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WO1996035157A1 - Procede et systeme de demodulation d'un signal m-aire - Google Patents

Procede et systeme de demodulation d'un signal m-aire Download PDF

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Publication number
WO1996035157A1
WO1996035157A1 PCT/US1996/003799 US9603799W WO9635157A1 WO 1996035157 A1 WO1996035157 A1 WO 1996035157A1 US 9603799 W US9603799 W US 9603799W WO 9635157 A1 WO9635157 A1 WO 9635157A1
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WO
WIPO (PCT)
Prior art keywords
classifier
signal
sequence
waveform
received
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US1996/003799
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English (en)
Inventor
Richard Comroe
Robert W. Furtaw
Mark A. Gannon
David A. Hayner
Bruce E. Stuckman
Eric Ziolko
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Motorola Solutions Inc
Original Assignee
Motorola Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Motorola Inc filed Critical Motorola Inc
Priority to AU52572/96A priority Critical patent/AU5257296A/en
Publication of WO1996035157A1 publication Critical patent/WO1996035157A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03K—PULSE TECHNIQUE
    • H03K7/00—Modulating pulses with a continuously-variable modulating signal
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03165—Arrangements for removing intersymbol interference using neural networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/38—Synchronous or start-stop systems, e.g. for Baudot code
    • H04L25/40—Transmitting circuits; Receiving circuits
    • H04L25/49—Transmitting circuits; Receiving circuits using code conversion at the transmitter; using predistortion; using insertion of idle bits for obtaining a desired frequency spectrum; using three or more amplitude levels ; Baseband coding techniques specific to data transmission systems
    • H04L25/4917—Transmitting circuits; Receiving circuits using code conversion at the transmitter; using predistortion; using insertion of idle bits for obtaining a desired frequency spectrum; using three or more amplitude levels ; Baseband coding techniques specific to data transmission systems using multilevel codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/03433—Arrangements for removing intersymbol interference characterised by equaliser structure
    • H04L2025/03439—Fixed structures
    • H04L2025/03445—Time domain
    • H04L2025/03464—Neural networks

