Nonbinary Convolutional Codes and Modified M-FSK Detectors for Power-Line Communications Channel

The Viterbi decoding algorithm, which provides maximum- likelihood decoding, is currently considered the most widelyused technique for the decoding of codes having a state description,including the class of linear error-correcting convolutionalcodes. Two classes of nonbinary convolutional codes are presented. Distance preserving mapping convolutional codes and M-ary convolutionalcodes are designed, respectively, from the distancepreservingmappings technique and the implementation of the conventionalconvolutional codes in Galois fields of order higher thantwo. We also investigated the performance of these codes whencombined with a multiple frequency-shift keying (M-FSK) modulationscheme to correct narrowband interference (NBI) in powerlinecommunications channel. Themodification of certain detectorsof the M-FSK demodulator to refine the selection and the detectionat the decoder is also presented. M-FSK detectors used in oursimulations are discussed, and their chosen values are justified. Interestingand promising obtained results have shown a very stronglink between the designed codes and the selected detector for MFSKmodulation. An important improvement in gain for certainvalues of the modified detectors was also observed. The paper alsoshows that the newly designed codes outperform the conventionalconvolutional codes in a NBI environment.