Nonideal Energy Efficiency Optimization Based on MIMO Communications

Jiaxuan Li, Xue Yin, Xuhui Ding*, Ziyi Yang*, Neng Ye, Kai Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In MIMO systems, hybrid digital and analog precoding structures are gaining attention for reducing power consumption and costs compared to fully digital precoding. However, deployment expenses and circuit power consumption still pose challenges. Nonideal hardware in practical applications further impacts energy efficiency (EE), making research into high-energy-efficiency MIMO structures under such conditions essential. To tackle this issue, an exceedingly effective hybrid precoding strategy is developed, incorporating the implications of nonideal hardware characteristics. Initially, the research models the aforementioned hardware characteristics, formulates the signal model for the hybrid-structured MIMO communication system, and discerns the nonconvex problem relative to energy efficiency optimization. Subsequently, the optimization problem is effectively resolved by choosing analog radio frequency (RF) precoding and digital baseband precoding designs, including the precoding design for array gain. Furthermore, fractional programming is utilized to achieve digital precoding. An iterative optimization method is utilized to solve this problem. Finally, the mixed precoding scheme is formulated to showcase the system’s energy efficiency performance through simulation and explore the impact of imperfect hardware on the system. Additionally, to further diminish design complexity, the implementation of various channels is analyzed to propose a low-complexity method via the approximation of the equivalent channel matrix. Simulation results show that the performance of this method achieves performance comparable to existing hybrid precoding methods, when the number of antennas is sufficiently large.

Original languageEnglish
Pages (from-to)23975-23987
Number of pages13
JournalIEEE Internet of Things Journal
Volume12
Issue number13
DOIs
Publication statusPublished - 2025

Keywords

  • Energy efficiency
  • MIMO
  • hybrid beamforming
  • optimization

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