BER Analysis of Space Shift Keying in Cooperative Multi-hop Multi-branch DF Relaying

Space shift keying (SSK) is an attractive modulation technique for multi-antenna communications. In SSK, only one among the available transmit antennas is activated during one channel use, and the index of the chosen transmit antenna conveys information. In this paper, we analyze the performance of SSK in multi-hop, multi-branch cooperative relaying systems. We consider the decode-and-forward relaying protocol, where a relay forwards the decoded symbol if it decodes the symbol correctly from the received signal. We derive closed-form expressions for the end-to-end bit error rate of SSK in this system. Analytical and simulation results match very well.

Filling-in Void and Sparse Regions in Protein Sequence Space by Protein-Like Artificial Sequences Enables Remarkable Enhancement in Remote Homology Detection Capability

Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

Optimal trajectory planning for path convergence in three-dimensional space

This article addresses the problem of determining the shortest path that connects a given initial configuration (position, heading angle, and flight path angle) to a given rectilinear or a circular path in three-dimensional space for a constant speed and turn-rate constrained aerial vehicle. The final path is assumed to be located relatively far from the starting point. Due to its simplicity and low computational requirements the algorithm can be implemented on a fixed-wing type unmanned air vehicle in real time in missions where the final path may change dynamically. As wind has a very significant effect on the flight of small aerial vehicles, the method of optimal path planning is extended to meet the same objective in the presence of wind comparable to the speed of the aerial vehicles. But, if the path to be followed is closer to the initial point, an off-line method based on multiple shooting, in combination with a direct transcription technique, is used to obtain the optimal solution. Optimal paths are generated for a variety of cases to show the efficiency of the algorithm. Simulations are presented to demonstrate tracking results using a 6-degrees-of-freedom model of an unmanned air vehicle.

Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs

Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.

Characterization and Space-Time Downscaling of the Inundation Extent over the Inner Niger Delta Using GIEMS and MODIS Data

The objective in this work is to develop downscaling methodologies to obtain a long time record of inundation extent at high spatial resolution based on the existing low spatial resolution results of the Global Inundation Extent from Multi-Satellites (GIEMS) dataset. In semiarid regions, high-spatial-resolution a priori information can be provided by visible and infrared observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). The study concentrates on the Inner Niger Delta where MODIS-derived inundation extent has been estimated at a 500-m resolution. The space-time variability is first analyzed using a principal component analysis (PCA). This is particularly effective to understand the inundation variability, interpolate in time, or fill in missing values. Two innovative methods are developed (linear regression and matrix inversion) both based on the PCA representation. These GIEMS downscaling techniques have been calibrated using the 500-m MODIS data. The downscaled fields show the expected space-time behaviors from MODIS. A 20-yr dataset of the inundation extent at 500 m is derived from this analysis for the Inner Niger Delta. The methods are very general and may be applied to many basins and to other variables than inundation, provided enough a priori high-spatial-resolution information is available. The derived high-spatial-resolution dataset will be used in the framework of the Surface Water Ocean Topography (SWOT) mission to develop and test the instrument simulator as well as to select the calibration validation sites (with high space-time inundation variability). In addition, once SWOT observations are available, the downscaled methodology will be calibrated on them in order to downscale the GIEMS datasets and to extend the SWOT benefits back in time to 1993.

Combined transparency and optical nonlinearity enhancement in flexible covalent multimers by operating through-space interactions between dipolar chromophores

Subtle manipulation of mutual repulsion and polarisation effects between polar and polarisable chromophores forced in closed proximity allows achieving major (100%) enhancement of the first hyperpolarisability together with increased transparency, breaking the well-known nonlinearity-transparency trade-off paradigm.

