Search Results (69)

Network slicing allows a single 5G New Radio (NR) carrier to serve services with significantly different reliability targets. However, the cost of each slice in spectral and energy terms, once it is realized as a concrete uplink, is rarely measured. This paper reports a link-level evaluation of the joint energy efficiency (EE) and spectral efficiency (SE) trade-off in a multi-slice 5G-NR uplink in which enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC) each receive a distinct Physical Uplink Shared Channel (PUSCH) configuration matched to a block error rate (BLER) target of 10⁻³, 10⁻⁵, and 10⁻¹, respectively. Using a 3GPP-compliant simulator built on the MATLAB 5G Toolbox (R2026a), 1440 operating points across different frequency bands, FR1 and FR2, propagation delay profiles, transmit power levels, and user distances from the gNB were evaluated. Each point is evaluated twice, with and without a co-channel fixed-service (FS) interferer. Every slice exhibits an interior energy-optimal transmit power; the three slices occupy clearly separated regions of the EE–SE plane, ordered eMBB above mMTC above URLLC. Finally, FS interference reshapes the trade-off through one mechanism with very different consequences per slice: eMBB, which earns its rate from 256-QAM, loses approximately a quarter of its peak throughput and roughly half of its peak EE under line-of-sight (LoS), while mMTC is the most resilient and URLLC shows the sharpest qualitative change, with its energy optimum migrating by approximately 16 dB. Therefore, the energy-optimal operating point is not a fixed property of the band, distance, and slice, but a function of the interference that the link actually sees; thus, slice-aware uplink power control must also be interference-aware. Full article

The rapid development of large model-driven agent applications, such as digital assistants and robots, requires 6G radio access networks (RAN) to deliver enhanced flexibility, adaptability, and low-latency capabilities. However, the existing RAN user plane (UP) architecture suffers from coarse decoupling granularity and significant cross-layer functional redundancy. These limitations severely hinder the on-demand orchestration and dynamic reconfiguration required by heterogeneous agent services. To address these challenges, this paper proposes a ComBERT-driven service-based RAN UP decoupling method, specifically targeting the functional coupling and redundancy between the PDCP and RLC sublayers. First, we develop a domain-specific language model, ComBERT, by pre-training a BERT model on a 3GPP protocol corpus and fine-tuning it on text-matching tasks to deeply comprehend protocol semantics. Subsequently, ComBERT is utilized to extract semantic features from UP functional components, employing a sliding window mechanism to overcome truncation in lengthy protocol texts and using cosine similarity to measure functional relevance. Finally, a threshold-based fusion algorithm is designed to identify and merge cross-layer redundant functions, thereby forming independent service units with distinct responsibilities. These fused units serve as the basic building blocks for scenario-specific orchestration. Simulation results demonstrate that the proposed method reduces the number of UP components by 12.5%, 18.7%, and 18.2% in eMBB, URLLC, and mMTC scenarios, respectively. Simultaneously, it decreases average processing delays by 7.9%, 10.2%, and 11.0% across these respective scenarios. Ultimately, this approach effectively improves the lightweight deployment, processing efficiency, and reconfiguration capabilities of the service-based UP, providing a crucial foundation for on-demand service orchestration in 6G networks tailored to agent services. Full article

Wearable robots that can support balance and prevent falls hold great promise to increase the longevity and quality of life of the older population. However, a lack of understanding of human–robot dynamic interactions and users’ reactions to robot interventions can limit the functionality and usability of these robots. A wearable lower-limb robot was developed to study different strategies to proactively prevent falls during obstacle navigation and to investigate human–robot interactions and users’ reactions to different intervention parameters. A novel non-anthropomorphic architecture was designed for robot legs to allow the direct modulation of foot-placement position in the sagittal plane, using only a single active degree of freedom per leg. Three participants completed a series of walking trials wearing the robot, with different levels of robot intervention. The developed robot was able to successfully modify users’ stride length (e.g., 6–12% and 7.5–20% change in step length for 12 Nm robot hip flexion and extension torques, respectively) in the desired direction, indicating the possibility for assisted balance during obstacle navigation through foot-placement modulation. The measurements show that users’ reactions to the robot intervention is subject-specific and time-varying but, in all cases, plays a considerable role in the final movement trajectory. Controllers of the balance assistance robots must take into account the user’s personalized response to different intervention parameters, to improve functionality, efficiency and user comfort. Full article

