Current Issue : July-September Volume : 2026 Issue Number : 3 Articles : 5 Articles
With the rapid evolution of wireless networks, the need to explore novel technologies to meet the demands of future systems, particularly 6G, has become a significant challenge. One promising solution is integrating radio frequency (RF) and optical wireless communication (OWC) technologies to leverage their unique strengths. This paper introduces a novel model for integrating RF and OWC technologies within the framework of emerging 6G. The main objective of this approach is the dynamic technology selection (TS) and modulation scheme selection (MSS), which play a pivotal role in optimizing network efficiency and adapting to diverse 6G requirements. The proposed cross-layer architecture integrates the application layer, network layer based on a software-defined network (SDN), and physical layer consisting of a hybrid cell and software-defined radio with optical functionality (SDRO). This approach facilitates real-time decision-making based on environmental factors and application requirements....
To address the phase noise issue in terahertz OFDM system, this paper proposes a dual-branch deep learning phase noise compensation network named AdaPhaseNet. The Transformer branch of this network leverages the powerful modeling capability of Transformers for long-range dependencies to achieve long-range phase noise estimation and compensation, while the CNN branch is employed for local signal enhancement. Finally, an optimized signal is output through a confidence-driven adaptive fusion module. For experimental validation of the algorithm, we constructed a photonic terahertz communication system comprising 10 km of fiber and 5 m of wireless transmission. Experimental results show that, compared with multiple baseline models, AdaPhaseNet achieves relative BER reductions ranging from 37.0% to 57.9% and EVM gains ranging from 1.4 dB to 3.2 dB....
Wireless communication systems, which rely on radio frequencies (RFs), are widely utilized in various applications, such as mobile communications, radio frequency identification, marine networks, smart farms, and smart homes. Due to their ease of installation, wireless systems offer advantages over wired alternatives. But the deployment of high-frequency radio waves for a communication system can pose potential health risks. To address these concerns, many researchers have explored the use of visible light as a safer alternative to radio frequency communication. In this context, optical camera communication has emerged as a good candidate compared to the RF system. Meanwhile, artificial intelligence (AI) is reshaping industries and human life by solving complex problems, enabling intelligent automation, and driving advancements in technologies such as smart farms, smart homes, and future internet of things systems. In this study, we recommend a Multiple- Input Multiple-Output Camera On–Off Keying (MIMO C-OOK) modulation that integrates a YOLOv11 for light source detection and tracking and a deep learning network-based decoder algorithm, optimized for long-range and mobility communication scenarios. The proposed approach enhances the conventional C-OOK system by increasing the data rate and transmission range while reducing errors at the receiver. Implementation results show that the proposed approach can achieve reliable communication up to 10 m with minimal errors, even under mobility conditions (3 m/s, equivalent to walking speed), by optimizing camera parameters and employing forward error correction (FEC)....
The growing requests for extremely fast indoor wireless connectivity have introduced significant challenges in designing nextgeneration communication systems to build Internet of things (IoT)–enabled fully connected smart environments, particularly at higher frequency bands such as millimeter wave (mmWave/MMW). Accurate channel modeling is critical for optimizing these systems, especially in indoor environments where reflections, diffractions, and penetration losses considerably impact signal propagation. This study presents a detailed channel modeling approach using ray tracing techniques to characterize mmWave signal behavior in complex indoor scenarios. To accurately capture essential parameters including path loss, delay spread, and angular spread, the approach simulates signal interactions with environmental elements (e.g., walls, floors, and furniture) by leveraging three-dimensional (3D) building models. The study provides a deeper understanding of line-of-sight (LOS) and nonline- of-sight (NLOS) propagation. Furthermore, it comprehensively compares the propagation characteristics of various frequency bands, ranging from sub-6 GHz (e.g., 2.4 and 6 GHz) to mmWave (e.g., 28, 60, and 100 GHz), thereby highlighting their distinct behaviors under identical indoor conditions and user trajectories. Using ray tracing, channel impulse responses and path loss metrics are extracted, and coverage map of received power is proposed for each position. Results demonstrate that mmWave bands experience higher path losses than sub-6 GHz frequencies and are significantly affected by shadowing and blockage. This study not only validates the accuracy of the ray tracing model against empirical data but also demonstrates its utility in designing robust mmWave communication systems, optimizing network deployments, and enhancing beamforming strategies for future 5G and 6G networks....
Future wireless networks require efficient device-to-device (D2D) communication to meet the demands of increasing connectivity; however, practical challenges such as limited coverage and severe interference persist. This paper addresses these issues by employing simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) equipped with low-resolution phase shifters, thereby enabling full-space coverage while conforming to hardware constraints. To further improve system performance, we propose an irregular STAR-RIS configuration, in which only a subset of elements is activated to enhance spatial diversity without increasing power consumption. Additionally, we introduce a group scheduling strategy that assigns users to different time slots, effectively mitigating interference and improving the overall sum rate. To solve the resulting high-dimensional and non-convex optimization problem, we develop a cross-entropy optimization framework that jointly optimizes element selection, amplitude and phase configurations, and user scheduling. Simulation results demonstrate that the proposed design significantly outperforms existing benchmarks in terms of both the sum rate and scalability, thus providing a practical and efficient solution for STAR-RIS-assisted D2D communication systems....
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