no code implementations • 26 Mar 2024 • Ke Yang, Rongen Dong, Wei Gao, Feng Shu, Weiping Shi, Yan Wang, Xuehui Wang, Jiangzhou Wang
In this paper, single large-scale IRS is divided to multiple small IRSs and a novel multi-IRS-aided multi-stream DM network is proposed to achieve a point-to-point multi-stream transmission by creating $K$ ($\geq3$) DoFs, where multiple small IRSs are placed distributively via multiple unmanned aerial vehicles (UAVs).
no code implementations • 15 Oct 2023 • Qiankun Cheng, Rongen Dong, Wenlong Cai, Ruiqi Liu, Feng Shu, Jiangzhou Wang
Subsequently, two high-performance PA strategies, enhanced multiple random initialization Newton's (EMRIN) and Taylor polynomial approximation (TPA), are proposed.
no code implementations • 31 May 2023 • Yan Wang, Feng Shu, Zhihong Zhuang, Rongen Dong, Qi Zhang, Di wu, Liang Yang, Jiangzhou Wang
Numerical simulation results show that a 3-bit discrete phase shifter is required to achieve a trivial performance loss for a large-scale active IRS.
no code implementations • 16 Dec 2022 • Yeqing Lin, Feng Shu, Rongen Dong, Riqing Chen, Siling Feng, Weiping Shi, Jing Liu, Jiangzhou Wang
In this paper, in order to boost the achievable rate of user in such a wireless network, three enhanced-rate iterative beamforming methods are proposed by designing the amplifying factors and the corresponding phases at active IRS.
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 • 29 Sep 2022 • Yeqing Lin, Rongen Dong, Peng Zhang, Feng Shu, Jiangzhou Wang
To reduce the computational complexity, a new method of maximizing receive power with zero-forcing constraint (Max-RP-ZFC) of only reflecting CM and no AN is proposed.