On the Decoding of Certain Generalized Concatenated Convolutional Codes

Concatenated Convolutional Codes Jung-Fu Cheng [email protected] Abstract Two classes of generalized concatenated (GC) codes with convolutional outer codes are studied. The rst class is based on the classical Plotkin ja bjbj construction. A new suboptimal multi-stage soft decision algorithm is proposed and the corresponding performance bounds are obtained. These codes are shown to achieve better performance than conventional convolutional codes with equal or less decoding complexity, and are capable of unequal error protection. The Plotkin construction is then generalized using an inner di erential encoding structure to obtain a second class of GC codes. A low-complexity two-iteration decoding algorithm using traditional hard-output Viterbi decoders is proposed. Numerical results show that the new coding systems can achieve comparable and sometimes superior performance to low-complexity turbo codes with similar computational complexity.