Definitions

  • the present invention is related to the following inventions which are assigned to the same assignee as the present invention:
  • the present invention relates generally to demodulation methods and systems and, in particular, to a methods and systems for demodulation which are capable of learning conditions for a particular communication channel,
  • Digital modulation techniques are widely used in communication systems today. These digital systems offer the advantages of greater noise immunity, greater versatility and higher efficiency than many of their analog predecessors.
  • the heart of these digital communication systems is the demodulator — the portion of the system which converts the waveforms representative of the digital information conveyed by these systems, into the digital information itself.
  • Many prior art systems use either matched filtering or correlation to demodulate the digital waveforms. These techniques are complex, yet they can be shown to be optimal under certain conditions such as Gaussian noise. Unfortunately, many actual noise conditions do not statistically conform to the Gaussian noise assumption. Therefore a need exists for a demodulation methods and systems that can conform to differing noise conditions.
  • FIG. 1 presents a block diagram representation of one embodiment of the present invention.
  • FIG. 2 presents an example waveform corresponding to a stream of information bits modulated by multi-level PCM.
  • FIG. 3 presents a flowchart representation of one embodiment of the present invention.
  • FIG. 4 presents a flowchart representation of a method of one embodiment of the present invention.
  • FIG. 5 presents a block diagram representation of a method in accordance with one embodiment of the present invention.
  • FIG. 6 presents an example waveform corresponding to a stream of information bits modulated by m-ary signaling.
  • FIG. 7 presents a flowchart representation of a method in accordance with one embodiment of the present invention.
  • FIG. 8 shows a schematic representation of the polynomial processor in accordance with one embodiment of the present invention.
  • FIG. 9 shows a flow chart representation of a method of training the coefficients for a processor in accordance with one embodiment of the present invention.
  • FIG. 10 presents a graphical representation of an example waveform used to determine the processor coefficients in accordance with one embodiment of the present invention.
  • FIG. 11 presents a graphical representation of an example waveform used to demonstrate the training of the polynomial coefficients in accordance with a further embodiment of the present invention.
  • the present invention provides a demodulation method and system for use in a communication system which is susceptible to noise in the communication link.
  • the various embodiments of the present invention are capable of learning and adapting to the modulation employed and demodulating in a fashion which is robust — that is capable of operating effectively in the presence of high degrees of noise which may or may not conform to Gaussian statistics.
  • nonlinear mathematics and parallel computation can be employed in a polynomial processor to provide the features described above.
  • FIG. 1 presents a block diagram representation of one embodiment of the present invention.
  • This embodiment presents a system 10 for demodulating a waveform corresponding to a stream of information bits modulated by multi-level PCM.
  • Receiver 12 receives the waveform to form a received signal.
  • Sampler 14, in communication with the receiver 12, receives the received signal and samples the received signal at a plurality of discrete times to form a sequence of received samples.
  • Processor 16 in communication with the sampler 14, receives the received samples from the sampler 14 and processes the received samples to form an output sequence having a plurality of output values, each output value being a polynomial function of at least one of the received samples; wherein each output value represents a respective level of the multi-level PCM corresponding to one or more binary information bits.
  • System 10 further includes a trainer 18, coupled to the processor and responsive to a plurality of demodulation data for determining a value for each of the plurality of polynomial coefficients by fitting the polynomial function to the plurality of demodulation data.
  • the demodulation data includes a sequence of training samples that represent a sample sequence of received samples, and a sequence of desired output values, each desired output value corresponding to at least one of the sequence of training samples.
  • FIG. 1 An example of the operation of the embodiment of the present invention illustrated by FIG. 1 can be described as follows.
  • FIG. 2 presents an example waveform corresponding to a stream of information bits modulated by multi-level PCM.
  • Waveform 30 represents a segment of 8-level PCM. Three bits of information are transmitted for each period T. The originally transmitted waveform (not shown) more closely corresponded to levels 5, 3, and 4 respectively for three consecutive time periods. The waveform 30 is corrupted by the noise present in the communication channel. Waveform 30 is received by receiver 12 and sampled by sampler 14 at four discrete times per period T. While a sampling frequency of 4/T is shown, it should be understood by those skilled in the art that greater or lessor frequencies could advantageously be employed in other circumstances, however the sampling frequency must be at least greater than 1/T.
  • the sampler consists of an analog to digital (A/D) converter.
  • the sequence of received samples 32 correspond to a sequence of digital words.
  • this sequence of received samples can be represented by (X(l), X(2), X(3), . . . X(n), X(n+1), . . .) .
  • Processor 16 calculates a sequence of output levels as polynomial function of a finite number (at least one) of the sequence of received samples. If the sequence of output levels is represented by (Y(l), Y(2), Y(3), . . . Y(n), Y(n+1), . . .), then the a general output level in the sequence Y(n) can be represented as follows:
  • the processor 16 includes a truncation function which generates the output levels by truncating an analog polynomial function value.
  • the processor 16 further includes a decoder for translating the output levels at a plurality of discrete times into their corresponding binary value.
  • FIG. 3 presents a flowchart representation of one embodiment of the present invention.
  • This flowchart represents a method used in conjunction with the system of FIG. 1.
  • Step 40 includes receiving the waveform to form a received signal.
  • the received signal is sampled at a plurality of discrete times to form a sequence of received samples as shown in step 42.
