Search Results (33)

With the increasing scale of low Earth orbit (LEO) satellite networks, leveraging non−terrestrial networks (NTNs) to complement terrestrial networks (TNs) has become a critical issue. In this paper, we investigate the issue of handover satellite selection between multiple terrestrial terminal groups (TTGs). To support effective handover decision-making, we propose a long short-term memory (LSTM)-network-based traffic prediction mechanism based on historical traffic data. Building on these predictions, we formulate the handover strategy as a Markov Decision Process (MDP) and propose an attention-enhanced rainbow-DQN-based joint traffic prediction and handover design framework (ARTHF) by jointly considering the satellite switching frequency, communication quality, and satellite load. Simulation results demonstrate that our approach significantly outperforms existing methods in terms of the handover efficiency, service quality, and load balancing across satellites. Full article

The evolution of 3GPP non-terrestrial networks (NTNs) is enabling new avenues for broadband connectivity via satellite, especially within the scope of 5G. The parallel rise in satellite mega-constellations has further fueled efforts toward ubiquitous global Internet access. This convergence has fostered collaboration between mobile network operators and satellite providers, allowing the former to leverage mature space infrastructure and the latter to integrate with terrestrial mobile standards. However, integrating these technologies presents significant architectural challenges. This study investigates 5G NTN architectures using satellite mega-constellations, focusing on transparent architectures where Starlink is employed to relay the backhaul, midhaul, and new radio (NR) links. The performance of these architectures is assessed through a testbed utilizing OpenAirInterface (OAI) and Open5GS, which collects key user-experience metrics such as round-trip time (RTT) and jitter when pinging the User Plane Function (UPF) in the 5G core (5GC). Results show that backhaul and midhaul relays maintain delays of 50–60 ms, while NR relays incur delays exceeding one second due to traffic overload introduced by the RFSimulator tool, which is indispensable to transmit the NR signal over Starlink. These findings suggest that while transparent architectures provide valuable insights and utility, regenerative architectures are essential for addressing current time issues and fully realizing the capabilities of space-based broadband services. Full article

The integration of reconfigurable intelligent surfaces (RISs) with non-terrestrial networks (NTNs), particularly those enabled by unmanned aerial vehicles (UAVs) or drone-based platforms, has emerged as a transformative approach to enhance 6G connectivity in high-mobility scenarios. UAV-assisted NTNs offer flexible deployment, dynamic altitude control, and rapid network reconfiguration, making them ideal candidates for RIS-based signal optimization. However, the high mobility of UAVs and their three-dimensional trajectory dynamics introduce unique challenges in maintaining robust, low-latency links and seamless handovers. This paper presents a comprehensive performance analysis of RIS-assisted UAV-based NTNs, focusing on optimizing RIS phase shifts to maximize the signal-to-interference-plus-noise ratio (SINR), throughput, energy efficiency, and reliability under UAV mobility constraints. A joint optimization framework is proposed that accounts for UAV path loss, aerial shadowing, interference, and user mobility patterns, tailored specifically for aerial communication networks. Extensive simulations are conducted across various UAV operation scenarios, including urban air corridors, rural surveillance routes, drone swarms, emergency response, and aerial delivery systems. The results reveal that RIS deployment significantly enhances the SINR and throughput while navigating energy and latency trade-offs in real time. These findings offer vital insights for deploying RIS-enhanced aerial networks in 6G, supporting mission-critical drone applications and next-generation autonomous systems. Full article

With the advancement of 5G-Advanced Non-Terrestrial Network (5G-A NTN) mobile communication technologies, direct satellite connectivity for mobile devices has been increasingly adopted. In the highly dynamic environment of low-Earth-orbit (LEO) satellite communications, the synchronization of satellite–ground signals remains a critical challenge. In this study, a Doppler frequency-shift estimation method applicable to high-mobility LEO scenarios is proposed, without reliance on the Global Navigation Satellite System (GNSS). Rapid access to satellite systems by mobile devices is enabled without the need for additional time–frequency synchronization infrastructure. The generation mechanism of satellite–ground Doppler frequency shifts is analyzed, and a relationship between satellite velocity and beam-pointing direction is established. Based on this relationship, a Doppler frequency-shift estimation method, referred to as DFS-BP (Doppler frequency-shift estimation using beam pointing), is developed. The effects of Earth’s latitude and satellite orbital inclination are systematically investigated and optimized. Through simulation, the estimation performance under varying minimum satellite elevation angles and terminal geographic locations is evaluated. The algorithm may provide a novel solution for Doppler frequency-shift compensation in Non-Terrestrial Networks (NTNs). Full article

