Transmit Antenna Selection for Interference Management in Cognitive Relay Networks

We propose transmit antenna selection (TAS) in decode-and-forward (DF) relaying as an effective approach to reduce the interference in underlay spectrum sharing networks with multiple primary users (PUs) and multiple antennas at the secondary users (SUs). We compare two distinct protocols: 1) TAS with receiver maximal-ratio combining (TAS/MRC) and 2) TAS with receiver selection combining (TAS/SC). For each protocol, we derive new closed-form expressions for the exact and asymptotic outage probability with independent Nakagami-m fading in the primary and secondary networks. Our results are valid for two scenarios related to the maximum SU transmit power, i.e., P, and the peak PU interference temperature, i.e., Q. When P is proportional to Q, our results confirm that TAS/MRC and TAS/SC relaying achieve the same full diversity gain. As such, the signal-to-noise ratio (SNR) advantage of TAS/MRC relaying relative to TAS/SC relaying is characterized as a simple ratio of their respective SNR gains. When P is independent of Q, we find that an outage floor is obtained in the large P regime where the SU transmit power is constrained by a fixed value of Q. This outage floor is accurately characterized by our exact and asymptotic results.

Secured Cooperative Cognitive Radio Networks with Relay Selection

In this paper, we propose physical layer security for cooperative cognitive radio networks (CCRNs) with relay selection in the presence of multiple primary users and multiple eavesdroppers. To be specific, we propose three relay selection schemes, namely, opportunistic relay selection (ORS), suboptimal relay selection (SoRS), and partial relay selection (PRS) for secured CCRNs, which are based on the availability of channel state information (CSI) at the receivers. For each approach, we derive exact and asymptotic expressions for the secrecy outage probability. Results show that under the assumption of perfect CSI, ORS outperforms both SoRS and PRS.

The List_Tree - an innovative solution to customer portfolio representation

The scale of BT's operations necessitates the use of very large scale computing systems, and the storage and management of large volumes of data. Customer product portfolios are an important form of data which can be difficult to store in a space efficient way. The difficulties arise from the inherently structured form of product portfolios, and the fact that they change over time as customers add or remove products. This paper introduces a new data-modelling abstraction called the List_Tree. It has been designed specifically to support the efficient storage and manipulation of customer product portfolios, but may also prove useful in other applications with similar general requirements.

Interference Investigation for Cognitive Spectrum Sharing Networks with Reactive DF Relay Selection

Cognitive radio (CR) with spectrum-sharing has been envisioned as emerging technology for the next generation of mobile and wireless networks by allowing the unlicensed customers simultaneously utilize the licensed radio frequency spectrums. However, the CR has faced some practical challenges due to its deduced system performance as compared to non spectrum-sharing counterpart. In this paper, we therefore consider the potential of incorporating the cooperative communications into CR by introducing the concept of reactive multiple decode-and-forward (DF) relays. In particular, we derive new results for exact and asymptotic expressions for the performance of cognitive relay networks with K-th best relay selection. Our novel results have exhibited the significance of using relay networks to enhance the system performance of CR.

Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio

Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

Covariance Averaging for Improved Estimation and Portfolio Allocation

We propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the idea of (model) covariance averaging o ered in the covariance shrinkage approach by means of greater ease of use, exibility and robustness in averaging information over different data segments. The suggested approach does not su er from the curse of dimensionality and can be used without problems of either approximation or any demand for numerical optimization.

Bandwidth selection by cross-validation for forecasting long memory financial time series

The paper addresses the issue of choice of bandwidth in the application of semiparametric estimation of the long memory parameter in a univariate time series process. The focus is on the properties of forecasts from the long memory model. A variety of cross-validation methods based on out of sample forecasting properties are proposed. These procedures are used for the choice of bandwidth and subsequent model selection. Simulation evidence is presented that demonstrates the advantage of the proposed new methodology.

The role of personality and self-efficacy in the selection and retention of successful nursing students:a longitudinal study

Aim: This paper is a report of a study to examine the role of personality and self-efficacy in predicting academic performance and attrition in nursing students.

Background: Despite a considerable amount of research investigating attrition in nursing students and new nurses, concerns remain. This particular issue highlights the need for a more effective selection process whereby those selected are more likely to complete their preregistration programme successfully, and remain employed as Registered Nurses.

Method: A longitudinal design was adopted. A questionnaire, which included measures of personality and occupational and academic self-efficacy, was administered to 384 students early in the first year of the study. At the end of the programme, final marks and attrition rates were obtained from university records for a total of 350 students. The data were collected from 1999 to 2002.

Findings: Individuals who scored higher on a psychoticism scale were more likely to withdraw from the programme. Occupational self-efficacy was revealed to be a statistically significant predictor of final mark obtained, in that those with higher self-efficacy beliefs were more likely to achieve better final marks. Extraversion was also shown to negatively predict academic performance in that those with higher extraversion scores were more likely to achieve lower marks.

Conclusion: More research is needed to explore the attributes of successful nursing students and the potential contribution of psychological profiling to a more effective selection process.

Automotive waste heat recovery: Working fluid selection and related boundary conditions

This paper presents the rational for the selection of fluids for use in a model based study of sub and supercritical Waste Heat Recovery (WHR) Organic Rankine Cycle (ORC). The study focuses on multiple vehicle heat sources and the potential of WHR ORC’s for its conversion into useful work. The work presented on fluid selection is generally applicable to any waste heat recovery system, either stationary or mobile and, with careful consideration, is also applicable to single heat sources. The fluid selection process presented reduces the number of potential fluids from over one hundred to a group of under twenty fluids for further refinement in a model based WHR ORC performance study. The selection process uses engineering judgement, legislation and, where applicable, health and safety as fluid selection or de-selection criteria. This paper also investigates and discusses the properties of specific ORC fluids with regard to their impact on the theoretical potential for delivering efficient WHR ORC work output. The paper concludes by looking at potential temperature and pressure WHR ORC limits with regard to fluid properties thereby assisting with the generation of WHR ORC simulation boundary conditions.

Optimal wafer site selection using forward selection component analysis

Reducing wafer metrology continues to be a major target in semiconductor manufacturing efficiency initiatives due to it being a high cost, non-value added operation that impacts on cycle-time and throughput. However, metrology cannot be eliminated completely given the important role it plays in process monitoring and advanced process control. To achieve the required manufacturing precision, measurements are typically taken at multiple sites across a wafer. The selection of these sites is usually based on a priori knowledge of wafer failure patterns and spatial variability with additional sites added over time in response to process issues. As a result, it is often the case that in mature processes significant redundancy can exist in wafer measurement plans. This paper proposes a novel methodology based on Forward Selection Component Analysis (FSCA) for analyzing historical metrology data in order to determine the minimum set of wafer sites needed for process monitoring. The paper also introduces a virtual metrology (VM) based approach for reconstructing the complete wafer profile from the optimal sites identified by FSCA. The proposed methodology is tested and validated on a wafer manufacturing metrology dataset. © 2012 IEEE.