Clipping noise cancellation receiver for the downlink of massive MIMO OFDM system

TL;DR

This paper introduces a multi-antenna clipping noise cancellation algorithm for massive MIMO OFDM systems, effectively reducing nonlinear distortion caused by limited RF linearity in 5G wireless networks.

Contribution

It proposes a novel multi-antenna clipping noise cancellation algorithm and a simplified version, improving distortion mitigation in massive MIMO OFDM systems.

Findings

The MCNC algorithm effectively removes nonlinear distortion under severe nonlinearity.

The simplified algorithm performs nearly as well as the full MCNC in direct visibility channels.

Simulations demonstrate significant distortion reduction in realistic scenarios.

Abstract

Massive multiple-input multiple-output (mMIMO) technology is considered a key enabler for the 5G and future wireless networks. In most wireless communication systems, mMIMO is employed together with orthogonal frequency-division multiplexing (OFDM) which exhibits a high peak-to-average-power ratio (PAPR). While passing the OFDM signal through one of the common RF front-ends of limited linearity, significant distortion of the transmitted signal can be expected. In mMIMO systems, this problem is still relevant as in some channels the distortion component is beamformed in the same directions as the desired signal. In this work, we propose a multi-antenna clipping noise cancellation (MCNC) algorithm for the downlink of the mMIMO OFDM system. Computer simulations show it can remove nonlinear distortion even under severe nonlinearity. Next, a simplified version of the algorithm is proposed. It was observed that for the direct visibility channels, its performance is only slightly degraded with respect to the MCNC algorithm.