NDLI: A combined technique for carrier frequency offset estimation and peak-to-average power ratio reduction in OFDM systems using null subcarriers and Cuckoo search algorithm

Content Provider	Springer Nature Link
Author	Namitha, A. S. Sameer, S. M.
Copyright Year	2015
Abstract	This paper presents a novel generic method for the carrier frequency offset (CFO) estimation and reduction of peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing based wireless communication systems. Estimation of CFO using null subcarriers embedded in one or more pilot symbol is one of the best known CFO estimation techniques that achieve an estimation range of inverse of the sampling interval with low implementation complexity. We propose to exploit a few null subcarriers in the pilot symbol for PAPR reduction by switching with some data subcarriers in the data block of which the PAPR is intended to be minimized. We define a new cost function for the PAPR reduction at the transmitter and CFO estimation at the receiver and the computational complexity of its evaluation is made significantly low by applying Cuckoo search optimization algorithm. Also, the proposed method requires less side information to be send to the receiver as compared to many of the prevailing PAPR reduction methods. Computer simulation studies reveal that the proposed combined technique offers significant performance advantage for both PAPR reduction and CFO estimation concurrently.
Starting Page	275
Ending Page	285
Page Count	11
File Format	PDF
ISSN	10184864
Journal	Telecommunication Systems
Volume Number	63
Issue Number	2
e-ISSN	15729451
Language	English
Publisher	Springer US
Publisher Date	2015-11-24
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Orthogonal frequency division multiplexing (OFDM) Carrier frequency offset (CFO) Peak-to-average power ratio (PAPR) Complementary cumulative distribution function (CCDF) Cuckoo search (CS) Computational complexity reduction ratio (CCRR) IT in Business Computer Communication Networks Artificial Intelligence (incl. Robotics) Probability Theory and Stochastic Processes
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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