Peak-to-average power ratio reduction in OFDM signals via self-adaptive EVM method

Abstract

Orthogonal frequency division multiplexing (OFDM) is an effective technique in wireless communication use. However, high peak-to-average power ratio (PAPR) is a big problem in OFDM signal. High PAPR can lead to significant distortion when signal passed through the nonlinear equipment, such as a transmitter power amplifier. Clipping is a simple and efficient way to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, clipping causes in-band distortion and out-of-band radiation. In this paper, a self-adaptive EVM (Error Vector Magnitude) method is proposed to reduce the PAPR of OFDM signals. Our self-adaptive EVM method consists of two independent parts, the first part to realize in-band noise processing, and the second part to satisfy the out-of-band spectral constraint. Achievable PAPR reduction results vary depending on different simulation requirements. Our results show that self-adaptive EVM method is a promising technique for crest factor reduction (CFR) when transmitting OFDM signals via linear amplifier. By using this method on a 64QAM Wimax signal with 2048 subcarriers, a 6.4dB PAPR reduction at the 10−4 complementary cumulative distribution function (CCDF) level can be obtained.