The deployment of 5G technology represents a significant advancement in telecommunications, offering unprecedented speed, connectivity, and innovation opportunities. However, this progress comes at a significant cost for Public Land Mobile Network (PLMN) operators, who face challenges in meeting high Quality of Service (QoS) standards for optimal user experience while ensuring appropriate levels of security. This paper addresses the joint optimization of latency and resource consumption under security constraints within 5G networks, focusing on the Packet Data Unit (PDU) session path to ensure compliance with security and latency requirements. We propose an innovative approach in which access control rules are distributed across User Plane Functions (UPFs) in the network. The optimization problem has been formulated as a mixed integer linear programming (MILP) problem that aims to minimize round-trip latency and operational costs for PLMN operators. We evaluate the performance of our model using a discrete event network simulator (NS3). The simulation results demonstrate the effectiveness of our approach, particularly in scenarios with stringent latency requirements. Latency is reduced, and a lower session drop rate is maintained, especially in conditions of network congestion. These findings emphasize the importance of considering both QoS and security in the design of next-generation 5G networks. Full article

Indoor visible light communication (VLC) has attracted increasing attention as a promising wireless access technology because of its large unlicensed bandwidth and dual functionality of illumination and data transmission. However, practical VLC systems are vulnerable to line-of-sight (LoS) blockage caused by user mobility, human shadowing, and indoor obstacles, which may degrade link reliability and service continuity. Although hybrid VLC/RF networks can improve robustness by using RF transmission as a backup link, excessive RF fallback under severe optical blockage may overload the bandwidth-limited RF interface and reduce the service quality of RF-associated users. To address this issue, this paper investigates a risk-aware illumination-constrained resource allocation scheme for hybrid VLC/RF indoor networks under random optical blockage. A unified system model is developed by considering Lambertian optical propagation, random optical blockage, RF backup transmission, and working-plane illumination constraints. Based on this model, a joint user association and power allocation problem is formulated under QoS, transmit-power, and illumination requirements. The proposed scheme evaluates VLC service utility under blockage uncertainty, controls RF fallback to avoid excessive backup-link loading, allocates VLC/RF transmission power, and performs illumination feasibility adjustment to preserve the required lighting level. Simulation results show that, under severe blockage conditions, the proposed scheme reduces the outage probability to approximately 0.26, compared with 0.68 for VLC-only transmission and 0.47 for threshold-based VLC/RF switching. For a 20-user network, the proposed scheme achieves an average sum rate of approximately 277 Mbps, maintains a 100% illumination compliance ratio, and achieves higher energy efficiency than the benchmark schemes. Further RF backup analysis shows that the proposed scheme can maintain the service quality of RF-associated users by avoiding excessive RF fallback. These results demonstrate the effectiveness of the proposed framework for reliable and illumination-feasible hybrid VLC/RF indoor communication. Full article

