Simple Weighted Diversity Combining Technique for Cyclostationarity Detection Based Spectrum Sensing in Cognitive Radio Networks

Daiki CHO  Shusuke NARIEDA  

Publication
IEICE TRANSACTIONS on Communications   Vol.E99-B   No.10   pp.2212-2220
Publication Date: 2016/10/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2015EBP3524
Type of Manuscript: PAPER
Category: Wireless Communication Technologies
Keyword: 
cognitive radio network,  cyclostationarity detection based spectrum sensing,  space diversity,  orthogonal frequency division multiplexing signal,  

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Summary: 
This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.