NDLI: Spectrum sensing via event-triggered sampling

Content Provider	IEEE Xplore Digital Library
Author	Yilmaz, Y. Moustakides, G. Xiaodong Wang
Copyright Year	2011
Description	Author affiliation: Electrical Engineering Department, Columbia University, New York, 10027, USA (Yilmaz, Y.; Xiaodong Wang) \|\| Dept. of Electrical & Computer Engineering, University of Patras, 26500 Rion, Greece (Moustakides, G.)
Abstract	We propose a new framework for cooperative spectrum sensing in cognitive radio networks, that is based on a novel class of non-uniform samplers called the event-triggered samplers, and sequential detection. In the proposed scheme, each secondary user computes its local sensing decision statistic based on its own channel output; and whenever such decision statistic crosses certain predefined threshold values, the secondary user sends one bit (or several bits) information to the fusion center. The fusion center asynchronously receives the bits from different secondary users, based on which it updates the global sensing decision statistic and performs the sequential probability ratio test (SPRT), until reaching a sensing decision. We provide an asymptotic analysis for the above scheme, and under different conditions, we compare it against the cooperative sensing scheme that is based on traditional uniform sampling and sequential detection. Through simulations we show show that the proposed scheme, using even 1 bit, can outperform its uniform sampling counterpart that uses infinite number of bits.
Starting Page	1420
Ending Page	1424
File Size	648196
Page Count	5
File Format	PDF
ISBN	9781467303217
ISSN	10586393
e-ISBN	9781467303231
DOI	10.1109/ACSSC.2011.6190251
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors event-triggered sampling decentralized detection sequential sensing asymptotic optimality
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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