Search Results (99)

With the rapid expansion of Internet of Things (IoT) and edge computing applications, efficient video transmission under constrained bandwidth and limited computational resources has become increasingly critical. In such environments, perception-based video coding plays a vital role in maintaining acceptable visual quality while minimizing bit rate and processing overhead. Although newer video coding standards have emerged, H.264/AVC remains the dominant compression format in many deployed systems, particularly in commercial CCTV surveillance, due to its compatibility, stability, and widespread hardware support. Motivated by these practical demands, this paper proposes a perception-based video coding algorithm specifically tailored for low-bit-rate H.264/AVC applications. By targeting regions most relevant to the human visual system, the proposed method enhances perceptual quality while optimizing resource usage, making it particularly suitable for embedded systems and bandwidth-limited communication channels. In general, regions containing human faces and those exhibiting significant motion are of primary importance for human perception and should receive higher bit allocation to preserve visual quality. To this end, macroblocks (MBs) containing human faces are detected using the Viola–Jones algorithm, which leverages AdaBoost for feature selection and a cascade of classifiers for fast and accurate detection. This approach is favored over deep learning-based models due to its low computational complexity and real-time capability, making it ideal for latency- and resource-constrained IoT and edge environments. Motion-intensive macroblocks were identified by comparing their motion intensity against the average motion level of preceding reference frames. Based on these criteria, a dynamic quantization parameter (QP) adjustment strategy was applied to assign finer quantization to perceptually important regions of interest (ROIs) in low-bit-rate scenarios. The experimental results show that the proposed method achieves superior subjective visual quality and objective Peak Signal-to-Noise Ratio (PSNR) compared to the standard JM software and other state-of-the-art algorithms under the same bit rate constraints. Moreover, the approach introduces only a marginal increase in computational complexity, highlighting its efficiency. Overall, the proposed algorithm offers an effective balance between visual quality and computational performance, making it well suited for video transmission in bandwidth-constrained, resource-limited IoT and edge computing environments. Full article

High-Bandwidth Memory (HBM) enables the bandwidth required by modern AI and high-performance computing, yet its three dimensional stack traps heat and amplifies thermo mechanical stress. We first review how conventional solutions such as heat spreaders, microchannels, high density Through-Silicon Vias (TSVs), and Mass Reflow Molded Underfill (MR MUF) underfills lower but do not eliminate the internal thermal resistance that rises sharply beyond 12layer stacks. We then synthesize recent hybrid bonding studies, showing that an optimized Cu pad density, interface characteristic, and mechanical treatments can cut junction-to-junction thermal resistance by between 22.8% and 47%, raise vertical thermal conductivity by up to three times, and shrink the stack height by more than 15%. A meta-analysis identifies design thresholds such as at least 20% Cu coverage that balances heat flow, interfacial stress, and reliability. The review next traces the chain from Coefficient of Thermal Expansion (CTE) mismatch to Cu protrusion, delamination, and warpage and classifies mitigation strategies into (i) material selection including SiCN dielectrics, nano twinned Cu, and polymer composites, (ii) process technologies such as sub-200 °C plasma-activated bonding and Chemical Mechanical Polishing (CMP) anneal co-optimization, and (iii) the structural design, including staggered stack and filleted corners. Integrating these levers suppresses stress hotspots and extends fatigue life in more than 16layer stacks. Finally, we outline a research roadmap combining a multiscale simulation with high layer prototyping to co-optimize thermal, mechanical, and electrical metrics for next-generation 20-layer HBM. Full article

The nitriding process was employed to optimize the low-frequency microwave absorption properties of Y₂Fe₁₂Co₄Si/paraffin composites. The effects of nitriding temperature on the phase composition, static magnetic properties, electromagnetic parameters, and microwave absorption performance were systematically investigated. As the nitriding temperature increases, lattice expansion results in a significant increase in saturation magnetization and a higher ratio of in-plane to out-of-plane anisotropy fields. This, in turn, boosts the electromagnetic parameters of the composite material. With a further rise in temperature, an increased content of α-Fe is produced and the ratio of the in-plane to out-of-plane anisotropy field diminishes, leading to a decline in electromagnetic parameters. At 500 °C, these factors reach an optimum level, maximizing the composite’s electromagnetic parameters. The composite exhibited a minimum reflection loss (RL_min) of −55.9 dB at 5.58 GHz with a thickness of 2.46 mm. Moreover, at a thickness of 2.21 mm, the composite achieved a maximum effective absorption bandwidth (EAB_max) of 2.95 GHz (5.05–8 GHz). Compared with other low-frequency-absorbing materials, the composite exhibited stronger absorption and a wider absorption bandwidth at a lower thickness in the C band. Full article

