Iterative interference cancellation using mixed feedback weights and stabilizing step sizes
First Claim
1. An interference canceller configured for performing at least one iteration for each of a plurality of input symbol estimates for producing updated interference-cancelled symbol estimates, the canceller comprising a weighting module, the weighting module configured to apply at least one symbol weight to the plurality of input symbol estimates, the at least one symbol weight comprising a function of an input symbol merit, wherein the canceller is configured to measure the input symbol merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the plurality of input symbol estimates and proximity of at least one of the plurality of input symbol estimates to a nearby constellation point, and wherein the function of the average ratio of signal power to interference-plus-noise power is substantially characterized by
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[ i ] = max { C , 1 1 + 1 / SINR [ i ] } , where γ
[i] is a symbol weight after an ith iteration of the interference canceller, max { } is a function for selecting a maximum value from a set of quantities within brackets { }, SINR[i] denotes an average ratio of signal power to interference-plus-noise power (SINR) of the symbol after the ith iteration of the interference canceller, and C is a non-negative real constant for enforcing a minimum symbol weight.
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Abstract
A receiver is configured for canceling intra-cell and inter-cell interference in coded, multiple-access, spread-spectrum transmissions that propagate through frequency-selective communication channels. The receiver employs iterative symbol-estimate weighting, subtractive cancellation with a stabilizing step-size, and mixed-decision symbol estimates. Receiver embodiments may be implemented explicitly in software or programmed hardware, or implicitly in standard Rake-based hardware either within the Rake (i.e., at the finger level) or outside the Rake (i.e., at the user or subchannel symbol level).
85 Citations
9 Claims
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1. An interference canceller configured for performing at least one iteration for each of a plurality of input symbol estimates for producing updated interference-cancelled symbol estimates, the canceller comprising a weighting module, the weighting module configured to apply at least one symbol weight to the plurality of input symbol estimates, the at least one symbol weight comprising a function of an input symbol merit, wherein the canceller is configured to measure the input symbol merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the plurality of input symbol estimates and proximity of at least one of the plurality of input symbol estimates to a nearby constellation point, and wherein the function of the average ratio of signal power to interference-plus-noise power is substantially characterized by
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[ i ] = max { C , 1 1 + 1 / SINR [ i ] } , where γ
[i] is a symbol weight after an ith iteration of the interference canceller, max { } is a function for selecting a maximum value from a set of quantities within brackets { }, SINR[i] denotes an average ratio of signal power to interference-plus-noise power (SINR) of the symbol after the ith iteration of the interference canceller, and C is a non-negative real constant for enforcing a minimum symbol weight.
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2. An interference canceller configured for performing at least one iteration for each of a plurality of input symbol estimates for producing updated interference-cancelled symbol estimates, the canceller comprising a weighting module, the weighting module configured to apply at least one symbol weight to the plurality of input symbol estimates, the at least one symbol weight comprising a function of an input symbol merit, wherein the canceller is configured to measure the input symbol merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the plurality of input symbol estimates and proximity of at least one of the plurality of input symbol estimates to a nearby constellation point, and wherein the canceller is configured to employ time-series averaging for calculating the proximity as a statistical average.
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3. An interference canceller configured for performing at least one iteration for each of a plurality of input symbol estimates for producing updated interference-cancelled symbol estimates, the canceller comprising a weighting module, the weighting module configured to apply at least one symbol weight to the plurality of input symbol estimates, the at least one symbol weight comprising a function of an input symbol merit wherein the at least one symbol weight is substantially characterized by:
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where γ
[i] is a symbol weight after an ith iteration of the interference canceller, {circumflex over (b)}[i] is a symbol decision after the ith iteration of the interference canceller, slice({circumflex over (b)}[i]) represents the quantization of {circumflex over (b)}[i] to a nearest constellation point, Re{ } returns a real part of an argument, E[ ] represents a statistical expectation or its estimate with a time average, ∥
represents the magnitude of a complex quantity, and * denotes the conjugate of a complex quantity.
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4. An interference cancellation method employing at least one iteration for each of a plurality of input symbol estimates for converting the plurality of input symbol estimates into updated interference-cancelled symbol estimates, wherein each of the at least one iteration comprises applying at least one symbol weight to the plurality of input symbol estimates, the method further comprising:
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providing for calculating the at least one symbol weight from a function of an input symbol merit, wherein providing for calculating the at least one symbol weight comprises measuring the input symbol merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the plurality of input symbol estimates and proximity of at least one of the plurality of input symbol estimates to a nearby constellation point, and wherein the function of the average ratio of signal power to interference-plus-noise power is substantially characterized by where γ
[i] is a symbol weight after an ith iteration of the interference canceller, max{ } is a function for selecting a maximum value from a set of quantities within brackets { }, SINR[i] denotes an average ratio of signal power to interference-plus-noise power (SINR) of the symbol after the ith iteration of the interference canceller, and C is a non-negative real constant for enforcing a minimum symbol weight.
