Search Results (162)

The limited availability of powerful, tunable, and reliable mid-infrared sources has historically prevented their widespread adoption in spectroscopy applications, even if most greenhouse gases’ fundamental absorption lines are found in this region of the electromagnetic spectrum. However, both mid-infrared fiber lasers and ICLs have enjoyed substantial growth in available output powers in recent years. Since the two technologies have complementary benefits, combining them could prove to be an interesting avenue to explore toward the development of a powerful, easily tunable, and narrow linewidth mid-infrared source. We report what we believe to be the first demonstration of fiber amplification of a distributed feedback interband cascade laser (DFB-ICL) operating in the mid-infrared. The system, based on an in-band pumped dysprosium-doped fluoride fiber amplifier, yields 10 dB of gain and up to 30 mW of output power at 3240 nm. We believe this is an important milestone toward power scaling of single-mode, single-frequency, and rapidly tunable mid-infrared laser sources suitable for advanced gas spectroscopy. Full article

In order to establish a general design methodology for water-based electromagnetic metamaterial absorber microstructures, a topology optimization method for water-based metamaterial absorber microstructures design was proposed in this paper. According to Mie resonance and impedance matching theory, the realization mechanism and physical model of the broadband water-based metamaterial absorber were constructed. The highest average in-band absorption rate was taken as the design object; the topological optimization model for water-based metamaterial absorber design was established. A metamaterial absorber microstructure with 16 discretized water columns inside the unit cell was designed as an example. The obtained structure exhibited a very high average in band absorption rate in the specific frequency band. The proposed method was a collaborative optimization approach that employed a single type of design variable, namely water column height, to simultaneously adjust surface impedance matching and specific resonant modes. It provided a feasible method for achieving the highest average absorption rate within a specific band. Full article

High parasitic capacitance from poly-insulator-poly capacitors in complementary metal oxide semiconductor (CMOS) processes presents a major bottleneck to achieving high-resolution successive approximation register (SAR) analog-to-digital converters (ADCs) in imaging systems. This study proposes a Phase-Adjustable SAR ADC that addresses this limitation through a reconfigurable architecture. The design utilizes a phase-adjustable logic unit to switch between a conventional SAR mode for high-speed operation and a noise-shaping (NS) SAR mode for high-resolution conversion, actively suppressing in-band quantization noise. An improved SAR logic unit facilitates the insertion of an adjustable phase while concurrently achieving an 86% area reduction in the core logic block. A prototype was fabricated and measured in a 0.35-µm CMOS process. In conventional mode, the ADC achieved a 7.69-bit effective number of bits at 2 MS/s. By activating the noise-shaping circuitry, performance was significantly enhanced to an 11.06-bit resolution, corresponding to a signal-to-noise-and-distortion ratio (SNDR) of 68.3 dB, at a 125 kS/s sampling rate. The results demonstrate that the proposed architecture effectively leverages the trade-off between speed and accuracy, providing a practical method for realizing high-performance ADCs despite the inherent limitations of non-ideal passive components. Full article

Network monitoring is becoming increasingly challenging as networks grow in scale, speed, and complexity. The evolution of monitoring approaches reflects a shift from device-centric, localized techniques toward network-wide observability enabled by modern networking paradigms. Early methods like SNMP polling and NetFlow provided basic insights but struggled with real-time visibility in large, dynamic environments. The emergence of Software-Defined Networking (SDN) introduced centralized control and a global view of network state, opening the door to more coordinated and programmable measurement strategies. More recently, programmable data planes (e.g., P4-based switches) and in-band telemetry frameworks have allowed fine grained, line rate data collection directly from traffic, reducing overhead and latency compared to traditional polling. These developments mark a move away from single point or per flow analysis toward holistic monitoring woven throughout the network fabric. In this survey, we systematically review the state of the art in network-wide monitoring. We define key concepts (topologies, flows, telemetry, observability) and trace the progression of monitoring architectures from traditional networks to SDN to fully programmable networks. We introduce a taxonomy spanning local device measures, path level techniques, global network-wide methods, and hybrid approaches. Finally, we summarize open research challenges and future directions, highlighting that modern networks demand monitoring frameworks that are not only scalable and real-time but also tightly integrated with network control and automation. Full article

