Enhanced DMT-optimality criterion for STBC schemes for asymmetric MIMO systems

For any n(t) transmit, n(r) receive antenna (n(t) x n(r)) multiple-input multiple-output (MIMO) system in a quasi-static Rayleigh fading environment, it was shown by Elia et al. that linear space-time block code schemes (LSTBC schemes) that have the nonvanishing determinant (NVD) property are diversity-multiplexing gain tradeoff (DMT)-optimal for arbitrary values of n(r) if they have a code rate of n(t) complex dimensions per channel use. However, for asymmetric MIMO systems (where n(r) < n(t)), with the exception of a few LSTBC schemes, it is unknown whether general LSTBC schemes with NVD and a code rate of n(r) complex dimensions per channel use are DMT optimal. In this paper, an enhanced sufficient criterion for any STBC scheme to be DMT optimal is obtained, and using this criterion, it is established that any LSTBC scheme with NVD and a code rate of min {n(t), n(r)} complex dimensions per channel use is DMT optimal. This result settles the DMT optimality of several well-known, low-ML-decoding-complexity LSTBC schemes for certain asymmetric MIMO systems.

A Novel Monte-Carlo-Sampling-Based Receiver for Large-Scale Uplink Multiuser MIMO Systems

In this paper, we propose low-complexity algorithms based on Monte Carlo sampling for signal detection and channel estimation on the uplink in large-scale multiuser multiple-input-multiple-output (MIMO) systems with tens to hundreds of antennas at the base station (BS) and a similar number of uplink users. A BS receiver that employs a novel mixed sampling technique (which makes a probabilistic choice between Gibbs sampling and random uniform sampling in each coordinate update) for detection and a Gibbs-sampling-based method for channel estimation is proposed. The algorithm proposed for detection alleviates the stalling problem encountered at high signal-to-noise ratios (SNRs) in conventional Gibbs-sampling-based detection and achieves near-optimal performance in large systems with M-ary quadrature amplitude modulation (M-QAM). A novel ingredient in the detection algorithm that is responsible for achieving near-optimal performance at low complexity is the joint use of a mixed Gibbs sampling (MGS) strategy coupled with a multiple restart (MR) strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for a large number of BS antennas and users (e. g., 64 and 128 BS antennas and users). The proposed Gibbs-sampling-based channel estimation algorithm refines an initial estimate of the channel obtained during the pilot phase through iterations with the proposed MGS-based detection during the data phase. In time-division duplex systems where channel reciprocity holds, these channel estimates can be used for multiuser MIMO precoding on the downlink. The proposed receiver is shown to achieve good performance and scale well for large dimensions.

Assessing resilience and state-transition models with historical records of cheatgrass Bromus tectorum invasion in North American sagebrush-steppe

1. Resilience-based approaches are increasingly being called upon to inform ecosystem management, particularly in arid and semi-arid regions. This requires management frameworks that can assess ecosystem dynamics, both within and between alternative states, at relevant time scales. 2. We analysed long-term vegetation records from two representative sites in the North American sagebrush-steppe ecosystem, spanning nine decades, to determine if empirical patterns were consistent with resilience theory, and to determine if cheatgrass Bromus tectorum invasion led to thresholds as currently envisioned by expert-based state-and-transition models (STM). These data span the entire history of cheatgrass invasion at these sites and provide a unique opportunity to assess the impacts of biotic invasion on ecosystem resilience. 3. We used univariate and multivariate statistical tools to identify unique plant communities and document the magnitude, frequency and directionality of community transitions through time. Community transitions were characterized by 37-47% dissimilarity in species composition, they were not evenly distributed through time, their frequency was not correlated with precipitation, and they could not be readily attributed to fire or grazing. Instead, at both sites, the majority of community transitions occurred within an 8-10year period of increasing cheatgrass density, became infrequent after cheatgrass density peaked, and thereafter transition frequency declined. 4. Greater cheatgrass density, replacement of native species and indication of asymmetry in community transitions suggest that thresholds may have been exceeded in response to cheatgrass invasion at one site (more arid), but not at the other site (less arid). Asymmetry in the direction of community transitions also identified communities that were at-risk' of cheatgrass invasion, as well as potential restoration pathways for recovery of pre-invasion states. 5. Synthesis and applications. These results illustrate the complexities associated with threshold identification, and indicate that criteria describing the frequency, magnitude, directionality and temporal scale of community transitions may provide greater insight into resilience theory and its application for ecosystem management. These criteria are likely to vary across biogeographic regions that are susceptible to cheatgrass invasion, and necessitate more in-depth assessments of thresholds and alternative states, than currently available.

