Search Results (737)

The complexity and uncertainty of the marine environment pose significant challenges to the stability and coverage of communication links. Due to the limited coverage range of traditional onshore base stations (BSs) in marine environments, relay technology has become an essential approach to extending communication coverage. However, the rapid variations in marine wireless channels and the complexity of hydrological conditions make it extremely difficult to obtain accurate channel state information (CSI). In particular, dynamic environmental factors such as waves, tides and wind speed cause channel parameters to fluctuate significantly over time. To address these challenges, this paper proposes a cooperative communication strategy based on ships and designs a novel channel modeling method to accurately capture the characteristics of marine wireless channels. Furthermore, a deep learning-based optimization scheme is proposed, which formulates the relay selection problem as a spatiotemporal classification task. By integrating the spatial positions of candidate relays and their communication conditions, the proposed scheme enables real-time selection of the optimal relay while evaluating link connectivity probabilities under hydrological influences. Simulation results confirm that the proposed method achieves high accuracy even in rapidly changing marine environments. Full article

The collection and real-time transmission of emergency environmental information are crucial for rapidly assessing the on-site situation of sudden disasters and responding promptly. However, the acquisition of emergency environmental information, particularly its seamless transmission, faces significant challenges under complex terrain and limited ground communication. This paper utilizes sensors, line-of-sight communication with unmanned aerial vehicles (UAVs), and LoRa long-distance communication to establish an integrated emergency environmental monitoring system that combines real-time monitoring, UAV-mounted LoRa gateway relaying, and backend data analysis. This system achieves real-time acquisition, seamless transmission, storage management, and visualization of environmental emergency information. First, a portable emergency environmental monitoring device was developed to collect and transmit environmental factor data. Second, a UAV-mounted LoRa gateway was designed to extend the data transmission coverage, ensuring seamless communication. Finally, multiple field experiments were conducted to evaluate the system’s performance. The experimental results indicate that the system possesses reliable capabilities for emergency data collection and transmission in complex environments, providing new technical solutions and practical support for developing and applying emergency environmental monitoring systems. Full article

Unmanned aerial vehicle (UAV)-based wireless sensor networks (WSNs) hold great promise for supporting ground-based sensors due to the mobility of UAVs and the ease of establishing line-of-sight links. UAV-based WSNs equipped with mobile edge computing (MEC) servers effectively mitigate challenges associated with long-distance transmission and the limited coverage of edge base stations (BSs), emerging as a powerful paradigm for both communication and computing services. Furthermore, incorporating simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) as passive relays significantly enhances the propagation environment and service quality of UAV-based WSNs. However, most existing studies place STAR-RISs in fixed positions, ignoring the flexibility of STAR-RISs. Some other studies equip UAVs with STAR-RISs, and UAVs act as flight carriers, ignoring the computing and caching capabilities of UAVs. To address these limitations, we propose an energy-efficient aerial STAR-RIS-aided computing offloading and content caching framework, where we formulate an energy consumption minimization problem to jointly optimize content caching decisions, computing offloading decisions, UAV hovering positions, and STAR-RIS passive beamforming. Given the non-convex nature of this problem, we decompose it into a content caching decision subproblem, a computing offloading decision subproblem, a hovering position subproblem, and a STAR-RIS resource allocation subproblem. We propose a deep reinforcement learning (DRL)–successive convex approximation (SCA) combined algorithm to iteratively achieve near-optimal solutions with low complexity. The numerical results demonstrate that the proposed framework effectively utilizes resources in UAV-based WSNs and significantly reduces overall system energy consumption. Full article

