Performance analysis of fixed gain amplify-and-forward relaying with time-efficient cascaded channel estimation

In a cooperative system with an amplify-and-forward relay, the cascaded channel training protocol enables the destination to estimate the source-destination channel gain and the product of the source-relay (SR) and relay-destination (RD) channel gains using only two pilot transmissions from the source. Notably, the destination does not require a separate estimate of the SR channel. We develop a new expression for the symbol error probability (SEP) of AF relaying when imperfect channel state information (CSI) is acquired using the above training protocol. A tight SEP upper bound is also derived; it shows that full diversity is achieved, albeit at a high signal-to-noise ratio (SNR). Our analysis uses fewer simplifying assumptions, and leads to expressions that are accurate even at low SNRs and are different from those in the literature. For instance, it does not approximate the estimate of the product of SR and RD channel gains by the product of the estimates of the SR and RD channel gains. We show that cascaded channel estimation often outperforms a channel estimation protocol that incurs a greater training overhead by forwarding a quantized estimate of the SR channel gain to the destination. The extent of pilot power boosting, if allowed, that is required to improve performance is also quantified.

Channel estimation using minimum bit error rate framework for BPSK signals

We consider the design of a linear equalizer with a finite number of coefficients in the context of a classical linear intersymbol-interference channel with additive Gaussian noise for channel estimation. Previous literature has shown that Minimum Bit Error Rate(MBER) based detection has outperformed Minimum Mean Squared Error (MMSE) based detection. We pose the channel estimation problem as a detection problem and propose a novel algorithm to estimate the channel based on the MBER framework for BPSK signals. It is shown that the proposed algorithm reduces BER compared to an MMSE based channel estimation when used in MMSE or MBER detection.

Joint data detection and dominant singular mode estimation in time varying reciprocal MIMO systems

This paper proposes an algorithm for joint data detection and tracking of the dominant singular mode of a time varying channel at the transmitter and receiver of a time division duplex multiple input multiple output beamforming system. The method proposed is a modified expectation maximization algorithm which utilizes an initial estimate to track the dominant modes of the channel at the transmitter and the receiver blindly; and simultaneously detects the un known data. Furthermore, the estimates are constrained to be within a confidence interval of the previous estimate in order to improve the tracking performance and mitigate the effect of error propagation. Monte-Carlo simulation results of the symbol error rate and the mean square inner product between the estimated and the true singular vector are plotted to show the performance benefits offered by the proposed method compared to existing techniques.

Linear programming approach for state estimation incorporating phasor measurements

This paper presents methodologies for incorporating phasor measurements into conventional state estimator. The angle measurements obtained from Phasor Measurement Units are handled as angle difference measurements rather than incorporating the angle measurements directly. Handling in such a manner overcomes the problems arising due to the choice of reference bus. Current measurements obtained from Phasor Measurement Units are treated as equivalent pseudo-voltage measurements at the neighboring buses. Two solution approaches namely normal equations approach and linear programming approach are presented to show how the Phasor Measurement Unit measurements can be handled. Comparative evaluation of both the approaches is also presented. Test results on IEEE 14 bus system are presented to validate both the approaches.

Estimation of electric stress and surface potential for traction insulators

Traction insulators are solid core insulators widely used for railway electrification. Constant exposure to detrimental effects of vandalism, and mechanical vibrations begets certain faults like shorting of sheds or cracks in the sheds. Due to fault in one/two sheds, stress on the remaining healthy sheds increases, owing to atmospheric pollution the stress may lead to a flashover of the insulator. Presently due to non availability of the electric stress data for the insulators, simulation study is carried out to find the potential and electric field for most widely used traction insulators in the country. The results of potential and electric field stress obtained for normal and faulty imposed insulators are presented.

