Abstract
In this paper, we propose a composite multiple-mode orthogonal frequency division multiplexing with index modulation (C-MM-OFDM-IM) scheme to increase the spectral efficiency (SE) of OFDM-IM systems by extending the indexing to the energy and constellation domains. In C-MM-OFDM-IM, the information bits are mapped to not only the subcarrier activation patterns (SAPs) and modulation symbols, but also the energy allocation patterns (EAPs) and constellation activation patterns (CAPs). To cope with the practical situations, we propose a variant IM scheme named C-MM-OFDM-IM-II to build a new mapping rule between information bits and the increased CAPs, capable of further increasing the SE of C-MM-OFDM-IM. Upper-bounded bit error rate (BER) and lower-bounded achievable rate are both derived in closed-form to evaluate the performance of C-MM-OFDM-IM(-II). Moreover, we further propose two enhanced schemes, named generalized C-MM-OFDM-IM(-II) and C-MM-OFDM with in-phase/quadrature IM(-II), where the former jointly considers all SAPs, EAPs, CAPs and modulated symbols, while the latter expands the index implementation to the in-phase and quadrature constellation domains. Simulation results show that C-MM-OFDM-IM(-II) outperforms the conventional OFDM-IM related schemes, especially in the high signal-to-noise ratio (SNR) region, and verify the accuracy of the theoretical analysis for the upper-bounded BER and achievable rate.
| Original language | English (US) |
|---|---|
| Journal | IEEE Transactions on Wireless Communications |
| DOIs | |
| State | Published - Nov 9 2022 |
Bibliographical note
KAUST Repository Item: Exported on 2022-11-11Acknowledgements: This work was supported in part by the Guangzhou Municipal Science and Technology Project under Grant 202102010416, in part by National Nature Science Foundation of China under Grants 61871190, 62272113 and 61872102, in part by the International Collaborative Research Program of Guangdong Science and Technology Department under Grant No. 2020A0505100061, in part by the Guangzhou University-The Hong Kong University of Science and Technology Joint Research Program under Grant YH202110, in part by Guangzhou Key Laboratory of Software-Defined Low Latency Network under Grant 202102100006, and in part by Innovation Training Program for College Students of Guangzhou Univeristy (Provincial) under Grant S202011078027.