Abstract: In a packet-based data transmission including incremental redundancy (IR) protocols, the memory consumption of the IR protocol is reduced by compressing and storing failed data units in their punctured format. The failed data units are compressed using low complexity compression/decompression algorithms. The compression algorithm includes two parts: calculating and storing a scale factor for each transmission burst that estimates the soft values in the burst, and storing each soft values' sign in local memory instead of the complete soft value. If the currently received data unit is a retransmission, its compressed versions in the punctured format stored in the IR memory are decompressed, de-punctured and combined with the currently received data unit. The combined data unit is then decoded. The decompression restores an estimated soft-value by multiplying the sign value stored in the IR memory with its corresponding scale factor obtained from a mapping table.

Abstract: In a packet-based data transmission including incremental redundancy (IR) protocols, the memory consumption of the IR protocol is reduced by compressing and storing failed data units in their punctured format. The failed data units are compressed using low complexity compression/decompression algorithms. The compression algorithm includes two parts: calculating and storing a scale factor for each transmission burst that estimates the soft values in the burst, and storing each soft values' sign in local memory instead of the complete soft value. If the currently received data unit is a retransmission, its compressed versions in the punctured format stored in the IR memory are decompressed, de-punctured and combined with the currently received data unit. The combined data unit is then decoded. The decompression restores an estimated soft-value by multiplying the sign value stored in the IR memory with its corresponding scale factor obtained from a mapping table.

Abstract: In a packet-based data transmission including incremental redundancy (IR) protocols, the memory consumption of the IR protocol is reduced by compressing and storing failed data units in their punctured format. The failed data units are compressed using low complexity compression/decompression algorithms. The compression algorithm includes two parts: calculating and storing a scale factor for each transmission burst that estimates the soft values in the burst, and storing each soft values' sign in local memory instead of the complete soft value. If the currently received data unit is a retransmission, its compressed versions in the punctured format stored in the IR memory are decompressed, de-punctured and combined with the currently received data unit. The combined data unit is then decoded. The decompression restores an estimated soft-value by multiplying the sign value stored in the IR memory with its corresponding scale factor obtained from a mapping table.

Abstract: A computationally efficient method for computing the filter coefficients for a prefilter in a decision feedback equalizer solves linear equations using a fast Toeplitz algorithm. Computations performed to compute the filter coefficients for the right half burst may be used to compute the prefilter for the left hand burst, thereby reducing the number of computations. Also, a square root-free algorithm may be used to solve the system of linear equations, further reducing computational complexity.

Abstract: A digital radio communications system including a suboptimal soft decision (e.g., errors and erasures) channel decoder and a speech decoder can be upgraded to effectively bypass the hard decision channel decoder and allow a higher performance soft decision (e.g., maximum likelihood sequence estimate (MLSE)) decoder to be used--without requiring physical removal or disconnection of the hard decision channel decoder. The new decoder can feed the existing decoder the right choice of received vector r' to force the existing decoder to produce a certain codeword y' and a certain bit error estimate b'. This technique is useful to test new MLSE decoders on existing radios, or to add an MLSE decoder as an upgrade on existing receivers.