With the continuous expansion of communication bandwidth, accurately modeling the non-linear characteristics of power amplifiers has become increasingly challenging, directly affecting the performance of digital pre-distortion (DPD) technology. The high peak-to-average power ratio and complex modulation schemes of wideband signals further exacerbate the difficulty of DPD implementation, necessitating more efficient algorithms. To address these challenges, this paper proposes a wideband DPD algorithm based on edge signal correction. By acquiring signals near the center frequency and comparing them with equally band-limited feedback signals, the algorithm effectively reduces the required processing bandwidth. The incorporation of cross-terms for model calibration enhances the model fitting accuracy, leading to significant improvement in pre-distortion performance. Simulation results demonstrate that compared with traditional DPD algorithms, the proposed method reduces the error vector magnitude (EVM) from 1.112% to 0.512%. Experimental validation shows an average improvement of 11.75 dBm in adjacent channel power at a 2 MHz frequency offset compared to conventional memory polynomial DPD. These improvements provide a novel solution for power amplifier linearization in wideband communication systems. Full article

Energy-selective surfaces (ESSs) have gained attention as an advanced electromagnetic protection technology. This review discusses the evolution of ESSs, focusing on four key areas: frequency bandwidth expansion, material innovations, functional enhancements, and application diversification. ESSs have evolved from narrowband designs to providing ultra-wideband protection, covering L-band to K-band frequencies. New designs, including non-reciprocal mechanisms and cascaded filters, enhance the shielding efficiency. Material advancements like the use of vanadium dioxide (VO₂) and micro–nano fabrication techniques have reduced costs and improved performance, enabling higher-frequency applications. Future developments aim to overcome the current limitations, offering a broader bandwidth, higher power tolerance, and faster response times. ESSs play a key role in integrated electromagnetic protection systems. Full article

This paper investigates the linear stability of the liquid film of Oldroyd-B fluid on an oscillating plate. The time-dependent Orr–Sommerfeld boundary-value problem is formulated through the assumption of a normal modal solution and the introduction of the stream function, which is further transformed into the Floquet system. A long-wavelength expansion analysis is performed to derive the analytical solution of the Orr–Sommerfeld equation. The results indicate that long-wave instability occurs only within specific bandwidths related to the Ohnesorge number ($Oh$). Fixing the elasticity parameter ($El$) and increasing the relaxation-to-delay time ratio ($\tilde{\lambda }$) from 2 to 4 or fixing ($\tilde{\lambda }$) and increasing ($El$) from 0.001 to 0.01 decreases the number of unstable bandwidths while enhancing the intensity of unstable modes. Increasing the surface-tension-related parameter (${\zeta }^{\ast }$) from 0 to 100 suppresses the wave growth rate, stabilizing the system. Additionally, increasing ($\tilde{\lambda }$) from 2 to 4 reduces the maximum values of the coupling of viscoelastic, gravitational, and surface-tension forces, as well as the maximum value of the Floquet exponent, further stabilizing the system. These findings provide supplements to the theoretical research on the stability of viscoelastic fluids and also offer a scientific basis for engineering applications in multiple fields. Full article

The widespread use of smart devices, such as phones and live-streaming cameras, has ushered in an era where digital images can be captured and shared on social networks anytime and anywhere. Sharing images demands more bandwidth and stricter security than text. This prevalence poses challenges for secure image forwarding, as it is susceptible to privacy leaks when sharing data. While standard encryption algorithms can safeguard the privacy of textual data, image data entail larger volumes and significant redundancy. The limited computing power of smart devices complicates the encrypted transmission of images, creating substantial obstacles to implementing security policies on low-computing devices. To address privacy concerns regarding image sharing on social networks, we propose a lightweight data forwarding mechanism for resource-constrained environments. By integrating large-scale data forwarding with visual cryptography, we enhance data security and resource utilization while minimizing overhead. We introduce a downsampling-based non-expansive scheme to reduce pixel expansion and decrease encrypted image size without compromising decryption quality. Experimental results demonstrate that our method achieves a peak signal-to-noise ratio of up to 20.54 dB, and a structural similarity index of 0.72, outperforming existing methods such as random-grid. Our approach prevents size expansion while maintaining high decryption quality, addressing access control gaps, and enabling secure and efficient data exchange between interconnected systems. Full article

