A Fast Settling Multi-Standard CMOS Fractional-N Frequency Synthesizer for DECT/GSM/ CDMA &/NADC Wireless Communication Standards

A fast settling multi-standard CMOS fractional-N frequency synthesizer for DECT, GSM, CDMA and NADC wireless communication standards is proposed. This frequency synthesizer was simulated with ADS2008 in TSMC RF CMOS 0.18 µm. Frequency range is 824-1900 MHz, a switched capacitor LC-VCO was used in order to produce this frequency range. Frequency synthesizers have three main specifications of phase noise, settling time and power consumption. A new channel select circuit was designed instead of ∑∆ modulator to locate spur tones far from center frequency. A high reference frequency was used in order to reduce the VCO phase noise and locate the spur tones far from center frequency; these tones are produced by charge pump (reference spur) and N/N+1 divider (fractional spur). Two ways were used for phase noise optimization; in the first way phase noise was reduced by a low pass filter and a bypass capacitor (CT) that eliminate thermal noise and 2ω0 harmonics of tail current source; in the second way with biasing of VCO transistors only in saturation region preventing reduction of quality factor(Q) in tank circuit. These two ways in VCO of DECT were used, consequently the phase noise at 1875MHz center frequency was improved from -119.4 dBc/Hz at 3.4 MHz offset frequency to -144.3 dBc/Hz at 3.4 MHz offset frequency. The settling time for all standards was achieved less than almost 1 μs over the entire frequency range. For DECT synthesizer phase noise of -116.37 dBc/Hz at 3 MHz offset frequency was obtained, the first spur tone was located in 7.35 MHz offset from center frequency, also settling time of 350ns was obtained. The whole frequency synthesizer in loop1 (for DECT) draws 13 mA and in loop2 (for GSM900, CDMA & NADC) draws 13.67 mA from a 1.8 V voltage supply.

System Level Simulation of Energy-Detection Based UWB Receivers

The performance of a non-coherent UWB receiver with Binary pulse position modulation is simulated with MATLAB; taking into account the effect of non-linearity, noise, pulse shape and channel effects. This simulation examines the minimum requirements for LNA, AGC, squarer, and operational transconductance amplifier in analog front-end for sensor network application with 100Kb/s data rate and 10-3 BER. The linearity requirement in OTA is achieved using Gilbert cell OTA with the technique of multiple gated transistors. For sensor network applications, analog front-end modules must have 4dB NF (Noise figure), -12dBm IIP3, 50dB gain and -75dBm sensitivity for 100Kb/s data rates. The transceiver power consumption is assumed to be below 50mW. The performance of energy detection non-coherent receiver is simulated in Simulink of MATLAB, it shows that BER of Gaussian pulse is lower than doublet and 4th Gaussian pulse. By increasing the number of transmitted pulse per bit and IIP3, the performance of receiver is improved.

Probabilistic Analysis of Local Liquefaction Potential Based on Spatial Variability of SPT Data

In this paper, the spatial distribution of liquefaction potential is estimated using in-situ data from the Standard Penetration Test (SPT). For this purpose, a case study of a liquefiable soil at the Azad University of Qeshm is selected in the numerical modeling. After conducting the site investigation and determining SPT results at four boreholes, two distinct modeling approaches are implemented to evaluate the Liquefaction Potential Index (LPI) at the considered site; In the first method, the conditional random field for SPT data is generated in a layer-by-layer strategy and then, the LPI is obtained using a SPT-based empirical relations at each elemental column. On the other hand, in the second method, the LPI is first determined at each borehole location and then, this parameter is adopted as a stochastic variable in the construction of surficial conditional random field. It can be concluded that both approaches are able to capture the varying severity levels of liquefaction at most locations across the area of study. However, the comparison shows that using the first approach results in a more fluctuated LPI results with almost the same extremum values.

Stability Analysis of Mineral Structures using FLAC Software

The safety factor for slopes (FS) is traditionally determined using two-dimensional limit equilibrium (LEM) methods, however, the safety factor of a slope can also be calculated by FLAC software with the technique of reducing soil shear strength in the time stages until the slope fails. In this presentation, we first describe the numerical methods of stability analysis, finite difference method and FLAC software, and then we analyze the static stability using FLAC software.

Slope Stability Analysis Methods

The presence of discontinuities, the inherent variability of the rock mass and discontinuity properties, and the uncertainties associated with directions and fcof the in-situstress makes the rock engineering problems challenging. The numerical modeling can assist the ground control engineers in designing and evaluating the stability of the excavations. If extensive geological and geotechnical data are available, then detailed predictions of deformation, stress and stability can be accomplished by performing numerical modeling. If not, still the numerical modeling can be used to perform parametric studies to gain insight into the possible ranges of responses of a system due to likely ranges of various parameters. The parametric studies can help to identify the key parameters and their impact on stability of underground excavations. The priorities of the material testing and site investigation can be set based on the selected key parameters from parametric studies. The most important modeling methods in stability analysis include finite element method, finite difference method, boundary element method and Distinct element method, which are used in three static, quasi-static and dynamic conditions and in both definite and probability modes. In this report, we investigate each of these methods their weaknesses and strengths.