To enable a globally integrated non-terrestrial network (NTN), the interconnection of heterogeneous low-earth orbit (LEO) satellite constellations via geostationary (GEO) relays is paramount. A significant challenge in this architecture lies in the dynamic allocation of hybrid free-space optical (FSO) and radio frequency (RF) links for the GEO-LEO interconnection. Conventional heuristic approaches that prioritize either instantaneous traffic demand or link visibility would be inadequate, as they fail to balance these conflicting metrics, resulting in performance bottlenecks and inefficient resource utilization. To resolve this allocation challenge, we propose a novel two-stage quasi-optimal control framework that maximizes the network-wide traffic accommodation rate. Our approach employs Binary Particle Swarm Optimization (BPSO) to solve the combinatorial FSO/RF link assignment problem, followed by convex optimization for RF bandwidth allocation. Simulation results demonstrate that our method consistently outperforms conventional approaches across various network loads, significantly improving the traffic accommodation rate and overall data throughput, thereby validating its effectiveness for dynamic resource management in hybrid satellite networks.

Low Earth Orbit (LEO) satellite constellation systems are expected to be integrated with terrestrial networks for future communication services over wide areas. For real-time applications, direct data relay between users is effective to minimize the propagation delay via LEO satellites, where multi-beam control is an essential function in LEO satellites to efficiently allocate beam resources over the areas. However, no previous works considered the satellite’s buffer limitations and the differences in throughput between uplink (UL) and downlink (DL) which caused queuing delays. This paper proposes a coordinated UL/DL multi-beam scheduling to minimize the end-to-end latency of data relay by considering the available buffer space of the satellite and variations in UL/DL throughput due to satellite movement. An optimization problem is formulated for the scheduling design to minimize the end-to-end latency. We demonstrate with simulation results that the proposed scheduling method reduces the latency by 16.0%, compared to the conventional methods.

The integration of satellite, aerial, and terrestrial networks in Satellite–Air–Ground Integrated Networks (SAGIN) enhances connectivity but also introduces new vulnerabilities to multi-layer jamming attacks. These attacks—originating from space-based, air-based, and ground-based sources—exhibit diverse signal characteristics, resource constraints, and durations, posing significant threats to communication performance and system security. A single mitigation technique is often insufficient to address these varied challenges effectively. In this paper, we propose a multi-layer adaptive jamming mitigation framework that dynamically adapts to the type of jamming encountered, with a particular focus on threats targeting Low Earth orbit (LEO) satellites within SAGIN. We evaluate a range of mitigation techniques and analyze their performance across different jamming scenarios. Our results show that tailored mitigation strategies are essential in SAGIN to achieve higher Signal-to-Noise Ratio (SNR) and lower Bit Error Rate (BER), highlighting the importance of jamming-aware defenses for enhancing the resilience and security of SAGIN systems.

For future network applications, ubiquitous connections and real-time cloud offloading are important paradigms for enabling important services. To achieve these goals, satellite networks, Free-Space Optical (FSO) communications, and Mobile Edge Computing (MEC) are key technologies. This paper proposes an efficient latency based task offloading strategy in a multi-tier Space-Air-Ground Integrated Network (SAGIN) with MEC and FSO communications. We consider a static deployment of ground users in Yamagata prefecture, Japan, offloading computational tasks to High Altitude Platforms (HAPs) and a Low Earth Orbit (LEO) satellite constellation. In this system, elevation-based FSO visibility and atmospheric attenuation can affect transmission latency, while server workload can impact computation latency. We design a hierarchical clustering-based framework and evaluate it alongside two other baseline approaches in terms of latency performance. Results show that our clustering-based task assignment achieves lower average latency and better load balancing, highlighting its potential for real-time edge-enabled FSO systems.

The use cases of satellite communications are rapidly expanding towards 6 G technology. Long propagation distances and dynamic changes in the network topology create an unstable environment with greater delays and disruptions than those of terrestrial networks. Delay/disruption-tolerant networks (DTN) have been developed to address these challenges. Since the nearearth satellite network is a scheduled network, contact plans can be created beforhand. Contact graph routing (CGR) is a contact-plan-based method used to determine the shortest path to deliver a bundle, a data unit of a DTN, to its destination. However, the conventional contact graph-based bundle transmission control methods do not consider the transfer order or bundle generation from multiple sources, such as observation satellites, ground, and marine users. Therefore, the bundle delivery ratio will decrease in future satellite networks, in which traffic of various sizes and acceptable delays are expected to flow in. In this study, we propose a bundle transmission control method for a multi-source DTN that considers the bundle variety. The simulation evaluation results demonstrated that the proposed method achieved a higher bundle delivery ratio than the conventional methods.

