Search Results (490)

This review traces Turkey’s mobile communication evolution from car phones to the commercial 5G phase launched on 1 April 2026. It combines a generation-based engineering matrix with an auditable framework covering spectrum, antenna/radio integration, RAN and core architecture, transport, performance objectives, trade-offs, costs, and evidence limits. Its quantitative synthesis uses 1990s ETSI standards, KPI targets, antenna parameters, regulatory comparisons, link budget illustrations, BTK 2026-Q1 indicators, and a deliberately limited single-point handset observation. At equal distance, free-space path loss at 3.5 GHz is 13.98 dB higher than at 700 MHz; for an illustrative path loss exponent of 3.5, the cell radius and coverage area ratios are about 0.40 and 0.159. The 2025 authorization comprises 60 MHz of paired 700 MHz spectrum and 340 MHz of 3.5 GHz TDD spectrum. The international comparison is limited to regulatory spectrum positioning and a common date fixed-broadband fiber proxy, not user-experienced performance or deployment maturity. BTK data demonstrate market and infrastructure scale, but nationwide province- and operator-level radio, latency, synchronization, energy, outage, and SA/NSA data remain unavailable. The evidence supports a pragmatic coverage-first low-/mid-band launch whose practical performance depends on site density, active antennas, fiber backhaul, synchronization, energy resilience, and legacy band refarming. Full article

The rapid development of wireless communication systems has increased the complexity of smartphone antenna design. Modern terminals are required to simultaneously support Sub-1 GHz cellular bands, 5G New Radio (NR), millimeter-wave communication, satellite links, and emerging sensing services within limited physical space. As a result, multiband operation has become a central challenge for mobile terminals. This paper reviews the recent research advances in multiband smartphone antennas, organized according to the evolution from single-antenna to multi-antenna architectures and including both Sub-6 GHz and millimeter-wave applications. Single-antenna Sub-3 GHz techniques, multiband multi-antenna systems, dual-band millimeter-wave antennas, and integrated Sub-6 GHz/millimeter-wave architectures are systematically summarized. The key technologies, including multi-mode cooperation, characteristic-mode design, multiple-input multiple-output (MIMO) decoupling, and shared-aperture integration, are discussed. The emerging B5G/6G-oriented technologies are also highlighted. This review provides an overview of current design strategies and future trends for next-generation multiband smartphone antennas. Full article

Mobile-reader trajectories strongly affect phase-based Radio Frequency Identification (RFID) localization because measurement geometry, noise, multipath, and packet loss determine the information available to the estimator. This paper presents a tabular Q-learning method whose reward is computed from the RFID localization error generated along each candidate antenna motion rather than from geometric coverage alone. The method is evaluated in two simulated $3\times 3$ m shelf regions using a 10 cm grid and one hundred Monte Carlo trials. Under matched sensing budgets of 5, 25, and 50 antenna samples, the proposed method reduces the mean error by approximately 72–99% relative to two non-learning baselines, with lower medians and dispersions. Q-table variation decreases substantially after the initial training stage, although later fluctuations remain. The contribution is an interpretable RFID-aware local trajectory-selection layer supported by matched-budget baseline comparisons. The validation is restricted to simulated local regions; hardware transfer and full-warehouse deployment remain subjects for subsequent investigation. Full article

The integration of low-Earth-orbit (LEO) satellites with unmanned aerial vehicles (UAVs) promises high-throughput and flexible wireless connectivity, yet it faces critical challenges in simultaneously guaranteeing data rates and long-term energy harvesting under mobility and imperfect channel state information (CSI). Additionally, the rate–energy trade-off imposed by simultaneous wireless information and power transfer (SWIPT) further complicates per-slot resource allocation. In this paper, we propose a Lyapunov-based scheduling framework that stabilizes UAV data and virtual energy queues while maximizing weighted throughput. The framework employs a custom inner solver combining successive convex approximation (SCA) and weighted minimum mean-square error (WMMSE) optimization to efficiently compute per-slot beamformers and power-splitting ratios. Our approach explicitly accounts for UAV mobility, Rician fading channels with Doppler, and circuit nonlinearities in energy harvesting, ensuring feasible and energy-aware SWIPT operation. A LEO satellite–UAV integrated communication system is considered, where multiple satellites provide wireless connectivity to energy-constrained UAVs operating in a dynamic three-dimensional environment. The satellites employ multi-antenna transmission, while the UAVs rely on energy harvesting mechanisms to sustain their operation. The communication links are characterized by dominant line-of-sight propagation conditions, and UAV trajectories are adaptively optimized to improve network performance and energy efficiency. Simulation results demonstrate that the proposed Lyapunov-based SCA-WMMSE framework significantly outperforms a fixed baseline approach, providing substantial improvements in signal quality, achievable data rates, and harvested energy. Moreover, the proposed method maintains stable energy management behavior and guarantees long-term energy sustainability for the UAVs. Full article

