TITLE:
Throughput Estimation with Noise Uncertainty for Cyclostationary Feature Detector in Cognitive Radio Network
AUTHORS:
Mohsen M. Tantawy
KEYWORDS:
Cognitive Radio Network, Cyclostationary Feature Detector, Throughput, Noise Uncertainty
JOURNAL NAME:
Wireless Engineering and Technology,
Vol.6 No.2,
June
5,
2015
ABSTRACT: Cognitive Radio
Networks (CRNs) are recognized as the enabling technology for improving the future
bandwidth utilization. In CRNs secondary users are allowed to utilize the
frequency bands of primary users when these bands are not currently being used.
The secondary users are required to sense the radio frequency environment. The
lower the probability of false alarm, the more chances the channel can be
reused and the higher the achievable throughput for the secondary network. The main
contribution of this paper is to formulate the sensing-throughput-noise uncertainty
tradeoff for cyclostationary feature detection. Computer simulations have shown
that for a 1 MHz channel, when the sensing duration is 2% of total time, the
spectrum will get 99% probability of detection regardless of 50% noise
uncertainty.