During the last years, Graphene based Field Effect Transistors (GFET) have shown outstanding RF performance; therefore, they have attracted considerable attention from the electronic devices and circuits communities. At the same time, analytical models that predict the electrical characteristics of GFETs have evolved rapidly. These models, however, have a complexity level that can only be handled with the help of a circuit simulator. On the other hand, analog circuit designers require simple models that enable them to carry out fast hand calculations, i.e., to create circuits using small-signal hybrid-{\pi} models, calculate figures of merit, estimate gains, pole-zero positions, etc. This paper presents a comprehensive GFET model that is simple enough for being used in hand-calculations during circuit design and at the same time it is accurate enough to capture the electrical characteristics of the devices in the operating regions of interest. Closed analytical expressions are provided for the drain current ID, small-signal transconductance gain gm, output resistance ro, and parasitic Vgs and Cgd. In addition, figures of merit such as intrinsic voltage gain AV, transconductance efficiency gm/ID, and transit frequency fT are presented. The proposed model has been compared to a complete analytical model and also to measured data available in current literature. The results show that the proposed model follows closely to both the complete analytical model and the measured data; therefore, it can be successfully applied in the design of GFET analog circuits.Comment: 9 pages,11 figure

This paper presents a microscopic traffic simulation-based method for urban traffic state estimation using Assisted Global Positioning System (A-GPS) mobile phones. In this approach, real-time location data are collected by A-GPS mobile phones to track vehicles traveling on urban roads. In addition, tracking data obtained from individual mobile probes are aggregated to provide estimations of average road link speeds along rolling time periods. Moreover, the estimated average speeds are classified to different traffic condition levels, which are prepared for displaying a real-time traffic map on mobile phones. Simulation results demonstrate the effectiveness of the proposed method, which are fundamental for the subsequent development of a system demonstrator.

The measurement of the biological tissue's electrical impedance is an active research field that has attracted a lot of attention during the last decades. Bio-impedances are closely related to a large variety of physiological conditions; therefore, they are useful for diagnosis and monitoring in many medical applications. Measuring living tissues, however, is a challenging task that poses countless technical and practical problems, in particular if the tissues need to be measured under the skin. This paper presents a bio-impedance sensor ASIC targeting a battery-free, miniature size, implantable device, which performs accurate 4-point complex impedance extraction in the frequency range from 2 kHz to 2 MHz. The ASIC is fabricated in 150 nm CMOS, has a size of 1.22 mm × 1.22 mm and consumes 165 μA from a 1.8 V power supply. The ASIC is embedded in a prototype which communicates with, and is powered by an external reader device through inductive coupling. The prototype is validated by measuring the impedances of different combinations of discrete components, measuring the electrochemical impedance of physiological solution, and performing ex vivo measurements on animal organs. The proposed ASIC is able to extract complex impedances with around 1 Ω resolution; therefore enabling accurate wireless tissue measurements.

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A dual-source energy harvesting interface that combines energy from implanted glucose biofuel cell and thermoelectric generator is presented. A single-inductor dual-input dual-output boost converter topology is employed to efficiently transfer the extracted power to the output. A dual-input feature enables the simultaneous maximum power extraction from two harvesters, while a dual-output allows a control circuit to perform complex digital functions at nW power levels. The control circuit reconfigures the converter to improve the efficiency and achieve zero-current and zero-voltage switching. The measurement results of the proposed boost converter, implemented in a 0.18 µm CMOS process, show a peak efficiency of 89.5% when both sources provide a combined input power of 66 µW. In the singlesource mode, the converter achieves a peak efficiency of 85.2% at 23 µW for the thermoelectric source and 90.4% at 29 µW for the glucose biofuel cell. The converter can operate from minimum input voltages of 10 mV for the thermoelectric source and 30 mV for the glucose biofuel cell.