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A. Ghassemi and T. A. Gulliver, “Low Autocorrelation Fractional PTS Subblocking for PAPR Reduction in OFDM Systems,” Proceedings of 6th Annual Conference on Communication Networks and Services Research, Nova Scotia, May 2008, pp. 41-45.

has been cited by the following article:

  • TITLE: A New Effective and Efficient Measure of PAPR in OFDM

    AUTHORS: Ibrahim M. Hussain, Imran A. Tasadduq, Abdul Rahim Ahmad

    KEYWORDS: Aperiodic Autocorrelation Co-Efficient, OFDM, PAPR, Power Variance, Partial Power Variance

    JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.3 No.9, September 30, 2010

    ABSTRACT: In multi-carrier wireless OFDM communication systems, a major issue is related to high peaks in transmitted signals, resulting in such problems as power inefficiency. In this regard, a common practice is to transmit the signal that has the lowest Peak to Average Power Ratio (PAPR). Consequently, some efficient and accurate method of estimating the PAPR of a signal is required. Previous literature in this area suggests a strong relationship between PAPR and Power Variance (PV). As such, PV has been advocated as a good measure of PAPR. However, contrary to what is suggested in the literature, our research shows that often low values of PV do not correspond to low values of PAPR. Hence, PV does not provide a sound scientific basis for comparing and estimating PAPR in OFDM signals. In this paper a novel, effective, and efficient measure of high peaks in OFDM signals is proposed, which is less complex than PAPR. The proposed measure, termed as Partial Power Variance (PPV), exploits the relationship among PAPR, Aperiodic Autocorrelation Co-efficient (AAC), and Power Variance (PV) of the transmitted signal. Our results demonstrate that, in comparison to PV, Partial Power Variance is a more efficient as well as a more effective measure of PAPR. In addition, we demonstrate that the computational complexity of PPV is far less than that of PAPR.