Implementation of a Wideband Spectrum Sensing Algorithm Using a Software-Defined Radio (SDR)

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Issue Date
2016
Authors
Robertson, Max
Bkassiny, Mario. Dr.
Publisher
Keywords
Radio frequency , Signal detection , Cognitive radio networks
Abstract
Implementation of a Wideband Spectrum Sensing Algorithm using a Software Defined Radio (SDR). Max Robertson, Prof. Mario Bkassiny This project consisted of implementing an autonomous algorithm that would be able to sense the electromagnetic radio frequency (RF) spectrum using a Universal Software Radio Peripheral (USRP) and to detect the center frequencies and bandwidths of the local active signals in the SUNY Oswego area. This information, once captured, is used to evaluate and analyze the spectrum activity in the surrounding RF environment. By comparing the actual spectral activity to the spectrum allocations of the Federal Communications Commission (FCC), we could give accurate conclusions on to the efficiency and utilization of the spectral resources. The proposed signal detection algorithm is based on a smoothed spectral estimation method. By applying hypothesis testing to the received signal, we could identify the center frequencies and bandwidths of the active signals, subject to a certain false alarm rate. Some signals that were detected include cell phone LTE, aeronautical radio-navigation, and Earth-Space communication signals. The project incorporates signal processing using MATLAB to create functions and scripts that can be used at different locations for reproduction of the project simulations. This project demonstrates the feasibility of wideband spectrum sensing for Cognitive Radio (CR) applications. It also showed the potential of using software-defined radio (SDR) platforms for various signal processing applications, including wideband signal detection.
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