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Bibliographic Details
Main Authors: Rou, Hyeon Seok, de Abreu, Giuseppe Thadeu Freitas, Takahashi, Takumi, G., David González, Gonsa, Osvaldo
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.08087
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author Rou, Hyeon Seok
de Abreu, Giuseppe Thadeu Freitas
Takahashi, Takumi
G., David González
Gonsa, Osvaldo
author_facet Rou, Hyeon Seok
de Abreu, Giuseppe Thadeu Freitas
Takahashi, Takumi
G., David González
Gonsa, Osvaldo
contents Index modulation (IM) is one of the key enabling technologies for beyond fifth generation (B5G) and sixth generation (6G) wireless systems, attracting attention for its inherent energy and spectral efficiency resulting from conveying information through the indexation of the resources utilized in during signal transmission. However, a remaining critical bottleneck for large-scale IM is the consequently infeasible detection complexity of combinatoric order. Therefore in this article, in order to maximally reap the advantages of IM in large scenarios, we propose a novel message passing (MP) decoder designed under the Gaussian belief propagation (GaBP) framework exploiting a novel unit vector decomposition (UVD) of IM signals with purpose-derived novel probability distributions. The proposed method enjoys a low decoding complexity that is independent of previously prohibitive combinatorial factors, while still approach-ing the performance of unfeasible state-of-the-art (SotA) search-based methods. The effectiveness of the proposed approach is demonstrated via complexity analysis and numerical results for the exemplary piloted generalized quadrature spatial modulation (GQSM) systems of truly massive sizes (up to 96 antennas).
format Preprint
id arxiv_https___arxiv_org_abs_2407_08087
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Enabling Massive Index Modulation Systems via Combinatorics-Free Detection
Rou, Hyeon Seok
de Abreu, Giuseppe Thadeu Freitas
Takahashi, Takumi
G., David González
Gonsa, Osvaldo
Signal Processing
Index modulation (IM) is one of the key enabling technologies for beyond fifth generation (B5G) and sixth generation (6G) wireless systems, attracting attention for its inherent energy and spectral efficiency resulting from conveying information through the indexation of the resources utilized in during signal transmission. However, a remaining critical bottleneck for large-scale IM is the consequently infeasible detection complexity of combinatoric order. Therefore in this article, in order to maximally reap the advantages of IM in large scenarios, we propose a novel message passing (MP) decoder designed under the Gaussian belief propagation (GaBP) framework exploiting a novel unit vector decomposition (UVD) of IM signals with purpose-derived novel probability distributions. The proposed method enjoys a low decoding complexity that is independent of previously prohibitive combinatorial factors, while still approach-ing the performance of unfeasible state-of-the-art (SotA) search-based methods. The effectiveness of the proposed approach is demonstrated via complexity analysis and numerical results for the exemplary piloted generalized quadrature spatial modulation (GQSM) systems of truly massive sizes (up to 96 antennas).
title Enabling Massive Index Modulation Systems via Combinatorics-Free Detection
topic Signal Processing
url https://arxiv.org/abs/2407.08087