Measuring Wireless Propagation in Sensor Networks

1. TX RX Center for Embedded Networked Sensing Measuring Wireless Propagation in Sensor Networks Valerie Bick, Katherine Kuan, Eric Seidler, Haleh Tabrizi Mentor: David Browne, UnWiReD Lab - http://www.unwired.ee.ucla.edu/ Introduction: Wireless Communication Network Sensors Near-Ground Peer-to-Peer Networks Long Term Goals for Radio Testbed System • Locations for optimal data sensing often suboptimal for wireless network communications • No data available on radio distortion in directional antennas operating in wilderness environments • Directional communication as a solution • More energy efficient in scenarios with sparsely connected nodes of fixed position and density, and a direct path of propagation • Focused energy beams ensure a propagation path with increased range • Develop a model for radio distortion as a function of distance and direction • Determine feasibility of directional communications Problem Description:Measure Peer-to-Peer Wireless Propagation in Forest Environments • Inefficient data collection for signal processing • Fixed settings on transmitter signal power, attenuation on TX and RX radios, and digitizer scaling are not optimized at each new antenna position , thus producing imprecise digital signal representation for analysis • Requirements for measurement testbed • Easily programmed via MATLAB • Robust, portable and self-contained • Autonomous operation • Measurement sensitivity adapts to propagation conditions • Remote access via Internet Receiver Transmitter Proposed Solution: Develop a System that uses Automatic Gain Control and Spectral Filtering Radio Testbed System Hardware Upgrades • Improve system setup time • Automated gain control using RX radio’s attenuators by parallel port interface • Automated tuning of RX radio synthesizers by parallel port interface • Robots and Control Node • Assemble analog on-board voltmeters for on-demand power monitoring • Standardize wiring and integrate analog to digital converter • Mount analog radio in environmentally robust case • Allow for battery-powered operation Graphical User Interface Automatic Gain Control Feedback Loop • User interaction with received/processed data • Control over start/stop, pause/resume, and displays of data acquired • Maximize dynamic range of system sensitivity • Utilize all 8 bits of resolution on digitizer to generate most accurate digital signal representation for analysis • Develop adaptive algorithm to maximize SNR • Algorithm adapts attenuation and gain settings in digitizer, tone generator, and wideband receiver Spectral Filtering • Generate a signal that mimics the 802.11 signal • Fourier transform filtering • Utilize the FFT function in MATLAB to recover the transmitted signal from noisy signal, thereby significantly increasing the signal-to-noise ratio Field Results GPS • Use to determine location of robots • Extract latitude, longitude, and number of satellites UCLA – UCR – Caltech – USC – CSU – JPL – UC Merced