  One of the major challenges in Dynamic Spectrum Access (DSA) systems is to
guarantee a required level of Quality of Service (QoS) to secondary users of
the spectrum. In this paper, we propose efficient algorithms for deriving
optimal policies for the sensing / transmitting trade-off in
hardware-constrained DSA systems. Unlike previous approaches which seek to
maximize mean data rate for the secondary users, the proposed algorithms derive
policies which minimize the probability of excessive queuing delays. Large
Deviations (LD) asymptotics are used to approximate the probability of interest
and policies maximizing the associated LD exponent are proposed. Although
dynamic programming is not able to identify the optimal policy in this case,
much more efficient algorithms than exhaustive search are proposed. These
algorithms are based on specific properties of the optimal policy which are
described and proven in this paper.