Millimeter-wave vehicular communication links are prone to blockage and suffer from severe path loss, and high mobility leads to rapidly time-varying channels. In addition, large-scale reconfigurable intelligent surface (RIS) arrays impose substantial channel-estimation overhead and phase-optimization complexity. To address these issues, a group-based and position-aided phase-optimization method is proposed for RIS-assisted millimeter-wave vehicular communications. First, an RIS-assisted uplink system is modeled with a multi-antenna base station (BS), an RIS configured as a uniform planar array (UPA) and a single-antenna vehicular terminal. Channel expressions are formulated for the direct vehicle–BS link, the vehicle–RIS link and the RIS–BS link. Rician fading, line-of-sight (LoS)-dominated millimeter-wave propagation, mobility-induced Doppler shifts and a standardized path-loss model for urban microcell street-canyon scenarios are incorporated to characterize the RIS-assisted vehicular cascaded channel. Based on this model, an optimization problem for the RIS phase-shift matrix is formulated under discrete phase-shift constraints to maximize the achievable rate per unit bandwidth. To avoid the exponential increase in complexity caused by conventional exhaustive search as the number of RIS reflecting elements increases, a successive refinement algorithm is introduced to derive an equivalent channel-gain expression. The original phase-optimization problem is then transformed into an element-wise iterative update process, thereby reducing the computational complexity of large-scale RIS phase configuration. To further reduce the reliance on full channel state information (CSI), two low-overhead phase-optimization schemes are designed. In the group-based scheme, the RIS reflecting elements are partitioned into several subgroups, with all elements in each subgroup constrained to share the same phase shift. This design reduces both the channel-estimation dimensionality and the number of optimization variables. In the position-aided scheme, the spatial coordinates of the BS, RIS and vehicle are used to derive the link distances and the associated angles of arrival and departure. Based on these geometric parameters, the vehicle–RIS–BS cascaded channel is reconstructed and a corresponding phase-alignment strategy is designed. The simulation results demonstrate that both proposed schemes achieve rates of approximately 6.5 bits ${\mathrm{s}}^{-1}{\mathrm{H}\mathrm{z}}^{-1}$ at a transmit power of 30 dBm and outperform existing phase-optimization techniques. When the successive refinement algorithm is applied, the computation time required for phase optimization with a 256-element RIS remains below 0.01 s. Under high-mobility conditions, both proposed schemes approach the performance upper bound achieved with perfect CSI, demonstrating strong robustness to channel variations. Full article

Terahertz (THz) radiation generated through ultrafast transient photocurrent mechanisms has become a cornerstone of modern THz photonics, enabling broadband coherent emission with sub-picosecond temporal resolution. This review provides a comprehensive and mechanism-driven analysis of THz pulse generation via photo-Dember diffusion currents, surface depletion field acceleration, and biased photoconductive antenna architectures. We present a comprehensive comparative analysis of wide- and low-bandgap material platforms, including III–V, II–VI, and group IV semiconductors, as well as two-dimensional materials, topological insulators, and Weyl semimetals, highlighting how their intrinsic properties, such as band structure, carrier mobility, recombination dynamics, doping, and dielectric response, govern their THz emission efficiency, bandwidth, and spectral tunability. Special emphasis is placed on germanium (Ge), which has re-emerged as a highly promising THz source material owing to its high carrier mobility, long diffusion lengths, strain-tunable band structure, and CMOS compatibility. We highlight the roles of doping, strain-induced direct transitions, and several fabrication techniques in controlling the nonlinear photoexcited charge-carrier dynamics in Ge, thereby unlocking enhanced broadband THz performance. Finally, we explore the emerging application prospects of THz radiation, ranging from non-invasive security screening to biochemical sensing and archeological preservation. By bridging fundamental material science with scalable device architectures, this review outlines current challenges, highlights evolving opportunities in novel materials, and charts future directions towards integrated THz technologies. Full article

