Analog decoding of product codes

Journal ArticleA design approach is presented for soft-decision decoding of block product codes ("block turbo codes") using analog computation with MOS devices. Application of analog decoding to large code sizes is also considered with the introduction of serial analog interfaces and pipeline schedules

Analog decoding of product codes

Journal ArticleAbstract - A method is presented for analog softdecision decoding of block product codes (block turbo codes). Extrinsic information is exchanged as analog signals between component row and column decoders. The component MAP decoders use low-power analog computation in subthreshold CMOS circuits to implement the sum-product algorithm. An example decoder design is presented for a (16,ll)? Hamming code

Analog decoding of product codes

Journal ArticleA design approach is presented for soft-decision decoding of block product codes ("block turbo codes") using analog computation with MOS devices. Application of analog decoding to large code sizes is also considered with the introduction of serial analog interfaces and pipeline schedules

Stochastic multiple-stream decoding of Cortex codes

International audienceCortex codes are short length block codes having a large Hamming distance. Their modular construction, based on simple and very short block codes, yield to difficulties in efficiently decoding them with digital decoders implementing the Sum-Product algorithm. However, this construction lends itself to analog decoding with performance close to ML decoding as was recently demonstrated. A digital decoding method close to analog decoding is stochastic decoding. This paper brings the two together to design a Cortex stochastic architecture with good decoding performance. Moreover, the proposed stochastic decoder architecture is simplified when compared to the customary one. Instead of edge or tracking forecast memories the proposed architecture uses multiple streams to represent the same probability and deterministic shufflers. This results in a more efficient architecture in terms of ratio between data throughput and hardware complexity. Finally, the proposed method offers decoding performance similar to a Min-Sum decoder with 50 iterations