A RGC-based,low-power,CMOS transimpedance amplifier for 10Gb/s optical receivers

ABSTRACT

In this paper, a new low-power transimpedance amplifier (TIA) based on a modified Regulated Cascode (RGC) circuit structure followed by a closed-loop post-amplifier is proposed for 10 Gb/s applications. The main objective of this work is to reduce the power consumption while, the frequency bandwidth of the proposed amplifier is increased considerably. The booster of a conventional RGC is modified by a cascoded transistor and its effect on the performance of the circuit is studied mathematically, which are verified by simulations. The bandwidth extension is occurred due to increasing the gain of the booster amplifier in the RGC stage, which isolates further the input capacitance and results in a reduced input resistance value hence, a higher input pole frequency is obtained in comparison with other conventional RGC structures. On the other hand, by using an active inductive peaking technique, the frequency of the output pole is also increased which results in a further extension of the frequency bandwidth for the proposed circuit. The proposed TIA is simulated using 90 nm CMOS technology parameters, which shows a 50.5 dBΩ transimpedance gain, 7.3 GHz frequency bandwidth and 1.22 µA_rms input referred noise value for only 1 mW of power consumption at 1.2 V supply voltage.     

Fabrication of metallic nanostructures of sub-20 nm with an optimized process of E-beam lithography and lift-off

A process consisting of e-beam lithography and lift-off was optimized to fabricate metallic nanostructures. This optimized process successfully produced gold and aluminum nanostructures with features size less than 20 nm. These structures range from simple parallel lines to complex photonic structures. Optical properties of gold split ring resonators (SRRs) were characterized with Raman spectroscopy. Surface-Enhanced Raman Scattering (SERS) on SRRs was observed with 4-mercaptopyridine (4-MPy) as molecular probe and greatly enhanced Raman scattering was observed.     

Time-domain analysis of lossy active transmission lines using FDTD method

In this paper, an accurate and efficient method for analysis of a GaAs MESFET including frequency-dependent losses of the electrodes in the time domain is presented. The time domain analysis is obtained based on the fully distributed model using finite-difference time-domain (FDTD) technique, with the assumption of the skin effect losses. The time-domain results are verified using the conventional time-domain to frequency-domain (TDFD) solution technique.     

A Lyapunov theory based UPFC controller for power flow control

Unified power flow controller (UPFC) is the most comprehensive multivariable device among the FACTS controllers. Capability of power flow control is the most important responsibility of UPFC. According to high importance of power flow control in transmission lines, the proper controller should be robust against uncertainty and disturbance and also have suitable settling time. For this purpose, a new controller is designed based on the Lyapunov theory and its stability is also evaluated. The Main goal of this paper is to design a controller which enables a power system to track reference signals precisely and to be robust in the presence of uncertainty of system parameters and disturbances. The performance of the proposed controller is simulated on a two bus test system and compared with a conventional PI controller. The simulation results show the power and accuracy of the proposed controller.     

Characterizations of strontium(II) and barium(II) adsorption from aqueous solutions using dolomite powder

In this research, adsorption technique was applied for strontium and barium removal from aqueous solution using dolomite powder. The process has been investigated as a function of pH, contact time, temperature and adsorbate concentration. The experimental data was analyzed using equilibrium isotherm, kinetic and thermodynamic models. The isotherm data was well described by Langmuir isotherm model. The maximum adsorption capacity was found to be 1.172 and 3.958 mg/g for Sr(II) and Ba(II) from the Langmuir isotherm model at 293 K, respectively. The kinetic data was tested using first and pseudo-second order models. The results indicated that adsorption fitted well with the pseudo-second order kinetic model. The thermodynamic parameters (ΔG°, ΔH°, and ΔS°) were also determined using the equilibrium constant value obtained at different temperatures. The results showed that the adsorption for both ions was feasible and exothermic.     

Action recognition based on statistical analysis from clustered flow vectors

A new technique for action clustering-based human action representation on the basis of optical flow analysis and random sample consensus (RANSAC) method is proposed in this paper. The apparent motion of the human subject with respect to the background is detected and localized by using optical flow analysis. The next task is to characterize the action through the frequent movement of the optical flow points or interest points at different regions of the moving subject. The RANSAC algorithm is used to filter out any unwanted interested points all around the scene and keep only those that are related to that particular subject’s motion. From the remaining salient key interest points, the area of the human body within the frame is estimated. The rectangular area surrounding the human body is then segmented both horizontally and vertically. Now, the percentage of change of interest points in each horizontal and vertical segments from frame to frame is estimated. Similar results are obtained for different persons performing the same action and the corresponding values are averaged for respective segments. The matrix constructed by this strategy is used as a feature vector for that particular action. Similar data are calculated for each block created at the intersections of the horizontal and vertical segments. In addition to these, the change in the position of the person along X- and Y-axes is accumulated for an action and included in the feature vectors. Afterward, for the purpose of recognition using the extracted feature vectors, a distance-based similarity measure and a support vector machine-based classifiers have been exploited. Several combination of the feature vectors is examined. From extensive experimentation upon benchmark motion databases, it is found that the proposed method offers not only a very high degree of accuracy but also computational savings.     

Ranking units in DEA based on efficiency intervals and decision‐maker's preferences

Data Envelopment Analysis (DEA) uses the best favorable weight set for the inputs and outputs of each decision‐making unit (DMU) to obtain its best possible score. Hence, this score can be considered as an upper bound of the real efficiency score. If we also use the least favorable weight set of each DMU, then a lower bound of the efficiency score can also be obtained. So, instead of one score, we can find an interval that gives all possible values of the efficiency score for each DMU. The aim of this paper is to propose an approach for determining efficiency intervals and setting up a full ranking of DMUs based on these intervals. We incorporate explicitly the decision‐maker's preferences in two phases. The first phase is for obtaining efficiency intervals, by introducing some restrictions on the input and output weights. The second one is for ranking the intervals based on the combination of the lower and the upper bounds of the efficiency intervals. The developed formulations will be illustrated through some numerical examples.