Behavior modelling and individual recognition of sonar transmitter for secure communication in UASNs

It is necessary to improve the safety of the underwater acoustic sensor networks (UASNs) since it is mostly used in the military industry. Specific emitter identification is the process of identifying different transmitters based on the radio frequency fingerprint extracted from the received signal. The sonar transmitter is a typical low-frequency radiation source and is an important part of the UASNs. Class D Power Amplifier, a typical non-linear amplifier, is usually used in sonar transmitters. The inherent nonlinearity of power amplifiers provides fingerprint features that can be distinguished without transmitters for specific emitter recognition. Firstly, the non-linearity of the sonar transmitter is studied in depth, and the nonlinearity of the power amplifier is modeled and its non-linearity characteristics are analyzed. After obtaining the nonlinear model of an amplifier, a similar amplifier in practical application is obtained by changing its model parameters as the research object. The output signals are collected by giving the same input of different models, and then the output signals are extracted and classified. In this paper, the memory polynomial model is used to model the amplifier. The power spectrum features of the output signals are extracted as fingerprint features. Then the dimensionality of the high-dimensional features is reduced. Finally, the classifier is used to recognize the amplifier. The experimental results show that the individual sonar transmitter can be well identified by using the non-linear characteristics of the signal. By this way, this method can enhance the communication safety of UASNs

The Luminosity - E_p Relation within Gamma--Ray Bursts and Implications for Fireball Models

Using a sample of 2408 time-resolved spectra for 91 BATSE gamma-ray bursts (GRBs) presented by Preece et al., we show that the relation between the isotropic-equivalent luminosity (L_iso) and the spectral peak energy (E_p) in the cosmological rest frame, L_iso \propto E_p^2, not only holds within these bursts, but also holds among these GRBs, assuming that the burst rate as a function of redshift is proportional to the star formation rate. The possible implications of this relation for the emission models of GRBs are discussed. We suggest that both the kinetic-energy-dominated internal shock model and the magnetic-dissipation-dominated external shock model can well interpret this relation. We constrain the parameters for these two models, and find that they are in a good agreement with the parameters from the fittings to the afterglow data (abridged).Comment: 3 pages plus 5 figures, emulateapj style, accepted for publication in ApJ Letter

Near-Optimal Distributed Approximation of Minimum-Weight Connected Dominating Set

This paper presents a near-optimal distributed approximation algorithm for the minimum-weight connected dominating set (MCDS) problem. The presented algorithm finds an $O(\log n)$ approximation in $\tilde{O}(D+\sqrt{n})$ rounds, where $D$ is the network diameter and $n$ is the number of nodes. MCDS is a classical NP-hard problem and the achieved approximation factor $O(\log n)$ is known to be optimal up to a constant factor, unless P=NP. Furthermore, the $\tilde{O}(D+\sqrt{n})$ round complexity is known to be optimal modulo logarithmic factors (for any approximation), following [Das Sarma et al.---STOC'11].Comment: An extended abstract version of this result appears in the proceedings of 41st International Colloquium on Automata, Languages, and Programming (ICALP 2014