Outage and throughput performance of cognitive radio based power domain based multiple access

This paper considers power domain based multiple access (PDMA) in cognitive radio network to serve numerous users who intend to multiple access to core network. In particular, we investigate the effect of signal combination scheme equipped at PDMA end-users as existence of direct link and relay link. This system model using relay scheme provides performance improvement on the outage probability of two PDMA end-users. We first propose a simple scheme of fixed power allocation to PDMA users who exhibit performance gap and fairness. Inspired by PDMA strategy, we then find signal to noise ratio (SNR) to detect separated signal for each user. In addition, the exact expressions of outage probability are derived in assumption that receiver can cancel out the interference completely with successive interference cancellation (SIC). By exploiting theoretical and simulation results, both considered combination schemes (Maximal Ratio Combining (MRC) and Selection Combining (SC) can achieve improved performance of two PDMA users significantly

Secrecy rate maximization for cooperative overlay cognitive radio networks with artificial noise

We consider physical-layer security in a novel MISO cooperative overlay cognitive radio network (CRN) with a single eavesdropper. We aim to design an artificial noise (AN) aided secondary transmit strategy to maximize the joint achievable secrecy rate of both primary and secondary links, subject to a global secondary transmit power constraint and guaranteeing any transmission of secondary should at least not degrade the receive quality of primary network, under the assumption that global CSI is available. The resulting optimization problem is challenging to solve due to its non-convexity in general. A computationally efficient approximation methodology is proposed based on the semidefinite relaxation (SDR) technique and followed by a two-step alternating optimization algorithm for obtaining a local optimum for the corresponding SDR problem. This optimization algorithm consists of a one-dimensional line search and a non-convex optimization problem, which, however, through a novel reformulation, can be approximated as a convex semidefinite program (SDP). Analysis on the extension to multiple eavesdroppers scenario is also provided. Simulation results show that the proposed AN-aided joint secrecy rate maximization design (JSRMD) can significantly boost the secrecy performance over JSRMD without AN