PAPR-Aware Massive MIMO-OFDM Downlink

Abstract

We investigate the peak-to-average power ratio (PAPR) reduction problem in orthogonal frequency-division multiplexing-based massive multi-user (MU) multiple-input multiple-output (MIMO) downlink systems. In this paper, we develop a downlink transmission scheme that performs jointly MU precoding and PAPR reduction (PP) by exploiting the excess degrees of freedom offered by equipping the BS by a large number of antennas. Specifically, the joint MU precoding and PAPR reduction scheme is formulated as a simple convex optimization problem solved via steepest gradient descent (GD) approach. Then, we develop a novel algorithm, referred to as MU-PP-GDm, to reduce the PAPR of the transmitted signals by exploiting the high-dimensional null space of the MIMO channel matrix while maintaining an excellent transmission quality. The simulation results show that the proposed MU-PP-GDm has low computational complexity and can achieve substantial PAPR performance with a fast convergence rate.

Keywords

• 5G+
• massive multiple-input multiple-output (MIMO)
• orthogonal frequency-division multiplexing (OFDM)
• peak-to-average power ratio (PAPR)
• multi-user (MU) precoding
• convex optimization