Magnetic induction (MI)-operated wireless sensor networks (WSNs), due to their similar performance in air, underwater, and underground mediums, are rapidly emerging networks that offer a wide range of applications, including mine prevention, power grid maintenance, underground pipeline monitoring, and upstream oil monitoring. MI-based wireless underground sensor networks (WUSNs), utilizing small antenna coils, offer a viable solution by providing consistent channel conditions. The cross-layer protocols address the specific challenges of WUSNs, leading to improved network performance and enhanced operational capabilities in real-world applications. This work proposes a distributed cross-layer solution, leveraging the hybrid marine predator naked mole rat algorithm (MPNMRA) for MI-operated WUSNs. The solution, called DECMN (distributed energy-throughput efficient cross-layer network using MPNMRA), is designed to optimize the MI communication channels, MI relay coils (MI waveguide), and MI waveguide with 3D coils to fulfill quality of service (QoS) parameters, while achieving energy savings and throughput gains. DECMN utilizes the interactions between various layers to develop cross-layer protocols based on MPNMRA. Simulation results demonstrate the effectiveness of DECMN, offering energy savings, increased throughput, and reliable transmissions within the performance limits. Full article

In this paper, we consider a three-node free space optical (FSO) decode-and-forward (DF) cooperative network. The relay is not connected to a permanent power supply and relies solely on the optical energy harvested (EH) from the source node. This energy is accumulated in an energy buffer in order to enable the relay–destination communications. Moreover, buffer-aided (BA) relaying is considered where the relay is equipped with a data buffer for storing the incoming packets. For such networks, we propose a relaying protocol that delineates the roles of the source and the EH BA relay in each time slot. We develop a Markov chain framework for capturing the dynamics of the data and energy buffers. We derive the transition probabilities between the states of the Markov chain after discretizing the continuous-value energy buffer allowing for the evaluation of the analytical performance of the considered system. A numerical analysis is also presented over a turbulence-induced gamma–gamma fading channel highlighting the impacts of the data rate threshold levels, relay position, relay transmit power and propagation conditions on the achievable performance levels. Results validate the accuracy of the theoretical analysis and demonstrate significant reductions in the network outage, especially when the relay’s transmit level is appropriately selected. Full article

In this study, we present a dual-hop decode-and-forward relaying-based free-space optical (FSO) communication system. We consider utilizing simultaneous lightwave information and power transfer (SLIPT) with a time-splitting technique at the relay, where the direct current component of the received optical signal is harvested as a transmit power for the relay. It is assumed that the FSO links experience a Malaga turbulence channel with pointing errors. In order to evaluate the performance of the proposed communication system, closed-form expressions for outage probability, ergodic capacity, average bit error rate, and throughput are derived. Additionally, to analyze the physical layer security of the proposed system, closed-form expressions for secrecy outage probability and strictly positive secrecy capacity are obtained. Finally, the accuracy of the derived analytical expressions are validated with Monte Carlo simulations. Results show that our proposed system model outperforms its non-SLIPT counterpart. Full article

Indoor Internet of Things (IoT) is considered as a crucial component of Industry 4.0, enabling devices and machine to communicate and share sensed data leading to increased efficiency, productivity, and automation. Increased energy efficiency is a significant focus within Industry 4.0, as it offers numerous benefits. To support this focus, we developed a hybrid switching mechanism to switch between energy harvesting techniques, ambient backscattering and Simultaneous Wireless Information and Power Transfer (SWIPT), which can be utilized within cooperative communications. To implement the proposed switching mechanism, we consider an indoor warehouse environment, where the moving sensor node transmits sensed data to the fixed relay located on the roof, which is then transmitted to an IoT gateway. The relay is equipped with the proposed switch to energize its communication capabilities while maintaining the expected quality of service at the IoT gateway. Simulation results illustrate the improved energy efficiency within the indoor communication setup while maintaining QoS at varying signal-to-noise (SNR) conditions. Full article

