Search Results (17)

The Mobile Reliable Opportunistic Routing (MROR) protocol improves data-forwarding reliability in Cognitive Radio Sensor Networks (CRSNs) through mobility-aware virtual contention groups and handover zoning. However, its heuristic decision logic is difficult to optimize under highly dynamic spectrum access and random node mobility. To address this limitation, we present DRL-MROR, a refined routing framework that incorporates deep reinforcement learning (DRL) to enable intelligent and adaptive forwarding decisions. In DRL-MROR, the secondary users (SUs) act as autonomous agents that observe local state information, including primary-user activity, link quality, residual energy, and neighbor-mobility patterns. Each agent learns a forwarding policy through a Deep Q-Network (DQN) optimized for long-term network utility in terms of throughput, delay, and energy efficiency. We formulate routing as a Markov Decision Process (MDP) and use experience replay with prioritized sampling to improve learning stability and convergence. The DQN used at each node is intentionally lightweight, requiring 5514 trainable parameters, about 21.5 kB of weight storage in 32-bit precision, and approximately 5.4k multiply-accumulate operations per inference, which supports practical deployment on edge-capable CRSN nodes. Extensive simulations show that DRL-MROR outperforms the original MROR protocol and representative AI-based routing baselines such as AIRoute under diverse operating conditions. The results indicate gains of up to 38% in throughput, 42% in goodput, a 29% reduction in energy consumed per packet, and an approximately 18% improvement in network lifetime, while maintaining high route stability and fairness. DRL-MROR also reduces control overhead by about 30% and average end-to-end delay by up to 32%, maintaining strong performance even under elevated PU activity and higher node mobility. These results show that augmenting opportunistic routing with lightweight DRL can substantially improve adaptability and efficiency in next-generation IoT-oriented CRSNs. Full article

5G technology represents a transformative shift in mobile communications, delivering improved ultra-low latency, data throughput, and the capacity to support huge device connectivity, surpassing the capabilities of LTE systems. As global telecommunication operators shift toward widespread 5G implementation, ensuring optimal network performance and intelligent resource management has become increasingly obvious. To address these challenges, this study explored the role of advanced clustering methods in optimizing cellular networks under heterogeneous and dynamic conditions. A systematic literature review (SLR) was conducted by analyzing 40 peer-reviewed and non-peer-reviewed studies selected from an initial collection of 500 papers retrieved from the Semantic Scholar Open Research Corpus. This review examines a diversity of clustering approaches, including spectral clustering with Bayesian non-parametric models and K-means, density-based clustering such as DBSCAN, and deep representation-based methods like Differential Evolution Memetic Clustering (DEMC) and Domain Adaptive Neighborhood Clustering via Entropy Optimization (DANCE). Key performance outcomes reported across studies include anomaly detection accuracy of up to 98.8%, delivery rate improvements of up to 89.4%, and handover prediction accuracy improvements of approximately 43%, particularly when clustering techniques are combined with machine learning models. In addition to summarizing their effectiveness, this review highlights methodological trends in clustering parameters, mechanisms, experimental setups, and quality metrics. The findings suggest that advanced clustering models play a crucial role in intelligent spectrum sensing, adaptive mobility management, and efficient resource allocation, thereby contributing meaningfully to the development of intelligent 5G/6G mobile network infrastructures. Full article