  • the received samples are processed to form an output sequence having a plurality of output values as shown in step 44, each output value being a polynomial function of at least one of the received samples; wherein each output value represents a respective level of the multi-level PCM corresponding to one or more binary information bits.
  • FIG. 4 presents a flowchart representation of a method of one embodiment of the present invention. This method is also used in conjunction with the system of FIG. 1. Steps 50 - 54 correspond to steps 40 - 44 of FIG. 3. Step 56 includes determining a value for each of the plurality of coefficients by fitting the polynomial function to a plurality of demodulation data.
  • FIG. 5 presents a block diagram representation of a method in accordance with one embodiment of the present invention.
  • This figure illustrates a system for demodulating a waveform, the waveform corresponding to a stream of information bits modulated by an m-ary signaling technique.
  • the system includes a receiver 60 for receiving the waveform to form a received signal.
  • This received signal is fed to a sampler 62, which samples the received signal at a plurality of discrete times to form a sequence of received samples.
  • the sequence of received samples is, in turn, fed to a processor 74 for processing the received samples in a plurality of signal classifiers 64 - 68, each signal classifier forming an classifier sequence having a plurality of classifier values, each classifier value corresponding to one of the plurality of discrete times, each classifier value being a polynomial function of at least one of the received samples.
  • Each of the classifier sequences are fed to a comparator 70 in communication with the processor 74.
  • the comparator 70 compares, at each of the plurality of discrete times, a magnitude of the classifier value for each of the plurality of signal classifiers.
  • a generator 72 coupled to the comparator, generates an output value corresponding to each of the plurality of discrete times based on the magnitude of at least one of the classifier values.
  • the polynomial function for each of the plurality of signal classifiers includes a plurality of coefficients and the system further includes a trainer 76, coupled to the processor and responsive to a plurality of demodulation data.
  • the trainer determines a value for each of the plurality of coefficients for each of the plurality of signal classifiers by fitting each polynomial function to the plurality of demodulation data.
  • the comparator determines, for each discrete time, which of the plurality of classifiers has a classifier value with the greatest magnitude.
  • each of the signal classifiers is trained to recognize one of the m- signals that could be transmitted by the transmitter.
  • the output value corresponds to a determination of which of the plurality of classifiers had the greatest magnitude—therefore indicating that the corresponding signal is most likely to have been transmitted.
  • FIG. 5 An example of the operation of the embodiment of the present invention illustrated by FIG. 5 can be described as follows.
  • FIG. 6 presents an example waveform corresponding to a stream of information bits modulated by m-ary signaling.
  • Waveform 80 represents a received signal of 4-ary signaling.
  • signals 82-88 are transmitted representing 2 bits of information.
  • signal 86 is corrupted by the noise present in the communication channel 90.
  • the process of carrier modulation is not shown, one of ordinary skill in the art will recognize that any of a wide variety of carrier modulation schemes could be used in conjunction with the present invention.
  • the signals 82-88 are presented solely to illustrate the operation of the present invention.
  • any of a wide variety of m-ary signaling schemes incorporating signals of differing shape, spectrum, frequency, phase, and/or amplitude could be employed in conjunction with the method and system of the present invention.
  • Waveform 80 is received by receiver 60 and sampled by sampler 62 at eight discrete times per period T. While a sampling frequency of 8/T is shown, it should be understood by those skilled in the art that greater or lessor frequencies could advantageously be employed in other circumstances, however the sampling frequency must be at least greater than 1/T.
  • the sampler consists of an analog to digital (A/D) converter.
  • the sequence of received samples 82 correspond to a sequence of digital words.
  • this sequence of received samples can be represented by (X(l), X(2), X(3), . . . X(n), X(n+1), . . .) .
  • Processor 74 calculates a sequence of output levels as polynomial function of a finite number (at least one) of the sequence of received samples for each of the plurality of signal classifiers. If the sequence of output levels for the kth signal classifier is represented by (Yk(l), Yk(2), Yk ⁇ 3), . . . Yk ⁇ n), Yk(n+1), . . .), then the a general output level in the sequence (n) can be represented as follows:
  • m is an integer which represents the number of terms in the polynomial
  • p is an integer that represents the number of past inputs considered (effectively the window-size for the polynomial in time)
  • gjik represents the power of X(j) in the ith term and the kth signal classifier
  • wki-l is the coefficient of the ith term and the kth signal classifier.
  • the number of signal classifiers corresponds to the number of possible signals to be sent.
  • four signal classifiers are used — each signal classifier trained to recognize one of the possible signals to be sent.
  • the outputs Y3(l) - Y3(8) are greater than the outputs of the other classifiers since this classifier has been trained to recognize the signal 86 which was the signal that was transmitted during this period of time.
  • a weighted sum is calculated for each classifier output over a time period T, (Yfc(n) , Yk(n+1), . . ., Yk(n+p-l)). These weighted sums are compared to determine the classifier output whose output is greatest.
  • Other schemes such as voting, the summing of rank transformed outputs, the summing of normal-scores transformed outputs or the use of parametric statistical techniques, could also be used to determine, for each time period T the classifier with the dominant output.
  • FIG. 7 presents a flowchart representation of a method in accordance with one embodiment of the present invention. This method is advantageously used in conjunction with the system presented in FIG. 5.
  • the method includes the step of determining a value for each of the plurality of coefficients by fitting the polynomial function to a plurality of demodulation data as shown in step 100.
  • a waveform is received as shown in step 102 in order to form a received signal.
  • the received signal is sampled as shown in step 104 at a plurality of discrete times to form a sequence of received samples.
  • the received samples are processed in a plurality of signal classifiers as shown in step 106, each signal classifier forming an classifier sequence having a plurality of classifier values, each classifier value corresponding to one of the plurality of discrete times, each classifier value being a polynomial function of at least one of the received samples.
