equalization in OFDM-based systems is achieved by a two stage process. First, at the transmitter, a Cyclic Prefix (CP) is employed by affixing an end-portion of each symbol to the beginning of the symbol. A cyclic prefix that is greater than the EDIR of the channel prevents one symbol from interfering with another. Furthermore, it also facilitates a simple method of neutralizing the time domain spread of each symbol forced by the channel. This is achieved through a simple frequency domain process in the receiver which requires one multiplication operation for each subcarrier used. The use of a Cyclic Prefix to reduce ISI is discussed, for example, in: Cimini, “Analysis and Simulation of a Digital Mobile Channel using Orthogonal Frequency Division Multiplexing,” IEEE Transactions on communications, pp 665-675, July 1985; Chow, “A Discrete Multi-Tone Transceiver System for HDSL applications,” IEEE Journal on Selected Areas of Communications, 9(6):895-908, August 1991; and “DMT Group VDSL PMD Draft Standard Proposal,” Technical Report, T1E1.4/96-329R2, ANSI 1997. [0007] Another problem arising in conventional DMT systems is noise bleeding, which occurs when noise from one frequency band interferes with a signal whose subcarrier is in another frequency band. Noise bleeding is caused, in general, by a discrete Fourier transform (DFT) operation at the receiver. Noise bleeding is discussed in, for example, Worthen et. al., “Simulation of VDSL Test Loops,” Technical Report T1E1.4/97-288, ANSI 1997. [0008] In a perfectly synchronized DMT system, a signal in one frequency band does not interfere with a signal whose subcarrier is in another frequency band. However, noise from one band may interfere with other less noisy bands and render them unusable. Techniques for dealing with noise-bleeding include wavelet-based solutions. However, wavelet-based solutions are, in general, computationally intensive. [0009] Other references dealing with time domain equalization include: Chow, J. S. and Cioffi, J. M., “A Cost-effective Maximum Likelihood Receiver for Multicarrier Systems”, Proceedings of the ICC, 1992; Melsa, Peter J. W., Younce, Richard C., and Rohrs, Charles E., “Optimal Impulse Response Shortening”, Proceedings of the thirty-third Annual Allerton Conference on Communication. Control and Computing, 1995, pp. 431-438; Harikumar, Gopal and Marchok, Daniel, “Shortening the Channel Impulse Response of VDSL Loops for Multicarrier Applications”, Technical report T1E1.4/97-289, ANSI, 1997. SUMMARY [0010] A spectrally constrained impulse shortening filter (SCISF) may be used, for example, in DMT systems. The coefficients of the SCISF may be computed efficiently. For example, the coefficients may be computed and changed through a training process that may occur upon start up of the communication system and periodically during its operation. [0011] The SCISF serves two primary functions. First, it reduces intersymbol interference (ISI) by reducing the length of the effective discrete-time impulse response (EDIR) of the communication channel. Conventional impulse shortening filters may have deep nulls in their frequency response. By contrast, the SCISF has a filter characteristic that is essentially free from undesired nulls that may attenuate or completely eliminate certain subcarriers. [0012] Second, the SCISF reduces noise bleeding between subchannels by attenuating noisy channels in a manner that does not reduce the signal to noise ratio (SNR) in these channels, but reduces the noise power that may appear in the sidelobes of adjacent subchannels. The SCISF accomplishes these functions by applying a frequency constraint to the signal based on a desired spectral response. [0013] The coefficients of the SCISF are computed independent of the length of the cyclic prefix, the symbol length, and the frequency domain equalization characteristics of the system. The SCISF is particularly effective in systems in which additive noise dominates intersymbol interference, or in which noise bleeding predominates. The SCISF reduces noise bleeding with a filter structure that is shorter than that obtained with other techniques. Consequently, the SCISF is less complex and its coefficients are easier to compute, which reduces system complexity and cost. The SCISF may be particularly well suited, for example, for very high-speed digital subscriber lines (VDSL) systems, which generally have low intersymbol interference and tend to suffer from noise bleeding. [0014] In addition, dynamic selection of a cyclic prefix (CP) that maximizes the data throughput for a communication channel having a particular noise profile is provided. Dynamic selection of the CP allows the communication system to adapt to changing noise conditions in the communication channel. [0015] In one aspect, generally, a primary impulse shortening filter is adapted in a multiple carrier communication system. A secondary impulse shortening filter is provided. An output signal of the secondary impulse shortening filter is compared to a reference signal to compute an error signal. Coefficients of the secondary impulse shortening filter are computed in an adaptive processor based on the error signal. Coefficients of the primary impulse shortening filter are replaced with coefficients of the secondary impulse shortening filter. [0016] Embodiments may include one or more of the following features. An output signal of the primary impulse shortening filter may be decoded to form output data. The output data may be encoded to form the reference signal. A discrete Fourier transform may be applied to the output signal of the primary impulse shortening filter prior to decoding the output signal. An inverse discrete Fourier transform may be applied to the encoded output data in forming the reference signal. [0017] A digital signal may be received from an output of an analog to digital converter. The digital signal may be input to the primary impulse shortening filter. The digital signal may be delayed. The delayed digital signal may be input to the secondary impulse shortening filter and the adaptive processor. [0018] The encoded output data may be scaled with a set of scaling factors in forming the reference signal. The scaling factors may be determined by: measuring received noise power spectral density, computing a desired spectral response based on the measured noise power, and computing the scaling factors so that the coefficients computed in the adaptive processor provide the secondary impulse shortening filter with a spectral response that matches the desired spectral response. A discrete Fourier transform may be applied to the output signal of the primary impulse shortening filter prior to decoding the output signal. The noise power spectral density may be measured at an output of the discrete Fourier transform. An inverse discrete Fourier transform may be applied to the scaled, encoded output data. [0019] In another aspect, an impulse shortening filter is adapted in a multiple carrier communication system having a spectrally constrained impulse shortening filter. An output signal of the spectrally constrained impulse shortening filter is compared to a reference signal to compute an error signal. Coefficients of the spectrally constrained impulse shortening filter are computed in an adaptive processor based on the error signal. [0020] Embodiments may include one or more of the following features. The reference signal may be a predetermined signal stored in a memory in the communication system. A discrete Fourier transform may be applied to predetermined reference values to form transformed reference values. The transformed reference values may be scaled with a set of scaling factors to form scaled. An inverse discrete Fourier transform may be applied to the scaled values to form the reference signal. [0021] A data signal may be received from an output of an analog to digital converter. The data signal may be input to the spectrally constrained impulse shortening filter and the adaptive processor. [0022] In another aspect, a multiple carrier communication system includes a primary impulse shortening filter that receives an output signal of an analog to digital converter and accepts coefficients. A secondary impulse shortening filter receives the output signal of the analog to digital converter, outputs an output signal, and passes coefficients to the primary impulse shortening filter. A reference signal generator outputs a reference signal. A comparator compares the output signal and the reference signal and outputs a resulting error signal. An adaptive processor computes coefficients for the secondary impulse shortening filter based on the error signal. [0023] Embodiments may include one or more of the following features. A discrete Fourier transform may receive an output signal of the primary impulse shortening filter. A decoder may receive the transformed output signal from the discrete Fourier transform. The reference signal generator may include an encoder that receives output data from the decoder. The reference signal generator may include a scaling filter that scales the output data from the encoder using a set of scaling factors. An inverse discrete Fourier transform may receive the scaled output signal from the scaling filer. [0024] In another aspect, a multiple carrier communication system may include a spectrally constrained impulse shortening filter that receives an output signal of an analog to digital converter and accepts coefficients. A reference signal generator outputs a reference signal. A comparator compares the output signal and the reference signal and outputs a resulting error signal. An adaptive processor computes coefficients for the spectrally constrained impulse shortening filter based on the error signal. [0025] Embodiments may include one or more of the following features. A memory may store the reference signal as a predetermined signal. A discrete Fourier transform may receive the reference signal from the memory. A scaling filter may scale the reference signal using a set of scaling factors. An inverse discrete Fourier transform may receive the scaled reference signal. [0026] Other features and advantages will be apparent from the following detailed description, including the drawings, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS [0027] [0027]FIG. 1 is a block diagram of a discrete multi-tone communication system with a spectrally constrained impulse shortening filter. [0028] [0028]FIG. 2 is a block diagram of a system for adapting a spectrally constrained impulse shortening filter in an initial training process. [0029] [0029]FIGS. 3A and 3B are block diagrams of a system for adapting a spectrally constrained impulse shortening filter in an periodic or continuous training process. [0030] [0030]FIG. 4 is a block diagram of a generalized adaptation system that employs frequency scaling in the feedback loop. [0031] [0031]FIG. 5 is a block diagram of a system for adapting a spectrally constrained impulse shortening filter in an initial training process that includes frequency scaling in the feedback loop. [0032] [0032]FIGS. 6A and 6B are block diagrams of a system for adapting a spectrally constrained impulse shortening filter in an periodic or continuous training process that includes frequency scaling in the feedback loop. [0033] FIGS. 7A-7D are plots of simulation results for a discrete multi-tone system. [0034] FIGS. 8A-8D are plots of simulation results for a discrete multi-tone system.