The rapid evolution of wireless communications has introduced new possibilities for the digital transformation of maritime operations. As 5G begins to take shape in selected nearshore and port environments, the forthcoming 6G promises to unlock transformative capabilities across the entire maritime domain, integrating Terrestrial/Non-Terrestrial Networks (TN/NTN) to form a space-air-ground-sea-underwater system. This paper presents a comprehensive review of how 6G-enabling technologies can be adapted to address the unique challenges of Maritime Communication Networks (MCNs). We begin by outlining a reference architecture for heterogeneous MCNs and reviewing the limitations of existing 5G deployments at sea. We then explore the key technical advancements introduced by 6G and map them to maritime use cases such as fleet coordination, just-in-time port logistics, and low-latency emergency response. Furthermore, the critical Artificial Intelligence/Machine Learning (AI/ML) concepts and algorithms are described to highlight their potential in optimizing maritime functionalities. Finally, we propose a set of resource optimization scenarios, including dynamic spectrum allocation, energy-efficient communications and edge offloading in MCNs, and discuss how AI/ML and learning-based methods can offer scalable, adaptive solutions. By bridging the gap between emerging 6G capabilities and practical maritime requirements, this paper highlights the role of intelligent, resilient, and globally connected networks in shaping the future of maritime communications. Full article

Maritime relay communication has emerged as a critical application scenario for non-terrestrial networks (NTNs), providing beyond-line-of-sight (BLOS) connectivity for offshore terminals. Unlike terrestrial environments, the complex marine propagation conditions lead to signal instability. To enhance the robustness of maritime two-way relay networks (TWRNs), we propose a novel physical-layer network coding (PNC) scheme based on block Markov superposition transmission (BMST). The proposed scheme introduces a novel co-design framework that achieves dual breakthroughs: (1) robust error correction via BMST’s spatially coupled coding architecture and (2) spectral efficiency maximization through PNC’s spatial-domain signal superposition. Moreover, we develop a decoding–computing (DC) algorithm that sequentially performs iterative decoding followed by computing. Compared to the computing–decoding (CD) algorithm, the proposed DC algorithm mitigates useful information loss at relay nodes, achieving a 2.9 dB coding gain at a bit error rate (BER) of ${10}^{-5}$. Owing to the DC algorithm’s dual-layer decoding architecture, we can further improve the overall system performance through targeted optimization of either the code rate or memory size for communication sides with poor channel conditions, yielding an extra 0.2 dB gain at a BER of ${10}^{-5}$ compared to non-optimized configurations. The simulation results demonstrate that the proposed scheme significantly enhances maritime relay communication performance under harsh oceanic channel conditions while providing actionable insights for optimizing next-generation maritime communication system designs. Full article

This study investigates the optimization of satellite constellations for Low-Power, Wide-Area Network (LPWAN)-based Internet of Things (IoT) communications in Very Low Earth Orbit (VLEO) at 200 km and 300 km altitudes and Low Earth Orbit (LEO) at 600km using a Genetic Algorithm (GA). Focusing on three LPWAN technologies—LoRa, Narrowband IoT (NB-IoT), and Mioty—we evaluate their performance in terms of revisit time, data transmission volume, and economic efficiency. Results indicate that a 300 km VLEO constellation with LoRa achieves the shortest average revisit time and requires the fewest satellites, offering notable cost benefits. NB-IoT provides the highest data transmission volume. Mioty demonstrates strong scalability but necessitates a larger satellite count. These findings highlight the potential of VLEO satellites, particularly at 300 km, combined with LPWAN solutions for efficient and scalable IoT Non-Terrestrial Network (IoT-NTN) applications. Future work will explore multi-altitude simulations and hybrid LPWAN integration for further optimization. Full article

