The impact of different kinds of interleavers on the performance of block Markov superposition transmission (BMST) systems is investigated. Simulation results show that the performance of a BMST system is insensitive to the types of interleavers, provided that multiple interleavers (if required) differ from each other. As a byproduct, a new interleaver called the binary linear interleaver is proposed, which can be easily implemented in hardware.Introduction: Since the invention of turbo codes [1], interleaving together with an iterative decoding algorithm has been considered as a powerful technique in channel coding to approach Shannon's capacity. Usually, different interleavers may have different coding gains [2][3][4]. For example, it was shown in [4] that uniform interleavers [5] perform better than block interleavers in turbo codes if the size of interleavers is medium to large.Block Markov superposition transmission (BMST) [6, 7] is a recently proposed coding scheme that has a capacity-approaching performance over the binary-input additive white Gaussian noise channel (BI-AWGNC). As with other turbo-like codes, BMST codes also require interleavers. An immediate question is, what types of interleavers are suitable for BMST codes? This question is answered in this Letter by a thorough comparative study. We present simulation results of BMST systems constructed with different types and different numbers of interleavers. It is shown that the BMST systems perform well enough, in the sense of matching well with the corresponding lower bounds, with most types of interleavers given that the involved interleavers differ from each other.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.