DESCRIPTION [0035] As shown in FIG. 1, a discrete multi-tone (DMT) communication system 10 has a transmitter 12 and a receiver 14. The transmitter 12 accepts an input data bit stream which passes through a constellation encoder 20. The encoder 20 divides the serial input bit stream into blocks of data. These blocks of data are further subdivided into smaller blocks corresponding to subchannels. Each of these smaller blocks are used to compute a complex value representing a constellation point. Each constellation point corresponds to a subsymbol. The subsymbols are then output by the encoder. Taken together, the subsymbols constitute a symbol. [0036] The subsymbols are supplied to an inverse discrete Fourier transform (IDFT) 30, which may be implemented, for example, in a digital signal processor. The IDFT 30 outputs N time samples of a symbol. The time samples are processed by a parallel to serial converter 40 to form a single stream of time samples. [0037] Following the parallel to serial converter 40, a prefix adder 50 adds a cyclic prefix to the beginning of each symbol to reduce intersymbol interference (ISI). Alternatively, the cyclic prefix may be added in the parallel to serial converter. After the cyclic prefix is added, the resulting signal passes through a digital-to-analog (D/A) converter 60 for transmission to the receiver 14 through a communication channel 70. An analog transmit filter 65 may be included following the D/A converter to band limit the transmitted signal. [0038] At the receiver 14, the signal passes through an analog-to-digital (A/D) converter 80 and then through a spectrally constrained impulse shortening filter (SCISF) 90. A prefix stripper 100 strips the cyclic prefixes from the resulting symbols and a serial to parallel converter 110 divides the stream of time samples into parallel signal paths that form the inputs to a discrete Fourier transform (DFT) 120. The DFT 120 converts the time samples into subsymbols. A frequency domain equalization filter 130 equalizes the subsymbols. A decoder 140 converts the subsymbols into a data bits and outputs the resulting data. An analog receive filter 75 may be included prior to the A/D converter in order to band limit the received signal. [0039] As discussed above, a cyclic prefix is added to each symbol prior to transmission through the communication channel to reduce the effects of ISI. The cyclic prefix is added by copying the last ν time samples from the end of a symbol and placing them at the beginning of the symbol. To eliminate ISI, the length of the cyclic prefix, ν, is chosen to be longer than the effective discrete-time impulse response (EDIR) of the channel. However, because the cyclic prefix constitutes redundant data, increasing the length of the cyclic prefix reduces the efficiency of the communication system. For example, in a system having N time samples per symbol and a cyclic prefix of ν time samples, the efficiency of the system will be reduced by a factor of N/(N+ν). Efficiency may be maximized either by minimizing ν or maximizing N. However, increasing N increases the complexity, latency and computational requirements of the system and at some point becomes impractical. Accordingly, it is desirable to minimize ν. [0040] A spectrally constrained impulse shortening filter having an impulse response, g(n), may be employed in the receiver to minimize the length of the cyclic prefix by decreasing the EDIR of the effective communication channel, which includes the transmit and receive filters, the impulse shortening filter, and the physical transmission channel. The use of an impulse shortening filter is referred to as time domain equalization. Decreasing the EDIR allows a shorter cyclic prefix to be used without increasing ISI. [0041] The SCISF may be configured, by determining the filter coefficients during a training or adaptation period. The SCISF filters the output {yk} of the receiver A/D 80. The coefficients are selected using an algorithm that minimizes the squared error between a reference sequence {uk} generated by the receiver and the output of the SCISF {ûk}. The SCISF may be a finite impulse response (FIR) filter or an infinite impulse response (IIR) filter. The SCISF may be trained following activation of the communication system or periodically during operation of the system to compensate for variations in the channel noise profile. [0042] The training may be performed using a variation of one of the classical adaptive algorithms, such as least mean squares (LMS), normalized LMS, or recursive least squares (RLS). For example, the following algorithm is a version of the normalized LMS algorithm in which b0, . . . , bN and a1, . . . , aN are the FIR and IIR parts of a SCISF having an impulse response, g. The z-transform G(z) is: G  ( z ) = b 0 + b 1  z - 1 + ⋯ + b N  z - N 1 - a 1  z - 1 - ⋯ - a N  z - N ( 1 ) [0043] The adaptation of coefficients ai and bi is defined in the following equations, in which ai(k) and bi(k) are the values of these coefficients during the kth iteration. The parameter μ is a predetermined constant with a value of 0.4. u ^ k = ∑ i = 0 N   b i  ( k )  y k - i + ∑ j = 1 N   a i  ( k )  u ^ k - i (2a) αk =[b 0(k), . . . , b N(k)] (2b)
[0044] [0044] e k  Δ _ _  u k - u ^ k (2f) a k + 1 = a k + μ  e k  d k  d k  2 (2g) β k + 1 = β k + µ  e k  c k  c k  2 (2h) [0045] In a first embodiment, the coefficients of the SCISF are determined during an initial training period following the activation of the communication system using the LMS algorithm described above. A predetermined sequence of bits xk is input to the transmitter 12. The sequence of bits results in a sequence of real numbers {xk} at the input of the D/A 60. As shown in FIGS. 1 and 2, the transmitted signal is filtered and noise-corrupted by the transmission channel 70, resulting in a received sequence {yk} at the output of the A/D 80 in the receiver 14. The SCISF 90 filters and transforms the received sequence {yk} into an output sequence {{circumflex over (x)}k}. The output sequence {{circumflex over (x)}k} is compared (in a signal comparator 205) to the predetermined sequence xk, which is stored in memory 210 in the receiver. The comparison results in an error signal ek that is input to the LMS algorithm processor 215 along with sequence {{circumflex over (x)}k}. [0046] The training process determines coefficients for the SCISF so that the output {{circumflex over (x)}k} matches the predetermined sequence {xk} as closely as possible in a least squares sense, i.e., the mean square error between the output and the predetermined sequence is minimized. During the training process, the coefficients of the SCISF converge to values that enable the SCISF to reduce ISI and additive noise. The resulting SCISF matches P1(ω) in the frequency domain in a least squares sense, where: P 1  ( ω ) = S x  ( ω )  H * ( ω ) S x  ( ω ) | H  ( ω )  | 2  + S η  ( ω ) ( 3 ) [0047] In the equation above, Sχ(ω) is the power-spectral density at the input ot the transmitter D/A 60, Sη(ω) is the power spectral density of the additive noise at the output of the A/D 80, and H(ω) is the frequency response of the effective discrete-time impulse response (EDIR) of the transmission channel 70, transmit filter 65, and receive filter 75 measured between the input of the transmitter D/A 60 and the output of the receiver A/D 80. [0048] Upon completion of the initial training of the SCISF, the SCISF coefficients are fixed and the frequency domain equalizer (FEQ 130) of the receiver is trained using standard techniques for DMT receivers. Following the training of the FEQ, the SCISF can be periodically trained or adapted during operation of the communication system. Since it is not efficient to repeatedly transmit a predetermined bit sequence during operation of the communication system, the periodic