Estimation of BT Interference in OFDM Sub Carriers with Training Signals

While wireless LAN (WLAN) is very popular now a days, its performance deteriorates in the presence of other signals like Bluetooth (BT) signal that operate in the same band as WLAN. Present interference mitigation techniques in WLAN due to BT cancel interference in WLAN sub carrier where BT has hopped but do not cancel interference in the adjacent sub carriers. In this paper BT interference signal in all the OFDM sub carriers is estimated. That is, leakage of BT in other sub carriers including the sub carriers in which it has hopped is also measured. BT signals are estimated using the training signals of OFDM system. Simulation results in AWGN noise show that proposed algorithm agrees closely with theoretical results.

Nonlinear Model Predictive Spread Acceleration Guidance with Impact Angle Constraint for Stationary Targets

A new technique named as model predictive spread acceleration guidance (MPSAG) is proposed in this paper. It combines nonlinear model predictive control and spread acceleration guidance philosophies. This technique is then used to design a nonlinear suboptimal guidance law for a constant speed missile against stationary target with impact angle constraint. MPSAG technique can be applied to a class of nonlinear problems, which leads to a closed form solution of the lateral acceleration (latax) history update. Guidance command assumed is the lateral acceleration (latax), applied normal to the velocity vector. The new guidance law is validated by considering the nonlinear kinematics with both lag-free as well as first order autopilot delay. The simulation results show that the proposed technique is quite promising to come up with a nonlinear guidance law that leads to both very small miss distance as well as the desired impact angle.

A Real-time clustering system for spatio-temporal signals from network of neurons

Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.

Optimizing resolution of signals in a low-IF receiver

The resolution of the digital signal path has a crucial impact on the design, performance and the power dissipation of the radio receiver data path, downstream from the ADC. The ADC quantization noise has been traditionally included with the Front End receiver noise in calculating the SNR as well as BER for the receiver. Using the IEEE 802.15.4 as an example, we show that this approach leads to an over-design for the ADC and the digital signal path, resulting in larger power. More accurate specifications for the front-end design can be obtained by making SNRreg a function of signal resolutions. We show that lower resolution signals provide adequate performance and quantization noise alone does not produce any bit-error. We find that a tight bandpass filter preceding the ADC can relax the resolution requirement and a 1-bit ADC degrades SNR by only 1.35 dB compared to 8-bit ADC. Signal resolution has a larger impact on the synchronization and a 1-bit ADC costs about 5 dB in SNR to maintain the same level of performance as a 8-bit ADC.

A hybrid pre-whitening technique for detection of additive spread spectrum watermarks in audio signals

Pre-whitening techniques are employed in blind correlation detection of additive spread spectrum watermarks in audio signals to reduce the host signal interference. A direct deterministic whitening (DDW) scheme is derived in this paper from the frequency domain analysis of the time domain correlation process. Our experimental studies reveal that, the Savitzky-Golay Whitening (SGW), which is otherwise inferior to DDW technique, performs better when the audio signal is predominantly lowpass. The novelty of this paper lies in exploiting the complementary nature to the two whitening techniques to obtain a hybrid whitening (HbW) scheme. In the hybrid scheme the DDW and SGW techniques are selectively applied, based on short time spectral characteristics of the audio signal. The hybrid scheme extends the reliability of watermark detection to a wider range of audio signals.

A simple numerical method for three-dimensional analysis of simple expansion chamber mufflers of rectangular as well as circular cross-section with a stationary medium

Three-dimensional effects are a primary source of discrepancy between the measured values of automotive muffler performance and those predicted by the plane wave theory at higher frequencies. The basically exact method of (truncated) eigenfunction expansions for simple expansion chambers involves very complicated algebra, and the numerical finite element method requires large computation time and core storage. A simple numerical method is presented in this paper. It makes use of compatibility conditions for acoustic pressure and particle velocity at a number of equally spaced points in the planes of the junctions (or area discontinuities) to generate the required number of algebraic equations for evaluation of the relative amplitudes of the various modes (eigenfunctions), the total number of which is proportional to the area ratio. The method is demonstrated for evaluation of the four-pole parameters of rigid-walled, simple expansion chambers of rectangular as well as circular cross-section for the case of a stationary medium. Computed values of transmission loss are compared with those computed by means of the plane wave theory, in order to highlight the onset (cutting-on) of various higher order modes and the effect thereof on transmission loss of the muffler. These are also compared with predictions of the finite element methods (FEM) and the exact methods involving eigenfunction expansions, in order to demonstrate the accuracy of the simple method presented here.

Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals

In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.

