The core message of this paper is to propose a novel system that incorporates a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) with simultaneous wireless information and power transfer (SWIPT) using rate splitting multiple access (RSMA) to optimize both the sum rate of information decoding receivers (IDRs) and the total harvested energy at energy harvesting receivers (EHRs).
The core message of this article is to investigate the performance of an active reconfigurable intelligent surface (RIS)-aided uplink massive multiple-input multiple-output (MIMO) system in the presence of imperfect channel state information (CSI) and phase noise at the active RIS. The authors derive a closed-form expression for a lower bound of the achievable rate and analyze the power scaling laws of the considered system.
The authors propose a double self-sustainable reconfigurable intelligent surfaces (RISs) aided multi-user multiple input multiple output (MIMO) communication system to minimize the transmission power at the base station while guaranteeing the quality of service requirements of the users and meeting the power consumption requirements of the RISs.
Deploying active and passive intelligent reflecting surfaces (IRSs) at optimal locations can significantly enhance wireless coverage and throughput in site-specific multi-building environments, with active IRSs outperforming passive IRSs in terms of coverage and fairness.
The ergodic spectral efficiency of intelligent omni-surface (IOS)-aided wireless communication systems is analyzed, considering imperfect channel state information (CSI) and transceiver hardware impairments.
The performance of reconfigurable holographic surfaces (RHS) in near-field cell-free networks is limited by phase shift errors at the RHS elements and hardware impairments in the radio frequency chains of transceivers. Increasing the number of base stations can compensate for these impairments.
This paper proposes an energy-efficient switch-controlled reconfigurable holographic surface (RHS) beamforming architecture that maximizes the energy efficiency by jointly optimizing the holographic beamformer, digital beamformer, total transmit power, and power allocation ratio, while considering the impact of realistic hardware impairments.
The achievable rate of an intelligent omni-surface (IOS) assisted holographic MIMO system employing non-orthogonal multiple access (NOMA) is higher than that of the orthogonal multiple access (OMA) counterpart, but saturates at high signal-to-noise ratios due to hardware impairments.
This paper proposes a novel framework to achieve robust performance in FDD massive MIMO systems by completely eliminating the need for downlink channel state information (CSIT) feedback. The key idea is to reconstruct the downlink channel from uplink training using the 2D-Newtonized orthogonal matching pursuit (2D-NOMP) algorithm, which exploits the partial frequency invariance of channel parameters between uplink and downlink. To overcome the inevitable multi-user interference caused by discrepancies between uplink and downlink channels, the authors employ rate-splitting multiple access (RSMA) and develop an error covariance matrix (ECM) estimation method using the observed Fisher information matrix.
The authors propose a power- and hardware-efficient, pragmatic, modular, multiuser/multibeam array-fed RIS architecture particularly suited for high-frequency bands where channels are typically sparse in the beamspace and line-of-sight (LOS) is required.