training process uses transmitted communication data to generate the reference and output sequences, as described below. [0049] During operation of the communication system, a sequence of communication data bits xk is input to the transmitter 12 (see FIG. 1). The sequence of data bits results in a sequence of real numbers {xk} at the input of the D/A 60. As shown in FIGS. 1 and 3A, the transmitted signal is filtered and noise-corrupted by the transmission channel 70, resulting in a received sequence {yk} at the output of the A/D 80 in the receiver 14. The SCISF 90 filters and transforms the received sequence {yk} into an output sequence {{circumflex over (x)}′k}. [0050] The received sequence {yk} is also input to a delay 305 and then to a secondary SCISF 300 that has the same coefficients as the primary SCISF 90 following the initial training. Such a configuration allows periodic training to be performed without disruption to the operation of the communication system. The secondary SCISF 300 is periodically or continuously trained using an algorithm similar to that used for the initial training. The new coefficients of the secondary SCISF 300 are periodically copied to the primary SCISF 90. [0051] In an initial training process, the output sequence {{circumflex over (x)}k} of the secondary SCISF 300 would be compared (in a signal comparator 205) to a predetermined sequence xk stored in memory. However, as discussed above, a sequence of data communication bits is used as a reference sequence for training rather than a predetermined sequence. As such, the receiver must have a way of generating a reference signal to compare to the output of the SCISF. [0052] To compute the reference sequence, the receiver essentially duplicates the encoding and modulation processes of the transmitter using the output of the decoder 140. Because the initial training has already been performed, the SCISF 90 output {{circumflex over (x)}′k} matches the predetermined sequence {xk} closely and ISI and additive noise are minimized. Hence, the data output of the decoder 140 closely matches the transmitted sequence of communication data bits Xk. The data bits are input to an encoder 320, an IDFT 330, a parallel to serial converter 340, and a prefix adder 350 similar to those in the transmitter. The output sequence {xk} of this chain is input to the LMS algorithm processor 215 and used as a reference sequence in the training algorithm. [0053] The output sequence {{circumflex over (x)}k} of the secondary SCISF 300 is compared (in a signal comparator 205) to the reference sequence {xk}, which is output by the encoding/modulation chain (320, 330, 340 and 350). As noted above, the received sequence {yk} passes through a delay 305 before being input to the secondary SCISF 300. The delay 305 compensates for the processing delay in the demodulation/decoding chain and the encoding/modulation chain. The comparison results in an error signal ek that is input to the LMS algorithm processor 215. The training process determines coefficients for the secondary SCISF 300 so that the output {{circumflex over (x)}k} matches the reference sequence {xk} as closely as possible in a least squares sense, i.e., the mean square error between the output and the reference sequence is minimized. Periodically, the coefficients of the secondary SCISF 300 are copied to the primary SCISF 90. [0054] Alternatively, as shown in FIG. 3B, the periodic training may be performed with a single SCISF 90. In this configuration, a received sequence {yk} is output by the A/D 80 in the receiver 14. The SCISF 90 filters and transforms the received sequence {yk} into an output sequence {{circumflex over (x)}′k}. The received sequence {yk} is also input to a delay 305. After the received sequence {yk} passes through the SCISF 90, a data switch 360 is changed from position A to position B, allowing the delayed received sequence to make a second pass through the SCISF 90. An output switch 370 also may be opened, so that data is not output during the training process. In addition, the SCISF coefficients are controlled by the LMS algorithm during the training process. [0055] A reference sequence is computed as in the configuration of FIG. 3A. The data bits are input to an encoder 320, an IDFT 330, a parallel to serial converter 340, and a prefix adder 350. The resulting reference sequence {xk} is input to the LMS algorithm processor. [0056] The output sequence {{circumflex over (x)}k} of the second pass through the SCISF 90 is compared (in signal comparator 205) to the reference sequence. As noted above, the received sequence {yk} passes through a delay 305 before being input to the SCISF 90 for the second pass. The delay 305 compensates for the processing delay in the demodulation/decoding chain and the encoding/modulation chain. The comparison results in an error signal ek that is input to the LMS algorithm processor 215. The training process determines coefficients for the SCISF 90 so that the output {{circumflex over (x)}k} matches the reference sequence {xk} as closely as possible in a least squares sense, i.e., the mean square error between the output and the reference sequence is minimized. The coefficients of the SCISF 90 then are updated to the coefficients determined in the training process. [0057] In a second embodiment, the SCISF 90 coefficients are chosen so that the frequency response of the SCISF matches a desired spectral response Gd(ω) that seeks to minimize the effects of noise-bleeding and maximize system bit throughput. The desired spectral response Gd(ω) is determined based on the signal-to-noise ratios observed in the various frequency bins of the DFT 120 in the receiver. [0058] For example, an OFDM system may have M tones, N of which (m1 through mN) are used. The system operates over a channel with analog frequency response Hc(ƒ). Referring again to FIG. 1, the analog noise power spectral density at the input of the receiver A/D 80 is Sη(ƒ). Prior to receiver A/D 80, the received analog signal may be filtered by an anti-aliasing filter (i.e., receive filter 75) having a transfer function Ha(ƒ). The effective discrete-time impulse response (EDIR) of the transmission channel of the OFDM system (including the transmit filter 65 and receive filter 75) is h(n). The output of the A/D 80 is input to a SCISF 90 having an impulse response g(n). G(ω) is the spectral response corresponding to g(n). [0059] The expected signal energy μ(k) observed in frequency bin k at the output of the DFT120, which has a length of NM, is: μ  ( k ) = C 1  D k | H  ( π   k M )  | 2 | G  ( π   k M )  | 2 ; H  ( ω ) = H c  ( ω 2  π   T )  H a  ( ω 2  π   T ) ( 4 ) [0060] where C1 is a constant, 1/T is the sampling frequency and Dk is the transmitted power in frequency bin k. The noise power η(k) in bin k is: η  ( k ) = C 2  [ S η  ( ω 2  π   T )   G  ( ω )  2   H a  ( ω 2  π   T )  2 ] * [ sin 2  ( M   ω ) sin 2  ( ω 2 ) ]  | ω = π   k ′ M ( 5 ) [0061] where C2 is a constant and * denotes a convolution of the discrete Fourier transforms. If the noise in the bands occupied by unused tones is sufficiently attenuated by the anti-alias filter (receive filter 75), η(k) is approximately: η  ( k ) ≈ C 3  ∑ l = M 1 M 2   S η  ( 1 2  MT )   G  ( π   l M )  2   H a  ( l 2  MT )  2  ( τ  ( k - l ) + τ  ( 2  M - k - l ) ) , ( 6 ) [0062] where τ(n) is defined as: τ  ( n ) = ∫ - π NM π NM  [ sin 2  ( M  ( π   n M - λ ) ) sin 2  ( 1 2  ( π   n M - λ ) ) ]    λ , ( 7 ) [0063] m1 . . . mN are the used tones, and C3 is a constant. A vector of frequency magnitudes g is defined as: g   Δ _ _  [ | G  ( π   m 1 M )  | 2 ⋮ | G  ( π   m N M )  | 2 ] = [ G 1 ⋮ G N ] ( 8 ) [0064] The SNR in frequency bin k is r k  G k s k T  g [0065] for scalars rk and vectors sk. The scalars rk are defined by: r k  Δ =  C 1  D k   H  ( π   k M )  2 ( 9 ) [0066] and sk(l), the lth component of sk is defined by: s k  ( 1 ) = C 3  S η  ( 1 2   MT )   H a  ( 1 2   MT )  2  ( τ  ( k - l ) + τ  ( 2  M - k - l ) ) ( 10 ) [0067] To determine an expression for g that maximizes system bit throughput, the capacity of each frequency bin k is approximated by log(1+SNRk). Accordingly, the optimal spectral profile is determined by minimizing the cost function F, where: F  ( g ) = - ∑ k = m 1 m N  log  ( 1 + r k  G k s k T  g ) ( 11 ) [0068] Since Gk=|G(πmk/M)|2, the minimization of the cost function is performed over all positive values of Gk, as: g opt = arg   min g   ε   G  F  ( g ) ( 12 ) [0069] where:
