Sharadhi Gunathilake, Ampalavanapillai Nirmalathas, Kosala Herath
et al.
The growing passion for indoor optical wireless networks reflects their immense capability to deliver consistent high-quality data connectivity across diverse indoor environments. This study examines how polarization can be engineered to enhance near-field beam focusing in optical wireless indoor networks using a modular clustered optical phased array aperture. The aperture follows a ceiling-mounted phased array embedded within a phased array layout, associating planar clusters of dipole nano-emitters, supported by a dual-carrier architecture for grating lobe mitigation. We introduce a polarization-adaptive synthesis strategy that determines the cluster-level emitter polarization to replicate any desired polarization at the focal spot. The optimization model accommodates both unconstrained and constrained modes, enabling electric (E)-field matching from linear to general elliptical receiver states. Moreover, we analyze how quantization can be applied to these optimized orientations and how it affects the final performance. To learn the benefits of polarization orthogonality in a multi-receiver environment, we extend the aperture to simultaneously manage multiple focused beams via sub-cluster segmentation. At this level, we apply two polarization control strategies: continuous-domain polarization optimization and binary polarization assignment to match user-specific polarization states and suppress inter-user interference. Numerical estimates of per-receiver signal-to-interference-plus-noise ratio (SINR), E-field patterns, beam characteristics, and mean SINR trends with increasing user availability confirm the superior performance of the proposed techniques over systems that do not consider polarization. Under realistic system- and hardware-level constraints, our results deepen understanding of polarization-engineered modular optical phased arrays and demonstrate their potential for efficient and secure next-generation indoor networks.
Telecommunication, Transportation and communications
Yu-Chao Hsu, Jiun-Cheng Jiang, Chun-Hua Lin
et al.
Long short-term memory (LSTM) models are a particular type of recurrent neural networks (RNNs) that are central to sequential modeling tasks in domains such as urban telecommunication forecasting, where temporal correlations and nonlinear dependencies dominate. However, conventional LSTMs suffer from high parameter redundancy and limited nonlinear expressivity. In this work, we propose the Quantum-inspired Kolmogorov-Arnold Long Short-Term Memory (QKAN-LSTM), which integrates Data Re-Uploading Activation (DARUAN) modules into the gating structure of LSTMs. Each DARUAN acts as a quantum variational activation function (QVAF), enhancing frequency adaptability and enabling an exponentially enriched spectral representation without multi-qubit entanglement. The resulting architecture preserves quantum-level expressivity while remaining fully executable on classical hardware. Empirical evaluations on three datasets, Damped Simple Harmonic Motion, Bessel Function, and Urban Telecommunication, demonstrate that QKAN-LSTM achieves superior predictive accuracy and generalization with a 79% reduction in trainable parameters compared to classical LSTMs. We extend the framework to the Jiang-Huang-Chen-Goan Network (JHCG Net), which generalizes KAN to encoder-decoder structures, and then further use QKAN to realize the latent KAN, thereby creating a Hybrid QKAN (HQKAN) for hierarchical representation learning. The proposed HQKAN-LSTM thus provides a scalable and interpretable pathway toward quantum-inspired sequential modeling in real-world data environments.
Ruggedized computers are the core of modern communication, guidance, control, and data-processing systems, and typically operate under extreme environmental conditions. However, under extreme service conditions such as temperature cycling, vibration, and mechanical shock, thermo–electro–mechanical (TME) multi-physics coupling in ball grid array (BGA) solder joints is particularly significant, severely affecting system reliability and signal integrity. To comprehensively elucidate the effects of thermal, electrical, and mechanical fields on solder joints and signal transmission, this study proposes a multiscale multi-physics modeling and analysis framework for BGA solder joints in microelectronic systems of ruggedized computers, covering the computer system level, motherboard level, solder joint level, and solder interconnect level. A model correlation study under ten thermal cycling conditions demonstrated an accuracy of 88.89%, confirming the validity and applicability of the proposed model. Based on this validated framework and model, the temperature distribution, stress–strain response, and signal integrity characteristics were further analyzed under combined conditions of thermal cycling, random vibration, and mechanical shock. The results indicate that a rise in temperature in solder joints induces thermal stresses and deformations, while variations in electrical conductivity under thermal loading trigger electromigration and concentration evolution, which further couple with stress gradients to form TME multi-physics interactions. Under such coupling, critical solder balls exhibit stress concentration at the metallurgical interfaces, with a maximum von Mises stress of 191.51 MPa accompanied by plastic strain accumulation. In addition, the PCIe high-speed interconnect experienced a maximum deformation of 16.104 μm and a voltage amplitude reduction of approximately 18.51% after 928 thermal cycles, exceeding the normal operating range. This research provides a theoretical basis and engineering reference for reliability assessment and optimization design of microelectronic systems in ruggedized computers in complex service environments.
