no code implementations • 7 Nov 2023 • Yifan Zhao, Xuehui Wang, Yan Wang, Xianpeng Wang, Zhilin Chen, Feng Shu, Cunhua Pan, Jiangzhou Wang
Due to its slow linear convergence from iterative GA, the proposed ESMPI-GA is high-complexity.
no code implementations • 5 Dec 2022 • Feng Shu, Jing Liu, Yeqing Lin, Yang Liu, Zhilin Chen, Xuehui Wang, Rongen Dong, Jiangzhou Wang
To fully exploit the amplifying gain achieved by active IRS, two high-rate methods, maximum ratio reflecting (MRR) and selective ratio reflecting (SRR) are presented, which are motivated by maximum ratio combining and selective ratio combining.
no code implementations • 27 Apr 2021 • Ziyue Wang, Ya-Feng Liu, Zhilin Chen, Wei Yu
Specifically, at each iteration, the proposed active set CD algorithm first selects a small subset of all devices, namely the active set, which contains a few devices that contribute the most to the deviation from the first-order optimality condition of the MLE problem thus potentially can provide the most improvement to the objective function, then applies the CD algorithm to perform the detection for the devices in the active set.
no code implementations • 6 Feb 2021 • Ziyue Wang, Zhilin Chen, Ya-Feng Liu, Foad Sohrabi, Wei Yu
Specifically, at each iteration, the proposed algorithm focuses on only a small subset of all potential sequences, namely the active set, which contains a few most likely active sequences (i. e., transmitted sequences by all active devices), and performs the detection for the sequences in the active set.