Inner and outer decoding performance of Convolutional codes

Convolutional codes are used extensively in numerous applications in order to achieve reliable data transfer. In this paper, the parameters of Convolutional codes are introduced and used to investigate its applications, characteristics and performance when employed as inner and outer code in decoding method. To evaluate the parameters, four schemes of Convolutional codes: non-systematic-recursive, systematic-recursive, non-systematic-non-recursive and systematic-non-recursive; are applied. In addition, the implementation of BCJR (Bahl, Cocke, Jelinek and Raviv) algorithm is discussed by applying APP-SISO (a posteriori probabilities - Soft Input Soft Output) decoding for Convolutional codes. The proposed scheme employing inner and outer decoding of Convolutional codes are analysed and compared by using EXIT characteristic of Convolutional decoders. The channel capacity measurements for different rates inner Convolutional codes are described by using BPSK modulation over AWGN channel. BER performances of outer decoding of Convolutional codes are observed for different schemes which are described the process of area beneath in the inverted EXIT function. This is essential to obtain better performance of BER plot indeed. The result shows that inner decoding of Convolutional codes is the best performance for the EXIT function, particularly for non-systematic-recursive. However, outer decoding of this code has not good performance due to having quite larger area beneath than inner code.