Sequential differential optimization of incremental redundancy transmission lengths: An example with tail-biting convolutional codes

Abstract

This paper applies the sequential differential optimization (SDO) algorithm to optimize the transmission lengths of incremental redundancy for a 1024-state tail-biting convolutional code. The tail-biting reliability-output Viterbi algorithm is used to determine whether to inform the transmitter that a message has been successfully received or to request that the transmitter provide additional convolutional code bits. In order to maximize the average throughput, SDO is used to determine the rate of the initial codeword and the number of bits of incremental redundancy to be sent in each increment. With the help of SDO, this paper demonstrates a system that achieves 86.3 percent of the binary-input AWGN capacity (for SNR 2 dB) with an average blocklength of 115.5 symbols.