NDLI: Feature detection based computationally efficient spectrum sensing by test statistics sharing among multiple receive antennas

Content Provider	IEEE Xplore Digital Library
Author	Daiki Cho Narieda, S.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Nat. Inst. of Technol., Akashi, Japan (Narieda, S.) \|\| Adv. Course of Mech. & Electron. Syst. Eng, Nat. Inst. of Technol., Akashi, Japan (Daiki Cho)
Abstract	This paper presents a feature detection based spectrum sensing technique by some test statistics sharing among multiple receive antennas. In conventional feature (signal cyclostationarity) detection based spectrum sensing techniques with multiple antenna systems, computational complexity is not low, and it increases in proportion to the number of receive antennas. In this paper, test statistics are shared among multiple receive antennas for improving computational efficiency. The results are compared with results obtained using some conventional techniques and they show that 1) the presented technique can obtain favorable results even though the presented technique has a low computational complexity in comparison with the conventional techniques; 2) the performances and computational complexity of the presented technique are better and lower than that of conventional techniques in proportion to the number of receive antennas; 3) when noise variances at each of the RF chains are different, degradation of performance can be suppressed by adjusting computational complexity.
File Size	272773
Starting Page	360
Ending Page	264
File Format	PDF
e-ISBN	9781467367820
DOI	10.1109/PIMRC.2015.7343324
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	OFDM Computational complexity Sensors Receiving antennas Feature extraction Cognitive radio Cognitive radio network spectrum sensing signal cyclostationarity
Content Type	Text
Resource Type	Article

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