A risk-estimation-based formulation for speech enhancement and its relation to Wiener filtering

The goal of speech enhancement algorithms is to provide an estimate of clean speech starting from noisy observations. The often-employed cost function is the mean square error (MSE). However, the MSE can never be computed in practice. Therefore, it becomes necessary to find practical alternatives to the MSE. In image denoising problems, the cost function (also referred to as risk) is often replaced by an unbiased estimator. Motivated by this approach, we reformulate the problem of speech enhancement from the perspective of risk minimization. Some recent contributions in risk estimation have employed Stein's unbiased risk estimator (SURE) together with a parametric denoising function, which is a linear expansion of threshold/bases (LET). We show that the first-order case of SURE-LET results in a Wiener-filter type solution if the denoising function is made frequency-dependent. We also provide enhancement results obtained with both techniques and characterize the improvement by means of local as well as global SNR calculations.

A generalized Stein's estimation approach to speech enhancement based on perceptual criteria

We address the problem of speech enhancement using a risk- estimation approach. In particular, we propose the use the Stein’s unbiased risk estimator (SURE) for solving the problem. The need for a suitable finite-sample risk estimator arises because the actual risks invariably depend on the unknown ground truth. We consider the popular mean-squared error (MSE) criterion first, and then compare it against the perceptually-motivated Itakura-Saito (IS) distortion, by deriving unbiased estimators of the corresponding risks. We use a generalized SURE (GSURE) development, recently proposed by Eldar for MSE. We consider dependent observation models from the exponential family with an additive noise model,and derive an unbiased estimator for the risk corresponding to the IS distortion, which is non-quadratic. This serves to address the speech enhancement problem in a more general setting. Experimental results illustrate that the IS metric is efficient in suppressing musical noise, which affects the MSE-enhanced speech. However, in terms of global signal-to-noise ratio (SNR), the minimum MSE solution gives better results.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.

Estimation of design basis earthquake using region-specific M-max, for the NPP site at Kalpakkam, Tamil Nadu, India

The objective of the paper is to estimate Safe Shutdown Earthquake (SSE) and Operating/Design Basis Earthquake (OBE/DBE) for the Nuclear Power Plant (NPP) site located at Kalpakkam, Tamil Nadu, India. The NPP is located at 12.558 degrees N, 80.175 degrees E and a 500 km circular area around NPP site is considered as `seismic study area' based on past regional earthquake damage distribution. The geology, seismicity and seismotectonics of the study area are studied and the seismotectonic map is prepared showing the seismic sources and the past earthquakes. Earthquake data gathered from many literatures are homogenized and declustered to form a complete earthquake catalogue for the seismic study area. The conventional maximum magnitude of each source is estimated considering the maximum observed magnitude (M-max(obs)) and/or the addition of 0.3 to 0.5 to M-max(obs). In this study maximum earthquake magnitude has been estimated by establishing a region's rupture character based on source length and associated M-max(obs). A final source-specific M-max is selected from the three M-max values by following the logical criteria. To estimate hazard at the NPP site, ten Ground-Motion Prediction Equations (GMPEs) valid for the study area are considered. These GMPEs are ranked based on Log-Likelihood (LLH) values. Top five GMPEs are considered to estimate the peak ground acceleration (PGA) for the site. Maximum PGA is obtained from three faults and named as vulnerable sources to decide the magnitudes of OBE and SSE. The average and normalized site specific response spectrum is prepared considering three vulnerable sources and further used to establish site-specific design spectrum at NPP site.

Resonance raman detection and estimation in the aqueous phase using water dispersible cyclodextrin: reduced-graphene oxide sheets

Resonance Raman spectroscopy is a powerful analytical tool for detecting and identifying analytes, but the associated strong fluorescence background severely limits the use of the technique. Here, we show that by attaching beta-cyclodextrin (beta-CD) cavities to reduced graphene-oxide (rGO) sheets we obtain a water dispersible material (beta-CD: rGO) that combines the hydrophobicity associated with rGO with that of the cyclodextrin cavities and provides a versatile platform for resonance Raman detection. Planar aromatic and dye molecules that adsorb on the rGO domains and nonplanar molecules included within the tethered beta-CD cavities have their fluorescence effectively quenched. We show that it is possible using the water dispersible beta-CD: rGO sheets to record the resonance Raman spectra of adsorbed and included organic chromophores directly in aqueous media without having to extract or deposit on a substrate. This is significant, as it allows us to identify and estimate organic analytes present in water by resonance Raman spectroscopy.

