Embodiments of the invention generally pertain to the field of communication systems and, more particularly, to impulse noise detection in multi-carrier communication systems.
There are various types of interference and noise sources in a multi-carrier communication system, such as a Discrete Multiple-Tone (DMT) system. Interference and noise may corrupt the data-bearing signal on a tone as the signal travels through the communication channel and is decoded at the receiver. The transmitted data-bearing signal may be decoded erroneously by the receiver because of this signal corruption. The number of data bits or the amount of information that a tone carries may vary from tone to tone and depends on the relative power of the data-bearing signal compared to the power of the corrupting signal on that particular tone.
In order to account for potential interference on the transmission line and to guarantee a reliable communication between the transmitter and receiver, each tone of a DMT system is typically designed to carry a limited number of data bits per unit time based on the tone's Signal to Noise Ratio (SNR) using a bit-loading algorithm, which is an algorithm to determine the number of bits per tone. The number of bits that a specific tone may carry decreases as the relative strength of the corrupting signal increases, that is when the SNR is low. Thus, the SNR of a tone may be used to determine how much data should be transmitted by the tone to achieve a target bit error rate.
It is often assumed that the corrupting signal is an additive random source with Gaussian distribution and white spectrum. With this assumption, the number of data bits that each tone can carry relates directly to the SNR. However, this assumption may not be true in many practical cases where there might exist various sources of interference that do not have a white, Gaussian distribution. Impulse noise is one such noise source. Bit-loading algorithms are usually designed based on the assumption of additive, white, Gaussian noise. With such algorithms, the effects of impulse noise can be underestimated, resulting in aggressive bit loading and, consequently, an excessive rate of error.
Further, channel estimation procedures that can be designed to optimize performance in the presence of stationary impairments such as additive, white, Gaussian noise, but are often poor at estimating non-stationary or cyclo-stationary impairments, such as impulse noise. Consequently, Digital Subscriber Line (DSL) modem training procedures are typically well suited to optimizing performance in the presence of additive, white, Gaussian noise, but leave the modem receivers relatively defenseless to impulse noise.
Impulse Noise can be a difficult impairment for DSL modems. Impulse noise with duration of tens of microseconds can cause errors in all the used tones at the receiver. Further, impulse noise can have power bursts that are much higher than the background noise level causing significant performance loss. These power bursts can have a very small duty cycle, such that they do not contribute significantly to average noise power. This can result in aggressive bit loading on some or all tones in a DMT system, resulting in an excessively high bit error rate. It is thus desirable to detect the presence of and mitigate the impact of impulse noise in Asymmetric DSL (ADSL) and Very high bit-rate DSL (VDSL) and other communications systems.
Methods and apparatuses for detecting impulse noise in a DSL communication system are described.
According to certain embodiments, the method applies to systems where a coding scheme such as Trellis Coded modulation is employed at the transmitter. The receiver decodes the received data sequence using a hard decision decoder as well as a soft decision decoder. The results of these two decoders are compared. The presence of impulse noise is detected based on a lack of agreement between the hard decision output and the soft decision output.
Other aspects of the invention will be apparent from the accompanying figures and from the detailed description that follows.
One or more embodiments of the present invention are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements and in which:
In general, methods and apparatuses for detecting presence of impulse noise in a communication system are discussed. According to certain embodiments, the method includes comparing a hard decision output of a decoder with a soft decision output for a convolution coded modulation symbol received at a digital subscriber line (DSL) receiver. The presence of impulse noise is detected based on a lack of agreement between the hard decision output and the soft decision output.
According to certain embodiments of the invention, an impulse noise detection method includes utilizing already existing coding in the communication system. Many modern variants of Digital Subscriber Line (DSL) systems, such as ADSL and VDSL, use codes, such as convolution codes, to improve performance. Convolution codes, such as trellis codes, are typically used to encode digital data before transmission through noisy or error-prone channels. Further, according to certain embodiments of the invention, a DSL modem takes advantage of certain properties of coded modulation, such as Trellis Coded Modulation (TCM), to determine where symbol errors due to impulse noise are most likely to have occurred. This information can be used to determine the presence of impulse noise.
