Modeling and performance analysis of VI‐CRA: A congestion control algorithm for vehicular networks

This study proposes a Vehicle ID‐based CAM Rate Adaptation (VI‐CRA) algorithm for beacon messages in the vehicular network. Foremost, an improved vehicle ID–based analytical model is proposed at the MAC layer of vehicular network. The model weighs the random back‐off number chosen by vehicles participating in the back‐off process, with the vehicle ID incorporated in their respective CAMs. This eventually leads to the selection of a vehicle ID–based random back‐off number, minimizing the probability of collision due to same back‐off number selection. It is worth noting that the improved analytical model outperforms the existing works in terms of average packet delay since only one fourth of the contention window size is used throughout the simulation. To enhance the performance of the analytical model, the paper incorporates a congestion control algorithm, by adapting the rate of CAM broadcast over the control channel. The algorithm is designed considering a wide range of scenarios, ranging from nonsaturated to extremely saturated network (in terms of collision probability) and sparsely distributed to teemed network (in terms of vehicular density). For better analyses of simulation results, the algorithm is applied over different vehicle ID–based back‐off numbers. Simulation results for all the back‐off numbers show that vehicle ID–based CAM rate adaptation algorithm performs better than the traditional fixed CAM rate IEEE 802.11p, even at high vehicular density.     

Cuckoo Search Based Optimization of Multiuser Cognitive Radio System Under the Effect of Shadowing

Shadow fading is one of the least investigated factors of received signal power in a typical wireless communication system. Variations in the received power caused by shadowing events can impose some serious changes in the communication. This paper, proposes a new multiuser cognitive radio system in shadowing environment and its design optimization using cuckoo search algorithm. The transmission parameters of multiple secondary users in the purposed CR model are considered on the basis of IEEE 802.22 WRAN standard. An attempt to optimize these parameters in shadowing environment to achieve multiple objectives for desired quality of service have been made using a relatively newer and simpler cuckoo search algorithm. The optimization results have been compared with another efficient biogeography based optimization technique and the traditional simulated annealing.     

First-Principles Investigation of Electronic Properties of GaAsxSb1 –x Ternary Alloys

Semiconductors - Compositional variations in GaAs based ternary alloys have exhibited wide range alterations in electronic properties. In the present paper, first-principles study of...     

Dithieno[3,2‐b:2′,3′‐d]pyrrol‐Cored Hole Transport Material Enabling Over 21% Efficiency Dopant‐Free Perovskite Solar Cells

Dopant‐free hole transport materials (HTMs) are essential for commercialization of perovskite solar cells (PSCs). However, power conversion efficiencies (PCEs) of the state‐of‐the‐art PSCs with small molecule dopant‐free HTMs are below 20%. Herein, a simple dithieno[3,2‐b:2′,3′‐d]pyrrol‐cored small molecule, DTP‐C6Th, is reported as a promising dopant‐free HTM. Compared with commonly used spiro‐OMeTAD, DTP‐C6Th exhibits a similar energy level, a better hole mobility of 4.18 × 10^?4 cm² V^?1 s^?1, and more efficient hole extraction, enabling efficient and stable PSCs with a dopant‐free HTM. With the addition of an ultrathin poly(methyl methacrylate) passivation layer and properly tuning the composition of the perovskite absorber layer, a champion PCE of 21.04% is achieved, which is the highest value for small molecule dopant‐free HTM based PSCs to date. Additionally, PSCs using the DTP‐C6Th HTM exhibit significantly improved long‐term stability compared with the conventional cells with the metal additive doped spiro‐OMeTAD HTM. Therefore, this work provides a new candidate and effective device engineering strategy for achieving high PCEs with dopant‐free HTMs.     

Performance analysis of wireless communication system over nonidentical cascaded generalised gamma fading channels

Multiplicative fading statistics usually encountered in different radio propagation environments. In this context, we evaluate and analyse the performance of a wireless communication system over the nonidentical cascaded generalised Gamma Fading Channels, also known as generalised Bessel‐K fading channel. To this end, the closed‐form expressions for the amount of fading (AOF), the outage probability (OP), the average symbol error probability (SEP), and the channel capacity are derived. In addition approximate expressions for the average SEP with maximal ratio combining (MRC) diversity are also provided. The low‐ and high‐power solutions for the channel capacity are also provided. Furthermore, simplified asymptotic average SEP expressions for MRC and selection combining (SC) are presented to gain the system performance with diversity. The proposed methodologies provide more flexibility to accommodate different radio propagation scenarios. To examine the accuracy of the proposed solutions, numerical and simulation results are compared and shown to fit for variety of fading parameters.     