As the Internet of Things (IoT) expands globally, the challenge of signal transmission in remote regions without traditional communication infrastructure becomes prominent. An effective solution involves integrating aerial, terrestrial, and space components to form a Space–Air–Ground Integrated Network (SAGIN). This paper discusses an uplink signal scenario in which various types of data collection sensors as IoT devices use Unmanned Aerial Vehicles (UAVs) as relays to forward signals to low-Earth-orbit satellites. Considering the fairness of resource allocation among IoT devices of the same category, our goal is to maximize the minimum uplink channel capacity for each category of IoT devices, which is a multi-objective optimization problem. Specifically, the variables include the deployment locations of UAVs, bandwidth allocation ratios, and the association between UAVs and IoT devices. To address this problem, we propose a multi-objective evolutionary algorithm that ensures fair resource distribution among multiple parties. The algorithm is validated in eight different scenario settings and compared with various traditional multi-objective optimization algorithms. The experimental results demonstrate that the proposed algorithm can achieve higher-quality Pareto fronts (PFs) and better convergence, indicating more equitable resource allocation and improved algorithmic effectiveness in addressing this issue. Moreover, these pre-prepared, high-quality solutions from PFs provide adaptability to varying requirements in signal collection scenarios. Full article

Unmanned aerial vehicles (UAVs) offer solutions to issues like traffic congestion and labor shortages. We developed a distributed UAV management system inspired by virtual circuit and datagram methods in packet-switching networks. By installing houses with wireless terminals, UAVs navigate routes in a multi-hop network, communicating with ground nodes. UAVs are treated as network packets, ground devices are treated as routers, and their connections are treated as links. Activating all nodes as relays increases control message traffic and node load. To optimize connectivity, we minimize relay nodes, connecting non-relay nodes to the nearest relay. This study proposes four relay node selection methods: random selection, two adjacency-based methods, and our innovative approach using Multipoint Relay (MPR) from the Optimized Link State Routing Protocol (OLSR). We evaluated these methods according to their route construction success rates, relay node counts, route lengths, and so on. The MPR-based method proved most effective for UAV route construction. However, fewer relay nodes increase link collisions, and we identify the minimum relay density needed to balance efficiency and conflict reduction. Full article

This study proposes a novel optical wireless communication system for high-speed, large-capacity data transmission, supporting underwater IoT devices in shallow seas. The system employs a mirror-equipped aerial drone as a relay between underwater drones and a terrestrial station, using 850 nm optical signals for low atmospheric loss and enhanced confidentiality. Adaptive modulation optimizes transmission capacity based on SNR, accounting for air and underwater channel characteristics. Experiments confirmed an exponential SNR decrease with distance (0.6–1.8 m) and demonstrated successful 4K UHD video streaming in shallow seawater (turbidity: 2.2 NTU) without quality loss. The design ensures cost-effectiveness and stable optical alignment using advanced posture control. Full article

Future 7G/8G networks are expected to integrate both terrestrial Internet and space-based networks. Space networks, including inter-planetary Internet such as cislunar and deep-space networks, will become an integral part of future 7G/8G networks. Vehicle-to-everything (V2X) communication networks will also be a significant component of 7G/8G networks. Therefore, space networks will eventually integrate with V2X communication networks, with both space vehicles (or spacecrafts) and terrestrial vehicles involved. DTN is the only candidate networking technology for future heterogeneous space communication networks. In this work, we study possible concatenations of different DTN convergence layer protocol adapters (CLAs) over a cislunar relay communication architecture. We present a performance characterization of the concatenations of different CLAs and the associated data transport protocols in an experimental manner. The performance of different concatenations is compared over a typical primary and secondary cislunar relay architecture. The intent is to find out which network relay path and DTN protocol configuration has the best performance over the end-to-end cislunar path. Full article

