In cognitive radio (CR) networks, efficient and reliable spectrum sensing is essential for opportunistic spectrum access. However, energy consumption remains a critical limitation, particularly in environments where power sources are constrained. This paper investigates a novel spectrum sensing framework where the primary source is powered via energy harvesting from ambient vibrations. The harvested energy is used to transmit a signal to the primary user (PU), which then performs spectrum sensing using an energy detection technique. We develop an analytical model to capture the behaviour of the vibration-powered primary transmitter and its impact on the received signal's energy characteristics at the PU. The proposed system combines two key technologies energy harvesting and cognitive sensing and presents a sustainable, low-power sensing mechanism suitable for remote or infrastructure-less deployments. Simulation results validate the theoretical findings, demonstrating how the energy availability, determined by the vibration profile, affects the detection probability.
Majed Abdouli (2026) studied this question.