This paper proposes a second-order low-pass Butterworth multiple-feedback (MFB) filter with a reconfigurable bandwidth and gain, implemented in a 28 nm CMOS. The filter supports independent tuning of the bandwidth from 10 MHz to 100 MHz and the gain from 0 dB to 19 dB, effectively addressing the challenge of a tightly coupled gain and quality factor in traditional MFB designs. Notably, compared to the widely adopted Tow–Thomas structure, the proposed filter achieves second-order filtering and the same degree of flexibility using only a single operational amplifier (OPA), significantly reducing both the power consumption and area. Additionally, an RC tuning circuit is employed to reduce fluctuations in the RC time constant under process, voltage, and temperature (PVT) variations. To meet the requirements for high linearity and low power consumption in broadband applications, a three-stage push–pull OPA with current re-use feedforward and an RC Miller compensation technique is proposed. With the current re-use feedforward, the OPA’s loop gain at 100 MHz is significantly enhanced from 22.34 dB to 28.75 dB, achieving a 2.14 GHz unity-gain bandwidth. Using this OPA, the filter achieves a 48.2 dBm in-band (IB) OIP3, a 53.4 dBm out-of-band (OOB) OIP3, and a figure of merit (FoM) of 185.5 dBJ⁻¹ at a100 MHz bandwidth while consuming only 3.6 mW from a 1.8 V supply. Full article

Vehicle-to-vehicle (V2V) and vehicle-to-network (V2N) communications are two key components of intelligent transport systems (ITSs) that can share spectrum resources through in-band overlay. V2V communication primarily supports traffic safety, whereas V2N primarily focuses on infotainment and information exchange. Achieving reliable V2V transmission alongside high-rate V2N services in resource-constrained, dynamically changing traffic environments poses a significant challenge for resource allocation. To address this, we propose a novel reinforcement learning (RL) framework, termed Graph Attention Network (GAT)-Advantage Actor–Critic (GAT-A2C). In this framework, we construct a graph based on V2V links and their potential interference relationships. Each V2V link is represented as a node, and edges connect nodes that may interfere. The GAT captures key interference patterns among neighboring vehicles while accounting for real-time mobility and channel variations. The features generated by the GAT, combined with individual link characteristics, form the environment state, which is then processed by the RL agent to jointly optimize the resource blocks allocation and the transmission power for both V2V and V2N communications. Simulation results demonstrate that the proposed method substantially improves V2N rates and V2V communication success ratios under various vehicle densities. Furthermore, the approach exhibits strong scalability, making it a promising solution for future large-scale intelligent vehicular networks operating in dynamic traffic scenarios. Full article

To address the efficiency bottlenecks of traditional full-wave simulation methods in the high-performance design and rapid optimization of microwave filters, this study proposes an efficient design method based on an improved surrogate model and a hybrid optimization algorithm. A one-dimensional dense convolutional autoencoder (1D-DenseCAE) model is constructed to enhance the model’s ability to extract key features and improve convergence speed. Additionally, the Ivy–Hiking optimization algorithm (IHOA) is introduced, combining the advantages of global search and local fine-tuning. Experiments demonstrate that this method achieves approximately a 25% improvement in convergence speed over the standard one-dimensional convolutional autoencoder (1D-CAE) in cavity filter design, and enables efficient optimization in complex structures such as interdigital filters and seventh-order cross-coupled cavity filters, meeting design requirements of return loss below −20 dB and in-band ripple under 0.5 dB. This method provides an effective technical pathway for the intelligent design of microwave filters. Full article

The enhancement of weak-fault signal characteristics in rolling bearings under strong background noise interference has always been a challenging problem in rotating machinery fault diagnosis. Research indicates that multivariate statistical indicators such as skewness and kurtosis can characterize the fault features of vibration signals. However, when the fault features in the signal are weak and severely affected by noise, the characterization capability of these indicators diminishes, significantly compromising diagnostic accuracy. To address this issue, this paper proposes a novel multivariate statistical filtering (MSF) method for multi-band filtering, which can effectively screen the target fault information bands in vibration signals during bearing faults. The core idea involves constructing a multivariate matrix of fused-fault multidimensional features by integrating fault and healthy signals, and then utilizing eigenvalue distance metrics to significantly characterize the spectral differences between fault and healthy signals. This enables the selection of frequency bands containing the most informative fault features from the segmented frequency spectrum. To address the inherent in-band residual noise in the MSF-processed signals, this paper further proposes the Hilbert differential Teager energy operator (HDTEO) based on MSF to suppress the filtered in-band noise, thereby enhancing transient fault impulses more effectively. The proposed method has been validated using both public datasets and laboratory datasets. Results demonstrate its effectiveness in accurately identifying fault characteristic frequencies, even under challenging conditions such as incipient bearing faults or severely weak vibration signatures caused by strong background noise. Finally, comparative experiments confirm the superior performance of the proposed approach. Full article

