Motorola Corporation

Frederic Fontaine

James Joseph Kosmach

Abdulkadir Dinc

Stephen B Wicker

A system and method for decoding a block code includes receiving a first word. The first word includes parity bit values and information bit values. A first partial word including the information bit values and a first subset of the parity bit values is generated. The first partial word is decoded to generate a first refined word. The first refined word includes a first set of refined information bit values. A second partial word including the first set of refined information bit values and a second subset of the parity bit values is generated. The second partial word is decoded to generate a second refined word, the second refined word including a second set of refined information bit values.

Method and apparatus for turbo decoding block codes

A receiver includes a detector and a decoder. The detector is adapted to demodulate a received signal to generate a received word. The received word includes a plurality of symbols, and each symbol contains data associated with a first phase and data associated with a second phase. The detector is further adapted to generate a plurality of energy values relating each received symbol to one of a plurality of potential symbols. The decoder is adapted to generate a first set of bit metrics based on the energy values in response to the receiver being assigned to the first phase and a second set of bit metrics based on the energy values in response to the receiver being assigned to the second phase. The decoder is further adapted to identify the least reliable bits in the received word based on one of the first and second sets of bit metrics.

Method and apparatus for assigning bit metrics for soft decision decoding

A method for improved decoding of received convolutionally coded input data uses data scaling to provide near ideal turbo decoding. The method includes a first step of loading a portion of the input data into a buffer. A next step includes calculating a mean of the data in the portion of the input data. A next step includes computing a root-mean-square value of the portion of the input data using the mean from the calculating step. A next step includes deriving a scaling factor from the root-mean-square value of the computing step, and a next step includes scaling the portion of input data by the scaling factor of the deriving step.

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New York, NY, United States of America

Frederic Fontaine