DocumentCode :
258062
Title :
Adaptive stochastic sensor scheduling for multi-channel radio environment mapping
Author :
Crawford, Joseph Ryan ; Paris, Bernd-Peter
Author_Institution :
Zeta Assoc., Fairfax, VA, USA
fYear :
2014
fDate :
3-5 Dec. 2014
Firstpage :
1204
Lastpage :
1208
Abstract :
This paper addresses the problem of scheduling a distributed set of RF sensors for the creation of a multichannel Radio Environment Map (REM). We propose a method for tracking the spatial distribution of the activity patterns on each channel via Kaiman filtering. The activity patterns on each channel are then used to inform schedule creation by balancing the achievable expected uncertainty across all channels by using the concepts of Permissible Consecutive Observation Loss (PCOL) and Least Consecutive Observation (LCO). For a stationary wireless sensor network, where each sensor can scan one channel at a time, we create an adaptive stochastic channel sensing order that balances the spatial uncertainty of the estimate of the REM for each of the channels of interest. Herein, the algorithm´s effectiveness is demonstrated through simulation. It will also be demonstrated on actual spectrum measurements under the DARPA RadioMap, for which this algorithm was developed.
Keywords :
Kalman filters; wireless sensor networks; DARPA RadioMap; Kaiman filtering; LCO; PCOL; REM; RF sensors; adaptive stochastic channel sensing order; adaptive stochastic sensor scheduling; least consecutive observation; multichannel radio environment mapping; permissible consecutive observation; stationary wireless sensor network; Channel estimation; Cognitive radio; Covariance matrices; Estimation error; Kalman filters; Schedules; Sensors; Kaiman filter; dynamic spectrum access; radio environment map; sensor scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
Conference_Location :
Atlanta, GA
Type :
conf
DOI :
10.1109/GlobalSIP.2014.7032313
Filename :
7032313
Link To Document :
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