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Long-term evolution (LTE)-CommSense is a novel instrumentation scheme, which analyzes channel-affected reference signals of LTE downlink signal to obtain knowledge about the environmental change. This paper presents the characterization of LTE-CommSense instrument to detect the presence or absence of objects in an outdoor environment. In addition, we analyze its capability of detecting and distinguishing when multiple objects are present. For performance evaluation and characterization of this instrument, we derive object detection accuracy, false acceptance rate (FAR), false rejection rate (FRR), and resolution which we believe are the most important figures of merit in this case. As the operation of LTE-CommSense is to detect events instead of objects, we redefine the concept of resolution for LTE-CommSense. Two different proposals to represent the redefined resolution, viz., Neyman-Pearson principle-based and Cramer-Rao principle-based resolutions, are presented here. All the performance metrics are derived using practical data captured using a software-defined radio (SDR) platform modeled as an LTE-CommSense receiver. We observe that LTE-CommSense provides better performance in detecting the presence or absence of objects at near range.

Performance Evaluation of LTE-CommSense System for Discriminating the Presence of Multiple Objects in Outdoor Environment