Modeling of terahertz heating effects in realistic tissues

Theterahertz (THz) propagation in real tissues causes heating as with any other electromagnetic radiation propagation. A finite-element (FE) model that provides numerical solutions to the heat conduction equation coupled with realistic models of tissues is employed in this study to compute the temperature raise due to THz propagation. The results indicate that the temperature raise is dependent on the tissue type and is highly localized. The developed FE model was validated through obtaining solutions for the steady-state case and showing that they were in good agreement with the analytical solutions. These types of models can also enable computation of specific absorption rates, which are very critical in planning/setting up experiments involving biological tissues.

Generalized distributive law for ML decoding of space-time block codes

The problem of designing good space-time block codes (STBCs) with low maximum-likelihood (ML) decoding complexity has gathered much attention in the literature. All the known low ML decoding complexity techniques utilize the same approach of exploiting either the multigroup decodable or the fast-decodable (conditionally multigroup decodable) structure of a code. We refer to this well-known technique of decoding STBCs as conditional ML (CML) decoding. In this paper, we introduce a new framework to construct ML decoders for STBCs based on the generalized distributive law (GDL) and the factor-graph-based sum-product algorithm. We say that an STBC is fast GDL decodable if the order of GDL decoding complexity of the code, with respect to the constellation size, is strictly less than M-lambda, where lambda is the number of independent symbols in the STBC. We give sufficient conditions for an STBC to admit fast GDL decoding, and show that both multigroup and conditionally multigroup decodable codes are fast GDL decodable. For any STBC, whether fast GDL decodable or not, we show that the GDL decoding complexity is strictly less than the CML decoding complexity. For instance, for any STBC obtained from cyclic division algebras which is not multigroup or conditionally multigroup decodable, the GDL decoder provides about 12 times reduction in complexity compared to the CML decoder. Similarly, for the Golden code, which is conditionally multigroup decodable, the GDL decoder is only half as complex as the CML decoder.

Advances in base- and mobile-station aided cooperative wireless communications : An overview

In recent years, there has been an upsurge of research interest in cooperative wireless communications in both academia and industry. This article presents a simple overview of the pivotal topics in both mobile station (MS)- and base station (BS)- assisted cooperation in the context of cellular radio systems. Owing to the ever-increasing amount of literature in this particular field, this article is by no means exhaustive, but is intended to serve as a roadmap by assembling a representative sample of recent results and to stimulate further research. The emphasis is initially on relay-base cooperation, relying on network coding, followed by the design of cross-layer cooperative protocols conceived for MS cooperation and the concept of coalition network element (CNE)-assisted BS cooperation. Then, a range of complexity and backhaul traffic reduction techniques that have been proposed for BS cooperation are reviewed. A more detailed discussion is provided in the context of MS cooperation concerning the pros and cons of dispensing with high-complexity, power-hungry channel estimation. Finally, generalized design guidelines, conceived for cooperative wireless communications, are presented.

Channel training signal design for reciprocal multiple antenna systems with beamforming

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes.

Proportional navigation with delayed line-of-sight rate

This brief discusses the convergence analysis of proportional navigation (PN) guidance law in the presence of delayed line-of-sight (LOS) rate information. The delay in the LOS rate is introduced by the missile guidance system that uses a low cost sensor to obtain LOS rate information by image processing techniques. A Lyapunov-like function is used to analyze the convergence of the delay differential equation (DDE) governing the evolution of the LOS rate. The time-to-go until which decreasing behaviour of the Lyapunov-like function can be guaranteed is obtained. Conditions on the delay for finite time convergence of the LOS rate are presented for the linearized engagement equation. It is observed that in the presence of line-of-sight rate delay, increasing the effective navigation constant of the PN guidance law deteriorates its performance. Numerical simulations are presented to validate the results.

A nine-level inverter topology for medium-voltage induction motor drive with open-end stator winding

A new scheme for nine-level voltage space-vector generation for medium-voltage induction motor (IM) drives with open-end stator winding is presented in this paper. The proposed nine-level power converter topology consists of two conventional three-phase two-level voltage source inverters powered by isolated dc sources and six floating-capacitor-connected H-bridges. The H-bridge capacitor voltages are effectively maintained at the required asymmetrical levels by employing a space vector modulation (SVPWM) based control strategy. An interesting feature of this topology is its ability to function in five-or three-level mode, in the entire modulation range, at full-power rating, in the event of any failure in the H-bridges. This feature significantly improves the reliability of the proposed drive system. Each leg of the three-phase two-level inverters used in this topology switches only for a half cycle of the reference voltage waveform. Hence, the effective switching frequency is reduced by half, resulting in switching loss reduction in high-voltage devices. The transient as well as the steady-state performance of the proposed nine-level inverter-fed IM drive system is experimentally verified in the entire modulation range including the overmodulation region.

Noise tolerance under risk minimization

In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.

Joint evaluation of channel feedback schemes, rate adaptation, and scheduling in OFDMA downlinks with feedback delays

Orthogonal frequency-division multiple access (OFDMA) systems divide the available bandwidth into orthogonal subchannels and exploit multiuser diversity and frequency selectivity to achieve high spectral efficiencies. However, they require a significant amount of channel state feedback for scheduling and rate adaptation and are sensitive to feedback delays. We develop a comprehensive analysis for OFDMA system throughput in the presence of feedback delays as a function of the feedback scheme, frequency-domain scheduler, and rate adaptation rule. Also derived are expressions for the outage probability, which captures the inability of a subchannel to successfully carry data due to the feedback scheme or feedback delays. Our model encompasses the popular best-n and threshold-based feedback schemes and the greedy, proportional fair, and round-robin schedulers that cover a wide range of throughput versus fairness tradeoff. It helps quantify the different robustness of the schedulers to feedback overhead and delays. Even at low vehicular speeds, it shows that small feedback delays markedly degrade the throughput and increase the outage probability. Further, given the feedback delay, the throughput degradation depends primarily on the feedback overhead and not on the feedback scheme itself. We also show how to optimize the rate adaptation thresholds as a function of feedback delay.