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5. An interference cancellation method employing at least one iteration for each of a plurality of input symbol estimates for converting the plurality of input symbol estimates into updated interference-cancelled symbol estimates, wherein each of the at least one iteration comprises applying at least one symbol weight to the plurality of input symbol estimates, the method further comprising:
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providing for calculating the at least one symbol weight from a function of an input symbol merit, wherein providing for calculating the at least one symbol weight comprises measuring the input symbol merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the plurality of input symbol estimates and proximity of at least one of the plurality of input symbol estimates to a nearby constellation point, and comprising providing for time-series averaging for calculating the proximity as a statistical average.
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6. An interference cancellation method employing at least one iteration for each of a plurality of input symbol estimates for converting the plurality of input symbol estimates into updated interference-cancelled symbol estimates, wherein each of the at least one iteration comprises applying at least one symbol weight to the plurality of input symbol estimates, the method further comprising:
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providing for calculating the at least one symbol weight from a function of an input symbol merit, wherein the at least one symbol weight is substantially characterized by; where γ
[i] is a symbol weight after an ith iteration of the interference canceller, {circumflex over (b)}[i] is a symbol decision after the ith iteration of the interference canceller, slice({circumflex over (b)}[i]) represents the quantization of {circumflex over (b)}[i] to a nearest constellation point, Re{ } returns a real part of an argument, E[ ] represents a statistical expectation or its estimate with a time average, ∥
represents the magnitude of a complex quantity, and * denotes the conjugate of a complex quantity.
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7. An interference cancellation system configured for converting input symbol estimates into updated interference-cancelled symbol estimates, wherein signal processing in each of at least one iteration for each of the input symbol decisions is performed by a weighting means configured for applying at least one symbol weight to the input symbol estimates, the system further comprising:
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a weight-calculation means configured for calculating the at least one symbol weight from a function of a merit of an input symbol, wherein the weight-calculation means is configured to measure the merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the input symbol estimates and proximity of at least one of the input symbol estimates to a nearby constellation point, and wherein the function of the average ratio of signal power to interference-plus-noise power is substantially characterized by where γ
[i] is a symbol weight after an ith iteration of the interference canceller, max { } is a function for selecting a maximum value from a set of quantities within brackets { }, SINR[i] denotes an average ratio of signal power to interference-plus-noise power (SINR) of the symbol after the ith iteration of the interference canceller, and C is a non-negative real constant for enforcing a minimum symbol weight.
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8. An interference cancellation system configured for converting input symbol estimates into updated interference-cancelled symbol estimates, wherein signal processing in each of at least one iteration for each of the input symbol decisions is performed by a weighting means configured for applying at least one symbol weight to the input symbol estimates, the system further comprising:
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a weight-calculation means configured for calculating the at least one symbol weight from a function of a merit of an input symbol, wherein the weight-calculation means is configured to measure the merit as at least one of a set of functions, the set comprising a function of an average ratio of signal power to interference-plus-noise power, and a function of at least one of the input symbol estimates and proximity of at least one of the input symbol estimates to a nearby constellation point, and wherein the weight-calculation means is configured to employ time-series averaging for calculating the proximity as a statistical average.
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9. An interference cancellation system configured for converting input symbol estimates into updated interference-cancelled symbol estimates, wherein signal processing in each of at least one iteration for each of the input symbol decisions is performed by a weighting means configured for applying at least one symbol weight to the input symbol estimates, the system further comprising:
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a weight-calculation means configured for calculating the at least one symbol weight from a function of a merit of an input symbol, wherein the at least one symbol weight is substantially characterized by; where γ
[i] is a symbol weight after an ith iteration of the interference canceller, {circumflex over (b)}[i] is a symbol decision after the ith iteration of the interference canceller, slice({circumflex over (b)}[i]) represents the quantization of {circumflex over (b)}[i] to a nearest constellation point, Re{ } returns a real part of an argument, E[ ] represents a statistical expectation or its estimate with a time average, ∥
represents the magnitude of a complex quantity, and * denotes the conjugate of a complex quantity.
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Specification