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

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 mini...

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Main Authors Liu, Sheng, Wang, Yajun
Format Conference Proceeding
LanguageEnglish
Published SPIE 07.08.2024
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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
AbstractList 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
Author Liu, Sheng
Wang, Yajun
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  organization: Jiangsu University of Science and Technology (China)
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DOI 10.1117/12.3038193
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Discipline Engineering
Editor Yang, Lvqing
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Notes Conference Date: 2024-05-10|2024-05-12
Conference Location: Nanchang, China
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Snippet 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...
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Title Low-complexity PAPR-aware precoding for large-scale MIMO-OFDM downlink systems
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