TCM is a modulation scheme that allows for efficient transmission of information used by many modern ADSL/VDSL systems over bandwidth-limited channels such as telephone lines. A typical TCM scheme involves the mapping of an encoder output directly to a point on a signal constellation, such as an 8-QAM constellation. The combination of the encoding and mapping elements is jointly optimized so as to obtain good error performance. For example, an encoder could take two bits as input and have a three-bit output that is mapped to an 8-QAM constellation. In such a case, the encoder would be said to encode at a ⅔ rate, that is, two inputs bits produce three encoded output bits. When the trellis coded signal is received and decoded by the system receiver, each branch of the trellis corresponds to one 8-QAM symbol, which facilitates soft decision decoding.
A DSL system 100 (e.g., ADSL or VDSL) may use a multi-tone system for transmission of information from a transmitter to a receiver over a number of tones. An example of a multi-tone communication system is a Discrete Multiple-Tone (DMT) system.
DMT communication systems use a modulation method in which the available bandwidth of a communication channel, such as twisted-pair copper media, is divided into these numerous tones. The term communication channel is understood to refer generally to a physical transmission medium, including copper, optical fiber, and so forth, as well as other transmission mediums, including radio frequency (RF) and other physical or non-physical communication signal paths.
The QAM/TCM Encoder 216 is designed so as to introduce an element of redundancy into the information sequence that is supplied by the Source Encoder 212 to generate a coded output. While initially appearing at odds with the function of the Source Encoder 212, in reality the redundancy added by the QAM/TCM Encoder 216 serves to enhance the error correction capability of the communication system. By introducing redundant information into the information sequence in a controlled manner, a receiver having knowledge of the codes used can decode without error data sequences that would be decoded with a high rate of error if the receiver were unable to make use of the redundant information. The particular QAM/TCM Encoder 216 produces “n+1” output bits for each “n” input bits. These output bits are mapped to constellation points differently than in an un-coded DMT system.
More generally, for TCM encoding, given Ki bits to encode for P-dimensional (e.g., 2D, 4D, etc.) symbol i, N bits are reserved for coset selection, and (Ki minus N) bits are used to select a point within the chosen coset. The P-dimensional constellations are divided into 2N sub-constellations called cosets. These cosets have much greater intra-coset distance than the original constellation. There will be N encoder output bits dedicated to selection of the coset, and these bits are the ones that are directly involved with the encoder state machine.
A point within the chosen coset is selected using the remaining (Ki minus P) bits left over from the first stage encoding process. The coset selection bits have two distinct properties that the other (Ki minus P) bits do not have: there is correlation from symbol to symbol created by the encoder state machine memory, and there is redundant information in these four bits also generated by the state machine. The transmitter output can be thought of as a sequence of cosets, this sequence constrained by the encoder such that not all possible sequences of cosets are allowed.
Considering an ADSL modem as an example, a trellis code may be used for coding. An example of a trellis code that may be used in an ADSL modem is a 16 state, 4 dimensional Wei code. This means that the DMT frame is organized such that carriers are encoded as pairs. Accordingly, there are 2 dimensions each for 2 carriers, yielding 4 dimensions total per symbol. A symbol is a unique signal state of a modulation scheme used on a transmission link that conveys one or more information bits to the receiver.
The encoder outputs a sequence of bits to a Constellation Mapper contained within the QAM/TCM Encoder 216. This Constellation Mapper converts a number represented by a group of bits to a point in 4-dimensional space. In a 4-dimensional scheme, such as that used for many DSL modems, the Constellation Mapper actually maps two groups of bits into 2, 2-dimensional points. Taken together, these two points are treated as a single 4-dimensional point. The set of all possible points is known as a “Constellation”. Typical signal constellations used in digital communications system modulation include 16 QAM, 8-PSK, 4-PSK and the like.
The Analog Processor 218 interfaces the combination QAM/TCM Encoder 216 and IFFT 218 to the communications channel 224, such as telephone wires. The Analog Processor 218 performs modulation to generate waveforms that both suit the physical nature of the channel 224 and can be efficiently transmitted over the channel 224. These output waveforms are generally selected with regard to either simplification of the communication system, detection performance, power requirements, or bandwidth availability.
The DMT Receiver 250 of the digital communications system 200 processes the received waveform (which may be corrupted by impulse noise during transmission) for any given symbol to determine which of the possible points in the signal constellation was transmitted. When the transmitted sequence includes redundancy introduced by channel coding, the DMT Receiver 250 invokes a TCM Decoder 250 that attempts to reconstruct the original information sequence from its a priori knowledge of the code used by the TCM coder 216.
