Search Results (195)

Millimeter-wave frequencies are crucial for meeting the high-capacity, low-latency demands of 5G communication systems, thereby driving the need for compact, high-gain antenna arrays capable of efficient beamforming. This paper presents the design, simulation, fabrication, and experimental validation of a compact, high-efficiency 1 × 6 linear series-fed microstrip patch antenna array for 5G millimeter-wave communication operating at 28 GHz. The proposed antenna is fabricated on a low-loss Rogers RO3003 substrate and incorporates an integrated symmetric two-way microstrip power divider to ensure balanced feeding and phase uniformity across elements. The antenna achieves a simulated peak gain of 11.5 dBi and a broad simulated impedance bandwidth of 30.21%, with measured results confirming strong impedance matching and a return loss better than −20 dB. The far-field radiation patterns demonstrate a narrow, highly directive beam in the E-plane, and the H-plane results reveal beam tilting behavior, validating the antenna’s capability for passive beam steering through feedline geometry and element spacing (~0.5λ). Surface current distribution analysis confirms uniform excitation and efficient radiation, further validating the design’s stability. The fabricated prototype shows excellent agreement with the simulation, with minor discrepancies attributed to fabrication tolerances. These results establish the proposed antenna as a promising candidate for applications requiring compact, high-gain, and beam-steerable solutions, such as 5G mm-wave wireless communication systems, point-to-point wireless backhaul, and automotive radar sensing. Full article

THz communication stands as a pivotal technology for 6G networks, designed to address the critical challenge of data demands surpassing current microwave and millimeter-wave (mmWave) capabilities. However, realizing Tbps and kilometer-range transmission confronts the “dual attenuation dilemma” comprising severe free-space path loss (FSPL) (>120 dB/km) and atmospheric absorption. This review comprehensively summarizes our group′s advancements in overcoming fundamental challenges of long-distance THz communication. Through systematic photonic–electronic co-optimization, we report key enabling technologies including photonically assisted THz signal generation, polarization-multiplexed multiple-input multiple-output (MIMO) systems with maximal ratio combining (MRC), high-gain antenna–lens configurations, and InP amplifier systems for complex weather resilience. Critical experimental milestones encompass record-breaking 1.0488 Tbps throughput using probabilistically shaped 64QAM (PS-64QAM) in the 330–500 GHz band; 30.2 km D-band transmission (18 Gbps with 543.6 Gbps·km capacity–distance product); a 3 km fog-penetrating link at 312 GHz; and high-sensitivity SIMO-validated 100 Gbps satellite-terrestrial communication beyond 36,000 km. These findings demonstrate THz communication′s viability for 6G networks requiring extreme-capacity backhaul and ultra-long-haul connectivity. 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

Free-space optical (FSO) communication is a promising high-capacity solution for future wireless networks, particularly for backhaul and fronthaul links in 5G and emerging 6G systems. However, it remains highly vulnerable to environmental impairment, especially in arid regions prone to dust storms. While prior studies have addressed atmospheric effects such as fog and turbulence, the specific impact of dust on signal performance remains insufficiently explored. This work presents a probabilistic modeling framework for evaluating the performance of an intensity modulation/direct detection (IM/DD) FSO system under dust storm conditions. Using a controlled laboratory environment, we conducted measurements of the optical signal under dust-induced channel conditions using real-world dust samples collected from an actual dust storm. We identified the Beta distribution as the most accurate model for the measured signal fluctuations. Closed-form expressions were derived for average bit error rate (BER), outage probability, and channel capacity. The close agreement between the analytical, approximate, and simulated results validates the proposed model as a reliable tool for evaluating FSO system performance. The results show that the forward error correction (FEC) BER threshold of ${10}^{-3}$ is achieved at approximately 10.5 dB, and the outage probability drops below ${10}^{-3}$ at 10 dB average SNR. Full article

Free-Space Optical (FSO) communication systems operating in arid regions, especially those envisioned for current and future 5G/6G networks, are significantly affected by dust storms, which cause signal attenuation and service disruptions. While previous studies have proposed deterministic models to characterize attenuation in both controlled and real environments, probabilistic modeling approaches remain largely unexplored, particularly for capturing the variability of FSO signal attenuation under dust conditions. This study proposes a probabilistic model for FSO signal attenuation developed from experiments conducted in a repeatable and well-characterized controlled dust chamber. The chamber-based setup allowed precise manipulation of dust visibility levels and consistent data collection, serving as a benchmark for statistical modeling. We analyzed the measurements to fit appropriate probability distributions for modeling the signal attenuation as a random variable. The empirical data were fitted to several candidate distributions, and the Johnson SB distribution consistently achieved superior performance with $R^2\ge 0.95$ and RMSE and MAE values close to zero across all dust conditions. The results offer a foundational framework for modeling dust-induced attenuation as a random process, providing statistical bounds for FSO link planning in desert environments. Full article