The scale of data centers has increased significantly in recent years, with their energy demands adversely impacting the environment. Consequently, distributed green data centers, equipped powered renewable energy, have gained considerable attention. However, conventional optical fibers installations for such data centers incur high costs and face locations constraints. Therefore, this study explores the use of optical satellite communications for distributed green data centers. Efficient task allocation is crucial to minimize service delays. However, task transmission time depends on satellite-ground link performance, while processing time is affected by the energy at data centers. Additionally, the non-linear relationship between the server per-formance and power consumption highlights the inefficiency, task allocation without future-aware considerations. To address this, we propose a method for task allocation and processing performance control that minimizes service delays through predictions of task generation, link performance, and power generation. In the proposed method, we formulate an optimization problem based on prediction data and find its solution by exploration. Simulations demonstrate that the proposed method significantly reduces tasks transmission and processing times.

Free-space optical (FSO) communication is a promising technology in satellite communications, offering numerous advantages, such as high capacity utilizing wide bandwidth, license-free operation, and high security. Despite these advantages, FSO communications are faced with challenges owing to significant attenuation in the atmosphere. Consequently, hybrid FSO/radio frequency (RF) space-air-ground integrated networks (SAGINs) with stable RF communications have garnered considerable attention. One key area that remains underdeveloped within SAGIN is the cooperative data transmission between satellites and high-altitude platform stations. To address this gap, this study proposed a coverage area control scheme for multiple downlink routing in a hybrid FSO/RF SAGIN to effectively utilize limited RF resources. Furthermore, we developed an algorithm to streamline the search for optimal control parameters within the network. Based on simulation results, integrating flexible bandwidth control with coverage area control improves spectral efficiency. Furthermore, our findings highlight the critical role of accurate traffic prediction in enhancing the performance of coverage area control mechanisms.

Low Earth Orbit (LEO) satellite communication systems are gaining prominence for providing extensive coverage in 6G networks. LEO satellites face challenges owing to the high path loss caused by long distances, thereby necessitating high-power or highly directional antennas. Traditional solutions, such as phased and reflective arrays, fail to meet the size, weight, and price/power (SWaP) requirements, as well as beam flexibility. To address these limitations, this study explores the potential of integrating intelligent reflecting surface (IRS) technology with LEO satellites, offering better SWaP compliance and beam control. Multi-beamforming technology is crucial for LEO satellite communications, and we propose a frequency prism technique to address this requirement. We introduce the delay adjustable-IRS (DA-IRS) as a solution to realize the frequency prism by controlling the time delay for incident wave reflections. Additionally, we model a control strategy to optimize the frequency utilization efficiency to address uneven throughput demands within the coverage area. The proposed approach is assessed through simulations. These findings demonstrate the viability of our model for meeting the key requirements of LEO satellite communication systems.

Recently, the utilization of non-terrestrial networks (NTN), including satellite communications, has expanded substantially. This expansion has resulted in heightened demands for improved communication performance from NTNs. Among the various solutions, inter-satellite optical wireless communication has emerged as a promising technology for enhancing communication capabilities. However, the complexity of optical pointing technology poses a significant challenge. Existing research often assumes limitations in establishing connections between satellites in intersecting orbits with high relative velocities, instead relying on links in the same and adjacent orbits that are comparatively easier to establish. This study bridges the gap in the existing research by conducting a quantitative comparison of the same, adjacent, and intersecting orbital connections. The primary objective of this comparison is to investigate the potential for enhancing communication stability and efficiency by transitioning from multi-hop information transmission using satellites on adjacent orbits to connections within the same orbit by utilizing intersecting-orbit satellites. Verification results show that, under certain conditions, communication stability and efficiency can be improved by using intersecting-orbit satellites.

