On the Performance of Cell-Free IoT Systems With RSMA and Downlink Training

被引：0

作者：

Zhang, Yao ^{[1
,2
]}

Xia, Wenchao ^{[3
]}

Wu, Bo ^{[4
]}

Zhao, Haitao ^{[3
]}

Sun, Yaoqi ^{[1
,2
]}

Wang, Hongkui ^{[1
,2
]}

Zhu, Hongbo ^{[3
]}

机构：

[1] Hangzhou Dianzi Univ, Sch Commun Engn, Hangzhou 310018, Peoples R China

[2] Hangzhou Dianzi Univ, Lishui Inst, Lishui 323050, Peoples R China

[3] Nanjing Univ Posts & Telecommun, Dept Wireless Commun Key Lab Jiangsu Prov, Nanjing 210003, Peoples R China

[4] Natl Dev & Reform Commiss, Ctr Innovat Driven Dev, Beijing 100824, Peoples R China

来源：

IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 22期

基金：

中国国家自然科学基金;

关键词：

Training; Downlink; Fading channels; Channel estimation; Uplink; Internet of Things; Interference; Cell-free Internet of Things (IoT); downlink (DL) training; rate-splitting multiple access (RSMA); spectral efficiency (SE); FREE MASSIVE MIMO;

D O I：

10.1109/JIOT.2024.3442294

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：37403 / 37406

页数：4

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