A New XOR-Free Approach for Implementation of Convolutional Encoder

Abstract

This letter presents a new algorithm to construct an XOR-Free architecture of a power efficient Convolutional Encoder. Optimization of XOR operators is the main concern while implementing polynomials over GF(2), which consumes a significant amount of dynamic power. The proposed approach completely removes the XOR-processing operation of a chosen nonsystematic, feed-forward generator polynomial and reduces the logical operators, thereby the encoding cost. Hardware (HW) implementation of the proposed design uses Read-only memory (ROM) with a preprocessed addressing operations to reduce ROM size by nearly 50%. The results of the new architecture reduce the dynamic power up to 21.4% and HW cost up to 15% with lesser design complexity as compared to conventional method. The Hardware cosimulation of the architecture is first validated and then implemented with Xilinx Virtex-V FPGA.