Comparative Analysis of Information Fusion
Techniques for Cooperative Spectrum Sensing in
Cognitive Radio Networks
(2014)Abstract
In Cognitive Radio Networks
(CRN), Cooperative Spectrum Sensing (CSS) is
used to improve performance of spectrum sensing techniques used for detection of licensed
(Primary) user
’s signal
. In CSS, the spectrum sensing information from multiple unlicensed
(Secondary) users are
combined
to take final decision about presence of primary signal. The
mixing techniques used to generate final decision about presence of PU’s signal are also
called as Fusion
techniques /
rules. The fusion techniques are further classified as data
fusion and
decision fusion techniques. In data fusion technique all the secondary users
(SUs) share their raw information of spectrum detection like detected energy or other
statistical information, while in decision fusion technique all the SUs take their local
d
ecisions and share the decision by sending ‘0’ or ‘1’ corresponding to absence and presence
of PU’s signal respectively. The rules used in decision fusion techniques are OR rule, AND
rule and K
-
out
-
of
-
N rule. The CSS is further classified as distributed CS
S and centralized
CSS. In distributed CSS all the SUs share the spectrum detection information with each
other and by mixing the shared information
;
all the SUs take final decision individually. In
centralized CSS all the SUs send their detected informatio
n to a
secondary base station /
central unit which combines the shared information and takes final decision
.
The
secondary
base station shares the final decision with all the SUs
in the CRN
. This paper covers
overview of
information fusion methods
used for
CSS and analysis of decision fusion rules
with simulation results.