Can frequency diversity provide performance gains for WSNs at 2.4GHz for the fire hydrant to above ground channel

Wireless Sensor Networks (WSNs) which utilise IEEE 802.15.4 technology offer the potential for low cost deployment and maintenance compared with conventional wired sensor networks, enabling effective and efficient condition monitoring of aged civil engineering infrastructure. We will address wireless propagation for a below to above ground scenario where one of the wireless nodes is located in a below ground fire hydrant chamber to permit monitoring of the local water distribution network. Frequency Diversity (FD) is one method that can be used to combat the damaging effects of multipath fading and so improve the reliability of radio links. However, no quantitative investigation concerning the potential performance gains from the use of FD at 2.4GHz is available for the outlined scenario. In this paper, we try to answer this question by performing accurate propagation measurements using modified and calibrated off-the-shelf 802.15.4 based sensor nodes. These measurement results are also compared with those obtained from simulations that employ our Modified 2D Finite-Difference Time-Domain (FDTD) approach. ©2009 IEEE.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

High performance nanocomposite thin film transistors with bilayer carbon nanotube-polythiophene active channel by ink-jet printing

Nanocomposite thin film transistors (TFTs) based on nonpercolating networks of single-walled carbon nanotubes (CNTs) and polythiophene semiconductor [poly [5, 5′ -bis(3-dodecyl-2-thienyl)- 2, 2′ -bithiophene] (PQT-12)] thin film hosts are demonstrated by ink-jet printing. A systematic study on the effect of CNT loading on the transistor performance and channel morphology is conducted. With an appropriate loading of CNTs into the active channel, ink-jet printed composite transistors show an effective hole mobility of 0.23 cm 2 V-1 s-1, which is an enhancement of more than a factor of 7 over ink-jet printed pristine PQT-12 TFTs. In addition, these devices display reasonable on/off current ratio of 105-10 6, low off currents of the order of 10 pA, and a sharp subthreshold slope (<0.8 V dec-1). The work presented here furthers our understanding of the interaction between polythiophene polymers and nonpercolating CNTs, where the CNT density in the bilayer structure substantially influences the morphology and transistor performance of polythiophene. Therefore, optimized loading of ink-jet printed CNTs is crucial to achieve device performance enhancement. High performance ink-jet printed nanocomposite TFTs can present a promising alternative to organic TFTs in printed electronic applications, including displays, sensors, radio-frequency identification (RFID) tags, and disposable electronics. © 2009 American Institute of Physics.

Nanometer scale thermal drift of 4Gbit/s uncooled laser for tight-channel-spacing low-cost WDM

A 4Gbit/s directly modulated DBR laser is demonstrated with nanometre scale thermal tuning over an extended 20-70°C temperature range. >40dB side mode suppression over the entire temperature range is achieved. © 2005 Optical Society of America.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.