A selective control information detection scheme for OFDM receivers

In wireless communications, both control information and payload (user-data) are concurrently transmitted and required to be successfully recovered. This paper focuses on block-level detection, which is applicable for detecting transmitted control information, particularly when this information is selected or chosen from a finite set of information that are known at both transmitting and receiving devices. Using an orthogonal frequency division multiplexing architecture, this paper investigates and evaluates the performance of a time-domain decision criterion in comparison with a form of Maximum Likelihood (ML) estimation method. Unlike the ML method, the proposed time-domain detection technique requires no channel estimation as it uses the correlation (in the time-domain) that exists between the received and the transmitted selective information as a means of detection. In comparison with the ML method, results show that the proposed method offers improved detection performance, particularly when the control information consists of at least 16. However, the implementation of the proposed method requires a slightly increased number of mathematical computations

A low complexity SI sequence estimator for pilot-aided SLM–OFDM systems

Selected mapping (SLM) is a well-known method for reducing peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. However, as a consequence of implementing SLM, OFDM receivers often require estimation of some side information (SI) in order to achieve successful data recovery. Existing SI estimation schemes have very high computational complexities that put additional constraints on limited resources and increase system complexity. To address this problem, an alternative SLM approach that facilitates estimation of SI in the form of phase detection is presented. Simulations show that this modified SLM approach produces similar PAPR reduction performance when compared to conventional SLM. With no amplifier distortion and in the presence of non-linear power amplifier distortion, the proposed SI estimation approach achieves similar data recovery performance as both standard SLM–OFDM (with perfect SI estimation) and also when SI estimation is implemented through the use of an existing frequency-domain correlation (FDC) decision metric. In addition, the proposed method significantly reduces computational complexity compared with the FDC scheme and an ML estimation scheme

A joint OFDM PAPR reduction and data decoding scheme with no SI estimation

The need for side information (SI) estimation poses a major challenge when selected mapping (SLM) is implemented to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. Recent studies on pilot-assisted SI estimation procedures suggest that it is possible to determine the SI without the need for SI transmission. However, SI estimation adds to computational complexity and implementation challenges of practical SLM-OFDM receivers. To address these technical issues, this paper presents the use of a pilot-assisted cluster-based phase modulation and demodulation procedure called embedded coded modulation (ECM). The ECM technique uses a slightly modified SLM approach to reduce PAPR and to enable data recovery with no SI transmission and no SI estimation. In the presence of some non-linear amplifier distortion, it is shown that the ECM method achieves similar data decoding performance as conventional SLM-OFDM receiver that assumed a perfectly known SI and when the SI is estimated using a frequency-domain correlation approach. However, when the number of OFDM subcarriers is small and due to the clustering in ECM, the modified SLM produces a smaller PAPR reduction gain compared with conventional SLM

Photochemistry, mixing and diurnal cycles in the upper ocean

The interplay between ocean photochemistry and surface boundary-layer physics is explored in a range of analytical and numerical process models. For simple systems, key attributes of the photochemical distribution—diurnal cycle, surface concentration, and the bulk concentration difference across the “mixed layer”—can be expressed in terms of a small number of physical (vertical diffusivity) and photochemical (turnover timescale and production depth scale) scaling factors. A coupled, 1-D photochemical/physical model is used to examine the more general case with finite mixing rates, variable photochemical production and evolving boundary layer depth. Finite boundary layer mixing rates act to increase both the diurnal cycle and mean concentration at the surface. The diurnal cycle and mean surface concentration are further amplified by coupling between photochemistry and diurnal physics. The daily heating/cooling cycle of the upper ocean can lead to a significant reduction in mixing and boundary-layer depth during the day when photochemical production is at a maximum. Accounting for these effects results in additional surface trapping of photochemically produced species and significant enhancements of the surface diurnal cycle and daily mean. The implications of our model results for field data interpretation and global air-sea flux calculations are also discussed

CBS domains form energy-sensing modules whose binding of adenosine ligands is disrupted by disease mutations