This paper presents a framework for real-time concealed weapon detection (CWD) on 3D radar images for walk-through screening systems. The walk-through screening system aims to ensure security in crowded areas by performing CWD on walking persons, hence it requires an accurate and real-time detection approach. To ensure accuracy, a weapon needs to be detected irrespective of its 3D orientation, thus we use the 3D radar images as detection input. For achieving real-time, we reformulate classic U-Net based segmentation networks to perform 3D detection tasks. Our 3D segmentation network predicts peak-shaped probability map, instead of voxel-wise masks, to enable position inference by elementary peak detection operation on the predicted map. In the peak-shaped probability map, the peak marks the weapon’s position. So, weapon detection task translates to peak detection on the probability map. A Gaussian function is used to model weapons in the probability map. We experimentally validate our approach on realistic 3D radar images obtained from a walk-through weapon screening system prototype. Extensive ablation studies verify the effectiveness of our proposed approach over existing conventional approaches. The experimental results demonstrate that our proposed approach can perform accurate and real-time CWD, thus making it suitable for practical applications of walk-through screening.

This paper presents a novel algorithm to reduce the complexity for Direction of Arrival estimation in an outdoor multipath scenario. The proposed Adaptive Search Space Quantization (ASSQ) algorithm is able to decrease the number of beamforming vectors compared to state of the art and thus matrix multiplications, achieving the same estimation accuracy. The idea of the algorithm is to adaptively decrease the search space and to increase the quantization level in multiple steps. We present numerical results from exhaustive and limited search using a three dimensional channel model, achieving an estimation accuracy of less than 1 m with a probability of 98%.

Massive MIMO with small-cells are attracting much attention as a promising scenario for 5G. In those deployment scenarios, it is considered that base stations (BSs) are located at heights below 10 m such as on a lamppost or an exterior wall of a building's second floor. However, the throughput performance in such scenarios has not been sufficiently evaluated yet, since the current widely used channel models such as the 3GPP 3D channel model is only applicable for BS heights at 10 m and above. This paper investigates the throughput performance of a downlink Massive MIMO small-cell located at heights below 10 m based on new realistic channel model parameters. The new channel model parameters have been obtained from a measurement campaign conducted at such BS heights using a carrier frequency of 3.7 GHz with 250 MHz bandwidth. We also compare the Massive MIMO performance with the conventional channel model parameters from 3GPP's 3D urban-microcell (3D-UMi) scenario. The computer simulation results show that the average cell throughput with one of the new channel models (called "Open Square") is 94% higher compared to 3D-UMi. This is because the parameters of the Open Square scenario have a lower path-loss and a larger angular spread of departure than the conventional. Therefore, the new channel model parameters can contribute to improve accuracy in design and evaluation of Massive MIMO small-cell network towards the 5G deployment.

Leaky coaxial cable (LCX) is widely used for wireless communication systems as an antenna for a linear-cell, which covers long and shallow areas. Since one LCX is usually utilized as one antenna, more than one LCX is required to configure a multi-input multi-output (MIMO) system. It means it is costly and space-consuming. To resolve these problems, we proposed a novel MIMO method for LCX. In this paper, we propose the method to utilize one composite cable, which consists of a pair of LCXs with different radiation characteristics, to configure a 4 × 4 MIMO channel. The measurement results confirmed that the proposed composite cable can realize a good channel condition for 4 × 4 MIMO transmission even if it is put in an anechoic chamber where no reflection path exists. On the other hand, the results also confirmed that it has good channel condition even if the spacing between a pair of LCX is as small as 2cm for the 5GHz band. Therefore the proposed system can reduce the space requirement for MIMO deployment for wireless application over linear-cell environments to cope with the high rapid increase of consumer electronics devices.

Leaky coaxial cables (LCX) have been widely used as antennas to form linear service areas for radio communication systems. Such services of linear cells have been deployed inside tunnels, along railways, and so on. Usually, one LCX is utilized as one antenna. Therefore it requires more than one LCX to configure an multi-input multi-output (MIMO) system. In this paper, we propose a MIMO system using single LCX, which can be utilized as two antennas. When different RF transmit signals are fed to each end of the proposed cable, single LCX can work as two antennas. To confirm the feasibility of the proposed MIMO system, we conduct experiments to measure the characteristics of 2 × 2 MIMO channel using single LCX. The results confirm that our proposed 2×2 MIMO channel using single LCX can realize a good channel condition for MIMO transmission even within a highly correlated propagation condition. The proposed MIMO system using LCX will release the space requirement and reduce the cost of system for configuration of LCX MIMO system especially with large number of LCXs. It benefits the design and configuration of LCX-MIMO system for many scenarios of linear-cell.

