Himani Joshi

Comparative study of laser produced Li plasma plumes from thin film and solid target

The evolution features of lithium ions and neutrals generated by two different schemes viz. the laser-blow-off (LBO) of multicomponent LiF–C thin film and conventional laser ablation (referred here as LPP) from solid lithium have been studied using optical emission spectroscopic technique. The optical signal emitted by Li I (at 670.8 nm) and Li II (548.4 nm) was monitored as a function of laser fluence, ambient gas pressure, and distance “z” from the target. Apart from their similarities, some interesting differences were noticed in temporal profiles of the plumes generated by LPP and LBO both in vacuum as well as in the presence of the ambient gas. A comparative analysis of experimental results indicates that the ablation mechanism and subsequent laser-plume interaction were responsible for the observed differences in LPP and LBO plumes. Expansion features of the plume are discussed in the light of two different models.

Generation of fast neutrals in a laser-blow-off of LiF–C film: A formation mechanism

The temporal profiles of the spectral lines LiI and LiII emitted by a laser blow off of LiF–C film were analyzed. Fast neutrals having energies of ∼310eV were observed. It was found that these fast neutrals have kinetic energies similar to that of the ablated ions. Photon production rates at 670.8nm were estimated for the recombination and charge exchange processes. We attempted to qualitatively understand the role of electron-ion recombination (two and three body recombinations) and charge exchange processes in producing observed fast neutrals. Our analysis indicates that charge exchange is the dominant process in the production of fast neutrals.

Effect of magnetic field on the expansion dynamics of laser-blow-off generated plasma plume: Role of atomic processes

The effect of a variable magnetic field on Li plasma produced by laser-blow-off technique has been studied experimentally. Enhancement in the intensity of the spectral lines from neutrals was observed, which varied with the magnetic field. The enhancement in emission from Li I was found to differ for the two different transitions viz . 670.8xa0nm (2s 2 S 1/2 xa0←xa02p 2 P 3/2,1/2 ) and 610.3xa0nm (2p 2 P 1/2,3/2 xa0←xa03d 2 P 3/2,5/2 ), which is more prominent for 670.8xa0nm. Conventionally, the enhancement in emission in the presence of the magnetic field has been explained in terms of radiative recombination. However, the atomic analysis by computing photon emissivity coefficients in the present case has revealed for the first time that it is due to electron impact excitation.

Dense strongly coupled plasma in double laser pulse ablation of lithium: Experiment and simulation

In a simple method of low power nano-second double pulsed laser ablation experiment in collinear geometry, formation of high density strongly coupled plasma is demonstrated. Using time-resolved measurements of the Stark broadened line width and line intensity ratio of the emission lines, the density and temperature of the plasma were estimated respectively. In this experiment, it is shown that ions are strongly coupled (ion-ion coupling parameter comes out to be >4). For comparison, both single and double pulsed laser ablations are presented. For the estimated experimental plasma parameters, first principle Langevin dynamics simulation corroborates the existence of a strongly coupled regime.

Blind and adaptive reconstruction approach for non-uniformly sampled wideband signal

In 5G, wideband communication receivers (WCRs) capable of digitizing signal ranging from 400 MHz to few GHz are desired to support various data intensive services. The design of such WCRs is a challenging task due to huge area, high cost, limited speed and dynamic range of analog-to-digital converters (ADCs) as well as poor reconfigurability of analog front-end. Recently, non-uniform (or sub-Nyquist) sampling techniques have been envisioned to digitize sparse wideband signal using existing ADCs. However, subsequent digital reconstruction works well only when the number of active users in the received signal are known i.e. they are not blind. To overcome this, a new Adaptive Orthogonal Matching Pursuit (AOMP) blind reconstruction approach has been proposed in this paper. The term adaptive means that the parameters of the AOMP are dynamically tuned based on learned spectral occupancy and channel quality statistics. The novelty of the AOMP is the use of online learning algorithm to estimate spectrum occupancy (or sparsity). Extensive simulation and complexity results indicate the superiority of the proposed AOMP approach over existing approaches for wide range of SNRs and different levels of sparsity. Numerically, AOMP offers as high as 64.5% improvement in normalized mean square error over existing approaches with slight penalty in terms of computational complexity. In the end, performance comparison of various reconstruction approaches for automatic modulation classification application is presented.

