Performance of DF Incremental Relaying with Energy Harvesting Relays in Underlay CRNs

In this paper, we analyze the throughput performance of incremental relaying using energy harvesting (EH) decode-and-forward (DF) relays in underlay cognitive radio networks (CRNs). The destination combines the direct and relayed signals when the direct link is in outage. From the derived closed-form expressions, we present an expression for the power-splitting parameter of the EH relay that optimizes the throughput performance. We demonstrate that relaying using EH DF relays results in better performance than direct signalling without a relay only when the destination combines the direct signal from the source with the relayed signal. Computer simulations demonstrate accuracy of the derived expressions

Optimization of the overall success probability of the energy harvesting cognitive wireless sensor networks

Wireless energy harvesting can improve the performance of cognitive wireless sensor networks (WSNs). This paper considers radio frequency (RF) energy harvesting from transmissions in the primary spectrum for cognitive WSNs. The overall success probability of the energy harvesting cognitive WSN depends on the transmission success probability and energy success probability. Using the tools from stochastic geometry, we show that the overall success probability can be optimized with respect to: 1) transmit power of the sensors; 2) transmit power of the primary transmitters; and 3) spatial density of the primary transmitters. In this context, an optimization algorithm is proposed to maximize the overall success probability of the WSNs. Simulation results show that the overall success probability and the throughput of the WSN can be significantly improved by optimizing the aforementioned three parameters. As RF energy harvesting can also be performed indoors, hence, our solution can be directly applied to the cognitive WSNs that are installed in smart buildings