Close-proximity operations play a crucial role in emerging mission concepts, such as Active Debris Removal or small celestial bodies exploration. When approaching a non-cooperative target, the increased risk of collisions and reduced reliance on ground intervention necessitate autonomous on-board relative pose (position and attitude) estimation. Although navigation strategies relying on monocular cameras which operate in the visible (VIS) spectrum have been extensively studied and tested in flight for navigation applications, their accuracy is heavily related to the target’s illumination conditions, thus limiting their applicability range. The novelty of the paper is the introduction of a thermal-infrared (TIR) camera to complement the VIS one to mitigate the aforementioned issues. The primary goal of this work is to evaluate the enhancement in navigation accuracy and robustness by performing VIS-TIR data fusion within an Extended Kalman Filter (EKF) and to assess the performance of such navigation strategy in challenging illumination scenarios. The proposed navigation architecture is tightly coupled, leveraging correspondences between a known uncooperative target and feature points extracted from multispectral images. Furthermore, handover from one camera to the other is introduced to enable seamlessly operations across both spectra while prioritizing the most significant measurement sources. The pipeline is tested on Tango spacecraft synthetically generated VIS and TIR images. A performance assessment is carried out through numerical simulations considering different illumination conditions. Our results demonstrate that a combined VIS-TIR navigation strategy effectively enhances operational robustness and flexibility compared to traditional VIS-only navigation chains. Full article

With the increase in user density, it is a challenging problem to achieve higher energy efficiency in vehicle-to-everything (V2X) networks, where frequent handovers occur as users continuously pass through dense cell boundaries. In this paper, we investigate this energy efficiency problem in a highly dense V2X network. To alleviate inter-cell interference and reduce unnecessary handovers, we propose a user-centric network architecture and utilize the coordinated multiple point (CoMP) transmission scheme to enable multiple roadside access points (APs) simultaneously to service one mobile vehicle. Moreover, non-orthogonal multiple access (NOMA) is adopted to enable multiple users to multiplex within one sub-channel and improve system spectrum reuse. Accordingly, the energy efficiency optimization problem is formulated as system achievable rate per joule, with the constraints of the AP transmit power budget, vehicle minimum rate requirements, and the maximum number of CoMP APs serving each vehicle. To solve the optimization problem, a semi-dynamic CoMP AP clustering algorithm is proposed to select a group of CoMP APs to serve a vehicle user by considering the vehicle–AP channel coefficients and the vehicle user’s achievable energy efficiency. Then, with the selected CoMP AP clusters, a bidirectional selection algorithm is applied via NOMA to select multiple vehicle users multiplexing within one sub-channel and perform sub-channel power allocation. Numerical simulations are presented to verify the effectiveness of the proposed algorithms, and the results show the improvements offered by the proposed algorithms compared to current benchmarks. Full article

The deployment of non-terrestrial networks (NTNs) is envisioned to achieve global coverage for 6G and beyond. In addition to space nodes, aerial NTN nodes such as high-altitude platform stations (HAPSs) and rotary-wing unmanned aerial vehicles (UAVs) could be deployed, based on the intended coverage and operational altitude requirements. NTN nodes have the potential to support both wireless access and backhauling. While the onboard base station provides wireless access for the end users, the backhauling link connects the airborne/space-borne base station to the core network. With its high data transmission capability comparable to fiber optics and its ability to operate in the interference-free optical spectrum, free space optical (FSO) communication is ideally suited to backhauling requirements in NTNs. In this paper, we present a comprehensive tutorial on airborne FSO backhauling. We first delve into the fundamentals of FSO signal transmission and discuss aspects such as geometrical loss, atmospheric attenuation, turbulence-induced fading, and pointing errors, all of which are critical for determining received signal levels and related link budget calculations. Then, we discuss the requirements of airborne backhaul system architectures, based on use cases. While single-layer backhaul systems are sufficient for providing coverage in rural areas, multi-layer designs are typically required to establish connectivity in urban areas, where line of sight (LoS) links are harder to maintain. We review physical layer design principles for FSO-based airborne links, discussing both intensity modulation/direct detection (IM/DD) and coherent modulation/coherent demodulation (CM/CD). Another critical design criteria for airborne backhauling is self-sustainability, which is further discussed in our paper. We conclude the paper by discussing current challenges and future research directions. In this context, we discuss reconfigurable intelligent surfaces (RIS) and spatial division multiplexing (SDM), for improved performance and an extended transmission range. We emphasize the importance of advanced handover techniques and scalability issues for practical implementation. We also highlight the growing role of artificial intelligence/machine learning (AI/ML) and their potential applications in the design and optimization of future FSO-based NTNs. Full article

