Low-Complexity Near-MAP Decoding of Large Non-Orthogonal STBCs Using PDA

Non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with hundreds of dimensions has been a challenge. In this paper, we present a probabilistic data association (PDA) based algorithm for decoding non-orthogonal STBCs with large dimensions. Our simulation results show that the proposed PDA-based algorithm achieves near SISO AWGN uncoded BER as well as near-capacity coded BER (within 5 dB of the theoretical capacity) for large non-orthogonal STBCs from CDA. We study the effect of spatial correlation on the BER, and show that the performance loss due to spatial correlation can be alleviated by providing more receive spatial dimensions. We report good BER performance when a training-based iterative decoding/channel estimation is used (instead of assuming perfect channel knowledge) in channels with large coherence times. A comparison of the performances of the PDA algorithm and the likelihood ascent search (LAS) algorithm (reported in our recent work) is also presented.

Belief Propagation Based Decoding of Large Non-Orthogonal STBCs

In this paper,we present a belief propagation (BP) based algorithm for decoding non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) having large dimensions. The proposed approachinvolves message passing on Markov random field (MRF) representation of the STBC MIMO system. Adoption of BP approach to decode non-orthogonal STBCs of large dimensions has not been reported so far. Our simulation results show that the proposed BP-based decoding achieves increasingly closer to SISO AWGN performance for increased number of dimensions. In addition, it also achieves near-capacity turbo coded BER performance; for e.g., with BP decoding of 24 x 24 STBC from CDA using BPSK (i.e.,n576 real dimensions) and rate-1/2 turbo code (i.e., 12 bps/Hz spectral efficiency), coded BER performance close to within just about 2.5 dB from the theoretical MIMO capacity is achieved.

Modelling the dynamics of a large sea area

Yhteenveto: Laajan merialueen dynamiikan mallintaminen

PIV studies of large scale structures in the near field of small aspect ratio elliptic jets

The near flow field of small aspect ratio elliptic turbulent free jets (issuing from nozzle and orifice) was experimentally studied using a 2D PIV. Two point velocity correlations in these jets revealed the extent and orientation of the large scale structures in the major and minor planes. The spatial filtering of the instantaneous velocity field using Gaussian convolution kernel shows that while a single large vortex ring circumscribing the jet seems to be present at the exit of nozzle, the orifice jet exhibited a number of smaller vortex ring pairs close to jet exit. The smaller length scale observed in the case of the orifice jet is representative of the smaller azimuthal vortex rings that generate axial vortex field as they are convected. This results in the axis-switching in the case of orifice jet and may have a mechanism different from the self induction process as observed in the case of contoured nozzle jet flow.

SC-FDMA versus OFDMA: Sensitivity to Large Carrier Frequency and Timing Offsets on the Uplink

In this paper, we present a comparison between the sensitivity of SC-FDMA and OFDMA schemes to large carrier frequency offsets (CFO) and timing offsets (TO) of different users on the uplink. Our study shows the following observations: 1) In the ideal case of zero CFOs and TOs (i.e., perfect synchronization), the uncoded BER performance of SC-FDMA with frequency domain MMSE equalizer is better than that of OFDMA due to the inherent frequency diversity that is possible in SCFDMA. Also, because of inter-symbol interference in SC-FDMA, the performance of SC-FDMA with MMSE equalizer can be further improved by using low-complexity interference cancellation (IC) techniques. 2) In the presence of large CFOs and TOs, significant multiuser interference (MUI) gets introduced, and hence the performance of SC-FDMA with MMSE equalizer can get worse than that of OFDMA. However, the performance advantage of SC-FDMA with MMSE equalizer over OFDMA (due to the potential for frequency diversity benefit in SC-FDMA) can be restored by adopting multistage IC techniques, using the knowledge of CFOs and TOs of different users at the receiver

A hybrid electrochemical-thermal method for the preparation of large ZnO nanoparticles