This paper presents the novel design of a printed, low-cost, dual-port, and dual-polarized slot antenna for microwave biomedical radars. The butterfly shape of the radiating element, with orthogonally positioned arms, enables simultaneous radiation of both vertically and horizontally polarized waves. The antenna is intended for full-duplex in-band applications using two mutually isolated antenna ports, with the CPW port on the same side of the substrate as the slot antenna and the microstrip port positioned orthogonally on the other side of the substrate. Those two ports can be used as transmit and receive ports in a radar transceiver, with a port isolation of 25 dB. Thanks to the bow-tie shape of the slots and an additional coupling region between the butterfly arms, there is more flexibility in simultaneous optimization of the resonant frequency and input impedance at both ports, avoiding the need for a complicated matching network that introduces the attenuation and increases antenna dimensions. The advantage of this design is demonstrated through the modeling of an eight-element dual-port linear array with an extremely simple feed network for high-gain biosensing applications. To validate the simulation results, prototypes of the proposed antenna were fabricated and tested. The measured operating band of the antennas spans from 2.35 GHz to 2.55 GHz, with reflection coefficients of less than—10 dB, a maximum gain of 8.5 dBi, and a front-to-back gain ratio that is greater than 15 dB, which is comparable with other published single dual-port slot antennas. This is the simplest proposed dual-port, dual-polarization antenna that enables straightforward scaling to other frequency bands. Full article

This paper presents a blind source separation (BSS)-based framework for joint communication and sensing (JCAS) in in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) systems operating under time-varying channel conditions. Conventionally, self-interference (SI) in IBFD systems is a major obstacle to recovering the signal of interest (SOI). Under the JCAS paradigm, however, this high-power SI signal presents an opportunity for efficient sensing. Since each transceiver node has access to the original SI signal, its environmental reflections can be exploited to estimate channel conditions and detect changes, without requiring dedicated radar waveforms. We propose a blind source separation (BSS)-based framework to simultaneously perform self-interference cancellation (SIC) and extract sensing information in IBFD MIMO settings. The approach applies the Fast Independent Component Analysis (FastICA) algorithm in dynamic scenarios to separate the SI and SOI signals while enabling simultaneous signal recovery and channel estimation. Simulation results quantify the trade-off between estimation accuracy and channel dynamics, demonstrating that while FastICA is effective, its performance is fundamentally limited by a frame size optimized for the rate of channel variation. Specifically, in static channels, the signal-to-residual-error ratio (SRER) exceeds 22 dB with 500-symbol frames, whereas for moderately time-varying channels, performance degrades significantly for frames longer than 150 symbols, with SRER dropping below 4 dB. Full article

In this study, we propose a novel wideband aperture-coupled magneto-electric (ME) dipole antenna that achieves enhanced bandwidth by simultaneously leveraging ME resonance and aperture-coupled excitation. Building upon the conventional ME dipole architecture, the antenna integrates a pair of horizontal metal patches forming the electric dipole and a pair of vertical metal patches forming the magnetic dipole. A key innovation is the aperture-coupled feeding mechanism, where electromagnetic energy is transferred from a tapered microstrip line to the dipole structure through a slot etched in the ground plane. This design not only excites the characteristic ME resonances effectively but also significantly improves impedance matching, delivering a markedly broader impedance bandwidth. To validate the proposed concept, a prototype antenna was fabricated and experimentally characterized. Measurements show an impedance bandwidth of 84.48% (3.61–8.89 GHz) for $S_{11}$ ≤ −10 dB and a maximum in-band gain of 7.88 dBi. The antenna also maintains a stable, unidirectional radiation pattern across the operating band, confirming its potential for wideband applications such as 5G wireless communications. Full article

