  We formulate the interaction between the communicating nodes and an adversary
within a game-theoretic context. We show that earlier information-theoretic
capacity results for a jammed channel correspond to a pure Nash Equilibrium
(NE). However, when both players are allowed to randomize their actions (i.e.,
coding rate and jamming power) new mixed Nash equilibria appear with surprising
properties. We show the existence of a threshold ($J_{TH}$) such that if the
jammer average power exceeds $J_{TH}$, the channel capacity at the NE is the
same as if the jammer was using its maximum allowable power, $J_{Max}$, all the
time. This indicates that randomization significantly advantages powerful
jammers. We also show how the NE strategies can be derived, and we provide very
simple (e.g., semi-uniform) approximations to the optimal communication and
jamming strategies. Such strategies are very simple to implement in current
hardware and software.
