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This work is concerned with the introduction and development of a technique to optimally position a Mobile Sensor (MS) in a location with adequate side lobe Radio Frequency (RF) signal power. The proposed method involves the generation of a database (DB) of side lobe power distribution for different azimuth angles of the downlink transmitted signal. The generated DB is subsequently used to train and test a Machine Learning (ML) multiclass classifier, as well as two distinct Convolution Neural Networks (CNN), to identify the desired MS location. Simulation experiments are performed which indicate a maximum accuracy of 99.25%, 96.56% and 96.10% for 8 different receiver locations.more » « less
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