A simple and efficient two-step hybrid electrochemical-thermal route was developed for the synthesis of large quantity of ZnO nanoparticles using aqueous sodium bicarbonate electrolyte and sacrificial Zn anode and cathode in an undivided cell under galvanostatic mode at room temperature. The bath concentration and current density were varied from 30 to 120 mmol and 0.05 to 1.5 A/dm(2). The electrochemically generated precursor was calcined for an hour at different range of temperature from 140 to 600 A degrees C. The calcined samples were characterized by XRD, SEM/EDX, TEM, TG-DTA, FT-IR, and UV-Vis spectral methods. Rietveld refinement of X-ray data indicates that the calcined compound exhibits hexagonal (Wurtzite) structure with space group of P63mc (No. 186). The crystallite sizes were in the range of 22-75 nm based on Debye-Scherrer equation. The TEM results reveal that the particle sizes were in the order of 30-40 nm. The blue shift was noticed in UV-Vis absorption spectra, the band gaps were found to be 5.40-5.11 eV. Scanning electron micrographs suggest that all the samples were randomly oriented granular morphology.

A Training-Based Iterative Detection/Channel Estimation Scheme for Large Non-Orthogonal STBC MIMO Systems

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems.The proposed scheme employs a block transmission strategy where an N-t x N-t pilot matrix is sent (for training purposes) followed by several N-t x N-t square data STBC matrices, where Nt is the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16 x 16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

Diagnosis of dominant forcing factors for large-scale vertical velocities during active and break phases of the monsoon

An attempt to diagnose the dominant forcings which drive the large-scale vertical velocities over the monsoon region has been made by computing the forcings like diabatic heating fields,etc. and the large-scale vertical velocities driven by these forcings for the contrasting periods of active and break monsoon situations; in order to understand the rainfall variability associated with them. Computation of diabatic heating fields show us that among different components of diabatic heating it is the convective heating that dominates at mid-tropospheric levels during an active monsoon period; whereas it is the sensible heating at the surface that is important during a break period. From vertical velocity calculations we infer that the prime differences in the large-scale vertical velocities seen throughout the depth of the atmosphere are due to the differences in the orders of convective heating; the maximum rate of latent heating being more than 10 degrees Kelvin per day during an active monsoon period; whereas during a break monsoon period it is of the order of 2 degrees Kelvin per day at mid-tropospheric levels. At low levels of the atmosphere, computations show that there is large-scale ascent occurring over a large spatial region, driven only by the dynamic forcing associated with vorticity and temperature advection during an active monsoon period. However, during a break monsoon period such large-scale spatial organization in rising motion is not seen. It is speculated that these differences in the low-level large-scale ascent might be causing differences in convective heating because the weaker the low level ascent, the lesser the convective instability which produces deep cumulus clouds and hence lesser the associated latent heat release. The forcings due to other components of diabatic heating, namely, the sensible heating and long wave radiative cooling do not influence the large-scale vertical velocities significantly.

