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1. (WO2008059360) APPARATUS, METHOD, AND COMPUTER PROGRAM PRODUCTS UTILIZING A GENERALIZED TURBO PRINCIPLE
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CLAIMS

What is claimed is:

1. A method comprising:
receiving an encoded signal (501); and
decoding the received signal using a generalized Turbo principle wherein region beliefs are exchanged between components (502).

2. A method as in claim 1 , wherein the components comprise elements of a structure representing at least one of a code, a communication channel, users in a multi-user system and other components for which a traditional Turbo principle may be employed.

3. A method as in claim 1 or 2, wherein the components may be represented by Markov random fields.

4. A method as in any one of claims 1 -3, wherein the components comprise at least two Markov chains.

5. A method as in claim 4, wherein one of the at least two Markov chains corresponds to a convolutive communication channel and another of the at least two Markov chains corresponds to a convolutional code.

6. A method as in claim 4, wherein at least two Markov chains correspond to a Turbo-like code.

7. A method as in any one of claims 1-6, wherein the method is utilized by a wireless communication system.

8. A method as in any one of claims 1-7, wherein the method is implemented by a computer program.

9. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine for performing operations, said operations comprising:
receiving an encoded signal; and
decoding the received signal using a generalized Turbo principle wherein region beliefs are exchanged between components.

10. A program storage device as in claim 9, wherein the components comprise elements of a structure representing at least one of a code, a communication channel, users in a multi-user system and other components for which a traditional Turbo principle may be employed.

11. A program storage device as in claim 9 or 10, wherein the components may be represented by Markov random fields.

12. A program storage device as in any one of claims 9-11, wherein the components comprise at least two Markov chains, and wherein one of the at least two Markov chains corresponds to a convolutive communication channel and another of the at least two Markov chains corresponds to a convolutional code.

13. A program storage device as in any one of claims 9-12, wherein the components comprise at least two Markov chains corresponding to a Turbo-like code.

14. A program storage device as in any one of claims 9-13, wherein the program storage device comprises an element of a wireless communication system.

15. An apparatus comprising :
means for receiving (22) an encoded signal; and
means for decoding (44) the received signal using a generalized Turbo principle wherein region beliefs are exchanged between components.

16. An apparatus as in claim 15, wherein the components comprise elements of a structure representing at least one of a code, a communication channel, users in a multiuser system and other components for which a traditional Turbo principle may be employed.

17. An apparatus as in claim 15 or 16, wherein the components may be represented by Markov random fields.

18. An apparatus as in any one of claims 15-17, wherein the components comprise at least two Markov chains, and wherein one of the at least two Markov chains corresponds to a convolutive communication channel and another of the at least two Markov chains corresponds to a convolutional code.

19. An apparatus as in any one of claims 15-18, wherein the components comprise at least two Markov chains corresponding to a Turbo-like code.

20. An apparatus as in any one of claims 15-19, wherein the apparatus comprises an element of a wireless communication system.

21. An apparatus as in any one of claims 15-20, further comprising: means for encoding a signal (38) such that the encoded signal is configured to be decoded utilizing the generalized Turbo principle and means for transmitting (22) the encoded signal.

22. A method for generating a graph structure for a system having a plurality of components, comprising:
defining a set of primary regions, each primary region comprising one observation and a corresponding set of variables required for conditional independence of the observation (601); and
defining a set of secondary regions describing intersections between two primary regions, wherein said intersections are in accordance with a component structure of the plurality of components, wherein each component specifies a subset of the set of secondary regions, wherein the set of primary regions and the set of secondary regions comprise the generated graph structure (602).

23. A method as in claim 22, wherein the generated graph structure is representative of at least two intersecting Markov chains, wherein the set of secondary regions describes intersections between primary regions in accordance with the at least two Markov chains, wherein each Markov chain specifies a subset of the set of secondary regions.

24. A method as in claim 22 or 23, further comprising: optimizing the generated graph structure by performing at least one of direct loop removal, merging and enlarging regions in order to minimize loop feedback while balancing an increase in complexity with at least one performance requirement, wherein said optimizing utilizes said intersections or at least one subset of said intersections.

25. A method as in any one of claims 22-24, further comprising: performing generalized belief propagation on the generated graph structure, wherein an exchange of information is handled by an exchange of region beliefs.

26. A method as in any one of claims 22-25, further comprising: utilizing the generated graph structure to decode a signal.

27. A method as in any one of claims 22-26, wherein the method is utilized by a wireless communication system.

28. A method as in any one of claims 22-27, wherein the method is implemented by a computer program.

29. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine for performing operations for generating a graph structure for a system having a plurality of components, said operations comprising:
defining a set of primary regions, each primary region comprising one observation and a corresponding set of variables required for conditional independence of the observation; and
defining a set of secondary regions describing intersections between two primary regions, wherein said intersections are in accordance with a component structure of the plurality of components, wherein each component specifies a subset of the set of secondary regions, wherein the set of primary regions and the set of secondary regions comprise the generated graph structure.

30. A program storage device as in claim 29, wherein the generated graph structure is representative of at least two intersecting Markov chains, wherein the set of secondary regions describes intersections between primary regions in accordance with the at least two Markov chains, wherein each Markov chain specifies a subset of the set of secondary regions.