High-frequency (HF) RFID systems operating at 13.56 MHz are widely used in applications such as near-field communication, contactless identification, and smart sensing. Their performance strongly depends on the inductive coupling between the reader and tag antennas, which is influenced by antenna geometry, relative position, orientation, and environmental conditions. This work investigates the antenna component of passive HF RFID tags, represented by planar spiral inductors, without integrating an RFID microchip, allowing the electromagnetic coupling to be analyzed independently of chip-specific effects. A low-cost automated measurement platform was developed to experimentally evaluate the influence of antenna geometry, distance, orientation, and temperature on inductively coupled HF RFID antennas. The platform combined an automated positioning system with a mobile application for remote operation, minimizing the influence of the operator during measurements. A second experimental setup was designed to investigate the effect of temperature on antenna performance. Experimental results show that rectangular spiral antennas generally provided stronger inductive coupling than the other geometries investigated. Furthermore, varying the receiving antenna orientation improved the coupling between rectangular and octagonal antennas under specific configurations. Temperature variations within the investigated range had only a minor influence on antenna performance. The proposed platform provides a low-cost, portable, and reproducible solution for the experimental characterization of HF RFID antennas operating at 13.56 MHz. Full article

5G electromagnetic field (EMF) measurement is more challenging than measurement in previous cellular generations because 5G New Radio uses time-division duplexing, flexible bandwidths, beam sweeping, massive MIMO, and user-specific traffic beams. As a result, the measured synchronisation signal block (SSB) or PBCH-DMRS level may not directly represent the maximum exposure produced by data transmission. This motivates a combined tutorial and structured survey of existing 5G EMF measurement studies and procedures. This paper reviews the literature on 5G EMF measurement by classifying existing methods into frequency-selective measurement, code-selective measurement, actual exposure assessment, maximum-exposure extrapolation, and network-counter-based assessment. Representative field studies, public measurement reports, and network-data-based studies are compared according to their measurement scenarios, exposure objectives, and limitations. The paper further discusses key uncertainty sources, including beam/gain offset, TDD duty cycle, bandwidth extrapolation, traffic variation, spatial sampling, and equipment-related uncertainty. Finally, open challenges related to FR2 millimetre-wave measurements and reconfigurable propagation environments are discussed. By combining tutorial background with a structured survey, this paper clarifies 5G EMF measurement procedures, maximum-exposure extrapolation, uncertainty sources, and FR2 millimetre-wave measurement challenges. Full article

Receiver mobility complicates channel state information (CSI) acquisition in fluid antenna system (FAS)-assisted grant-free random access (GFRA), because user activity and multi-port channels evolve across pilot frames. Existing FAS acquisition methods are mainly frame-wise, while temporal recovery schemes do not directly combine receiver geometry with Doppler information. This article proposes geo-temporal expectation-maximization approximate message passing (GT-EM-AMP), which transfers posterior information between frames and refines the channel prior using receiver trajectory, effective Doppler, and coarse geometry. The proposed recursion preserves the low-complexity structure of EM-AMP while introducing only limited additional state updates. Simulations over an SNR range from $-14$ to 8 dB show that GT-EM-AMP achieves lower channel-estimation error and a favorable activity-detection tradeoff relative to static, temporal-only, geometry-only, and greedy baselines. Ablation, robustness, mobility, scalability, and statistical evaluations characterize the operating range of GT-EM-AMP and show that its activity-detection advantage depends on the SNR regime. GT-EM-AMP introduces modest runtime and memory overhead relative to static EM-AMP. The evaluation focuses on short acquisition windows with coarse geometry information under a Jakes-type temporal model. Full article