At a first stage of decoding the Trellis Decoder 304 may use the Viterbi algorithm to decide which one of 2N, P-Dimensional Cosets were sent. For instance, for a 4-Dimensional trellis code, the Trellis Decoder 304 may decide which one of eight, 4-Dimensional (4D) Cosets were sent. Specifically, the Trellis Decoder 304 may determine the distance from the received 4D point to the nearest point within each of the 8 cosets. This yields 8 coset decisions 306 with 8 distances. The best (smallest distance) coset from the eight is selected and recorded. This result is equivalent to the best slicer output produced by the hard decision slicer in an uncoded system.
At a second stage of decoding, the Trellis decoder 304 uses the hard slicer output data in conjunction with knowledge of the code (allowed coset sequences) to determine which of the allowed sequences of cosets is the best match to the received sequence. The results are called Soft Decisions 308.
The best coset choice from the first stage process is compared to the corresponding coset choice in the best sequence selected by the second stage decoder. As shown in
The indicators can also be used to detect presence of narrow band impulse noise having a noise bandwidth that is narrower than the DMT system bandwidth. The indicators can be looked at on a 4D symbol basis and associated with specific tones. If the indicators show errors consistently for some tones and not others, then the prediction can be made that narrow band interference is present.
According to certain embodiments, parameters of the impulse noise, such as the periodicity and tone location information of the impulse noise, can be sent to the DSL transmitter, so that it can reduce or eliminate data payload in frames and tones where the impulse noise is detected. This reduces or eliminates the need for retransmission of corrupted data.
The example shown in
The frequency with which a given symbol is “rescued” by the trellis decoder can be used in locating unreliable symbols. The impulse noise detection system 300 can be used to identify DMT frames that are suspected to have been corrupted by impulse noise. Further, the impulse noise detection system 300 can also be used to pinpoint specific carriers within a frame that are likely to be plagued by decoder errors. Additionally, information from this error location technique can be used to locate troublesome carriers in DMT systems that are operating at excessively high error rates. These carriers can then be optimized via one of several on-line procedures such as Dynamic Rate Adaptation or Bit Swapping to reduce error rates to acceptable levels.
Impulse noise detection methods discussed herein can also be very beneficial for flagging erasures to improve the performance of a Reed Solomon (RS) decoder in the modem receiver. For instance, an erasure indicator for systems employing erasure decoding can be implemented. Erasure decoding is a scheme that is sometimes used to extend the error correction capability of RS decoding. For instance, for a RS codeword consisting of 255 bytes total, and K redundant bytes, the decoder is capable of correcting up to K/2 errored bytes distributed randomly in the 255-byte RS codeword. However, if there is some means of identifying the errored bytes to the decoder, then the decoder is capable of correcting up to K known errored bytes. An errored byte is one that contains one or more bit errors. Impulse noise detection methods discussed herein can be used to help locate errored bytes, thus improving the performance of the RS decoder.
An exemplary implementation is illustrated in
Thus, methods and apparatus for detecting impulse noise in a multi-tone communication system by taking advantage of the basic properties of coded modulation have been described. The impulse noise detection methods described herein can perform as well as other techniques with much lower complexity, requiring only the addition of a hard decision process. Other techniques require the addition of considerable hardware and/or software because of the added computational burden. No knowledge of the constellation is required as it operates on the P-Dimensional cosets, which are already understood by the trellis decoder apparatus. Furthermore, the methods discussed herein are able to detect and distinguish the difference between narrow band and broadband noise, which can be useful in systems employing erasure decoding, because the number of erasures is reduced by not always erasing an entire DMT Frame, but rather just the symbols within the frame which are deemed unreliable by this method.
Thus, a method and apparatus for detecting impulse noise have been described. As part of the process of decoding in a coded system (such as a system employing trellis code), the decoder makes P-Dimensional coset hard decisions and soft decisions. The assumption may be made that if the system is operating with enough noise margin, the hard decisions and the soft decisions will disagree only once for every million symbols or so. When the actual noise increases beyond the allocated noise margin, as can happen in the presence of impulse noise, the soft decisions and hard decisions will tend to disagree more often. Hence, impulse noise can be detected by monitoring the difference between soft decisions and the hard decisions.
The detection and mitigation of the impulse noise may use various features of the ADSL, ADSL2, and VDSL specifications. Note that references throughout this specification to “one embodiment” or “an embodiment” or “certain embodiments” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment” or “one embodiment” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics being referred to may be combined as suitable in one or more embodiments of the invention, as will be recognized by those of ordinary skill in the art.
