Publication: Quadrature permutation matrix modulation
Program
KU Authors
Co-Authors
Editor & Affiliation
Compiler & Affiliation
Translator
Other Contributor
Date
Language
Type
Embargo Status
No
Journal Title
Journal ISSN
Volume Title
Alternative Title
Abstract
This paper introduces the in-phase and quadrature (IQ) extension to the permutation matrix modulation (PMM) technique and proposes the quadrature PMM (QPMM) scheme for higher spectral efficiency without any expense in RF chains. Assuming a single-user MIMO (SU-MIMO) system model with all antennas activated, the proposed QPMM scheme utilizes the permutation matrices as the spatial indexing unit for both the IQ components of the complex symbol vector. Furthermore, a low-complex detector, conditional maximum likelihood detector (C-MLD), that achieves the same bit error rate (BER) performance as the optimal joint MLD is presented. In addition to the low-complex C-MLD detector, a deep learning (DL) based detector, called FusionDet, is also proposed for the QPMM scheme. This DL-based detector provides a trade-off between complexity and BER performance. The BER performance of the QPMM scheme and the complexities of the detectors are examined. The provided computer simulations reveal that the proposed QPMM scheme outperforms the conventional PMM method for different MIMO setups and modulation levels. In addition, the complexity analysis shows that C-MLD attains the same BER performance as the optimal joint MLD with significantly lower complexity. Finally, FusionDet is observed to further decrease detector complexity in exchange for sub-optimal detection performance.
Source
Publisher
IEEE
Subject
Engineering, Telecommunications
Citation
Has Part
Source
IEEE Transactions on Wireless Communications
Book Series Title
Edition
DOI
10.1109/TWC.2025.3581483
item.page.datauri
Link
Rights
CC BY-NC-ND (Attribution-NonCommercial-NoDerivs)
Copyrights Note
Creative Commons license
Except where otherwised noted, this item's license is described as CC BY-NC-ND (Attribution-NonCommercial-NoDerivs)
