  The radio network model is a well-studied model of wireless, multi-hop
networks. However, radio networks make the strong assumption that messages are
delivered deterministically. The recently introduced noisy radio network model
relaxes this assumption by dropping messages independently at random.
  In this work we quantify the relative computational power of noisy radio
networks and classic radio networks. In particular, given a non-adaptive
protocol for a fixed radio network we show how to reliably simulate this
protocol if noise is introduced with a multiplicative cost of
$\mathrm{poly}(\log \Delta, \log \log n)$ rounds where $n$ is the number nodes
in the network and $\Delta$ is the max degree. Moreover, we demonstrate that,
even if the simulated protocol is not non-adaptive, it can be simulated with a
multiplicative $O(\Delta \log ^2 \Delta)$ cost in the number of rounds. Lastly,
we argue that simulations with a multiplicative overhead of $o(\log \Delta)$
are unlikely to exist by proving that an $\Omega(\log \Delta)$ multiplicative
round overhead is necessary under certain natural assumptions.

Data Structures and Algorithms;Distributed, Parallel, and Cluster Computing