S3: low cost real-time spectrum sensing using SDR

Abstract

It is always an urgent problem to detect unauthorized access to spectrum by malicious devices in real time, such that the access of legal devices can be guaranteed. Dedicate spectrum sensing devices are extremely expensive and bulky, which can not be applied in normal scenario. We present S3, a real-time spectrum sensing and analyzing method, in which a smartphone is adopted as the upper computer to send instructions to a master control module of Raspberry Pi, and the master control module drives a Software Defined Radio (SDR) based spectrum sensing module. The real-time sensing results are displayed on the smartphone, and stored into a local database at the same time for further analyzing. We evaluate the accuracy and effectiveness of our S3 by comparing with a dedicated spectrum analyzer. Evaluation results demonstrate that S3 can achieve high accuracy realtime sensing. In average, the relative difference between S3 and its comparison is 1.045%. Furthermore, we implement four real-time spectrum analysis functions, including signal strength, channel occupancy, frequency band occupancy and waterfall plot.