31. A program storage device as in claim 29 or 30, said operations further comprising: optimizing the generated graph structure by performing at least one of direct loop removal, merging and enlarging regions in order, to minimize loop feedback while balancing an increase in complexity with at least one performance requirement, wherein said optimizing utilizes said intersections or at least one subset of said intersections.

32. A program storage device as in any one of claims 29-31, the operations further comprising: performing generalized belief propagation on the generated graph structure, wherein an exchange of information is handled by an exchange of region beliefs.

33. A program storage device as in any one of claims 29-32, the operations further comprising: utilizing the generated graph structure to decode a signal.

34. A program storage device as in any one of claims 29-33, wherein the program storage device comprises an element of a wireless communication system.

35. An apparatus comprising:
means for defining a set of primary regions (18), each primary region comprising one observation and a corresponding set of variables required for conditional independence of the observation; and
means for defining a set of secondary regions (18) describing intersections between two primary regions, wherein said intersections are in accordance with a component structure of a plurality of components of a system, wherein each component specifies a subset of the set of secondary regions,
wherein the set of first regions and the set of second regions comprise a generated graph structure.

36. An apparatus as in claim 35, wherein the generated graph structure is representative of at least two intersecting Markov chains, wherein the set of secondary regions describes intersections between primary regions in accordance with the at least two Markov chains, wherein each Markov chain specifies a subset of the set of secondary regions.

37. An apparatus as in claim 35 or 36, further comprising: means for optimizing the generated graph structure by performing at least one of direct loop removal, merging and enlarging regions in order to minimize loop feedback while balancing an increase in complexity with at least one performance requirement, wherein said means for optimizing utilizes said intersections or at least one subset of said intersections.

38. An apparatus as in any one of claims 35-37, further comprising: means for performing generalized belief propagation on the generated graph structure, wherein an exchange of information is handled by an exchange of region beliefs.

39. An apparatus as in any one of claims 35-38, further comprising: means for decoding a signal utilizing the generated graph structure.

40. An apparatus as in any one of claims 35-39, wherein the apparatus comprises an element of a wireless communication system.

41. An apparatus as in any one of claims 35-40, further comprising: means for storing the generated graph structure.

42. An apparatus as in any one of claims 35-41, wherein the apparatus comprises: a terminal or a base station.

43. Ail apparatus comprising:
a receiver (22) configured to receive an encoded signal; and
a decoder (44) configured to decode the received signal using a generalized

Turbo principle wherein region beliefs are exchanged between components.

44. An apparatus as in claim 43, wherein the components comprise elements of a structure representing at least one of a code, a communication channel, users in a multiuser system and other components for which a traditional Turbo principle may be employed.

45. An apparatus as in claim 43 or 44, wherein the components may be represented by Markov random fields.

46. An apparatus as in any one of claims 43-45, wherein the components comprise at least two Markov chains, and wherein one of the at least two Markov chains corresponds to a convolutive communication channel and another of the at least two Markov chains corresponds to a convolutional code.

47. An apparatus as in any one of claims 43-46, wherein the components comprise at least two Markov chains corresponding to a Turbo-like code.

48. An apparatus as in any one of claims 43-47, wherein the apparatus comprises an element of a wireless communication system.

49. An apparatus as in any one of claims 43-48, further comprising: an encoder (38) configured to encode a signal such that the encoded signal is configured to be decoded utilizing the generalized Turbo principle and a transmitter (22) configured to transmit the encoded signal.

50. An apparatus comprising:
a processor (18) configured to define a set of primary regions and to define a set of secondary regions describing intersections between two primary regions, wherein the set of first regions and the set of second regions comprise a generated graph structure; and
a memory (20) configured to store the generated graph structure, wherein each primary region comprises one observation and a corresponding set of variables required for conditional independence of the observation, wherein said intersections are in accordance with a component structure of a plurality of components of a system.

51. An apparatus as in claim 50, wherein the generated graph structure is representative of at least two intersecting Markov chains, wherein the set of secondary regions describes intersections between primary regions in accordance with the at least two Markov chains, wherein each Markov chain specifies a subset of the set of secondary regions.

52. An apparatus as in claim 50 or 51 , wherein the processor is further configured to optimize the generated graph structure by performing at least one of direct loop removal, merging and enlarging regions in order to minimize loop feedback while balancing an increase in complexity with at least one performance requirement, wherein said optimizing utilizes said intersections or at least one subset of said intersections.

53. An apparatus as in any one of claims 50-52, wherein the processor is further configured to perform generalized belief propagation on the generated graph structure, wherein an exchange of information is handled by an exchange of region beliefs.

54. An apparatus as in any one of claims 50-53, further comprising: a decoder (44) configured to decode a signal utilizing the generated graph structure.

55. An apparatus as in any one of claims 50-54, wherein the apparatus comprises an element of a wireless communication system.

56. An apparatus as in any one of claims 50-55, further comprising: a memory (20) configured to store the generated graph structure.

57. An apparatus as in any one of claims 50-56, wherein the apparatus comprises: a terminal or a base station.