In high-mobility non-terrestrial networks (NTN), the reference signal received power (RSRP)-based handover (RBH) mechanism is often unsuitable due to its limitations in handling dynamic satellite movements. RSRP, a key metric in cellular networks, measures the received power of reference signals from a base station or satellite and is widely used for handover decision-making. However, in NTN environments, the high mobility of satellites causes frequent RSRP fluctuations, making RBH ineffective in managing handovers, often leading to excessive ping-pong handovers and a high handover failure rate. To address this challenge, we propose an innovative approach called location-based handover with particle filter and reinforcement learning (LBH-PRL). This approach integrates a particle filter to estimate the distance between user equipment (UE) and NTN satellites, combined with reinforcement learning (RL), to dynamically adjust hysteresis, time-to-trigger (TTT), and handover decisions to better adapt to the mobility characteristics of NTN. Unlike the location-based handover (LBH) approach, LBH-PRL introduces adaptive parameter tuning based on environmental dynamics, significantly improving handover decision-making robustness and adaptability, thereby reducing unnecessary handovers. Simulation results demonstrate that the proposed LBH-PRL approach significantly outperforms conventional LBH and RBH mechanisms in key performance metrics, including reducing the average number of handovers, lowering the ping-pong rate, and minimizing the handover failure rate. These improvements highlight the effectiveness of LBH-PRL in enhancing handover efficiency and service continuity in NTN environments, providing a robust solution for intelligent mobility management in high-mobility NTN scenarios. Full article

Ubiquitous connectivity is envisioned through the integration of terrestrial (TNs) and non-terrestrial networks (NTNs). However, NTNs face multiple routing and Quality of Service (QoS) provisioning challenges due to the mobility of network nodes. Distributed Software-Defined Networking (SDN) combined with Multi-Agent Deep Reinforcement Learning (MADRL) is widely used to introduce programmability and intelligent Traffic Engineering (TE) in TNs, yet applying DRL to NTNs is hindered by frequently changing state sizes, model scalability, and coordination issues. This paper introduces 3DQR, a novel TE framework that combines hierarchical multi-controller SDN, hierarchical MADRL based on Graph Neural Networks (GNNs), and network topology predictions for QoS path provisioning, effective load distribution, and flow rejection minimisation in future 3D networks. To enhance SDN scalability, introduced are metrics and path operations abstractions to facilitate domain agents coordination by the global agent. To the best of the authors’ knowledge, 3DQR is the first routing scheme to integrate MADRL and GNNs for optimising centralised routing and path allocation in SDN-based 3D mobile networks. The evaluations show up to a 14% reduction in flow rejection rate, a 50% improvement in traffic distribution, and effective QoS class prioritisation compared to baseline techniques. 3DQR also exhibits strong transfer capabilities, giving consistent performance gains in previously unseen environments. Full article

With the development of 5G new radio (NR) applications in high-speed scenarios, such as 5G non-terrestrial networks (NTN), the Doppler shift in the systems is significant. In this paper, an estimation scheme for frequency offset with large range in orthogonal frequency division multiplexing (OFDM) systems is proposed. The proposed scheme firstly takes advantage of the $2\pi$-periodicity of the phase offset between two pilot OFDM symbols to estimate a set of candidate frequency offsets. It then uses the autocorrelation of the pilot sequence to determine the final estimated frequency offset. This method allows for a large estimation range, independent of the symbol gap between the two pilot OFDM symbols. Moreover, the low-complexity implementation of the scheme is provided. The simulation results based on 5G NR physical uplink shared channel (PUSCH) show the effectiveness of the proposed scheme in both single-user and multi-user scenarios, where various Doppler shifts and numbers of configured resource blocks (RB) are considered. The simulation results also show that the proposed frequency-domain method outperforms the conventional time-domain method with additional computation complexity. Full article

