Nonlinear symbols combining for Power Amplifier-distorted OFDM signal reception

TL;DR

This paper proposes a machine learning-based Higher-Order Combining (HOC) scheme for OFDM signals distorted by Power Amplifier nonlinearities, improving BER performance without decision aid but with high computational complexity.

Contribution

It introduces a non-decision-aided HOC reception method using machine learning to derive combining coefficients for nonlinear PA-distorted OFDM signals.

Findings

Improved BER performance over standard and decision-aided receivers

Machine learning effectively derives combining coefficients

High computational complexity limits wideband application

Abstract

Nonlinear distortion of a multicarrier signal by a transmitter Power Amplifier (PA) can be a serious problem when designing new highly energy-efficient wireless systems. Although the performance of standard reception algorithms is seriously deteriorated by the nonlinear distortion, the more advanced solutions allow the utilization of additional frequency diversity caused by nonlinear PA. However, while most of the advanced receivers are decision-aided, their gains are observed mostly in a relatively low Bit Error Rate (BER) region, not targeted by adaptive Modulation Coding Schemes utilizing Forward Error Correction (FEC). In this paper, a non-decision-aided Higher-Order Combining (HOC) reception scheme is proposed. While the analytical formulas for finding symbols combining coefficients are not known, machine learning is used for deriving them. The simulation results show an improved BER performance with respect to a standard reception and one of the established decision-aided receivers. However, as HOC has computational complexity that increases rapidly with the number of subcarriers utilized, more studies are needed to apply it in a wideband system.