CONVOLUTIONAL APPROACH FOR DECODING FEC IN LTE AND WiMAX SYSTEMS THROUGH UBP ALGORITHM

Forward Error correcting Codes (FEC) is a technique used for controlling errors in data transmission over unreliable or noisy communication channels. This scheme is overhead in many wireless communication systems, even though they have enhanced data rates for the GSM evolution (EDGE), because, worldwide interoperability for microwave access (WiMAX) and long term evolution (LTE) have adopted low-density parity-check (LDPC). There are many efficient algorithms for decoding these codes. However, the different decoding approaches for these two families of codes usually lead to different hardware architectures. The belief propagation BP algorithm provides a highly effective general methodology for devising low-complexity iterative decoding algorithms for all convolutional code classes as well as turbo codes. In this paper, we exploit the parity-check matrix (H) representation of tailbiting convolutional and turbo codes, enabling decoding through a unified belief propagation (UBP) algorithm. This unified propagation and scaling algorithm reduces to a convergent alternative to loopy belief propagation when no constraints are present. While a small performance loss is observed when decoding turbo codes with BP, this is offset by the lower complexity of the BP algorithm and the inherent advantage of a unified decoding architecture.