[0070] A variety of constrained optimization strategies may be used to solve the above equations for gopt. [0071] Once the optimal impulse response gopt and desired spectral response Gd(ω) (which may be expressed as Gd(πmk/M) for a system having M tones) have been determined, a training process is used to adapt the SCISF 90 so that its impulse response g matches the desired spectral response. As shown in FIG. 4, the training process may be generalized as a feedback system. A reference sequence xk is input to the system. This corresponds to inputting a predetermined reference bit sequence to a transmitter. The reference sequence passes through a transmission channel 410 having frequency response H(ƒ) (including the physical transmission channel and the transmit and receive filters). Additive noise ηk from the transmission channel is represented in this general model as an external input 420 to the system. The resulting signal Yk is input to a filter 430 having a frequency response G(ƒ), e.g., a SCISF. The output of the filter 430 is then passed to an adaptation processor 440, which computes an error signal based on the feedback loop 450 and adapts the filter accordingly. The adaptation processor may, for example, use the LMS algorithm described above. [0072] The reference sequence xk is also input to the feedback loop 450, which passes the reference sequence xk through a scaling filter 460 with frequency characteristic Q(ƒ). The frequency characteristic Q(ƒ) of the scaling filter 460 (which may be expressed as a set of frequency domain scaling factors Qk) is determined so that the SCISF adapts to the desired spectral response. The output of the scaling filter 460 is used a reference for the calculation of the error signal in the adaptation processor 440, as described above. [0073] Using the general feedback system shown in FIG. 4, a SCISF having an impulse response g may be trained to minimize the error ∥q*x−x*g*h−η*g∥2. The resulting filter matches P2(ω) in the frequency domain in a least-squares sense, where: P 2  ( ω ) = S x  ( ω )  H * ( ω )  Q  ( ω ) S x  ( ω )   H  ( ω )  2 + S η  ( ω ) , ( 14 ) [0074] Sχ(ω) is the power-spectral density at the input of the system, H(ω) is the frequency response of the effective discrete-time impulse response (EDIR) of the transmission channel, Sη(ω) is the power spectral density of the additive noise, and Q(ω) is the spectral response of the scaling filter 460 having impulse response q. [0075] The solution for gopt in the equations above specifies only the magnitude of the spectral response of the SCISF. If the SCISF is a FIR filter, a linear phase characteristic may be used. If the length of the SCISF is ng, the desired values of G(ω) for the frequency bins of interest are: G d  ( π   M k / M )  Δ =  g opt  ( k )  exp  ( - j   π   M k  ( n g - 1 ) 2   M ) . ( 15 ) [0076] The values Qk are defined by: Q k = G d  ( π   m k / M )  ( S x  ( j   π   k / M )   H  ( j   π   k / M )  2 + S η  ( j   π   k / M ) ) S η  ( j   π   k / M )  H * ( j   π   k / M ) ( 16 ) [0077] The values of Qk may be computed during an initial training period and may be periodically updated during operation of the communication system. [0078] As shown in FIGS. 5, 6A and 6B, the general feedback training process may be used to perform an initial training of a SCISF followed by periodic training analogous to the process described above with respect to FIGS. 1-3. One difference between the techniques is that a scaled reference signal (x*q)k is used rather than an unscaled reference xk. [0079] Referring to FIG. 5, to perform the initial training, a predetermined sequence of bits xk is input to the transmitter. The transmitted signal is filtered and noise-corrupted by the transmission channel, resulting in a received sequence {yk} at the output of the A/D 80 in the receiver. The SCISF 90 filters and transforms the received sequence {yk} into an output sequence {{circumflex over (x)}k}. The output sequence {{circumflex over (x)}k} is compared (in a signal comparator 205) to a scaled reference sequence (x*q)k. [0080] The scaled reference sequence is computed from a copy of the predetermined sequence xk that is stored in memory 210 in the receiver. As a first step, the predetermined sequence is input to a serial to parallel converter 510 and a DFT 515. The resulting frequency domain signal is input to a scaling filter 520 which applies the set of frequency domain scaling factors Qk that causes the SCISF to adapt to the desired spectral response, as discussed above. The scaled signal is input to an inverse discrete Fourier transform 330, a parallel to serial converter 340 and a cyclic prefix adder 350, resulting in a scaled reference sequence (x*q)k. The comparison of the output sequence {{circumflex over (x)}k} to the scaled reference sequence (x*q)k results in an error signal ek that is input to the LMS algorithm processor 215 along with sequence {{circumflex over (x)}k}. Alternatively, a frequency domain reference (e.g., a predetermined bit sequence that has been processed by a serial to parallel converter and DFT) may be stored in memory in the receiver, which would eliminate the need for the serial to parallel converter and discrete Fourier transform in the feedback loop. [0081] Following the initial training, the SCISF is periodically trained during operation of the communication system. A sequence of communication data bits xk is input to the transmitter. Referring to FIG. 6A, the transmitted signal is filtered and noise-corrupted by the transmission channel, resulting in a received sequence {yk} at the output of the A/D 80 in the receiver. The SCISF 90 filters and transforms the received sequence {yk} into an output sequence {{circumflex over (x)}′k}. [0082] The received sequence {yk} is also input to a delay 305 and then to a secondary SCISF 300 that has the same coefficients as the primary SCISF 90 following the initial training. The secondary SCISF 300 provides output sequence {{circumflex over (x)}k}, which is compared to a reference sequence during the periodic training process. Such a configuration allows periodic training to be performed without disruption to the operation of the communication system. The secondary SCISF 300 is periodically or continuously trained using an algorithm similar to that used for the initial training. The new coefficients of the secondary SCISF 300 are periodically copied to the primary SCISF 90. [0083] To compute the reference sequence, the data output of the decoder 140 is input to an encoder 320. The resulting frequency domain signal is input to a scaling filter 520 which applies the set of frequency domain scaling factors Qk that causes the SCISF to adapt to the desired spectral response, as discussed above. The scaled signal is input to an inverse discrete Fourier transform 330, a parallel to serial converter 340 and a cyclic prefix adder 350, resulting in a scaled reference sequence (x*q)k. The comparison of the output sequence {{circumflex over (x)}k} to the scaled reference sequence (x*q)k results in an error signal ek that is input to the LMS algorithm processor 215. The training process determines coefficients for the secondary SCISF 300 so that the