Fifth Generation (5G) signals using the millimeter wave (mmWave) spectrums are highly vulnerable to blockage due to rapid variations in channel link quality. This can cause the devices or User Equipment (UE) to suffer from connection failure. In a dual connectivity (DC) network, the channel’s intermittency issues were partially solved by maintaining the UE’s connectivity to primary (LTE advanced stations) and secondary (5G mmWave stations) simultaneously. Even though the dual-connected network performs excellently in maintaining connectivity, its performance drops significantly due to the inefficient handover from one 5G mmWave station to another. The situation worsens when UE travels a long distance in a highly dense obstacle environment, which requires multiple ineffective handovers that eventually lead to performance degradation. This research aimed to propose an Adaptive TTT Handover (ATH) mechanism that deals with unpredictable 5G mmWave wireless channel behaviors that are highly intermittent. An adaptive algorithm was developed to automatically adjust the handover control parameters, such as Time-to-Trigger (TTT), based on the current state of channel condition measured by the Signal-to-Interference-Noise Ratio (SINR). The developed algorithm was tested under a 5G mmWave statistical channel model to represent a time-varying channel matrix that includes fading and the Doppler effect. The performance of the proposed handover mechanism was analyzed and evaluated in terms of handover probability, latency, and throughput by using the Network Simulator 3 tool. The comparative simulation result shows that the proposed adaptive handover mechanism performs excellently compared to conventional handovers and other enhancement techniques. Full article

Visible light communication (VLC) has the advantages of rich spectrum resources, endogenous safety and anti-electromagnetic interference, so the application of VLC to the Industrial Internet of Things is one of its current development directions. Due to the limited coverage of light emitting diodes (LEDs), dense placement is often required in industrial manufacturing scenarios. However, mobile users will face frequent handover between these LEDs, and reliable reception of signals on mobile terminals requires receivers with a large detection area. In this paper, we used a cubic receiver to increase the detection area, which is more conducive to signal reception than a single photo-detector plane receiver. Then we studied the handover scheme for a cubic receiver to ensure the performance of the communication link. We also rotated the receiver to further improve signal quality and obtain the optimal rotation angles using a genetic algorithm with low complexity. The results show that a cubic receiver has a better received signal quality than a plane receiver, and rotation can enhance the signal quality more. In addition, it can be seen that the handover for the cubic receiver depends not only on the distance, but also on its structure, angle and position. Considering these factors jointly when performing a handover, users can connect to LEDs, which provide the best quality of service, and system communication performance can be improved. Full article

In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a large number of CC algorithm variations have been developed to accommodate various network environments. The fifth-generation (5G) mobile network presents a new challenge for the implementation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic flows. In contrast to the pre-5G networks that operate in the sub-6 GHz bands, the implementation of TCP CC algorithms in 5G mmWave communications will be further compromised with high variations in channel quality and susceptibility to blockages due to high penetration losses and atmospheric absorptions. These challenges will be particularly present in environments such as sensor networks and Internet of Things (IoT) applications. To alleviate these challenges, this paper provides an overview of the most popular single-flow and multy-flow TCP CC algorithms used in pre-5G networks. The related work on the previous examinations of TCP CC algorithm performance in 5G networks is further presented. A possible implementation of TCP CC algorithms is thoroughly analysed with respect to the specificities of 5G networks, such as the usage of high frequencies in the mmWave spectrum, the frequent horizontal and vertical handovers, the implementation of the 5G core network, the usage of beamforming and data buffering, the exploitation of edge computing, and the constantly transmitted always-on signals. Moreover, the capabilities of machine learning technique implementations for the improvement of TCPs CC performance have been presented last, with a discussion on future research opportunities that can contribute to the improvement of TCP CC implementation in 5G networks. This survey paper can serve as the basis for the development of novel solutions that will ensure the reliable implementation of TCP CC in different usage scenarios of 5G networks. Full article