CBS domains are defined as sequence motifs that occur in several different proteins in all kingdoms of life. Although thought to be regulatory, their exact functions have been unknown. However, their importance was underlined by findings that mutations in conserved residues within them cause a variety of human hereditary diseases, including (with the gene mutated in parentheses): Wolff-Parkinson-White syndrome (γ2 subunit of AMP-activated protein kinase); retinitis pigmentosa (IMP dehydrogenase-1); congenital myotonia, idiopathic generalized epilepsy, hypercalciuric nephrolithiasis, and classic Bartter syndrome (CLC chloride channel family members); and homocystinuria (cystathionine β-synthase). AMP-activated protein kinase is a sensor of cellular energy status that is activated by AMP and inhibited by ATP, but the location of the regulatory nucleotide-binding sites (which are prime targets for drugs to treat obesity and diabetes) was not characterized. We now show that tandem pairs of CBS domains from AMP-activated protein kinase, IMP dehydrogenase-2, the chloride channel CLC2, and cystathionine β-synthase bind AMP, ATP, or S-adenosyl methionine,while mutations that cause hereditary diseases impair this binding. This shows that tandem pairs of CBS domains act, in most cases, as sensors of cellular energy status and, as such, represent a newly identified class of binding domain for adenosine derivatives

Non-spherical sources of static gravitational fields: investigating the boundaries of the no-hair theorem

A new, globally regular model describing a static, non spherical gravitating object in General Relativity is presented. The model is composed by a vacuum Weyl--Levi-Civita special field - the so called gamma metric - generated by a regular static distribution of mass-energy. Standard requirements of physical reasonableness such as, energy, matching and regularity conditions are satisfied. The model is used as a toy in investigating various issues related to the directional behavior of naked singularities in static spacetimes and the blackhole (Schwarschild) limit.Comment: 10 pages, 2 figure

Quantification of the performance of iterative and non-iterative computational methods of locating partial discharges using RF measurement techniques

Partial discharge (PD) is an electrical discharge phenomenon that occurs when the insulation materialof high voltage equipment is subjected to high electric field stress. Its occurrence can be an indication ofincipient failure within power equipment such as power transformers, underground transmission cableor switchgear. Radio frequency measurement methods can be used to detect and locate discharge sourcesby measuring the propagated electromagnetic wave arising as a result of ionic charge acceleration. Anarray of at least four receiving antennas may be employed to detect any radiated discharge signals, thenthe three dimensional position of the discharge source can be calculated using different algorithms. These algorithms fall into two categories; iterative or non-iterative. This paper evaluates, through simulation, the location performance of an iterative method (the standardleast squares method) and a non-iterative method (the Bancroft algorithm). Simulations were carried outusing (i) a "Y" shaped antenna array and (ii) a square shaped antenna array, each consisting of a four-antennas. The results show that PD location accuracy is influenced by the algorithm's error bound, thenumber of iterations and the initial values for the iterative algorithms, as well as the antenna arrangement for both the non-iterative and iterative algorithms. Furthermore, this research proposes a novel approachfor selecting adequate error bounds and number of iterations using results of the non-iterative method, thus solving some of the iterative method dependencies

Transition Metal-free Methylation of Amines with Formaldehyde as the Reductant and Methyl Source

A simple transition metal-free procedure using formal dehyde for the N,N-dimethylation and N-methylation of primary and secondary anilines is reported. The reaction showed limitations on sterically hindered and electron-withdrawing anilines, but is successful on amines with electron-donating substituents. Formaldehyde acts as both the reducing agent and the carbon source in the reaction

An investigative study into the sensitivity of different partial discharge φ-q-n pattern resolution sizes on statistical neural network pattern classification

This paper investigates the sensitivity of statistical fingerprints to different phase resolution (PR) and amplitude bins (AB) sizes of partial discharge (PD) φ-q-n (phase-amplitude-number) patterns. In particular, this paper compares the capability of the ensemble neural network (ENN) and the single neural network (SNN) in recognizing and distinguishing different resolution sizes of φ-q-n discharge patterns. The training fingerprints for both the SNN and ENN comprise statistical fingerprints from different φ-q-n measurements. The result shows that there exists statistical distinction for different PR and AB sizes on some of the statistical fingerprints. Additionally, the ENN and SNN outputs change depending on training and testing with different PR and AB sizes. Furthermore, the ENN appears to be more sensitive in recognizing and discriminating the resolution changes when compared with the SNN. Finally, the results are assessed for practical implementation in the power industry and benefits to practitioners in the field are highlighted