Abstract: A method and apparatus for decoding a linear block encoded string of information bits comprising: converting the string into a plurality of codewords. Performing hard and soft decisions on each codeword to generate a hard and soft decision vector. Computing the syndrome and finding the location of the two minimum values by Galois Field Arithmetic. Designating these values LOW1 and LOW2 and xoring with a Nc1, thus generating Nc2. Swapping Nc1 with Nc2 and determining the lowest soft decision value, Min1 and a next lowest value, Min2. The two bit locations creating Min1 are designated as MinA and MinB. MinA being replaced with Min2 minus the value MinA. MinB being replaced with Min2 minus the value at MinB. Generating an output codeword by subtracting Min1 from all other bit locations values and 2's complementing all soft values with 0 in their location. Creating the new soft value vector.

Abstract: A hyper encoder module encodes a block of data having a plurality of sub-blocks. Each sub-block includes a plurality of systematic block code codewords. A parity sub-block is added to the block. The parity sub-block is a first sub-block rotated by a predetermined number of bits. Each subsequent sub-block in the n-dimensional block is rotated by an appropriate number of bits and bit-wise XORed. An encoder method and apparatus which includes the hyper encoder module receives the block of data. A row of the block is immediately output and encoded by a first module according to a first encoding scheme. A column is encoded by a second module according to a second encoding scheme. A second set of encoded data is generated, iteratively updated and output by the second module. The hyper encoder module hyper-diagonally encodes the information bits as described above and then output.

Abstract: A method and apparatus for decoding a linear block encoded string of information bits comprising: converting the string into a plurality of codewords. Performing hard and soft decisions on each codeword to generate a hard and soft decision vector. Computing the syndrome and finding the location of the two minimum values by Galois Field Arithmetic. Designating these values LOW1 and LOW2 and xoring with a Nc1, thus generating Nc2. Swapping Nc1 with Nc2 and determining the lowest soft decision value, Min1 and a next lowest value, Min2. The two bit locations creating Min1 are designated as MinA and MinB. MinA being replaced with Min2 minus the value MinA. MinB being replaced with Min2 minus the value at MinB. Generating an output codeword by subtracting Min1 from all other bit locations values and 2's complementing all soft values with 0 in their location. Creating the new soft value vector.

Abstract: A method and apparatus for decoding a linear block encoded string of information bits comprising: converting the string into a plurality of codewords. Performing hard and soft decisions on each codeword to generate a hard and soft decision vector. Computing the syndrome and finding the location of the two minimum values by Galois Field Arithmetic. Designating these values LOW1 and LOW2 and xoring with a Nc1, thus generating Nc2. Swapping Nc1 with Nc2 and determining the lowest soft decision value, Min1 and a next lowest value, Min2. The two bit locations creating Min1 are designated as MinA and MinB. MinA being replaced with Min2 minus the value MinA. MinB being replaced with Min2 minus the value at MinB. Generating an output codeword by subtracting Min1 from all other bit locations values and 2's complementing all soft values with 0 in their location. Creating the new soft value vector. Some embodiments include a system and method that organizes an encoded codeword.

Abstract: The present invention is a turbo product code decoder decoding multi-dimensional coding schemes. The decoder may be implemented in any digital communication system receiving an encoded stream of data. The decoder is configured for receiving soft decision values. The decoder iteratively decodes the data by generating new soft difference values for each axis-iteration of decoding. These soft difference values represent the change in soft decision values after each axis-iteration. The soft difference values from each axis-iteration are then summed with the original soft decision values in decoding each of the other axis. After any full iteration—i.e. after all axis dimensions have been decoded one full time, the previous difference values for any axis are discarded when that axis is decoded in subsequent iterations. Accordingly, the same information is not continuously fed into the decoder during each subsequent iteration, thereby decreasing the likelihood of error and offering improved decoding.

Abstract: A method and apparatus for decoding a linear block encoded string of information bits comprising: converting the string into a plurality of codewords. Performing hard and soft decisions on each codeword to generate a hard and soft decision vector. Computing the syndrome and finding the location of the two minimum values by Galois Field Arithmetic. Designating these values LOW1 and LOW2 and xoring with a Nc1, thus generating Nc2. Swapping Nc1 with Nc2 and determining the lowest soft decision value, Min1 and a next lowest value, Min2. The two bit locations creating Min1 are designated as MinA and MinB. MinA being replaced with Min2 minus the value MinA. MinB being replaced with Min2 minus the value at MinB. Generating an output codeword by subtracting Min1 from all other bit locations values and 2's complementing all soft values with 0 in their location. Creating the new soft value vector.

Abstract: The present invention is a turbo product code decoder capable of decoding multi-dimensional coding schemes. The decoder may be implemented in any digital communication system capable of receiving an encoded stream of data. The decoder is configured for receiving soft decision values. The decoder iteratively decodes the data by generating new soft difference values for each axis-iteration of decoding. These soft difference values represent the change in soft decision values after each axis-iteration. The soft difference values from each axis-iteration are then summed with the original soft decision values in decoding each of the other axis. After any full iteration—i.e. after all axis dimensions have been decoded one full time, the previous difference values for any axis are discarded when that axis is decoded in subsequent iterations.

Abstract: An RF local oscillator, particularly useful in connection with phase shift key modulation in satellite communications systems, provides a low phase noise signal by use of a phase locked loop having a phase stable oscillator to provide frequency conversion of a frequency synthesizer output signal.

Abstract: In a predetection combiner there is provided AGC amplifier which uses an electronically controlled RF attenuator, such as a PIN-diode attenuator, which is linearly controlled by use of digital signals. A programmed read-only-memory provides a linearity correction for generating the appropriate control voltage for the diode attenuation device.