An EKV-based high voltage MOSFET model with improved mobility and drift model

An EKV-based high voltage MOSFET model is presented. The intrinsic channel model is derived based on the charge based EKV-formalism. An improved mobility model is used for the modeling of the intrinsic channel to improve the DC characteristics. The model uses second order dependence on the gate bias and an extra parameter for the smoothening of the saturation voltage of the intrinsic drain. An improved drift model [Chauhan YS, Anghel C, Krummenacher F, Ionescu AM, Declercq M, Gillon R, et al. A highly scalable high voltage MOSFET model. In: IEEE European solid-state device research conference (ESSDERC), September 2006. p. 270–3; Chauhan YS, Anghel C, Krummenacher F, Maier C, Gillon R, Bakeroot B, et al. Scalable general high voltage MOSFET model including quasi-saturation and self-heating effect. Solid State Electron 2006;50(11–12):1801–13] is used for the modeling of the drift region, which gives smoother transition on output characteristics and also models well the quasi-saturation region of high voltage MOSFETs. First, the model is validated on the numerical device simulation of the VDMOS transistor and then, on the measured characteristics of the SOI-LDMOS transistor. The accuracy of the model is better than our previous model [Chauhan YS, Anghel C, Krummenacher F, Maier C, Gillon R, Bakeroot B, et al. Scalable general high voltage MOSFET model including quasi-saturation and self-heating effect. Solid State Electron 2006;50(11–12):1801–13] especially in the quasi-saturation region of output characteristics.     

Optically-controlled ion-implanted GaAs MESFET characteristic withopaque gate

An analytical modelling has been carried out for an ion-implanted GaAs MESFET having a Schottky gate opaque to incident radiation. The radiation is absorbed in the device through the spacings of source, gate, and drain unlike the other model where gate is transparent/semitransparent. Continuity equations have been solved for the excess carriers generated in the neutral active region, the extended gate depletion region and the depletion region of active (n) and substrate (p) junction. The photovoltage across the channel and the p-layer junction and that across the Schottky junction due to generation in the arc region of the gate depletion layer are the two important controlling parameters. The I-V characteristics and the transconductance of the device have been evaluated and discussed     

Generating optimal adaptive fuzzy-neural models of dynamicalsystems with applications to control

The paper describes an approach to generating optimal adaptive fuzzy neural models from I/O data. This approach combines structure and parameter identification of Takagi-Sugeno-Kang (TSK) fuzzy models. We propose to achieve structure determination via a combination of modified mountain clustering (MMC) algorithm, recursive least squares estimation (RLSE), and group method of data handling (GMDH). Parameter adjustment is achieved by training the initial TSK model using the algorithm of an adaptive network based fuzzy inference system (ANFIS), which employs backpropagation (BP) and RLSE. Further, a procedure for generating locally optimal model structures is suggested. The structure optimization procedure is composed of two phases: 1) locally optimal rule premise variables subsets (LOPVS) are identified using MMC, GMDH, and a search tree (ST); and 2) locally optimal numbers of model rules (LONOR) are determined using MMC/RLSE along with parallel simulation mean square error (PSMSE) as a performance index. The effectiveness of the proposed approach is verified by a variety of simulation examples. The examples include modeling of a nonlinear dynamical process from I/O data and modeling nonlinear components of dynamical plants, followed by tracking control based on a model reference adaptive scheme (MRAC). Simulation results show that this approach is fast and accurate and leads to several optimal models     

Sub-quarter micron silicon integrated circuits and single wafer processing

This paper describes the role of single wafer processing in the development of sub-quarter micron silicon integrated circuits (ICs). The issues related to device processing, choice of materials, performance, reliability, and manufacturing are covered. Single wafer processing based rapid photothermal processing (dominant photons with wavelength less than about 800 nm) is an ideal answer to almost all the thermal processing requirements of current and future Si ICs. For process integration, a new model for process optimization based on minimization of thermal stress is proposed. For breaking the sub-100 nm manufacturing barriers, high throughput lithography based on direct writing is a proposed solution.