This paper proposes FAS-LLM, a novel large language model (LLM)–based architecture for predicting future channel states in Orthogonal Time Frequency Space (OTFS)-enabled satellite downlinks equipped with fluid antenna systems (FAS). The proposed method introduces a two-stage channel compression strategy combining reference-port selection and separable principal component analysis (PCA) to extract compact, delay–Doppler–aware representations from highdimensional OTFS channels. These representations are then embedded into a Low Rank Adaptation (LoRA)-adapted LLM, enabling efficient time-series forecasting of channel coefficients. Performance evaluations demonstrate that FAS-LLM outperforms classical baselines including GRU, LSTM, and Transformer models, achieving up to 10 dB normalized mean squared error (NMSE) improvement and up to threefold root mean squared error (RMSE) reduction across prediction horizons. Furthermore, the predicted channels preserve key physical-layer characteristics, enabling near-optimal performance in ergodic capacity, spectral efficiency, and outage probability across a wide range of signal-to-noise ratios (SNRs). These results highlight the potential of LLM-based forecasting for delay-sensitive and energy-efficient link adaptation in future satellite IoT networks.

Integrated data and energy transfer (IDET) is considered as a key enabler of 6G, as it can provide both wireless energy transfer (WET) and wireless data transfer (WDT) services towards low power devices. Thanks to the extra degree of freedom provided by fluid antenna (FA), incorporating FA into IDET systems presents a promising approach to enhance energy efficiency performance. This paper investigates a FA assisted IDET system, where the transmitter is equipped with multiple FAs and transmits wireless signals to the data receiver (DR) and the energy receiver (ER), both of which are equipped with a single traditional antenna. The switching delay and energy consumption induced by port selection are taken into account in IDET system for the first time. We aim to obtain the optimal beamforming vector and the port selection strategy at the transmitter, in order to maximize the short-term and long-term WET efficiency, respectively. The instant sub-optimal solution is obtained by alternatively optimizing the beamforming vector and port selection in each transmission frame, while a novel constrained soft actor critic (C-SAC) algorithm is proposed to find the feasible policy of port selection from the long-term perspective. Simulation results demonstrate that our scheme is able to achieve greater gain in terms of both the short-term and long-term WET efficiency compared to other benchmarks, while not degrading WDT performance.

In the evolving landscape of high-speed communication, the shift from traditional pilot-based methods to a Sensing-Oriented Approach (SOA) is anticipated to gain momentum. This paper delves into the development of an innovative Integrated Sensing and Communication (ISAC) framework, specifically tailored for beamforming and trajectory prediction processes. Central to this research is the exploration of an Unmanned Aerial Vehicle (UAV)-enabled communication system, which seamlessly integrates ISAC technology. This integration underscores the synergistic interplay between sensing and communication capabilities. The proposed system initially deploys omnidirectional beams for the sensing-focused phase, subsequently transitioning to directional beams for precise object tracking. This process incorporates an Extended Kalman Filtering (EKF) methodology for the accurate estimation and prediction of object states. A novel frame structure is introduced, employing historical sensing data to optimize beamforming in real-time for subsequent time slots, a strategy we refer to as ‘temporal-assisted’ beamforming. To refine the temporal-assisted beamforming technique, we employ Successive Convex Approximation (SCA) in tandem with Iterative Rank Minimization (IRM), yielding high-quality suboptimal solutions. Comparative analysis with conventional pilot-based systems reveals that our approach yields a substantial improvement of 156% in multi-object scenarios and 136% in single-object scenarios.

Autonomous aerial vehicles (AAV) can alleviate the computational burden on edge devices through assisted computing. However, with the increase in the number of Internet of Things Devices (IoTDs), it is essential to establish a task queue on the AAV to schedule computing tasks from IoTDs. In addition, the load fairness of AAVs should be optimized to fully utilize the computing resources. Therefore, a multi-AAV-assisted mobile edge computing (MEC) network framework based on the queuing model is proposed, which aims at optimizing the average delay of all user devices and the load fairness of AAVs. Firstly, we prove that the arrangement of tasks with different computing delays on the AAV queue can affect the user’s average delay, so a short-job-first (SJF) queuing model is proposed to minimize the average delay of users. On this basis, a joint optimization problem related to the AAV’s three-dimensional trajectory and user connection scheduling is formulated. A SJF based low-complexity connection scheduling algorithm is proposed and combined in a deep reinforcement learning (DRL) to solve this NP-hard problem. To evaluate the performance of the proposed algorithm, we compare it with deep deterministic policy gradient (DDPG), particle swarm optimization (PSO), random moving (RM), and local computing (LC). Simulation results show that our algorithm effectively reduces user average delay and enhances AAV load fairness. Finally, SJF is compared with the traditional first-come-first-served (FCFS) queuing model on different algorithms. The results indicate that the average delay of SJF is significantly lower than that of FCFS.