Model-checking bisimulation-based information flow properties for infinite state sstems

Bisimulation-based information flow properties were introduced by Focardi and Gorrieri [1] as a way of specifying security properties for transition system models. These properties were shown to be decidable for finite-state systems. In this paper, we study the problem of verifying these properties for some well-known classes of infinite state systems. We show that all the properties are undecidable for each of these classes of systems.

Versatility of azide in serendipitous assembly of Copper(II) Magnetic Polyclusters

Engineering at the molecular level is one of the most exciting new developments for the generation of functional materials. However, the concept of designing polynuclear extended structures from bottom up is still not mature. Although progress has been made with secondary building units (SBUs) in metal organic frameworks (MOFs), the control seems to be just an illusion when it comes to bridging ligands such as the azide ion. When we say that the azido ligand is versatile in its bridging capabilities, what we mean is that it would be difficult to predict or control its bridging properties. However, this kind of serendipity is not always bad news. For example, scientists have shown that the azido ligand can mediate magnetic exchanges between paramagnetic metals in a predictable fashion (usually depending upon the bonding geometries). Therefore, it is a well-respected ligand in polynuclear assemblies. Serendipitous assemblies offer new magnetic structures that we may not otherwise even think about synthesizing. The azido ligand forms a variety of complexes with copper(II) using different blocking amines or pyridine based ligands. Its structural nature changes upon changing the substitution on amine, as well as the amount of blocking ligand. In principle, if we take any of these complexes and provide more coordination sites to the bridging azido ligands by removing a fraction of the blocking ligands, we can get new complexes with intricate structural networks and therefore different magnetic properties with the same components as used for the parent complex. In this Account, we mainly discuss the development of a number of new topological and magnetic exchange systems synthesized using this concept. Not all of these new complexes can be grouped according to their basic building structures or even by the ratio of the metal to blocking ligand. Therefore, we divided the discussion by the nuclearity of the basic building structures. Some of the complexes with the same nuclearities have very similar or even almost identical basic structures. However, the way these building units are joined together (by the azido bridges) to form the overall extended structures differ almost in every case. The complexes having the Cu-6 core are particularly interesting from a structural point of view. Although they have almost identical basic structures, some of them are extended in three dimensions, but two of them are extended in two dimensions by two different bridging networks. In the complexes having linear Cu-4 basic units, we find that using similar ligands does not always give the same bridging networks even within the basic building structures. These complexes have also enriched the field of molecular magnetism. One of the complexes with a Cu-3 building unit has provided us with the opportunity to study the competing behavior of two different kinds of magnetic exchange mechanism (ferromagnetic and antiferromagnetic) acting simultaneously between two metal ions. Through density functional theory calculations, we showed how they work independently and their additive nature to produce the overall effect. The exciting methodology for the generation of copper(II) polyclusters presented in this Account will provide the opportunity to explore analogous serendipitous assembly of diverse structures with interesting magnetic behavior using other transition metal ions having more than one unpaired electrons.

Low-complexity near-optimal signal detection in underdetermined large-MIMO systems

In this paper, we consider signal detection in nt × nr underdetermined MIMO (UD-MIMO) systems, where i) nt >; nr with a overload factor α = nt over nr >; 1, ii) nt symbols are transmitted per channel use through spatial multiplexing, and iii) nt, nr are large (in the range of tens). A low-complexity detection algorithm based on reactive tabu search is considered. A variable threshold based stopping criterion is proposed which offers near-optimal performance in large UD-MIMO systems at low complexities. A lower bound on the maximum likelihood (ML) bit error performance of large UD-MIMO systems is also obtained for comparison. The proposed algorithm is shown to achieve BER performance close to the ML lower bound within 0.6 dB at an uncoded BER of 10-2 in 16 × 8 V-BLAST UD-MIMO system with 4-QAM (32 bps/Hz). Similar near-ML performance results are shown for 32 × 16, 32 × 24 V-BLAST UD-MIMO with 4-QAM/16-QAM as well. A performance and complexity comparison between the proposed algorithm and the λ-generalized sphere decoder (λ-GSD) algorithm for UD-MIMO shows that the proposed algorithm achieves almost the same performance of λ-GSD but at a significantly lesser complexity.

