  In this paper, the problem of opportunistic spectrum sharing for the next
generation of wireless systems empowered by the cloud radio access network
(C-RAN) is studied. More precisely, low-priority users employ cooperative
spectrum sensing to detect a vacant portion of the spectrum that is not
currently used by high-priority users. The design of the scheme is to maximize
the overall throughput of the low-priority users while guaranteeing the quality
of service of the high-priority users. This objective is attained by optimally
adjusting spectrum sensing time with respect to imposed target probabilities of
detection and false alarm as well as dynamically allocating and assigning C-RAN
resources, i.e., transmit powers, sub-carriers, remote radio heads (RRHs), and
base-band units. The presented optimization problem is non-convex and NP-hard
that is extremely hard to tackle directly. To solve the problem, a low-complex
iterative approach is proposed in which sensing time, user association
parameters and transmit powers of RRHs are alternatively assigned and optimized
at every step. Numerical results are then provided to demonstrate the necessity
of performing sensing time adjustment in such systems as well as balancing the
sensing-throughput tradeoff.
