The Method of Conditional Expectations for PAPR and Cubic Metric Reduction

TL;DR

This paper introduces the Method of Conditional Expectations for reducing PAPR and Cubic Metric in OFDM signals, providing an efficient, suboptimal sign selection approach with consistent performance improvements across various subcarrier counts.

Contribution

It proposes a novel CE-based sign selection method for PAPR and CM reduction, offering a computationally efficient and effective alternative to existing techniques.

Findings

Reduces effective PAPR from 10.5/11.7 dB to about 6.5 dB

Achieves steady 3 dB reduction in Cubic Metric

Halves rate loss with pruned sign selection approach

Abstract

The OFDM waveform exhibits high fluctuation in the signal envelope which causes distortion in the nonlinear power amplifier of the transmitter. Peak-to-Average Power Ratio (PAPR) and Cubic Metric (CM) are the common metrics to quantify the phenomenon. A promising approach for PAPR or CM reduction is Sign Selection which is based on altering the signs of the data symbols. In this paper, the Method of Conditional Expectations (CE Method) is proposed to obtain a competing suboptimal solution to the Sign Selection problem. For PAPR reduction, a surrogate metric is introduced which allows for an efficient application of the CE Method. For CM reduction, the tractability of the definition of CM is exploited to this end. The algorithm is analyzed to obtain an upper bound on the worst-case reduced metric value. A noticeable characteristic is the persistent reduction capability for a wide range of subcarrier numbers. In particular, simulations show a reduction of the so-called "effective PAPR" to about 6.5 dB from 10.5 dB and 11.7 dB respectively for 64 to 1024 subcarriers. A similar steady reduction of 3 dB is observed for CM. In addition, the CE Method leads to a pruned version of Sign Selection which halves the rate loss.