The detailed description above includes several modules. These modules may be implemented by hardware components, such as logic, or may be embodied in machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with the instructions to perform the operations described herein. Alternatively, the operations may be performed by a combination of hardware and software. In one embodiment, the software used to facilitate the impulse noise mitigation can be embodied onto a machine-readable storage medium. A machine-readable storage medium includes any mechanism that provides (e.g., stores and/or transmits) information in a form readable by a machine (e.g., a computer). For example, a machine-readable medium includes read only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; DVD's, electrical, optical, acoustical or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, EPROMs, EEPROMs, FLASH, magnetic or optical cards, or any type of media suitable for storing electronic instructions. The information representing the apparatuses and/or methods stored on the machine-readable medium may be used in the process of creating the apparatuses and/or methods described herein.
Although the present invention has been described with reference to specific exemplary embodiments, it will be recognized that the invention is not limited to the embodiments described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. Accordingly, the specification and drawings are to be regarded in an illustrative sense rather than a restrictive sense.
Number | Name | Date | Kind |
---|---|---|---|
4024359 | De Marco et al. | May 1977 | A |
4024360 | Biraghi et al. | May 1977 | A |
4173714 | Bloch et al. | Nov 1979 | A |
4384355 | Werner | May 1983 | A |
4679227 | Hughes-Hartogs | Jul 1987 | A |
4733389 | Puvogel | Mar 1988 | A |
4845466 | Hariton et al. | Jul 1989 | A |
4882733 | Tanner | Nov 1989 | A |
4977591 | Chen et al. | Dec 1990 | A |
5285474 | Chow et al. | Feb 1994 | A |
5304940 | Harasawa et al. | Apr 1994 | A |
5483551 | Huang et al. | Jan 1996 | A |
5524125 | Tsujimoto | Jun 1996 | A |
5555274 | Sheets | Sep 1996 | A |
5559890 | Obermeier et al. | Sep 1996 | A |
5596258 | Kimura et al. | Jan 1997 | A |
5596439 | Dankberg et al. | Jan 1997 | A |
5627859 | Parr | May 1997 | A |
5703904 | Langberg | Dec 1997 | A |
5768473 | Eatwell et al. | Jun 1998 | A |
5815538 | Grell et al. | Sep 1998 | A |
5818872 | Gupta | Oct 1998 | A |
5844940 | Goodson et al. | Dec 1998 | A |
5852630 | Langberg et al. | Dec 1998 | A |
5867539 | Koslov | Feb 1999 | A |
5901205 | Smith et al. | May 1999 | A |
5909178 | Balch et al. | Jun 1999 | A |
5930268 | Kurby et al. | Jul 1999 | A |
5952914 | Wynn | Sep 1999 | A |
5974098 | Tsuda | Oct 1999 | A |
5978373 | Hoff et al. | Nov 1999 | A |
6006083 | Tong et al. | Dec 1999 | A |
6014376 | Abreu et al. | Jan 2000 | A |
6052420 | Yeap et al. | Apr 2000 | A |
6118769 | Pries et al. | Sep 2000 | A |
6147963 | Walker et al. | Nov 2000 | A |
6161209 | Moher | Dec 2000 | A |
6185429 | Gehrke et al. | Feb 2001 | B1 |
6205220 | Jacobsen et al. | Mar 2001 | B1 |
6205410 | Cai | Mar 2001 | B1 |
6212227 | Ko et al. | Apr 2001 | B1 |
6226322 | Mukherjee | May 2001 | B1 |
