Operating characteristics of underlay cognitive relay networks

Understanding the performance of cognitive relay networks (CRNs) is of great interest. Recently, stochastic geometry is being used to model and characterize the performance of CRNs. It is a known fact that sensing is an integral part of the CRN, however, in most cases it is not perfect. Moreover, the model inaccuracies caused by simplifications and/or approximations when deriving the analytical expressions for characterizing CRNs may distort their true performance. With no sensing in the system, we determine a lower performance bound (LPB) that can be used to judge the reliability of other systems that include sensing and model approximations. Based on the LPB, the operating characteristics (OC) for the CRN are obtained, which determine the joint performance of the primary and secondary system. Finally, OC are used to investigate the system performance under different scenarios.