output {{circumflex over (x)}k} matches the scaled reference sequence (x*q)k as closely as possible in a least squares sense, i.e., the mean square error between the output and the reference sequence is minimized. Periodically, the coefficients of the secondary SCISF 300 are copied to the primary SCISF 90. [0084] Alternatively, as shown in FIG. 6B, the periodic training may be performed with a single SCISF 90. In this configuration, a received sequence {yk} is output by the A/D 80 in the receiver. The SCISF 90 filters and transforms the received sequence {yk} into an output sequence {{circumflex over (x)}′k}. The received sequence {yk} is also input to a delay. After the received sequence {yk} passes through the SCISF 90, a data switch 360 is changed from position A to position B, allowing the delayed received sequence to make a second pass through the SCISF 90. An output switch 370 also may be opened, so that data is not output during the training process. In addition, the SCISF coefficients are controlled by the LMS algorithm during the training process. [0085] A reference sequence is computed as in the configuration of FIG. 6A. The data output of the decoder 140 is input to an encoder 320. The resulting frequency domain signal is input to a scaling filter 520 which applies the set of frequency domain scaling factors Qk that causes the SCISF to adapt to the desired spectral response, as discussed above. The scaled signal is input to an inverse discrete Fourier transform 330, a parallel to serial converter 340 and a cyclic prefix adder 350, resulting in a scaled reference sequence (x*q)k. The scaled reference sequence is input to the LMS algorithm processor. [0086] The output sequence {{circumflex over (x)}k} of the second pass through the SCISF 90 is compared (in signal comparator 205) to the reference sequence (x*q)k. As noted above, the received sequence {yk} passes through a delay 305 before being input to the SCISF 90 for the second pass. The delay 305 compensates for the processing delay in the demodulation/decoding chain and the encoding/modulation chain. The comparison results in an error signal ek that is input to the LMS algorithm processor 215. The training process determines coefficients for the SCISF 90 so that the output {{circumflex over (x)}k} matches the scaled reference sequence (x*q)k as closely as possible in a least squares sense, i.e., the mean square error between the output and the reference sequence is minimized. The coefficients of the SCISF 90 then are updated to the coefficients determined in the training process. [0087] In a third embodiment, the system dynamically selects the length of the cyclic prefix (CP) to maximize data throughput for a communication channel having a particular noise profile. As discussed above, a CP is added to each symbol prior to transmission through the communication channel to reduce the effects of ISI. However, because the CP constitutes redundant data, increasing the length of the CP reduces the efficiency of the communication system. Hence, to maximize efficiency, the length of the CP must be as short as the noise characteristics of the communication channel permit. [0088] For a DMT communication system with M tones, the maximum sample rate W (samples/second) for a particular channel depends, in part, on the available bandwidth and hardware limitations. The sample rate includes communication data and CP bits. For a CP length of nc, the maximum symbol rate (which includes communication data, but not the CP) is W/(2M+nc). [0089] Before determining the optimal CP length, the SCISF should be initially trained to the channel. However, a communication system need not have a SCISF to employ the CP optimization algorithm. It is noted that the SCISF coefficients determined during the training process do not depend on the CP length. The capacity of the sub-channel may be approximated as log(1+SNRi) bits per second, so the number of bits per symbol is Σilog(1+SNRi). For a CP length of nc, the maximum bit rate is expressed as a function of the cyclic prefix as: B a  ( n c ) = W   ∑ i  log   ( 1 + SNR i ) 2   M + n c ( 17 ) [0090] The optimal CP length is determined by computing the maximum bit rate for a set of candidate values of CP length and finding the length that maximizes Ba(nc). [0091] The signal to noise ratio SNRi of each subchannel is determined by measuring the received signal and noise power and computing the ratio of the two. The noise power γi for the ith bin may be measured by transmitting a data communication sequence and computing the average of the squares of the errors measured at the output of the receiver DFT. The total received power (signal and noise) δi for the ith bin may be measured by computing the average of the squares of the outputs of the receiver DFT. The signal to noise ratio is determined from the expression: δi/γi=1+SNRi. Since the signal to noise ratio is determined in the receiver, the computed bit rate Ba(nc) must be transmitted back to the transmitter. The transmitter compares the bit rate to the values computed for other candidate CP lengths and selects the CP length nc with the highest maximum bit rate Ba(nc). [0092] FIGS. 7A-7D and 8A-8D show performance simulations for test systems based on system parameters and test loops described in VDSL Alliance SDMT VDSL Draft Standard Proposal, Technical report, ANSI, 1998; and Very-high-speed digital subscriber lines: System requirements, T1E1.4/97-131R1, Technical report, ANSI, 1997. The results are for a VDSL system working over test loops 2 and 6 of length 4500 feet in the upstream direction. The system has a sampling frequency of 11.04 MHz. Noise is generated by near-end cross talk from an interfering ADSL and an interfering HDSL and white noise at a level of −140 dBm. The SCISF used in the simulations is length-15 FIR. A version of the Normalized LMS algorithm is used to train the SCISF during an initial training period using a predetermined transmitted sequence. [0093] FIGS. 7A-7D show the simulated system performance for a communication system having the parameters defined for Test Loop 2, which is 4500 feet in length. FIG. 7A shows channel frequency response with and without a SCISF. The SCISF provides a much more uniform frequency response across the frequency band of interest and significantly improves the signal to noise ratio (SNR) in the higher frequency bins. FIG. 7B is a plot of the error signal (10log |{circumflex over (x)}k−xk|) during the training process. The error decreases rapidly during the first few iterations and is nearly converged after only 20-30 iterations. FIG. 7C is a plot of transmitted power spectral density, received power spectral density and the additive noise power spectral density over the used subchannels at the output of the receiver A/D. FIG. 7D is a plot of SNR at the input to the receiver A/D, which is the maximum attainable SNR. The plot also shows the SNR at the output of the receiver DFT without a SCISF and the SNR at the outputs of the receiver DFT using an adapted SCISF. [0094] FIGS. 8A-8D show the simulated system performance for a communication system having the parameters defined for Test Loop 6, which is 4500 feet in length. FIG. 8A shows channel frequency response with and without a SCISF. FIG. 8B is a plot of the error signal (10log |{circumflex over (x)}k−xk|) during the training process. FIG. 8C is a plot of transmitted power spectral density, received power spectral density and the additive noise power spectral density over the used subchannels at the output of the receiver A/D. FIG. 8D is a plot of SNR at the input to the receiver A/D. The plot also shows the SNR at the output of the receiver DFT without a SCISF and the SNR at the outputs of the receiver DFT using an adapted SCISF. [0095] Other embodiments are within the scope of the following claims.
