Method and system for forward error correction decoding with parity check for use in low complexity highly-spectrally efficient communications
A receiver receives an inter-symbol correlated (ISC) signal with information symbols and a corresponding parity symbol. Values of information symbols are estimated utilizing parity samples that are generated from the parity symbols. One or more maximum likelihood (ML) decoding metrics are generated for the information symbols. One or more estimations are generated for the information symbols based on the one or more ML decoding metrics. A parity metric is generated for each of the one or more generated estimations of the information symbols. The parity metric is generated by summing a plurality of values of one of the generated estimations to generate a sum, and wrapping the sum to obtain a parity check value that is within the boundaries of a symbol constellation utilized in generating the information symbols.
1. A system comprising:
circuitry for use in an electronic receiver, wherein said circuitry comprises:
a receiver front-end operable to receive a plurality of symbols of a signal transmitted over a communication channel, wherein:
said plurality of symbols comprise a plurality of information symbols and a parity symbol; and
each of said information symbols represents a plurality of bits; and
a sequence estimation circuit operable to:
generate one or more symbol-domain parity metrics; and
determine values of said plurality of information symbols based on said one or more symbol-domain parity metrics and said received parity symbol.
2. The system of claim 1 wherein:
said sequence estimation circuit is operable to generate one or more survivor vectors; and
each of said one or more symbol-domain parity metrics corresponds to one of said one or more survivor vectors.
3. The system of claim 2 wherein said generation of said symbol-domain parity metric comprises a calculation of a sum of symbol values in an observation region of said one or more survivor vectors.
4. The system of claim 3 wherein said generation of said symbol-domain parity metric comprises modifying said sum to obtain a value within boundaries of a symbol constellation used to generate said information symbols.
5. The system of claim 2 wherein:
said sequence estimation circuit is operable to generate one or more maximum likelihood metrics corresponding to said one or more survivor vectors; and
said determination of said values of said plurality of information symbols is based on said one or more maximum likelihood metrics.
6. The system of claim 2 wherein:
said sequence estimation circuit is operable to generate one or more maximum likelihood metrics corresponding to said one or more survivor vectors;
said circuitry is operable to combine said one or more maximum likelihood metrics and said one or more symbol-domain parity metrics to generate one or more super metrics; and
said determination of said values of said plurality of information symbols is based on said one or more super metrics.
7. The system of claim 6 wherein said combination of said one or more maximum likelihood metrics and said one or more symbol-domain parity metrics is a linear combination.
8. The system of claim 6 wherein said combination one or more maximum likelihood metrics and said one or more symbol-domain parity metrics is a nonlinear combination.
9. The system of claim 6 wherein a manner in which said one or more maximum likelihood metrics and said one or more symbol-domain parity metrics are combined varies based on a measured performance metric.
10. The system of claim 1 wherein each of said plurality of symbols is an N-QAM symbol, where N is an integer.
11. A method comprising:
performing in an electronic receiver:
receiving, via a front-end of said electronic receiver, a plurality of symbols of a signal transmitted over a communication channel, wherein:
said plurality of symbols comprise a plurality of information symbols and a parity symbol; and
each of said information symbols represents a plurality of bits;
generating, by sequence estimation circuitry of said electronic receiver, one or more symbol-domain parity metrics; and
determining, by said sequence estimation circuitry of said electronic receiver, values of said plurality of information symbols based on said one or more symbol-domain parity metrics and said received parity symbol.
12. The method of claim 11 comprising generating, by said sequence estimation circuitry, one or more survivor vectors, wherein each of said one or more symbol-domain parity metrics corresponds to one of said one or more survivor vectors.
13. The method of claim 12 comprising calculating, by said sequence estimation circuitry as part of said generating said symbol-domain parity metric, a sum of symbol values in an observation region of said one or more survivor vectors.
14. The method of claim 13 comprising modifying, by said sequence estimation circuitry as part of said generating said symbol-domain parity metric, said sum to obtain a value within boundaries of a symbol constellation used to generate said information symbols.
15. The method of claim 12 comprising:
generating, by said sequence estimation circuitry, one or more maximum likelihood metrics corresponding to said one or more survivor vectors; and
determining, by said sequence estimation circuitry, said values of said plurality of information symbols based on said one or more maximum likelihood metrics.
16. The method of claim 12 comprising:
generating, by said sequence estimation circuitry, one or more maximum likelihood metrics corresponding to said one or more survivor vectors;
combining, by said sequence estimation circuitry, said one or more maximum likelihood metrics and said one or more symbol-domain parity metrics to generate one or more super metrics; and
determining, by said sequence estimation circuitry, said values of said plurality of information symbols based on said one or more super metrics.
17. The method of claim 16 wherein said combining said one or more maximum likelihood metrics and said one or more symbol-domain parity metrics is a linear combining.
18. The method of claim 16 wherein said combining said one or more maximum likelihood metrics is a nonlinear combining.
19. The method of claim 16 comprising varying, by said sequence estimation circuitry, a manner in which combining said one or more maximum likelihood metrics and said one or more symbol-domain parity metrics is performed based on a measured performance metric.
20. The method of claim 11 , wherein each of said plurality of symbols is an N-QAM symbol, where N is an integer.