As 5G technology rapidly advances, the extension of spectrum into millimeter-wave bands enables higher data speeds and reduced latency. However, this frequency expansion introduces significant electromagnetic interference (EMI) issues, particularly in environments with dense equipment and base stations. To tackle these challenges, this paper presents a multilayer transparent ultra-wideband microwave absorber (MA) using indium tin oxide (ITO) that operates between 4 and 26 GHz. This optimized MA design successfully achieves absorption from 4.07 to 25.07 GHz, encompassing both the 5G Sub-6 GHz and n258 bands, with a relative bandwidth of 144% and a minimal thickness of 0.129λ_L (where λ_L is the free-space wavelength at the lowest cutoff frequency). For TE and TM polarization with incidence angles ranging from 0° to 45°, the MA demonstrates exceptional performance, maintaining a relative bandwidth exceeding 120%. Notably, for TM polarization with incidence angles between 60° and 70°, the MA can sustain an absorption capacity with a relative bandwidth greater than 100%. By integrating the principles of impedance matching, surface current theory, and equivalent circuit simulation fitting, the absorption mechanism is further analyzed, thereby confirming the reliability of the design. This design offers exceptional wideband absorption, optical transparency, and wide-angle incidence characteristics, demonstrating great potential for applications in electromagnetic stealth, EMI suppression, and electromagnetic compatibility (EMC) in 5G communications. Full article

Multi-band optical communication presents a promising avenue for the significant enhancement of fiber-optic transmission capacity without incurring additional costs related to new cable deployment via the utilization of the bandwidth beyond the established C&L bands. However, a big challenge in its field implementation lies in the high cost and suboptimal performance of optical amplifiers, stemming from the underdeveloped state of rare-earth-doped fiber-optic amplifier technologies for these bands. Fiber-optic parametric amplifiers provide an alternative for wideband optical amplification, yet their low power efficiency limits their practical use in the field. In this paper, we study a hybrid optical amplifier that combines the excellent power efficiency of rare-earth-doped amplifiers with broadband wavelength conversion capability of parametric amplifiers. It uses wavelength converters to shift signals between the S- and L-bands, amplifying them with an L-band erbium-doped fiber amplifier, and converting them back to the S-band. We experimentally demonstrate such a hybrid S-band amplifier, characterize its performance with 16-QAM input signals, and evaluate its power efficiency and four-wave-mixing-induced crosstalk. This hybrid approach paves the way for scalable expansion of optical communication bands without waiting for advancements in rare-earth-doped amplifier technology. Full article

Artificial intelligence (AI) transforms communication networks by enabling more efficient data management, enhanced security, and optimized performance across diverse environments, from dense urban 5G/6G networks to expansive IoT and cloud-based systems. Motivated by the increasing need for reliable, high-speed, and secure connectivity, this study explores key AI applications, including traffic prediction, load balancing, intrusion detection, and self-organizing network capabilities. Through detailed case studies, I illustrate AI’s effectiveness in managing bandwidth in high-density urban networks, securing IoT devices and edge networks, and enhancing security in cloud-based communications through real-time intrusion and anomaly detection. The findings demonstrate AI’s substantial impact on creating adaptive, secure, and efficient communication networks, addressing current and future challenges. Key directions for future work include advancing AI-driven network resilience, refining predictive models, and exploring ethical considerations for AI deployment in network management. Full article

This paper presents a novel dual-band Gysel filtering power divider (FPD) with an excellent isolation performance and a significantly wide isolation bandwidth. Although Gysel power dividers have been extensively studied in the field of radio frequency (RF), the integration of filtering functionality and the expansion of isolation bandwidth remain challenging. The proposed design addresses these challenges by incorporating frequency transform resonators (FTRs) and a microstrip/slotline (M/S) phase inverter into the classic Gysel topology. The FTR is directly connected to the output port to provide a dual-band response, enabling the Gysel FPD to operate without external coupling between the resonator and the port. The M/S phase inverter is a dual-layer 180° phase shifter, designed to replace the conventional 180° transmission lines loaded between the two isolation resistors of the Gysel FPD, achieving a wide isolation bandwidth. To validate the proposed design method, a dual-band Gysel FPD with center frequencies of 1.4 GHz and 1.7 GHz is designed, fabricated, and measured. The measured results show that the in-band return loss is greater than 20 dB, and the in-band insertion loss is about 0.6 dB, and the amplitude and phase imbalance characteristics are good. In addition, the 20 dB-isolation fractional bandwidth achieves 97% (0.78–2.25 GHz). The measured results show excellent agreement with the simulation results, validating the effectiveness of the proposed design methodology. Full article