  • a magnitude of each of the plurality of classifier values is determined for each of the plurality of signal classifiers as shown in step 108.
  • an output value is generated, corresponding to each of the plurality of discrete times, based on the magnitude of at least one of the classifier values as shown in step 110.
  • step 110 includes the substep of determining, for each discrete time, which of the plurality of classifiers has a classifier value with the greatest magnitude.
  • FIG. 8 shows a schematic representation of the polynomial processor in accordance with one embodiment of the present invention.
  • Polynomial processor 190 can be used in the implementation of either the processor 16 or each signal classifier for the processor 74. This processor 190 generates output signals as a polynomial function of one or more input signals.
  • a plurality of input signals, xi, X 2 , . . ., x n are fed to input nodes 176, 178, . . . 180 of an input layer.
  • the output of each input node 176, 178, . . . 180 in the input layer is distributed to at least one processing element of a hidden layer (of which only processing elements 182, 184, 186 are shown) .
  • Each processing element applies a gating function (exponent) to each of the control inputs to produce a corresponding gated input. Any given processing element may apply a different gating function to each different input it receives.
  • processing element 182 applies a gating function (911) to the input it receives from input node 176; it applies a gating function (g2i) to the input it receives from input node 78; and so forth.
  • the gated inputs are multiplied together by a multiplier in the processing element to form a product, which is then multiplied by a coefficient wj . - ⁇ to form the ith term of the polynomial.
  • processing element 182 which happens to be responsible for generating the first polynomial term, multiplies its gated inputs together to form a product (which happens to be one because in this case the gating functions gn, g21/ • • • 9nl are all 0) , which is multiplied by a coefficient w 0 to produce a corresponding output w 0 .
  • Processing element 184 which happens to be responsible for generating the wi xi term of the polynomial, multiplies its gated inputs together to form a product (which happens to be xi because in this case the gated functions are all 0 except for the gating function that is applied to the i output of the input node 176) , which is multiplied by a coefficient wi to produce a corresponding output i w]_.
  • processing element 186 produces an output w n - ⁇ xi to the power of gin, X2 to the power of g2n / • • • , xn to the power of gnN-
  • the outputs of processing elements 182, 184, . . . 186 are summed together by a suitable summing means or function, such as summer 188, in an output layer to produce the output signal y of the processor as follows:
  • m is an integer which represents the number of terms in the polynomial.
  • processor 190 has been described to fulfill the functions ascribed to processors 16 and 74, one of ordinary skill in the art will recognize that, in certain embodiments of the present invention, processor 190 would serve merely as a co-processor which performs the polynomial calculations called for by processors 16 and 74.
  • An additional processing element such as a conventional microprocessor can be used in conjunction with processor 190 to provide additional functionality.
  • processors 16 and 74 are implemented without the use of a processor such as processor 190.
  • a traditional processor such as a digital signal processor or microprocessor, with or without a traditional math co ⁇ processor, is employed.
  • FIG. 9 shows a flow chart representation of a method of training the coefficients for a processor in accordance with one embodiment of the present invention.
  • the demodulation data are provided.
  • the number of data is compared with the number of coefficients.
  • decision box 171 if the number of data equal the number of coefficients, the procedure goes to box 172 which indicates that a matrix inversion technique is used to solve for the initial value of each coefficient. If, on the other hand, the number of data is not equal to the number of coefficients, the procedure goes to box 173, which indicates that a least squares estimation technique is used to solve for the initial value of each coefficient.
  • FIG. 10 presents a graphical representation of an example waveform used to determine the processor coefficients in accordance with one embodiment of the present invention. More particularly, FIG. 10 will be used to illustrate the operation of the method of FIG. 9 in the trainer 18.
  • Waveform 200 represents a segment of 8-level PCM.
  • the demodulation data used to determine the coefficients of the polynomial function in processor 16 includes a sequence of training samples 202, X(n), that represent an example sequence of received samples.
  • the demodulation data further includes a sequence of desired output values 204, Y(n), each desired output value corresponding to at least one of the sequence of training samples.
  • the coefficients of the polynomial can be determined based on the curve-fitting techniques previous discussed and/or presented in Related Invention #3.
  • example waveform 200 is shown to be relatively noiseless, in an alternative embodiment of the present invention, actual received data such as data produced in the presence of noise can also be used to train the processor. In this fashion, the actual operating conditions of the demodulation method and system can be more closely approximated during the training phase of the system.
  • FIG. 11 presents a graphical representation of an example waveform used to demonstrate the training of the polynomial coefficients in accordance with a further embodiment of the present invention.
  • FIG. 11 will be used to demonstrate the operation of the system of FIG. 5 and specifically trainer 76.
  • Waveform 210 represents a segment of 4-ary signaling in relation to the example discussed in conjunction with FIG. 6.
  • the demodulation data used to determine the coefficients of the polynomial function in processor 74 includes a sequence of training samples 212, X(n), that represent an example sequence of received samples.
  • the demodulation data further includes a sequence of desired classifier values, each desired classifier value corresponding to at least one of the sequence of training samples.
  • example waveform 210 is shown to be relatively noiseless, in an alternative embodiment of the present invention, actual received data such as data produced in the presence of noise can also be used to train the processor. In this fashion, the actual operating conditions of the demodulation method and system can be more closely approximated during the training phase of the system.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Digital Transmission Methods That Use Modulated Carrier Waves (AREA)