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS6073179 *Jun 30, 1997Jun 6, 2000Integrated Telecom ExpressProgram for controlling DMT based modem using sub-channel selection to achieve scaleable data rate based on available signal processing resources* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS7088787 *Sep 24, 2001Aug 8, 2006Atheros Communications, Inc.Post-FFT scaling to reduce multiple effectsUS7272171 *Jul 31, 2003Sep 18, 2007Aware, Inc.Variable state length initializationUS8102924 *Dec 16, 2004Jan 24, 2012Stmicroelectronics N.V.Arrangements and methods for per tone equalization with reduced complexityUS8102928Sep 25, 2008Jan 24, 2012Tellabs Operations, Inc.Spectrally constrained impulse shortening filter for a discrete multi-tone receiverUS8208520Oct 20, 2010Jun 26, 2012Daphimo Co. B.V., LlcVariable state length initializationUS9014250Dec 28, 2012Apr 21, 2015Tellabs Operations, Inc.Filter for impulse response shortening with additional spectral constraints for multicarrier transmissionUS9191169 *Oct 3, 2013Nov 17, 2015Intel CorporationCommunication device and method for packet-based OFDM communications with differing length cyclic prefixesUS9554319 *Jul 25, 2007Jan 24, 2017Qualcomm IncorporatedChannel handoff methods in wireless broadcast systemsUS20030152021 *Sep 24, 2001Aug 14, 2003Yi-Hsiu WangPost-fft scaling to reduce multiple effectsUS20040022305 *Jul 31, 2003Feb 5, 2004Aware, Inc.Variable state length initializationUS20050135496 *Dec 16, 2004Jun 23, 2005Fabio PisoniArrangements and methods for per tone equalization with reduced complexityUS20070064784 *Dec 18, 2003Mar 22, 2007Dehghan Shirin FCommunication network and method for simulating or designing thereofUS20080020768 *Jul 25, 2007Jan 24, 2008Qualcomm IncorporatedChannel handoff methods in wireless broadcast systemsUS20110032975 *Oct 20, 2010Feb 10, 2011Tzannes Marcos CVariable state length initialization* Cited by examinerClassifications U.S. Classification375/232, 375/260International ClassificationG11B33/12, G11B25/04, H04L25/03Cooperative ClassificationH04L25/03012, H04L2025/03414European ClassificationH04L25/03B1Legal EventsDateCodeEventDescriptionFeb 28, 2008FPAYFee paymentYear of fee payment: 4Mar 10, 2008REMIMaintenance fee reminder mailedDec 28, 2011FPAYFee paymentYear of fee payment: 8Dec 6, 2013ASAssignmentOwner name: CERBERUS BUSINESS FINANCE, LLC, AS COLLATERAL AGENFree format text: SECURITY AGREEMENT;ASSIGNORS:TELLABS OPERATIONS, INC.;TELLABS RESTON, LLC (FORMERLY KNOWN AS TELLABS RESTON, INC.);WICHORUS, LLC (FORMERLY KNOWN AS WICHORUS, INC.);REEL/FRAME:031768/0155Effective date: 20131203Nov 10, 2014ASAssignmentOwner name: TELLABS OPERATIONS, INC., ILLINOISFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:HARIKUMAR, GOPAL;MARCHOK, DANIEL J.;RUDOFSKI, KENNETH;SIGNING DATES FROM 20020726 TO 20020814;REEL/FRAME:034140/0860Nov 26, 2014ASAssignmentOwner name: TELECOM HOLDING PARENT LLC, CALIFORNIAFree format text: ASSIGNMENT FOR SECURITY - - PATENTS;ASSIGNORS:CORIANT OPERATIONS, INC.;TELLABS RESTON, LLC (FORMERLY KNOWN AS TELLABS RESTON, INC.);WICHORUS, LLC (FORMERLY KNOWN AS WICHORUS, INC.);REEL/FRAME:034484/0740Effective date: 20141126Feb 18, 2016FPAYFee paymentYear of fee payment: 12RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services

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Today, will you stand outside your boss’s office hoping that she’ll meet with you about your new project, or will you hunker down in your cube hoping she doesn’t notice you?
Will you raise your hand in class hoping to get some airtime, or will you sit in the back, avoiding it?
Will you track down a recalcitrant customer and see if you can make things better, or will you duck voice mail in case they’re trying to track you down?
It’s possible to spend your entire day mov
Do you really want the grease?
Or would you rather make things better?
The best way to contribute to a community or a brand isn’t by complaining.
It’s by making things better.
Taking responsibility (without authority) and creating a positive cycle of generous action. Leading by example. Finding a small corner where you can make a difference–and then making a difference.
We keep optimizing our systems for squeaky wheels.
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If you’re going to do a presentation (instead of sending a memo)…
If you’re going to do a sales call (instead of staying home)…
it’s because you want to make a change happen. What action are you seeking?
There are two kinds of changes you could work with:
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The rationale for traditional education is that more learning gets you a better job, and a job gets you paid, which makes the learning a worthwhile investment.
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In some organizations, that’s the end of that. You might pick up experience and wisdom on the job, but the short-sighted organization may view ongoing learning as too expensive.
The insight is to realize that stuck employees are far more expensive than educated ones.
It seems more productive to judge tomorrow by something more relevant, useful and in our control than whether or not it’s raining, doesn’t it?
We can judge a day by how many tools we get to use, how many people are open to hearing from us, how many problems are available to be solved.
Weather, or anything else that’s not in our short-term control, can become an excuse and a distraction. If you can’t do anything about it, it might not be worth your focus and energy.
All moths are the same.
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To hedonistic pleasure.
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Over the last few months, I’ve added a few recipes to the pages of this blog, mostly so I have them handy, partly because I haven’t found anything like them online.
If you want insight into the official lunch foods in the office, here you go:
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Principles that we suspend during difficult times aren’t really principles. Principles really count when they’re difficult to maintain.
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“Free speech,” is a fine principle, one to live by. But shouting “fire” in a crowded movie theater isn’t allowed, for good reason.
The edge cases are always subject to endless debate. There are no easy bright lines. It’s tempting, then, to never consider the edg
On Fisherman’s Wharf, there’s one restaurant after another. Is that a smart place to open a business, right next to all the others?
At the bookstore, there are tens of thousands of books, each competing to find a reader.
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The biggest competitor most marketers face is “none.” Inaction always has the biggest market share of all.
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Getting used to the fact that our lines are unique is the first step in figuring out how to engage with people who see things differently.
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Wheat Gluten and Seitan - Bibliography and Sourcebook, A. D. 535 to 1993: Detailed Information on 462 Published Documents (Extensively Annotated Bibliography), 363 Commercial Gluten and Seitan Products, 208 Original Interviews... by William Shurtleff | Barnes & Noble
Wheat Gluten and Seitan - Bibliography and Sourcebook, A. D. 535 to 1993: Detailed Information on 462 Published Documents (Extensively Annotated Bibliography), 363 Commercial Gluten and Seitan Products, 208 Original Interviews... by
William Shurtleff (Compiler),
Akiko Aoyagi (Compiler)
ISBN-13: 9780933332867
Vegetable Proteins Series Format: Spiral BoundPages: 347

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Shared principles in NF-kappaB signaling. - PubMed - NCBI
AbstractFormatSummarySummary (text)AbstractAbstract (text)MEDLINEXMLPMID ListApplySend to:Choose DestinationFileClipboardCollectionsE-mailOrderMy BibliographyCitation managerFormatSummary (text)Abstract (text)MEDLINEXMLPMID ListCSVCreate File1 selected item: 18267068FormatSummarySummary (text)AbstractAbstract (text)MEDLINEXMLPMID ListMeSH and Other DataE-mailSubjectAdditional textE-mailDidn't get the message? Find out why...Add to ClipboardAdd to CollectionsOrder articlesAdd to My BibliographyGenerate a file for use with external citation management software.Create File
See comment in PubMed Commons belowCell. 2008 Feb 8;132(3):344-62. doi: 10.1016/j.cell.2008.01.020.Shared principles in NF-kappaB signaling.Hayden MS1, Ghosh S.Author information1Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06510, USA.AbstractThe transcription factor NF-kappaB has served as a standard for inducible transcription factors for more than 20 years. The numerous stimuli that activate NF-kappaB, and the large number of genes regulated by NF-kappaB, ensure that this transcription factor is still the subject of intense research. Here, we attempt to synthesize some of the basic principles that have emerged from studies of NF-kappaB, and we aim to generate a more unified view of NF-kappaB regulation.PMID: 18267068 [PubMed - indexed for MEDLINE] Free full textSharePublication Types, MeSH Terms, Substances, Grant SupportPublication TypesResearch Support, N.I.H., ExtramuralReviewMeSH TermsAnimalsHumansI-kappa B Kinase/metabolismI-kappa B Proteins/metabolismNF-kappa B/geneticsNF-kappa B/metabolism*Signal Transduction*Transcription, GeneticSubstancesI kappa B beta proteinI-kappa B ProteinsNF-kappa BI-kappa B KinaseGrant SupportAI033443/AI/NIAID NIH HHS/United StatesAI059440/AI/NIAID NIH HHS/United StatesAI066109/AI/NIAID NIH HHS/United StatesAI068977/AI/NIAID NIH HHS/United StatesGM07205/GM/NIGMS NIH HHS/United StatesR01 AI059440/AI/NIAID NIH HHS/United StatesR01 AI066109/AI/NIAID NIH HHS/United StatesR37 AI033443/AI/NIAID NIH HHS/United StatesLinkOut - more resourcesFull Text SourcesElsevier ScienceOther Literature SourcesCOS Scholar UniverseAccess more work from the authors - ResearchGateCited by Patents in - The LensPubMed Commons home

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Emperor of Dawn by Steve White | 2940148670896 | NOOK Book (eBook) | Barnes & Noble
An Empire in DangerThe Empire is in danger, with a weak sybarite on the throne and rebellion rising in outlying regions of the Galaxy and on Earth itself. Then the Emperor is assassinated, and General Ivar Brady-Schiovana is forced to declare himself Emperor. But hope appears in the persons of two men and a woman who are rumored to be legendary heroes. See more details below
Emperor of Dawn available in
An Empire in DangerThe Empire is in danger, with a weak sybarite on the throne and rebellion rising in outlying regions of the Galaxy and on Earth itself. Then the Emperor is assassinated, and General Ivar Brady-Schiovana is forced to declare himself Emperor. But hope appears in the persons of two men and a woman who are rumored to be legendary heroes. At the publisher's request, this title is sold without DRM (Digital Rights Management).