Atomic Processes in Emission Characteristics of a Lithium Plasma Plume Formed by Double-Pulse Laser Ablation

High resolution spectral analysis of lithium plasma formed by single and double laser ablation has been undertaken to understand the plume-laser interaction, especially at the early stages of the plasma plume. In order to identify different atomic processes in evolving plasma, time resolved spectral emission studies at different inter-pulse delays have been performed for ionic and neutral lithium lines emitting from different levels. Along with the enhancement in emission intensity, a large line broadening and spectral shift, especially in the case of excited state transition Li I 610.3 nm have been observed in the presence of the second pulse. This broadening and shift gradually decrease with increasing time delay. Another interesting feature is the appearance of a multi-component structure in the ionic line at 548.4 nm and these components change conversely into a single structure at the later stages of the plasma. The multi-component structures are correlated with the presence of different velocity (temperature) distributions in non-LTE conditions. Atomic analyses by computing photon emissivity coefficients with an ADAS code have been used to identify the above processes.

Testbed and experimental analysis of automatic modulation classifier for non-uniformly sampled signal

In dynamic spectrum environment, radio terminals adapt the modulation type of transmission according to channel parameters such as noise, fading etc. to meet the desired quality of service. Subsequently, receiver needs automatic modulation classifier (AMC) to identify the modulation type of transmitted signal if not informed explicitly. Also, an opportunistic spectrum access based cognitive radio needs AMC to accurately characterize the status of frequency bands. In this paper, USRP testbed has been developed to analyze the performance of cumulant based AMC in real radio environment for BPSK, QPSK, 16-QAM and 64-QAM modulation schemes. In the proposed testbed, the received signal is either uniformly sampled at Nyquist rate or non-uniformly sampled at sub-Nyquist rate and subsequently reconstructed. For non-uniform sampling (NUS), multi-coset sampling and orthogonal matching pursuit based reconstruction approach is realized. Experimental results, for various modulation types, antenna gains and various distances between transmitter and receiver, show that performance of AMC does not degrade significantly with NUS given that received signal is approximately sparse in frequency.

Spectrum Blind Recovery and Application in Non-uniform Sampling Based Automatic Modulation Classifier

Multi-standard wireless communication radios (MWCRs) capable of digitizing wideband signal to support wide variety of data-intensive services are desired. Limited reconfigurability of the analog front end along with hardware and cost constraints of high-speed analog-to-digital converters have generated significant interest in non-uniform (sub-Nyquist) sampling (NUS) and digital reconstruction-based MWCRs. Existing reconstruction approaches require prior knowledge of sparsity which may not be available in the dynamic spectrum environment. To alleviate this problem, a blind and adaptive reconstruction approach has been proposed in this paper. The proposed approach employs multi-armed Bandit framework to estimate the spectrum occupancy. Simulation results show that the average normalized mean square error of the proposed approach is 10–20% lower than other reconstruction approaches. Next, cumulant and machine learning-based automatic modulation classifier (AMC) is designed to validate the usefulness of the proposed approach in practical applications. Simulation results show that the classification accuracy of NUS-based AMC approaches, uniform sampling-based AMC with increase in signal-to-noise ratio and proposed approach is superior to others. The simulation results are further verified on the proposed universal software radio peripheral testbed in real radio environment. Experimental results demonstrate the close resemblance with simulation results.

Sub-Nyquist sampling and machine learning based online automatic modulation classifier for multi-carrier waveform

Reconfigurable terminals capable of adapting their transmission parameters such as modulation scheme, data and coding rates are desired to enhance the quality of service along with energy and spectral efficiency. However, spectrum bandwidth and time delay constraints limit the explicit sharing of these parameters and hence, they need to be estimated blindly. Though significant work has been done in blind parameter estimation, the task becomes non-trivial when reconfigurable terminals employ sub-Nyquist sampling (SNS) for wideband signal digitization. The proposed work presents the SNS and blind reconstruction based automatic modulation classifier (AMC) to blindly identify the modulation scheme of wideband multi-carrier signal, e.g. OFDM waveform. Simulation results along with experimental results on the proposed USRP testbed show that the classification accuracy of SNS based AMC approaches to that of Nyquist sampling based AMC with increase in signal to noise ratio given that the received signal is sufficiently sparse in the frequency.

Emission analysis of a laser-produced barium plasma plume.

In the present work we report the characteristic emission features of a laser-produced barium plasma plume. The time-resolved analysis for the different spectral lines of neutral and singly charged ionic barium has been carried out. It has been observed that the temporal evolution of electron temperature and density shows a peculiar behavior which is significantly different from the reported results of laser ablation of materials. The electron density increases with increase in delay time but the temperature does not change to any significant extent. Strong self-reversal in the emission of a resonant singly charged barium ionic line (455.4xa0nm) with time delay indicates the increase of population of singly charged barium ion with time. The results are explained on the basis of the increased population of barium metastables and subsequent ionization (Penning type).