Light Fidelity (LiFi) is a new candidate for wireless networking that utilizes the visible light spectrum and exploits the existing lighting infrastructure in the form of light-emitting diodes (LEDs). It provides point-to-point and point-to-multipoint communication on a bidirectional channel at very high data rates. However, the LiFi has small coverage, and its optical gain is closely related to the receiver’s directionality vis-à-vis the transmitter, therefore it can experience frequent service outages. To provide reliable coverage, the LiFi is integrated with other networking technologies such as wireless fidelity (WiFi) thus forming a hybrid system. The hybrid LiFi/WiFi system faces many challenges including but not limited to seamless integration with the WiFi, support for mobility, handover management, resource sharing, and load balancing. The existing literature has addressed one or the other aspect of the issues facing LiFi systems. There are limited free source tools available to holistically address these challenges in a scalable manner. To this end, we have developed an open-source simulation framework based on the network simulator 3 (ns-3), which realizes critical aspects of the LiFi wireless network. Our developed ns-3 LiFi framework provides a fully functional AP equipped with the physical layer and medium access control (MAC), a mobility model for the user device, and integration between LiFi and WiFi with a handover facility. Simulation results are produced to demonstrate the mobility and handover capabilities, and the performance gains from the LiFi-WiFi hybrid system in terms of packet delay, throughput, packet drop ratio (PDR), and fairness between users. The source code of the framework is made available for the use of the research community. Full article

This paper proposes a cooperation-assisted spectrum handover (CASH) scheme in vehicular ad hoc networks (VANETs). In CASH, each vehicle uses cognitive radio technology to collect the surrounding spectrum information, computes the stability of the spectrum, exchanges neighbor information by vehicle-to-vehicle collaboration technology, and then executes a partial prescan mechanism to reduce the handover delay. The proposed method can improve the spectrum utilization, shorten the delay time of the spectrum handover, and reduce the total number of handovers. Finally, the simulation results show that the proposed method outperforms other existing schemes. In spectrum utilization, CASH is about 20% better than that of the traditional full scan method. In average scan time, the time of CASH is about 5 times less than the time of the traditional full scan method. In total number of handovers, CASH improves the performance of the full scan scheme by 33%. Full article

(1) Background: Sepsis is the leading cause of maternal death in 11–15% of women worldwide. This emphasises the importance of administrating timely and appropriate antibiotic therapy to women with sepsis. We aimed to evaluate the appropriateness of antimicrobial prescribing in women diagnosed with peripartum sepsis. (2) Method: A prospective observational cohort study in a single Scottish health region with 12,233 annual live births. Data were collected on women diagnosed with sepsis in the peripartum period using physical and electronic medical records, drug Kardex^® (medication administration) and ward handover records. (3) Results: A sepsis diagnosis was concluded in 89 of the 2690 pregnancy cases reviewed, with a median hospital stay of four days. Good overall adherence to the local guidelines for the empiric antimicrobial treatment of sepsis was observed. Group B Streptococcus was associated with 20.8% of maternal sepsis cases, whilst in 60% of clinical specimens tested no causative pathogen was isolated. (4) Conclusion: The lack of specific and sensitive clinical markers for sepsis, coupled with their inconsistent clinical application to inform diagnosis, hindered effective antimicrobial stewardship. This was further exacerbated by the lack of positive culture isolates from clinical specimens, which meant that patients were often continued on broader-spectrum empiric treatment. Full article

With an ever increasing demand for data, better and efficient spectrum operation has become crucial in cellular networks. In this paper, we present a detailed survey of various resource allocation schemes that have been considered for the cellular network’s operation in the unlicensed spectrum. The key channel access mechanisms for cellular network’s operation in the unlicensed bands are discussed. The various channel selection techniques are explored and their operation explained. The prime issue of fairness between cellular and Wi-Fi networks is discussed, along with suitable resource allocation techniques that help in achieving this fairness. We analyze the coverage, capacity, and impact of coordination in LTE-U systems. Furthermore, we study and discuss the impact and discussed the impact of various traffic type, environments, latency, handover, and scenarios on LTE-U’s performance. The new upcoming 5G New Radio and MulteFire is briefly described along with some of the critical aspects of LTE-U which require further research. Full article

