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This paper presents the first wireless and programmable neural stimulator leveraging magnetoelectric (ME) effects for power and data transfer. Thanks to low tissue absorption, low misalignment sensitivity and high power transfer efficiency, the ME effect enables safe delivery of high power levels (a few milliwatts) at low resonant frequencies (~250 kHz) to mm-sized implants deep inside the body (30-mm depth). The presented MagNI (Magnetoelectric Neural Implant) consists of a 1.5-mm$^2$ 180-nm CMOS chip, an in-house built 4x2 mm ME film, an energy storage capacitor, and on-board electrodes on a flexible polyimide substrate with a total volume of 8.2 mm$^3$ . The chip with a power consumption of 23.7 $mu$W includes robust system control and data recovery mechanisms under source amplitude variations (1-V variation tolerance). The system delivers fully-programmable bi-phasic current-controlled stimulation with patterns covering 0.05-to-1.5-mA amplitude, 64-to-512-$mu$s pulse width, and 0-to-200Hz repetition frequency for neurostimulation.
The high reflect beamforming gain of the intelligent reflecting surface (IRS) makes it appealing not only for wireless information transmission but also for wireless power transfer. In this letter, we consider an IRS-assisted wireless powered communi
Mobile-edge computing (MEC) and wireless power transfer are technologies that can assist in the implementation of next generation wireless networks, which will deploy a large number of computational and energy limited devices. In this letter, we cons
Future IoT networks consist of heterogeneous types of IoT devices (with various communication types and energy constraints) which are assumed to belong to an IoT service provider (ISP). To power backscattering-based and wireless-powered devices, the
In this paper, a novel intelligent reflecting surface (IRS)-assisted wireless powered communication network (WPCN) architecture is proposed for low-power Internet-of-Things (IoT) devices, where the IRS is exploited to improve the performance of WPCN
The rapid growth of the so-called Internet of Things is expected to significantly expand and support the deployment of resource-limited devices. Therefore, intelligent scheduling protocols and technologies such as wireless power transfer, are importa