Decoding of forward error correction codes in the presence of phase noise
First Claim
1. A communication receiver, comprising:
- a front end, which is arranged to receive a Radio Frequency (RF) signal, which comprises modulated symbols carrying data that have been encoded by a block Forward Error Correction (FEC) code, and to convert the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least first and second noise components having respective at least first and second statistical distributions;
a metric calculation unit, which is arranged to process the soft received symbols so as to extract a first parameter indicative of the first statistical distribution and a second parameter indicative of the second statistical distribution, and to compute FEC metrics based on the extracted first and second parameters by evaluating the FEC metrics responsively to the first statistical distribution over a range of values of the second noise component assuming the second statistical distribution is constant, weighting the evaluated FEC metrics using a weight function, and integrating the weighted FEC metrics over the range of values of the second noise component; and
a FEC decoder, which is arranged to accept the FEC metrics as input, and to process the metrics in an iterative FEC decoding process so as to decode the FEC code and reconstruct the data.
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Abstract
A communication receiver includes a front end, which is arranged to receive a Radio Frequency (RF) signal, which includes modulated symbols carrying data that have been encoded by a block Forward Error Correction (FEC) code. The front end converts the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least first and second noise components having respective at least first and second statistical distributions. A metric calculation unit is arranged to process the soft received symbols so as to extract parameters indicative of the at least first and second statistical distributions, and to compute FEC metrics based on the extracted parameters. A FEC decoder is arranged to accept the FEC metrics as input, and to process the metrics in an iterative FEC decoding process so as to decode the FEC code and reconstruct the data.
183 Citations
24 Claims
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1. A communication receiver, comprising:
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a front end, which is arranged to receive a Radio Frequency (RF) signal, which comprises modulated symbols carrying data that have been encoded by a block Forward Error Correction (FEC) code, and to convert the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least first and second noise components having respective at least first and second statistical distributions; a metric calculation unit, which is arranged to process the soft received symbols so as to extract a first parameter indicative of the first statistical distribution and a second parameter indicative of the second statistical distribution, and to compute FEC metrics based on the extracted first and second parameters by evaluating the FEC metrics responsively to the first statistical distribution over a range of values of the second noise component assuming the second statistical distribution is constant, weighting the evaluated FEC metrics using a weight function, and integrating the weighted FEC metrics over the range of values of the second noise component; and a FEC decoder, which is arranged to accept the FEC metrics as input, and to process the metrics in an iterative FEC decoding process so as to decode the FEC code and reconstruct the data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A communication receiver, comprising:
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a front end, which is arranged to receive a Radio Frequency (RF) signal comprising modulated symbols, which carry data and are selected from a predetermined constellation of nominal symbols that correspond to respective decision regions in an In-phase/Quadrature (I/Q) plane, and to convert the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least first and second noise components having respective at least first and second statistical distributions; and a slicer circuit, which is arranged to convert the soft received symbols to respective hard symbol decisions based on the decision regions in which the soft received symbols fall, to reconstruct the data from the hard symbol decisions, and to modify the decision regions in the I/Q plane responsively to the at least first and second statistical distributions, wherein the constellation is divided into multiple cosets and wherein each of the nominal symbols represents a respective group of bits, such that one or more of the bits, which are coded by a Forward Error Correction (FEC) code, select a coset from among the cosets and the other bits, which are not coded by the FEC code, select the nominal symbol within the selected coset, and wherein the slicer circuit is arranged to separately modify the decision regions among the nominal symbols of each coset. - View Dependent Claims (15)
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16. A method for communication, comprising:
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receiving a Radio Frequency (RF) signal, which comprises modulated symbols carrying data that have been encoded by a block Forward Error Correction (FEC) code; converting the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least first and second noise components having respective at least first and second statistical distributions; processing the soft received symbols responsively to the at least first and second statistical distributions, so as to extract from the soft received symbols a first parameter indicative of the first statistical distribution and a second parameter indicative of the second statistical distribution; computing FEC metrics based on the extracted first and second parameters by evaluating the FEC metrics responsively to the first statistical distribution over a range of values of the second noise component assuming the second statistical distribution is constant, weighting the evaluated FEC metrics using a weight function, and integrating the weighted FEC metrics over the range of values of the second noise component; and processing the FEC metrics in an iterative FEC decoding process that uses the FEC metrics as input, so as to decode the FEC code and reconstruct the data. - View Dependent Claims (17, 18, 19, 20, 21)
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22. A method for communication, comprising:
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receiving a Radio Frequency (RF) signal comprising modulated symbols, which carry data and are selected from a predetermined constellation of nominal symbols that correspond to respective decision regions in an In-phase/Quadrature (I/Q) plane; converting the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least first and second noise components having respective at least first and second statistical distributions; converting the soft received symbols to respective hard symbol decisions based on the decision regions in which the soft received symbols fall, so as to reconstruct the data from the hard symbol decisions; and modifying the decision regions in the I/Q plane responsively to the at least first and second statistical distributions, wherein the constellation is divided into multiple cosets and wherein each of the nominal symbols represents a respective group of bits, such that one or more of the bits, which are coded by a Forward Error Correction (FEC) code, select a coset from among the cosets and the other bits, which are not coded by the FEC code, select the nominal symbol within the selected coset, and wherein the slicer circuit is arranged to separately modify the decision regions among the nominal symbols of each coset.
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23. A communication receiver, comprising:
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a front end, which is arranged to receive a Radio Frequency (RF) signal, which comprises modulated symbols carrying data that have been selected from a constellation of nominal symbols and encoded by a block Forward Error Correction (FEC) code, and to convert the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least a thermal noise component and a phase noise component having respective at least first and second statistical distributions; a metric calculation unit, which is arranged to process the soft received symbols so as to extract parameters indicative of the at least first and second statistical distributions, and to compute FEC metrics based on the extracted parameters, such that computation of each FEC metric is performed only over a respective subset of the nominal symbols that are selected by applying a Euclidean distance metric to the thermal noise component and a modified Euclidean distance metric, modified based on the second noise distribution, to the phase noise component; and a FEC decoder, which is arranged to accept the FEC metrics as input, and to process the metrics in an iterative FEC decoding process so as to decode the FEC code and reconstruct the data.
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24. A method for communication, comprising:
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receiving a Radio Frequency (RF) signal, which comprises modulated symbols carrying data that have been selected from a constellation of nominal symbols and encoded by a block Forward Error Correction (FEC) code; converting the RF signal to a sequence of soft received symbols, wherein the soft received symbols are subject to distortion by at least a thermal noise component and a phase noise component having respective at least first and second statistical distributions; processing the soft received symbols responsively to the at least first and second statistical distributions, so as to extract from the soft received symbols parameters indicative of the at least first and second statistical distributions; computing FEC metrics based on the extracted parameters, such that computation of each FEC metric is performed only over a respective subset of the nominal symbols that are selected by applying a Euclidean distance metric to the thermal noise component and a modified Euclidean distance metric, modified based on the second noise distribution, to the phase noise component; and processing the FEC metrics in an iterative FEC decoding process that uses the FEC metrics as input, so as to decode the FEC code and reconstruct the data.
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Specification