Millimeter-wave (mmWave) technology is essential for meeting the reliable connectivity and high-capacity demands of autonomous driving applications. Vehicle-to-infrastructure (V2I) networks have been modeled and analyzed based on stochastic geometry (SG) in many studies. However, most studies focus only on two-dimensional (2D) antenna models and disregard a key characteristic of V2I networks, i.e., the rapid mobility of vehicles. In this work, a three-dimensional (3D) coverage and connectivity analysis framework is proposed for mmWave V2I downlink transmission based on SG. First, a realistic 3D system model is developed, which includes 3D transmission channel, blockage, and antenna array models. Then, exact expressions for the coverage probability, connectivity probability, and effective throughput of a typical vehicle are derived. Finally, the theoretical analysis is validated through simulation results, which also reveal that an optimal density of roadside units (RSUs) that maximizes spectral efficiency exists and that disregarding the effect of the vertical beam of a 3D antenna array can lead to inaccurate evaluations. Moreover, appropriately setting system parameters can mitigate the negative impact of high vehicular mobility on connectivity performance. Full article

Mobile RFID inventory in libraries must be planned and evaluated under noisy observations, configuration-dependent read regimes, and incomplete supervision. This paper presents an uncertainty-aware analytics framework for robot-assisted RFID inventory using the public RFID Location dataset. The framework has three phases. Phase 1 converts irregular list-encoded logs into atomic RFID events and quantifies how operating configuration changes read density and signal variability. Phase 2 performs map-constrained Bayesian shelf inference by synchronizing RFID reads with robot trajectory and antenna geometry and by fusing RSSI and carrier phase over feasible shelf candidates. Phase 3 translates posterior spread and non-convergence into proxy review workload and cost, enabling configuration comparison and certainty–throughput trade-off analysis when strict EPC-to-item linkage is unavailable. Across 688,073 aligned RFID observations, the pipeline produces 18,190 posterior tag estimates from five inventory runs. The empirical results show strong run dependence: the best run achieves a mean posterior spread of 0.906 m with a convergence rate of 0.553, whereas a degraded run reaches only 0.004 convergence with a mean spread above 2.1 m. Because EPC-to-item linkage is unavailable, these values are posterior concentration and workload indicators rather than ground-truthed localization-accuracy metrics. A saved phase-weight ablation further shows that adding phase information substantially sharpens posterior concentration relative to an RSSI-only baseline. Under the proxy workload model, autonomous-S1-P30 provides the most favorable balance among posterior certainty, scan effort, and implied review burden. Full article

To mitigate 3D spatial blockages and channel uncertainty in VHF/low-UHF UAV emergency networks, this paper presents a multimodal environment-aware framework for 3D virtual fluid antenna port scheduling within an Integrated Sensing, Computing, and Communication (ISCCC) architecture. Under rigorously verified spatial resolution and channel stationarity conditions, UAV micro-mobility is mapped onto a discrete 3D virtual port array, transforming continuous flight space into a controllable fluid antenna system (FAS). We define a spatial efficiency metric that quantifies the Pareto trade-off between spatial degrees of freedom and estimation error, parameterized by an error-sensitivity index, and prove the existence of a unique optimal flight scale. Utilizing a joint spatio-temporal channel model, we derive the irreducible entropy lower bound of channel uncertainty, demonstrating that intrinsic environmental randomness constitutes a fundamental predictability limit regardless of port density—a benchmark independent of any specific scheduling strategy. To ensure real-time viability, we introduce an ISCCC-inspired computation-and-caching strategy that leverages pre-calculated stationary probabilities to drive a multidimensional scoring mechanism incorporating channel entropy-based stability, predictive SNR, and load balancing. The suboptimality gap relative to a perfect-CSI oracle is analytically bounded, and proven to narrow significantly under the high temporal correlation inherent in VHF bands. Numerical results confirm that the proposed strategy attains 10.36 bps/Hz effective throughput and 10.5% outage probability, consistently outperforming rule-based, learning-based, and 2D spatial baselines, particularly under prolonged structural obstructions. Full article