Universal flame propagation behavior in packed bed of biomass

This article aims at seeking the universal behavior of propagation rate variation with air superficial velocity (V-s) in a packed bed of a range of biomass particles in reverse downdraft mode while also resolving the differing and conflicting explanations in the literature. Toward this, measurements are made of exit gas composition, gas phase and condensed phase surface temperature (T-g and T-s), and reaction zone thickness for a number of biomass with a range of properties. Based on these data, two regimes are identified: gasificationvolatile oxidation accompanied by char reduction reactions up to 16 +/- 1cm/s of V-s and above this, and char oxidationsimultaneous char oxidation and gas phase combustion. In the gasification regime, the measured T-s is less than T-g; a surface heat balance incorporating a diffusion controlled model for flaming combustion gives and matches with the experimental results to within 5%. In the char oxidation regime, T-g and T-s are nearly equal and match with the equilibrium temperature at that equivalence ratio. Drawing from a recent study of the authors, the ash layer over the oxidizing char particle is shown to play a critical role in regulating the radiation heat transfer to fresh biomass in this regime and is shown to be crucial in explaining the observed propagation behavior. A simple model based on radiation-convection balance that tracks the temperature-time evolution of a fresh biomass particle is shown to support the universal behavior of the experimental data on reaction front propagation rate from earlier literature and the present work for biomass with ash content up to 10% and moisture fraction up to 10%. Upstream radiant heat transfer from the ash-laden hot char modulated by the air flow is shown to be the dominant feature of this model.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

Efficient gradient-free simplex method for estimation of optical properties in image-guided diffuse optical tomography

Typical image-guided diffuse optical tomographic image reconstruction procedures involve reduction of the number of optical parameters to be reconstructed equal to the number of distinct regions identified in the structural information provided by the traditional imaging modality. This makes the image reconstruction problem less ill-posed compared to traditional underdetermined cases. Still, the methods that are deployed in this case are same as those used for traditional diffuse optical image reconstruction, which involves a regularization term as well as computation of the Jacobian. A gradient-free Nelder-Mead simplex method is proposed here to perform the image reconstruction procedure and is shown to provide solutions that closely match ones obtained using established methods, even in highly noisy data. The proposed method also has the distinct advantage of being more efficient owing to being regularization free, involving only repeated forward calculations. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

Novel procedure for the estimation of swelling pressures of compacted bentonites based on diffuse double layer theory

Bentonite clays are proven to be attractive as buffer and backfill material in high-level nuclear waste repositories around the world. A quick estimation of swelling pressures of the compacted bentonites for different clay-water-electrolyte interactions is essential in the design of buffer and backfill materials. The theoretical studies on the swelling behavior of bentonites are based on diffuse double layer (DDL) theory. To establish theoretical relationship between void ratio and swelling pressure (e versus P), evaluation of elliptic integral and inverse analysis are unavoidable. In this paper, a novel procedure is presented to establish theoretical relationship of e versus P based on the Gouy-Chapman method. The proposed procedure establishes a unique relationship between electric potentials of interacting and non-interacting diffuse clay-water-electrolyte systems. A procedure is, thus, proposed to deduce the relation between swelling pressures and void ratio from the established relation between electric potentials. This approach is simple and alleviates the need for elliptic integral evaluation and also the inverse analysis. Further, application of the proposed approach to estimate swelling pressures of four compacted bentonites, for example, MX 80, Febex, Montigel and Kunigel V1, at different dry densities, shows that the method is very simple and predicts solutions with very good accuracy. Moreover, the proposed procedure provides continuous distributions of e versus P and thus it is computationally efficient when compared with the existing techniques.