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

Sheng Liu; Yajun Wang

doi:10.1117/12.3038193

7 August 2024 Low-complexity PAPR-aware precoding for large-scale MIMO-OFDM downlink systems

Sheng Liu, Yajun Wang

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 132291W (2024) https://doi.org/10.1117/12.3038193
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

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

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Sheng Liu and Yajun Wang "Low-complexity PAPR-aware precoding for large-scale MIMO-OFDM downlink systems", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 132291W (7 August 2024); https://doi.org/10.1117/12.3038193

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