A Phase Transition for the Uniform Distribution in the Pattern Maximum Likelihood Problem

In this paper, we consider the setting of the pattern maximum likelihood (PML) problem studied by Orlitsky et al. We present a well-motivated heuristic algorithm for deciding the question of when the PML distribution of a given pattern is uniform. The algorithm is based on the concept of a ``uniform threshold''. This is a threshold at which the uniform distribution exhibits an interesting phase transition in the PML problem, going from being a local maximum to being a local minimum.

Modeling Time-Varying Aggregate Interference in Cognitive Radio Systems, and Application to Primary Exclusive Zone Design

Accurately characterizing the time-varying interference caused to the primary users is essential in ensuring a successful deployment of cognitive radios (CR). We show that the aggregate interference at the primary receiver (PU-Rx) from multiple, randomly located cognitive users (CUs) is well modeled as a shifted lognormal random process, which is more accurate than the lognormal and the Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, which depends on path-loss, shadowing, and small-scale fading of the link from the primary transmitter to the CU; the interweave and underlay modes or CR operation, which determine the transmit powers of the CUs; and time-correlated shadowing and fading of the links from the CUs to the PU-Rx. It leads to expressions for the probability distribution function, level crossing rate, and average exceedance duration. The impact of cooperative spectrum sensing is also characterized. We validate the model by applying it to redesign the primary exclusive zone to account for the time-varying nature of interference.

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.

Direct hexagonal transition of amorphous (Ge2Sb2Te5)(0.9)Se-0.1 thin films

Ge2Sb2Te5 (GST) is well known for its phase change properties and applications in memory and data storage. Efforts are being made to improve its thermal stability and transition between amorphous and crystalline phases. Various elements are doped to GST to improve these properties. In this work, Se has been doped to GST to study its effect on phase change properties. Amorphous GST film crystallized in to rock salt (NaCl) type structure at 150 degrees C and then transformed to hexagonal structure at 250 degrees C. Interestingly, Se doped GST ((GST)(0.9)Se-0.1) film crystallized directly into hexagonal phase and the intermediate phase of NaCl is not observed. The crystallization temperature (T-c) of (GST)(0.9)Se-0.1 is around 200 degrees C, which is 50 degrees C higher than the T-c of GST. For (GST)(0.9)Se-0.1, the threshold switching occurs at about 4.5V which is higher than GST (3 V). Band gap (E-opt) values of as deposited films are calculated from Tauc plot which are 0.63 eV for GST and 0.66 eV for (GST)(0.9)Se-0.1. The E-opt decreases for the films annealed at higher temperatures. The increased T-c, E-opt, the contrast in resistance and the direct transition to hexagonal phase may improve the data readability and thermal stability in the Se doped GST film. (C) 2014 AIP Publishing LLC.

Estimation of time variant reliability of randomly parametered non-linear vibrating systems

The problem of time variant reliability analysis of randomly parametered and randomly driven nonlinear vibrating systems is considered. The study combines two Monte Carlo variance reduction strategies into a single framework to tackle the problem. The first of these strategies is based on the application of the Girsanov transformation to account for the randomness in dynamic excitations, and the second approach is fashioned after the subset simulation method to deal with randomness in system parameters. Illustrative examples include study of single/multi degree of freedom linear/non-linear inelastic randomly parametered building frame models driven by stationary/non-stationary, white/filtered white noise support acceleration. The estimated reliability measures are demonstrated to compare well with results from direct Monte Carlo simulations. (C) 2014 Elsevier Ltd. All rights reserved.

Transition from Cassie to impaled state during drop impact on groove-textured solid surfaces