Unmanned aerial vehicles (UAVs) are expected to serve as core nodes for next-generation communication networks, while the broadcast nature of line-of-sight (LoS) links makes the security of transmissions a server problem, which is more prominent for a mobile eavesdropper scenario. In this paper, the security enhancement of UAV swarm communication is considered. Specifically, a UAV swarm with aerial base stations attempts to transmit confidential information to terrestrial nodes, and a mobile eavesdropper lurking nearby tries to approach better receiving points to intercept communications. For the purpose of enhancing the security of transmissions utilizing spatial freedom, a virtual antenna array is formed by the UAV swarm, and a multi-agent proximal policy optimization (MAPPO)-based approach is developed to jointly optimize the collaborative beamforming and cooperative trajectories of the UAV swarm under a maximum power constraint. The simulation results demonstrate the capability of the proposed method to direct the UAV swarm to transmit mission information directionally and validate the superiority of security performance compared to benchmarks. Full article

A pressing challenge of modern wireless networks is ensuring stable radio coverage inside buildings, where radio signal propagation is significantly complicated by the influence of building structures. Reinforced concrete walls, floor slabs, internal partitions, and energy-efficient windows with metallized coatings create substantial obstacles to the propagation of electromagnetic waves, causing reflection, absorption, and scattering. As a result, areas with weakened coverage are formed inside buildings, leading to deterioration in mobile communication quality and reduced data transmission rates. This study presents an experimental investigation of the received signal strength of mobile operators inside a multi-storey residential complex. An analysis was conducted to evaluate the impact of building height, architectural features, and construction materials on radio signal propagation. In addition, the frequency bands used in 4G LTE and 5G networks by mobile operators were examined. It was found that LTE networks mainly operate in the 1.8–2.1 GHz frequency range, whereas 5G networks operate in the n77 band (3.6–3.7 GHz), which provides higher data throughput but is characterized by greater signal attenuation when propagating inside buildings. To address this issue, a Distributed Antenna System (DAS) based on GPON technology was implemented in the studied building. The placement of antenna equipment on the roof enabled the efficient reception of the signal from the base station and its subsequent distribution inside the building through an internal antenna network. The measurement results demonstrated that the deployment of a GPON-based DAS significantly improves the received signal level and ensures more uniform radio coverage inside indoor environments. The obtained results confirm that the use of distributed antenna systems is an effective solution for compensating signal losses caused by the shielding effect of building structures and can significantly improve the quality of mobile communications in dense urban environments. The results show that the RSRP level in indoor environments without DAS decreases to approximately −100 to −110 dBm, while after deployment of the GPON-based DAS, it improves to −45 to −75 dBm. This corresponds to a signal gain of up to 40–50 dB, ensuring stable connectivity and significantly improved data transmission performance. Full article

Aiming at the problems that existing detection methods struggle to accurately identify early insulation faults of induction motors, are susceptible to interference, and have poor installation adaptability, a non-intrusive detection method for early insulation faults of induction motors based on a microstrip antenna array is proposed. Relying on the low-loss electromagnetic wave transmission characteristic of the heat dissipation hole at the tail of the induction motor, a four-element microstrip antenna array with multiple narrow beams and dual detection frequencies is designed, with the detection frequencies accurately set at 1.14 GHz and 2.23 GHz, which effectively avoids the motor operation noise frequency band (≤300 MHz) and the strong interference frequency band of mobile base stations (900 MHz, 1.8 GHz, 2.4 GHz). Utilizing the high gain and strong directivity of the array antenna, the accurate extraction and amplification of weak electromagnetic wave signals from early insulation fault discharge penetrating through the heat dissipation hole are realized. The full-dimensional simulation design of the antenna array is completed by using HFSS electromagnetic simulation software, and an industrial-grade experimental platform is built to carry out multi-condition verification experiments. The results show that the proposed detection system can realize non-intrusive, non-stop, and non-disassembly identification of early insulation discharge faults in induction motors, with a fault recognition rate of 94% for single faults and 90% for composite faults, and the average signal-to-noise ratio reaches 31.6–35.2 dB. Even under strong industrial electromagnetic interference, the recognition rate remains above 85%. This method overcomes the problems of traditional methods such as severe noise interference, difficult installation, and inability to monitor online, providing a high-efficiency scheme for real-time insulation state monitoring of industrial induction motors with good engineering application value. Full article