Giovanni Finco, Filippo Miserocchi, Andreas Maeder
et al.
Optical quantum communication technologies are making the prospect of unconditionally secure and efficient information transfer a reality. The possibility of generating and reliably detecting quantum states of light, with the further need of increasing the private data-rate is where most research efforts are focusing. The physical concept of entanglement is a solution guaranteeing the highest degree of security in device-independent schemes, yet its implementation and preservation over long communication links is hard to achieve. Lithium niobate-on-insulator has emerged as a revolutionising platform for high-speed classical telecommunication and is equally suited for quantum information applications owing to the large second-order nonlinearities that can efficiently produce entangled photon pairs. In this work, we generate maximally entangled quantum states in the time-bin basis using lithium niobate-on-insulator photonics at the fibre optics telecommunication wavelength, and reconstruct the density matrix by quantum tomography on a single photonic integrated circuit. We use on-chip periodically-poled lithium niobate as source of entangled qubits with a brightness of 242 MHz/mW and perform quantum tomography with a fidelity of 91.9+-1.0 %. Our results, combined with the established large electro-optic bandwidth of lithium niobate, showcase the platform as perfect candidate to realise fibre-coupled, high-speed time-bin quantum communication modules that exploit entanglement to achieve information security.
The importance of big data in telecommunications for the governance of intelligent societies was delved into. Taking into account the current policy environment, the research objectives and contributions was elucidated. The theoretical foundations of telecommunications big data, its developmental trends, and its status both domestically and internationally was presented, and the necessity and application directions for constructing a big data open platform was discussed. The solutions to key issues, including multi-domain data fusion, spatiotemporal data model construction, and big data openness strategies, was deeply analyzed, and the project outcomes and their impact at the technological, economic, and social levels was forecasted. This study provides a valuable reference for the future application of telecom big data.
Vitalii Velychko, Svitlana Voinova, Valery Granyak
et al.
The monograph summarizes and analyzes the current state of development of computer and mathematical simulation and modeling, the automation of management processes, the use of information technologies in education, the design of information systems and software complexes, the development of computer telecommunication networks and technologies most areas that are united by the term Industry 4.0
We derive exact analytical expressions for the spatial Fourier spectrum of the fundamental bright soliton solution for the $(1 + 1)$-dimensional nonlinear Schrödinger equation. Similar to a Gaussian profile, the Fourier transform for the hyperbolic secant shape is also shape-preserving. We further confirm that the fundamental soliton indeed satisfies essential characteristics such as Parseval's relation and the stretch-bandwidth reciprocity relationship. The fundamental bright solitons find rich applications in nonlinear fiber optics and optical telecommunication systems.
Every video stream possesses temporal redundancy based on the amount of motion presenting in it. An ample amount of motion in a video sequence may cause distorting artifacts, and in order to avoid them, there is a possibility to mask the motion or temporal activity that is not noticeable to a human eye in real time. The artifacts such as blockiness and blurriness are instigated in the video sequence as soon as it is subjected to the process of compression, and they tend to become more and more intense with the increase in temporal activity. In this paper, an algorithm is proposed to mask the temporal activity using temporal masking coefficient ( q ) that is unnoticeable by a human eye to bring down the distortion levels. It is possible to adjust the quality of the video sequence by varying the q parameter and thus controlling its overall quality index. Frames are extracted from the video sequence, and displacement or motion vectors are also calculated from the consecutive frames using a bi-directional block matching algorithm. These motion vectors are used to estimate the quantity of motion present between consecutive frames of the same scene. Video sequences used for this purpose are basically H.264 format. Temporal masking is performed on a video sequence with and without the implementation of motion vector. Structural similarity index and peak signal-to-noise ratio are the quality measurement tools used to assess the performance of the proposed algorithm. A bit rate of 1.2% was saved by implementing proposed algorithm at q = 1 in contrast to the standard H.264/Advanced Video Coding.