With opening up of the TV white spaces for opportunistic access, designing a flexible physical layer (PHY) scheme has become an important focus for cognitive radio (CR) systems. Two possible PHY design solutions proposed are: generalized frequency division multiplexing (GFDM) and interference avoidance by partitioned frequency and time domain transmission (IA-PFT). Both of these methods extend the orthogonal frequency division multiplexing (OFDM) scheme to be applicable as a flexible CR PHY solution in a fragmented spectrum. In GFDM, introduction of pulse shaping filters reduces the out-of-band radiation of the opportunistic signals into the frequency band of the incumbent users; while in IA-PFT, simultaneous cancellation carrier insertion and time windowing technique suppress spectral leakage into the incumbent band of operation. In this paper, these two different approaches are compared in terms of interference suppression, transmission performance and processing complexity.

This paper presents an interference avoidance transmission technique for dynamic spectrum access (DSA). Generally, OFDM transmission induces high out-of-band emission due to the side-lobes of the transmitted sub-carriers. For a DSA based OFDM system, it is thus important to reduce the out-of-band emission. Aiming at providing high suppression effect for an interference avoidance notch, an interference avoidance transmission by partitioned frequency- and time-domain processing (IA-PFT) is proposed. IA-PFT is configured by a partitioned combination of the CC processing in the frequency domain and windowing processing in the time domain. Computer simulations show that IA-PFT reduces the interference power spectrum density under the condition of a highly prioritized wireless microphone in white space. Moreover, it is shown that IA-PFT realizes transmission performance and PAPR performance as much as those attained by conventional interference avoidance methods.

In this paper, we propose novel criterion and novel power control schemes based on the capacity conservation ratio (CCR) by taking the Rayleigh fading effect into account using theoretical analysis. The CCR is defined as the ratio of the decreased capacity in the spectrum sharing to the original capacity of a system. We utilize the CCR as a novel metric for protecting a primary system (PS) from large capacity degradation. The proposed power control schemes based on CCR are divided into two kinds of power control scheme; an exact power control scheme and a simplified power control scheme. We analytically evaluate the performance of the simplified power control scheme and compare it with that of the other. We find that the simplified power control scheme offers sufficient PS protection performance without high computational cost.

Experimental system of IP/sup 2/ mobility management was designed and implemented in order to confirm feasibility of the protocol and identify its bottlenecks. The experimental system is based on a prototype implementation of IP/sup 2/ mobility management which runs on PC servers. Series of experiments were conducted in order to check validity of protocol sequence and impact of load status on system performance. From the feasibility tests results, it was confirmed that there was no fundamental error in IP/sup 2/ mobility management and it could interwork with other IP protocols. Throughout the bottleneck tests, degradation in performance due to limitation of the transport: mechanism was observed when the MN had relatively large number of active peers. Experimental results indicated that alternate mechanism to improve reliability of signalling messages was highly needed. From user-plane viewpoint, additional processing that is specific to IP/sup 2/ mobility management put negligible effect on the packet forwarding delay of the AR.

In conventional trellis coded modulation (TCM), a higher-ary modulation scheme combining with a convolutional code is employed not to expand the transmitted bandwidth. This forces the system to be attended by signal constellation expansion and increasing the average signal power. As solutions to avoid signal constellation expansion, TCM systems using totally overlapped signal sets (TO-TCM and RU-TCM) were proposed. These schemes can realize a coded modulation system with no signal constellation expansion and achieve more coding gain than conventional TCM. However, a problem that the systems with totally overlapped signal sets might be catastrophic has been remained. The authors propose a novel TCM system using partially overlapped signal sets of nonequiprobable signaling (PO-TCM-NE). This scheme employs the partially overlapped signal constellation to control increasing signal points, and to avoid catastrophic error propagation. The nonequiprobable signaling is employed to reduce average signal power. Coding gain of proposed PO-TCM-NE is considerably improved; in consequence the average signal power is reduced much lower than other TCM systems with equiprobable signaling.