On the Performance of Cell-Free IoT Systems With RSMA and Downlink Training
This letter establishes a novel transmission framework that amalgamates downlink (DL) training with rate-splitting multiple access, thereby being expected to enhance the spectral efficiency (SE) of a cell-free massive multiple-input multiple-output enabled Internet of Things (IoT) system. Considering a correlated Ricean fading environment coupled with imperfect channel knowledge, we derive a closed-form expression for the achievable SE and evaluate the DL SE under a variety of system configurations. Our comprehensive simulations corroborate the theoretical findings and yield critical insights pertinent to the system’s architectural design.
Authors
- Yaoqi Sun
- Wenchao Xia (ORCID: https://orcid.org/0000-0001-6245-0347)
- Yao Zhang (ORCID: https://orcid.org/0000-0003-4496-2650)
- Hongkui Wang (ORCID: https://orcid.org/0000-0002-4443-798X)
- Haitao Zhao (ORCID: https://orcid.org/0000-0002-3539-3532)
- Hongbo Zhu (ORCID: https://orcid.org/0000-0002-1032-4434)
- Bo Wu (ORCID: https://orcid.org/0000-0001-9883-5097)
Institutions
- National Development and Reform Commission (CN)
- Nanjing University of Posts and Telecommunications (CN)
- Hangzhou Dianzi University (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1109/jiot.2024.3442294
- Citations
- 3
- Primary Topic
- IoT Networks and Protocols
- Type
- article
- Field-Weighted Citation Impact
- 0.63
Funders
- National Natural Science Foundation of China
- Vignan's Foundation for Science, Technology and Research