Control engineering systems. Automatic machinery (General), Technology (General)
With the change of the power communication network,the data of the bearer service of the power communication network has increased exponentially,which puts higher requirements on the processing capability of the power communication network.In order to guarantee the service quality of communication network,aiming at the current unreasonable distribution of network bandwidth,a bandwidth prediction algorithm based on deep confidence for power communication network was proposed.The deep confidence network formed by the Boltzmann machine was used to obtain the characteristics that could perfectly express the network bandwidth,and the reasonable prediction of the bandwidth of the power communication network planning stage was realized.The implementation results show that the proposed algorithm is more accurate and robust than neural network.It has the advantage of improving the carrying capacity of the power communication network and providing a powerful guarantee for the safe and stable operation of the power system.
To alleviate the traffic pressure on roads,reduce the appearance of road congestion,and avoid the occurrence of traffic accidents,a privacy-preserving intelligent monitoring (PPIM) scheme based on intelligent traffic was proposed in combination with the safe and k-nearest neighbor (KNN) algorithm.To ensure the security of traffic data,the data content was randomly divided into independent parts via the secure multi-party computing strategy,and the data components were stored and encrypted separately by non-colluding multi-servers.To improve the accuracy of road condition monitoring,an improved KNN traffic monitoring algorithm was proposed.By virtue of the similarity calculation of data,the correlation value to measure the degree of traffic condition relationship between roads was obtained.And it was integrated with the KNN as the weight coefficient.To speed up the processing of dense data,a series of data security computing protocols were designed,and the data security processing was realized.In addition,real traffic data were used to verify the algorithm.The results show that the improved KNN algorithm is helpful to improve the accuracy of traffic monitoring.The analysis shows that the algorithm can not only guarantee the safety of data but improve the accuracy of traffic monitoring.
We theoretically propose and numerically validate an all-optical scheme to generate optical pulse trains with varying peak-powers and durations. A shaping of the spectral phase thanks to discrete $π/2$ phase shifts enables an efficient phase-to-intensity conversion of a temporal phase modulation based on a two-tone sinusoidal beating. Experiments carried out at telecommunication wavelengths and at a repetition rate of 10 GHz confirm the ability of our approach to efficiently generate a train made of pulses with properties that vary from pulse-to-pulse. The levels of jitters can be accurately controlled.
Along with the widespread use of Enterprise Social Media (ESM) by various large companies in Indonesia, this research is conducted to discover what the factors that drive employees’ intention to use ESM as knowledge sharing media are, and what factor is the most dominant in driving employees’ intention. This research is a quantitative research which uses Innovation Diffusion Technology (IDT) and Extended Technology Acceptance Model (TAM) as the research model. Data collection in this research is conducted by the survey method. The questionnaires are distributed to 374 respondents. Based on the data collected, data processing and hypothesis testing are carried out using Partial Least Square Structural Equation Modelling (PLS-SEM). The result of this study indicates that relative advantage, compatibility, and perceived ease of use have a significant influence on perceived usefulness and perceived enjoyment. Meanwhile, perceived usefulness and perceived enjoyment have a significant influence on employees’ intention to use ESM. Furthermore, it is also found that the most dominant factor among those two variables is perceived enjoyment.
