Method for iterative and non-iterative data detection using reduced-state soft-input/soft-output algorithms for complexity reduction

A method for generating higher confidence information on data inputs of a process modeled as a finite state machine (FSM) represented by a reduced-state trellis, the FSM receiving a plurality of FSM inputs and producing a plurality of FSM outputs, the FSM inputs being defined on a base set of symbols, the method comprising:

• (a) inputting said soft decision information in a first index set;
• (b) performing forward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a forward truncated survivor path comprising decisions not specified by the reduced-state trellis, to produce forward state metrics and forward transition metrics;
• (c) performing backward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a backward truncated survivor path comprising decisions not specified by the reduced-state trellis, the backward truncated survivor path being distinct from the forward truncated survivor path, to produce backward state metrics and backward transition metrics;
• (d) operating on said forward state metrics, said forward state transition metrics, said backward state metrics and said backward state transition metrics to produce said higher confidence information;
• and
• (e) outputting said higher confidence information.

A system for generating higher confidence information on data inputs of a process modeled as a finite state machine (FSM) represented by a reduced-state trellis, the FSM receiving a plurality of FSM inputs and producing a plurality of FSM outputs, the FSM inputs being defined on a base set of symbols, the system comprising:

• means for inputting said soft decision information in a first index set;
• means for performing forward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a forward truncated survivor path comprising decisions not specified by the reduced-state trellis, to produce forward state metrics;
• means for performing backward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a backward truncated survivor path comprising decisions not specified by the reduced-state trellis, the backward truncated survivor path being distinct from the forward truncated survivor path, to produce backward state metrics;
• means for operating on said forward state metrics and said backward state metrics to produce said higher confidence information;
• and
• means for outputting said higher confidence information.

A system for generating higher confidence information on data inputs of a process modeled as a finite state machine (FSM) represented by a reduced-state trellis, the FSM receiving a plurality of FSM inputs and producing a plurality of FSM outputs, the FSM inputs being defined on a base set of symbols, the system comprising:

• means for inputting said soft decision information in a first index set;
• means for performing forward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a forward truncated survivor path comprising decisions not specified by the reduced-state trellis, to produce forward state metrics and forward state transition metrics;
• means for performing backward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a backward truncated survivor path comprising decisions not specified by the reduced-state trellis, the backward truncated survivor path being distinct from the forward truncated survivor path, to produce backward state metrics and backward state transition metrics;
• means for operating on said forward state metrics, said forward state transition metrics, said backward state metrics and said backward state transition metrics to produce said higher confidence information;
• and
• means for outputting said higher confidence information.

A device for generating higher confidence information on data inputs of a process modeled as a finite state machine (FSM) represented by a reduced-state trellis, the FSM receiving a plurality of FSM inputs and producing a plurality of FSM outputs, the FSM inputs being defined on a base set of symbols, the device comprising:

• a plurality of device inputs for inputting said soft decision information in a first index set;
• a plurality of processing units for performing forward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a forward truncated survivor path comprising decisions not specified by the reduced-state trellis, to produce forward state metrics, performing backward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a backward truncated survivor path comprising decisions not specified by the reduced-state trellis, the backward truncated survivor path being distinct from the forward truncated survivor path, to produce backward state metrics, and operating on said forward state metrics and said backward state metrics to produce said higher confidence information;
• and
• a plurality of device outputs for outputting said higher confidence information.

A device for generating higher confidence information on data inputs of a process modeled as a finite state machine (FSM) represented by a reduced-state trellis, the FSM receiving a plurality of FSM inputs and producing a plurality of FSM outputs, the FSM inputs being defined on a base set of symbols, the device comprising:

• a plurality of device inputs for inputting said soft decision information in a first index set;
• a plurality of processing units for performing forward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a forward truncated survivor path comprising decisions not specified by the reduced-state trellis, to produce forward state metrics and forward state transition metrics, performing backward recursion calculations on said reduced-state trellis representation using said input soft decision information and using a backward truncated survivor path comprising decisions not specified by the reduced-state trellis, the backward truncated survivor path being distinct from the forward truncated survivor path, to produce backward state metrics and backward state transition metrics, and operating on said forward state metrics, said forward state transition metrics, said backward state metrics and said backward state transition metrics to produce said higher confidence information;
• and
• a plurality of device outputs for outputting said higher confidence information.