  Assume that an interferer behaves according to a parametric model but one
does not know the value of the model parameters. Sensing enables to improve the
model knowledge and therefore perform a better link adaptation. However, we
consider a half-duplex scenario where, at each time slot, the communication
system should decide between sensing and communication. We thus propose to
investigate the optimal policy to maximize the expected sum rate given a
finite-time communication. % the following question therefore arises: At a
given time slot, should one sense or communicate? We first show that this
problem can be modelled in the Markov decision process (MDP) framework. We then
demonstrate that the optimal open-loop and closed-loop policies can be found
significantly faster than the standard backward-induction algorithm.
