Table of Contents
ISRN Signal Processing
Volume 2012 (2012), Article ID 584941, 7 pages
http://dx.doi.org/10.5402/2012/584941
Research Article

An Efficient Adaptive Technique with Low Complexity for Reducing PAPR in OFDM-Based Cognitive Radio

1Faculty of Electronic Engineering, El-Menoufia University, Menouf, Egypt
2Faculty of Engineering, Cairo University, Giza, Egypt

Received 6 March 2012; Accepted 17 May 2012

Academic Editors: G. Camps-Valls and H. Hu

Copyright © 2012 Hefdhallah Sakran et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Cognitive radio (CR) is considered nowadays as a strong candidate solution for the spectrum scarcity problem. On standards level, many cognitive radio standards have chosen Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) as their modulation scheme. Similar to OFDM, NC-OFDM suffers from the problem of having a high Peak to Average Power Ratio (PAPR). If not solved, either the transmitted signal will be distorted, which will cause interference to primary (licensed) users, or the effeciency of the power amplifier will be seriously degraded. The effect of the PAPR problem in NC-OFDM based cognitive radio networks is worse than normal OFDM systems. In this paper, we propose enhanced techniques to reduce the PAPR in NC-OFDM systems. We start by showing that combining two standard PAPR reduction techniques (interleaver-based and selective mapping) results in a lower PAPR than using them individually. Then, an “adaptive number of interleavers” will be proposed that achieves the same performance of conventional interleaver-based PAPR reduction while reducing the CPU time by 41.3%. Finally, adaptive joint interleaver with selective mapping is presented, and we show that it gives the same performance as conventional interleaver-based technique, with reduction in CPU time by a factor of 50.1%.