Performance analysis of Hexagonal QAM constellations on quadrature spatial modulation with perfect and imperfect channel estimation

Cogen F., AYDIN E.

PHYSICAL COMMUNICATION, vol.47, 2021 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 47
  • Publication Date: 2021
  • Doi Number: 10.1016/j.phycom.2021.101379
  • Journal Indexes: Science Citation Index Expanded, Scopus, Compendex, INSPEC
  • Keywords: Spatial modulation, Quadrature spatial modulation, Hexagonal quadrature amplitude modulation, MIMO systems


In this study, the quadrature spatial modulation (QSM) technique, which is a rational multiple-input multiple-output (MIMO) transmission technique and frequently encountered in recent studies in the literature, and the hexagonal quadrature amplitude modulation (HQAM) constellation technique, which combines symbols in an "optimum" way are combined. This new MIMO scheme has been named by the authors as HQAM-QSM. Also, the impact of imperfect channel knowledge on the performance of the proposed scheme is examined. The HQAM constellation technique is a technique that provides better results under the same power assumption than the conventional QAM constellation in terms of symbol separation and is more often encountered when it comes to energy-efficiency. Due to the nature of HQAM symbols, error-floor occurs when the QSM system is applied. Hence, the optimum angle is obtained by rotating the HQAM symbols. With this optimum angle, it has been seen that the error-floor disappeared and the performance of the system is improved. Besides, the HQAM technique performs similar bit error rates (BER) to QAM at high signal-to-noise ratio (SNR) values. From this point forth, in our study, the rational HQAM-QSM technique, which uses energy-efficient HQAM symbols instead of traditional modulated QAM symbols and also carries information effectively on two active antennas, is proposed. Performance analysis of the HQAM-QSM technique is performed on Rayleigh fading channels. (C) 2021 Elsevier B.V. All rights reserved.