The 5G Wireless and Wireline Convergence (5G-WWC) standards introduce critical network functions—notably the Access Gateway Function (AGF) and the User Plane Function (UPF)—to enable unified wired and wireless access through a single 5G core. However, deploying and integrating these functions across heterogeneous programmable hardware platforms remains a significant open architectural challenge. This paper presents a configurable integration framework that orchestrates AGF and UPF workloads on heterogeneous programmable data planes, specifically NVIDIA BlueField-2 Data Processing Units (DPUs) and P4-based switches. Unlike traditional, hardware-specific implementations, the framework provides a unified control plane that dynamically manages AGF-only, UPF-only, or Combined AGF/UPF deployments. A hardware abstraction mechanism decouples the control logic from pipeline-specific details, enabling the same control plane to drive different underlying hardware without modification. A Generic Flow Rule interface standardises communication between the control plane and each user-plane backend, while a merged DPU pipeline for Combined AGF/UPF eliminates the redundant GTP-U encapsulation and decapsulation steps inherent in a naively cascaded design. Experiments on NVIDIA BlueField-2 DPUs achieve near-100 Gbps throughput across all three TR-470 scenarios (AGF-only, UPF-only, and Collocated AGF/UPF). The Combined AGF/UPF configuration exhibits lower end-to-end latency than the separated AGF + UPF configuration, confirming both the feasibility and the efficiency of the proposed framework for next-generation high-performance programmable networks. Full article

Understanding the variations in the bidirectional reflectance distribution function (BRDF) and albedo over snow surface under various conditions is important for interpreting the surface–atmosphere processes of the cryosphere, and the kernel-driven model is among the most popular methods to obtain this information for a comprehensive analysis. Recently, the RossThick-LiSparseReciprocal-Snow (RTLSRS) model was developed to better characterize the anisotropic reflectance of snow and shows strong potential for integration into operational remote sensing algorithms for snow BRDF/albedo retrieval. To comprehensively test the ability of the RTLSRS model to reproduce snow reflectance, the fitting accuracy to different multi-angular data derived from ground, tower, aircraft, and satellite platforms across the full optical wavelength range were demonstrated in this study. Special attention in this study was directed to analyzing the model performance under extreme illumination observation geometries, particularly with respect to the retrieval accuracy and stability under large Solar Zenith Angles (SZAs) and different Relative Azimuth Angles (RAAs). The model performance for silt-polluted snow surface with different concentrations is also assessed to provide necessary supplementation, relative to “pure” snow surface in the previous study. The main findings of this study are summarized as follows: (1) The RTLSRS model exhibits strong robustness under various SZAs; even when the SZA exceeds 80°, the model maintains high accuracy in BRDF reconstruction, with root mean square error (RMSE) values below 0.05. (2) The model also demonstrates satisfactory inversion capability when observations deviate from the principal plane (PP); the model can achieve fitting accuracy with R² approaching 0.5 and RMSE below 0.05 for MODIS data. (3) In the spectral range below 1300 nm, the RTLSRS model effectively reconstructs the scattering characteristics of snow surfaces with light impurity levels (<20 g/0.5 m²). (4) The spectral shape of snow reflectance remains consistent across different view zenith angles (VZAs) in general. However, the variations caused by different SZAs can be as high as 38.49% and such SZA-induced difference can result in WSA estimation discrepancy of up to 63.43%. This comprehensive assessment further affirms and demonstrates the applicability of the RTLSRS model for the first time in fitting observations across different platforms with various optical wavelengths and geometries, and provides an improved understanding to analyze BRDF variations for the user community. Full article

The rollout of 5G Standalone networks introduces unprecedented flexibility and performance through service-based architecture (SBA), virtualization, open APIs, and network slicing, while simultaneously expanding the attack surface across control, user, and cross-plane interfaces. This article provides a systematic, vulnerability-prioritized, selective characterization of the current state of weaknesses specific to the 5G control and user planes and transparent risk scoring. Using a PRISMA-aligned methodology, vulnerabilities are mapped explicitly to 3GPP network functions and interfaces (e.g., AMF, SMF, UPF; N2, N4, SBA APIs) and categorized by operational evidence level ranging from theoretical analysis to documented live-network exploitation. A normalized criticality scoring model integrates likelihood, impact, exploitability, and CVSS-derived severity. The analysis shows that control-plane signaling floods, PFCP misuse, and container escapes stand out as the most pressing risks. It also exposes how little attention has been given to securing the user plane and strengthening slice isolation. The paper wraps up with clear, evidence-based hardening priorities for each plane, along with research areas that matter for today’s 5G networks and the shift toward 6G. Full article

