Fluid antenna systems (FAS) have emerged as a promising paradigm for wireless communications, enabling channel reconfigurability that offers a novel spatial degree of freedom. Nevertheless, efficiently acquiring accurate and high-resolution channel state information (CSI) in FAS remains challenging, primarily due to its dynamic spatial structure and limited coherence time. This paper proposes a novel diffusion framework that takes the partially observed CSI matrix as the terminal state of the Markov chain and operates exclusively on the unobserved ports. Built upon this framework, we design a UNet-based architecture, termed the channel extrapolation UNet (CEUNet), that integrates modified MaxViT (mMaxViT) blocks and residual blocks (ResBlocks) to jointly capture local and global channel dependencies for accurate CSI extrapolation. Extensive experiments on the Jakes’ channel model are conducted to evaluate CEUNet. Numerical results show that CEUNet consistently outperforms state-of-the-art deep learning models in estimation accuracy across all signal-to-noise ratios and observation ratios, even with only two sampling steps. Furthermore, a comprehensive complexity analysis is conducted to compare the computational efficiency of CEUNet with that of the baseline models, while ablation studies are carried out to quantitatively evaluate the contribution of each component integrated into the proposed CEUNet.
Xue-Feng Wang, Yu-Hang Li, Yang Lu et al.· IEEE Transactions on Wireles...· 0 citations
Fluid reconfigurable intelligent surfaces (FRISs) have recently emerged as a promising extension of conventional reconfigurable intelligent surfaces (RISs), with the dynamic spatial control capability of fluid antenna systems (FASs). By replacing fixed reflecting elements with densely deployed, position-selective sub-elements capable of discrete phase adjustment, the FRIS provides additional spatial degrees of freedom (DoFs). Exploiting this advantage, we investigate the use of FRIS to maximize energy efficiency (EE) for a non-orthogonal multiple access (NOMA) system under predefined quality-of-service (QoS) constraints. The optimization problem is non-convex due to the fractional EE objective, coupled transmit power allocation, binary FRIS mask selection, and discrete phase shifts. To address this challenge, an alternating optimization (AO) framework is developed by integrating Dinkelbach’s method, first-order Taylor expansion, and a top- $M_{o}$ activation mechanism. Numerical results demonstrate that the proposed FRIS framework achieves substantial EE gains over conventional RIS-based benchmarks.
Wen-Yu Song, Hongyi Luo, Daniel K. C. So et al.· IEEE Wireless Communications...· 0 citations
High-capacity satellite network is the cornerstone of future space-air-ground integrated networks. However, the satellite uplink transmissions still face critical challenges, including severe path loss, complex multi-user interference, and payload constraints. Recently, Reconfigurable Intelligent Surfaces (RIS) and Fluid Antenna Systems (FAS) have shown promise for satellite communications through their dynamic signal reconfiguration. This paper proposes a multi-RIS-assisted satellite Compact Ultra-Massive Antenna Array (CUMA) architecture for multi-user satellite uplink transmission. Specifically, we deploy multiple RISs on the terrestrial side to separate interfering Line-of-Sight (LoS) channels via optimized phase shifts, and adopt a CUMA receiver on the satellite to further mitigate interference through FAS port selection. To solve a sum-rate maximization problem, we alternately optimize FAS port selection using a Forward-Backward Greedy Selection (FBGS) algorithm and RIS phase shifts based on Fractional Programming (FP). To the best of our knowledge, this is the first work to jointly optimize multi-RIS and CUMA in a satellite uplink context, where strong LoS and extreme path loss fundamentally distinguish the design from terrestrial counterparts. Simulation results confirm the effectiveness of the proposed architecture across frequency bands. At 6 GHz, our scheme achieves 181% and 32% rate gains over fixed antennas and traditional CUMA schemes, respectively, while the gains also reach 138% and 27% at 26 GHz, illustrating superiority in both interference-limited and noise-limited regimes.
Kai Feng, Runke Fan, Tianheng Xu et al.· IEEE Open Journal of the Com...· 0 citations
The unprecedented growth of machine-type devices has underscored the need for fundamental solutions to support emerging massive connectivity. In particular, unsourced random access (URA) has emerged as a promising paradigm, reframing the massive connectivity problem as a coding-theoretic challenge with favorable energy and spectral efficiency. Among the widely studied URA models, the Gaussian multiple-access channel (GMAC) and multi-input multi-output (MIMO) systems are of particular significance. Sparse code design is well-suited for URA, offering scalable solutions while retaining many advantages of legacy access protocols. However, existing sparse code designs often suffer from limited sparsity control, inefficient interference cancellation, and a strong dependence on specific channel code designs, posing challenges for long-term adaptability as more powerful channel codes continue to evolve. In MIMO-URA systems, additional activity detection and channel estimation phases typically lead to increased missed detection (MD) and false alarm (FA) errors compared with the GMAC model, which does not require these phases. While prior studies have predominantly focused on minimizing MD errors, the effective mitigation of FA errors remains an open problem. To address this challenge, we propose a sparse code with slotted transmission under the GMAC model, combined with an analytical power division strategy to enhance interference cancellation. Furthermore, we introduce a novel MIMO receiver framework based on joint pattern–data–channel (JPDC) estimation, which significantly reduces FA errors by leveraging the intrinsic correlation between user activity and transmitted data. Notably, the proposed method achieves improved overall system performance without requiring additional transmission overhead or complex algorithms.
Zhen-Tian Zhang, Mohammad Javad Ahmadi, Kai-Kit Wong et al.· IEEE Transactions on Wireles...· 5 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
