A review of radio channel models for body centric communications

The human body is an extremely challenging environment for the operation of wireless communications systems, not least because of the complex antenna-body electromagnetic interaction effects which can occur. This is further compounded by the impact of movement and the propagation characteristics of the local environment which all have an effect upon body centric communications channels. As the successful design of body area networks (BANs) and other types of body centric system is inextricably linked to a thorough understanding of these factors, the aim of this paper is to conduct a survey of the current state of the art in relation to propagation and channel models primarily for BANs but also considering other types of body centric communications. We initially discuss some of the standardization efforts performed by the Institute of Electrical and Electronics Engineers 802.15.6 task group before focusing on the two most popular types of technologies currently being considered for BANs, namely narrowband and Ultrawideband (UWB) communications. For narrowband communications the applicability of a generic path loss model is contended, before presenting some of the scenario specific models which have proven successful. The impacts of human body shadowing and small-scale fading are also presented alongside some of the most recent research into the Doppler and time dependencies of BANs. For UWB BAN communications, we again consider the path loss as well as empirical tap delay line models developed from a number of extensive channel measurement campaigns conducted by research institutions around the world. Ongoing efforts within collaborative projects such as Committee on Science and Technology Action IC1004 are also described. Finally, recent years have also seen significant developments in other areas of body centric communications such as off-body and body-to-body communications. We highlight some of the newest relevant research in these areas as well as discussing some of the advanced topics which are currently being addressed in the field of body centric communications. Key Points Channel models for body centric comms ©2014. The Authors.

Promoting science literacy via science journalism: Issues and challenges

Science journalism is the source of much of the science an individual will encounter beyond formal education. Science-based media reports, which might have been associated with informal education, are increasingly becoming incorporated into formal school contexts. Unlike science textbooks, the science reported in the news is often tentative and sometimes contested. It can involve difficult socio-scientific issues. Descriptors of ‘science literacy’ generally include reading and responding critically to media reports of science. The challenge of using science-based news effectively encourages teachers to reassess their knowledge and pedagogical practices.
In addition to creating interest in science and making links beyond the classroom, news media can be used to introduce pupils to elements of science enquiry and teachers can promote basic literacy and critical reading skills through systematic and imaginative use of media reports with a science component.
This chapter explores the knowledge, skills and attitudes that underpin the use of science journalism in the classroom. The unique characteristics and constraints of science journalism that influence the way science is presented and perceived are considered, and the importance of media awareness as a foundation for critical reading of science news is argued. Finally the characteristics of teaching programmes to support critical engagement with science-based media reports are outlined and the opportunities for cross-curricular initiatives highlighted.

ZIL: An Energy-Efficient Indoor Localization System Using ZigBee Radio to Detect WiFi Fingerprints

In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.

On the Security of Cognitive Radio Networks

Cognitive radio has emerged as an essential recipe for future high-capacity high-coverage multi-tier hierarchical networks. Securing data transmission in these networks is of utmost importance. In this paper, we consider the cognitive wiretap channel and propose multiple antennas to secure the transmission at the physical layer, where the eavesdropper overhears the transmission from the secondary transmitter to the secondary receiver. The secondary receiver and the eavesdropper are equipped with multiple antennas, and passive eavesdropping is considered where the channel state information of the eavesdropper’s channel is not available at the secondary transmitter. We present new closedform expressions for the exact and asymptotic secrecy outage probability. Our results reveal the impact of the primary network on the secondary network in the presence of a multi-antenna wiretap channel.

Supernovae and radio transients in M82

We present optical and near-infrared (NIR) photometry and NIR spectroscopy of SN 2004am, the only optically detected supernova (SN) in M82. These demonstrate that SN 2004am was a highly reddened Type II-P SN similar to the low-luminosity Type II-P events such as SNe 1997D and 2005cs. We show that SN 2004am was located coincident with the obscured super star cluster M82-L, and from the cluster age infer a progenitor mass of 12{^{+ 7}_{- 3}} M⊙. In addition to this, we present a high spatial resolution Gemini-North Telescope K-band adaptive optics image of the site of SN 2008iz and a second transient of uncertain nature, both detected so far only at radio wavelengths. Using image subtraction techniques together with archival data from the Hubble Space Telescope, we are able to recover a NIR transient source coincident with both objects. We find the likely extinction towards SN 2008iz to be not more than AV ˜ 10. The nature of the second transient remains elusive and we regard an extremely bright microquasar in M82 as the most plausible scenario.