Optical diffraction of second-harmonic signals in the LiBO2-Nb2O5 glasses induced by self-organized LiNbO3 crystallites

The nanocrystallites ( ≈ 3 nm) of LiNbO3, evolved in the (100−x)LiBO2-xNb2O5 (5x20, in molar ratio) glass system exhibited intense second-harmonic signals in transmission mode when exposed to infrared (IR) light at λ = 1064 nm. The second-harmonic waves were found to undergo optical diffraction which was attributed to the presence of self-organized submicrometer-sized LiNbO3 crystallites that were grown within the glass matrix along the parallel damage fringes created by the IR laser radiation. Micro-Raman studies carried out on the laser-irradiated samples confirmed the self-organized crystallites to be LiNbO3.

Calculating the Effect of Uneven Terrain on Glide Path Signals

A method for calculating the bends in the glide slope due to uneven terrain is presented. A computer program written for the purpose enables the calculation of the difference in depth of modulation (DDM) at any point, taking into account the effect of uneven terrain. Results are presented for a hypothetical case of a hill in front of the runway. The program enables us to predict the glide slope bends due to irregular terrain, so that proper selection of glide slope antenna location can be made.

Validation of a Modified Eddy Dissipation Concept Model for Stationary and Nonstationary Turbulent Diffusion Flames

A transient flame simulation tool based on unsteady Reynolds average Navier Stokes (RANS) is characterized for stationary and nonstationary flame applications with a motivation of performing computationally affordable flame stability studies. Specifically, the KIVA-3V code is utilized with incorporation of a recently proposed modified eddy dissipation concept for simulating turbulence-chemistry interaction along with a model for radiation loss. Detailed comparison of velocities, turbulent kinetic energies, temperature, and species are made with the experimental data of the turbulent, non-premixed DLR_A CH4/H-2/N-2 jet flame. The comparison shows that the model is able to predict flame structure very well. The effect of some of the modeling assumptions is assessed, and strategies to model a stationary diffusion flame are recommended. Unsteady flame simulation capabilities of the numerical model are assessed by simulating an acoustically excited, experimental, oscillatory H-2-air diffusion flame. Comparisons are made with oscillatory velocity field and OH plots, and the numerical code is observed to predict transient flame structure well.

Nonthermal-Plasma-Promoted Catalysis for the Removal of NOx From a Stationary Diesel-Engine Exhaust

A detailed study on the removal of oxides of nitrogen (NOx) from the exhaust of a stationary diesel engine was carried out using nonthermal-plasma (pulsed electrical-discharge plasma)-promoted catalytic process. In this paper, the filtered exhaust from the diesel engine is made to pass through a combination of nonthermal plasma reactor and a catalytic reactor connected in series. This combination is referred to as cascade. Two types of cascaded systems were studied. In one type, the plasma treating filtered exhaust was cascaded with a reduction catalyst V2O5/TiO2 using ammonia as reducing agent, and in the other type, the plasma treating filtered exhaust was cascaded with activated-alumina catalyst without any additive. Improved NOx-removal performance of both the cascaded processes and the role of nonthermal plasma in promoting catalysis are explained. Along with the NOx, total hydrocarbon and aldehydes were also removed. Furthermore, experiments were conducted at different temperatures and engine-loading conditions.

Pulsed plasma treatment for NOx reduction from filtered/unfiltered stationary diesel engine exhaust

A detailed study on the removal of oxides of nitrogen (NOx) from the filtered/unfiltered exhaust of a stationary diesel engine was carried out using non-thermal plasma (pulsed electrical discharge plasma) process and cascaded processes namely plasma- adsorbent and plasma-catalyst processes. The superior performance of discharge plasma with regard to NOx removal, energy consumption and formation of by-products in unfiltered exhaust environment is identified. In the cascaded plasma-adsorbent process, the plasma was cascaded with adsorbents (MS13X/Activated alumina/Activated charcoal). The cascaded process treating unfiltered exhaust exhibits a very high NOx removal compared to the individual processes and further, the cascaded process gives almost the same NOx removal efficiency irrespective of type of adsorbent used. In the cascaded plasma- catalyst process, the plasma was cascaded with activated alumina catalyst at high temperature. The synergy effect and improved performance of the cascaded process are explained. Further, experiments were conducted at room temperature as well as at higher temperatures.

Corona treatment for NOx reduction from stationary diesel engine exhaust: Impact of nature of energization and exhaust composition

A detailed study on the removal of oxides of nitrogen (NOx) from the exhaust of a stationary diesel engine was carried out using non-thermal plasma (dielectric barrier discharge) process. The objective of the study was to explore the effect of different voltage energizations and exhaust composition on the NOx removal process. Three types of voltage energizations, namely AC, DC and Pulse were examined. Due to the ease of generation of high voltage AC/DC electrical discharges from automobile/Vehicular battery supply for possible retrofitting in exhaust cleaning circuit, it was found relevant to investigate individual energisation cases in detail for NOx removal. AC and Pulse energisations exhibit a superior NOx removal efficiency compared to DC energisation. However,Pulse energisation is found to be more energy efficient. Experiments were further carried out with filtered/ unfiltered (raw) exhaust under pulse energisations. The results were discussed with regard to NOx removal, energy consumption and formation of by-products.