We propose a physically based analytical compact model to calculate Eigen energies and Wave functions which incorporates penetration effect. The model is applicable for a quantum well structure that frequently appears in modern nano-scale devices. Th
is model is equally applicable for both silicon and III-V devices. Unlike other models already available in the literature, our model can accurately predict all the eigen energies without the inclusion of any fitting parameters. The validity of our model has been checked with numerical simulations and the results show significantly better agreement compared to the available methods.
We investigated Capacitance-Voltage (C-V) characteristics of the Depletion Mode Buried Channel InGaAs/InAs Quantum Well FET by using Self-Consistent method incorporating Quantum Mechanical (QM) effects. Though the experimental results of C-V for enha
ncement type device is available in recent literature, a complete characterization of electrostatic property of depletion type Buried Channel Quantum Well FET (QWFET) structure is yet to be done. C-V characteristics of the device is studied with the variation of three important process parameters: Indium (In) composition, gate dielectric and oxide thickness. We observed that inversion capacitance and ballistic current tend to increase with the increase in Indium (In) content in InGaAs barrier layer.
In this work, we propose an explicit analytical equation to show the variation of top gate threshold voltage with respect to the JFET bottom gate voltage for a Flexible Threshold Voltage Field Effect Transistor (Flexible-FET) by solving 2-D Poissons
equation with appropriate boundary conditions, incorporating Youngs parabolic approximation. The proposed model illustrates excellent match with the experimental results for both n-channel and p-channel 180nm Flexible-FETs. Threshold voltage variation with several important device parameters (oxide and silicon channel thickness, doping concentration) is observed which yields qualitative matching with results obtained from SILVACO simulations.
Energy harvesting (EH) nodes can play an important role in cooperative communication systems which do not have a continuous power supply. In this paper, we consider the optimization of conventional and buffer-aided link adaptive EH relaying systems,
where an EH source communicates with the destination via an EH decode-and-forward relay. In conventional relaying, source and relay transmit signals in consecutive time slots whereas in buffer-aided link adaptive relaying, the state of the source-relay and relay-destination channels determines whether the source or the relay is selected for transmission. Our objective is to maximize the system throughput over a finite number of transmission time slots for both relaying protocols. In case of conventional relaying, we propose an offline and several online joint source and relay transmit power allocation schemes. For offline power allocation, we formulate an optimization problem which can be solved optimally. For the online case, we propose a dynamic programming (DP) approach to compute the optimal online transmit power. To alleviate the complexity inherent to DP, we also propose several suboptimal online power allocation schemes. For buffer-aided link adaptive relaying, we show that the joint offline optimization of the source and relay transmit powers along with the link selection results in a mixed integer non-linear program which we solve optimally using the spatial branch-and-bound method. We also propose an efficient online power allocation scheme and a naive online power allocation scheme for buffer-aided link adaptive relaying. Our results show that link adaptive relaying provides performance improvement over conventional relaying at the expense of a higher computational complexity.
