NDLI: Analysis of DCO-OFDM and flip-OFDM for IM/DD optical-wireless system

Content Provider	IEEE Xplore Digital Library
Author	Islam, Rashed Choudhury, Pallab Islam, Muhammad Ashiqul
Copyright Year	2014
Description	Author affiliation: Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology (KUET), 9203, Bangladesh (Islam, Rashed; Choudhury, Pallab; Islam, Muhammad Ashiqul)
Abstract	The paper analyzes the performance of two forms of orthogonal frequency division multiplexing (OFDM) techniques called as DC biased Optical OFDM (DCO-OFDM) and Flip- OFDM for intensity modulated direct detection (IM/DD) system. The aforementioned OFDM schemes are compared in terms of peak-to-average power ratio (PAPR) and bit error rate (BER) as a function of electrical energy per bit to noise power ratio (E) when the signal is affected by additive white Gaussian noise (AWGN). In particular, 7-dB and 13-dB DC bias are used for DCO-OFDM in BER analysis and finally compared with flip-OFDM for the different data formats such as 4-,16-,64-,256- QAMs. The results show that flip-OFDM performs better in BER analysis with reduced value of (E) and thus, it can be considered as a power efficient unipolar modulation format. However, Flip-OFDM signal provides a high PAPR value that can deteriorate the overall system performance. Finally, OFDM signal performance tradeoff is measured as a function of transmitted optical power, QAM size, and spectral efficiency.
Starting Page	32
Ending Page	35
File Size	1614014
Page Count	4
File Format	PDF
e-ISBN	9781479941667
DOI	10.1109/ICECE.2014.7026929
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-20
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bit error rate Peak to average power ratio Optical transmitters Adaptive optics Optical fibers Direct Detection DCO-OFDM Flip-OFDM PAPR BER Intensity Modulation
Content Type	Text
Resource Type	Article

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