Table based decoding of rate one-half convolutional codes

Table based error correction and decoding of rate one-half convolutional codes is described. A new class of fast-decodeable locally invertible convolutional codes based on a one-to-one mapping between information and encoded blocks of equal lengths is defined. The syndrome is used as an address to access a correction table which stores pre-computed correction information. The correction table generation process is described and a specific table based correction algorithm is given. Performance of this scheme is analyzed and simulation results are presented.<>