Experiences with a centralized scheduling approach for performance management of IEEE 802.11 wireless LANs

We present a centralized integrated approach for: 1) enhancing the performance of an IEEE 802.11 infrastructure wireless local area network (WLAN), and 2) managing the access link that connects the WLAN to the Internet. Our approach, which is implemented on a standard Linux platform, and which we call ADvanced Wi-fi Internet Service EnhanceR (ADWISER), is an extension of our previous system WLAN Manager (WM). ADWISER addresses several infrastructure WLAN performance anomalies such as mixed-rate inefficiency, unfair medium sharing between simultaneous TCP uploads and downloads, and inefficient utilization of the Internet access bandwidth when Internet transfers compete with LAN-WLAN transfers, etc. The approach is via centralized queueing and scheduling, using a novel, configurable, cascaded packet queueing and scheduling architecture, with an adaptive service rate. In this paper, we describe the design of ADWISER and report results of extensive experimentation conducted on a hybrid testbed consisting of real end-systems and an emulated WLAN on Qualnet. We also present results from a physical testbed consisting of one access point (AP) and a few end-systems.

Thermoelectric performance of a single-layer graphene sheet for energy harvesting

We investigate the thermoelectric (TE) figure-of-merit of a single-layer graphene (SLG) sheet by a physics-based analytical technique. We first develop analytical models of electrical and thermal resistances and the Seebeck coefficient of SLG by considering electron interactions with the in-plane and flexural phonons. Using those models, we show that both the figure-of-merit and the TE efficiency can be substantially increased with the addition of isotope doping as it significantly reduces the phonon-dominated thermal conductivity. In addition, we report that the TE open circuit output voltage and output power depends weakly on the SLG sheet dimensions and sheet concentration in the strongly diffusive regime. Proposed models agree well with the available experimental data and demonstrate the immense potential of graphene for waste-heat recovery application.

Performance and reliability of Gd2O3 and stacked Gd2O3-Eu2O3 metal-insulator-metal capacitors

Gd2O3-based metal-insulator-metal capacitors have been characterized with single layer (Gd2O3) and bilayer (Gd2O3/Eu2O3 and Eu2O3/Gd2O3) stacks for analog and DRAM applications. Although single layer Gd2O3 capacitors provide highest capacitance density (15 fF/mu m(2)), they suffer from high leakage current density, poor capacitance density-voltage linearity, and reliability. The stacked dielectrics help to reduce leakage current density (1.2x10(-5) A/cm(2) and 2.7 x 10(-5) A/cm(2) for Gd2O3/Eu2O3 and Eu2O3/Gd2O3, respectively, at -1 V), improve quadratic voltage coefficient of capacitance (331 ppm/V-2 and 374 ppm/V-2 for Gd2O3/Eu2O3 and Eu2O3/Gd2O3, respectively, at 1 MHz), and improve reliability, with a marginal reduction in capacitance density. This is attributed to lower trap heights as determined from Poole-Frenkel conduction mechanism, and lower defect density as determined from electrode polarization model.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Mitigation of lower order harmonics in a grid-connected single-phase PV inverter

In this paper, a simple single-phase grid-connected photovoltaic (PV) inverter topology consisting of a boost section, a low-voltage single-phase inverter with an inductive filter, and a step-up transformer interfacing the grid is considered. Ideally, this topology will not inject any lower order harmonics into the grid due to high-frequency pulse width modulation operation. However, the nonideal factors in the system such as core saturation-induced distorted magnetizing current of the transformer and the dead time of the inverter, etc., contribute to a significant amount of lower order harmonics in the grid current. A novel design of inverter current control that mitigates lower order harmonics is presented in this paper. An adaptive harmonic compensation technique and its design are proposed for the lower order harmonic compensation. In addition, a proportional-resonant-integral (PRI) controller and its design are also proposed. This controller eliminates the dc component in the control system, which introduces even harmonics in the grid current in the topology considered. The dynamics of the system due to the interaction between the PRI controller and the adaptive compensation scheme is also analyzed. The complete design has been validated with experimental results and good agreement with theoretical analysis of the overall system is observed.

Common-mode filter design for PWM rectifier-based motor drives

A common-mode (CM) filter based on the LCL filter topology is proposed in this paper, which provides a parallel path for ground currents and which also restricts the magnitude of the EMI noise injected into the grid. The CM filter makes use of the components of a line to line LCL filter, which is modified to address the CM voltage with minimal additional components. This leads to a compact filtering solution. The CM voltage of an adjustable speed drive using a PWM rectifier is analyzed for this purpose. The filter design is based on the CM equivalent circuit of the drive system. The filter addresses the adverse effects of the PWM rectifier in an adjustable speed drive. Guidelines are provided on the selection of the filter components. Different variants of the filter topology are evaluated to establish the effectiveness of the proposed circuit. Experimental results based on EMI measurement on the grid side and the CM current measurement on the motor side are presented. These results validate the effectiveness of the filter.