Fluid antenna multiple access (FAMA) exploits spatial opportunities in wireless channels through port switching to overcome multiuser interference, achieving better performance than traditional fixed MIMO systems. Integrated Data and Energy Transfer (IDET) is capable of providing both wireless data transfer (WDT) and wireless energy transfer (WET) services for low-power devices. This paper investigates an FAMA-assisted IDET system, where a base station (BS) equipped withNfixed antennas provides dedicated IDET services toNuser equipments (UEs). Each UE is equipped with a single fluid antenna, while the power splitting (PS) approach is conceived for coordinating WDT and WET. Under the Rayleigh channel model, we derive both exact expressions and approximate closed forms for the outage probabilities of WDT and WET, where the fluid antenna (FA) at each UE selects the optimal port to maximize either the signal-to-interference-plus-noise ratio (SINR) or the energy harvesting power (EHP). The IDET outage probabilities are defined and subsequently derived and approximated into closed-forms. Further, multiplexing gains of the proposed system are defined and analyzed to evaluate the performance. Further, we analyze the IDET outage probabilities and multiplexing gains of the proposed system. Additionally, to provide a more general analysis, we extend our analytical framework to the Rician channel model. Numerical results validate the theoretical analysis while also illustrating that the trade-off is achieved between WDT and WET performance by exploiting different port selection strategies and numbers of UEs.

Fluid antenna multiple access (FAMA) is capable of exploiting the high spatial diversity of wireless channels to mitigate multi-user interference via flexible port switching, which achieves a better performance than traditional multi-input-multi-output (MIMO) systems. Moreover, integrated data and energy transfer (IDET) is able to provide both the wireless data transfer (WDT) and wireless energy transfer (WET) services towards low-power devices. In this paper, a FAMA assisted IDET system is studied, where$N$access points (APs) provide dedicated IDET services towards$N$user equipments (UEs). Each UE is equipped with a single fluid antenna. The performance of WDT and WET, i.e., the WDT outage probability, the WET outage probability, the reliable throughput and the average energy harvesting amount, are analysed theoretically by using time switching (TS) between WDT and WET. Numerical results validate our theoretical analysis, which reveals that the number of UEs and TS ratio should be optimized to achieve a trade-off between the WDT and WET performance. Moreover, FAMA assisted IDET achieves a better performance in terms of both WDT and WET than traditional MIMO with the same antenna size.

Fluid antenna system (FAS) represents all forms of movable and non-movable position-flexible antenna system, and opens up the possibility of a new form of modulation schemes. In this paper, we investigate the design of position index modulation (PIM) for FAS for decreasing the bit error rate (BER) while taking advantage of the rate gain in index modulation. We further derive the BER and data rate expressions to assess the achievable performance of PIM. Simulation results are provided to illustrate the performance and some insights are drawn into the impact of both channel estimation accuracy and transmission power.

Fluid antennas located at the user device (UD) can exploit the natural multipath propagation and randomness of the desired data by adjusting its position spatially to find the point at which an interference null occurs. A fast fluid antenna multiple access (f-FAMA) system uses a large antenna array at the base station to transmit each user’s signal from each antenna. The interference is then overcome by a single fluid antenna located at each receiving UD. Previous work has established a channel model for such a f-FAMA system with a technique that estimates the best port for the fluid antenna to receive the signal at every symbol instance. This paper proposes an improved version of the channel model by also taking into consideration the difference in path loss between different ports and also looks into how different fluid antenna architectures effect the performance of an f-FAMA system. Simulation results demonstrate the necessity of considering path loss variations, particularly in scenarios where there are substantial differences in distances from the transmitter to different ports. Additionally, among the three different antenna architectures considered, the performance of the wheel topology antenna is worse than the linear topology and circular topology antennas at shorter reference distances.