مدل شبیه سازی حمله و کانال آمار در شبکه های سنسور آکوستیک زیر آب
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|9692||2011||11 صفحه PDF||سفارش دهید||6006 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Tsinghua Science & Technology, Volume 16, Issue 6, December 2011, Pages 611–621
In recent years, underwater acoustic wireless sensor networks have been used in many areas. There have been many field trials of acoustic propagation models and statistics for shallow water conditions. However, field trials are limited environmentally and, hence, not widely accepted. Simulations of the impulse response of a shallow underwater acoustic channel allows less expensive system tests that are reproducable. This paper presents a shallow water acoustic channel model based on the actual acoustic propagation characteristics with path attenuation, ambient noise, multiple paths, and Doppler effects. The second-order statistical characteristics of the simulation model are verified with the autocorrelations and crosscorrelations of the quadrature components and the complex envelopes of channel impulse responses. The channel model is implemented in Matlab with the results showing that the absorption coefficient and path losses are both dependent on the frequencies and propagation distances and that the path gain can be improved with Light of Sight (LOS) and short range acoustic propagation. Analysis of the channel impulse response and the frequency response that the zero-order Bessel function of first kind can be used to describe the correlation functions for the impulse response. The shallow underwater acoustic channel is time-varying and can not be modeled as a wide-sense stationary-uncorrelated scattering channel.
Underwater acoustic wireless sensor networks have grown exponentially in many scientific, industrial, and research areas. The network performance is strongly affected by the acoustic propagation characteristics of the underwater acoustic channel. However, underwater acoustic channels differ from radio channels in many aspects, with the underwater channel being a typical dispersive channel characterized by severe multipath effects, strong noise, and long delays. Underwater acoustic channels are recognized as one of the most difficult communication media to analyze1, 2 and 3. The symbol duration decreases with increasing data rate with severe frequency and time variations caused by dispersive fading of the channel. Such effects are more obvious in shallow water environments because the acoustic signals suffer more severe time and frequency selective fading than in radio channels. Therefore, high speed, large capacity, bandwidth-efficient digital communications are different in underwater conditions. Many methods have been developed for this purpose such as Orthogonal Frequency Division Multiplexing (OFDM). OFDM is a multicarrier modulation technique which has been widely applied in wireless communication systems and has received considerable attention for underwater acoustic communications over the past two decades4 and 5. The channel state information is necessary for coherent demodulation, inter-carrier interference equalization; carrier frequency offset estimates and others which are key techniques in OFDM systems. Hence, channel simulation models are needed and the channel statistical characteristics need to be analyzed to further improve the performance of high-data-rate underwater acoustic communication systems.
نتیجه گیری انگلیسی
This paper presents a model for a time-varying shallow water acoustic channel based on acoustic propagation characteristics. The second-order statistical properties of the impulse responses are analyzed. The path gain can be improved by increasing the incident angle or decreasing the propagation distance for a given frequency. Thus, the transmission performance can be improved with LOS and short range acoustic signals. The statistical correlation curve profiles closely match those of the Clark model, a zero-order Bessel function of the first kind; however, the magnitudes are smaller than for the Clarke model because transmission losses in underwater acoustic channels are more severe than in radio channels. The statistical correlation curves oscillation decay with increasing 2πfD2πfDfor a given τ′τ′. The number of paths has little effect on the correlation characteristics. The cross-correlation curves are not the same as for the Clarks model; therefore, the underwater acoustic channel is not a wide-sense stationary-uncorrelated scattering channel.