Driven by technological innovation, service diversification, and the evolution and defects of current networks, the 6th-generation (6G) network architecture is lacking in research. One of the challenges in this research is that the architectural design should take into account multiple factors: customers, operators, and vendors. For service-oriented and network-oriented design requirements, this article proposes a data-driven distributed autonomous architecture (DDAA) for 6G with a three-layer four-plane logical hierarchy. The architecture is simplified as four network function units (NFUs), the interaction among which is carried via dual-bus interfaces, i.e., the service-based interface (SBI) and data transmission interface (DTI). In addition, it is user data-centric and rendered as distributed autonomous domains (ADs) with different scales to better adapt to customized services. Different transition stages from the 5th generation (5G) to 6G are discussed. Network simplification evaluation is further provided by going through several signaling procedures of the 3rd-generation partnership project (3GPP), inspiring advanced research and subsequent standardization of the 6G network architecture. Full article

Background: Children with spastic hand impairments resulting from cerebral palsy or neuromuscular disorders often exhibit a restricted range of motion and diminished functional use. Rehabilitation devices that assist joint mobilization can enhance therapeutic outcomes, yet few solutions target pediatric populations. Methods: This study aimed to design, implement, and preliminarily evaluate a biomechanical device tailored to promote flexo-extension, radial–ulnar deviation, and supination movements in spastic hands of school-aged children. A prototype combining a motor-driven actuation system, adjustable wrist and finger supports, and a MATLAB-based graphical user interface was developed. Two participants (aged 8 and 10) with clinically diagnosed spastic hemiparesis underwent 25-minute sessions over 15 consecutive days. Joint angles were recorded before and after each session using an electro-goniometer. Data normality was assessed via the Shapiro–Wilk test, and pre–post differences were analyzed with the Wilcoxon signed-rank test (α = 0.05). Results: Both participants demonstrated consistent increases in their active range of motion across all measured planes. Median flexo-extension improved by 12.5° (p = 0.001), ulnar–radial deviation by 7.3° (p = 0.002), and supination by 9.1° (p = 0.001). No adverse events occurred, and device tolerance remained high throughout the intervention. Conclusions: The device facilitated statistically significant enhancements in joint mobility in a small pediatric cohort, supporting its feasibility and safety in spastic hand rehabilitation. These preliminary findings warrant larger controlled trials to confirm the device’s efficacy, optimize treatment protocols, and assess its long-term functional benefits. Full article

This paper presents a non-intrusive method for estimating the distance between a camera and a human subject using a monocular vision system and statistically derived interpupillary distance (IPD) values. The proposed approach eliminates the need for individual calibration by utilizing average IPD values based on biological sex, enabling accurate, scalable distance estimation for diverse users. The algorithm, implemented in Python 3.12.11 using the MediaPipe Face Mesh framework, extracts pupil coordinates from facial images and calculates IPD in pixels. A sixth-degree polynomial calibration function, derived from controlled experiments using a uniaxial displacement system, maps pixel-based IPD to real-world distances across three intervals (20–80 cm, 80–160 cm, and 160–240 cm). Additionally, a geometric correction is applied to compensate for in-plane facial rotation. Experimental validation with 26 participants (15 males, 11 females) demonstrates the method’s robustness and accuracy, as confirmed by relative error analysis against ground truth measurements obtained with a Bosch GLM120C laser distance meter. Males exhibited lower relative errors across the intervals (3.87%, 4.75%, and 5.53%), while females recorded higher mean relative errors (6.0%, 6.7%, and 7.27%). The results confirm the feasibility of the proposed method for real-time applications in human–computer interaction, augmented reality, and camera-based proximity sensing. Full article

