Resource Allocation with Successive Coding for OFDM-Based Cognitive System Subject to Statistical CSI

This paper investigates the resource allocation problem for a multicarrier underlay cognitive radio system, under the assumption that only statistical Channel State Information (CSI) about the primary channels is available at the secondary user. More specifically, we maximize the system utility under primary and secondary user outage constraints and the total power constraint. The secondary user transmission is also constrained by the interference threshold imposed by the primary user. Moreover, the secondary receiver adapts its decoding strategy, which is either treating interference as noise or using successive interference cancellation or superposition coding. This leads to a nonconvex optimization problem, with either perfect or statistical CSI. Consequently, we propose a sequential-based algorithm to efficiently obtain a solution to the problem. The simulation results show that the sequential algorithm is convergent and that our global proposed scheme achieves larger secondary and sum rates than other algorithms where the decoding strategy is not adapted.