In this letters, an energy-efficient integrated sensing and communication (ISAC) for space-air-ground integrated network (SAGIN)-based Internet of Things (IoT) systems is proposed to facilitate wide coverage and real-time 6G services. For processing a sizable data collected at a IoT device, a hybrid edge computing scheme is applied with the cloudlets mounted at autonomous aerial vehicle (AAV) and low earth orbit (LEO) satellite, where the AAV with multiple antennas performs uplink sensing of the nearby target. With the aim of minimizing the total AAV's energy consumption, we optimize the duration of training and data phase and the bit allocation coupled with the offloading ratio under the constraints for offloading and sensing. Via simulations, the superiority of the proposed algorithm is verified to be pronounced with the sufficient mission time and the high sensing performance constraint.

This letter aims to provide sensing capabilities for a potential eavesdropper, while simultaneously enabling the secure communications with the legitimate users in a cell-free multipleinput multiple-output system with limited fronthaul links. In order to maximize the sensing performance, the joint design of fronthaul compression and beamforming is proposed considering the constraints on the finite fronthaul-capacity links and the maximum power along with the worst-case secrecy rate requirements. To this end, we propose an algorithmic solution based on the minorization-maximization method and semidefinite programming relaxation techniques, whose performance superiority is verified via simulations compared to the reference schemes such as distributed sensing and random beamforming.

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 nonterrestrial network (NTN) solution to provide high-traffic and low-latency data transfer services 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 the multiple low-Earth orbit (LEO) satellites, we developed the LR-FHSS transceiver to improve system efficiency, which is the first attempt in real satellite communication systems using LR-FHSS. Moreover, as an extension of our previous work with perfect synchronization, we applied 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 soft-output-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 field-programmable 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 sixth-generation (6G) networks.

In this correspondence, we propose a joint mechanical and electrical adjustment of intelligent reflecting surface (IRS) for the performance improvements of low-earth orbit (LEO) satellite multiple-input multiple-output (MIMO) communications. In particular, we construct a three-dimensional (3D) MIMO channel model for the mechanically-tilted IRS in general deployment, and consider two types of scenarios with and without the direct path of LEO-ground user link due to the orbital flight. With the aim of maximizing the end-to-end performance, we jointly optimize tilting angle and phase shift of IRS along with the transceiver beamforming, whose performance superiority is verified via simulations with the Orbcomm LEO satellite using a real orbit data.

In this correspondence, we propose an unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) system, where a full-duplex UAV equipped with uniform planar array (UPA) is adopted as a base station for the multiuser downlink communications, while sensing and jamming a passive ground eavesdropper. The goal of this work is to maximize the sum secrecy rate of ground users subject to the constraints of sensing accuracy and UAV's operational capability by jointly optimizing the transceiver beamforming and UAV's trajectory. To this end, we develop the algorithmic solution based on block coordinate descent (BCD) and semidefinite programming (SDP) relaxation techniques, whose performance is verified via simulations indicating its efficacy in improving communication security with the sufficient mission period.

In this correspondence, we propose to use an intelligent reflective surface (IRS) installed on unmanned aerial vehicle (UAV), referred to as aerial IRS (AIRS), for vehicular networks, where simultaneous wireless information and power transfer (SWIPT) receivers to concurrently allow information decoding (ID) and energy harvesting (EH) are equipped at the battery-limited vehicles. For efficiently supporting the multiple moving vehicles, we adopt rate-splitting multiple access (RSMA) technique. With the aim of maximizing the sum rate of vehicles, we jointly optimize trajectory and phase shift design of AIRS, transmit power and rate allocation for RSMA along with power splitting ratio for SWIPT implementation. Via simulations, the superior performances of the proposed algorithm are validated compared to the conventional partial optimizations.