2940148670896
Prince of Sunset Series
Emperor of Dawn 4 out of 5 based on 0 ratings.


text:
Re: [Agile-Orlando] quick ask - please share about Thu session - Agile Orlando (Orlando, FL) | Meetup
Re: [Agile-Orlando] quick ask - please share about Thu session
Sent on: Monday, February 24, 2014 2:57 PM
On Mon, Feb 24, 2014 at 2:31 PM, Mark Kilby <[address removed]> wrote:
Will the attached work?
Mark Kilby agile coach and mentor
Tel: [masked] | http://markkilby.com
co-founder: agileorlando.com | lean coffee Orlando
On Mon, Feb 24, 2014 at 10:08 AM, Sarah <[address removed]> wrote:
Do you have a flyer I can print out and put up at work?
On Mon, Feb 24, 2014 at 8:27 AM, Mark Kilby <[address removed]> wrote:
We have a great presenter and facilitator coming to town this week, but we were a little late getting the notice up. I'd like to make sure everyone knows about this interactive session by Bachan Anand on self-organizing teams.
If you are thinking of attending, please do RSVP as soon as you can. This will make sure we have plenty of food for all. Thanks in advance to our food sponsor LeadingAgile (http://leadingagile.com)
Also, it would be a huge help if you can share with other folks you know in the Orlando area via email, Twitter, LinkedIn, G+, Facebook, etc.
I'll be posting updates daily like the following via social media:
great interactive session on self-organizing teams Thur @agileorlando RSVP for food provided by @leadingagile http://meetu.ps/2cmDR0
Feel free to use it or connect with me to retweet/repeat what I send out.
https://twitter.com/agileorlando
http://www.linkedin.com/in/mkilby
http://google.com/+MarkKilby-FL
Thanks much! Hope to see you this Thursday at Kony for a great session.
co-founder: agileorlando.com | lean coffee Orlando http://twitter.com/agileorlando
This message was sent by Mark Kilby ([address removed]) from Agile Orlando.
To learn more about Mark Kilby, visit his/her member profile
This message was sent by Sarah ([address removed]) from Agile Orlando.
To learn more about Sarah, visit his/her member profile
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Ken Nordquist, Hung, Lakshmi Ramaseshan, Luis Moros, Mark Kilby, Sarah and 6 more
Lean Startup · Agile Transformation · Kanban · Agile Project Management · Scrum · Extreme Programming · Project Management
Agile Orlando is a meetup for Agile practitioners in and around Central Florida to learn about a variety of Agile topics (Scrum, XP, Lean) and discuss how they can be applied to real world scenarios. We're a collaborative group, and want to know what topics you'd like to discuss. Follow us on Twitter to let us know http://twitter.com/agileorlando
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Questions adapted to Grimshaws History of England, continued to the accession of Victoria, in 1837: 9781172104598 - AbeBooks.com
Questions adapted to Grimshaws History of England, continued to the accession of Victoria, in 1837
ISBN 10: 117210459X / ISBN 13: 9781172104598
We're sorry; this specific copy is no longer available. Here are our closest matches for Questions adapted to Grimshaws History of England, continued to the accession of Victoria, in 1837.
Questions adapted to Grimshaws History of England, continued to the accession of Victoria, in 1837. Bookseller Inventory #
Title: Questions adapted to Grimshaws History of ...
1. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 *EBOOK*
Grimshaw, [William]
Book Description 2013. Book Condition: New. ***This is the EBook version (.pdf format) of the 1847 edition. Scanned from the original book !!** You will be receiving the text of this book via download. An email will be sent shortly to your email address containing the download instructions. Refund requests for 'Buyer does not want item' after an ebook has been received will not be accepted. Bookseller Inventory # 119277
2. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 1847
Grimshaw, [William], .
Book Description 2017. Softcover. Book Condition: New. 186 Lang: - eng, Pages 186, Print on Demand. Reprinted in 2017 with the help of original edition published long back [1847]. This book is Printed in black & white, sewing binding for longer life with Matt laminated multi-Colour Soft Cover {HARDCOVER EDITION IS ALSO AVAILABLE}, Printed on high quality Paper, re-sized as per Current standards, professionally processed without changing its contents. As these are old books, we processed each page manually and make them readable but in some cases some pages which are blur or missing or black spots. If it is multi volume set, then it is only single volume. We expect that you will understand our compulsion in these books. We found this book important for the readers who want to know more about our old treasure so we brought it back to the shelves. (Any type of Customisation is possible). Hope you will like it and give your comments and suggestions. Language: eng. Bookseller Inventory # PB1111000499406
3. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 1847
Grimshaw, [William],
Book Description 2016. Softcover. Book Condition: New. 186 Lang: - eng, Pages 186, Print on Demand. Reprinted in 2016 with the help of original edition published long back[1847]. This book is Printed in black & white, sewing binding for longer life with Matt laminated multi-Colour Soft Cover {HARDCOVER EDITION IS ALSO AVAILABLE}, Printed on high quality Paper, re-sized as per Current standards, professionally processed without changing its contents. As these are old books, we processed each page manually and make them readable but in some cases some pages which are blur or missing or black spots. If it is multi volume set, then it is only single volume. We expect that you will understand our compulsion in these books. We found this book important for the readers who want to know more about our old treasure so we brought it back to the shelves. (Any type of Customisation is possible). Hope you will like it and give your comments and suggestions. Language: eng. Bookseller Inventory # PB1111005127082
4. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 (1847)
Book Description ReInk Books, 2017. Softcover. Book Condition: NEW. Reprinted from 1847 edition. Language: eng. NO changes have been made to the original text. This is NOT a retyped or an ocr'd reprint. Illustrations, Index, if any, are included in black and white. Each page is checked manually before printing. As this reprint is from very old book, there could be some missing or flawed pages, but we always try to make the book as complete as possible. Fold-outs, if any, are not part of the book. If the original book was published in multiple volumes then this reprint is of only one volume, not the whole set. This paperback book is SEWN, where the book block is actually sewn (smythe sewn/section sewn) with thread before binding which results in a more durable type of paperback binding. It can also be open wide. The pages will not fall out and will be around for a lot longer than normal paperbacks. This print on demand book is printed on high quality acid-free paper. Original Publisher: Philadelphia, Grigg. Elliot & co. 186 pages. Bookseller Inventory # 451698780
5. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837. 1847 [Ebook PDF]
Book Description 2017. Ebook. Book Condition: New. eng Lang:- eng, It is an Ebook edition of the original edition published long back [1847]. We found this book important for the readers who want to know about our old treasure so we brought it back in ebook (pdf) format. These are scanned images of the original book in pdf format. We provide you the best available ebook for your ebook shelf. Once you place the order, you will receive a link to download the pdf file. An email will be sent shortly to your email address containing the download instructions. This is an Ebook. All sales final unless there is illegibility to text. Bookseller Inventory # HT00003956769
6. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 1847 [Hardcover]
