PAPR Reduction of Software Radio Signals Using PRC Method

Hussain, S. and Louet, Y. (2009) PAPR Reduction of Software Radio Signals Using PRC Method. In: IEEE Sarnoff 2009, Princeton, NJ, USA, 30 Mar - 1 Apr 2009, pp. 1-6. ISBN 9781424433810 (doi: 10.1109/SARNOF.2009.4850331)

Abstract

Software radio (SWR) system being a combination of different standards, where each standard consisting of multi-carrier signals makes SWR signal extremely power fluctuating which results in high peak to average power ratio (PAPR). OFDM and SWR signals due to their multi-carrier nature inherit the same PAPR distribution characteristics and this fact makes it possible to employ already developed OFDM PAPR reduction techniques to SWR signals. Several techniques have been devised to reduce the PAPR of the OFDM signal. One of these PAPR reduction techniques is based on peak reducing carriers (PRC) concept where a set of subcarriers is employed to reduce the temporal signal's peak. This paper employs PRC method for SWR signal PAPR reduction. A SWR base station would transmit a multiplex of standards signal where each standard having its own transmitting power requirements different from the other standards present in the SWR signal. An initial study is done for a bi-standard SWR system to see the variations in PAPR reduction gain with the variations in transmit power gap between the standards. Then PRC method is employed to reduce PAPR of a bi-standard SWR system containing standards with transmit power gap of 25 dB. PAPR is not only reduced by using in-band unused carriers of the standards as peak reducing carriers but also some inter-standard out-of-band (OOB) carriers are also used to reduce PAPR. The PAPR reduction performance by inband and OOB peak reducing carriers is compared. Also the effect of variation in mean power of OOB peak reducing carriers on PAPR reduction performance is discussed.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hussain, Dr Sajjad
• Authors: Hussain, S., and Louet, Y.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• ISBN: 9781424433810

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