In this article, we propose a deep Q-learning based algorithm for optimal resource allocation
in energy harvested cognitive radio networks (EH-CRN). In EH-CRN, channel resources of …

In this paper, a reinforcement learning technique is employed to maximize the performance
of a cognitive radio network (CRN). In the presence of primary users (PUs), it is presumed …

The present work explores a multihop cognitive radio network model that adopts energy
harvesting (EH) and reinforcement learning based Q-routing. An optimization problem is …

In this paper, an underlay cognitive radio network with energy harvesting is considered
which works in slotted mode. SU decides to transmit data or harvest energy from …

The energy harvesting cognitive wireless sensor network (EHCWSN) introduces energy
harvesting technology and cognitive radio technology into the traditional wireless sensor …

Cognitive radio (CR) and energy harvesting (EH) have been deemed two promising
technologies in the spectrum-scarce and energy-limited wireless networks. In this paper, the …

Spectrum scarcity and energy limitation are becoming two critical issues in designing
Internet of Things (IoT). As two promising technologies, cognitive radio (CR) and radio …

The present work explores mitigation in end-to-end outage probability in an energy
harvesting (EH) enabled cognitive radio networks (CRNs) through reinforcement learning …

A wideband cognitive radio network relying on energy harvesting is studied under a
practically non-linear energy harvesting model. In order to efficiently exploit the harvesting …

An optimal power allocation (OPA) policy for orthogonal frequency division multiplexing
(OFDM)-based cognitive radio networks (CRNs) using underlay spectrum access model is …