Liquid drops impacted on textured surfaces undergo a transition from the Cassie state characterized by the presence of air pockets inside the roughness valleys below the drop to an impaled state with at least one of the roughness valleys filled with drop liquid. This occurs when the drop impact velocity exceeds a particular value referred to as the critical impact velocity. The present study investigates such a transition process during water drop impact on surfaces textured with unidirectional parallel grooves referred to as groove-textured surfaces. The process of liquid impalement into a groove in the vicinity of drop impact through de-pinning of the three-phase contact line (TPCL) beneath the drop as well as the critical impact velocity were identified experimentally from high speed video recordings of water drop impact on six different groove-textured surfaces made from intrinsically hydrophilic (stainless steel) as well as intrinsically hydrophobic (PDMS and rough aluminum) materials. The surface energy of various 2-D configurations of liquid-vapor interface beneath the drop near the drop impact point was theoretically investigated to identify the locally stable configurations and establish a pathway for the liquid impalement process. A force balance analysis performed on the liquid-vapor interface configuration just prior to TPCL de-pinning provided an expression for the critical drop impact velocity, U-o,U-cr, beyond which the drop state transitions from the Cassie to an impaled state. The theoretical model predicts that Uo, cr increases with the increase in pillar side angle, a, and intrinsic hydrophobicity whereas it decreases with the increase in groove top width, w, of the groove-textured surface. The quantitative predictions of the theoretical model were found to show good agreement with the experimental measurements of U-o,U-cr plotted against the surface texture geometry factor in our model, {tan(alpha/2)/w}(0.5).

Fair Scheduling in Cellular Systems in the Presence of Noncooperative Mobiles

We consider the problem of ``fair'' scheduling the resources to one of the many mobile stations by a centrally controlled base station (BS). The BS is the only entity taking decisions in this framework based on truthful information from the mobiles on their radio channel. We study the well-known family of parametric alpha-fair scheduling problems from a game-theoretic perspective in which some of the mobiles may be noncooperative. We first show that if the BS is unaware of the noncooperative behavior from the mobiles, the noncooperative mobiles become successful in snatching the resources from the other cooperative mobiles, resulting in unfair allocations. If the BS is aware of the noncooperative mobiles, a new game arises with BS as an additional player. It can then do better by neglecting the signals from the noncooperative mobiles. The BS, however, becomes successful in eliciting the truthful signals from the mobiles only when it uses additional information (signal statistics). This new policy along with the truthful signals from mobiles forms a Nash equilibrium (NE) that we call a Truth Revealing Equilibrium. Finally, we propose new iterative algorithms to implement fair scheduling policies that robustify the otherwise nonrobust (in presence of noncooperation) alpha-fair scheduling algorithms.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

Pressure Dependence of Glass Transition in As2Te3 Glass

Amorphous solids prepared from their melt state exhibit glass transition phenomenon upon heating. Viscosity, specific heat, and thermal expansion coefficient of the amorphous solids show rapid changes at the glass transition temperature (T-g). Generally, application of high pressure increases the T-g and this increase (a positive dT(g)/dP) has been understood adequately with free volume and entropy models which are purely thermodynamic in origin. In this study, the electrical resistivity of semiconducting As2Te3 glass at high pressures as a function of temperature has been measured in a Bridgman anvil apparatus. Electrical resistivity showed a pronounced change at T-g. The T-g estimated from the slope change in the resistivity-temperature plot shows a decreasing trend (negative dT(g)/dP). The dT(g)/dP was found to be -2.36 degrees C/kbar for a linear fit and -2.99 degrees C/kbar for a polynomial fit in the pressure range 1 bar to 9 kbar. Chalcogenide glasses like Se, As2Se3, and As30Se30Te40 show a positive dT(g)/dP which is very well understood in terms of the thermodynamic models. The negative dT(g)/dP (which is generally uncommon in liquids) observed for As2Te3 glass is against the predictions of the thermodynamic models. The Adam-Gibbs model of viscosity suggests a direct relationship between the isothermal pressure derivative of viscosity and the relaxational expansion coefficient. When the sign of the thermal expansion coefficient is negative, dT(g)/dP = Delta k/Delta alpha will be less than zero, which can result in a negative dT(g)/dP. In general, chalcogenides rich in tellurium show a negative thermal expansion coefficient (NTE) in the supercooled and stable liquid states. Hence, the negative dT(g)/dP observed in this study can be understood on the basis of the Adams-Gibbs model. An electronic model proposed by deNeufville and Rockstad finds a linear relation between T-g and the optical band gap (E-g for covalent semiconducting glasses when they are grouped according to their average coordination number. The electrical band gap (Delta E) of As2Te3 glass decreases with pressure. The optical and electrical band gaps are related as Delta E-g = 2 Delta E; thus, a negative dT(g)/dP is expected when As2Te3 glass is subjected to high pressures. In this sense, As2Te3 is a unique glass where its variation of T-g with pressure can be understood by both electronic and thermodynamic models.