Electron dynamics and frequency coupling in a radio-frequency capacitively biased planar coil inductively coupled plasma system

The electron dynamics in a planar coil inductively coupled plasma (ICP) system with a capacitively biased electrode is investigated using space and phase resolved optical emission spectroscopy. The two power source frequencies are exact multiple of each other and phase-locked. In this configuration, the system is investigated when the coil is operated in both E-mode and H-mode. The results show that in a phase synchronized RF biased ICP, the electrode bias power couples with the capacitive contribution of the coil, in both E-mode and H-modes, similar to dual-frequency capacitively coupled plasmas (2f-CCPs). It is also demonstrated that in H-mode, the phase between the electrode bias frequency and the ICP coil frequency influences the electron heating, similar to the electrical asymmetry effect in 2f-CCPs.

EARLY RADIO AND X-RAY OBSERVATIONS OF THE YOUNGEST NEARBY TYPE Ia SUPERNOVA PTF 11kly (SN 2011fe)

On 2011 August 24 (UT) the Palomar Transient Factory (PTF) discovered PTF11kly (SN 2011fe), the youngest and most nearby Type Ia supernova (SN Ia) in decades. We followed this event up in the radio (centimeter and millimeter bands) and X-ray bands, starting about a day after the estimated explosion time. We present our analysis of the radio and X-ray observations, yielding the tightest constraints yet placed on the pre-explosion mass-loss rate from the progenitor system of this supernova. We find a robust limit of from sensitive X-ray non-detections, as well as a similar limit from radio data, which depends, however, on assumptions about microphysical parameters. We discuss our results in the context of single-degenerate models for SNe Ia and find that our observations modestly disfavor symbiotic progenitor models involving a red giant donor, but cannot constrain systems accreting from main-sequence or sub-giant stars, including the popular supersoft channel. In view of the proximity of PTF11kly and the sensitivity of our prompt observations, we would have to wait for a long time (a decade or longer) in order to more meaningfully probe the circumstellar matter of SNe Ia.

An empirical polarization domain channel availability model for cognitive radio

In dynamic spectrum access networks, cognitive radio terminals monitor their spectral environment in order to detect and opportunistically access unoccupied frequency channels. The overall performance of such networks depends on the spectrum occupancy or availability patterns. Accurate knowledge on the channel availability enables optimum performance of such networks in terms of spectrum and energy efficiency. This work proposes a novel probabilistic channel availability model that can describe the channel availability in different polarizations for mobile cognitive radio terminals that are likely to change their orientation during their operation. A Gaussian approximation is used to model the empirical occupancy data that was obtained through a measurement campaign in the cellular frequency bands within a realistic operational scenario.

An HMM-based spectrum occupancy predictor for energy efficient cognitive radio

Spectrum sensing is the cornerstone of cognitive radio technology and refers to the process of obtaining awareness of the radio spectrum usage in order to detect the presence of other users. Spectrum sensing algorithms consume considerable energy and time. Prediction methods for inferring the channel occupancy of future time instants have been proposed as a means of improving performance in terms of energy and time consumption. This paper studies the performance of a hidden Markov model (HMM) spectrum occupancy predictor as well as the improvement in sensing energy and time consumption based on real occupancy data obtained in the 2.4GHz ISM band. Experimental results show that the HMM-based occupancy predictor outperforms a kth order Markov and a 1-nearest neighbour (1NN) predictor. Our study also suggests that by employing such a predictive scheme in spectrum sensing, an improvement of up to 66% can be achieved in the required sensing energy and time.