In the next-generation communication systems, multiple access (MA) will play a crucial role in achieving high throughput to support future-oriented services. Recently, rate-splitting multiple access (RSMA) has received much attention from both academia and industry due to its ability to flexibly mitigate inter-user interference in a broad range of interference regimes. Further, with the growing emphasis on spectrum resource utilization, integrated sensing and communication (ISAC) technology, which improves spectrum efficiency by merging communication and radar signals, is expected to be one of the key candidate technologies for the sixth-generation (6G) wireless networks. In this paper, we first investigate the evolution of existing MA techniques and basic principles of RSMA-assisted ISAC systems. Moreover, to make the future RSMA-assisted ISAC systems, we highlight prime technologies of 6G such as non-terrestrial networks (NTN), reconfigurable intelligent surfaces (RIS), millimeter wave (mmWave) and terahertz (THz) technologies, and vehicular-to-everything (V2X), along with the main technical challenges and potential benefits to pave the way for RSMA-assisted ISAC systems. Full article

This article examines the transformative potential of integrating reconfigurable intelligent surfaces (RISs) into sixth-generation (6G) wireless non-terrestrial networks (NTNs). The focus is on the RIS’s capability to address diverse user requirements, including secure data transmission, power efficiency, extended coverage, and enhanced data rates. The paper delves into the synergy between RISs and NTNs, emphasizing key components like multiple-input multiple-output (MIMO) systems and advanced radio communications. Additionally, it highlights the crucial role of artificial intelligence (AI) and machine learning (ML) in optimizing RIS-based beamforming to solve scientific and engineering challenges while ensuring energy efficiency and sustainability in NTN operations. By positioning RISs as a key enabler in shaping the future of wireless communication systems, this research underscores their significance in unlocking the full potential of NTNs and advancing next-generation wireless communications. This paper contributes valuable insights and projections for future research directions, highlighting RISs’ potential to revolutionize NTNs for 6G technologies. Full article

Toward the vision of seamless global connectivity in the 6G era, the non-terrestrial network (NTN) in space-air-ground integrated networks (SAGINs) network architecture is one of the highly promising solutions. From the perspective of relay nodes, NTN includes satellite nodes and space-based platform nodes. As a resource management technology in satellite communication, beam-hopping has garnered significant attention from researchers due to its effectiveness in ad-dressing the disparity between offered capacities and uneven terrestrial traffic demands. Recognizing that the larger beams offer broader coverage but the smaller ones provide better an-ti-interference capabilities and higher throughput, this paper introduces an adaptive cluster-ing-based approach. It provides large, medium, and small user beams to target ground users. The proposed algorithm aims to minimize total system latency and enhance system throughput. Sim-ulation results show that employing the proposed algorithm in the baseline model results in a 3.44% increase in system throughput and a 35.5% reduction in system latency. Furthermore, simulation results based on alternative models indicate that while the proposed algorithm may lead to a slight decrease in system throughput, it brings significant improvements in system latency. Full article

The deployment of fifth-generation (5G) wireless networks has already laid the ground-work for futuristic smart cities but along with this, it has also triggered the rapid growth of a wide range of applications, for example, the Internet of Everything (IoE), online gaming, extended/virtual reality (XR/VR), telemedicine, cloud computing, and others, which require ultra-low latency, ubiquitous coverage, higher data rates, extreme device density, ultra-high capacity, energy efficiency, and better reliability. Moreover, the predicted explosive surge in mobile traffic until 2030 along with envisioned potential use-cases/scenarios in a smart city context will far exceed the capabilities for which 5G was designed. Therefore, there is a need to harness the 6th Generation (6G) capabilities, which will not only meet the stringent requirements of smart megacities but can also open up a new range of potential applications. Other crucial concerns that need to be addressed are related to network security, data privacy, interoperability, the digital divide, and other integration issues. In this article, we examine current and emerging trends for the implementation of 6G in the smart city arena. Firstly, we give an inclusive and comprehensive review of potential 6th Generation (6G) mobile communication technologies that can find potential use in smart cities. The discussion of each technology also covers its potential benefits, challenges and future research direction. Secondly, we also explore promising smart city applications that will use these 6G technologies, such as, smart grids, smart healthcare, smart waste management, etc. In the conclusion part, we have also highlighted challenges and suggestions for possible future research directions. So, in a single paper, we have attempted to provide a wider perspective on 6G-enabled smart cities by including both the potential 6G technologies and their smart city applications. This paper will help readers gain a holistic view to ascertain the benefits, opportunities and applications that 6G technology can bring to meet the diverse, massive and futuristic requirements of smart cities. Full article

The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP’s roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era. Full article