Throughput enhancement of cognitive radio networks-nonorthogonal multiple access with energy harvesting and adaptive transmit power

In this article, we derive the theoretical throughput of cognitive radio networks using nonorthogonal multiple access with energy harvesting nodes. We also optimize both power allocation coefficients and harvesting duration to maximize the throughput. In the primary network, there are a primary source and a primary destination. The secondary network contains a secondary source, K relays R-k, and N nonorthogonal multiple access users D-i. Secondary source and relays harvest energy from radio frequency signals received from node A. Secondary nodes adapt their powers to generate low interference at primary destination. We also suggest two strategies for user classification using average or instantaneous channel gains while taking into account the interference from primary source. We show that users' ranking using instantaneous channel gains offers the largest throughput. In addition, the suggested optimal power allocation and optimal harvesting duration allow to increase the throughput. Our theoretical derivations are also compared with computer simulations performed in the presence of Rayleigh fadingchannels.