6256326 | Kudo | Jul 2001 | B1 |
6266347 | Amrany et al. | Jul 2001 | B1 |
6266422 | Ikeda | Jul 2001 | B1 |
6295323 | Gabara | Sep 2001 | B1 |
6345071 | Hamdi | Feb 2002 | B1 |
6351509 | Vitenberg et al. | Feb 2002 | B1 |
6359926 | Isaksson | Mar 2002 | B1 |
6363109 | Polley et al. | Mar 2002 | B1 |
6378234 | Luo | Apr 2002 | B1 |
6411657 | Verbin et al. | Jun 2002 | B1 |
6433819 | Li et al. | Aug 2002 | B1 |
6445773 | Liang et al. | Sep 2002 | B1 |
6456673 | Wiese et al. | Sep 2002 | B1 |
6459739 | Vitenberg | Oct 2002 | B1 |
6466588 | Michaels | Oct 2002 | B1 |
6493395 | Isaksson et al. | Dec 2002 | B1 |
6498808 | Tzannes | Dec 2002 | B1 |
6507608 | Norrell | Jan 2003 | B1 |
6519291 | Dagdeviren et al. | Feb 2003 | B1 |
6542028 | Norrell et al. | Apr 2003 | B1 |
6546025 | Dupuy | Apr 2003 | B1 |
6556635 | Dehghan | Apr 2003 | B1 |
6597732 | Dowling | Jul 2003 | B1 |
6621346 | Nabicht et al. | Sep 2003 | B1 |
6631175 | Harikumar et al. | Oct 2003 | B2 |
6633545 | Milbrandt | Oct 2003 | B1 |
6674795 | Liu et al. | Jan 2004 | B1 |
6690666 | Norrell et al. | Feb 2004 | B1 |
6721394 | Murphy et al. | Apr 2004 | B1 |
6731914 | Creigh et al. | May 2004 | B2 |
6738418 | Stiscia et al. | May 2004 | B1 |
6754170 | Ward | Jun 2004 | B1 |
6763061 | Strait et al. | Jul 2004 | B1 |
6775241 | Levin | Aug 2004 | B1 |
6791995 | Azenkot et al. | Sep 2004 | B1 |
6798735 | Tzannes et al. | Sep 2004 | B1 |
6822998 | Yun et al. | Nov 2004 | B1 |
6826404 | Delfs et al. | Nov 2004 | B2 |
6839429 | Gaikwad et al. | Jan 2005 | B1 |
6859488 | Azenkot et al. | Feb 2005 | B2 |
6871066 | Khullar et al. | Mar 2005 | B1 |
6898236 | Sun | May 2005 | B1 |
6940973 | Yeap et al. | Sep 2005 | B1 |
6965636 | DesJardins et al. | Nov 2005 | B1 |
6999504 | Amrany et al. | Feb 2006 | B1 |
6999507 | Jin | Feb 2006 | B2 |
7023910 | Norrell | Apr 2006 | B1 |
7031669 | Vaidyanathan et al. | Apr 2006 | B2 |
7035661 | Yun | Apr 2006 | B1 |
7085315 | Kelton | Aug 2006 | B1 |
7085539 | Furman | Aug 2006 | B2 |
7120211 | Shmulyian et al. | Oct 2006 | B2 |
7155007 | Upton | Dec 2006 | B1 |
7174022 | Zhang et al. | Feb 2007 | B1 |
7177419 | Sedarat et al. | Feb 2007 | B2 |
7184467 | Jacobsen et al. | Feb 2007 | B2 |
7200196 | Li et al. | Apr 2007 | B2 |
7215727 | Yousef et al. | May 2007 | B2 |
7221722 | Thomas et al. | May 2007 | B2 |
7283509 | Moon et al. | Oct 2007 | B2 |
7302379 | Cioffi et al. | Nov 2007 | B2 |
7315592 | Tsatsanis et al. | Jan 2008 | B2 |
7315967 | Azenko et al. | Jan 2008 | B2 |
7330544 | D'Angelo et al. | Feb 2008 | B2 |
7356049 | Rezvani | Apr 2008 | B1 |
7366258 | Kolze et al. | Apr 2008 | B2 |
7369607 | Sedarat | May 2008 | B2 |
7421015 | Sedarat | Sep 2008 | B2 |
7433395 | Sedarat | Oct 2008 | B2 |
7443916 | Sedarat et al. | Oct 2008 | B2 |
7502336 | Romano et al. | May 2009 | B2 |
7529984 | Heise | May 2009 | B2 |
7555037 | Sedarat | Jun 2009 | B2 |
20010009850 | Kushige | Jul 2001 | A1 |
20010011019 | Jokimies | Aug 2001 | A1 |
20010055332 | Sadjadpour et al. | Dec 2001 | A1 |
20020001340 | Shenoi et al. | Jan 2002 | A1 |
20020044597 | Shively et al. | Apr 2002 | A1 |
20020057713 | Bagchi et al. | May 2002 | A1 |
20020078247 | Lu et al. | Jun 2002 | A1 |