The continuous expansion of wireless communication application scenarios demands the active tuning of electromagnetic (EM) metamaterials, which is essential for their flexible adaptation to complex EM environments. However, EM reconfigurable systems based on intricate designs and smart materials often exhibit limited flexibility and incur high manufacturing costs. Inspired by mechanical metastructures capable of switching between multistable configurations under repeated deformation, we propose a planar kirigami frequency selective surface (FSS) that enables mechanical control of its resonant frequency. This FSS is composed of periodically arranged copper square-ring resonators embedded in a kirigami-structured ecoflex substrate. Through simple tensile deformation, the shapes and positions of the square-ring resonators on the kirigami substrate are altered, resulting in changes to the coupling between capacitance and inductance, thereby achieving active tuning. Combining EM finite element simulations and transmittance measurements, we demonstrate that biaxial mechanical stretching allows for continuous adjustment of the FSS resonant frequency and −10 dB bandwidth. Additionally, the FSS exhibits excellent polarization and incident angle stability. Structural parameterization of the square-ring kirigami FSS was conducted to elucidate the deformation–electromagnetic coupling mechanism underlying the active tuning. These insights provide a foundation for guiding the application of square-ring kirigami FSS in various practical engineering domains. Full article

The rapid expansion of the Internet of Things ecosystem has created an urgent need for efficient data processing and analysis technologies. This review aims to systematically examine and compare edge computing, cloud computing, and hybrid architectures, focusing on their applications within IoT environments. The methodology involved a comprehensive search and analysis of peer-reviewed journals, conference proceedings, and industry reports, highlighting recent advancements in computing technologies for IoT. Key findings reveal that edge computing excels in reducing latency and enhancing data privacy through localized processing, while cloud computing offers superior scalability and flexibility. Hybrid approaches, such as fog and mist computing, present a promising solution by combining the strengths of both edge and cloud systems. These hybrid models optimize bandwidth use and support low-latency, privacy-sensitive applications in IoT ecosystems. Hybrid architectures are identified as particularly effective for scenarios requiring efficient bandwidth management and low-latency processing. These models represent a significant step forward in addressing the limitations of both edge and cloud computing for IoT, offering a balanced approach to data analysis and resource management. Full article

This paper presents the theory, design, and application of a dual-branch series-diode analog pre-distortion (APD) linearizer to improve the linearity and efficiency of a K-band high-power amplifier (HPA). A first-of-its-kind, frequency-dependent large-signal APD model is presented. This model is used to evaluate different phase relationships between the linear and nonlinear branches, suggesting independent gain and phase expansion characteristics with this topology. This model is used to assess the impact of diode resistance, capacitance, and ideality factors on the APD characteristics. This feature is showcased with two similar GaAs diodes to find the best fit for the considered HPA. The selected diode is characterized and modeled between 1 and 26.5 GHz. A comprehensive APD design and simulation workflow is reported. Before fabrication, the simulated APD is evaluated with the measured HPA to verify linearity improvements. The APD prototype achieves a large-signal bandwidth of 6 GHz with 3 dB gain expansion and 8° phase rotation. This linearizer is demonstrated with a 17–21 GHz GaN HPA with 41 dBm output power and 35% efficiency. Using a wideband 750 MHz signal, this APD improves the noise–power ratio (NPR) by 6.5–8.2 dB over the whole HPA bandwidth. Next, the HPA output power is swept to compare APD vs. power backoff for the same NPR. APD improves the HPA output power by 1–2 W and efficiency by approximately 5–9% at 19 GHz. This efficiency improvement decreases by only 1–2% when including the APD post-amplifier consumption, thus suggesting overall efficiency and output power improvements with APD at K-band frequencies. Full article

To guarantee the reliability of Tactile Internet (TI) applications such as telesurgery, which demand extremely high reliability and are experiencing rapid expansion, we propose a novel smart resilience mechanism for Next-Generation Ethernet Passive Optical Networks (NG-EPONs). Our architecture integrates Artificial Intelligence (AI) and Software-Defined Networking (SDN)-Enabled Broadband Access (SEBA) platform to proactively enhance network reliability and performance. By harnessing the AI’s capabilities, our system automatically detects and localizes fiber faults, establishing backup communication links using Radio Frequency over Glass (RFoG) to prevent service disruptions. This empowers NG-EPONs to maintain uninterrupted, high-quality network service even in the face of unexpected failures, meeting the stringent Quality-of-Service (QoS) requirements of critical TI applications. Our AI model, rigorously validated through 5-fold cross-validation, boasts an average accuracy of 81.49%, with a precision of 84.33%, recall of 78.18%, and F1-score of 81.00%, demonstrating its robust performance in fault detection and prediction. The AI model triggers immediate corrective actions through the SDN controller. Simulation results confirm the efficacy of our proposed mechanism in terms of delay, system throughputs and packet drop rate, and bandwidth waste, ultimately ensuring the delivery of high-quality network services. Full article