نتایج جستجو برای: path loss prediction
تعداد نتایج: 819848 فیلتر نتایج به سال:
Wireless sensor networking technology has great potential to advance monitoring of animal environments. Recent applications are very limited due to a lack of understanding of the performance of wireless sensors in large-scale, concentrated, and confined animal feeding operations. Wireless sensor performance in poultry layer facilities was evaluated through empirical testing of path loss, which ...
A heuristic algorithm is developed for the prediction of indoor coverage. Measurements on one floor of an office building are performed to investigate propagation characteristics and validations with very limited additional tuning are performed on another floor of the same building and in three other buildings. The prediction method relies on the free-space loss model for every environment, thi...
This paper reviews most commonly used ray tracing techniques and applies a ray tracing technique which incorporates site specific environmental data to predict path loss in newly constructed hostels in Universiti Teknologi Malaysia (UTM) for 5.8 GHz Industrial, Scientific and Medical (ISM) band in Malaysia. Radio propagation path loss has been measured in order to verify the predicted results. ...
Malignant tumors that contain a high proportion of regions deprived of adequate oxygen supply (hypoxia) in areas supplied by a microvessel (i.e., a microcirculatory supply unit MCSU) have been shown to present resistance to common cancer treatments. Given the importance of the estimation of this proportion for improving the clinical prognosis of such treatments, a manual annotation has been pro...
Due to mobility of the node, the packet loss occurs often while the nodes are moving out of range, or the node has not enough either path and link stability or neighbour node stability. In this paper we propose modified stability scheme to make a correct balance between stability of path, link, neighbour node and total mobile nodes to extend the network lifetime. The main of the proposed work i...
Model-Aided Deep Learning Method for Path Loss Prediction in Mobile Communication Systems at 2.6 GHz
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