In-band full-duplex (IBFD) technology has attracted significant attention for its potential to double the spectral efficiency by enabling a simultaneous transmission and reception over the same frequency channel. However, achieving high isolation between closely spaced transmit and receive paths remains a critical challenge. In this paper, a novel compact co-polarized monopole antenna with self-decoupling capability is proposed based on common-mode/differential-mode (CM/DM) theory. By innovatively folding the ends of the monopole elements, the antenna exploits the distinct behaviors under CM and DM excitations at a close spacing to achieve simultaneous impedance matching in both modes. This effectively enhances the isolation between antenna elements. The design enables self-interference suppression without requiring any additional decoupling structures, even under compact antenna and port spacing. Measurement results confirm that the proposed antenna achieves over 20 dB isolation within the 3.4–3.6 GHz operating band, with a compact spacing of 0.008 λ₀ (λ₀ corresponds to the wavelength at the center frequency). Full article

A low-profile dual-polarized shared-aperture phased array antenna is proposed for Ku-band satellite communications in this paper. The stacked octagonal patches loaded with Via-rings are proposed as dual-polarized shared-aperture radiation elements, with the characteristics of wide impedance bandwidth, high gain, and weak coupling. Furthermore, innovative minimized three-port ring couplers are utilized for the differential-fed antenna array, further suppressing the cross-polarization component. Substrate integrated coaxial line (SICL) and microstrip line (MS) feed networks are employed for the excitation of transmitting band (Tx) horizontal polarization and receiving band (Rx) vertical polarization, respectively. The non-uniform subarray architecture is optimized to minimize the sidelobe levels with the reduced number of transmitter and receiver (T/R) radio frequency phase-shifting modules. As proof-of-concept examples, 16 × 24 and 32 × 24 array antennas are demonstrated and fabricated. The measured impedance bandwidths of the proposed phased array antennas are around 21.1%, while the in-band isolations are above 36.7 dB. Gains up to 29 dBi and 32.4 dBi are performed by two prototypes separately. In addition, the T/R phase-shifting modules are utilized to validate the beam-scanning characteristic, which is of value for dynamic satellite communications. Full article

This paper presents our research on an E-band Radio Frequency (RF) front-end packaging structure based on back-to-back gap waveguide (GW). This design effectively mitigates the impact of air gaps on performance and offers the advantage of large assembly tolerances. Additionally, its back-to-back structure enables structural stacking, which can reduce the overall packaging size. In terms of functionality, the structure integrates hybrid couplers, bandpass filters, and amplifier packaging structures. Notably, the hybrid couplers provide high port isolation, facilitating a higher isolation duplex function by simply connecting high-order bandpass filters at the output ports without the need for additional optimization. Furthermore, these couplers also serve as power dividers/combiners. When combined with the H-plane amplifier packaging structures, the output power of the module is theoretically increased by 3 dB. Based on the measurements, the results indicate that this structure operates within the frequency ranges of 71–76 GHz and 81–86 GHz. The common port return loss is below 12 dB, while the in-band insertion loss is less than 2.26 dB and 2.42 dB, respectively. These findings demonstrate excellent electrical performance and suitability for E-band communication systems. Full article

With the continuous expansion of low-Earth-orbit (LEO) satellite networks, the services within these networks have exhibited diverse and differentiated demand characteristics. Due to the limited onboard resources, efficient network resource allocation is required to ensure high-quality network performance. However, the dynamic topology and differentiated resource requirements for diversified services pose great challenges when existing resource awareness or prediction methods are applied to satellite networks, resulting in poor awareness latency and the inaccurate prediction of resource status. To solve these problems, a network resource allocation method based on awareness–prediction joint compensation is proposed. The method utilizes the node awareness latency as a prediction step and employs a long short-term memory model for resource status prediction. A dynamic compensation model is also proposed to compensate for the prediction results, which is achieved by adjusting compensation weights according to the awareness latencies and prediction accuracies. Furthermore, an efficient, accelerated alternating-direction method of multipliers (ADMM) resource allocation algorithm is proposed with the aim of maximizing the satisfaction of service resources requirements. The simulation results indicate that the relative error between the compensation data and onboard resource status does not exceed 5%, and the resource allocation method can improve the service resource coverage by 15.8%, thus improving the evaluation and allocation capabilities of network resources. Full article