A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Turbo Equalization of Non-Linear Satellite Channels using Soft Interference Cancellation

Satellite communication channels can be well described as non-linear functions with memory. The Volterra series representation provides accurate modeling of satellite channel dynamics, and thus, it constitutes a widely used approach to mathematically describe them. In this work, iterative correction of the non-linear distortion introduced by such channels is considered, by employing a soft interference canceller operating in a turbo equalization framework

Power-efficient wireless sensor reachback for SHM

Wireless sensor networks have recently received great attention from the scientic community, because they hold the key to revolutionize many aspects of our economy and life. On the other hand, the design, implementation and operation of a wireless sensor network in an SHM system requires the synergy of many disciplines, including civil engineering, signal processing, networking, etc. The process of collecting the measurements acquired by a sensor network into a central sink node, constitutes one of the main challenges in this area of research and is often referred to as the sensor reachback problem. In this work, we describe a time-division multiple-access based protocol for sensor reachback, that takes into account the fact that sensor measurements are correlated in time and space, in order to reduce the amount of information that needs to be transmitted to the sink node. Furthermore, cooperative communication is incorporated into the developed protocol, so as to achieve reduced energy consumption. Experiments with real acceleration measurements, obtained from the Canton Tower in China during an earthquake, have demonstrated the effectiveness of the proposed method

Computer-aided detection of prostate cancer in T2-weighted MRI within the peripheral zone

In this paper we propose a prostate cancer computer-aided diagnosis (CAD) system and suggest a set of discriminant texture descriptors extracted from T2-weighted MRI data which can be used as a good basis for a multimodality system. For this purpose, 215 texture descriptors were extracted and eleven different classifiers were employed to achieve the best possible results. The proposed method was tested based on 418 T2-weighted MR images taken from 45 patients and evaluated using 9-fold cross validation with five patients in each fold. The results demonstrated comparable results to existing CAD systems using multimodality MRI. We achieved an area under the receiver operating curve (A z ) values equal to $90.0\%\pm 7.6\%$ , $89.5\%\pm 8.9\%$ , $87.9\%\pm 9.3\%$ and $87.4\%\pm 9.2\%$ for Bayesian networks, ADTree, random forest and multilayer perceptron classifiers, respectively, while a meta-voting classifier using average probability as a combination rule achieved $92.7\%\pm 7.4\%$