The Internet of Things (IoT) has revolutionized modern communication systems by enabling seamless connectivity among low-power devices. However, the increasing demand for high-performance wireless networks necessitates advanced frameworks that optimize both energy efficiency (EE) and security. Cell-free massive multiple-input multiple-output (CF m-MIMO) has emerged as a promising solution for IoT networks, offering enhanced spectral efficiency, low-latency communication, and robust connectivity. Nevertheless, balancing EE and security in such systems remains a significant challenge due to the stringent power and computational constraints of IoT devices. This study employs secrecy energy efficiency (SEE) as a key performance metric to evaluate the trade-off between power consumption and secure communication efficiency. By jointly considering energy consumption and secrecy rate, our analysis provides a comprehensive assessment of security-aware energy efficiency in CF m-MIMO-based IoT networks. To enhance SEE, we introduce a hybrid deep-learning (DL) framework that integrates convolutional neural networks (CNN) and long short-term memory (LSTM) networks for joint EE and security optimization. The CNN extracts spatial features, while the LSTM captures temporal dependencies, enabling a more robust and adaptive modeling of dynamic IoT communication patterns. Additionally, a multi-objective improved biogeography-based optimization (MOIBBO) algorithm is utilized to optimize hyperparameters, ensuring an improved balance between convergence speed and model performance. Extensive simulation results demonstrate that the proposed MOIBBO-CNN–LSTM framework achieves superior SEE performance compared to benchmark schemes. Specifically, MOIBBO-CNN–LSTM attains an SEE gain of up to 38% compared to LSTM and 22% over CNN while converging significantly faster at early training epochs. Furthermore, our results reveal that SEE improves with increasing AP transmit power up to a saturation point (approximately 9.5 Mb/J at $P_{\mathrm{AP}}^{max}=500$ mW), beyond which excessive power consumption limits efficiency gains. Additionally, SEE decreases as the number of APs increases, underscoring the need for adaptive AP selection strategies to mitigate static power consumption in backhaul links. These findings confirm that MOIBBO-CNN–LSTM offers an effective solution for optimizing SEE in CF m-MIMO-based IoT networks, paving the way for more energy-efficient and secure IoT communications. Full article

Conceptually, this paper aims to help reduce the communication blind spots originating from the design of millimeter-wave (mmW) beamforming by deploying radio units of an open radio access network (O-RAN) with free-space optics (FSOs) as the backhaul and the fiber-optic link as the fronthaul. At frequencies exceeding 24 GHz, the transmission reach of 5G/6G beamforming is limited to a few hundred meters, and the periphery area of the sector operational range of beamforming introduces a communication blind spot. Using FSOs as the backhaul and a fiber-optic link as the fronthaul, O-RAN empowers the radio unit to extend over greater distances to supplement the communication range that mmW beamforming cannot adequately cover. Notably, O-RAN is a prime example of next-generation wireless networks renowned for their adaptability and open architecture to enhance the cost-effectiveness of this integration. A 200 meter-long FSO link for backhaul and a fiber-optic link of up to 10 km for fronthaul were erected, thereby enabling the reach of communication services from urban centers to suburban and remote rural areas. Furthermore, in the context of beamforming, reinforcement learning (RL) was employed to optimize the error vector magnitude (EVM) by dynamically adjusting the beamforming phase based on the communication user’s location. In summary, the integration of RL-based mmW beamforming with the proposed O-RAN communication setup is operational. It lends scalability and cost-effectiveness to current and future communication infrastructures in urban, peri-urban, and rural areas. Full article

The ports and shipping industry is crucial in the global supply chain. Amid complex market and geopolitical dynamics, strengthening stakeholder collaboration becomes imperative to enhance maritime supply chain profit. Therefore, we develop a three-stage game model consisting of a port operator and a shipping company. We consider the impact of upgrading port facilities with advanced technology on the logistic decisions of the shipping company. In the first stage, the port decides whether to invest in upgrades, while the shipping company chooses one-way or two-way logistics. In subsequent stages, the port sets cargo handling charges, and the shipping company determines the freight rate. Equilibria under decentralized and centralized decision frameworks are derived. The equilibrium results show that market size has a significant effect on the shipping company’s choice. Specifically, the shipping company prefers two-way logistics when the market size is moderate, while one-way logistics is preferred when the market size is large or small. In addition, based on the fixed costs associated with port facility upgrades and two-way logistics, it is found that there exist three possible equilibria. Moreover, further analysis suggests that collaboration between the two parties, under appropriate financial conditions, can result in mutually beneficial outcomes. Our findings highlight the critical role of port–shipping company collaboration in enhancing operational efficiency and achieving greater mutual benefits. Full article

