Multi-Hop Cooperative G-SFIM System With Low-Complexity Detection Under Imperfect CSI

This paper proposes a multi-hop cooperative grouping space-frequency index modulation (G-SFIM) system with decode-and-forward (DF) protocol. By using group mapping and 3D constellation, the minimum Euclidean distance of the G-SFIM signals is increased. Meanwhile, the signals are conveyed through the multi-hop architecture to improve the communication reliability. Under the imperfect and perfect channel state information (CSI), the closed-form expressions of the average bit error probability (ABEP) are derived. To reduce the complexity of the optimal maximum-likelihood (ML) detection, the minimum mean-squared error (MMSE) based grouping ML (MMSE-GML), the MMSE based grouping greedy detection (MMSE-GGD), and the grouping ordered block based ML (GOB-ML) detection algorithms are proposed. Numerical results validate the correctness of the theoretical ABEP of the multi-hop cooperative G-SFIM system under different CSI conditions. Meanwhile, the proposed system achieves better ABEP performance and is less sensitive to the imperfect CSI. Additionally, the three presented low-complexity detection algorithms offer the flexible compromise between the ABEP performance and the complexity.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-10-24
DOI
https://doi.org/10.1109/tvt.2024.3486046
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Hop Cooperative G-SFIM System With Low-Complexity Detection Under Imperfect CSI

Ke Pang, Zhiquan Bai, Haijun Zhang, Dongfeng Yuan et al.
IEEE Transactions on Vehicular Technology
Advanced Algorithms and Applications
article

Multi-Hop Cooperative G-SFIM System With Low-Complexity Detection Under Imperfect CSI

Ke Pang, Zhiquan Bai, Haijun Zhang, Dongfeng Yuan, K. S. KWAK
article en

Abstract

This paper proposes a multi-hop cooperative grouping space-frequency index modulation (G-SFIM) system with decode-and-forward (DF) protocol. By using group mapping and 3D constellation, the minimum Euclidean distance of the G-SFIM signals is increased. Meanwhile, the signals are conveyed through the multi-hop architecture to improve the communication reliability. Under the imperfect and perfect channel state information (CSI), the closed-form expressions of the average bit error probability (ABEP) are derived. To reduce the complexity of the optimal maximum-likelihood (ML) detection, the minimum mean-squared error (MMSE) based grouping ML (MMSE-GML), the MMSE based grouping greedy detection (MMSE-GGD), and the grouping ordered block based ML (GOB-ML) detection algorithms are proposed. Numerical results validate the correctness of the theoretical ABEP of the multi-hop cooperative G-SFIM system under different CSI conditions. Meanwhile, the proposed system achieves better ABEP performance and is less sensitive to the imperfect CSI. Additionally, the three presented low-complexity detection algorithms offer the flexible compromise between the ABEP performance and the complexity.

IEEE Transactions on Vehicular TechnologyVol. 74(3)
Shandong University (CN), Inha University (KR), Changzhou University (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 78%
Advanced Algorithms and Applications
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