Subchannel-sharing based distributed optimization of ad-hoc cognitive radio network

In this paper, we study the optimization of an adhoc cognitive radio network (CRN) coexisting with a multicell primary radio network (PRN) utilizing spectrum underlay and multi-subchannel communication. To maximize the weighted sum rate (WSR) of the CRN, we utilize the Lagrangian dual composition tool and design a shared subchannel assignment (SSA) duality method assuming discrete-rate modulation. The SSA method allows multiple secondary user (SU) links to share the same subchannel to achieve a higher WSR than the exclusive subchannel assignment (ESA) technique, but suboptimal SSA methods, such as iterative waterfilling (IWF), can provide even lower WSR than ESA. The optimization problem becomes more complicated when the CRN-to-PRN interference constraint has to be strictly satisfied. We design fast-convergent SSA duality schemes and use the interior point search to satisfy various system constraints. Additionally, we design distributed duality schemes which involve only a small number of CRN local information exchanges for dual update. Effects of many system parameters are presented via simulation results, which show that the SSA duality scheme can perform significantly better than the suboptimal ESA duality and SSA-IWF schemes, and that the performance loss of the distributed schemes is small compared to their centralized counterparts.