Pilotless Recovery of Clipped OFDM Signals by Compressive Sensing over Reliable Data Carriers

TL;DR

This paper introduces a novel clipping mitigation method for OFDM signals using compressive sensing over reliable data carriers, avoiding rate loss and improving recovery of nonlinear distortions.

Contribution

It presents a new approach that leverages reliable data carriers for compressive sensing, eliminating the need for tone reservation in OFDM clipping mitigation.

Findings

Achieves clipping mitigation without rate loss.

Successfully recovers sparse nonlinear distortions.

Enhances initial decoding accuracy in iterative methods.

Abstract

In this paper we propose a novel form of clipping mitigation in OFDM using compressive sensing that completely avoids tone reservation and hence rate loss for this purpose. The method builds on selecting the most reliable perturbations from the constellation lattice upon decoding at the receiver, and performs compressive sensing over these observations in order to completely recover the temporally sparse nonlinear distortion. As such, the method provides a unique practical solution to the problem of initial erroneous decoding decisions in iterative ML methods, offering both the ability to augment these techniques and to solely recover the distorted signal in one shot.