Input Optimization in the Composite DNA Storage Channel

Recent advancements in DNA storage show that composite DNA letters can significantly enhance storage capacity. We model this process as a multinomial channel and propose an optimization algorithm to determine its capacity-achieving input distribution (CAID) for an arbitrary number of output reads. Our empirical results match a scaling law that determines that the support size grows exponentially with capacity. In addition, we introduce a limited-support optimization algorithm that optimizes the input distribution under a restricted support size, making it more feasible for real-world DNA storage systems. We also extend our model to account for noise and study its effect on capacity and input design.