ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 A Blind OFDM Signal Detection Method Based on Cyclostationarity Analysis
Cited 2 time in scopus Download 2 time Share share facebook twitter linkedin kakaostory
저자
Xiang Sun, 김진영, 민소희, Asmatullah Chaudhry, 최승호, 김창주
발행일
201706
출처
Wireless Personal Communications, v.94 no.3, pp.393-413
ISSN
0929-6212
출판사
Springer
DOI
https://dx.doi.org/10.1007/s11277-015-3060-4
초록
In this paper, we present a novel technique to sense, blindly infer signal features [FFT size, cyclic prefix (CP) length], and detect OFDM signals based on second order cyclostationarity analysis. First, we infer accurate FFT size and CP length from the sensed signal based on cross correlation, through considering FFTs of different size (2L) and CPs length. In our experimental study, we assume that CP length in the sensed OFDM signal could be 5??15혻% of the FFT size {64, 128, 256, 512, 1024, 2048 and 4096} used at primary user level. We successfully estimate accurate FFT size and CP length, and carry out performance analysis of the proposed approach at various channel conditions, and the effect of increase in sample length (frames) of the sensed signal. Additionally, we derive a recursive procedure to calculate the cross-correlation at sample (l혻+혻1), using the cross-correlation value at sample (l) and a few mathematical operations. We have also tested MAX values distribution for FFT size and CP, whether inferred parameters are valid or not, by finding the confidence of estimation. With experimental results we evaluated that the proposed approach can successfully measure unknown OFDM signal parameters and detect OFDM signals.
키워드
Cognitive radio, Cyclostationarity analysis, OFDM signal detection
KSP 제안 키워드
Carry out, Cross-Correlation, Cyclic prefix(CP), Detection Method, Different sizes, Experimental study, Novel technique, OFDM signal, Performance analysis, Recursive procedure, Sample length