In this research paper, an adaptive and intelligent protection scheme is developed that brings selectivity and sensitivity to the conventional overcurrent relays considering the changes in grid topologies, changes in grid operation modes, and changes in short-circuit behavior due to the contributions from distributed energy resources in the medium-voltage distribution grids. A quasi-static medium-voltage benchmark grid model is used in the Python-based power system tool pandapower. Definite-time overcurrent relay devices are extended with a communication signal-based tripping scheme suitable for a decentralized communication architecture. Current phasor angles are compared between two primary relays and the result is fed into a tripping logic to achieve selectivity of the primary protection. Furthermore, communication between the primary and backup relays is established, extending the communication signal-based tripping scheme. It analyzes in which cases the proposed communication-based protection scheme’s ability to isolate the faulty section after short-circuit events is comparable to conventional schemes based on distance relays that require additional voltage measurements or differential relays that require dedicated high-speed communication. Therefore, the pre-existing and installed communication capabilities can be used to avoid the need for additional measurement hardware or communication technology. Full article

In order to improve the network performance of multi-unmanned ground vehicle (UGV) systems in urban environments, this article proposes a novel online autonomous motion-control method for the relay UAV. The problem is solved by jointly considering unknown RF channel parameters, unknown multi-agent mobility, the impact of the environments on channel characteristics, and the unavailable angle-of-arrival (AoA) information of the received signal, making the solution of the problem more practical and comprehensive. The method mainly consists of two parts: wireless channel parameter estimation and optimal relay position search. Considering that in practical applications, the radio frequency (RF) channel parameters in complex urban environments are difficult to obtain in advance and are constantly changing, an estimation algorithm based on Gaussian process learning is proposed for online evaluation of the wireless channel parameters near the current position of the UAV; for the optimal relay position search problem, in order to improve the real-time performance of the method, a line search algorithm and a general gradient-based algorithm are proposed, which are used for point-to-point communication and multi-node communication scenarios, respectively, reducing the two-dimensional search to a one-dimensional search, and the stability proof and convergence conditions of the algorithm are given. Comparative experiments and simulation results under different scenarios show that the proposed motion-control method can drive the UAV to reach or track the optimal relay position and improve the network performance, while demonstrating that it is beneficial to consider the impact of the environments on the channel characteristics. Full article

This paper proposes a novel polar coding scheme tailored for indoor visible light communication (VLC) systems. Simulation results demonstrate a significant reduction in bit error rate (BER) compared to uncoded transmission, with a coding gain of at least 5 dB. Furthermore, the reliable communication area of the VLC system is substantially extended. Building on this foundation, this study explores the joint design of polar codes and physical-layer network coding (PNC) for VLC systems. Simulation results illustrate that the BER of our scheme closely approaches that of the conventional VLC relay scheme. Moreover, our approach doubles the throughput, cuts equipment expenses in half, and boosts effective bit rates per unit time-slot twofold. This proposed design noticeably advances the performance of VLC systems and is particularly well-suited for scenarios with low-latency demands. Full article

In this article, we consider an UAV (unmanned aerial vehicle)-assisted free space optical (FSO) secure communication network. Since FSO signal is impossible to detect by eavesdroppers without proper beam alignment and security authentication, a BS employs FSO technique to transfer information to multiple authenticated sensors, to improve the transmission security and reliability with the help of an UAV relay with decode and forward (DF) mode. All the sensors need to first send information to the UAV to obtain security authentication, and then the UAV forwards corresponding information to them. Successive interference cancellation (SIC) is used to decode the information received at the UAV and all authenticated sensors. With consideration of fairness, we introduce a statistical metric for evaluating the network performance, i.e., the maximum decoding outage probability for all authenticated sensors. In particular, applying an intelligent approach, we obtain a near-optimal scheme for secure transmit power allocation. With a well-trained allocation scheme, approximate closed-form expressions for optimal transmit power levels can be obtained. Through some numerical examples, we illustrate the various design trade-offs for such a system. Additionally, the validity of our approach was verified by comparing with the result from exhaustive search. In particular, the result with DRL was only 0.3% higher than that with exhaustive search. These results can provide some important guidelines for the fairness-aware design of UAV-assisted secure FSO communication networks. Full article