102 resultados para Radio beacons


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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.

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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.

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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.

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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.

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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.

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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.

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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.