Attacking Massive MIMO Cognitive Radio Networks by Optimized Jamming

Massive multiple-input multiple-output (MaMIMO) and cognitive radio networks (CRNs) are two promising technologies for improving spectral efficiency of next-generation wireless communication networks. In this paper, we investigate the problem physical layer security in that jointly use both technologies, named MaMIMO-CRN. Specifically, to vulnerability network, design an optimized attacking scenario MaMIMO-CRNs by a jammer. For having most adversary effect on uplink transmission legitimate MaMIMO-CRN, propose efficient method power allocation The network consists training data phase, these phases attacked jammer using split between them. resulting is non-convex. We thus three different methods solving problem, show under some assumptions, closed-form solution can also be obtained. Our results MaMIMO-CRN It shown increasing number antennas at does not improve network.