Low-complexity PAPR-aware precoding for large-scale MIMO-OFDM downlink systems

• Main Authors: Liu, Sheng, Wang, Yajun
• Format: Conference Proceeding
• Language: English
• Published: SPIE 07.08.2024
• ISBN: 9781510681866; 1510681868
• ISSN: 0277-786X
• DOI: 10.1117/12.3038193

The abundant degrees of freedom provided by a large number of antennas at the base station are harnessed in MU-MIMO-OFDM downlink systems. We formulate the OFDM modulation, MU precoding, and peak-to-average power ratio (PAPR) constraints into a non-convex optimization problem for transmit power minimization. This problem is subject to predefined thresholds for PAPR of each antenna and multi- user interference (MUI). Instead of using existing relaxation- based convex optimization methods, we directly address this non-convex PAPR-aware precoding problem using the linearized alternating direction method of multipliers (LADMM). Simulation experiments confirm that the proposed LADMM method significantly reduces PAPR and minimizes symbol error rate (SER). Importantly, compared to existing methods, our LADMM method exhibits faster convergence speed and lower complexity