Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Coupling geomorphology parameters with lithology for micro-level groundwater resource assessment: a case study from semi-arid hard rock terrain in Tamil Nadu, India

The standard procedure of groundwater resource estimation in India till date is based on the specific yield parameters of each rock type (lithology) derived through pumping test analysis. Using the change in groundwater level, specific yield, and area of influence, groundwater storage change could be estimated. However, terrain conditions in the form of geomorphological variations have an important bearing on the net groundwater recharge. In this study, an attempt was made to use both lithology and geomorphology as input variables to estimate the recharge from different sources in each lithology unit influenced by the geomorphic conditions (lith-geom), season wise separately. The study provided a methodological approach for an evaluation of groundwater in a semi-arid hard rock terrain in Tirunelveli, Tamil Nadu, India. While characterizing the gneissic rock, it was found that the geomorphologic variations in the gneissic rock due to weathering and deposition behaved differently with respect to aquifer recharge. The three different geomorphic units identified in gneissic rock (pediplain shallow weathered (PPS), pediplain moderate weathered (PPM), and buried pediplain moderate (BPM)) showed a significant variation in recharge conditions among themselves. It was found from the study that Peninsular gneiss gives a net recharge value of 0.13 m/year/unit area when considered as a single unit w.r.t. lithology, whereas the same area considered with lith-geom classes gives recharge values between 0.1 and 0.41 m/year presenting a different assessment. It is also found from this study that the stage of development (SOD) for each lith-geom unit in Peninsular gneiss varies from 168 to 230 %, whereas the SOD is 223 % for the lithology as a single unit.

Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method

Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.

Estimation of activation energy for electroporation and pore growth rate in liquid crystalline and gel phases of lipid bilayers using molecular dynamics simulations

Molecular dynamics simulations of electroporation in POPC and DPPC lipid bilayers have been carried out at different temperatures ranging from 230 K to 350 K for varying electric fields. The dynamics of pore formation, including threshold field, pore initiation time, pore growth rate, and pore closure rate after the field is switched off, was studied in both the gel and liquid crystalline (L-alpha) phases of the bilayers. Using an Arrhenius model of pore initiation kinetics, the activation energy for pore opening was estimated to be 25.6 kJ mol(-1) and 32.6 kJ mol(-1) in the L-alpha phase of POPC and DPPC lipids respectively at a field strength of 0.32 V nm(-1). The activation energy decreases to 24.2 kJ mol(-1) and 23.7 kJ mol(-1) respectively at a higher field strength of 1.1 V nm(-1). At temperatures below the melting point, the activation energy in the gel phase of POPC and DPPC increases to 28.8 kJ mol(-1) and 34.4 kJ mol(-1) respectively at the same field of 1.1 V nm(-1). The pore closing time was found to be higher in the gel than in the L-alpha phase. The pore growth rate increases linearly with temperature and quadratically with field, consistent with viscosity limited growth models.

Estimation of background carrier concentration in fully depleted GaN films

Buffer leakage is an important parasitic loss mechanism in AlGaN/GaN high electron mobility transistors (HEMTs) and hence various methods are employed to grow semi-insulating buffer layers. Quantification of carrier concentration in such buffers using conventional capacitance based profiling techniques is challenging due to their fully depleted nature even at zero bias voltages. We provide a simple and effective model to extract carrier concentrations in fully depleted GaN films using capacitance-voltage (C-V) measurements. Extensive mercury probe C-V profiling has been performed on GaN films of differing thicknesses and doping levels in order to validate this model. Carrier concentrations as extracted from both the conventional C-V technique for partially depleted films having the same doping concentration, and Hall measurements show excellent agreement with those predicted by the proposed model thus establishing the utility of this technique. This model can be readily extended to estimate background carrier concentrations from the depletion region capacitances of HEMT structures and fully depleted films of any class of semiconductor materials.

Power Allocation in MIMO Wiretap Channel with Statistical CSI and Finite-Alphabet Input

In this paper, we consider the problem of power allocation in MIMO wiretap channel for secrecy in the presence of multiple eavesdroppers. Perfect knowledge of the destination channel state information (CSI) and only the statistical knowledge of the eavesdroppers CSI are assumed. We first consider the MIMO wiretap channel with Gaussian input. Using Jensen's inequality, we transform the secrecy rate max-min optimization problem to a single maximization problem. We use generalized singular value decomposition and transform the problem to a concave maximization problem which maximizes the sum secrecy rate of scalar wiretap channels subject to linear constraints on the transmit covariance matrix. We then consider the MIMO wiretap channel with finite-alphabet input. We show that the transmit covariance matrix obtained for the case of Gaussian input, when used in the MIMO wiretap channel with finite-alphabet input, can lead to zero secrecy rate at high transmit powers. We then propose a power allocation scheme with an additional power constraint which alleviates this secrecy rate loss problem, and gives non-zero secrecy rates at high transmit powers.

Detection and estimation of liquid flow through a pipe in a tissue-like object with ultrasound-assisted diffuse correlation spectroscopy

Using coherent light interrogating a turbid object perturbed by a focused ultrasound (US) beam, we demonstrate localized measurement of dynamics in the focal region, termed the region-of-interest (ROI), from the decay of the modulation in intensity autocorrelation of light. When the ROI contains a pipe flow, the decay is shown to be sensitive to the average flow velocity from which the mean-squared displacement (MSD) of the scattering centers in the flow can be estimated. While the MSD estimated is seen to be an order of magnitude higher than that obtainable through the usual diffusing wave spectroscopy (DWS) without the US, it is seen to be more accurate as verified by the volume flow estimated from it. It is further observed that, whereas the MSD from the localized measurement grows with time as tau(alpha) with alpha approximate to 1.65, without using the US, a is seen to be much less. Moreover, with the local measurement, this super-diffusive nature of the pipe flow is seen to persist longer, i.e., over a wider range of initial tau, than with the unassisted DWS. The reason for the super-diffusivity of flow, i.e., alpha < 2, in the ROI is the presence of a fluctuating (thermodynamically nonequilibrium) component in the dynamics induced by the US forcing. Beyond this initial range, both methods measure MSDs that rise linearly with time, indicating that ballistic and near-ballistic photons hardly capture anything beyond the background Brownian motion. (C) 2015 Optical Society of America

Optimal input cross-power spectra in shake table testing of asymmetric structures

The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.