This study proposes optimizing the performance of free space optic signal transmission using spatial division multiplexing. The research uses different modified duobinary modulation schemes to model and optimize three hybrid mode division multiplexing-free-space optical (MDM-FSO) channels, each operating at 40 Gb/s–40 GHz. The study also includes the parametric optimization of various components to enhance system performance. The findings are significant for achieving high data rate links for backhaul solutions and improving bandwidth for future MDM-based wireless distributed networks. The research shows that employing three linearly polarized modes as data transmission channels with direct detection can be effective. Additionally, it is discovered that adjusting the bias voltages of the two LiNbO₃ modulators can improve power sharing between the modes, thereby mitigating the power penalty. Full article

In recent years, the demand for maritime wireless communication has been increasing, particularly in areas such as ship operations management, marine resource utilization, and safety assurance. However, due to the difficulty of deploying base stations(BSs), maritime communication still faces challenges in terms of limited coverage and unreliable communication quality. As the number of users on ships and offshore platforms increases, along with the growing demand for mobile communication at sea, conventional terrestrial base stations struggle to provide stable connectivity. Therefore, existing maritime communication primarily relies on satellite communication and long-range Wi-Fi. However, these solutions still have limitations in terms of cost, stability, and communication efficiency. Satellite communication solutions, such as Starlink and Iridium, provide global coverage and high reliability, making them essential for deep-sea and offshore communication. However, these systems have high operational costs and limited bandwidth per user, making them impractical for cost-sensitive nearshore communication. Additionally, geostationary satellites suffer from high latency, while low Earth orbit (LEO) satellite networks require specialized and expensive terminals, increasing hardware costs and limiting compatibility with existing maritime communication systems. On the other hand, 5G-based maritime communication offers high data rates and low latency, but its infrastructure deployment is demanding, requiring offshore base stations, relay networks, and high-frequency mmWave (millimeter-wave) technology. The high costs of deployment and maintenance restrict the feasibility of 5G networks for large-scale nearshore environments. Furthermore, in dynamic maritime environments, maintaining stable backhaul connections presents a significant challenge. To address these issues, this paper proposes a low-cost nearshore wireless communication solution utilizing tethered balloons as coastal base stations. Unlike satellite communication, which relies on expensive global infrastructure, or 5G networks, which require extensive offshore base station deployment, the proposed method provides a more economical and flexible nearshore communication alternative. The tethered balloon is physically connected to the coast, ensuring stable power supply and data backhaul while providing wide-area coverage to support communication for ships and offshore platforms. Compared to short-range communication solutions, this method reduces operational costs while significantly improving communication efficiency, making it suitable for scenarios where global satellite coverage is unnecessary and 5G infrastructure is impractical. Additionally, conventional uniform power allocation or channel-gain-based amplification methods often fail to meet the communication demands of dynamic maritime environments. This paper introduces a nonlinear dynamic power allocation method based on channel gain information to maximize downlink communication efficiency. Simulation results demonstrate that, compared to conventional methods, the proposed approach significantly improves downlink communication performance, verifying its feasibility in achieving efficient and stable communication in nearshore environments. Full article

Low-Earth-Orbit (LEO) satellite networks have the advantage of global internet coverage and low latency, and they have enjoyed great success in the past few years. In LEO satellite networks, laser-based inter-satellite links (ISLs) are widely employed to achieve on-board data relay, and further to provide high-capacity backhaul worldwide. However, ISLs are prone to break due to the outage of the ISL capturing, tracking, and aiming systems. Meanwhile, breaks caused by different reasons can last from milliseconds to hours. The hybrid ISL fault leads to the on-board routing protocol to flap frequently, thus causing high routing overheads, low convergence speed, and degraded service consistency. In this work, we propose a hybrid fault detection mechanism to identify transient and long-term ISL outage. Further, for transient link outage, the segment routing-based loop-free backup path is adopted to provide real-time transmission recovery, and precise global route convergence is adopted to restore the long-term routing failure. For the inconsistent routing table switch between the phase from transient to long-term fault, we propose a dual timer mechanism to make sure the path can be smoothly switched without micro-loops. Simulation results validate the feasibility and efficiency of the proposed scheme. Full article