20020122515 | Bodenschatz | Sep 2002 | A1 |
20020154620 | Azenkot et al. | Oct 2002 | A1 |
20020163959 | Haddad | Nov 2002 | A1 |
20030021240 | Moon et al. | Jan 2003 | A1 |
20030035469 | Frank et al. | Feb 2003 | A1 |
20030043925 | Stopler et al. | Mar 2003 | A1 |
20030048368 | Bosco et al. | Mar 2003 | A1 |
20030055996 | Mori et al. | Mar 2003 | A1 |
20030091053 | Tzannes et al. | May 2003 | A1 |
20030099285 | Graziano et al. | May 2003 | A1 |
20030099286 | Graziano et al. | May 2003 | A1 |
20030099350 | Bostoen et al. | May 2003 | A1 |
20030108094 | Lai et al. | Jun 2003 | A1 |
20030112860 | Erdogan | Jun 2003 | A1 |
20030124983 | Parssinen et al. | Jul 2003 | A1 |
20030185176 | Lusky et al. | Oct 2003 | A1 |
20030206579 | Bryant | Nov 2003 | A1 |
20030227967 | Wang et al. | Dec 2003 | A1 |
20040057502 | Azenkot et al. | Mar 2004 | A1 |
20040066865 | Yousef et al. | Apr 2004 | A1 |
20040071240 | Betts | Apr 2004 | A1 |
20040087278 | Lin et al. | May 2004 | A1 |
20040091025 | Sindhushayana et al. | May 2004 | A1 |
20040111345 | Chuang et al. | Jun 2004 | A1 |
20040141548 | Shattil | Jul 2004 | A1 |
20040156441 | Peeters et al. | Aug 2004 | A1 |
20040176063 | Choi | Sep 2004 | A1 |
20040185852 | Son et al. | Sep 2004 | A1 |
20040213170 | Bremer | Oct 2004 | A1 |
20040223449 | Tsuie et al. | Nov 2004 | A1 |
20050041753 | Cunningham | Feb 2005 | A1 |
20050047489 | Yousef et al. | Mar 2005 | A1 |
20050047514 | Bolinth et al. | Mar 2005 | A1 |
20050053229 | Tsatsanis et al. | Mar 2005 | A1 |
20050094550 | Huh et al. | May 2005 | A1 |
20050099967 | Baba | May 2005 | A1 |
20050111561 | Sedarat et al. | May 2005 | A1 |
20050143008 | Bailey | Jun 2005 | A1 |
20050159128 | Collins et al. | Jul 2005 | A1 |
20050169357 | Sedarat | Aug 2005 | A1 |
20050190825 | Sedarat | Sep 2005 | A1 |
20050190848 | Kiyanagii et al. | Sep 2005 | A1 |
20050190871 | Sedarat | Sep 2005 | A1 |
20050216441 | Thomas et al. | Sep 2005 | A1 |
20050271129 | Reina | Dec 2005 | A1 |
20050276355 | Chow et al. | Dec 2005 | A1 |
20060002457 | Romano et al. | Jan 2006 | A1 |
20060019687 | Garg et al. | Jan 2006 | A1 |
20060039550 | Chadha et al. | Feb 2006 | A1 |
20060062379 | Sedarat et al. | Mar 2006 | A1 |
20060067388 | Sedarat et al. | Mar 2006 | A1 |
20060078044 | Norrell et al. | Apr 2006 | A1 |
20060083321 | Sedarat | Apr 2006 | A1 |
20060083322 | DesJardins et al. | Apr 2006 | A1 |
20060083323 | DesJardins et al. | Apr 2006 | A1 |
20060083324 | DesJardins et al. | Apr 2006 | A1 |
20060115030 | Erving et al. | Jun 2006 | A1 |
20060126747 | Wiese | Jun 2006 | A1 |
20060171480 | Erving et al. | Aug 2006 | A1 |
20060193390 | Sedarat | Aug 2006 | A1 |
20060203843 | Liu | Sep 2006 | A1 |
20060227913 | Sedarat | Oct 2006 | A1 |
20060291537 | Fullerton et al. | Dec 2006 | A1 |
20070002940 | Zhou | Jan 2007 | A1 |
20070217492 | Cox et al. | Sep 2007 | A1 |
Number | Date | Country |
---|---|---|
0 377 965 | Jul 1989 | EP |
0844758 | May 1998 | EP |
0 966 134 | Dec 1999 | EP |
1 389 846 | Feb 2004 | EP |
1388944 | Feb 2004 | EP |
1389846 | Feb 2004 | EP |
WO 2006042274 | Apr 2006 | WO |
Number | Date | Country | |
---|---|---|---|
20070183526 A1 | Aug 2007 | US |