Marine Internet of Things (IoT) systems have grown substantially with the development of non-terrestrial networks (NTN) via aerial and space vehicles in the upcoming sixth-generation (6G), thereby assisting environment protection, military reconnaissance and sea transportation. Due to the unpredictable climate changes and the extreme channel conditions of maritime networks, however, it is challenging to efficiently and reliably collect and compute a huge amount of maritime data. In this paper, we propose a hybrid low-Earth orbit (LEO) and unmanned aerial vehicle (UAV) edge computing method in space-air-sea integrated networks for marine IoT systems. Specifically, two types of edge servers mounted on UAVs and LEO satellites are endowed with computational capabilities for the real-time utilization of a sizable data collected from ocean IoT sensors. Our system aims at minimizing the total energy consumption of the battery-constrained UAV by jointly optimizing the bit allocation of communication and computation along with the UAV path planning under latency, energy budget and operational constraints. For availability and practicality, the proposed methods are developed for three different cases according to the accessibility of the LEO satellite“, Always On”, “Always Off” and “Intermediate Disconnected”, by leveraging successive convex approximation (SCA) strategies. Via numerical results, we verify that significant energy savings can be accrued for all cases of LEO accessibility by means of joint optimization of bit allocation and UAV path planning compared to partial optimization schemes that design for only the bit allocation or trajectory of the UAV.

This paper encompasses various topics for 5G-involved broadcasting under the common context converged distribution of 5G media. Particularly, two primary subtopics are addressed: An overlaid coexistence of 5G terrestrial broadcast and Advanced Television Systems Committee (ATSC) 3.0; and dual connectivity applications built on top of the convergence between digital broadcasting and 5G unicasting. In the first part, a viable, time-sharing co-transmission system is introduced to overlay 5G Broadcast and ATSC 3.0 frames in the same radio spectrum. The system is carefully designed to comply with current 5G and ATSC 3.0 standards, so that it does not require modifications in either ATSC 3.0 or 5G specifications. To help the future planning in a technical aspect, the reliability performance is in-depth compared between 5G Broadcast and ATSC 3.0 frames, and the motivation of tower overlaying is discussed as well. Subsequently in the $2^{\mathrm{ nd}}$ part, the convergence is in parallel explored with respect to the dual connectivity. To settle a broad-ranged consensus for future convergence, various possible use cases are proposed in an application aspect. Technical, conceptual proposals and implementations are presented, specifically related to edge caching; 8K streaming (with a working prototype); large-scale software updating; data security; and location tracking. We hereby point out how dual connectivity can contribute to realistic scenarios. In turn, the scope of convergence use cases is desirably expanded, so that would encourage the initiatives bridging 5G and broadcasting into practice.

This paper presents a novel transceiver design aimed at enabling Direct-to-Satellite Internet of Things (DtS-IoT) systems based on the long-range frequency-hopping spread spectrum (LR-FHSS). Our focus is on the development of an accurate framing scheme through an analysis of the frame structure and key parameters pertaining to a Long-Range Wide-Area-Network (LoRaWAN) [1]. To handle the Doppler effect in DtS-IoT networks and simultaneously enable the reception of numerous frequency hopping signals, a robust signal detector for the receiver is proposed. We verify the performance of the proposed LR-FHSS transceiver design through simulations conducted in a realistic satellite channel environment, assessing several metrics.

With increasing interest in mmWave and THz communication systems, an unmanned aerial vehicle (UAV)-mounted intelligent reflecting surface (IRS) has been suggested as a key enabling technology to establish robust Line-of-Sight (LoS) connections with ground nodes owing to their free mobility and high altitude, especially for emergency and disaster response. This article investigates a secure offloading system, where the UAV-mounted IRS assists the offloading procedures between ground users and an access point (AP) acting as an edge cloud. In this system, the users except the intended recipients in the offloading process are considered as potential eavesdroppers. The system aims to achieve the minimum total energy consumption of battery-limited ground user devices under constraints for secure offloading accomplishment and operability of UAV-mounted IRS, which is done by optimizing the transmit power of ground user devices, the trajectory and phase shift matrix of UAV-mounted IRS, and the offloading ratio between local execution and edge computing based on the successive convex approximation (SCA) algorithms. Numerical results show that the proposed algorithm can provide the considerable energy savings compared with local execution and partial optimizations.

This paper proposes a long range-frequency hopping spread spectrum (LR-FHSS) transceiver design for the Direct-to-Satellite Internet of Things (DtS-IoT) communication system. The DtS-IoT system has recently attracted attention as a promising non-terrestrial network (NTN) solution to provide high-traffic and delay-tolerant data transfer services, such as wide-area situational awareness (WASA) in smart grids and car share management in automotive applications, to IoT devices in global coverage. In particular, this study provides guidelines for the overall DtS-IoT system architecture and design details that conform to the Long Range Wide-Area Network (LoRaWAN). Furthermore, we also detail various DtS-IoT use cases. Considering low-Earth orbit (LEO) satellites, we develop the LR-FHSS transceiver to improve system efficiency, which is a leading attempt to build practical satellite communication systems using LR-FHSS, excluding commercial products. Moreover, we apply a robust synchronization scheme against the Doppler effect and co-channel interference (CCI) caused by LEO satellite channel environments, including signal detection for the simultaneous reception of numerous frequency hopping signals and an enhanced softoutput-Viterbi-algorithm (SOVA) for the header and payload receptions. Lastly, we present proof-of-concept implementation and testbeds using an application-specific integrated circuit (ASIC) chipset and a fieldprogrammable gate array (FPGA) that verify the performance of the proposed LR-FHSS transceiver design of DtS-IoT communication systems. The laboratory test results reveal that the proposed LR-FHSS-based framework with the robust synchronization technique can provide wide coverage, seamless connectivity, and high-throughput communication links for the realization of future satellite communication networks.

In this study, a reconfigurable intelligent surface (RIS)-assisted wireless-powered mobile edge computing (WP-MEC) system is proposed, where a single-antenna unmanned aerial vehicle (UAV)-mounted cloudlet provides offloading opportunities to K user equipments (UEs) with a single antenna, and the K UEs can harvest the energy from the broadcast radio-frequency signals of the UAV. In addition, rate-splitting multiple access is used to provide offloading opportunities to multiple UEs for effective power control and high spectral efficiency. The aim of this paper is to minimize the total energy consumption by jointly optimizing the resource allocation in terms of time, power, computing frequency, and task load, along with the UAV trajectory and RIS phase-shift matrix. Since coupling issues between optimization variable designs are caused, however, an alternating optimization-based algorithm is developed. The performance of the proposed algorithm is verified via simulations and compared with the benchmark schemes of partial optimizations of resource allocation, path planning, and RIS phase design. The proposed algorithm exhibits high performance in WP-MEC systems with insufficient resources, e.g., achieving up to 40% energy reduction for a UAV with eight elements of RIS.