Herein, we report a USB-powered VR-HMD prototype integrated with our 33 mm aperture varifocal liquid lenses and electronic drive components, all assembled in a conventional VR-HMD form-factor. In this volumetric-display-based VR system, a sequence of virtual images are rapidly flash-projected at different plane depths in front of the observer and are synchronized with the correct accommodations provided by the varifocal lenses for depth-matched focusing at chosen sweep frequency. This projection mechanism aids in resolving the VAC that is present in conventional fixed-depth VR. Additionally, this system can address refractive error corrections like myopia and hyperopia for prescription users and do not require any eye-tracking systems. We experimentally demonstrate these lenses can vibrate up to frequencies approaching 100 Hz and report the frequency response of the varifocal lenses and their focal characteristics in real time as a function of the drive frequency. When integrated with the prototype’s 120 fps VR display system, these lenses produce a net diopter change of 2.3 D at a sweep frequency of 45 Hz while operating at ~70% of its maximum actuation voltage. The components add a total weight of around 50 g to the off-the-shelf VR set, making it a cost-effective but lightweight minimal solution. Full article

This paper presents the development, modeling, and analysis of an autonomous active ankle prosthesis with two degrees of freedom (2-DoF), designed to reproduce movements in the sagittal (dorsiflexion/plantarflexion) and frontal (inversion/eversion) planes in order to enhance the stability and naturalness of the user’s gait. Unlike most commercial prostheses, which typically feature only one active degree of freedom, the proposed device combines a lightweight mechanical design, a screw drive with a stepper motor, and a microcontroller-based control system. The prototype was developed using CAD modeling in SolidWorks 2024, followed by dynamic modeling and finite element analysis (FEA). The simulation results confirmed the achievement of physiological angular ranges of ±20–22 deg. in both planes, with stable kinematic behavior and minimal vertical displacements. According to the FEA data, the maximum von Mises stress (1.49 × 10⁸ N/m²) and deformation values remained within elastic limits under typical loading conditions, though cyclic fatigue and impact energy absorption were not experimentally validated and are planned for future work. The safety factor was estimated at ~3.3, indicating structural robustness. While sensor feedback and motor dynamics were idealized in the simulation, future work will address real-time uncertainties such as sensor noise and ground contact variability. The developed design enables precise, energy-efficient, and adaptive motion control, with an estimated average power consumption in the range of 7–9 W and an operational runtime exceeding 3 h per charge using a standard 18,650 cell pack. These results highlight the system’s potential for real-world locomotion on uneven surfaces. This research contributes to the advancement of affordable and functionally autonomous prostheses for individuals with transtibial amputation. Full article

Private 5G networks offer exclusive, secure wireless communication with full control deployments for many clients, such as enterprises and campuses. In these networks, edge computing plays a critical role by hosting both application services and the User Plane Functions (UPFs) as containerized workloads close to end devices, reducing latency and ensuring stringent Quality of Service (QoS). However, edge environments often face resource constraints and unpredictable failures such as network disruptions or hardware malfunctions, which can severely affect the reliability of the network. In addition, existing redundancy-based UPF resilience strategies, which maintain standby instances, incur substantial overheads and degrade resource efficiency and scalability for the applications. To address this issue, this study introduces a novel design that enables quick detection of UPF failures and two failover mechanisms to restore failed UPF instances either within the cluster hosting the failed UPF or across multiple clusters, depending on that cluster’s resource availability and health. We implemented and evaluated our proposed approach on a Kubernetes-based testbed, and the results demonstrate that our approach reduces UPF redeployment time by up to 37% compared to baseline methods and lowers system cost by up to 50% under high-reliability requirements compared to traditional redundancy-based failover methods. These findings demonstrate that our design can serve as a complementary solution alongside traditional resilience strategies, offering a particularly cost-effective and resource-efficient alternative for edge computing and other constrained environments. 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