Robust Resource Optimization for Cooperative Cognitive Radio Networks
with Imperfect CSI
Abstract:
We develop robust resource-allocation schemes for a cognitive radio
network (CRN), where the secondary users (SUs) try to communicate with
each other from different small cell primary user (PU) networks. User
cooperation technique is considered for communication among the SUs
since PUs are in close proximity and there are tight interference constraints
on the PU bands. Power allocation and relay selection schemes are
optimized with the provision of quality of service to each SU considering
different channel uncertainty models. We incorporate the channel outage
events that have resulted from the imperfect channel state information
under slow-fading channels in our resource optimization algorithms. We
maximize the system goodput of the CRN while satisfying the interference
constraints of the PU bands both probabilistically and for the worst case
scenario. The original probabilistic optimization problem is approximated
and transformed into a convex deterministic form, and a closed-form
analytical solution for power allocation is derived. The closed-form power
allocation solution helps us to develop an efficient relay selection scheme
based on Hungarian algorithm. Simulation results reveal the effectiveness
of our proposed schemes and the implications of ignoring the
imperfectness among different channels when developing resourceallocation algorithms for CRNs.