Abstract
In this thesis, we study a spectrum sharing based cognitive relay-assisted network (CRAN) where $N$ secondary users (SUs) share the same spectrum with a primary user (PU) over block fading channels with the aid of \( N \) secondary relays (SRs). We considered two scenarios where each relay can only serve a particular SU or can be shared by all SUs. both scenarios are operated in full-duplex (FD) mode and decode-and forward (DF) protocol is employed. We assume complete perfect channel state information (CSI) at the secondary transmitters (or secondary sources) and relay transmitters while only local instantaneous CSI is assumed at the primary transmitter. Based on these assumptions, we investigate the optimal probabilistic power allocation that seeks to maximize the system utilities for SUs subject to the primary interference power constraint, and the secondary rate outage constraints and the individual power constraints. To handle the non-convex constraints in the resulting optimization problem, we applied conservative convex first-order approximation techniques. Furthermore, by the successive convex approximation (SCA), we proposed an algorithm that provides high-quality approximate solutions via solving a sequence of convex approximation problems. To demonstrate that the limit point generated by our proposed SCA algorithm is indeed a stationary point of the optimization problem before applying convex approximation, we proposed a suboptimal scheme and verified the convergence proof. Extensive simulations validated our analyses and demonstrated that superior performance is indeed achieved by both our proposed algorithms, where the achieved utilities are close to the optimum. Further simulations results revealed the trade-off between duplex modes and two scenarios.