Time-varying requirements of users on communication push mobile operators to increase density of base stations. However, the dense deployment of conventional static base stations (SBSs) is not always economical, for example, when periods of peak load are short and infrequent. In such cases, several flying base stations (FlyBSs) mounted on unmanned aerial vehicles can be seen as a convenient substitution for the dense deployment of SBSs. This paper focuses on maximization of user satisfaction with provided data rates. To this end, we propose an algorithm that associates users with the most suitable SBS/FlyBS and finds optimal positions of all FlyBSs. Furthermore, we investigate the performance of two proposed approaches for the joint association and positioning based on the genetic algorithm (GA) and particle swarm optimization (PSO). It is shown that both solutions improve the satisfaction of users with provided data rates in comparison with a competitive approach. We also demonstrate trade-offs between the GA and the PSO. While the PSO is of lower complexity than the GA, the GA requires a slightly lower number of active FlyBSs to serve the users.
We consider downlink channel training of a frequency division duplex (FDD) massive multiple-input-multiple-output (MIMO) system when a multi-antenna jammer is present in the network. The jammer intends to degrade mean square error (MSE) of the downlink channel training by designing an attack based on second-order statistics of its channel. The channels are assumed to be spatially correlated. First, a closed-form expression for the channel estimation MSE is derived and then the jammer determines the conditions under which the MSE is maximized. Numerical results demonstrate that the proposed jamming can severely increase the estimation MSE even if the optimal training signals with a large number of pilot symbols are used by the legitimate system.
Based on the theory of the Federal Communications Commission, the spectrum available on cognitive radio networks is limit and the non-optimal use of the spectrum necessitates the need for a telecommunications model, so that this pattern can exploit the existing spectral positions. In this spectrum subscription scenario, when the primary users are not present, it is also possible to assign this telecommunication to tenants who are unauthorized or secondary. The challenge of using this scenario is to allocate time-frequency resources to them and how to access nodes in one channel without any interactions between primary and secondary users and the throughput will increase. The main idea of this research is using chaotic recurrent neural network for improving access to spectrum in congestion times and the main purposes are reduce interference and increase throughput in cognitive radio networks. In this method, in addition to the throughput, the amount of unwanted blockage of packets, the reduction of the cost of operations for secondary users, the hardware requirements for secondary users and the coefficient of justice are considered which in fact, it is a new channel assignment process with respect to the environment response, the updates the probability that the channels are empty in subsequent periods, and increases the permeability by reducing interference with chaotic recurrent neural network.
Electro-optic modulators transform electronic signals into the optical domain and are critical components in modern telecommunication networks, RF photonics, and emerging applications in quantum photonics and beam steering. All these applications require integrated and voltage-efficient modulator solutions with compact formfactors that are seamlessly integratable with Silicon photonics platforms and feature near-CMOS material processing synergies. However, existing integrated modulators are challenged to meet these requirements. Conversely, emerging electro-optic materials heterogeneously integrated with Si photonics open a new avenue for device engineering. Indium tin oxide (ITO) is one such compelling material for heterogeneous integration in Si exhibiting formidable electro-optic effect characterized by unity order index at telecommunication frequencies. Here we overcome these limitations and demonstrate a monolithically integrated ITO electro- optic modulator based on a Mach Zehnder interferometer (MZI) featuring a high-performance half-wave voltage and active device length product, VpL = 0.52 V-mm. We show, how that the unity-strong index change enables a 30 micrometer-short pi-phase shifter operating ITO in the index-dominated region away from the epsilon-bear-zero ENZ point. This device experimentally confirms electrical phase shifting in ITO enabling its use in multifaceted applications including dense on-chip communication networks, nonlinearity for activation functions in photonic neural networks, and phased array applications for LiDAR.
A new transmission mechanism called direct and relay-aided transmissions based on inter group cooperation was proposed for the cognitive radio network.The performance of a single-relay system based on amplify-forward in the Rayleigh fading environment by considering the interference constraints and peak power constraints was analyzed.The impact of the relay node and the primary users（PU）location on power allocation and system throughout was investigated and the performance of the optimal power allocation（OPA）scheme and equal power allocation（EPA）scheme was compared.The result shows that the locations of relay node and PU are crucial to the system performance and the proposal optimum power allocation scheme significantly outperforms the equal power allocation scheme.The best performance was achieved when the relay is at an equal distance from the sender and the destination in EPA scheme or the relay is closer to the destination around in OPA scheme.