Book Description 2017. Hardcover. Book Condition: New. 186 Lang: - eng, Pages 186, Print on Demand. Reprinted in 2017 with the help of original edition published long back [1847]. This book is Printed in black & white, Hardcover, sewing binding for longer life with Matt laminated multi-Colour Dust Cover, Printed on high quality Paper, re-sized as per Current standards, professionally processed without changing its contents. As these are old books, we processed each page manually and make them readable but in some cases some pages which are blur or missing or black spots. If it is multi volume set, then it is only single volume. We expect that you will understand our compulsion in these books. We found this book important for the readers who want to know more about our old treasure so we brought it back to the shelves. (Any type of Customisation is possible). Hope you will like it and give your comments and suggestions. Language: eng. Bookseller Inventory # 1111000499406
7. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 1847 [Hardcover]
Book Description 2016. Hardcover. Book Condition: New. 186 Lang: - eng, Pages 186, Print on Demand. Reprinted in 2016 with the help of original edition published long back[1847]. This book is Printed in black & white, Hardcover, sewing binding for longer life with Matt laminated multi-Colour Dust Cover, Printed on high quality Paper, re-sized as per Current standards, professionally processed without changing its contents. As these are old books, we processed each page manually and make them readable but in some cases some pages which are blur or missing or black spots. If it is multi volume set, then it is only single volume. We expect that you will understand our compulsion in these books. We found this book important for the readers who want to know more about our old treasure so we brought it back to the shelves. (Any type of Customisation is possible). Hope you will like it and give your comments and suggestions. Language: eng. Bookseller Inventory # 1111005127082
8. Questions Adapted to Grimshaw's History of England, Continued to the Accession of Victoria, in 1837 (Classic Reprint)
ISBN 10: 133078555X ISBN 13: 9781330785553
Book Description Forgotten Books, 2015. Book Condition: New. This item is printed on demand for shipment within 3 working days. Bookseller Inventory # LP9781330785553
9. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 1847 [Leather Bound]
Book Description 2017. Leather Bound. Book Condition: New. 186 Leather Binding on Spine and Corners with Golden Leaf Printing on round Spine (extra customization on request like complete leather, Golden Screen printing in Front, Color Leather, Colored book etc.) Reprinted in 2017 with the help of original edition published long back [1847]. This book is printed in black & white, sewing binding for longer life, Printed on high quality Paper, re-sized as per Current standards, professionally processed without changing its contents. As these are old books, we processed each page manually and make them readable but in some cases some pages which are blur or missing or black spots. If it is multi volume set, then it is only single volume. We expect that you will understand our compulsion in these books. We found this book important for the readers who want to know more about our old treasure so we brought it back to the shelves. Hope you will like it and give your comments and suggestions. Lang: - eng, Pages 186, Print on Demand. EXTRA 10 DAYS APART FROM THE NORMAL SHIPPING PERIOD WILL BE REQUIRED FOR LEATHER BOUND BOOKS. COMPLETE LEATHER WILL COST YOU EXTRA US$ 70 APART FROM THE LEATHER BOUND BOOKS. Language: eng. Bookseller Inventory # LB11000499406
10. Questions adapted to Grimshaw's History of England, continued to the accession of Victoria, in 1837 1847 [Leather Bound]
Grimshaw, [William], -. [from old catalog]
Book Description 2017. Leather Bound. Book Condition: New. 186 Leather Binding on Spine and Corners with Golden Leaf Printing on round Spine (extra customization on request like complete leather, Golden Screen printing in Front, Color Leather, Colored book etc.) Reprinted in 2017 with the help of original edition published long back [1847]. This book is printed in black & white, sewing binding for longer life, Printed on high quality Paper, re-sized as per Current standards, professionally processed without changing its contents. As these are old books, we processed each page manually and make them readable but in some cases some pages which are blur or missing or black spots. If it is multi volume set, then it is only single volume. We expect that you will understand our compulsion in these books. We found this book important for the readers who want to know more about our old treasure so we brought it back to the shelves. Hope you will like it and give your comments and suggestions. Lang: - eng, Pages 186, Print on Demand. EXTRA 10 DAYS APART FROM THE NORMAL SHIPPING PERIOD WILL BE REQUIRED FOR LEATHER BOUND BOOKS. COMPLETE LEATHER WILL COST YOU EXTRA US$ 70 APART FROM THE LEATHER BOUND BOOKS. Language: eng. Bookseller Inventory # LB11005127082

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Revision as of 17:11, 16 August 2012 by Martinvi (talk | contribs) (ofsp)
Retrieved from "https://www.familysearch.org/wiki/en/index.php?title=Alabama,_County_Marriages_(FamilySearch_Historical_Records)&oldid=1092327"

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Amazon.co.uk: Customer Reviews: Rumpelstiltskin (Matthew Hope)
4.0 out of 5 stars Spinning a Yarn
The second of McBain's Matthew Hope mysteries (the first was "Goldilocks"), following the career of the Florida lawyer. McBain provides a distinctly contemporary take on fairy tales, this time in the form of a faded rock star whose fragile voice had once been turned from pure chaff into purest gold.Matthew leaves her bed one night, and leaves her to the mercies of...
Read the full review › Published on 26 Feb 2004 by Budge Burgess
3.0 out of 5 stars The dwarf.
A well developed plot but with a predictable culprit and end.I also found Matthew Hopes love interest a boor.
Published 3 months ago by Patricia Morris Jones
4.0 out of 5 stars Spinning a Yarn, 26 Feb 2004
The second of McBain's Matthew Hope mysteries (the first was "Goldilocks"), following the career of the Florida lawyer. McBain provides a distinctly contemporary take on fairy tales, this time in the form of a faded rock star whose fragile voice had once been turned from pure chaff into purest gold.Matthew leaves her bed one night, and leaves her to the mercies of a murderer who brutally silences her then kidnaps her child. Is this an opportunistic kidnapping? Or is there a more sinister element tied to a trust fund set up for the singer?McBain again explores the angst of divorce and separation from one's children, with telling passages on the trials and tribulations of the single male parent trying to cope with the demands of a teenage daughter (I speak as the father of girls myself).The Matthew Hope mysteries are well-crafted, beautifully written whodunnits: they are also exploratons of male sexuality and relationships; and the pace is regulated by moments of wry humour, philosophical insights ... and a discourse on the colour of pubic hair.A fine page-turner of a book - elegant, satisfying, a good example of the craftsman at work.
4.0 out of 5 stars McBain spins a fresh yarn, 22 Oct 2004
By V Collins - See all my reviews
3.0 out of 5 stars The dwarf., 31 May 2014
3.0 out of 5 stars OK, 17 Mar 2014
3.0 out of 5 stars An easy read, 12 Jan 2014
Easy to get through but not that sophisticated when it comes to the writing. Good if you`'re not after too much to think about.
5.0 out of 5 stars I loved it, 12 Jan 2014
Ist Ed McBain Ive ever read but wont be the last. Excellent storyline. Would reccommend anyone intersted in crime stories to read this one
5.0 out of 5 stars RUMPLESTILTSKIN, 28 Dec 2013
By MAMMAKIZ - See all my reviews
Really good with twists and turns. Looking out for clues that would link to original story.Would recommend to any one who likes crime thrillers, Hitchcock, etc.
4.0 out of 5 stars this series not up to standard of 87th precinct, 11 Dec 2013
Rumpelstiltskin (Matthew Hope) by Ed McBain


text:
Search results for Map, Michigan, Available Online, History, County Landownership Maps, Cultural Landscapes, Genesee County, Directories, United States, Image | Library of Congress
Results: 1-1 of 1 | Refined by: Original Format: Map Remove Available Online Remove Subject: History Remove Part of: County Landownership Maps Remove Part of: Cultural Landscapes Remove Location: Genesee County Remove Subject: Directories Remove Subject: United States Remove Online Format: Image Remove

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