This paper reviews a series of metamaterial-assisted RF windows (MMWs) for their potential application in broadband RF systems. Here, we choose the following MMWs: i) MMW with square pillars, ii) MMW with square pillars ending in cylindrical tips, iii) MMW with cylindrical pillars, iv) MMW with cylindrical pillars ending in hemispherical tips, v) MMW with cylindrical pillars ending in conical tips, vi) MMW with hollow cylindrical pillars, vii) MMW with slots, viii) MMW with rings, and ix) MMW with metallic hexagonal rings. These windows are demonstrated in various frequency ranges covering 25 ? 144 GHz. The return-loss characteristics are studied and the bandwidth and center frequency of the band estimated. When the relative merits of the various considered MMWs are compared, the MMW with cylindrical pillars with conical tips shows the highest relative bandwidth for the TE0,1-mode, and the MMW with hexagonal metallic rings is comparatively complex in its structural configuration.
Terahertz (THz) technology has emerged as a promising enabler for future sixth-generation (6G) communications, integrated sensing and communication (ISAC), and biomedical imaging applications. Among the available semiconductor technologies, CMOS is particularly attractive because of its low cost, high integration density, and compatibility with mass production. However, realizing high-performance THz systems in CMOS remains challenging due to limited transistor speed, severe passive losses, low antenna efficiency, and limited output power. This article reviews recent advances in CMOS THz electronics and highlights how cross-level innovations spanning transistor modeling, circuit design, antenna engineering, heterogeneous integration, and system architectures can address these challenges. Key developments, including electromagnetic-based transistor optimization, THz amplifiers, phase-locked loops, dielectric-resonator antennas, and system-on-package heterogeneous integration, are discussed. Representative communication and sensing systems are also presented to demonstrate the integration of these technologies into practical THz applications.
Backscatter communication has emerged as a promising enabler for battery-free and low-complexity Internet of Things (IoT) devices, and advances in radar sensing and millimeter-wave (mm-wave) systems have expanded its capabilities beyond identification toward localization, monitoring, and environmental awareness. More recently, these trends have converged into integrated sensing and backscatter communication (ISABC), where the same reflected waveform supports both data transmission and sensing. This article reviews the foundations and recent progress of ISABC, with emphasis on frequency-modulated continuous-wave (FMCW) radar-based implementations, which is meaningful to clarify how range estimation, tag identification, and data transfer can be jointly realized within a unified passive architecture. The article highlights both the opportunities and current limitations of ISABC and argues that future systems will evolve toward spatially aware, waveform-coordinated, and electromagnetically engineered backscatter platforms for battery-free sensing and 6G integrated wireless intelligence.
As terahertz (THz) technologies transition from laboratory-grade demonstrations to practical deployment, the need for compact and cost-effective imaging solutions capable of bridging the gap between proof-of-concept prototypes and real-world applications has never been greater. This article synthesizes recent advances in high-performance CMOS-based THz direct detectors, highlighting their role in enabling monolithic integration of detector front ends, signal processing, and readout electronics for uncooled real-time imaging and focal-plane arrays (FPAs). By establishing a device-to-system analytical framework, we elucidate how nonlinear plasma-wave rectification, antenna–transistor geometries, parasitic effects, circuit architectures, and array-level implementation constraints interact across multiple hierarchical levels to govern detector figures of merit and multipixel scalability. Extending beyond isolated device-level characteristics, we identify the fundamental tradeoffs linking electrical metrics—including responsivity, sensitivity, dynamic range, power consumption, response speed, and spectral bandwidth—with electromagnetic, material, and structural attributes such as coupling efficiency, thermal stability, antenna footprint, pixel pitch, and fill factor, thereby providing a unified perspective for rational detector optimization. Key engineering considerations spanning antenna–transistor co-design, pixel-level amplification, impedance matching, distributed self-mixing, pixel-to-pixel uniformity, and noise mitigation are systematically analyzed to formulate physically grounded design guidelines and a roadmap toward next-generation CMOS-integrated high-resolution THz imaging systems.
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
Derivative-free optimization (DFO) provides a practical approach to solving expensive black-box problems in RF/microwave engineering without requiring gradient information. This article reviews representative DFO methods and their use in compact model parameter extraction and robust transistor sizing. Across these applications, DFO enables systematic exploration of high-dimensional design spaces, simultaneous fitting of coupled model parameters, and balancing of competing design objectives under uncertainty. When guided by physically meaningful parameters, design variables, constraints, and performance metrics, DFO can reduce manual tuning, improve reproducibility, and accelerate the development of accurate compact models and robust, high-performing designs.
This article reviews efficient modeling and optimization strategies for microwave tunable filters with multiple tuning states. We first investigate a surrogate-assisted simultaneous optimization framework for multistate tunable filters, where multiple sub-surrogate models are established for different tuning states while sharing a common set of nontunable parameters. In this way, multiple tuning states can be optimized jointly within a unified framework, thereby enhancing the coordination among the design requirements of different states. Building on this, we further discuss a multiphysics optimization method based on space mapping, which combines a shared coarse model with mappings that depend on the tuning state. By exploiting low-cost electromagnetic responses as prior knowledge and using multiphysics data for corrective learning, this method improves optimization efficiency and reduces the computational cost of multiphysics design. The effectiveness of the two optimization methods is verified through a representative tunable four-pole waveguide filter example.
A floating-body SOI MOSFET delivers impressive gain, higher peak current, and an enticing boost in unity-gain frequency. However, under large-signal excitation, the same device exhibits bias sensitivity, gain compression, phase distortion, and memory effects that are difficult to model or predict [[1]-[5]](#ref-0001). Tying the body to the source makes the behavior more stable but at the cost of reduced peak performance. This trade-off is not merely a theoretical modeling consideration; it manifests explicitly in measured DC I–V characteristics, small-signal S-parameters, and time-domain RF waveforms. Fundamentally, the underlying origin of this behavior can be traced to a single physical mechanism: the dynamic evolution of the body potential in partially depleted SOI MOSFETs. This article examines how floating-body (FB) and body-tied (BT) SOI MOSFETs behave from DC through RF. Through a unified set of measurements including static and pulsed I?V, large signal characterization, multi-bias S-parameters, and vector load-pull the kink effect becomes a powerful lens for understanding RF nonlinearity, dispersion, and stability.
As the deployment of 5G networks matures and the research community pivots toward the conceptual frameworks of 6G [1], the demand for data throughput is accelerating rapidly. There is a fundamental shift in wireless network requirements, driven by greater demands for bandwidth that are difficult to meet with the congested sub-6-GHz spectrum. The primary solution is to go up in frequencies, in search of wider available bandwidths and less contention, toward millimeter-wave (mm-wave), specifically the E band (71–86 GHz) [2]. These bands represent the current industrial frontier of wireless backhaul systems, offering the larger spectrum allocations necessary to support multigigabit data links.
