The core message of this article is to propose a joint optimization framework to maximize the sum spectral efficiency of a reconfigurable intelligent surface (RIS)-assisted cell-free massive multiple-input multiple-output (mMIMO) non-orthogonal multiple access (NOMA) system, considering imperfect channel state information and imperfect successive interference cancellation.
A complex-valued, geometry-aware meta-learning neural network that maximizes the weighted sum rate in an RIS-aided multi-user MISO system by leveraging the complex circle geometry for phase shifts and spherical geometry for the precoder, leading to faster convergence and higher weighted sum rates compared to existing approaches.
Efficient resource allocation schemes, including orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), and rate-splitting multiple access (RSMA), are investigated to enable the coexistence of semantic and bit communications in future 6G networks.
An iterative optimization algorithm is proposed to jointly adjust the transmit precoder and the weights of the dynamic metasurface antenna (DMA) elements to minimize the bit error probability (BEP) in a DMA-based communication system.
This work proposes a novel upper bound on the outage probability of finite-blocklength IR-HARQ, which enables efficient power allocation to minimize energy consumption while meeting the outage probability constraint.
The content presents a comprehensive overview of the decade-long advancements in in-band full-duplex (IBFD) massive multiple-input multiple-output (MIMO) systems, ranging from cellular networks to network-assisted cell-free massive MIMO (NAFD CF-mMIMO) architectures, highlighting the evolutionary trajectory and key benefits of each implementation.
Integrating active reconfigurable intelligent surfaces (RISs) can significantly enhance energy transfer efficiency and data transmission performance in wireless-powered communication (WPC) systems for Internet of Things (IoT) networks.
This paper investigates the performance of active reconfigurable intelligent surface (RIS)-aided terahertz (THz) communication systems, focusing on the impact of discrete phase shifts and beam misalignment.
Deploying a refracting reconfigurable intelligent surface on high-speed train windows can effectively enhance the coverage and reliability of millimeter wave communications for ultra-reliable and low-latency applications.
This paper proposes an optimization framework to maximize the achievable covert rate in an XL-RIS empowered near-field communication system, by jointly optimizing the hybrid analog-digital beamforming at the transmitter and the reflection coefficient matrix at the XL-RIS.