Error Vector Magnitude-Based Low Complexity Adaptive Power Allocation in SM-MIMO System

Abeer Mohamed, Zhiquan Bai*, Jianing Guo, Ke Pang, Oloruntomilayo Femi-Philips, Twarayisenze Jean Paul, Xinhong Hao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In this article, we propose the error vector magnitude (EVM)-based adaptive power allocation (PA) for spatial modulation (SM) multiple-input-multiple-output (MIMO) system to optimize the minimum squared Euclidean distance and reduce the system complexity. We first investigate the typical Euclidean distance (ED)-based PA (ED-PA) algorithm. Second, an EVM-based ED-PA algorithm is proposed, where a simplified closed-form PA solution for the quadrature amplitude modulation is obtained in the case of two transmit antennas. For more transmit antennas, we further propose a low complexity-PA (LC-PA) algorithm, where all the transmit antennas are grouped with two antennas in each group and the proposed EVM-based ED-PA algorithm is utilized to assign the power within each group. Numerical results reveal that the proposed EVM-based ED-PA and LC-PA algorithms have considerably lower complexity and can achieve the optimal average bit error rate (ABER) and suboptimal ABER performance at low-and-moderate signal-to-noise ratio (SNR) region and high-SNR region, respectively, compared with the typical PA algorithms in SM-MIMO system.

Original languageEnglish
Pages (from-to)6164-6174
Number of pages11
JournalIEEE Systems Journal
Volume16
Issue number4
DOIs
Publication statusPublished - 1 Dec 2022

Keywords

  • Adaptive power allocation (PA)
  • Euclidean distance (ED)
  • error vector magnitude (EVM)
  • quadrature amplitude modulation (QAM)
  • spatial modulation multiple-input multiple-output (SM-MIMO)

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