Role of orography in modulating space-time scales of convection over South Asia

Propagation of convective systems in the meridional direction during boreal summer is responsible for active and break phases of monsoon over south Asia. This region is unique in the world in its characteristics of monsoon variability and is in close proximity of mountains like the Himalayas. Here, using an atmospheric general circulation model, we try to understand the role of orography in determining spatial and temporal scales of these convective systems. Absence of orography (noGlOrog) decreased the simulated seasonal mean precipitation over India by 23 % due to delay in onset by about a month vis-a-vis the full-mountain case. In noGlOrog, poleward propagations were absent during the delayed period prior to onset. Post-onset, both simulations had similar patterns of poleward propagations. The spatial and temporal scales of propagating clouds bands were determined using wavelet analysis. These scales were found to be different in full-mountain and no-mountain experiments in June-July. However, after the onset of monsoon in noGlOrog, these scales become similar to that with orography. Simulations with two different sets of convection schemes confirmed this result. Further analysis shows that the absence (presence) of meridional propagations during early (late) phase of summer monsoon in noGlOrog was associated with weaker (stronger) vertical shear of zonal wind over south Asia. Our study shows that orography plays a major role in determining the time of onset over the Indian region. However, after onset, basic characteristics of propagating convective systems and therefore the monthly precipitation over India, are less sensitive to the presence of orography and are modulated by moist convective processes.

Space-Vector-Based Hybrid Pulsewidth Modulation Techniques for a Three-Level Inverter

Novel switching sequences have been proposed recently for a neutral-point-clamped three-level inverter, controlled effectively as an equivalent two-level inverter. It is shown that the four novel sequences can be grouped into two pairs of sequences. Using each pair of sequences, a hybrid pulsewidth modulation (PWM) technique is proposed, which deploys the two sequences in appropriate spatial regions to reduce the current ripple. Further, a third hybrid PWM technique is proposed which uses all the five sequences (including the conventional sequence) in appropriate spatial regions. Each proposed hybrid PWM is shown, both analytically and experimentally, to outperform its constituent PWM methods in terms of harmonic distortion. In particular, the third proposed hybrid PWM reduces the total harmonic distortion considerably at low- and high-speed ranges of a constant volts-per-hertz induction motor drive, compared to centered space vector PWM.

A Nearly Constant Switching Frequency Current Error Space Vector Based Hysteresis Controller for an IM Drive with 12-sided Polygonal Voltage Space Vectors

In this paper, a current error space vector (CESV) based hysteresis controller for a 12-sided polygonal voltage space vector inverter fed induction motor (IM) drive is proposed, for the first time. An open-end winding configuration is used for the induction motor. The proposed controller uses parabolic boundary with generalized vector selection logic for all sectors. The drive scheme is first studied with a space vector based PWM (SVPWM) control and from this the current error space phasor boundary is obtained. This current error space phasor boundary is approximated with four parabolas and then the system is run with space phasor based hysteresis PWM controller by limiting the CESV within the parabolic boundary. The proposed controller has increased modulation range, absence of 5th and 7th order harmonics for the entire modulation range, nearly constant switching frequency, fast dynamic response with smooth transition to the over modulation region and a simple controller implementation.

Optimal sequential wireless relay placement on a random lattice path

Our work is motivated by impromptu (or ``as-you-go'') deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control center), and evolving randomly over a lattice in the positive quadrant. A person walks along the path deploying relay nodes as he goes. At each step, the path can, randomly, either continue in the same direction or take a turn, or come to an end, at which point a data source (e.g., a sensor) has to be placed, that will send packets to the data sink. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple link-by-link scheduling, we consider the problem of sequential relay placement so as to minimize the expectation of an end-to-end cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process. First, we derive the optimal policy in terms of an optimal placement set and show that this set is characterized by a boundary (with respect to the position of the last placed relay) beyond which it is optimal to place the next relay. Next, based on a simpler one-step-look-ahead characterization of the optimal policy, we propose an algorithm which is proved to converge to the optimal placement set in a finite number of steps and which is faster than value iteration. We show by simulations that the distance threshold based heuristic, usually assumed in the literature, is close to the optimal, provided that the threshold distance is carefully chosen. (C) 2014 Elsevier B.V. All rights reserved.