This paper aims to unlock the unlicensed band potential in realizing the Industry 4.0 communication goals of the Fifth-Generation (5G) and beyond. New Radio in the Unlicensed band (NR-U) is a new NR Release 16 mode of operation that has the capability to offer the necessary technology for cellular operators to integrate the unlicensed spectrum into 5G networks. NR-U enables both uplink and downlink operation in unlicensed bands, supporting 5G advanced features of ultra-high-speed, high bandwidth, low latency, and improvement in the reliability of wireless communications, which is essential to address massive-scale and highly-diverse future industrial networks. This paper highlights NR-U as a next-generation communication technology for smart industrial network communication and discusses the technology trends adopted by 5G in support of the Industry 4.0 revolution. However, due to operation in the shared/unlicensed spectrum, NR-U possesses several regulatory and coexistence challenges, limiting its application for operationally intensive environments such as manufacturing, supply chain, transportation systems, and energy. Thus, we discuss the significant challenges and potential solution approaches such as shared maximum channel occupancy time (MCOT), handover skipping, the self-organized network (SON), the adaptive back-off mechanism, and the multi-domain coexistence approach to overcome the unlicensed/shared band challenges and boost the realization of NR-U technology in mission-critical industrial applications. Further, we highlight the role of machine learning in providing the necessary intelligence and adaptation mechanisms for the realization of industrial 5G communication goals. Full article

With the arrival of 5G, the wireless network will be provided with abundant spectrum resources, massive data transmissions and low latency communications, which makes Vehicle-to-Everything applications possible. However, VANETs always accompany with frequent network topology changes due to the highly mobile feature of vehicles. As a result, the network performance will be affected by the frequent handover. In this paper, a seamless handover scheme is proposed where the Software-Defined Networking (SDN) and Mobile Edge Computing (MEC) technologies are employed to adapt to the dynamic topology change in VANETs. The introduction of SDN provides a global view of network topology and centralized control, which enables a stable transmission layer connection when a handover takes place, so that the upper layer performance is not influenced by the network changes. By employing MEC server, the data are cached in advance before a handover happens, so that the vehicle can restore normal communication faster. In order to confirm the superiority of our proposal, computer simulations are conducted from different aspects. The results show that our proposal can significantly improve the network performance when a handover happens. Full article

Femtocell technology has been gaining popularity as an inexpensive means of enhancing cellular coverage and capacity. However, under co-channel deployment—expected to be commonplace due to high spectrum costs—femtocells may incur harmful interference to existing macrocells, and vice versa. To alleviate this problem, This paper proposes a new architecture called HandOver-driven Femtocell Interference Management (HO-FIM) that offloads macrocells by handing macrocell users over to “hybrid-access” femtocells that allow the access of both subscribed and unsubscribed users. This use of handovers adds a new degree-of-freedom for solving the interference problem, thus overcoming the capacity limit of the existing approaches that exploit radio resource coordination only. A new challenge associated with this approach is how to minimize handovers while reaching a desired system condition due to the inevitable service interruptions that accompany handovers. This paper proposes to overcome this challenge by triggering handovers only when needed and, once triggered, to find an optimal sequence to reach a target system condition with minimal handovers. This paper designs a greedy per-user control algorithm that has a fine control granularity and thus enables convergence to an optimal solution. The in-depth evaluation of the paper shows that HO-FIM improves the service quality of both macro- and femtocell users; in an example simulation scenario, HO-FIM is shown to improve the signal-to-interference and noise ratios (SINRs) of macro- and femtocell users by up to 23.3 and 2.9 dB, respectively, on average, compared to the case of no handovers. Full article