Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Steganography & Support vector machine. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

Dynamic Queuing Model for the Secondary Users in a Cognitive Radio Network for Improvement of QoS

Abstract: The advent of various bandwidth-hungry applications now-a-days has increased the spectrum demand, thereby resulting in spectrum scarcity. Cognitive Radio Networks (CRN), proposed by the researchers, is a probable solution to the problem. CRN allows licensed Primary Users (PUs) to partly lease their unutilized spectrum to the opportunistic Secondary Users (SU) for effective Channel Utilization (CU) and enhanced Quality of Service (QoS). Now, use of buffers is a common approach to provide improved QoS to the SUs. However, if the waiting time of the SUs in the buffers exceed their time-out interval, the QoS degrades instead of improving. Thus, in this work, firstly, a CRN has been modeled using two buffers, namely, the New Queue (NQ) and the Pre-empted Queue (PQ). The NQ holds the newly requesting SUs while the PQ holds the SUs pre-empted by the PUs. Next, a model to determine the dynamic length of buffers has been proposed. It works based on the prior activity of the end-users and the requesting SU's waiting threshold. The model ensures service to user if it is admitted in the network. Otherwise, it is blocked or dropped. Blocking or dropping of the calls in this case provides a chance to the SUs to transmit via other base stations. The system is modeled using a multidimensional Continuous Time Markov Chain (CTMC) model. The dynamic queue helps to restrict the Level of Impatience (LOI) to 19.90% for the New Queue SUs and 14.93% for Preempted Queue SUs while achieving 99.33% CU.

Analysis of Length Dependent Gain and Noise Figure in a Dual Stage L-Band EDFA configuration

Abstract: In an Erbium Doped Fiber Amplifier the gain and noise figure are strongly dependent on fiber length This paper presents simulative studies on Length Dependent Gain and Noise Figure Analysis in a Dual Stage L-Band EDFA WDM Network A high gain of 42dB was obtained at 1562nm wavelength with a total EDF (EDF-I 5m and EDF-II 5m) length of 10m and total pump power (980nm pump and 1480nm pump) of 270mW Low noise figure of less than 47dB occurs in the entire wavelength range (1561nm-1617nm) A high Power Conversion Efficiency of 48% and Quantum Conversion Efficiency of 60% has been obtained This paper also studies the variation of gain and noise figure with varying temperature and fiber length The configuration discussed in this capable of successfully implemented for L-band amplification with high gain and low noise figure

Borate Based Spintronic Materials in Bulk Form above Room Temperature

Abstract: Magnetization above room temperature (RT) is a necessary parameter for achieving practical application of spintronic devices. Magnetization above room temperature in bulk form has been achieved in nanocrystalline Mn-doped ZnO dispersed in borate matrix. A simple glass-ceramic route has been used for the preparation of these materials. The material-processing route used here is cheaper and easier than other routes used frequently. X-ray diffraction (XRD) study reveals that the Mn-doped ZnO was in nanocrystalline form. Since these nanocrystals are dispersed in a glass matrix, they will be protected from agglomeration, so size will remain controlled, which affects the magnetization. There are no possibilities of an extrinsic origin such as ferromagnetic impurity segregation, etc. for this magnetization.

A Fuzzy-Based Modified Gain Adaptive Scheme for Model Reference Adaptive Control

Abstract: In this paper, a fuzzy-based adaptive scheme for model reference adaptive control (MRAC) is proposed. In MRAC, the choice of proper adaptive gain (γ) is a cumbersome job, and it is usually done by trial and error method. To eliminate this shortcoming, here fuzzy logic is incorporated in the control loop to tune the adaptive gain (γ). In design of model reference adaptive control, MIT rule is followed, where a cost function is defined as a function of error between the outputs of the plant and the reference model, and the controller parameters are adjusted in such a way so that this cost function is minimized. The experiments on the different second-order linear/nonlinear systems are illustrated to show the merits of the proposed fuzzy-based model reference adaptive control (FMRAC) scheme over the MRAC. The performances of the proposed control algorithms are evaluated and shown by means of simulation on MATLAB and Simulink.