Space vector based modulation scheme for reducing capacitor RMS current in three-level diode-clamped inverter

The DC capacitor is an important component in a voltage source inverter.The RMS current flowing through the capacitor determines the capacitor size and losses. The losses, in turn, influence the capacitor life. This paper proposes a space vector based modulation strategy for reducing the capacitor RMS current in a three-level diode-clamped inverter. An analytical closed-form expression is derived for the DC capacitor RMS current with the proposed PWM strategy. The analytical expression is validated through simulations and also experimentally. Theoretical and experimental results are presented, comparing the proposed strategy with conventional space vector PWM (CSVPWM). It is shown that the proposed strategy reduces the capacitor RMS current significantly at high modulation indices and high power factors. (C) 2014 Elsevier B.V. All rights reserved.

Spectrum sensing using distributed sequential detection via noisy reporting MAC

This paper considers cooperative spectrum sensing algorithms for Cognitive Radios which focus on reducing the number of samples to make a reliable detection. We propose algorithms based on decentralized sequential hypothesis testing in which the Cognitive Radios sequentially collect the observations, make local decisions and send them to the fusion center for further processing to make a final decision on spectrum usage. The reporting channel between the Cognitive Radios and the fusion center is assumed more realistically as a Multiple Access Channel (MAC) with receiver noise. Furthermore the communication for reporting is limited, thereby reducing the communication cost. We start with an algorithm where the fusion center uses an SPRT-like (Sequential Probability Ratio Test) procedure and theoretically analyze its performance. Asymptotically, its performance is close to the optimal centralized test without fusion center noise. We further modify this algorithm to improve its performance at practical operating points. Later we generalize these algorithms to handle uncertainties in SNR and fading. (C) 2014 Elsevier B.V. All rights reserved.

OFDM-Aided Differential Space-Time Shift Keying Using Iterative Soft Multiple-Symbol Differential Sphere Decoding

Soft-decision multiple-symbol differential sphere decoding (MSDSD) is proposed for orthogonal frequency-division multiplexing (OFDM)-aided differential space-time shift keying (DSTSK)-aided transmission over frequency-selective channels. Specifically, the DSTSK signaling blocks are generated by the channel-encoded source information and the space-time (ST) blocks are appropriately mapped to a number of OFDM subcarriers. After OFDM demodulation, the DSTSK signal is noncoherently detected by our soft-decision MSDSD detector. A novel soft-decision MSDSD detector is designed, and the associated decision rule is derived for the DSTSK scheme. Our simulation results demonstrate that an SNR reduction of 2 dB is achieved by the proposed scheme using an MSDSD window size of N-w = 4 over the conventional soft-decision-aided differential detection benchmarker, while communicating over dispersive channels and dispensing with channel estimation (CE).

Use of Exocentric and Egocentric Representations in the Concurrent Planning of Sequential Saccades

The concurrent planning of sequential saccades offers a simple model to study the nature of visuomotor transformations since the second saccade vector needs to be remapped to foveate the second target following the first saccade. Remapping is thought to occur through egocentric mechanisms involving an efference copy of the first saccade that is available around the time of its onset. In contrast, an exocentric representation of the second target relative to the first target, if available, can be used to directly code the second saccade vector. While human volunteers performed a modified double-step task, we examined the role of exocentric encoding in concurrent saccade planning by shifting the first target location well before the efference copy could be used by the oculomotor system. The impact of the first target shift on concurrent processing was tested by examining the end-points of second saccades following a shift of the second target during the first saccade. The frequency of second saccades to the old versus new location of the second target, as well as the propagation of first saccade localization errors, both indices of concurrent processing, were found to be significantly reduced in trials with the first target shift compared to those without it. A similar decrease in concurrent processing was obtained when we shifted the first target but kept constant the second saccade vector. Overall, these results suggest that the brain can use relatively stable visual landmarks, independent of efference copy-based egocentric mechanisms, for concurrent planning of sequential saccades.