This study proposes a bidirectional underwater optical wireless communication network that maximizes data transmission capacity by dynamically switching between underwater and aerial optical paths based on channel conditions. The proposed system employs adaptive modulation and beam steering techniques to address dynamic factors, such as turbidity and transmission distance, in underwater channels. The experimental results revealed that switching to the aerial optical path when the underwater transmission distance exceeded 1.8 m led to significant performance improvements, with consistent SNR and bit rates maintained in the aerial channel, unlike the exponential degradation observed underwater. Dynamic evaluations demonstrated that the system maintained high transmission capacity and SNR stability, even with incremental increases in underwater distances. In a 4K UHD video streaming experiment, switching from the underwater optical path to the aerial path reduced video quality degradation, delivering near-original video quality with latency as low as 20 ms. Furthermore, tolerance experiments for beam steering misalignment showed a sharp performance drop at a maximum misalignment of 2 degrees, with a 12 dB SNR loss and a reduction of 222 Mbps in transmission capacity. These findings suggest that selectively utilizing underwater and aerial optical paths based on channel conditions enables reliable and efficient data transmission, paving the way for next-generation underwater optical wireless communication networks. Full article

In this paper, we present a novel design for unmanned aerial vehicle (UAV) communication networks with wireless backhaul, where an active reconfigurable intelligent surface (ARIS) is deployed to improve connections between a UAV and multiple users, while mitigating channel impairments in complex environments. The proposed design aims to maximize the achievable sum rate of all networks by jointly optimizing UAV placement; resource management strategies; transmit power allocation; and ARIS reflection coefficients, subject to backhaul constraints and power budget limitations in the ARIS system. The resulting optimization problem is highly non-convex, posing significant challenges. To tackle this, we decompose the problem into three interrelated sub-problems and apply inner approximation (IA) techniques to handle the non-convexities within each sub-problem. Moreover, a comprehensive alternating optimization framework is proposed to implement an iterative solution for the sub-problems. Simulation results demonstrate that the proposed algorithm achieves approximately 59% improvement in the average sum rate, substantially enhancing overall network reliability compared to existing benchmark schemes. Full article

5G, the fifth-generation mobile network, is predicted to significantly increase the traditional trajectory of energy consumption. It now uses four times as much energy as 4G, the fourth-generation mobile network. As a result, compared to previous generations, 5G’s increased cell density makes energy efficiency a top priority. The objective of this paper is to formulate end-to-end power consumption models for three different 5G radio access network (RAN) deployment architectures, namely the 5G distributed RAN, the 5G centralized RAN with dedicated hardware and the 5G Cloud Centralized-RAN. The end-to-end modelling of the power consumption of a complete 5G system is obtained by combining the power models of individual components such as the base station, the core network, front-haul, mid-haul and backhaul links, as applicable for the different architectures. The authors considered the deployment of software-defined networking (SDN) at the 5G Core network and gigabit passive optical network as access technology for the backhaul network. This study examines the end-to-end power consumption of 5G networks across various architectures, focusing on key dependent parameters. The findings indicate that the 5G distributed RAN scenario has the highest power consumption among the three models evaluated. In comparison, the centralized 5G and 5G Cloud C-RAN scenarios consume 12% and 20% less power, respectively, than the Centralized RAN solution. Additionally, calculations reveal that base stations account for 74% to 78% of the total power consumption in 5G networks. These insights helped pioneer the calculation of the end-to-end power requirements of different 5G network architectures, forming a solid foundation for their sustainable implementation. Furthermore, this study lays the groundwork for extending power modeling to future 6G networks. Full article

In this article, we propose a cell-free network architecture for an unmanned aerial vehicle (UAV) base station (BS), i.e., UBS, incorporating high-altitude platform stations (HAPSs) as central processing units (CPUs). The goal is to guarantee the quality of service (QoS) of user equipment (UE), reduce energy consumption, extend communication time, and facilitate rescue operations. The millimeter-wave (mmWave) frequency band is deployed in access and backhaul links to satisfy UE QoS requirements and high backhaul demands. The proposed framework jointly optimizes user association, backhaul bandwidth allocation, and power allocation to maximize energy efficiency while meeting QoS requirements. The optimization problem, modeled as non-convex mixed-integer nonlinear fractional programming, is solved through a three-stage iterative algorithm. This includes (1) optimizing power allocation based on Dinkelbach transformation and a successive convex approximation (SCA) method, (2) clustering UBSs using the Lagrangian method, and (3) deriving a closed-form bandwidth allocation factor. The proposed algorithm significantly outperforms many traditional algorithms in performance while maintaining low computational complexity. Full article