Distributed nonlinear optimization algorithms for general network problems

There are a number of large networks which occur in many problems dealing with the flow of power, communication signals, water, gas, transportable goods, etc. Both design and planning of these networks involve optimization problems. The first part of this paper introduces the common characteristics of a nonlinear network (the network may be linear, the objective function may be non linear, or both may be nonlinear). The second part develops a mathematical model trying to put together some important constraints based on the abstraction for a general network. The third part deals with solution procedures; it converts the network to a matrix based system of equations, gives the characteristics of the matrix and suggests two solution procedures, one of them being a new one. The fourth part handles spatially distributed networks and evolves a number of decomposition techniques so that we can solve the problem with the help of a distributed computer system. Algorithms for parallel processors and spatially distributed systems have been described.There are a number of common features that pertain to networks. A network consists of a set of nodes and arcs. In addition at every node, there is a possibility of an input (like power, water, message, goods etc) or an output or none. Normally, the network equations describe the flows amoungst nodes through the arcs. These network equations couple variables associated with nodes. Invariably, variables pertaining to arcs are constants; the result required will be flows through the arcs. To solve the normal base problem, we are given input flows at nodes, output flows at nodes and certain physical constraints on other variables at nodes and we should find out the flows through the network (variables at nodes will be referred to as across variables).The optimization problem involves in selecting inputs at nodes so as to optimise an objective function; the objective may be a cost function based on the inputs to be minimised or a loss function or an efficiency function. The above mathematical model can be solved using Lagrange Multiplier technique since the equalities are strong compared to inequalities. The Lagrange multiplier technique divides the solution procedure into two stages per iteration. Stage one calculates the problem variables % and stage two the multipliers lambda. It is shown that the Jacobian matrix used in stage one (for solving a nonlinear system of necessary conditions) occurs in the stage two also.A second solution procedure has also been imbedded into the first one. This is called total residue approach. It changes the equality constraints so that we can get faster convergence of the iterations.Both solution procedures are found to coverge in 3 to 7 iterations for a sample network.The availability of distributed computer systems — both LAN and WAN — suggest the need for algorithms to solve the optimization problems. Two types of algorithms have been proposed — one based on the physics of the network and the other on the property of the Jacobian matrix. Three algorithms have been deviced, one of them for the local area case. These algorithms are called as regional distributed algorithm, hierarchical regional distributed algorithm (both using the physics properties of the network), and locally distributed algorithm (a multiprocessor based approach with a local area network configuration). The approach used was to define an algorithm that is faster and uses minimum communications. These algorithms are found to converge at the same rate as the non distributed (unitary) case.

Unified large and small signal non-quasi-static model for long channel symmetric DG MOSFET

We propose a unified model for large signal and small signal non-quasi-static analysis of long channel symmetric double gate MOSFET. The model is physics based and relies only on the very basic approximation needed for a charge-based model. It is based on the EKV formalism Enz C, Vittoz EA. Charge based MOS transistor modeling. Wiley; 2006] and is valid in all regions of operation and thus suitable for RF circuit design. Proposed model is verified with professional numerical device simulator and excellent agreement is found. (C) 2010 Elsevier Ltd. All rights reserved.

Design of speaker identification schemes for large number of speakers (A)

Design of speaker identification schemes for a small number of speakers (around 10) with a high degree of accuracy in controlled environment is a practical proposition today. When the number of speakers is large (say 50–100), many of these schemes cannot be directly extended, as both recognition error and computation time increase monotonically with population size. The feature selection problem is also complex for such schemes. Though there were earlier attempts to rank order features based on statistical distance measures, it has been observed only recently that the best two independent measurements are not the same as the combination in two's for pattern classification. We propose here a systematic approach to the problem using the decision tree or hierarchical classifier with the following objectives: (1) Design of optimal policy at each node of the tree given the tree structure i.e., the tree skeleton and the features to be used at each node. (2) Determination of the optimal feature measurement and decision policy given only the tree skeleton. Applicability of optimization procedures such as dynamic programming in the design of such trees is studied. The experimental results deal with the design of a 50 speaker identification scheme based on this approach.

Crystal Structure of Staphylococcus aureus Metallopeptidase (Sapep) Reveals Large Domain Motions between the Manganese-bound and Apo-states

Proteases belonging to the M20 family are characterized by diverse substrate specificity and participate in several metabolic pathways. The Staphylococcus aureus metallopeptidase, Sapep, is a member of the aminoacylase-I/M20 protein family. This protein is a Mn2+-dependent dipeptidase. The crystal structure of this protein in the Mn2+-bound form and in the open, metal-free state suggests that large interdomain movements could potentially regulate the activity of this enzyme. We note that the extended inactive conformation is stabilized by a disulfide bond in the vicinity of the active site. Although these cysteines, Cys(155) and Cys(178), are not active site residues, the reduced form of this enzyme is substantially more active as a dipeptidase. These findings acquire further relevance given a recent observation that this enzyme is only active in methicillin-resistant S. aureus. The structural and biochemical features of this enzyme provide a template for the design of novel methicillin-resistant S. aureus-specific therapeutics.