Unmanned aerial vehicles (UAVs) can be harnessed as relay nodes in free-space optical (FSO) communication systems to realize a flexible and cost-effective approach for delivering on-demand communication in next-generation wireless communications. However, fading channels can adversely affect the performance of UAV-assisted dual-hop FSO systems owing to various factors. This paper presents a unified system performance analysis of UAV-assisted dual-hop FSO/FSO systems with the amplify-and-forward relaying protocol and intensity modulation/direct detection technique. For general applicability, the influence of the attenuation loss, atmospheric turbulence, pointing error impairments, and angle-of-arrival (AOA) fluctuations on the FSO link between the source and the UAV is considered. Meanwhile, the FSO link between the UAV and the destination is modeled using Málaga distribution channels, which are affected by atmospheric turbulence. The tight closed-form expressions for the outage probability and the average bit error rate of the dual-hop system are derived, followed with the diversity order of the system in the high signal-to-noise ratio range. Furthermore, the impact of various system parameters and channel parameters correlated with the attenuation loss, atmospheric turbulence, pointing error impairments, and AOA fluctuations on the system performance is studied, and a detailed comparative investigation of the various modulation schemes is conducted. Finally, simulation results are presented to validate the analytical results.

In order to better explore the ocean, autonomous underwater vehicles (AUVs) have been widely applied to facilitate the information collection. However, considering the extremely large-scale deployment of sensor nodes in the Internet of Underwater Things (IoUT), a homogeneous AUV-enabled information collection system cannot support timely and reliable information collection considering the time-varying underwater environment as well as AUV’s energy and mobility constraints. In this article, we propose a multi-AUV-assisted heterogeneous underwater information collection scheme for the sake of optimizing the peak Age of Information (AoI). Moreover, the limited service M/G/1 vacation queueing model is utilized to model the process of information exchange, where the optimal upper limit of the number of AUVs served in the queueing system as well the steady-state distribution of the queue length are derived. A low-complexity adaptive algorithm for adjusting the upper limit of the queuing length is also proposed. Finally, simulation results validate the effectiveness of our proposed scheme and algorithm, which outperform traditional methods in terms of the peak AoI.

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions.

High throughput satellite (HTS) is viewed as a promise solution for the next generation of satellite-based Internet of Things (S-IoT). Considering the onboard communication resources such as power and storage are limited, we formulate a joint network stability and resource allocation optimization problem to maximize the long-term network utility of a non-orthogonal multiple access S-IoT downlink system. First, we establish two virtual queues for both the data queueing and power expenditure, respectively. Then, a joint optimal problem can be formulated as a problem that optimizes the time average of network utility, which perfectly matches the Lyapunov optimization framework. Therefore, by taking into account the condition of successive interference cancellation decoding, we propose a practical solution under the Karush-Kuhn-Tucker conditions, and further introduce an optimal solution by using the particle swarm optimization algorithm for the joint resource allocation problem. Simulation results demonstrate that our joint optimization allocation schemes outperform the existing benchmark schemes.

A hybrid satellite-terrestrial relay network (HSTRN) has been envisioned as a promising communication architecture for future wireless communications, which can prominently reduce the impact of shadow fading and expand service coverage. In this paper, we conduct theoretical performance analysis for a dual-hop communication system, consisting of multiple relays and multiple users in the HSTRN with the amplify-and-forward protocol. For the shadowing effect and the multipath effect, we introduce the shadowed-Rician distribution and Nakagami- $m$ fading to characterize the channel models for the satellite-relay and the relay-user links, respectively. Additionally, the opportunistic scheduling scheme is employed, where the optimal relay and the optimal user are selected from the alternative nodes with the maximum instantaneous signal-to-noise ratio. Thereafter, the analytical expressions including ergodic capacity and average symbol error rate (SER) are derived. More specifically, we also present the asymptotic behavior of the average SER at the high signal-to-noise ratio (SRN) regime. The theoretical analysis is validated by the numerical results. Moreover, the results also reveal that the performance of the system can be improved by increasing the number of relays and users under different channel parameters and various modulation schemes.

In the coming sixth generation (6G) communication era, to provide seamless and ubiquitous connections, the space-air-ground-sea integrated network (SAGSIN) is envisioned to address the challenges of communication coverage in areas with difficult conditions, such as the forest, desert, and sea. Considering the fundamental limitations of the SAGSIN including large-scale scenarios, highly dynamic channels, and limited device capabilities, traditional communications based on Shannon information theory cannot satisfy the communication demands. Moreover, bit-level reconstruction is usually redundant for many human-to-machine or machine-to-machine applications in the SAGSIN. Therefore, it is imperative to consider high-level communications towards semantics exchange, called semantic communications. In this survey, according to the interpretations of the term “semantics", including “significance"“, meaning", and “effectiveness-related information", we review state-of-the-art works on semantic communications from three perspectives, which are 1) significance representation and protection, 2) meaning similarity measurement and meaning enhancement, and 3) ultimate effectiveness and effectiveness yielding. Sequentially, three types of semantic communication systems can be correspondingly introduced, namely the significance-oriented, meaning-oriented, and effectiveness/task-oriented semantic communication systems. Implementation of the above three types of systems in the SAGSIN necessitates a new perception-communication-computing-actuation-integrated paradigm (PCCAIP), where all the available perception, computing, and actuation techniques jointly facilitate significance-oriented sampling & transmission, semantic extraction & reconstruction, and task decision. Finally, we point out some future challenges on semantic communications in the SAGSIN. This survey provides a comprehensive review on the future semantic communications in the SAGSIN, and elaborates on the performance metrics and techniques related to semantic communications for references and further in-depth investigations.