Abstract

L'invention porte sur un procédé de démodulation d'une forme d'onde (40) modulée, à l'aide d'une technique de signalisation m-aire recevant la forme d'onde et la transformant en signal reçu. Ledit signal reçu est échantillonné à intervalles réguliers de manière à constituer une suite d'échantillons de réception (42), qui sont traités (44) dans plusieurs classifieurs de signaux (16) dont chacun forme une séquence classifiée à plusieurs valeurs, dont chacune correspond à l'un des temps d'échantillonnage et constitue une fonction polynomiale d'un échantillon au moins. L'amplitude de chacune des valeurs classifiées est déterminée pour chacun des classifieurs. Une valeur de sortie est générée pour chacun des temps d'échantillonnage en fonction de l'amplitude de l'une au moins des valeurs classifiées.
PCT/US1996/003799 1995-05-05 1996-03-21 Procede et systeme de demodulation d'un signal m-aire Ceased WO1996035157A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU52572/96A AU5257296A (en) 1995-05-05 1996-03-21 Method and system for demodulation of m-ary signaling

Applications Claiming Priority (2)

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US43512395A 1995-05-05 1995-05-05
US08/435,123 1995-05-05

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WO1996035157A1 true WO1996035157A1 (fr) 1996-11-07

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5121391A (en) * 1985-03-20 1992-06-09 International Mobile Machines Subscriber RF telephone system for providing multiple speech and/or data singals simultaneously over either a single or a plurality of RF channels
US5212448A (en) * 1991-08-09 1993-05-18 General Electric Company Nmr pulse sequence with burst rf excitation pulses having separately controlled phase

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5121391A (en) * 1985-03-20 1992-06-09 International Mobile Machines Subscriber RF telephone system for providing multiple speech and/or data singals simultaneously over either a single or a plurality of RF channels
US5212448A (en) * 1991-08-09 1993-05-18 General Electric Company Nmr pulse sequence with burst rf excitation pulses having separately controlled phase

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